Search results for: fatigue testing machine

Authors: A. El Amri, M. El Yakhloufi Haddou, A. Khamlichi

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The numerical simulation based on the Finite Element Method (FEM) is widely used in academic institutes and in the industry. It is a useful tool to predict many phenomena present in the classical manufacturing forming processes such as fracture. But, the results of such numerical model depend strongly on the parameters of the constitutive behavior model. The influences of thermal and mechanical loads cause damage. The temperature and strain rate dependent materials’ properties and their modelling are discussed. A Johnson-Cook Model of damage has been selected for the numerical simulations. Virtual software called the ABAQUS 6.11 is used for finite element analysis. This model was introduced in order to give information concerning crack initiation during thermal and mechanical loads.

Keywords: Thermomechanical fatigue, failure, numerical simulation, fracture, damages.

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Authors: Imran Ahmed, Muhammad Islam, Syed Inayat Ali Shah, Awais Adnan

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The identification and classification of weeds are of major technical and economical importance in the agricultural industry. To automate these activities, like in shape, color and texture, weed control system is feasible. The goal of this paper is to build a real-time, machine vision weed control system that can detect weed locations. In order to accomplish this objective, a real-time robotic system is developed to identify and locate outdoor plants using machine vision technology and pattern recognition. The algorithm is developed to classify images into broad and narrow class for real-time selective herbicide application. The developed algorithm has been tested on weeds at various locations, which have shown that the algorithm to be very effectiveness in weed identification. Further the results show a very reliable performance on weeds under varying field conditions. The analysis of the results shows over 90 percent classification accuracy over 140 sample images (broad and narrow) with 70 samples from each category of weeds.

Keywords: Weed detection, Image Processing, real-timerecognition, Standard Deviation.

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Authors: Hyun-Woo Cho

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Real-time or in-line process monitoring frameworks are designed to give early warnings for a fault along with meaningful identification of its assignable causes. In artificial intelligence and machine learning fields of pattern recognition various promising approaches have been proposed such as kernel-based nonlinear machine learning techniques. This work presents a kernel-based empirical monitoring scheme for batch type production processes with small sample size problem of partially unbalanced data. Measurement data of normal operations are easy to collect whilst special events or faults data are difficult to collect. In such situations, noise filtering techniques can be helpful in enhancing process monitoring performance. Furthermore, preprocessing of raw process data is used to get rid of unwanted variation of data. The performance of the monitoring scheme was demonstrated using three-dimensional batch data. The results showed that the monitoring performance was improved significantly in terms of detection success rate of process fault.

Keywords: Process Monitoring, kernel methods, multivariate filtering, data-driven techniques, quality improvement.

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Authors: Nadia Masood Khan, Muhammad Salman Khan, Gul Muhammad Khan

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Cardiologists perform cardiac auscultation to detect abnormalities in heart sounds. Since accurate auscultation is a crucial first step in screening patients with heart diseases, there is a need to develop computer-aided detection/diagnosis (CAD) systems to assist cardiologists in interpreting heart sounds and provide second opinions. In this paper different algorithms are implemented for automated heart sound classification using unsegmented phonocardiogram (PCG) signals. Support vector machine (SVM), artificial neural network (ANN) and cartesian genetic programming evolved artificial neural network (CGPANN) without the application of any segmentation algorithm has been explored in this study. The signals are first pre-processed to remove any unwanted frequencies. Both time and frequency domain features are then extracted for training the different models. The different algorithms are tested in multiple scenarios and their strengths and weaknesses are discussed. Results indicate that SVM outperforms the rest with an accuracy of 73.64%.

Keywords: Pattern recognition, machine learning, computer aided diagnosis, heart sound classification, and feature extraction.

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Authors: Dong Xie, Leah Howard, Yiming Weng

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The objective of this study was to synthesize and characterize 5-acryloyloxy-3,4-dichlorocrotonolactone (a furanone derivative), use this derivative to modify a dental restorative, and study the effect of the derivative on the antibacterial activity and compressive strength of the formed restorative. In this study, a furanone derivative was synthesized, characterized, and used to formulate a dental restorative. Compressive strength (CS) and S. mutans viability were used to evaluate the mechanical strength and antibacterial activity of the formed restorative. The fabricated restorative specimens were photocured and conditioned in distilled water at 37^oC for 24 h, followed by direct testing for CS or/and incubating with S. mutans for 48 h for antibacterial testing. The results show that the modified dental restorative showed a significant antibacterial activity without substantially decreasing the mechanical strengths. With addition of the antibacterial derivative up to 30%, the restorative kept its original CS nearly unchanged but showed a significant antibacterial activity with 68% reduction in the S. mutans viability. Furthermore, the antibacterial function of the modified restorative was not affected by human saliva. The aging study also indicates that the modified restorative may have a long-lasting antibacterial function. It is concluded that this experimental antibacterial restorative may potentially be developed into a clinically attractive dental filling restorative due to its high mechanical strength and antibacterial function.

Keywords: Antibacterial, dental filling restorative, compressive strength, S. mutans viability.

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Authors: Somkiat Tangjitsitcharoen, Siripong Damrongthaveesak

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This paper presents an advance in monitoring and process control of surface roughness in CNC machine for the turning and milling processes. An integration of the in-process monitoring and process control of the surface roughness is proposed and developed during the machining process by using the cutting force ratio. The previously developed surface roughness models for turning and milling processes of the author are adopted to predict the inprocess surface roughness, which consist of the cutting speed, the feed rate, the tool nose radius, the depth of cut, the rake angle, and the cutting force ratio. The cutting force ratios obtained from the turning and the milling are utilized to estimate the in-process surface roughness. The dynamometers are installed on the tool turret of CNC turning machine and the table of 5-axis machining center to monitor the cutting forces. The in-process control of the surface roughness has been developed and proposed to control the predicted surface roughness. It has been proved by the cutting tests that the proposed integration system of the in-process monitoring and the process control can be used to check the surface roughness during the cutting by utilizing the cutting force ratio.

Keywords: Turning, milling, monitoring, surface roughness, cutting force ratio.

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Authors: A. Yazdanmehr, H. Jahed

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Being made with the lightest commercially available industrial metal, Magnesium (Mg) alloys are of interest for light-weighting. Expanding their application to different material processing methods requires Mg properties at large strains. Several room-temperature processes such as shot and laser peening and hole cold expansion need compressive large strain data. Two methods have been proposed in the literature to obtain the stress-strain curve at high strains: 1) anti-buckling guides and 2) small cubic samples. In this paper, an anti-buckling fixture is used with the help of digital image correlation (DIC) to obtain the compression-tension (C-T) of AZ31B-H24 rolled sheet at large strain values of up to 10.5%. The effect of the anti-bucking fixture on stress-strain curves is evaluated experimentally by comparing the results with those of the compression tests of cubic samples. For testing cubic samples, a new fixture has been designed to increase the accuracy of testing cubic samples with DIC strain measurements. Results show a negligible effect of anti-buckling on stress-strain curves, specifically at high strain values.

Keywords: Large strain, compression-tension, loading-unloading, Mg alloys.

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Authors: Kazeem K. Adewole, Julia M. Race, Steve J. Bull

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The fracture performance of steel wires for civil engineering applications remains a major concern in civil engineering construction and maintenance of wire reinforced structures. The need to employ approaches that simulate micromechanical material processes which characterizes fracture in civil structures has been emphasized recently in the literature. However, choosing from the numerous micromechanics-based fracture models, and identifying their applicability and reliability remains an issue that still needs to be addressed in a greater depth. Laboratory tensile testing and finite element tensile testing simulations with the shear, ductile and Gurson-Tvergaard-Needleman’s micromechanics-based models conducted in this work reveal that the shear fracture model is an appropriate fracture model to predict the fracture performance of steel wires used for civil engineering applications. The need to consider the capability of the micromechanics-based fracture model to predict the “cup and cone” fracture exhibited by the wire in choosing the appropriate fracture model is demonstrated.

Keywords: Fracture performance, FE simulation, Shear fracture model, Ductile fracture model, Gurson-Tvergaard-Needleman fracture model, Wires.

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Authors: E. Irankhah, M. Zarif, E. Mazrooei Rad, K. Ghandehari

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Alzheimer's prevalence is on the rise, and the disease comes with problems like cessation of treatment, high cost of treatment, and the lack of early detection methods. The pathology of this disease causes the formation of protein deposits in the brain of patients called plaque amyloid. Generally, the diagnosis of this disease is done by performing tests such as a cerebrospinal fluid, CT scan, MRI, and spinal cord fluid testing, or mental testing tests and eye tracing tests. In this paper, we tried to use the Medial Temporal Atrophy (MTA) method and the Leave One Out (LOO) cycle to extract the statistical properties of the three Fz, Pz, and Cz channels of ERP signals for early diagnosis of this disease. In the process of CT scan images, the accuracy of the results is 81% for the healthy person and 88% for the severe patient. After the process of ERP signaling, the accuracy of the results for a healthy person in the delta band in the Cz channel is 81% and in the alpha band the Pz channel is 90%. In the results obtained from the signal processing, the results of the severe patient in the delta band of the Cz channel were 89% and in the alpha band Pz channel 92%.

Keywords: Alzheimer's disease, image and signal processing, medial temporal atrophy, LOO Cycle.

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Authors: Igor Miňo, Lenka Lešková

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Over the past 80 years, open-field method has evolved as a commonly used tool for the analysis of animal behaviour. The study was carried out using 50 kennel-reared purebred puppies of the German Shepherd dog breed. All dogs were tested in 5^th, 7^th, and 9^th week of age. For the purpose of behavioural analysis, an open-field evaluation report was designed prior to testing to ensure the most convenient, rapid, and suitable way to assess selected behavioural patterns in field conditions. Onset of vocalisation, intensity of vocalisation, level of physical activity, response to sound, and overall behaviour was monitored in the study. Correlations between measures of height, weight and chest circumference, and behavioural characteristics in the 5^th, 7^th, and 9^th week of age were not statistically significant. Onset of vocalisation, intensity of vocalisation, level of physical activity and response to sound differed on statistically significant level between 5^th, 7^th, and 9^th week of age. Results suggest that our practical assessment report may be used as an applicable method to evaluate the suitability of service dog puppies for future working roles.

Keywords: Dog, behaviour, open-field, testing.

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Authors: Anis Gharbi

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This paper considers the problem of scheduling maintenance actions for identical aircraft gas turbine engines. Each one of the turbines consists of parts which frequently require replacement. A finite inventory of spare parts is available and all parts are ready for replacement at any time. The inventory consists of both new and refurbished parts. Hence, these parts have different field lives. The goal is to find a replacement part sequencing that maximizes the time that the aircraft will keep functioning before the inventory is replenished. The problem is formulated as an identical parallel machine scheduling problem where the minimum completion time has to be maximized. Two models have been developed. The first one is an optimization model which is based on a 0-1 linear programming formulation, while the second one is an approximate procedure which consists in decomposing the problem into several two-machine subproblems. Each subproblem is optimally solved using the first model. Both models have been implemented using Lingo and have been tested on two sets of randomly generated data with up to 150 parts and 10 turbines. Experimental results show that the optimization model is able to solve only instances with no more than 4 turbines, while the decomposition procedure often provides near-optimal solutions within a maximum CPU time of 3 seconds.

Keywords: Aircraft turbines, Scheduling, Identical parallel machines, 0-1 linear programming, Heuristic.

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Authors: Aikaterini Fountoulaki, Nikos Karacapilidis, Manolis Manatakis

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This paper proposes an innovative methodology for Acceptance Sampling by Variables, which is a particular category of Statistical Quality Control dealing with the assurance of products quality. Our contribution lies in the exploitation of machine learning techniques to address the complexity and remedy the drawbacks of existing approaches. More specifically, the proposed methodology exploits Artificial Neural Networks (ANNs) to aid decision making about the acceptance or rejection of an inspected sample. For any type of inspection, ANNs are trained by data from corresponding tables of a standard-s sampling plan schemes. Once trained, ANNs can give closed-form solutions for any acceptance quality level and sample size, thus leading to an automation of the reading of the sampling plan tables, without any need of compromise with the values of the specific standard chosen each time. The proposed methodology provides enough flexibility to quality control engineers during the inspection of their samples, allowing the consideration of specific needs, while it also reduces the time and the cost required for these inspections. Its applicability and advantages are demonstrated through two numerical examples.

Keywords: Acceptance Sampling, Neural Networks, Statistical Quality Control.

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Authors: Swapnil Rajan Jadhav, Ajay Vasantrao Kashikar

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Lubrication, cooling and chip removal are the desired functions of any cutting fluid. Conventional or flood lubrication requires high volume flow rate and cost associated with this is higher. In addition, flood lubrication possesses health risks to machine operator. To avoid these consequences, dry machining and minimum quantity are two alternatives. Dry machining cannot be a suited alternative as it can generate greater heat and poor surface finish. Here, turning work is carried out on a Lathe machine using EN3 Mild steel. Variable cutting speeds and depth of cuts are provided and corresponding temperatures and surface roughness values were recorded. Experimental results are analyzed by Minitab software. Regression analysis, main effect plot, and interaction plot conclusion are drawn by using ANOVA. There is a 95.83% reduction in the use of cutting fluid. MQL gives a 9.88% reduction in tool temperature, this will improve tool life. MQL produced a 17.64% improved surface finish. MQL appears to be an economical and environmentally compatible lubrication technique for sustainable manufacturing.

Keywords: ANOVA, MQL, regression analysis, surface roughness

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Authors: Swapnil Rajan Jadhav, Ajay Vasantrao Kashikar

Abstract:

Lubrication, cooling and chip removal are the desired functions of any cutting fluid. Conventional or flood lubrication requires high volume flow rate and cost associated with this is higher. In addition, flood lubrication possesses health risks to machine operator. To avoid these consequences, dry machining and minimum quantity are two alternatives. Dry machining cannot be a suited alternative as it can generate greater heat and poor surface finish. Here, turning work is carried out on a Lathe machine using EN3 Mild steel. Variable cutting speeds and depth of cuts are provided and corresponding temperatures and surface roughness values were recorded. Experimental results are analyzed by Minitab software. Regression analysis, main effect plot, and interaction plot conclusion are drawn by using ANOVA. There is a 95.83% reduction in the use of cutting fluid. MQL gives a 9.88% reduction in tool temperature, this will improve tool life. MQL produced a 17.64% improved surface finish. MQL appears to be an economical and environmentally compatible lubrication technique for sustainable manufacturing.

Keywords: ANOVA, MQL, regression analysis, surface roughness

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Authors: Tanawat Limwathanagura, Chartree Sithananun, Teekayu Limchamroon, Thanyarat Singhanart

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The objective of this paper is to study the analysis and testing for determining the torsional stiffness of the student formula-s space frame. From past study, the space frame for Chulalongkorn University Student Formula team used in 2011 TSAE Auto Challenge Student Formula in Thailand was designed by considering required mass and torsional stiffness based on the numerical method and experimental method. The numerical result was compared with the experimental results to verify the torsional stiffness of the space frame. It can be seen from the large error of torsional stiffness of 2011 frame that the experimental result can not verify by the numerical analysis due to the different between the numerical model and experimental setting. In this paper, the numerical analysis and experiment of the same 2011 frame model is performed by improving the model setting. The improvement of both numerical analysis and experiment are discussed to confirm that the models from both methods are same. After the frame was analyzed and tested, the results are compared to verify the torsional stiffness of the frame. It can be concluded that the improved analysis and experiments can used to verify the torsional stiffness of the space frame.

Keywords: Space Frame, Student Formula, Torsional Stiffness, TSAE Auto Challenge

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Authors: M. Sedighizadeh, A. Rezazadeh

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Wind turbines with double output induction generators can operate at variable speed permitting conversion efficiency maximization over a wide range of wind velocities. This paper presents the performance analysis of a wind driven double output induction generator (DOIG) operating at varying shafts speed. A periodic transient state analysis of DOIG equipped with two converters is carried out using a hybrid induction machine model. This paper simulates the harmonic content of waveforms in various points of drive at different speeds, based on the hybrid model (dqabc). Then the sinusoidal and trapezoidal pulse-width–modulation control techniques are used in order to improve the power factor of the machine and to weaken the injected low order harmonics to the supply. Based on the frequency spectrum, total harmonics distortion, distortion factor and power factor. Finally advantages of sinusoidal and trapezoidal pulse width modulation techniques are compared.

Keywords: DOIG, Harmonic Analysis, Wind.

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Authors: U. Bottigli, R.Chiarucci, B. Golosio, G.L. Masala, P. Oliva, S.Stumbo, D.Cascio, F. Fauci, M. Glorioso, M. Iacomi, R. Magro, G. Raso

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Purpose of this work is to develop an automatic classification system that could be useful for radiologists in the breast cancer investigation. The software has been designed in the framework of the MAGIC-5 collaboration. In an automatic classification system the suspicious regions with high probability to include a lesion are extracted from the image as regions of interest (ROIs). Each ROI is characterized by some features based generally on morphological lesion differences. A study in the space features representation is made and some classifiers are tested to distinguish the pathological regions from the healthy ones. The results provided in terms of sensitivity and specificity will be presented through the ROC (Receiver Operating Characteristic) curves. In particular the best performances are obtained with the Neural Networks in comparison with the K-Nearest Neighbours and the Support Vector Machine: The Radial Basis Function supply the best results with 0.89 ± 0.01 of area under ROC curve but similar results are obtained with the Probabilistic Neural Network and a Multi Layer Perceptron.

Keywords: Neural Networks, K-Nearest Neighbours, Support Vector Machine, Computer Aided Detection

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Authors: František Šebek, Petr Kubík, Jindřich Petruška, Jiří Hůlka

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Present study is aimed on the cutting process of circular cross-section rods where the fracture is used to separate one rod into two pieces. Incorporating the phenomenological ductile fracture model into the explicit formulation of finite element method, the process can be analyzed without the necessity of realizing too many real experiments which could be expensive in case of repetitive testing in different conditions. In the present paper, the steel AISI 1045 was examined and the tensile tests of smooth and notched cylindrical bars were conducted together with biaxial testing of the notched tube specimens to calibrate material constants of selected phenomenological ductile fracture models. These were implemented into the Abaqus/Explicit through user subroutine VUMAT and used for cutting process simulation. As the calibration process is based on variables which cannot be obtained directly from experiments, numerical simulations of fracture tests are inevitable part of the calibration. Finally, experiments regarding the cutting process were carried out and predictive capability of selected fracture models is discussed. Concluding remarks then make the summary of gained experience both with the calibration and application of particular ductile fracture criteria.

Keywords: Ductile fracture, phenomenological criteria, cutting process, explicit formulation, AISI 1045 steel.

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Authors: M. O. Welcome, E. V. Pereverzeva, V. A. Pereverzev

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The regulatory competence of blood glucose homeostasis might determine the degree of academic performance. The aim of this study was to produce a model of students' alcohol use based on glucose homeostasis control and cognitive functions that might define the pathogenetic mechanism of alcohol's effect on academic performance. The study took six hours and thirty minutes on fasting, involving thirteen male students. Disturbances in cognitive functions, precisely a decrease in the effectiveness of active attention and a faster development of fatigue after four to six hours of mental work in alcohol users, compared to abstainers was statistically proven. These disturbances in alcohol users were retained even after seven to ten days of moderate alcohol use and might be the reason for the low academic performances among students who use alcoholic beverages.

Keywords: Alcohol, academic performance, pathogenetic mechanism.

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Authors: Chongyang Ye, Rong Liu

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Compression textiles such as compression stockings (CSs) have been extensively applied for the prevention and treatment of chronic venous insufficiency of lower extremities. The involvement of multiple mechanical factors such as interface pressure, frictional force, and elastic materials make the interactions between lower limb and CSs to be complex. Determination of Poisson’s ratio and elastic moduli of CS materials are critical for constructing finite element (FE) modeling to numerically simulate a complex interactive system of CS and lower limb. In this study, a mixed approach, including an analytic model based on the orthotropic Hooke’s Law and experimental study (uniaxial tension testing and pure shear testing), has been proposed to determine Young’s modulus, Poisson’s ratio, and shear modulus of CS fabrics. The results indicated a linear relationship existing between the stress and strain properties of the studied CS samples under controlled stretch ratios (< 100%). The proposed method and the determined key mechanical properties of elastic orthotropic CS fabrics facilitate FE modeling for analyzing in-depth the effects of compression material design on their resultant biomechanical function in compression therapy.

Keywords: Elastic compression stockings, Young’s modulus, Poisson’s ratio, shear modulus, mechanical analysis.

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Authors: B. A. Parate, C. P. Shetty

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This research article describes the evaluation methodology of an internal ballistics of multi-perforated grain in a closed vessel (CV). The propellant testing in a CV is conducted to characterize the propellants and to ascertain the various internal ballistic parameters. The assessment of an internal ballistics plays a very crucial role for suitability of its use in the selection for a given particular application. The propellant used in defense sectors has to satisfy the user requirements as per laid down specifications. The outputs from CV evaluation of multi-propellant grain are maximum pressure of 226.75 MPa, differentiation of pressure with respect to time of 36.99 MPa/ms, average vivacity of 9.990×10-4/MPa ms, force constant of 933.9 J/g, rise time of 9.85 ms, pressure index of 0.878 including burning coefficient of 0.2919. This paper addresses an internal ballistic of multi-perforated grain, propellant selection, its calculation, and evaluation of various parameters in a CV testing. For the current analysis, the propellant is evaluated in 100 cc CV with propellant mass 20 g. The loading density of propellant is 0.2 g/cc. The method for determination of internal ballistic properties consists of burning of propellant mass under constant volume.

Keywords: Burning rate, closed vessel, force constant, internal ballistic, loading density, maximum pressure, multi-propellant grain, propellant, rise time, vivacity.

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Authors: Qiuyu Dai, Haochong Zhang, Xiangrong Liu

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Efficient matrix-vector multiplication with diagonal sparse matrices is pivotal in a multitude of computational domains, ranging from scientific simulations to machine learning workloads. When encoded in the conventional Diagonal (DIA) format, these matrices often induce computational overheads due to extensive zero-padding and non-linear memory accesses, which can hamper the computational throughput, and elevate the usage of precious compute and memory resources beyond necessity. The ’DIA-Adaptive’ approach, a methodological enhancement introduced in this paper, confronts these challenges head-on by leveraging the advanced parallel instruction sets embedded within Machine Learning Units (MLUs). This research presents a thorough analysis of the DIA-Adaptive scheme’s efficacy in optimizing Sparse Matrix-Vector Multiplication (SpMV) operations. The scope of the evaluation extends to a variety of hardware architectures, examining the repercussions of distinct thread allocation strategies and cluster configurations across multiple storage formats. A dedicated computational kernel, intrinsic to the DIA-Adaptive approach, has been meticulously developed to synchronize with the nuanced performance characteristics of MLUs. Empirical results, derived from rigorous experimentation, reveal that the DIA-Adaptive methodology not only diminishes the performance bottlenecks associated with the DIA format but also exhibits pronounced enhancements in execution speed and resource utilization. The analysis delineates a marked improvement in parallelism, showcasing the DIA-Adaptive scheme’s ability to adeptly manage the interplay between storage formats, hardware capabilities, and algorithmic design. The findings suggest that this approach could set a precedent for accelerating SpMV tasks, thereby contributing significantly to the broader domain of high-performance computing and data-intensive applications.

Keywords: Adaptive method, DIA, diagonal sparse matrices, MLU, sparse matrix-vector multiplication.

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Authors: Daniel Y. Abebe, Jeonghyun Jang, Jaehyouk Choi

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This study aims to evaluate the effective size, section and structural characteristics of circular hollow steel (CHS) damper. CHS damper is among steel dampers which are used widely for seismic energy dissipation because they are easy to install, maintain and are inexpensive. CHS damper dissipates seismic energy through metallic deformation due to the geometrical elasticity of circular shape and fatigue resistance around connection part. After calculating the effective size, which is found to be height to diameter ratio of √3, nonlinear FE analyses were carried out to evaluate the structural characteristics and effective section (diameter-to-ratio).

Keywords: Circular hollow steel damper, structural characteristics, effective size, effective section, large deformation, FE analysis.

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Authors: Jong-Ian Tsai, Chi-Chuan Chen, Tung-Sheng Zhan, Rong-Ching Wu

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Single-pole switching scheme is widely used in the Extra High Voltage system. However, the substantial negativesequence current injected to the turbine-generators imposes the electromagnetic (E/M) torque of double system- frequency components during the dead time (between single-pole clearing and line reclosing). This would induce supersynchronous resonance (SPSR) torque amplifications on low pressure turbine generator blades and even lead to fatigue damage. This paper proposes the design of a mechanical filter (MF) with natural frequency close to double-system frequency. From the simulation results, it is found that such a filter not only successfully damps the resonant effect, but also has the characteristics of feasibility and compact.

Keywords: Single-pole, Supersynchronous, Blade, Unbalance, filter

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Authors: Megha Gupta, Nupur Prakash

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Identification of plant diseases has been performed using machine learning and deep learning models on the datasets containing images of healthy and diseased plant leaves. The current study carries out an evaluation of some of the deep learning models based on convolutional neural network architectures for identification of plant diseases. For this purpose, the publicly available New Plant Diseases Dataset, an augmented version of PlantVillage dataset, available on Kaggle platform, containing 87,900 images has been used. The dataset contained images of 26 diseases of 14 different plants and images of 12 healthy plants. The CNN models selected for the study presented in this paper are AlexNet, ZFNet, VGGNet (four models), GoogLeNet, and ResNet (three models). The selected models are trained using PyTorch, an open-source machine learning library, on Google Colaboratory. A comparative study has been carried out to analyze the high degree of accuracy achieved using these models. The highest test accuracy and F1-score of 99.59% and 0.996, respectively, were achieved by using GoogLeNet with Mini-batch momentum based gradient descent learning algorithm.

Keywords: comparative analysis, convolutional neural networks, deep learning, plant disease identification

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Authors: Gautham Das, Edward Morrone, Erik Treble, Clinton Binder

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The purpose of this study was to evaluate the efficacy of a low-cost filter regarding per- and polyfluoroalkyl substances (PFAS). PFAS is a commonly used man-made chemical that can be found in a variety of household and industrial products with deleterious effects on humans. The filter consists of a combination of low-cost materials which could be locally procured. Water testing results for 4 different PFAS contaminants indicated that for Perfluorooctane sulfonic acid (PFOS), the Agency for Toxic Substances and Disease Registry (ATSDR) regulation is 7 ppt, the initial concentration was 15 ppt, and the final concentration was 3.9 ppt. For Perfluorononanoic acid (PFNA), the ATSDR regulation is 10.5 ppt, the initial concentration was 15 ppt, and the final concentration was 3.9 ppt. For Perfluorooctanoic acid (PFOA), the ATSDR regulation is 11 ppt, the initial concentration was 15 ppt, and the final concentration was 3.9 ppt. For Perfluorohexane sulfonic acid (PFHxS), the ATSDR regulation is 70 ppt, the initial concentration was 15 ppt, and the final concentration was 3.9 ppt. The results indicated a 74% reduction in PFAS concentration in filtered samples. Statistical data through regression analysis showed 0.9 validity of the sample data. Initial tests show the efficiency of the proposed filter described could be far greater if tested at a greater scale. It is highly recommended further testing to be conducted to validate the data for an innovative solution to a ubiquitous problem.

Keywords: PFAS, PFOS, PFOA, PFHxS, low-cost filter.

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Authors: H. Merhni, A. Sbiti, I. Ratbi, A. Sefiani

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The proximal spinal muscular atrophy (SMA) is a group of neuromuscular disorders characterized by progressive muscle weakness due to the degeneration and loss of anterior motor neurons of the spinal cord. Depending on the age of onset of symptoms and their evolution, four types of SMA, varying in severity, result in a mutations of the SMN gene (survival of Motor neuron). We have analyzed the DNA of 295 patients referred to our genetic counseling; since January 1996 until October 2014; for suspected SMA. The homozygous deletion of exon 7 of the SMN gene was found in 133 patients; of which, 40.6% were born to consanguineous parents. In countries like Morocco, where the frequency of heterozygotes for SMA is high, genetic testing should be offered as first-line and, after careful clinical assessment, especially in newborns and infants with congenital hypotonia unexplained and prognosis compromise. The molecular diagnosis of SMA allows a quick and certainly diagnosis, provide adequate genetic counseling for families at risk and suggest, for couples who want prenatal diagnosis. The analysis of the SMN gene is a perfect example of genetic testing with an excellent cost/benefit ratio that can be of great interest in public health, especially in low-income countries. We emphasize in this work for the benefit of the generalization of molecular diagnosis of SMA by the technique of PCR-enzymatic digestion in other centers in Morocco.

Keywords: Exon7, PCR-digestion, SMA, SMN gene.

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Authors: J. P. Dubois, O. M. Abdul-Latif

Abstract:

Support Vector Machine (SVM) is a statistical learning tool that was initially developed by Vapnik in 1979 and later developed to a more complex concept of structural risk minimization (SRM). SVM is playing an increasing role in applications to detection problems in various engineering problems, notably in statistical signal processing, pattern recognition, image analysis, and communication systems. In this paper, SVM was applied to the detection of SAR (synthetic aperture radar) images in the presence of partially developed speckle noise. The simulation was done for single look and multi-look speckle models to give a complete overlook and insight to the new proposed model of the SVM-based detector. The structure of the SVM was derived and applied to real SAR images and its performance in terms of the mean square error (MSE) metric was calculated. We showed that the SVM-detected SAR images have a very low MSE and are of good quality. The quality of the processed speckled images improved for the multi-look model. Furthermore, the contrast of the SVM detected images was higher than that of the original non-noisy images, indicating that the SVM approach increased the distance between the pixel reflectivity levels (the detection hypotheses) in the original images.

Keywords: Least Square-Support Vector Machine, SyntheticAperture Radar. Partially Developed Speckle, Multi-Look Model.

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Authors: M. O. Bayram, H. B. Gencdal, N. O. Fercan, B. Basbug

Abstract:

Liquid limit, which is used as a measure of soil strength, can be detected by Casagrande and fall-cone testing methods. The two methods majorly diverge from each other in terms of operator dependency. The Casagrande method that is applied according to ASTM D4318-17 standards may give misleading results, especially if the calibration process is not performed well. In this study, to reveal the effect of calibration for drop height and amount of soil paste placement in the Casagrande cup, a series of tests were carried out by multipoint method as it is specified in the ASTM standards. The tests include the combination of 6 mm, 8 mm, 10 mm, and 12 mm drop heights and under-filled, half-filled, and full-filled Casagrande cups by kaolin samples. It was observed that during successive tests, the drop height of the cup deteriorated; hence the device was recalibrated before and after each test to provide the accuracy of the results. Besides, the tests by under-filled and full-filled samples for higher drop heights revealed lower liquid limit values than the lower drop heights revealed. For the half-filled samples, it was clearly seen that the liquid limit values did not change at all as the drop height increased, and this explains the function of standard specifications.

Keywords: Calibration, Casagrande cup method, drop height, kaolin, liquid limit, placing form.

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Authors: W. Thepsuwan, N. Monmaturapoj

Abstract:

Calcium phosphate cement (CPC) is one of the most attractive bioceramics due to its moldable and shape ability to fill complicated bony cavities or small dental defect positions. In this study, CPC was produced by using mixture of tetracalcium phosphate (TTCP, Ca4O(PO4)2) and dicalcium phosphate anhydrous (DCPA, CaHPO4) in equimolar ratio (1/1) with aqueous solutions of acetic acid (C2H4O2) and disodium hydrogen phosphate dehydrate (Na2HPO4.2H2O) in combination with sodium alginate in order to improve theirs moldable characteristic. The concentration of the aqueous solutions and sodium alginate were varied to investigate the effect of different aqueous solutions and alginate on properties of the cements. The cement paste was prepared by mixing cement powder (P) with aqueous solution (L) in a P/L ratio of 1.0g/0.35ml. X-ray diffraction (XRD) was used to analyses phase formation of the cements. Setting time and compressive strength of the set CPCs were measured using the Gilmore apparatus and Universal testing machine, respectively. The results showed that CPCs could be produced by using both basic (Na2HPO4.2H2O) and acidic (C2H4O2) solutions. XRD results show the precipitation of hydroxyapatite in all cement samples. No change in phase formation among cements using difference concentrations of Na2HPO4.2H2O solutions. With increasing concentration of acidic solutions, samples obtained less hydroxyapatite with a high dicalcium phosphate dehydrate leaded to a shorter setting time. Samples with sodium alginate exhibited higher crystallization of hydroxyapatite than that of without alginate as a result of shorten setting time in a basic solution but a longer setting time in an acidic solution. The stronger cement was attained from samples using the acidic solution with sodium alginate; however the strength was lower than that of using the basic solution.

Keywords: Calcium phosphate cements, TTCP, DCPA, hydroxyapatite, properties.

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