Search results for: strength prediction

Authors: Tawanda Mushiri, Charles Mbohwa

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The performance of door assembly is very significant for the vehicle design. In the present paper, the finite element method is used in the development processes of the door assembly. The stiffness, strength, modal characteristic, and anti-extrusion of a newly developed passenger vehicle door assembly are calculated and evaluated by several finite element analysis commercial software. The structural problems discovered by FE analysis have been modified and finally achieved the expected door structure performance target of this new vehicle. The issue in focus is to predict the performance of the door assembly by powerful finite element analysis software, and optimize the structure to meet the design targets. It is observed that this method can be used to forecast the performance of vehicle door efficiently when it’s designed. In order to reduce lead time and cost in the product development of vehicles more development will be made virtually.

Keywords: vehicle door, structure, strength, stiffness, modal characteristic, anti-extrusion, Finite Element Method

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Authors: Reza Dinarvand, Mahdi Sadeghian, Somaye Sadeghian

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Prediction of the ultimate bearing capacity of piles (Qu) is one of the basic issues in geotechnical engineering. So far, several methods have been used to estimate Qu, including the recently developed artificial intelligence methods. In recent years, optimization algorithms have been used to minimize artificial network errors, such as colony algorithms, genetic algorithms, imperialist competitive algorithms, and so on. In the present research, artificial neural networks based on colonial competition algorithm (ANN-ICA) were used, and their results were compared with other methods. The results of laboratory tests of short piles in clayey soils with parameters such as pile diameter, pile buried length, eccentricity of load and undrained shear resistance of soil were used for modeling and evaluation. The results showed that ICA-based artificial neural networks predicted lateral bearing capacity of short piles with a correlation coefficient of 0.9865 for training data and 0.975 for test data. Furthermore, the results of the model indicated the superiority of ICA-based artificial neural networks compared to back-propagation artificial neural networks as well as the Broms and Hansen methods.

Keywords: artificial neural network, clayey soil, imperialist competition algorithm, lateral bearing capacity, short pile

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Authors: Lucas Viani, Benedetta Mennucci, Soo Young Park, Johannes Gierschner

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Organic semiconductors have attracted the attention of the scientific community in the past decades due to their unique physicochemical properties, allowing new designs and alternative device fabrication methods. Until today, organic electronic devices are largely based on conjugated polymers mainly due to their easy processability. In the recent years, due to moderate ET and CT efficiencies and the ill-defined nature of polymeric systems the focus has been shifting to small conjugated molecules with well-defined chemical structure, easier control of intermolecular packing, and enhanced CT and ET properties. It has led to the synthesis of new small molecules, followed by the growth of their crystalline structure and ultimately by the device preparation. This workflow is commonly followed without a clear knowledge of the ET and CT properties related mainly to the macroscopic systems, which may lead to financial and time losses, since not all materials will deliver the properties and efficiencies demanded by the current standards. In this work, we present a theoretical workflow designed to predict the key properties of ET of these new materials prior synthesis, thus speeding up the discovery of new promising materials. It is based on quantum mechanical, hybrid, and classical methodologies, starting from a single molecule structure, finishing with the prediction of its packing structure, and prediction of properties of interest such as static and averaged excitonic couplings, and exciton diffusion length.

Keywords: organic semiconductor, organic crystals, energy transport, excitonic couplings

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Authors: A. P .I. Popoola, V. S. Aigbodion, O. S. I. Fayomi

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The experimental study of the microstructure and properties of Al-Cu-Mg alloy/bean pod ash (BPA) nanoparticles was investigated. The aluminium matrix composites (AMCs) were produced by varying the BPA nanoparticles from 1-4wt%. The microstructure and phases of the composites produced were examined by SEM/EDS and XRD. Properties such as: hardness, tensile strength, impact energy, fatigue and wear were evaluated. The results showed that tensile strength and hardness values increased by 35 and 44.1% at 4wt% BPA nanoparticles with appreciable impact energy. The fatigue limit of 167MPa, 135 MPa and 75Mpa were obtained for the nano-particle (55nm), micro-particle (100µm) BPA composites and unreinforced alloy respectively. The wear properties of the as-cast Al–3.7%Cu-1.4%Mg/BPA nanoparticle have been improved significantly even with a low weight percent of BPA nanoparticle. The properties of the as-cast aluminium nanoparticles (MMNCs) have been improved significantly even with a low weight percent of nano-sized BPAp.

Keywords: bean pod ash nanoparticles, al-cu-mg alloy, mechanical properties, wear, microstructures

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Authors: Javed Iqbal

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Filling of Xiangjiaba Reservoir Lake in Southwest China triggered and re-activated numerous landslides due to water fluctuation. In order to understand the relationship between reservoirs and slope instability, a typical reservoir landslide (Dasha landslide) at right bank of Jinsha River was selected as a case study for in-depth investigations. The detailed field investigations were carried out in order to identify the landslide with respect to its surroundings and to find out the slip-surface. Boreholes were drilled in order to find out the subsurface lithology and the depth of failure of Dasha landslide. The in-situ geotechnical tests were performed, and the soil samples from exposed slip surface were retrieved for geotechnical laboratory analysis. Finally, stability analysis was done using 3D strength reduction method under different conditions of reservoir water level fluctuations and rainfall conditions. The in-depth investigations show that the Dasha landslide is a bedding rockslide which was once activated in 1986. The topography of Dasha landslide is relatively flat, while the back scarp and local terrain are relatively steep. The landslide area is about 29 × 104 m², and the maximum thickness of the landslide deposits revealed by drilling is about 40 m with the average thickness being about 20 m, and the volume is thus estimated being about 580 × 10⁴ m³. Bedrock in the landslide area is composed of Suining Formation of Jurassic age. The main rock type is silty mudstone with sandstone, and bedding orientation is 300~310° ∠ 7~22°. The factor of safety (FOS) of Dasha landslide obtained by 3D strength reduction cannot meet the minimum safety requirement under the working condition of reservoir level fluctuation as designed, with effect of rainfall and rapid drawdown.

Keywords: Dasha landslide, Xiangjiaba reservoir, strength reduction method, bedding rockslide

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Authors: Jiin Jeong, Taekwang Kim, Kwang Ryel Ryu

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The target microgrid in this paper is isolated from the large central power system and is assumed to consist of wind generators, photovoltaic power generators, an energy storage system (ESS), a diesel power generator, the community load, and a dump load. The operation of such a microgrid can be hazardous because of the uncertain prediction of power supply and demand and especially due to the high fluctuation of the output from the wind generators. In this paper, we propose an iterative replanning method for determining the appropriate level of diesel generation and the charging/discharging cycles of the ESS for the upcoming one-hour horizon. To cope with the uncertainty of the estimation of supply and demand, the one-hour plan is built repeatedly in the regular interval of one minute by rolling the one-hour horizon. Since the plan should be built with a sufficiently large safe margin to avoid any possible black-out, some energy waste through the dump load is inevitable. In our approach, the level of safe margin is optimized through learning from the past experience. The simulation experiments show that our method combined with the margin optimization can reduce the dump load compared to the method without such optimization.

Keywords: microgrid, operation planning, power efficiency optimization, supply and demand prediction

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Authors: Claire Xu, Welton Wang, Manasvi Pinnaka, Anqi Pan, Michael Han

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Hospitalizations account for one-third of the total health care spending in the US. Early risk detection and intervention can reduce this high cost and increase the satisfaction of both patients and physicians. Due to the lack of awareness of the potential arising risks in home environment, the opportunities for patients to seek early actions of clinical visits are dramatically reduced. This research aims to offer a highly personalized remote patients monitoring and risk assessment AI framework to identify the potentially preventable hospitalization for both acute as well as chronic diseases. A hybrid-AI framework is trained with data from clinical setting, patients surveys, as well as online databases. 20+ risk factors are analyzed ranging from activities, biometric info, demographic info, socio-economic info, hospitalization history, medication info, lifestyle info, etc. The AI model yields high performance of 87% accuracy and 88 sensitivity with 20+ features. This hybrid-AI framework is proven to be effective in identifying the potentially preventable hospitalization. Further, the high indicative features are identified by the models which guide us to a healthy lifestyle and early intervention suggestions.

Keywords: hospitalization prevention, machine learning, remote patient monitoring, risk prediction

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Authors: M. Gangadharappa, M. Ravi Kumar, H. N. Reddappa

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The mechanical properties and morphological analysis of Al6061-Red mud particulate composites were investigated. The compositions of the composite include a matrix of Al6061 and the red mud particles of 53-75 micron size as reinforcement ranging from 0% to 12% at an interval of 2%. Stir casting technique was used to fabricate Al6061-Red mud composites. Density measurement, estimation of percentage porosity, tensile properties, fracture toughness, hardness value, impact energy, percentage elongation and percentage reduction in area. Further, the microstructures and SEM examinations were investigated to characterize the composites produced. The result shows that a uniform dispersion of the red mud particles along the grain boundaries of the Al6061 alloy. The tensile strength and hardness values increases with the addition of Red mud particles, but there is a slight decrease in the impact energy values, values of percentage elongation and percentage reduction in area as the reinforcement increases. From these results of investigation, we concluded that the red mud, an industrial waste can be used to enhance the properties of Al6061 alloy for engineering applications.

Keywords: Al6061, red mud, tensile strength, hardness and microstructures

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Authors: G. Singer, M. Golan

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Providing students with learning disabilities (LD) with extra time to grant them equal access to the exam is a necessary but insufficient condition to compensate for their LD; there should also be a clear indication that the additional time was actually used. For example, if students with LD use more time than students without LD and yet receive lower grades, this may indicate that a different accommodation is required. If they achieve higher grades but use the same amount of time, then the effectiveness of the accommodation has not been demonstrated. The main goal of this study is to evaluate the effect of including parameters related to LD and extended exam time, along with other commonly-used characteristics (e.g., student background and ability measures such as high-school grades), on the ability of ordinal decision-tree algorithms to predict exam performance. We use naturally-occurring data collected from hundreds of undergraduate engineering students. The sub-goals are i) to examine the improvement in prediction accuracy when the indicator of exam performance includes 'actual time used' in addition to the conventional indicator (exam grade) employed in most research; ii) to explore the effectiveness of extended exam time on exam performance for different courses and for LD students with different profiles (i.e., sets of characteristics). This is achieved by using the patterns (i.e., subgroups) generated by the algorithms to identify pairs of subgroups that differ in just one characteristic (e.g., course or type of LD) but have different outcomes in terms of exam performance (grade and time used). Since grade and time used to exhibit an ordering form, we propose a method based on ordinal decision-trees, which applies a weighted information-gain ratio (WIGR) measure for selecting the classifying attributes. Unlike other known ordinal algorithms, our method does not assume monotonicity in the data. The proposed WIGR is an extension of an information-theoretic measure, in the sense that it adjusts to the case of an ordinal target and takes into account the error severity between two different target classes. Specifically, we use ordinal C4.5, random-forest, and AdaBoost algorithms, as well as an ensemble technique composed of ordinal and non-ordinal classifiers. Firstly, we find that the inclusion of LD and extended exam-time parameters improves prediction of exam performance (compared to specifications of the algorithms that do not include these variables). Secondly, when the indicator of exam performance includes 'actual time used' together with grade (as opposed to grade only), the prediction accuracy improves. Thirdly, our subgroup analyses show clear differences in the effect of extended exam time on exam performance among different courses and different student profiles. From a methodological perspective, we find that the ordinal decision-tree based algorithms outperform their conventional, non-ordinal counterparts. Further, we demonstrate that the ensemble-based approach leverages the strengths of each type of classifier (ordinal and non-ordinal) and yields better performance than each classifier individually.

Keywords: actual exam time usage, ensemble learning, learning disabilities, ordinal classification, time extension

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Authors: Anthropometric, Physical Fitness Ability Profile of Elite, Non-Elite Boxers of Manipur

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Background: Boxing is one of the oldest combat sports where different anthropological and fitness ability parameters determine performance. It is characterized by short duration, high intensity bursts of activity. The purpose of this research was to determine anthropometric and physical fitness profile of male elite and non-elite boxers of Manipur and to compare the two groups. Materials and Methods: Nineteen subjects were selected as elite boxers and twenty-four were non-elite boxers of Manipur. A cross-sectional study was conducted on anthropometric measurements and physical fitness ability tests on 33 subjects (elite and non-elite boxers). Statistical analysis was done using descriptive statistics, t-test and logistic regression with the help of SPSS version 15 software. Results: Results showed elite boxers have significantly reduced neck girth and calf girth as compare to non-elite boxers. Elite boxers have significantly lower sub scapular skin fold (SSF) and supra iliac skin fold (SISF) than their counterparts. Higher stature, larger BTB and lower percent fat are associated with higher performance in boxing. Sit ups (SU), standing Broad Jump (SBJ), Plat taping (PT), Sit and reach (SAR) and Harvard Step Test (HST) are predicted as most contributing factors enhancing performance level among the physical fitness components. Elite boxers are found to have more functional strength (sit ups), higher explosive strength (SBJ), more agility (PT), cardio-vascular endurance and flexibility (SAR) than non-elite boxers. Conclusion: In conclusion, lower fat, higher lean body mass, larger bi-trochantric breadth, high explosive strength, agility and flexibility are significantly associated with higher performance and chance of becoming elite boxers.

Keywords: anthropometry, elite and non-elite boxers, Manipur, physical fitness

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Authors: Shenlun Chen, Leonard Wee

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Tumor grading is an essential reference for colorectal cancer (CRC) staging and survival prognostication. The widely used World Health Organization (WHO) grading system defines histological grade of CRC adenocarcinoma based on the density of glandular formation on whole slide images (WSI). Tumors are classified as well-, moderately-, poorly- or un-differentiated depending on the percentage of the tumor that is gland forming; >95%, 50-95%, 5-50% and <5%, respectively. However, manually grading WSIs is a time-consuming process and can cause observer error due to subjective judgment and unnoticed regions. Furthermore, pathologists’ grading is usually coarse while a finer and continuous differentiation grade may help to stratifying CRC patients better. In this study, a deep learning based automatic differentiation grading algorithm was developed and evaluated by survival analysis. Firstly, a gland segmentation model was developed for segmenting gland structures. Gland regions of WSIs were delineated and used for differentiation annotating. Tumor regions were annotated by experienced pathologists into high-, medium-, low-differentiation and normal tissue, which correspond to tumor with clear-, unclear-, no-gland structure and non-tumor, respectively. Then a differentiation prediction model was developed on these human annotations. Finally, all enrolled WSIs were processed by gland segmentation model and differentiation prediction model. The differentiation grade can be calculated by deep learning models’ prediction of tumor regions and tumor differentiation status according to WHO’s defines. If multiple WSIs were possessed by a patient, the highest differentiation grade was chosen. Additionally, the differentiation grade was normalized into scale between 0 to 1. The Cancer Genome Atlas, project COAD (TCGA-COAD) project was enrolled into this study. For the gland segmentation model, receiver operating characteristic (ROC) reached 0.981 and accuracy reached 0.932 in validation set. For the differentiation prediction model, ROC reached 0.983, 0.963, 0.963, 0.981 and accuracy reached 0.880, 0.923, 0.668, 0.881 for groups of low-, medium-, high-differentiation and normal tissue in validation set. Four hundred and one patients were selected after removing WSIs without gland regions and patients without follow up data. The concordance index reached to 0.609. Optimized cut off point of 51% was found by “Maxstat” method which was almost the same as WHO system’s cut off point of 50%. Both WHO system’s cut off point and optimized cut off point performed impressively in Kaplan-Meier curves and both p value of logrank test were below 0.005. In this study, gland structure of WSIs and differentiation status of tumor regions were proven to be predictable through deep leaning method. A finer and continuous differentiation grade can also be automatically calculated through above models. The differentiation grade was proven to stratify CAC patients well in survival analysis, whose optimized cut off point was almost the same as WHO tumor grading system. The tool of automatically calculating differentiation grade may show potential in field of therapy decision making and personalized treatment.

Keywords: colorectal cancer, differentiation, survival analysis, tumor grading

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Authors: P. van Tonder, U. Bagdadi, B. M. D. Lario, Z. Masina, T. R. Motshwari

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This paper analyses how concrete reinforcing steel bars corrode and how it can be minimised through the use of various protection methods against corrosion, such as metal-based paint, alloying, cathodic protection and electroplating. Samples of carbon steel bars were protected, using these four methods. Tests performed on the samples included durability, electrical resistivity and bond strength. Durability results indicated relatively low corrosion rates for alloying, cathodic protection, electroplating and metal-based paint. The resistivity results indicate all samples experienced a downward trend, despite erratic fluctuations in the data, indicating an inverse relationship between electrical resistivity and corrosion rate. The results indicated lowered bond strengths when the reinforced concrete was cured in seawater compared to being cured in normal water. It also showed that higher design compressive strengths lead to higher bond strengths which can be used to compensate for the loss of bond strength due to corrosion in a real-world application. In terms of implications, all protection methods have the potential to be effective at resisting corrosion in real-world applications, especially the alloying, cathodic protection and electroplating methods. The metal-based paint underperformed by comparison, most likely due to the nature of paint in general which can fade and chip away, revealing the steel samples and exposing them to corrosion. For alloying, stainless steel is the suggested material of choice, where Y-bars are highly recommended as smooth bars have a much-lowered bond strength. Cathodic protection performed the best of all in protecting the sample from corrosion, however, its real-world application would require significant evaluation into the feasibility of such a method.

Keywords: protection methods, corrosion, concrete, reinforcing steel bars

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Authors: B. Adebayo, A. O. Omotehinse, C. Arum

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This study investigates the suitability of dredged samples for the production of bricks. Some geotechnical properties (moisture content, grain size distribution) of dredged samples were also determined using the British Standard. Bricks were produced using appropriate mixes of two dredged wastes. The dredged samples (Oroto dredged samples and Igbokoda dredged samples) have high moisture content of 90.48 % and 37.5 % respectively and both are classified as silty materials. The two dredged samples were mixed in different percentage (1- Oroto dredged sample (DS) 85 % and Igbokoda dredged sample (IS) 15 %, 2-DS 70 % and IS 30 %, 3- DS 55 % and IS 45 %, 4- DS 50 % and IS 50 %, 5- DS 45 % and IS 55 %,6- DS 30 % and IS 70 %, 7- DS 15 % and IS 85 %, 8- Clay 100 %, 9- DS 100 %, 10-IS 100 %) for the production of bricks and were tested for 7 days, 14 days, 21 days and 28 days. Although, the water absorption level of the bricks produced were high (5.635 to 33.4 %), the compressive strength on the 28th day was within the accepted British Standard. The Igbokoda dredge sample is a good material for the production of bricks when mixed with Oroto Dredged sample because the compressive strength of the material is within the accepted limit.

Keywords: bricks, dredged, moisture content, suitability

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Authors: Maria Santana, Jose Estaire

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Even though recycling strategies are becoming more important in recent years, there is still a huge amount of industrial by-products that are the disposal of at landfills. Due to the size, possible dangerous composition, and heterogeneity, most of the wastes are located at landfills without a basic geotechnical characterization. This lack of information may have an important influence on the correct stability calculations. This paper presents the results of geotechnical characterization of some industrial wastes disposed at one landfill. The shear strength parameters were calculated based on direct shear test results carried out in a large shear box owned by CEDEX, which has a shear plane of 1 x 1 m. These parameters were also compared with the results obtained in a 30 x 30 cm shear box. The paper includes a sensitive analysis of the global safety factor of the landfill's overall stability as a function of shear strength variation. The stability calculations were assessed for various hydrological scenarios to simulate the design and performance of the leachate drainage system. The characterization was completed with leachate tests to study the potential impact on the environment.

Keywords: industrial wastes, landfill, leachate tests, stability

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Authors: Kamrun N. Keya, Nasrin A. Kona, Ruhul A. Khan

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Pineapple leaf fiber (PALF) reinforced polypropylene (PP) based composites were fabricated by a conventional compression molding technique. In this investigation, PALF composites were manufactured using different percentages of fiber, which were varying from 25-50% on the total weight of the composites. To fabricate the PALF/PP composites, untreated and treated fibers were selected. A systematic study was done to observe the physical, mechanical and interfacial behavior of the composites. In this study, mechanical properties of the composites such as tensile, impact and bending properties were observed precisely. It was found that 45wt% of fiber composites showed better mechanical properties than others. Maximum tensile strength (TS) and bending strength (BS) was observed, 65 MPa and 50 MPa respectively, whereas the highest tensile modulus (TM) and bending modulus (BM) was examined, 1.7 GPa and 0.85 GPa respectively. The PALF/PP based composites were treated with irradiated under gamma radiation (the source strength 50 kCi Cobalt-60) of various doses (2.5 kGy to 10 kGy). The effect of gamma radiation on the composites was also investigated, and it found that the effect of 5.0 kGy (i.e. units for radiation measurement is 'gray', kGy=kilogray ) gamma dose showed better mechanical properties than other doses. The values of TS, BS, TM, and BM of the irradiated (5.0 kGy) composites were found to improve by 19%, 23%, 17% and 25 % over non-irradiated composites. After flexural testing, fracture sides of the untreated and treated both composites were studied by scanning electron microscope (SEM). SEM results of the treated PALF/PP based composites showed better fiber-matrix adhesion and interfacial bonding than untreated PALF/PP based composites. Water uptake and soil degradation tests of untreated and treated composites were also investigated.

Keywords: PALF, polypropylene, compression molding technique, gamma radiation, mechanical properties, scanning electron microscope

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Authors: Yu-Ting Wang, Yun-Hsiang Cheng, Chien-Cheng Lin, Kun-Lin Lin

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Using a transient liquid phase method, Al was successfully bonded with Al₂O₃, which deposited Ni, Cu, Ge, and Si at the surface of the Al₂O₃ substrate after annealing at the relatively low melting point of Al. No reaction interlayer existed at the interface of any Al/Al₂O₃ specimens. Al−Fe intermetallic compounds, such as Al₉Fe₂ and Al₃Fe, formed in the Al substrate because of the precipitation of Fe, which was an impurity of the Al foil, and the reaction with Al at the grain boundaries of Al during annealing processing. According to the evaluation results of mechanical and thermal properties, the Al/Al₂O₃ specimen deposited on the Ni film possessed the highest shear strength, thermal conductivity, and bonding area percentage, followed by the Cu, Ge, and Si films. The properties of the Al/Al₂O₃ specimens deposited with Ge and Si were relatively unsatisfactory, which could be because the deposited amorphous layers easily formed oxide, resulting in inferior adhesion between Al and Al₂O₃. Therefore, the optimal choice for use in high-power devices is Al/Al₂O₃, with the deposition of Ni film.

Keywords: direct-bonded aluminum, transient liquid phase, thermal conductivity, microstructures, shear strength

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Authors: Mohammad S. Rouhi, Magdalena Juntikka

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Processing of polymer fiber composites has a remarkable influence on their mechanical performance. These mechanical properties are even more influenced when using recycled reinforcement. Therefore, we place particular attention on the evaluation of micromechanical models to estimate the mechanical properties and compare them against the experimental results of the manufactured composites. For the manufacturing process, an epoxy matrix and carbon fiber production cut-offs as reinforcing material are incorporated using a vacuum infusion process. In addition, continuous textile reinforcement in combination with the epoxy matrix is used as reference material to evaluate the kick-down in mechanical performance of the recycled composite. The experimental results show less degradation of the composite stiffness compared to the strength properties. Observations from the modeling also show the same trend as the error between the theoretical and experimental results is lower for stiffness comparisons than the strength calculations. Yet still, good mechanical performance for specific applications can be expected from these materials.

Keywords: composite recycling, carbon fibers, mechanical properties, micromechanics

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Authors: Arun Goel

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The present paper attempts to investigate the prediction of air entrainment rate and aeration efficiency of a free over-fall jets issuing from a triangular sharp crested weir by using regression based modelling. The empirical equations, support vector machine (polynomial and radial basis function) models and the linear regression techniques were applied on the triangular sharp crested weirs relating the air entrainment rate and the aeration efficiency to the input parameters namely drop height, discharge, and vertex angle. It was observed that there exists a good agreement between the measured values and the values obtained using empirical equations, support vector machine (Polynomial and rbf) models, and the linear regression techniques. The test results demonstrated that the SVM based (Poly & rbf) model also provided acceptable prediction of the measured values with reasonable accuracy along with empirical equations and linear regression techniques in modelling the air entrainment rate and the aeration efficiency of a free over-fall jets issuing from triangular sharp crested weir. Further sensitivity analysis has also been performed to study the impact of input parameter on the output in terms of air entrainment rate and aeration efficiency.

Keywords: air entrainment rate, dissolved oxygen, weir, SVM, regression

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Authors: Konrad Pietrykowski, Michał Gęca, Michał Bialy

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The paper presents the results of the crankshaft strength simulation. The crankshaft was taken from the opposed piston engine. Calculations were made using finite element method (FEM) in Abaqus software. This program allows to perform strength tests of individual machine parts as well as their assemblies. The crankshaft that was used in the calculations will be used in the two-stroke aviation research aircraft engine. The assumptions for the calculations were obtained from the AVL Boost software, from one-dimensional engine cycle model and from the multibody model using the method developed in the MSC Adams software. The research engine will be equipped with 3 combustion chambers and two crankshafts. In order to shorten the calculation time, only one crankcase analysis was performed. The cut of the shaft has been selected with the greatest forces resulting from the engine operation. Calculations were made for two cases. For maximum piston force when maximum bending load occurs and for the maximum torque. Cast iron material was adopted. For this material, Poisson's number, density, and Young's modulus were determined. The computational grid contained of 1,977,473 Tet elements. This type of elements was chosen because of the complex design of the crankshaft. Results are presented in the form of stress distributions maps and displacements on the surface and inside the geometry of the shaft. The results show the places of tension stresses, however, no stresses are exceeded at any place. The shaft can thus be applied to the engine in its present form. Acknowledgement: This work has been realized in the cooperation with The Construction Office of WSK 'PZL-KALISZ’ S.A. and is part of Grant Agreement No. POIR.01.02.00-00-0002/15 financed by the Polish National Centre for Research and Development.

Keywords: aircraft diesel engine, crankshaft, finite element method, two-stroke engine

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Authors: Ya Lv

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This article presents the application of the semi-analytic method (SAM) in the thermal management solution (TMS) of the energy storage system (ESS). The TMS studied in this work is fluid cooling. In fluid cooling, both effective heat conduction and heat convection are indispensable due to the heat transfer from solid to fluid. Correspondingly, an efficient TMS requires a design investigation of the following parameters: fluid inlet temperature, ESS initial temperature, fluid flow rate, working c rate, continuous working time, and materials properties. Their variation induces a change of thermal performance in the battery module, which is usually evaluated by numerical simulation. Compared to complicated computation resources and long computation time in simulation, the SAM is developed in this article to predict the thermal influence within a few seconds. In SAM, a fast prediction model is reckoned by combining numerical simulation with theoretical/empirical equations. The SAM can explore the thermal effect of boundary parameters in both steady-state and transient heat transfer scenarios within a short time. Therefore, the SAM developed in this work can simplify the design cycle of TMS and inspire more possibilities in TMS design.

Keywords: semi-analytic method, fast prediction model, thermal influence of boundary parameters, energy storage system

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Authors: Syed Atif Hassan, Luv Mehta, Syed Asif Hassan

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Hit song science is a field of investigation wherein machine learning techniques are applied to music tracks in order to extract such features from audio signals which can capture information that could explain the popularity of respective tracks. Record companies invest huge amounts of money into recruiting fresh talents and churning out new music each year. Gaining insight into the basis of why a song becomes popular will result in tremendous benefits for the music industry. This paper aims to extract basic musical and more advanced, acoustic features from songs while also taking into account external factors that play a role in making a particular song popular. We use a dataset derived from popular Spotify playlists divided by genre. We use ten genres (blues, classical, country, disco, hip-hop, jazz, metal, pop, reggae, rock), chosen on the basis of clear to ambiguous delineation in the typical sound of their genres. We feed these features into three different classifiers, namely, SVM with RBF kernel, a deep neural network, and a recurring neural network, to build separate predictive models and choosing the best performing model at the end. Predicting song popularity is particularly important for the music industry as it would allow record companies to produce better content for the masses resulting in a more competitive market.

Keywords: classifier, machine learning, music tracks, popularity, prediction

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Authors: Sanja O. Podunavac-Kuzmanović, Lidija R. Jevrić, Strahinja Z. Kovačević

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Benzimidazoles are a group of compounds with significant antibacterial, antifungal and anticancer activity. The studied compounds consist of the main benzimidazole structure with different combinations of substituens. This study is based on the two-dimensional and three-dimensional molecular modeling and calculation of molecular descriptors (physicochemical and lipophilicity descriptors) of structurally diverse benzimidazoles. Molecular modeling was carried out by using ChemBio3D Ultra version 14.0 software. The obtained 3D models were subjected to energy minimization using molecular mechanics force field method (MM2). The cutoff for structure optimization was set at a gradient of 0.1 kcal/Åmol. The obtained set of molecular descriptors was used in principal component analysis (PCA) of possible similarities and dissimilarities among the studied derivatives. After the molecular modeling, the quantitative structure-property relationship (QSPR) analysis was applied in order to get the mathematical models which can be used in prediction of pKb values of structurally similar benzimidazoles. The obtained models are based on statistically valid multiple linear regression (MLR) equations. The calculated cross-validation parameters indicate the high prediction ability of the established QSPR models. This study is financially supported by COST action CM1306 and the project No. 114-451-347/2015-02, financially supported by the Provincial Secretariat for Science and Technological Development of Vojvodina.

Keywords: benzimidazoles, chemometrics, molecular modeling, molecular descriptors, QSPR

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Authors: Sandile Daniel Ngidi

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Masonry structures often crack due to different factors, which include differential movement of structures, thermal expansion, and seismic waves. Retrofitting is introduced to ensure that these cracks do not expand to a point of making the wall fail. Crack stitching is one of many repairing methods used to repair cracked masonry walls. It is done by stitching helical stainless steel reinforcement bars to reconnect and stabilize the wall. The basic element of this reinforcing system is the mechanical interlink between the helical stainless-steel bar and the grout, which makes it such a flexible and well-known masonry repair system. The objective of this review was to use previous experimental work done by different authors to check the efficiency and effectiveness of using the crack stitching technique to repair and stabilize masonry walls. The technique was found to be effective to rejuvenate the strength of a masonry structure to be stronger than initial strength. Different factors were investigated, which include economic features, sustainability, buildability, and suitability of this technique for application in developing communities.

Keywords: brickforce, crack-stitching, masonry concrete, reinforcement, wall panels

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Authors: Jing Zhao, Dayong Liu, Shihao Wang, Xinghua Zhu, Delong Li

Abstract:

Uhumanned Underwater Vehicles generally operate in the deep sea, which has its own unique working conditions. Lithium-ion power batteries should have the necessary stability and endurance for use as an underwater vehicle’s power source. Therefore, it is essential to accurately forecast how long lithium-ion batteries will last in order to maintain the system’s reliability and safety. In order to model and forecast lithium battery Remaining Useful Life (RUL), this research suggests a model based on Complete Ensemble Empirical Mode Decomposition with Adaptive noise-Temporal Convolutional Net (CEEMDAN-TCN). In this study, two datasets, NASA and CALCE, which have a specific gap in capacity data fluctuation, are used to verify the model and examine the experimental results in order to demonstrate the generalizability of the concept. The experiments demonstrate the network structure’s strong universality and ability to achieve good fitting outcomes on the test set for various battery dataset types. The evaluation metrics reveal that the CEEMDAN-TCN prediction performance of TCN is 25% to 35% better than that of a single neural network, proving that feature expansion and modal decomposition can both enhance the model’s generalizability and be extremely useful in industrial settings.

Keywords: lithium-ion battery, remaining useful life, complete EEMD with adaptive noise, temporal convolutional net

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Authors: M. Belouadah, S. Rahmouni, N. Teballe

Abstract:

The durability of concrete is not one of its features, but its response to service loads and environmental conditions. Thus, the durability of concrete depends on a variety of material characteristics, but also the aggressiveness of the environment. Much durability problems encountered in tropical regions (region M'sila) due to the presence of chlorides and sulfates (in the ground or in the aggregate) with the additional aggravation of the effect of hot weather and arid. This lack of sustainability has a direct influence on the structure of the building and can lead to the complete deterioration of many buildings. The characteristics of the nature of fillers are evaluated based on the degree of aggressiveness of the environment considering as a means of characterization: mechanical strength, porosity. Specimens will be exposed to different storage media chemically aggressive drinking water, salts and sulfates (sodium chloride, MgSO4), solutions are not renewed or PH control solutions. The parameters taken into account are: age, the nature and degree of aggressiveness of the environment conservation, the incorporation of adjuvant type superplasticizer dosage and mineral additives.

Keywords: ordinary concretes, marble powder fillers, adjuvant, strength

Procedia PDF Downloads 260

Authors: A. Lakshumu Naidu, K. Krishna Kishor

Abstract:

This paper examines the results of an experimental study based on the engineering properties of banana peel reinforced epoxy composites. Experiments are carried out to study the effect of weight fraction on mechanical behavior of epoxy based polymer composites. The composites were made by varying the weight fraction of banana peel from 0 to 30% and banana peel were made using hand layup method. The fabricated composite samples were cut according to the ASTM standards for different experiments. Hardness test and density test were carried out at the samples. The maximum hardness, density, tensile strength, flexural strength and ILSS are getting for the material prepared with the 20 % reinforced banana peel epoxy composite. The detailed test results and observations are discussed sequentially in the paper.

Keywords: engineering properties, polymer, composite, mechanical behavior of banana peel

Procedia PDF Downloads 353

Authors: M. Abou-Amouna, A. Radwan, L. Al-kuwari, A. Hammuda, K. Al-Khalifa

Abstract:

There is growing concern over increasing incidences of road accidents and consequent loss of human life in Qatar. In light to the future planned event in Qatar, World Cup 2022; Qatar should put into consideration the future deaths caused by road accidents, and past trends should be considered to give a reasonable picture of what may happen in the future. Qatar roads should be arranged and paved in a way that accommodate high capacity of the population in that time, since then there will be a huge number of visitors from the world. Qatar should also consider the risk issues of road accidents raised in that period, and plan to maintain high level to safety strategies. According to the increase in the number of road accidents in Qatar from 1995 until 2012, an analysis of elements affecting and causing road accidents will be effectively studied. This paper aims to identify and criticize the factors that have high effect on causing road accidents in the state of Qatar, and predict the total number of road accidents in Qatar 2022. Alternative methods are discussed and the most applicable ones according to the previous researches are selected for further studies. The methods that satisfy the existing case in Qatar were the multiple linear regression model (MLR) and artificial neutral network (ANN). Those methods are analyzed and their findings are compared. We conclude that by using MLR the number of accidents in 2022 will become 355,226 accidents, and by using ANN 216,264 accidents. We conclude that MLR gave better results than ANN because the artificial neutral network doesn’t fit data with large range varieties.

Keywords: road safety, prediction, accident, model, Qatar

Procedia PDF Downloads 240

Authors: Ellisha Iling, Dayang Siti Hazimmah Ali

Abstract:

Experimental composite boards were fabricated using oil palm (Elaeis guineensis Jacq) fronds particles by applying hot press pressure of 5MPa, 6MPa and 7MPa respectively. Modulus of rupture (MOR) and internal bond strength (IB) of the composite boards made with target density of 0.80 g/cm³ were evaluated. Composite board fabricated under hot press pressure of 5MPa had MOR and IB values of 16.27 and 4.34 N/mm² respectively. Corresponding values for composite board fabricated under hot press pressure of 6MPa were 16.76 and 5.41 N/mm² respectively. Whereas, the MOR and IB values of composite board fabricated under hot press pressure of 7MPa were 17.24 and 6.19 N/mm² respectively. All composite boards met the MOR and IB requirement stated in Japanese Industrial Standard (JIS). Based on results of this work, the strength of mechanical properties of composite board increased with increase of hot press pressure. This study revealed that the selection of applied pressure during fabrication of composite board is important to improve mechanical properties of composite boards.

Keywords: composite board, Elaeis guineensis Jacq. Fronds, hot press pressure, mechanical properties

Procedia PDF Downloads 178

Authors: Deepa T., Inchara S. R., Venkatesh S. V., Seema Tharannum

Abstract:

Concrete is the most widely used structural material. It is usually made using locally available materials. However, concrete has low tensile strength and may crack in the early days with exothermic hydration, for which water is essential. To address the increased construction water demand, treated greywater may be used. Bacillus subtilis bacteria that form endospores is the biological agent considered in this study for biomineralization or Microbially Induced Calcite Precipitation (MICP) technique to heal cracks. Treated grey water which is obtained from STP of PES University, opted in place of Potable water, which had qualities within the standard range as per codal provisions. In this work, M30 grade conventional concrete is designed using OPC 53-grade cement, manufactured sand, natural coarse aggregates, and potable water. Conventional concrete (CC), bacterial concrete with potable water (BS), and treated grey water concrete (TGWBS) are the three different concrete specimens cast. Experimental studies such as the strength test and the surface hardness test are performed on conventional and bacterial concrete samples after 7, 28, and 56 days of curing. Concrete cubes are subjected to a temperature of 50° C to investigate the effect of higher temperature. Cracked cube specimens are observed for self-healing -as well as microstructure analysis with Scanning Electron Microscope (SEM), Energy Dispersive X-Ray Analysis (EDAX), and X-Ray Diffraction Analysis (XRD). Noticeable calcium salt deposition is observed on the surface of the BS and TGWBS cracked specimen. Surface hardness and the EDAX test gave promising results on the advantage of using spore-forming bacteria in concrete. This is followed by the strength gained in compression and flexure. Results also indicate that treated grey water can be a substitute for potable water in concrete.

Keywords: Bacillus subtilis concrete, microstructure, temperature, treated greywater

Procedia PDF Downloads 80

Authors: S. H. Chew, Z. X. Eng, K. E. Chuah, T. Y. Lim, H. M. A. Yim

Abstract:

In recent years, geotextile tube has been widely used in the hydraulic engineering and dewatering industry. To construct a stable containment bund with geotextile tubes, the sand slurry is always the preference infilling material. However, the shortage of sand supply posts a problem in Singapore to adopt this construction method in the actual construction of long containment bund. Hence, utilizing the soft dredged clay or the excavated soft clay as the infilling material of geotextile tubes has a great economic benefit. There are any technical issues with using this soft clayey material as infilling material, especially on the excessive settlement and stability concerns. To minimize the shape deformation and settlement of geotextile tube associated with the use of this soft clay infilling material, a modified innovative infilling material is proposed – lightly cemented soft clay. The preliminary laboratory studies have shown that the dewatering mechanism via geotextile material of the tube skin, and the introduction of cementitious chemical action of the lightly cemented soft clay will accelerate the consolidation and improve the shear strength of infill material. This study aims to extend the study by conducting a pilot test of the geotextile tube filled with lightly cemented clay. This study consists of testing on a series of miniature geo-tubes and two full-size geotextile tube. In the miniature geo-tube tests, a number of small scaled-down size of geotextile tubes were filled with cemented clay (at water content of 150%) with cement content of 0% to 8% (by weight). The shear strength development of the lightly cemented clay under dewatering mechanism was evaluated using a modified in-situ Cone Penetration Test (CPT) at 0 days, 3 days, 7 days and 28 days after the infilling. The undisturbed soil samples of lightly cemented infilled clay were also extracted at 3-days and 7-days for triaxial tests and evaluation of final water content. The results suggested that the geotextile tubes filled with un-cemented soft clay experienced very significant shape change over the days (as control test). However, geotextile mini-tubes filled with lightly cemented clay experienced only marginal shape changed, even that the strength development of this lightly cemented clay inside the tube may not show significant strength gain at the early stage. The shape stability is believed to be due to the confinement effect of the geotextile tube with clay at non-slurry state. Subsequently, a full-scale instrumented geotextile tube filled with lightly cemented clay was performed. The extensive results of strain gauges and pressure transducers installed on this full-size geotextile tube demonstrated a substantial mobilization of tensile forces on the geotextile skin corresponding to the filling activity and the subsequent dewatering stage. Shape change and the in-fill material strength development was also monitored. In summary, the construction of containment bund with geotextile tube filled with lightly cemented clay is found to be technically feasible and stable with the use of the sufficiently strong (i.e. adequate tensile strength) geotextile tube, the adequate control on the dosage of cement content, and suitable water content of infilling soft clay material.

Keywords: cemented clay, containment bund, dewatering, geotextile tube

Procedia PDF Downloads 257