Search results for: compressive strength prediction
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5945

Search results for: compressive strength prediction

3005 Production and Characterization of Al-BN Composite Materials by Using Powder Metallurgy

Authors: Ahmet Yonetken, Ayhan Erol

Abstract:

Aluminum matrix composites containing 3, 6, 9, 12 and 15% BN has been fabricated by conventional microwave sintering at 550°C temperature. Compounds formation between Al and BN powders is observed after sintering under Ar shroud. XRD, SEM (Scanning Electron Microscope), mechanical testing and measurements were employed to characterize the properties of Al + BN composite. Experimental results suggest that the best properties as hardness 42,62 HV were obtained for Al+12% BN composite. In this study, the powder metallurgy method was used. It is aimed to produce a light composite with Al matrix BN powders. It has been increased in strength and hardness besides its lightness. Ceramic powders are added to improve mechanical properties.

Keywords: ceramic-metal composites, proporties, powder metallurgy, sintering

Procedia PDF Downloads 191
3004 AI-Driven Strategies for Sustainable Electronics Repair: A Case Study in Energy Efficiency

Authors: Badiy Elmabrouk, Abdelhamid Boujarif, Zhiguo Zeng, Stephane Borrel, Robert Heidsieck

Abstract:

In an era where sustainability is paramount, this paper introduces a machine learning-driven testing protocol to accurately predict diode failures, merging reliability engineering with failure physics to enhance repair operations efficiency. Our approach refines the burn-in process, significantly curtailing its duration, which not only conserves energy but also elevates productivity and mitigates component wear. A case study from GE HealthCare’s repair center vividly demonstrates the method’s effectiveness, recording a high prediction of diode failures and a substantial decrease in energy consumption that translates to an annual reduction of 6.5 Tons of CO2 emissions. This advancement sets a benchmark for environmentally conscious practices in the electronics repair sector.

Keywords: maintenance, burn-in, failure physics, reliability testing

Procedia PDF Downloads 62
3003 Water Purification By Novel Nanocomposite Membrane

Authors: E. S. Johal, M. S. Saini, M. K. Jha

Abstract:

Currently, 1.1 billion people are at risk due to lack of clean water and about 35 % of people in the developed world die from water related problem. To alleviate these problems water purification technology requires new approaches for effective management and conservation of water resources. Electrospun nanofibres membrane has a potential for water purification due to its high large surface area and good mechanical strength. In the present study PAMAM dendrimers composite nynlon-6 nanofibres membrane was prepared by crosslinking method using Glutaraldehyde. Further, the efficacy of the modified membrane can be renewed by mere exposure of the saturated membrane with the solution having acidic pH. The modified membrane can be used as an effective tool for water purification.

Keywords: dendrimer, nanofibers, nanocomposite membrane, water purification

Procedia PDF Downloads 352
3002 Implementation of a Method of Crater Detection Using Principal Component Analysis in FPGA

Authors: Izuru Nomura, Tatsuya Takino, Yuji Kageyama, Shin Nagata, Hiroyuki Kamata

Abstract:

We propose a method of crater detection from the image of the lunar surface captured by the small space probe. We use the principal component analysis (PCA) to detect craters. Nevertheless, considering severe environment of the space, it is impossible to use generic computer in practice. Accordingly, we have to implement the method in FPGA. This paper compares FPGA and generic computer by the processing time of a method of crater detection using principal component analysis.

Keywords: crater, PCA, eigenvector, strength value, FPGA, processing time

Procedia PDF Downloads 547
3001 Insights into Particle Dispersion, Agglomeration and Deposition in Turbulent Channel Flow

Authors: Mohammad Afkhami, Ali Hassanpour, Michael Fairweather

Abstract:

The work described in this paper was undertaken to gain insight into fundamental aspects of turbulent gas-particle flows with relevance to processes employed in a wide range of applications, such as oil and gas flow assurance in pipes, powder dispersion from dry powder inhalers, and particle resuspension in nuclear waste ponds, to name but a few. In particular, the influence of particle interaction and fluid phase behavior in turbulent flow on particle dispersion in a horizontal channel is investigated. The mathematical modeling technique used is based on the large eddy simulation (LES) methodology embodied in the commercial CFD code FLUENT, with flow solutions provided by this approach coupled to a second commercial code, EDEM, based on the discrete element method (DEM) which is used for the prediction of particle motion and interaction. The results generated by LES for the fluid phase have been validated against direct numerical simulations (DNS) for three different channel flows with shear Reynolds numbers, Reτ = 150, 300 and 590. Overall, the LES shows good agreement, with mean velocities and normal and shear stresses matching those of the DNS in both magnitude and position. The research work has focused on the prediction of those conditions favoring particle aggregation and deposition within turbulent flows. Simulations have been carried out to investigate the effects of particle size, density and concentration on particle agglomeration. Furthermore, particles with different surface properties have been simulated in three channel flows with different levels of flow turbulence, achieved by increasing the Reynolds number of the flow. The simulations mimic the conditions of two-phase, fluid-solid flows frequently encountered in domestic, commercial and industrial applications, for example, air conditioning and refrigeration units, heat exchangers, oil and gas suction and pressure lines. The particle size, density, surface energy and volume fractions selected are 45.6, 102 and 150 µm, 250, 1000 and 2159 kg m-3, 50, 500, and 5000 mJ m-2 and 7.84 × 10-6, 2.8 × 10-5, and 1 × 10-4, respectively; such particle properties are associated with particles found in soil, as well as metals and oxides prevalent in turbulent bounded fluid-solid flows due to erosion and corrosion of inner pipe walls. It has been found that the turbulence structure of the flow dominates the motion of the particles, creating particle-particle interactions, with most of these interactions taking place at locations close to the channel walls and in regions of high turbulence where their agglomeration is aided both by the high levels of turbulence and the high concentration of particles. A positive relationship between particle surface energy, concentration, size and density, and agglomeration was observed. Moreover, the results derived for the three Reynolds numbers considered show that the rate of agglomeration is strongly influenced for high surface energy particles by, and increases with, the intensity of the flow turbulence. In contrast, for lower surface energy particles, the rate of agglomeration diminishes with an increase in flow turbulence intensity.

Keywords: agglomeration, channel flow, DEM, LES, turbulence

Procedia PDF Downloads 314
3000 A Generalized Framework for Adaptive Machine Learning Deployments in Algorithmic Trading

Authors: Robert Caulk

Abstract:

A generalized framework for adaptive machine learning deployments in algorithmic trading is introduced, tested, and released as open-source code. The presented software aims to test the hypothesis that recent data contains enough information to form a probabilistically favorable short-term price prediction. Further, the framework contains various adaptive machine learning techniques that are geared toward generating profit during strong trends and minimizing losses during trend changes. Results demonstrate that this adaptive machine learning approach is capable of capturing trends and generating profit. The presentation also discusses the importance of defining the parameter space associated with the dynamic training data-set and using the parameter space to identify and remove outliers from prediction data points. Meanwhile, the generalized architecture enables common users to exploit the powerful machinery while focusing on high-level feature engineering and model testing. The presentation also highlights common strengths and weaknesses associated with the presented technique and presents a broad range of well-tested starting points for feature set construction, target setting, and statistical methods for enforcing risk management and maintaining probabilistically favorable entry and exit points. The presentation also describes the end-to-end data processing tools associated with FreqAI, including automatic data fetching, data aggregation, feature engineering, safe and robust data pre-processing, outlier detection, custom machine learning and statistical tools, data post-processing, and adaptive training backtest emulation, and deployment of adaptive training in live environments. Finally, the generalized user interface is also discussed in the presentation. Feature engineering is simplified so that users can seed their feature sets with common indicator libraries (e.g. TA-lib, pandas-ta). The user also feeds data expansion parameters to fill out a large feature set for the model, which can contain as many as 10,000+ features. The presentation describes the various object-oriented programming techniques employed to make FreqAI agnostic to third-party libraries and external data sources. In other words, the back-end is constructed in such a way that users can leverage a broad range of common regression libraries (Catboost, LightGBM, Sklearn, etc) as well as common Neural Network libraries (TensorFlow, PyTorch) without worrying about the logistical complexities associated with data handling and API interactions. The presentation finishes by drawing conclusions about the most important parameters associated with a live deployment of the adaptive learning framework and provides the road map for future development in FreqAI.

Keywords: machine learning, market trend detection, open-source, adaptive learning, parameter space exploration

Procedia PDF Downloads 82
2999 Prediction and Reduction of Cracking Issue in Precision Forging of Engine Valves Using Finite Element Method

Authors: Xi Yang, Bulent Chavdar, Alan Vonseggern, Taylan Altan

Abstract:

Fracture in hot precision forging of engine valves was investigated in this paper. The entire valve forging procedure was described and the possible cause of the fracture was proposed. Finite Element simulation was conducted for the forging process, with commercial Finite Element code DEFORMTM. The effects of material properties, the effect of strain rate and temperature were considered in the FE simulation. Two fracture criteria were discussed and compared, based on the accuracy and reliability of the FE simulation results. The selected criterion predicted the fracture location and shows the trend of damage increasing with good accuracy, which matches the experimental observation. Additional modification of the punch shapes was proposed to further reduce the tendency of fracture in forging. Finite Element comparison shows a great potential of such application in the mass production.

Keywords: hotforging, engine valve, fracture, tooling

Procedia PDF Downloads 274
2998 Effect of Grain Size and Stress Parameters on Ratcheting Behaviour of Two Different Single Phase FCC Metals

Authors: Jayanta Kumar Mahato, Partha Sarathi De, Amrita Kundu, P. C. Chakraborti

Abstract:

Ratcheting is one of the most important phenomena to be considered for design and safety assessment of structural components subjected to stress controlled asymmetric cyclic loading in the elasto-plastic domain. In the present study uniaxial ratcheting behavior of commercially pure annealed OFHC copper and aluminium with two different grain sizes has been investigated. Stress-controlled tests have been conducted at various combinations of stress amplitude and mean stress. These stresses were selected in such a way that the ratio of equivalent stress amplitude (σₐeq) to ultimate tensile strength (σUTS) of the selected materials remains constant. It is found that irrespective of grain size the ratcheting fatigue lives decrease with the increase of both stress amplitude and mean stress following power relationships. However, the effect of stress amplitude on ratcheting lives is observed higher as compared to mean stress for both the FCC metals. It is also found that for both FCC metals ratcheting fatigue lives at a constant ratio of equivalent stress amplitude (σ ₐeq) to ultimate tensile strength (σUTS) are more in case fine grain size. So far ratcheting strain rate is concerned, it decreases rapidly within first few cycles and then a steady state is reached. Finally, the ratcheting strain rate increases up to the complete failure of the specimens due to a very large increase of true stress for a substantial reduction in cross-sectional area. The steady state ratcheting strain rate increases with the increase in both stress amplitude and mean stress. Interestingly, a unique perfectly power relationship between steady state ratcheting strain rate and cycles to failure has been found irrespective of stress combination for both FCC metals. Similar to ratcheting strain rate, the strain energy density decreases rapidly within first few cycles followed by steady state and then increases up to a failure of the specimens irrespective of stress combinations for both FCC metals; but strain energy density at steady state decreases with increase in mean stress and increases with the increase of stress amplitude. From the fractography study, it is found that the void density increases with the increase of maximum stress, but the void size and void density are almost same for any combination of stress parameters considering constant maximum stress.

Keywords: ratcheting phenomena, grain size, stress parameter, ratcheting lives, ratcheting strain rate

Procedia PDF Downloads 288
2997 Application of Smplify-X Algorithm with Enhanced Gender Classifier in 3D Human Pose Estimation

Authors: Jiahe Liu, Hongyang Yu, Miao Luo, Feng Qian

Abstract:

The widespread application of 3D human body reconstruction spans various fields. Smplify-X, an algorithm reliant on single-image input, employs three distinct body parameter templates, necessitating gender classification of individuals within the input image. Researchers employed a ResNet18 network to train a gender classifier within the Smplify-X framework, setting the threshold at 0.9, designating images falling below this threshold as having neutral gender. This model achieved 62.38% accurate predictions and 7.54% incorrect predictions. Our improvement involved refining the MobileNet network, resulting in a raised threshold of 0.97. Consequently, we attained 78.89% accurate predictions and a mere 0.2% incorrect predictions, markedly enhancing prediction precision and enabling more precise 3D human body reconstruction.

Keywords: SMPLX, mobileNet, gender classification, 3D human reconstruction

Procedia PDF Downloads 86
2996 Use of Recycled Aggregates in Current Concretes

Authors: K. Krizova, R. Hela

Abstract:

The paper a summary of the results of concretes with partial substitution of natural aggregates with recycled concrete is solved. Design formulas of the concretes were characterised with 20, 40 and 60% substitution of natural 8-16 mm fraction aggregates with a selected recycled concrete of analogous coarse fractions. With the product samples an evaluation of coarse fraction aggregates influence on fresh concrete consistency and concrete strength in time was carried out. The results of concretes with aggregates substitution will be compared to reference formula containing only the fractions of natural aggregates.

Keywords: recycled concrete, natural aggregates, fresh concrete, properties of concrete

Procedia PDF Downloads 392
2995 Microstructure and Mechanical Properties Evaluation of Graphene-Reinforced AlSi10Mg Matrix Composite Produced by Powder Bed Fusion Process

Authors: Jitendar Kumar Tiwari, Ajay Mandal, N. Sathish, A. K. Srivastava

Abstract:

Since the last decade, graphene achieved great attention toward the progress of multifunction metal matrix composites, which are highly demanded in industries to develop energy-efficient systems. This study covers the two advanced aspects of the latest scientific endeavor, i.e., graphene as reinforcement in metallic materials and additive manufacturing (AM) as a processing technology. Herein, high-quality graphene and AlSi10Mg powder mechanically mixed by very low energy ball milling with 0.1 wt. % and 0.2 wt. % graphene. Mixed powder directly subjected to the powder bed fusion process, i.e., an AM technique to produce composite samples along with bare counterpart. The effects of graphene on porosity, microstructure, and mechanical properties were examined in this study. The volumetric distribution of pores was observed under X-ray computed tomography (CT). On the basis of relative density measurement by X-ray CT, it was observed that porosity increases after graphene addition, and pore morphology also transformed from spherical pores to enlarged flaky pores due to improper melting of composite powder. Furthermore, the microstructure suggests the grain refinement after graphene addition. The columnar grains were able to cross the melt pool boundaries in case of the bare sample, unlike composite samples. The smaller columnar grains were formed in composites due to heterogeneous nucleation by graphene platelets during solidification. The tensile properties get affected due to induced porosity irrespective of graphene reinforcement. The optimized tensile properties were achieved at 0.1 wt. % graphene. The increment in yield strength and ultimate tensile strength was 22% and 10%, respectively, for 0.1 wt. % graphene reinforced sample in comparison to bare counterpart while elongation decreases 20% for the same sample. The hardness indentations were taken mostly on the solid region in order to avoid the collapse of the pores. The hardness of the composite was increased progressively with graphene content. Around 30% of increment in hardness was achieved after the addition of 0.2 wt. % graphene. Therefore, it can be concluded that powder bed fusion can be adopted as a suitable technique to develop graphene reinforced AlSi10Mg composite. Though, some further process modification required to avoid the induced porosity after the addition of graphene, which can be addressed in future work.

Keywords: graphene, hardness, porosity, powder bed fusion, tensile properties

Procedia PDF Downloads 125
2994 Groundwater Recharge Suitability Mapping Using Analytical Hierarchy Process Based-Approach

Authors: Aziza Barrek, Mohamed Haythem Msaddek, Ismail Chenini

Abstract:

Excessive groundwater pumping due to the increasing water demand, especially in the agricultural sector, causes groundwater scarcity. Groundwater recharge is the most important process that contributes to the water's durability. This paper is based on the Analytic Hierarchy Process multicriteria analysis to establish a groundwater recharge susceptibility map. To delineate aquifer suitability for groundwater recharge, eight parameters were used: soil type, land cover, drainage density, lithology, NDVI, slope, transmissivity, and rainfall. The impact of each factor was weighted. This method was applied to the El Fahs plain shallow aquifer. Results suggest that 37% of the aquifer area has very good and good recharge suitability. The results have been validated by the Receiver Operating Characteristics curve. The accuracy of the prediction obtained was 89.3%.

Keywords: AHP, El Fahs aquifer, empirical formula, groundwater recharge zone, remote sensing, semi-arid region

Procedia PDF Downloads 115
2993 Evaluation of the Mechanical Properties of Nano TiO2 and Clay Filler Filled Epoxy Composites

Authors: A. Mimaroglu, H. Unal

Abstract:

In this study, the mechanical properties of nano filled epoxy composites were evaluated. The matrix material is epoxy. nano fillers are Al2O3, TiO2 and clay added in 2.5- 10 wt% by weight ratio. Test samples were prepared using an open mould type die. Mechanical tests were carried out. The tensile strength, elastic modulus, elongation at break and the hardness of the composite materials were obtained and evaluated. It was seen from the results that the filler content had a high influence on the level of the mechanical properties of the epoxy composites.

Keywords: nano, epoxy, composite, fillers, clay

Procedia PDF Downloads 386
2992 General Mathematical Framework for Analysis of Cattle Farm System

Authors: Krzysztof Pomorski

Abstract:

In the given work we present universal mathematical framework for modeling of cattle farm system that can set and validate various hypothesis that can be tested against experimental data. The presented work is preliminary but it is expected to be valid tool for future deeper analysis that can result in new class of prediction methods allowing early detection of cow dieseaes as well as cow performance. Therefore the presented work shall have its meaning in agriculture models and in machine learning as well. It also opens the possibilities for incorporation of certain class of biological models necessary in modeling of cow behavior and farm performance that might include the impact of environment on the farm system. Particular attention is paid to the model of coupled oscillators that it the basic building hypothesis that can construct the model showing certain periodic or quasiperiodic behavior.

Keywords: coupled ordinary differential equations, cattle farm system, numerical methods, stochastic differential equations

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2991 Prediction and Identification of a Permissive Epitope Insertion Site for St Toxoid in cfaB from Enterotoxigenic Escherichia coli

Authors: N. Zeinalzadeh, Mahdi Sadeghi

Abstract:

Enterotoxigenic Escherichia coli (ETEC) is the most common cause of non-inflammatory diarrhea in the developing countries, resulting in approximately 20% of all diarrheal episodes in children in these areas. ST is one of the most important virulence factors and CFA/I is one of the frequent colonization factors that help to process of ETEC infection. ST and CfaB (CFA/I subunit) are among vaccine candidates against ETEC. So, ST because of its small size is not a good immunogenic in the natural form. However to increase its immunogenic potential, here we explored candidate positions for ST insertion in CfaB sequence. After bioinformatics analysis, one of the candidate positions was selected and the chimeric gene (cfaB*st) sequence was synthesized and expressed in E. coli BL21 (DE3). The chimeric recombinant protein was purified with Ni-NTA columns and characterized with western blot analysis. The residue 74-75 of CfaB sequence could be a good candidate position for ST and other epitopes insertion.

Keywords: bioinformatics, CFA/I, enterotoxigenic E. coli, ST toxoid

Procedia PDF Downloads 445
2990 Fabric-Reinforced Cementitious Matrix (FRCM)-Repaired Corroded Reinforced Concrete (RC) Beams under Monotonic and Fatigue Loads

Authors: Mohammed Elghazy, Ahmed El Refai, Usama Ebead, Antonio Nanni

Abstract:

Rehabilitating corrosion-damaged reinforced concrete (RC) structures has been accomplished using various techniques such as steel plating, external post-tensioning, and external bonding of fiber reinforced polymer (FRP) composites. This paper reports on the use of an innovative technique to strengthen corrosion-damaged RC structures using fabric-reinforced cementitious matrix (FRCM) composites. FRCM consists of dry-fiber fabric embedded in cement-based matrix. Twelve large-scale RC beams were constructed and tested in flexural monotonic and fatigue loads. Prior to testing, ten specimens were subjected to accelerated corrosion process for 140 days leading to an average mass loss in the tensile steel bars of 18.8 %. Corrosion was restricted to the main reinforcement located in the middle third of the beam span. Eight corroded specimens were repaired and strengthened while two virgin and two corroded-unrepaired/unstrengthened beams were used as benchmarks for comparison purpose. The test parameters included the FRCM materials (Carbon-FRCM, PBO-FRCM), the number of FRCM plies, the strengthening scheme, and the type of loading (monotonic and fatigue). The effects of the pervious parameters on the flexural response, the mode of failure, and the fatigue life were reported. Test results showed that corrosion reduced the yield and ultimate strength of the beams. The corroded-unrepaired specimen failed to meet the provisions of the ACI-318 code for crack width criteria. The use of FRCM significantly increased the ultimate strength of the corroded specimen by 21% and 65% more than that of the corroded-unrepaired specimen. Corrosion significantly decreased the fatigue life of the corroded-unrepaired beam by 77% of that of the virgin beam. The fatigue life of the FRCM repaired-corroded beams increased to 1.5 to 3.8 times that of the corroded-unrepaired beam but was lower than that of the virgin specimen. The specimens repaired with U-wrapped PBO-FRCM strips showed higher fatigue life than those repaired with the end-anchored bottom strips having similar number of PBO-FRCM-layers. PBO-FRCM was more effective than Carbon-FRCM in restoring the fatigue life of the corroded specimens.

Keywords: corrosion, concrete, fabric-reinforced cementitious matrix (FRCM), fatigue, flexure, repair

Procedia PDF Downloads 292
2989 Evaluation of Modern Natural Language Processing Techniques via Measuring a Company's Public Perception

Authors: Burak Oksuzoglu, Savas Yildirim, Ferhat Kutlu

Abstract:

Opinion mining (OM) is one of the natural language processing (NLP) problems to determine the polarity of opinions, mostly represented on a positive-neutral-negative axis. The data for OM is usually collected from various social media platforms. In an era where social media has considerable control over companies’ futures, it’s worth understanding social media and taking actions accordingly. OM comes to the fore here as the scale of the discussion about companies increases, and it becomes unfeasible to gauge opinion on individual levels. Thus, the companies opt to automize this process by applying machine learning (ML) approaches to their data. For the last two decades, OM or sentiment analysis (SA) has been mainly performed by applying ML classification algorithms such as support vector machines (SVM) and Naïve Bayes to a bag of n-gram representations of textual data. With the advent of deep learning and its apparent success in NLP, traditional methods have become obsolete. Transfer learning paradigm that has been commonly used in computer vision (CV) problems started to shape NLP approaches and language models (LM) lately. This gave a sudden rise to the usage of the pretrained language model (PTM), which contains language representations that are obtained by training it on the large datasets using self-supervised learning objectives. The PTMs are further fine-tuned by a specialized downstream task dataset to produce efficient models for various NLP tasks such as OM, NER (Named-Entity Recognition), Question Answering (QA), and so forth. In this study, the traditional and modern NLP approaches have been evaluated for OM by using a sizable corpus belonging to a large private company containing about 76,000 comments in Turkish: SVM with a bag of n-grams, and two chosen pre-trained models, multilingual universal sentence encoder (MUSE) and bidirectional encoder representations from transformers (BERT). The MUSE model is a multilingual model that supports 16 languages, including Turkish, and it is based on convolutional neural networks. The BERT is a monolingual model in our case and transformers-based neural networks. It uses a masked language model and next sentence prediction tasks that allow the bidirectional training of the transformers. During the training phase of the architecture, pre-processing operations such as morphological parsing, stemming, and spelling correction was not used since the experiments showed that their contribution to the model performance was found insignificant even though Turkish is a highly agglutinative and inflective language. The results show that usage of deep learning methods with pre-trained models and fine-tuning achieve about 11% improvement over SVM for OM. The BERT model achieved around 94% prediction accuracy while the MUSE model achieved around 88% and SVM did around 83%. The MUSE multilingual model shows better results than SVM, but it still performs worse than the monolingual BERT model.

Keywords: BERT, MUSE, opinion mining, pretrained language model, SVM, Turkish

Procedia PDF Downloads 137
2988 Simulation the Stress Distribution of Wheel/Rail at Contact Region

Authors: Norie A. Akeel, Z. Sajuri, A. K. Ariffin

Abstract:

This paper discusses the effect of different loading analysis on crack initiation life of wheel/rail in the contact region. A simulated three dimensional (3D) elasto plastic model of a wheel/rail contact is modeled using the fine mesh technique in the contact region by using Finite Element Method FEM code ANSYS 11.0 software. Different loads of approximately from 70 to 140 KN was applied on the wheel tread through the running surface on the railhead surface to simulate stress distribution (Von Mises) and a life prediction of the crack initiation under rolling contact motion. Stress analysis is achieved and the fatigue life to the rail head surface is calculated numerically by using a multi-axial fatigue life of crack initiation model. All results obtained from the previous researches are compared with this research.

Keywords: FEM, rolling contact, rail track, stress distribution, fatigue life

Procedia PDF Downloads 550
2987 Study of Biocomposites Based of Poly(Lactic Acid) and Olive Husk Flour

Authors: Samra Isadounene, Amar Boukerrou, Dalila Hammiche

Abstract:

In this work, the composites were prepared with poly(lactic acid) (PLA) and olive husk flour (OHF) with different percentages (10, 20 and 30%) using extrusion method followed by injection molding. The morphological, mechanical properties and thermal behavior of composites were investigated. Tensile strength and elongation at break of composites showed a decreasing trend with increasing fiber content. On the other hand, Young modulus and storage modulus were increased. The addition of OHF resulted in a decrease in thermal stability of composites. The presence of OHF led to an increase in percentage of crystallinity (Xc) of PLA matrix.

Keywords: biopolymers, composites, mechanical properties, poly(lactic acid)

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2986 Studying the Effect of Nanoclays on the Mechanical Properties of Polypropylene/Polyamide Nanocomposites

Authors: Benalia Kouini, Aicha Serier

Abstract:

Nanocomposites based on polypropylene/polyamide 66 (PP/PA66) nanoblends containing organophilic montmorillonite (OMMT) and maleic anhydride grafted polypropylene (PP-g-MAH) were prepared by melt compounding method followed by injection molding. Two different types of nanoclays were used in this work. DELLITE LVF is the untreated nanoclay and DELLITE 67G is the treated one. The morphology of the nanocomposites was studied using the XR diffraction (XRD). The results indicate that the incorporation of treated nanoclay has a significant effect on the impact strength of PP/PA66 nanocomposites. Furthermore, it was found that XRD results revealed the intercalation, exfoliation of nanaclays of nanocomposites.

Keywords: nNanoclay, Nanocomposites, Polypropylene, Polyamide, melt processing, mechanical properties.

Procedia PDF Downloads 348
2985 Response Surface Methodology for Optimum Hardness of TiN on Steel Substrate

Authors: R. Joseph Raviselvan, K. Ramanathan, P. Perumal, M. R. Thansekhar

Abstract:

Hard coatings are widely used in cutting and forming tool industries. Titanium Nitride (TiN) possesses good hardness, strength and corrosion resistant. The coating properties are influenced by many process parameters. The coatings were deposited on steel substrate by changing the process parameters such as substrate temperature, nitrogen flow rate and target power in a D.C planer magnetron sputtering. The structure of coatings were analysed using XRD. The hardness of coatings was found using Micro hardness tester. From the experimental data, a regression model was developed and the optimum response was determined using Response Surface Methodology (RSM).

Keywords: hardness, RSM, sputtering, TiN XRD

Procedia PDF Downloads 317
2984 Performance Analysis of Wireless Sensor Networks in Areas for Sports Activities and Environmental Preservation

Authors: Teles de Sales Bezerra, Saulo Aislan da Silva Eleuterio, José Anderson Rodrigues de Souza, Ítalo de Pontes Oliveira

Abstract:

This paper presents a analysis of performance the Received Strength Signal Indicator (RSSI) to Wireless Sensor Networks, with a finality of investigate a behavior of ZigBee devices operating into real environments. The test of performance was realize using two Series 1 ZigBee Module and two modules of development Arduino Uno R3, evaluating in this form a measurements of RSSI into environments like places of sports, preservation forests and water reservoir.

Keywords: wireless sensor networks, RSSI, Arduino, environments

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2983 Numerical Static and Seismic Evaluation of Pile Group Settlement: A Case Study

Authors: Seyed Abolhassan Naeini, Hamed Yekehdehghan

Abstract:

Shallow foundations cannot be used when the bedding soil is soft. A suitable method for constructing foundations on soft soil is to employ pile groups to transfer the load to the bottom layers. The present research used results from tests carried out in northern Iran (Langarud) and the FLAC3D software to model a pile group for investigating the effects of various parameters on pile cap settlement under static and seismic conditions. According to the results, changes in the strength parameters of the soil, groundwater level, and the length of and distance between the piles affect settlement differently.

Keywords: FLACD 3D software, pile group, settlement, soil

Procedia PDF Downloads 123
2982 Comparative Analysis of Hybrid Dynamic Stabilization and Fusion for Degenerative Disease of the Lumbosacral Spine: Finite Element Analysis

Authors: Mohamed Bendoukha, Mustapha Mosbah

Abstract:

The Radiographic apparent assumed that the asymptomatic adjacent segment disease ASD is common after lumbar fusion, but this does not correlate with the functional outcomes while compensatory increased motion and stresses at the adjacent level of fusion is well-known to be associated to ASD. Newly developed, the hybrid stabilization are allocated to substituted for mostly the superior level of the fusion in an attempt to reduce the number of fusion levels and likelihood of degeneration process at the adjacent levels during the fusion with pedicle screws. Nevertheless, its biomechanical efficiencies still remain unknown and complications associated with failure of constructs such screw loosening and toggling should be elucidated In the current study, a finite element (FE) study was performed using a validated L2/S1 model subjected to a moment of 7.5 Nm and follower load of 400 N to assess the biomedical behavior of hybrid constructs based on dynamic topping off, semi rigid fusion. The residual range of motion (ROM), stress distribution at the fused and adjacent levels, stress distribution at the disc and the cage-endplate interface with respect to changes of bone quality were investigated. The hybrid instrumentation was associated with a reduction in compressive stresses compared to the fusion construct in the adjacent-level disc and showed high substantial axial force in the implant while fusion instrumentation increased the motion for both flexion and extension.

Keywords: intervertebral disc, lumbar spine, degenerative nuclesion, L4-L5, range of motion finite element model, hyperelasticy

Procedia PDF Downloads 183
2981 Hydrothermal Aging Behavior of Continuous Carbon Fiber Reinforced Polyamide 6 Composites

Authors: Jifeng Zhang , Yongpeng Lei

Abstract:

Continuous carbon fiber reinforced polyamide 6 (CF/PA6) composites are potential for application in the automotive industry due to their high specific strength and stiffness. However, PA6 resin is sensitive to the moisture in the hydrothermal environment and CF/PA6 composites might undergo several physical and chemical changes, such as plasticization, swelling, and hydrolysis, which induces a reduction of mechanical properties. So far, little research has been reported on the assessment of the effects of hydrothermal aging on the mechanical properties of continuous CF/PA6 composite. This study deals with the effects of hydrothermal aging on moisture absorption and mechanical properties of polyamide 6 (PA6) and polyamide 6 reinforced with continuous carbon fibers composites (CF/PA6) by immersion in distilled water at 30 ℃, 50 ℃, 70 ℃, and 90 ℃. Degradation of mechanical performance has been monitored, depending on the water absorption content and the aging temperature. The experimental results reveal that under the same aging condition, the PA6 resin absorbs more water than the CF/PA6 composite, while the water diffusion coefficient of CF/PA6 composite is higher than that of PA6 resin because of interfacial diffusion channel. In mechanical properties degradation process, an exponential reduction in tensile strength and elastic modulus are observed in PA6 resin as aging temperature and water absorption content increases. The degradation trend of flexural properties of CF/PA6 is the same as that of tensile properties of PA6 resin. Moreover, the water content plays a decisive role in mechanical degradation compared with aging temperature. In contrast, hydrothermal environment has mild effect on the tensile properties of CF/PA6 composites. The elongation at breakage of PA6 resin and CF/PA6 reaches the highest value when their water content reaches 6% and 4%, respectively. Dynamic mechanical analysis (DMA) and scanning electron microscope (SEM) were also used to explain the mechanism of mechanical properties alteration. After exposed to the hydrothermal environment, the Tg (glass transition temperature) of samples decreases dramatically with water content increase. This reduction can be ascribed to the plasticization effect of water. For the unaged specimens, the fibers surface is coated with resin and the main fracture mode is fiber breakage, indicating that a good adhesion between fiber and matrix. However, with absorbed water content increasing, the fracture mode transforms to fiber pullout. Finally, based on Arrhenius methodology, a predictive model with relate to the temperature and water content has been presented to estimate the retention of mechanical properties for PA6 and CF/PA6.

Keywords: continuous carbon fiber reinforced polyamide 6 composite, hydrothermal aging, Arrhenius methodology, interface

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2980 Iraq Water Resources Planning: Perspectives and Prognoses

Authors: Nadhir Al-Ansari, Ammar A. Ali, Sven Knutsson

Abstract:

Iraq is located in the Middle East. It covers an area of 433,970 square kilometres populated by about 32 million inhabitants. Iraq greatly relies in its water resources on the Tigris and Euphrates Rivers. Recently, Iraq is suffering from water shortage problems. This is due to external and internal factors. The former includes global warming and water resources policies of neighbouring countries while the latter includes mismanagement of its water resources. The supply and demand are predicted to be 43 and 66.8 Billion Cubic Meters (BCM) respectively in 2015, while in 2025 it will be 17.61 and 77 BCM respectively. In addition, future prediction suggests that Tigris and Euphrates Rivers will be completely dry in 2040. To overcome this problem, prudent water management policies are to be adopted. This includes Strategic Water Management Vision, development of irrigation techniques, reduction of water losses, use of non-conventional water resources and research and development planning.

Keywords: Iraq, Tigris River, Euphrates River, water scarcity, water resources management

Procedia PDF Downloads 444
2979 The Twin Terminal of Pedestrian Trajectory Based on City Intelligent Model (CIM) 4.0

Authors: Chen Xi, Liu Xuebing, Lao Xueru, Kuan Sinman, Jiang Yike, Wang Hanwei, Yang Xiaolang, Zhou Junjie, Xie Jinpeng

Abstract:

To further promote the development of smart cities, the microscopic "nerve endings" of the City Intelligent Model (CIM) are extended to be more sensitive. In this paper, we develop a pedestrian trajectory twin terminal based on the CIM and CNN technology. It also uses 5G networks, architectural and geoinformatics technologies, convolutional neural networks, combined with deep learning networks for human behavior recognition models, to provide empirical data such as 'pedestrian flow data and human behavioral characteristics data', and ultimately form spatial performance evaluation criteria and spatial performance warning systems, to make the empirical data accurate and intelligent for prediction and decision making.

Keywords: urban planning, urban governance, CIM, artificial intelligence, sustainable development

Procedia PDF Downloads 406
2978 Creatine Associated with Resistance Training Increases Muscle Mass in the Elderly

Authors: Camila Lemos Pinto, Juliana Alves Carneiro, Patrícia Borges Botelho, João Felipe Mota

Abstract:

Sarcopenia, a syndrome characterized by progressive and generalized loss of skeletal muscle mass and strength, currently affects over 50 million people and increases the risk of adverse outcomes such as physical disability, poor quality of life and death. The aim of this study was to examine the efficacy of creatine supplementation associated with resistance training on muscle mass in the elderly. A 12-week, double blind, randomized, parallel group, placebo controlled trial was conducted. Participants were randomly allocated into one of the following groups: placebo with resistance training (PL+RT, n=14) and creatine supplementation with resistance training (CR + RT, n=13). The subjects from CR+RT group received 5 g/day of creatine monohydrate and the subjects from the PL+RT group were given the same dose of maltodextrin. Participants were instructed to ingest the supplement on non-training days immediately after lunch and on training days immediately after resistance training sessions dissolved in a beverage comprising 100 g of maltodextrin lemon flavored. Participants of both groups undertook a supervised exercise training program for 12 weeks (3 times per week). The subjects were assessed at baseline and after 12 weeks. The primary outcome was muscle mass, assessed by dual energy X-ray absorptiometry (DXA). The secondary outcome included diagnose participants with one of the three stages of sarcopenia (presarcopenia, sarcopenia and severe sarcopenia) by skeletal muscle mass index (SMI), handgrip strength and gait speed. CR+RT group had a significant increase in SMI and muscle (p<0.0001), a significant decrease in android and gynoid fat (p = 0.028 and p=0.035, respectively) and a tendency of decreasing in body fat (p=0.053) after the intervention. PL+RT only had a significant increase in SMI (p=0.007). The main finding of this clinical trial indicated that creatine supplementation combined with resistance training was capable of increasing muscle mass in our elderly cohort (p=0.02). In addition, the number of subjects diagnosed with one of the three stages of sarcopenia at baseline decreased in the creatine supplemented group in comparison with the placebo group (CR+RT, n=-3; PL+RT, n=0). In summary, 12 weeks of creatine supplementation associated with resistance training resulted in increases in muscle mass. This is the first research with elderly of both sexes that show the same increase in muscle mass with a minor quantity of creatine supplementation in a short period. Future long-term research should investigate the effects of these interventions in sarcopenic elderly.

Keywords: creatine, dietetic supplement, elderly, resistance training

Procedia PDF Downloads 470
2977 Heart Failure Identification and Progression by Classifying Cardiac Patients

Authors: Muhammad Saqlain, Nazar Abbas Saqib, Muazzam A. Khan

Abstract:

Heart Failure (HF) has become the major health problem in our society. The prevalence of HF has increased as the patient’s ages and it is the major cause of the high mortality rate in adults. A successful identification and progression of HF can be helpful to reduce the individual and social burden from this syndrome. In this study, we use a real data set of cardiac patients to propose a classification model for the identification and progression of HF. The data set has divided into three age groups, namely young, adult, and old and then each age group have further classified into four classes according to patient’s current physical condition. Contemporary Data Mining classification algorithms have been applied to each individual class of every age group to identify the HF. Decision Tree (DT) gives the highest accuracy of 90% and outperform all other algorithms. Our model accurately diagnoses different stages of HF for each age group and it can be very useful for the early prediction of HF.

Keywords: decision tree, heart failure, data mining, classification model

Procedia PDF Downloads 398
2976 Studying Projection Distance and Flow Properties by Shape Variations of Foam Monitor

Authors: Hyun-Kyu Cho, Jun-Su Kim, Choon-Geun Huh, Geon Lee Young-Chul Park

Abstract:

In this study, the relationship between flow properties and fluid projection distance look into connection for shape variations of foam monitor. A numerical analysis technique for fluid analysis of a foam monitor was developed for the prediction. Shape of foam monitor the flow path of fluid flow according to the shape, The fluid losses were calculated from flow analysis result.. The modified model used the length increase model of the flow path, and straight line of the model. Inlet pressure was 7 [bar] and external was atmosphere codition. am. The results showed that the length increase model of the flow path and straight line of the model was improved in the nozzle projection distance.

Keywords: injection performance, finite element method, foam monitor, Projection distance

Procedia PDF Downloads 341