Search results for: strength prediction

Authors: Yongyu Duo, Xiaogang Liu, Qingrui Yue

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The anchor plays a critical role in the utilization of the tensile strength of carbon fiber-reinforced polymer (CFRP) plate when it is applied for the prestressed retrofitted and cable structures. In this paper, the anchor behavior of planar clamping anchor (PCA) under different interface treatment forms and normal pressures was investigated by the uniaxial static tensile test. Two interface treatment forms were adopted, including pure friction and the coupling action of friction and bonding. The results indicated that the load-bearing capacity of PCA could be obviously improved by the coupling action of friction and bonding compared with the action of pure friction. Under the normal pressure of 11 MPa, 22 MPa, and 33 MPa, the load-bearing capacity of PCA was enhanced by 164.61%, 68.40%, and 52.78%, respectively, and the tensile strength of the CFRP plate was fully exploited when the normal pressure reached 44 MPa. In addition, the experimental coefficient of static friction between the galling CFRP plate and a sandblasted steel plate was in the range of 0.28-0.30, corresponding to various normal pressure. Moreover, the failure mode was determined by the interface treatment form and normal pressure. The research in this paper has important guiding significance to optimize the design of the mechanical clamping anchor, contributing to promoting the application of CFRP plate in reinforcement and cable structure.

Keywords: PCA, CFRP plate, interface treatment form, normal pressure, friction, coupling action

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Authors: Sanela Slavkovic, Congor Nad, Spela Golubovic

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Background: The diagnosis of multiple sclerosis (MS) is a major life challenge and has repercussions on all aspects of the daily functioning of those attained by it – personal activities, social participation, and quality of life. Regular follow-up of only the neurological status is not informative enough so that it could provide data on the sort of support and rehabilitation that is required. Objective: The aim of this study was to establish the current level of functioning of persons attained by MS and the factors that influence it. Methods: The study was conducted in Serbia, on a sample of 108 persons with relapse-remitting form of MS, aged 20 to 53 (mean 39.86 years; SD 8.20 years). All participants were fully ambulatory. Methods applied in the study include Expanded Disability Status Scale-EDSS and World Health Organization Disability Assessment Schedule, WHODAS 2.0 (36-item version, self-administered). Results: Participants were found to experience the most problems in the domains of Participation, Mobility, Life activities and Cognition. The least difficulties were found in the domain of Self-care. Symptom duration was the only control variable with a significant partial contribution to the prediction of the WHODAS scale score (β=0.30, p < 0.05). The total EDSS score correlated with the total WHODAS 2.0 score (r=0.34, p=0.00). Statistically significant differences in the domain of EDSS 0-5.5 were found within categories (0-1.5; 2-3.5; 4-5.5). The more pronounced a participant’s EDSS score was, although not indicative of large changes in the neurological status, the more apparent the changes in the functional domain, i.e. in all areas covered by WHODAS 2.0. Pyramidal (β=0.34, p < 0.05) and Bowel and bladder (β=0.24, p < 0.05) functional systems were found to have a significant partial contribution to the prediction of the WHODAS score. Conclusion: Measuring functioning and disability is important in the follow-up of persons suffering from MS in order to plan rehabilitation and define areas in which additional support is needed.

Keywords: disability, functionality, multiple sclerosis, rehabilitation

Procedia PDF Downloads 103

Authors: Krishnaiah Arkanti, Ramulu Malothu

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The experiments have been conducted to study the mechanical properties of commercially pure copper processing at room temperature by severe plastic deformation using equal channel angular extrusion (ECAE) through a die of 90^oangle up to 3 passes by route B_C i.e. rotating the sample in the same direction by 90^o after each pass. ECAE is used to produce from existing coarse grains to ultra-fine, equiaxed grains structure with high angle grain boundaries in submicron level by introducing a large amount of shear strain in the presence of hydrostatic pressure into the material without changing billet shape or dimension. Mechanical testing plays an important role in evaluating fundamental properties of engineering materials as well as in developing new materials and in controlling the quality of materials for use in design and construction. Yield stress, ultimate tensile stress and ductility are structure sensitive properties and vary with the structure of the material. Microhardness and tensile tests were carried out to evaluate the hardness, strength and ductility of the ECAE processed materials. The results reveal that the strength and hardness of commercially pure copper samples improved significantly without losing much ductility after each pass.

Keywords: equal channel angular extrusion, severe plastic deformation, copper, mechanical properties

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Authors: Camila Hurtado, Maria A. Morales, Diego Torres, L.H. Reyes, Alejandro Maranon, Alicia Porras

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This work presents the physical and chemical characterization of beer brand fibers and the properties of novel composite materials made of these fibers and polylactic acid (PLA). Treated and untreated fibers were physically characterized in terms of their moisture content (ASTM D1348), density, and particle size (ASAE S319.2). A chemical analysis following TAPPI standards was performed to determine ash, extractives, lignin, and cellulose content on fibers. Thermal stability was determined by TGA analysis, and an FTIR was carried out to check the influence of the alkali treatment in fiber composition. An alkali treatment with NaOH (5%) of fibers was performed for 90 min, with the objective to improve the interfacial adhesion with polymeric matrix in composites. Composite materials based on either treated or untreated beer brand fibers and polylactic acid (PLA) were developed characterized in tension (ASTM D638), bending (ASTM D790) and impact (ASTM D256). Before composites manufacturing, PLA and brand beer fibers (10 wt.%) were mixed in a twin extruder with a temperature profile between 155°C and 180°C. Coupons were manufactured by compression molding (110 bar) at 190°C. Physical characterization showed that alkali treatment does not affect the moisture content (6.9%) and the density (0.48 g/cm³ for untreated fiber and 0.46 g/cm³ for the treated one). Chemical and FTIR analysis showed a slight decrease in ash and extractives. Also, a decrease of 47% and 50% for lignin and hemicellulose content was observed, coupled with an increase of 71% for cellulose content. Fiber thermal stability was improved with the alkali treatment at about 10°C. Tensile strength of composites was found to be between 42 and 44 MPa with no significant statistical difference between coupons with either treated or untreated fibers. However, compared to neat PLA, composites with beer bran fibers present a decrease in tensile strength of 27%. Young modulus increases by 10% with treated fiber, compared to neat PLA. Flexural strength decreases in coupons with treated fiber (67.7 MPa), while flexural modulus increases (3.2 GPa) compared to neat PLA (83.3 MPa and 2.8 GPa, respectively). Izod impact test results showed an improvement of 99.4% in coupons with treated fibers - compared with neat PLA.

Keywords: beer bran, characterization, green composite, polylactic acid, surface treatment

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Authors: Etienne Gaborit, Dorothy Durnford, Daniel Deacu, Marco Carrera, Nathalie Gauthier, Camille Garnaud, Vincent Fortin

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A new experimental streamflow forecasting system was recently implemented at the Environment and Climate Change Canada’s (ECCC) Canadian Centre for Meteorological and Environmental Prediction (CCMEP). It relies on CaLDAS (Canadian Land Data Assimilation System) for the assimilation of surface variables, and on a surface prediction system that feeds a routing component. The surface energy and water budgets are simulated with the SVS (Soil, Vegetation, and Snow) Land-Surface Scheme (LSS) at 2.5-km grid spacing over Canada. The routing component is based on the Watroute routing scheme at 1-km grid spacing for the Great Lakes and Nelson River watersheds. The system is run in two distinct phases: an analysis part and a forecast part. During the analysis part, CaLDAS outputs are used to force the routing system, which performs streamflow assimilation. In forecast mode, the surface component is forced with the Canadian GEM atmospheric forecasts and is initialized with a CaLDAS analysis. Streamflow performances of this new system are presented over 2019. Performances are compared to the current ECCC’s operational streamflow forecasting system, which is different from the new experimental system in many aspects. These new streamflow forecasts are also compared to persistence. Overall, the new streamflow forecasting system presents promising results, highlighting the need for an elaborated assimilation phase before performing the forecasts. However, the system is still experimental and is continuously being improved. Some major recent improvements are presented here and include, for example, the assimilation of snow cover data from remote sensing, a backward propagation of assimilated flow observations, a new numerical scheme for the routing component, and a new reservoir model.

Keywords: assimilation system, distributed physical model, offline hydro-meteorological chain, short-term streamflow forecasts

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Authors: Aya Belal, Ahmed Maher Eltair, Maggie Ahmed Mashaly

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Geopolymer concrete is gaining recognition as a sustainable alternative to conventional Portland Cement concrete due to its environmentally friendly nature, which is a key goal for Smart City initiatives. It has demonstrated its potential as a reliable material for the design of structural elements. However, the production of Geopolymer concrete is hindered by batch-to-batch variations, which presents a significant challenge to the widespread adoption of Geopolymer concrete. To date, Machine learning has had a profound impact on various fields by enabling models to learn from large datasets and predict outputs accurately. This paper proposes an integration between the current drift to Artificial Intelligence and the composition of Geopolymer mixtures to predict their mechanical properties. This study employs Python software to develop machine learning model in specific Decision Trees. The research uses the percentage oxides and the chemical composition of the Alkali Solution along with the curing conditions as the input independent parameters, irrespective of the waste products used in the mixture yielding the compressive strength of the mix as the output parameter. The results showed 90 % agreement of the predicted values to the actual values having the ratio of the Sodium Silicate to the Sodium Hydroxide solution being the dominant parameter in the mixture.

Keywords: decision trees, geopolymer concrete, machine learning, smart cities, sustainability

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Authors: Hassan Gomar, Shahin Bagheri, Nader Keyvan, Mozhdeh Shirinzadeh

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Air-Cooled Condenser (ACC) platform structures are the most complicated and principal structures in power plants and other industrial parts which need to condense the low-pressure steam in the cycle. Providing large spans for this structure has great merit as there would be more space for other subordinate buildings and pertinent equipment. Moreover, applying methods to reduce the overall cost of construction while maintaining its strength against severe seismic loading is of high significance. Tabular spatial structures and composite frames have been widely used in recent years to satisfy the need for higher strength at a reasonable price. In this research program, three different structural systems have been regarded for ACC steel platform using Special Concentrate Braced Frames (SCBF), which is the most common system (first scheme), modular spatial frames (second scheme) and finally, a modified method applying Concrete Filled Steel Tabular (CFST) columns (third scheme). The finite element method using Sap2000 and Etabs software was conducted to investigate the behavior of the structures and make a precise comparison between the models. According to the results, the total weight of the steel structure in the second scheme decreases by 13% compared to the first scheme and applying CFST columns in the third scheme causes a 3% reduction in the total weight of the structure in comparison with the second scheme while all the lateral displacements and P-M interaction ratios are in the admissible limit.

Keywords: ACC, SCBF frames, spatial structures, CFST frames

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Authors: K. Almi, S.Lakel, A. Benchabane, A. Kriker

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The fiber–matrix compatibility can be improved if suitable enforcements are chosen. Whenever the reinforcements have more thermal stability, they can resist to the main processes for wood–thermoplastic composites. This paper is an investigation of effect of different treatment process on the mechanical proprieties and on the thermal stability of date palm leaflets fibers with a view to improve the date palm fiber proprieties used as reinforcement of thermoplastic materials which main processes require extrusion, hot press. To compare the effect of alkali and acid treatment on the date palm leaflets fiber properties, different treatment were used such as Sodium hydroxide NaOH solution, aluminium chloride AlCl3 and acid treatment with HCL solution. All treatments were performed at 70°C for 4h and 48 h. The mechanical performance (tensile strength and elongation) is affected by immersion time in alkaline and acid solutions. The reduction of the tensile strength and elongation of fibers at 48h was higher in acid treatment than in alkali treatment at high concentration. No significant differences were observed in mechanical and thermal proprieties of raw fibers and fibers submerged in AlCl3 at low concentration 1% for 48h. Fibers treated by NaOH at 6% for 4h showed significant increase in the mechanical proprieties and thermal stability of date palm leaflets fibers. Hence, soda treatment is necessary to improve the fibers proprieties and consequently optimize the composite performance.

Keywords: date palm fibers, surface treatments, thermoplastic composites, thermal analysis

Procedia PDF Downloads 328

Authors: Xiaomin Zhong, Alexander Pate, Ya-Ting Yang, Ali Fahmi, Darren M. Ashcroft, Ben Goldacre, Brian Mackenna, Amir Mehrkar, Sebastian C. J. Bacon, Jon Massey, Louis Fisher, Peter Inglesby, Kieran Hand, Tjeerd van Staa, Victoria Palin

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Background: This study aimed to predict risks of potentially inappropriate antibiotic type and repeat prescribing and assess changes during COVID-19. Methods: With the approval of NHS England, we used the OpenSAFELY platform to access the TPP SystmOne electronic health record (EHR) system and selected patients prescribed antibiotics from 2019 to 2021. Multinomial logistic regression models predicted the patient’s probability of receiving an inappropriate antibiotic type or repeating the antibiotic course for each common infection. Findings: The population included 9.1 million patients with 29.2 million antibiotic prescriptions. 29.1% of prescriptions were identified as repeat prescribing. Those with same-day incident infection coded in the EHR had considerably lower rates of repeat prescribing (18.0%), and 8.6% had a potentially inappropriate type. No major changes in the rates of repeat antibiotic prescribing during COVID-19 were found. In the ten risk prediction models, good levels of calibration and moderate levels of discrimination were found. Important predictors included age, prior antibiotic prescribing, and region. Patients varied in their predicted risks. For sore throat, the range from 2.5 to 97.5th percentile was 2.7 to 23.5% (inappropriate type) and 6.0 to 27.2% (repeat prescription). For otitis externa, these numbers were 25.9 to 63.9% and 8.5 to 37.1%, respectively. Interpretation: Our study found no evidence of changes in the level of inappropriate or repeat antibiotic prescribing after the start of COVID-19. Repeat antibiotic prescribing was frequent and varied according to regional and patient characteristics. There is a need for treatment guidelines to be developed around antibiotic failure and clinicians provided with individualised patient information.

Keywords: antibiotics, infection, COVID-19 pandemic, antibiotic stewardship, primary care

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Authors: Fatih Kılıç, Burak Birol, Necmettin Maraşlı

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The directional solidification process is generally used for homogeneous compound production, single crystal growth, and refining (zone refining), etc. processes. The most important two parameters that control eutectic structures are temperature gradient and grain growth rate which are called as solidification parameters The solidification behavior and microstructure characteristics is an interesting topic due to their effects on the properties and performance of the alloys containing eutectic compositions. The solidification behavior of multicomponent and multiphase systems is an important parameter for determining various properties of these materials. The researches have been conducted mostly on the solidification of pure materials or alloys containing two phases. However, there are very few studies on the literature about multiphase reactions and microstructure formation of multicomponent alloys during solidification. Because of this situation, it is important to study the microstructure formation and the thermodynamical, thermophysical and microstructural properties of these alloys. The production process is difficult due to easy oxidation of magnesium and therefore, there is not a comprehensive study concerning alloys containing high Mg (> 30 wt.% Mg). With the increasing amount of Mg inside Al alloys, the specific weight decreases, and the strength shows a slight increase, while due to formation of β-Al8Mg5 phase, ductility lowers. For this reason, production, examination and development of high Mg containing alloys will initiate the production of new advanced engineering materials. The original value of this research can be described as obtaining high Mg containing (> 30% Mg) Al based multicomponent alloys by melting under vacuum; controlled directional solidification with various growth rates at a constant temperature gradient; and establishing relationship between solidification rate and microstructural, mechanical, electrical and thermal properties. Therefore, within the scope of this research, some > 30% Mg containing ternary or quaternary Al alloy compositions were determined, and it was planned to investigate the effects of directional solidification rate on the mechanical, electrical and thermal properties of these alloys. Within the scope of the research, the influence of the growth rate on microstructure parameters, microhardness, tensile strength, electrical conductivity and thermal conductivity of directionally solidified high Mg containing Al-32,2Mg-0,37Si; Al-30Mg-12Zn; Al-32Mg-1,7Ni; Al-32,2Mg-0,37Fe; Al-32Mg-1,7Ni-0,4Si; Al-33,3Mg-0,35Si-0,11Fe (wt.%) alloys with wide range of growth rate (50-2500 µm/s) and fixed temperature gradient, will be investigated. The work can be planned as; (a) directional solidification of Al-Mg based Al-Mg-Si, Al-Mg-Zn, Al-Mg-Ni, Al-Mg-Fe, Al-Mg-Ni-Si, Al-Mg-Si-Fe within wide range of growth rates (50-2500 µm/s) at a constant temperature gradient by Bridgman type solidification system, (b) analysis of microstructure parameters of directionally solidified alloys by using an optical light microscopy and Scanning Electron Microscopy (SEM), (c) measurement of microhardness and tensile strength of directionally solidified alloys, (d) measurement of electrical conductivity by four point probe technique at room temperature (e) measurement of thermal conductivity by linear heat flow method at room temperature.

Keywords: directional solidification, electrical conductivity, high Mg containing multicomponent Al alloys, microhardness, microstructure, tensile strength, thermal conductivity

Procedia PDF Downloads 246

Authors: Nameer A. Alwash, Dunia A. Abd AlRadha, Arshed M. Aljanaby

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This study present an experimental investigation of composite behavior for hybrid reinforced concrete slab on girder from locale material in Iraq, ordinary concrete, NC, in slab and reactive powder concrete in girder ,RPC, with steel fibers of different types(straight, hook, and mix between its), tested as simply supported span subjected under two point loading, also study effects on overall behavior such as the ultimate load, crack width and deflection. The result shows that the most suitable for production girder from RPC by using 2% micro straight steel fiber, in terms of ultimate strength and min crack width. Also the results shows that using RPC in girder of composite section increased ultimate load by 79% when compared with same section made of NC, and increased the shear strength which erased the effect of changing reinforcement in shear, and using RPC in girder and epoxy (in shear transfer between composite section) (meaning no stirrups) equivalent presence of shear reinforcement by 90% when compared with same section using Φ8@100 as shear reinforcement. And the result shows that changing the cross section girder shape of the composite section to inverted T, with same section area, increased the ultimate load by 5% when compared with same section of rectangular shape girder.

Keywords: reactive powder concrete, RPC, hybrid concrete, composite section, RC girder, RC slab, shear connecters, inverted T section, shear reinforcment, shear span over effective depth

Procedia PDF Downloads 346

Authors: Dongping Fang, Lian Duan, Xiaojing Yuan, Mike Xu, Allyn Klunder, Kevin Tan, Suiting Cao, Yeqing Ji

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Accurate prediction of a medical condition with straight clinical evidence is a long-sought topic in the medical management and health insurance field. Although great progress has been made with machine learning algorithms, the medical community is still, to a certain degree, suspicious about the model's accuracy and interpretability. This paper presents an innovative hierarchical attention deep learning model to achieve good prediction and clear interpretability that can be easily understood by medical professionals. This deep learning model uses a hierarchical attention structure that matches naturally with the medical history data structure and reflects the member’s encounter (date of service) sequence. The model attention structure consists of 3 levels: (1) attention on the medical code types (diagnosis codes, procedure codes, lab test results, and prescription drugs), (2) attention on the sequential medical encounters within a type, (3) attention on the medical codes within an encounter and type. This model is applied to predict the occurrence of stage 3 chronic kidney disease (CKD3), using three years’ medical history of Medicare Advantage (MA) members from a top health insurance company. The model takes members’ medical events, both claims and electronic medical record (EMR) data, as input, makes a prediction of CKD3 and calculates the contribution from individual events to the predicted outcome. The model outcome can be easily explained with the clinical evidence identified by the model algorithm. Here are examples: Member A had 36 medical encounters in the past three years: multiple office visits, lab tests and medications. The model predicts member A has a high risk of CKD3 with the following well-contributed clinical events - multiple high ‘Creatinine in Serum or Plasma’ tests and multiple low kidneys functioning ‘Glomerular filtration rate’ tests. Among the abnormal lab tests, more recent results contributed more to the prediction. The model also indicates regular office visits, no abnormal findings of medical examinations, and taking proper medications decreased the CKD3 risk. Member B had 104 medical encounters in the past 3 years and was predicted to have a low risk of CKD3, because the model didn’t identify diagnoses, procedures, or medications related to kidney disease, and many lab test results, including ‘Glomerular filtration rate’ were within the normal range. The model accurately predicts members A and B and provides interpretable clinical evidence that is validated by clinicians. Without extra effort, the interpretation is generated directly from the model and presented together with the occurrence date. Our model uses the medical data in its most raw format without any further data aggregation, transformation, or mapping. This greatly simplifies the data preparation process, mitigates the chance for error and eliminates post-modeling work needed for traditional model explanation. To our knowledge, this is the first paper on an interpretable deep-learning model using a 3-level attention structure, sourcing both EMR and claim data, including all 4 types of medical data, on the entire Medicare population of a big insurance company, and more importantly, directly generating model interpretation to support user decision. In the future, we plan to enrich the model input by adding patients’ demographics and information from free-texted physician notes.

Keywords: deep learning, interpretability, attention, big data, medical conditions

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Authors: Panaya Sudta, Wanchalerm Patanacharoenwong, Prachya Bumrungkun

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As With the evolution of smart grids, ensuring the reliability and efficiency of electrical systems in smart cities has become crucial. This paper proposes a distinct approach that combines advanced machine learning techniques to accurately predict electrical failures and address voltage reliability issues. This approach aims to improve the accuracy and efficiency of reliability evaluations in smart cities. The aim of this research is to develop a comprehensive predictive model that accurately predicts electrical failures and voltage reliability in smart cities. This model integrates RFM analysis, K-means clustering, and LSTM networks to achieve this objective. The research utilizes RFM analysis, traditionally used in customer value assessment, to categorize and analyze electrical components based on their failure recency, frequency, and monetary impact. K-means clustering is employed to segment electrical components into distinct groups with similar characteristics and failure patterns. LSTM networks are used to capture the temporal dependencies and patterns in customer data. This integration of RFM, K-means, and LSTM results in a robust predictive tool for electrical failures and voltage reliability. The proposed model has been tested and validated on diverse electrical utility datasets. The results show a significant improvement in prediction accuracy and reliability compared to traditional methods, achieving an accuracy of 92.78% and an F1-score of 0.83. This research contributes to the proactive maintenance and optimization of electrical infrastructures in smart cities. It also enhances overall energy management and sustainability. The integration of advanced machine learning techniques in the predictive model demonstrates the potential for transforming the landscape of electrical system management within smart cities. The research utilizes diverse electrical utility datasets to develop and validate the predictive model. RFM analysis, K-means clustering, and LSTM networks are applied to these datasets to analyze and predict electrical failures and voltage reliability. The research addresses the question of how accurately electrical failures and voltage reliability can be predicted in smart cities. It also investigates the effectiveness of integrating RFM analysis, K-means clustering, and LSTM networks in achieving this goal. The proposed approach presents a distinct, efficient, and effective solution for predicting and mitigating electrical failures and voltage issues in smart cities. It significantly improves prediction accuracy and reliability compared to traditional methods. This advancement contributes to the proactive maintenance and optimization of electrical infrastructures, overall energy management, and sustainability in smart cities.

Keywords: electrical state prediction, smart grids, data-driven method, long short-term memory, RFM, k-means, machine learning

Procedia PDF Downloads 39

Authors: Reeta Devi, Hitender Kumar Tyagi, Dinesh Kumar

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In present scenario, cardiovascular problems are growing challenge for researchers and physiologists. As heart disease have no geographic, gender or socioeconomic specific reasons; detecting cardiac irregularities at early stage followed by quick and correct treatment is very important. Electrocardiogram is the finest tool for continuous monitoring of heart activity. Heart rate variability (HRV) is used to measure naturally occurring oscillations between consecutive cardiac cycles. Analysis of this variability is carried out using time domain, frequency domain and non-linear parameters. This paper presents HRV analysis of the online dataset for normal sinus rhythm (taken as healthy subject) and sudden cardiac death (SCD subject) using all three methods computing values for parameters like standard deviation of node to node intervals (SDNN), square root of mean of the sequences of difference between adjacent RR intervals (RMSSD), mean of R to R intervals (mean RR) in time domain, very low-frequency (VLF), low-frequency (LF), high frequency (HF) and ratio of low to high frequency (LF/HF ratio) in frequency domain and Poincare plot for non linear analysis. To differentiate HRV of healthy subject from subject died with SCD, k –nearest neighbor (k-NN) classifier has been used because of its high accuracy. Results show highly reduced values for all stated parameters for SCD subjects as compared to healthy ones. As the dataset used for SCD patients is recording of their ECG signal one hour prior to their death, it is therefore, verified with an accuracy of 95% that proposed algorithm can identify mortality risk of a patient one hour before its death. The identification of a patient’s mortality risk at such an early stage may prevent him/her meeting sudden death if in-time and right treatment is given by the doctor.

Keywords: early stage prediction, heart rate variability, linear and non-linear analysis, sudden cardiac death

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Authors: Mohamed Loutou, Mohamed Hajjaji, Mohamed Ait Babram, Mohammed Mansori, Rachid Hakkou, Claude Favotto

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More than 26,4 million tons of phosphates are produced by the phosphates industries in Morocco (2010), generating huge amounts of sludge by flocculation during the ore beneficiation. They way are stored at the end of the process in open air ponds. Its accumulation and storage may have an impact on several scales such as ground water and human being. For this purpose, an efficient way to use it the field of the ceramic is proposed. The as received sludge and a clay-rich sediment have been studied in terms of chemical, mineralogical and micro-structural side using various analytical methods. Several formulations have been performed by mixing the sludge with the binder shaped in the form of granules. After being dried at 105 °C, the samples were heated in the range of 900-1200 °C. As well as the ceramic properties (firing shrinkage, water absorption, total porosity and compressive strength) the micro structure has been investigated using X-ray diffraction, scanning electron microscopy and Fourier transform infrared spectroscopy. The relations between properties and the operating factors were formulated using the design of experiments (DOE). Gehlenite was the only phase neo-formed in the sintering samples. SEM micrographs revealed the presence of nano metric stains. Based on RSM results, all factors had positive effects on Firing shrinkage, compressive strength and total porosity. However, they manifested opposite effects on density and water absorption.

Keywords: phosphate sludge, clay, ceramic properties, granule

Procedia PDF Downloads 494

Authors: R. Ziaie Moayed, S. P. Emadoleslami Oskoei, S. D. Beladi Mousavi, A. Taleb Beydokhti

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There have been many reports of the destructive effects of cement on the environment in recent years. In the present research, it has been attempted to reduce the destructive effects of cement by replacing silica fume as adhesive materials instead of cement. The present study has attempted to improve the mechanical properties of cement slurry by using waste material from a glass production factory, located in Qazvin city of Iran, in which accumulation volume has become an environmental threat. The chemical analysis of the waste material indicates that this material contains about 94% of SiO₂ and AL₂O₃ and has a close structure to silica fume. Also, the particle grain size test was performed on the mentioned waste. Then, the unconfined compressive strength test of the slurry was performed by preparing a mixture of water and adhesives with different percentages of cement and silica fume. The water to an adhesive ratio of this mixture is 1:3, and the curing process last 28 days. It was found that the sample had an unconfined compressive strength of about 300 kg/cm² in a mixture with equal proportions of cement and silica fume. Besides, the sample had a brittle fracture in the slurry sample made of pure cement, however, the fracture in cement-silica fume slurry mixture is flexible and the structure of the specimen remains coherent after fracture. Therefore, considering the flexibility that is achieved by replacing this waste, it can be used to stabilize soils with cracking potential.

Keywords: cement replacement, cement slurry, environmental threat, natural pozzolan, silica fume, waste material

Procedia PDF Downloads 116

Authors: A. Alshebani, Y. Swesi, S. Mrayed, F. Altaher

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This paper present some preliminary work on the preparation and physicochemical caracterization of nanocomposite MFI-alumina structures based on alumina hollow fibres. The fibers are manufactured by a wet spinning process. α-alumina particles were dispersed in a solution of polysulfone in NMP. The resulting slurry is pressed through the annular gap of a spinneret into a precipitation bath. The resulting green fibres are sintered. The mechanical strength of the alumina hollow fibres is determined by a three-point-bending test while the pore size is characterized by bubble-point testing. The bending strength is in the range of 110 MPa while the average pore size is 450 nm for an internal diameter of 1 mm and external diameter of 1.7 mm. To characterize the MFI membranes various techniques were used for physicochemical characterization of MFI–ceramic hollow fibres membranes: The nitrogen adsorption, X-ray diffractometry, scanning electron microscopy combined with X emission microanalysis. Scanning Electron Microscopy (SEM) and Energy Dispersive Microanalysis by the X-ray were used to observe the morphology of the hollow fibre membranes (thickness, infiltration into the carrier, defects, homogeneity). No surface film, has been obtained, as observed by SEM and EDX analysis and confirmed by high temperature variation of N2 and CO2 gas permeances before cation exchange. Local analysis and characterise (SEM and EDX) and overall (by ICP elemental analysis) were conducted on two samples exchanged to determine the quantity and distribution of the cation of cesium on the cross section fibre of the zeolite between the cavities.

Keywords: physicochemical characterization of MFI, ceramic hollow fibre, CO2, ion-exchange

Procedia PDF Downloads 336

Authors: Hasan Taherkhani

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Increasingly accumulation of the solid waste materials has become a major environmental problem of communities. In addition to the protection of environment, the recycling and reusing of the waste materials are financially beneficial. Waste materials can be used in highway construction. This study aimed to investigate the applicability of recycled concrete, asphalt and steel slag powder, as a replacement of the primary mineral filler in asphalt concrete has been investigated. The primary natural siliceous aggregate filler, as control, has been replaced with the secondary recycled concrete, asphalt and steel slag powders, and some engineering properties of the mixtures have been evaluated. Marshal Stability, flow, indirect tensile strength, moisture damage, static creep and volumetric properties of the mixtures have been evaluated. The results show that, the Marshal Stability of the mixtures containing recycled powders is higher than that of the control mixture. The flow of the mixtures containing recycled steel slag is lower, and that of the mixtures containing recycled asphalt and cement concrete powder is found to be higher than that of the control mixture. It is also found that the resistance against moisture damage and permanent deformation of the mixture can be improved by replacing the natural filler with the recycled powders. The volumetric properties of the mixtures are not significantly influenced by replacing the natural filler with the recycled powders.

Keywords: filler, steel slag, recycled concrete, recycled asphalt concrete, tensile strength, moisture damage, creep

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Authors: M. Sirhan, S. Bekhor, A. Sidess

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In-service pavements deteriorate with time due to traffic wheel loads, environment, and climate conditions. Pavement deterioration leads to a reduction in their serviceability and structural behavior. Consequently, proper maintenance and rehabilitation (M&R) are necessary actions to keep the in-service pavement network at the desired level of serviceability. Due to resource and financial constraints, the pavement management system (PMS) prioritizes roads most in need of maintenance and rehabilitation action. It recommends a suitable action for each pavement based on the performance and surface condition of each road in the network. The pavement performance and condition are usually quantified and evaluated by different types of roughness-based and stress-based indices. Examples of such indices are Pavement Serviceability Index (PSI), Pavement Serviceability Ratio (PSR), Mean Panel Rating (MPR), Pavement Condition Rating (PCR), Ride Number (RN), Profile Index (PI), International Roughness Index (IRI), and Pavement Condition Index (PCI). PCI is commonly used in PMS as an indicator of the extent of the distresses on the pavement surface. PCI values range between 0 and 100; where 0 and 100 represent a highly deteriorated pavement and a newly constructed pavement, respectively. The PCI value is a function of distress type, severity, and density (measured as a percentage of the total pavement area). PCI is usually calculated iteratively using the 'Paver' program developed by the US Army Corps. The use of soft computing techniques, especially Artificial Neural Network (ANN), has become increasingly popular in the modeling of engineering problems. ANN techniques have successfully modeled the performance of the in-service pavements, due to its efficiency in predicting and solving non-linear relationships and dealing with an uncertain large amount of data. Typical regression models, which require a pre-defined relationship, can be replaced by ANN, which was found to be an appropriate tool for predicting the different pavement performance indices versus different factors as well. Subsequently, the objective of the presented study is to develop and train an ANN model that predicts the PCI values. The model’s input consists of percentage areas of 11 different damage types; alligator cracking, swelling, rutting, block cracking, longitudinal/transverse cracking, edge cracking, shoving, raveling, potholes, patching, and lane drop off, at three severity levels (low, medium, high) for each. The developed model was trained using 536,000 samples and tested on 134,000 samples. The samples were collected and prepared by The National Transport Infrastructure Company. The predicted results yielded satisfactory compliance with field measurements. The proposed model predicted PCI values with relatively low standard deviations, suggesting that it could be incorporated into the PMS for PCI determination. It is worth mentioning that the most influencing variables for PCI prediction are damages related to alligator cracking, swelling, rutting, and potholes.

Keywords: artificial neural networks, computer programming, pavement condition index, pavement management, performance prediction

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Authors: Christos Lampropoulos, Maria Konsta, Vicky Dradaki, Irini Dri, Konstantina Panouria, Tamta Sirbilatze, Ifigenia Apostolou, Vaggelis Lambas, Christina Kordali, Georgios Mavras

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Objectives: Malnutrition in hospitalized patients is related to increased morbidity and mortality. The purpose of our study was to compare various nutritional scores in order to detect the most suitable one for assessing the nutritional status of elderly, hospitalized patients and correlate them with mortality and extension of admission duration, due to patients’ critical condition. Methods: Sample population included 150 patients (78 men, 72 women, mean age 80±8.2). Nutritional status was assessed by Mini Nutritional Assessment (MNA full, short-form), Malnutrition Universal Screening Tool (MUST) and short Nutritional Appetite Questionnaire (sNAQ). Sensitivity, specificity, positive and negative predictive values and ROC curves were assessed after adjustment for the cause of current admission, a known prognostic factor according to previously applied multivariate models. Primary endpoints were mortality (from admission until 6 months afterwards) and duration of hospitalization, compared to national guidelines for closed consolidated medical expenses. Results: Concerning mortality, MNA (short-form and full) and SNAQ had similar, low sensitivity (25.8%, 25.8% and 35.5% respectively) while MUST had higher sensitivity (48.4%). In contrast, all the questionnaires had high specificity (94%-97.5%). Short-form MNA and sNAQ had the best positive predictive value (72.7% and 78.6% respectively) whereas all the questionnaires had similar negative predictive value (83.2%-87.5%). MUST had the highest ROC curve (0.83) in contrast to the rest questionnaires (0.73-0.77). With regard to extension of admission duration, all four scores had relatively low sensitivity (48.7%-56.7%), specificity (68.4%-77.6%), positive predictive value (63.1%-69.6%), negative predictive value (61%-63%) and ROC curve (0.67-0.69). Conclusion: MUST questionnaire is more advantageous in predicting mortality due to its higher sensitivity and ROC curve. None of the nutritional scores is suitable for prediction of extended hospitalization.

Keywords: duration of admission, malnutrition, nutritional assessment scores, prognostic factors for mortality

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Authors: Sukhdeep Singh Gill, Gurbhinder Singh Brar

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In recent years, friction stir welding (FSW) has attracted the main attention of the concerned researcher especially in case of joining of nonferrous alloys like aluminum and magnesium due to its unmatchable properties with respect to other welding techniques. Friction stir welding is a solid state welding process which is most suitable for the welding of nonferrous alloys, especially aluminum and magnesium alloys. Aluminum and magnesium alloys are widely used for structural applications of all types of automobiles due to their superior mechanical properties with their low density. This paper deals with the critical review of the different properties (like tensile strength, microhardness, impact strength, corrosion resistance, and metallurgical investigation on SEM) obtained by the FSW of aluminum and magnesium alloys. After a critical review of the existing published literature on concerned topics, all the properties of welding joins are compared in the tabulated manner to optimize the selection of materials and FSW parameters according to mechanical and tribological properties. Different tool designs used for the FSW process are also thoroughly studied, and the influence of the design of the tool used in FSW on the different properties has also been incorporated in this paper. It has been observed from the existing published literature that FSW is the most effective and practical technique for joining the non ferrous alloys especially aluminum and magnesium alloys, and among the different FSW tools, left hand threaded tri-flute (LHTTF) tool is best for the welding of non ferrous alloys like aluminum and magnesium alloys which gives the superior mechanical properties to welding joint.

Keywords: aluminum, friction stir welding, magnesium, structural applications, tool design

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Authors: Erjola Reufi, Thomas Beer

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Plain, unreinforced concrete is a brittle material, with a low tensile strength, limited ductility and little resistance to cracking. In order to improve the inherent tensile strength of concrete there is a need of multi directional and closely spaced reinforcement, which can be provided in the form of randomly distributed fibers. Fiber reinforced concrete (FRC) is a composite material consisting of cement, sand, coarse aggregate, water and fibers. In this composite material, short discrete fibers are randomly distributed throughout the concrete mass. The behavioral efficiency of this composite material is far superior to that of plain concrete and many other construction materials of equal cost. The present experimental study considers the effect of steel fibers and polypropylene fiber on the modulus of elasticity of concrete. Hook end steel fibers of length 5 cm and 3 cm at volume fraction of 0.25%, 0.5% and 1.% were used. Also polypropylene fiber of length 12, 6, 3 mm at volume fraction 0.1, 0.25, and 0.4 % were used. Fifteen mixtures has been prepared to evaluate the effect of fiber on modulus of elasticity of concrete. Ultrasonic pulse velocity (UPV) and resonant frequency methods which are two non-destructive testing techniques have been used to measure the elastic properties of fiber reinforced concrete. This study found that ultrasonic wave propagation is the most reliable, easy and cost effective testing technique to use in the determination of the elastic properties of the FRC mix used in this study.

Keywords: fiber reinforced concrete(FRC), polypropylene fiber, resonance, ultrasonic pulse velocity, steel fiber

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Authors: Oluwagbenga B. Fatile, Felix U. Idu, Olajide T. Sanya

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This paper reports the viability of developing Zn-27Al alloy matrix hybrid composites reinforced with alumina, graphite and fly ash (a solid waste byproduct of coal in thermal power plants). This research work was aimed at developing low cost-high performance Zn-27Al matrix composite with low density. Alumina particulates (Al2O3), graphite added with 0, 2, 3, 4, and 5 wt% fly ash were utilized to prepare 10wt% reinforcing phase with Zn-27Al alloy as matrix using two-step stir casting method. Density measurement estimated percentage porosity, tensile testing, micro hardness measurement, and optical microscopy were used to assess the performance of the composites produced. The results show that the hardness, ultimate tensile strength, and percent elongation of the hybrid composites decrease with increase in fly ash content. The maximum decrease in hardness and ultimate tensile strength of 13.72% and 15.25% respectively were observed for composite grade containing 5wt% fly ash. The percentage elongation of composite sample without fly ash is 8.9% which is comparable with that of the sample containing 2wt% fly ash with percentage elongation of 8.8%. The fracture toughness of the fly ash containing composites was, however, superior to those of composites without fly ash with 5wt% fly ash containing composite exhibiting the highest fracture toughness. The results show that fly ash can be utilized as complementary reinforcement in ZA-27 alloy matrix composite to reduce cost.

Keywords: fly ash, hybrid composite, mechanical behaviour, stir-cast

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Authors: Siri Marthe Arbo, Afaf Saai, Sture Sørli, Mette Nedreberg

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This work aims to establish a reliable approach for optimizing a Laser Metal Deposition (LMD) process for a critical maritime component, based on the material properties and structural performance required by the maritime industry. The component of interest is a water jet impeller, for which specific requirements for material properties are defined. The developed approach is based on the assessment of the effects of LMD process parameters on microstructure and material performance of standard AM 2205 duplex stainless steel powder. Duplex stainless steel offers attractive properties for maritime applications, combining high strength, enhanced ductility and excellent corrosion resistance due to the specific amounts of ferrite and austenite. These properties are strongly affected by the microstructural characteristics in addition to microstructural defects such as porosity and welding defects, all strongly influenced by the chosen LMD process parameters. In this study, the influence of deposition speed and heat input was evaluated. First, the influences of deposition speed and heat input on the microstructure characteristics, including ferrite/austenite fraction, amount of porosity and welding defects, were evaluated. Then, the achieved mechanical properties were evaluated by standard testing methods, measuring the hardness, tensile strength and elongation, bending force and impact energy. The measured properties were compared to the requirements of the water jet impeller. The results show that the required amounts of ferrite and austenite can be achieved directly by the LMD process without post-weld heat treatments. No intermetallic phases were observed in the material produced by the investigated process parameters. A high deposition speed was found to reduce the ductility due to the formation of welding defects. An increased heat input was associated with reduced strength due to the coarsening of the ferrite/austenite microstructure. The microstructure characterizations and measured mechanical performance demonstrate the great potential of the LMD process and generate a valuable database for the optimization of the LMD process for duplex stainless steels.

Keywords: duplex stainless steel, laser metal deposition, process optimization, microstructure, mechanical properties

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Authors: Mohammad Amin Tutunchian, Pedram Roshani, Reza Rezvani, Julio Ángel Infante Sedano

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The highly recommended approach to design, known as the load and resistance factor design (LRFD) method, employs the geotechnical resistance factor (GRF) for shaping pile foundation designs. Within the standard process for designing pile foundations, geotechnical engineers commonly adopt a design strategy rooted in saturated soil mechanics (SSM), often disregarding the impact of unsaturated soil behavior. This oversight within the design procedure leads to the omission of the enhancement in shear strength exhibited by unsaturated soils, resulting in a more cautious outcome in design results. This research endeavors to present a methodology for fine-tuning the GRF used for axially loaded driven piles in Winnipeg, Canada. This is achieved through the application of a well-established probabilistic approach known as the first-order second moment (FOSM) method while also accounting for the influence of unsaturated soil behavior. The findings of this study demonstrate that incorporating the influence of unsaturated conditions yields an elevation in projected bearing capacity and recommends higher GRF values in accordance with established codes. Additionally, a novel factor referred to as phy has been introduced to encompass the impact of saturation conditions in the calculation of pile bearing capacity, as guided by prevalent static analysis techniques.

Keywords: unsaturated soils, shear strength, LRFD, FOSM, GRF

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Authors: Sukhwinder K. Bhullar, M. B. G. Jun

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The developments in biomedical industry have demanded the development of biocompatible, high performance materials to meet higher engineering specifications. The general requirements of such materials are to provide a combination of high stiffness and strength with significant weight savings, resistance to corrosion, chemical resistance, low maintenance, and reduced costs. Auxetic materials which come under the category of smart materials offer huge potential through measured enhancements in mechanical properties. Unique deformation mechanism, providing cushioning on indentation, automatically adjustable with its strength and thickness in response to forces and having memory returns to its neutral state on dissipation of stresses make them good candidate in biomedical industry. As simple extension and compression of tissues is of fundamental importance in biomechanics, therefore, to study the elastic behaviour of auxetic soft tissues implant is targeted in this paper. Therefore development and characterization of auxetic soft tissue implant is studied in this paper. This represents a real life configuration where soft tissue such as meniscus in knee replacement, ligaments and tendons often are taken as transversely isotropic. Further, as composition of alternating polydisperse blocks of soft and stiff segments combined with excellent biocompatibility make polyurethanes one of the most promising synthetic biomaterials. Hence selecting auxetic polyurathylene foam functional characterization is performed and compared with conventional polyurathylene foam.

Keywords: auxetic materials, deformation mechanism, enhanced mechanical properties, soft tissues

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Authors: Samantha Borja, Vladimir Valle, Pamela Molina

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The development of adhesives from renewable raw materials attracts the attention of the scientific community, due to it promises the reduction of the dependence with materials derived from oil. This work proposes the use of modified 'oca (Oxalis tuberosa)' starch and polyvinyl alcohol (PVA) in the elaboration of adhesives for lignocellulosic substrates. The investigation focused on the formulation of adhesives with 3 different PVA:starch (modified and native) ratios (of 1,0:0,33; 1,0:1,0; 1,0:1,67). The first step to perform it was the chemical modification of starch through acid hydrolysis and a subsequent urea treatment to get carbamate starch. Then, the adhesive obtained was characterized in terms of instantaneous viscosity, Fourier-transform infrared spectroscopy (FTIR) and shear strength. The results showed that viscosity and mechanical tests exhibit data with the same tendency in relation to the native and modified starch concentration. It was observed that the data started to reduce its values to a certain concentration, where the values began to grow. On the other hand, two relevant bands were found in the FTIR spectrogram. The first in 3300 cm⁻¹ of OH group with the same intensity for all the essays and the other one in 2900 cm⁻¹, belonging to the group of alkanes with a different intensity for each adhesive. On the whole, the ratio PVA:starch (1:1) will not favor crosslinking in the adhesive structure and causes the viscosity reduction, whereas, in the others ones, the viscosity is higher. It was also observed that adhesives made with modified starch had better characteristics, but the adhesives with high concentrations of native starch could equal the properties of the adhesives made with low concentrations of modified starch.

Keywords: polyvinyl alcohol, PVA, chemical modification, starch, FTIR, viscosity, shear strength

Procedia PDF Downloads 137

Authors: Z. Chen, C. S. Poon

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In Hong Kong, about 1,000 tonnes of sewage sludge were produced every day in 2014 representing a major fraction of the total solid municipal waste. Traditionally, sewage sludge is disposed of at landfills. This disposal method causes environmental issues and uses up precious space in landfills which are becoming saturated one by one. To tackle the disposal problem, Hong Kong government has just built a sewage sludge incinerator. Through incineration the volume of waste can be reduced up to 90% by converting sewage sludge into ash. Whilst sewage sludge ash (SSA) still needs to be disposed of at landfills, research has been conducted at the Hong Kong Polytechnic University on using SSA to substitute cement for the production of construction materials. Results demonstrated that SSA contained many open and isolated pores and thus can reduce the cement dilution effect resulting in only slight decrease in the flexural and compressive strengths of cement mortar. The incorporation of SSA in cement mortar can be up to 20% of the binder, without too much worry about adverse effect on strength development of mortar. There was some enhancement in strength using ground SSA in comparison to the original SSA. The original SSA shortened the relative initial setting time of cement paste but ground SSA caused slight delay in the setting of cement paste. The research also found that increasing the percentage of SSA lead to decreasing workability of cement mortar with the same water/binder ratio, and ground SSA was beneficial to workability although grinding increased the surface area of SSA. This paper summarizes the major findings of the research.

Keywords: cement replacement, construction material, sewage sludge ash, waste recycling

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Authors: Wenhao Li, Shijun Guo

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Carbon fibre reinforced composites are progressively replacing metal structures in modern civil aircraft. This is because composite materials have large potential of weight saving compared with metal. However, the achievement to date of weight saving in composite structure is far less than the theoretical potential due to many uncertainties in structural integrity and safety concern. Unlike the conventional metallic structure, composite components are bonded together along the joints where structural integrity is a major concern. To ensure the safety, metal fasteners are used to reinforce the composite bonded joints. One of the solutions for a significant weight saving of composite structure is to develop an effective technology of on-board Structural Health Monitoring (SHM) System. By monitoring the real-life stress status of composite structures during service, the safety margin set in the structure design can be reduced with confidence. It provides a means of safeguard to minimize the need for programmed inspections and allow for maintenance to be need-driven, rather than usage-driven. The aim of this paper is to develop smart composite joint. The key technology is a multifunctional thermoplastic composite fastener (MTCF). The MTCF will replace some of the existing metallic fasteners in the most concerned locations distributed over the aircraft composite structures to reinforce the joints and form an on-board SHM network system. Each of the MTCFs will work as a unit of the AU and AE technology. The proposed MTCF technology has been patented and developed by Prof. Guo in Cranfield University, UK in the past a few years. The manufactured MTCF has been successfully employed in the composite SLJ (Single-Lap Joint). In terms of the structure integrity, the hybrid SLJ reinforced by MTCF achieves 19.1% improvement in the ultimate failure strength in comparison to the bonded SLJ. By increasing the diameter or rearranging the lay-up sequence of MTCF, the hybrid SLJ reinforced by MTCF is able to achieve the equivalent ultimate strength as that reinforced by titanium fastener. The predicted ultimate strength in simulation is in good agreement with the test results. In terms of the structural health monitoring, a signal from the MTCF was measured well before the load of mechanical failure. This signal provides a warning of initial crack in the joint which could not be detected by the strain gauge until the final failure.

Keywords: composite single-lap joint, crack propagation, multifunctional composite fastener, structural health monitoring

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Authors: Sam S. Hashemi

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The breakage of bonding between sand particles and their dislodgment from the borehole wall are among the main factors resulting in a borehole failure in poorly cemented granular formations. The grain debonding usually precedes the borehole failure and it can be considered as a sign that the onset of the borehole collapse is imminent. Detecting the bonding breakage point and introducing an appropriate failure criterion will play an important role in borehole stability analysis. To study the influence of different factors on the initiation of sand bonding breakage at the borehole wall, a series of laboratory tests was designed and conducted on poorly cemented sand samples. The total absorbed strain energy per volume of material up to the point of the observed particle debonding was computed. The results indicated that the particle bonding breakage point at the borehole wall was reached both before and after the peak strength of the thick-walled hollow cylinder specimens depending on the stress path and cement content. Three different cement contents and two borehole sizes were investigated to study the influence of the bonding strength and scale on the particle dislodgment. Test results showed that the stress path has a significant influence on the onset of the sand bonding breakage. It was shown that for various stress paths, there is a near linear relationship between the absorbed energy and the normal effective mean stress.

Keywords: borehole stability, experimental studies, poorly cemented sands, total absorbed strain energy

Procedia PDF Downloads 194