Search results for: compressive strength prediction

Authors: Khaled M. Youssef, Sara I. Ahmed

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In this study, artifacts-free bulk nanocrystalline pure aluminum alloy samples were prepared through mechanical milling under ultra-high purity argon and at both liquid nitrogen and room temperatures. The nanostructure evolution during milling was examined using X-ray diffraction and transmission electron microscope techniques. The in-situ consolidated samples after milling exhibited an average grain size of 18 nm. The tensile properties of this novel material are reported in comparison with coarse-grained aluminum alloys. The 0.2% offset yield strength of the nanocrystalline aluminum was found to be 340 MPa. This value is at least one order of magnitude higher than that of the coarse-grained aluminum alloy. In addition to this extraordinarily high strength, the nanocrystalline aluminum showed a significant tensile ductility, with 6% uniform elongation and 11% elongation-to-failure. The transmission electron microscope observations in this study provide evidence of deformation twinning in the plastically deformed nanocrystalline aluminum. These results highlight a change of the deformation mechanism from a typical dislocation slip to twinning deformation induced by partial dislocation activities.

Keywords: nanocrystalline, aluminum, strength, ductility

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

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Sugarcane bagasse (SCB)-reinforced Polypropylene (PP) Based matrix composites (25-45 wt% fiber) were fabricated by a compression molding technique. The SCB surface was chemically modified using 5%-10% sodium hydroxide (NaOH), and after that, mechanical properties, water uptake, and soil degradation of the composites were investigated. Tensile strength (TS), tensile modulus (TM), bending strength (BS), bending modulus (BM) and elongation at break (Eb%) of the 30wt% composites were found to be 35.6 MPa, 10.2 GPa, 56 MPa, 5.6 GPa, and 11%, respectively. The SCB/PP based composites were treated with irradiated under gamma radiation (the source strength 50 kCi Cobalt-60) of various doses (2.5 kGy to 10 kGy). The effect of gamma radiation on the composites was also investigated, and it found that the effect of 5.0 kGy (i.e. units for radiation measurement is 'gray', kGy=kilogray ) gamma dose showed better mechanical properties than other doses. The results revealed that the combination of the chemical modification of the SCB fibers and irradiation of the composites were more effective in compatibility improvement than chemical modification alone. After flexural testing, fracture sides of the untreated and treated both composites were studied by scanning electron microscope (SEM). SEM results of the treated SCB/PP based composites showed better fiber-matrix adhesion than untreated SCB/PP based composites. However, it was found that the treated SCB/PP composite has better mechanical strength, durability, and more receptivity than untreated SCB/PP based composite.

Keywords: sugarcane bagasse (SCB), polypropylene (PP), mechanical properties, scanning electron microscope (SEM), gamma radiation, water uptake tests and soil degradation

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Authors: Harun Sepet, Necmettin Tarakcioglu

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The present study investigated the impact strength and fracture mechanism of nano-CaCO3 and nanoclay reinforced HDPE nanocomposites by using Charpy impact test. The nano-CaCO3 and nanoclay reinforced HDPE granules were prepared by the melt blending method using a compounder system, which consists of industrial banbury mixer, single screw extruder and granule cutting in industrial-scale. The nano-CaCO3 and nanoclay reinforced HDPE granules were molded using an injection-molding machine as plates, and then impact samples were cut by using punching die from the nanocomposite plates. As a result of impact experiments, nano-CaCO3 and nanoclay reinforced HDPE nanocomposites were determined to have lower impact energy level than neat HDPE. Also, the impact strength of HDPE further decreased by addition nanoclay compared to nano-CaCO3. The occurred fracture areas with the impact were detected by SEM examination. It is understood that fracture surface morphology changes when nano-CaCO3 and nanoclay ratio increases. The fracture surface changes were examined to determine the fracture mechanism of nano-CaCO3 and nanoclay reinforced HDPE nanocomposites.

Keywords: charpy, HDPE, industrial scale nano-CaCO3, nanoclay, nanocomposite

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Authors: Doaa H. Elgohary, Tamer F. Khalifa, Mona M. Salem, M. A. Saad, Ehab Haider Sherazy

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Textiles have conquered new areas over the past three decades, including agriculture, transportation, filtration, military, and medicine. The use of textiles in the medical field has increased significantly in recent years and covers almost everything. Medical textiles represent a huge market as they are widely used not only in hospitals, hygiene, and healthcare but also in hotels and other environments where hygiene is required. However, not all fibers are suitable for the manufacture of medical textile products. Some special properties are required for the manufactured materials, e.g. Strength, elasticity, spinnability, etc. In addition to the usual properties of medical fibers, non-toxicity, sterilizability, biocompatibility, biodegradability, good absorbability, softness, and freedom from additives, etc., desirable properties include impurities. Stitching is one of the most common practices in the medical field. as it is a biomaterial device, either natural or synthetic, used to connect blood vessels and connect tissues. In addition to being very strong, suture material should easily dissolve in bodily fluids and lose strength as the tissue gains strength. In this work, a study to select the most used materials for sutures, it was found that silk, VICRYL and polypropylene were the most used materials in varying numbers. The research involved the analysis of 36 samples from three different materials (mostly commonly used), the tests were carried out on 36 imported samples for four different companies. Each company supplied three different materials (silk, VICRYL and polypropylene) with three different gauges (4, 3.5 and 3 metric). The results of the study were tabulated, presented, and discussed. Practical statistical science serves to support the practical analysis of experimental work products and the various relationships between variables to achieve the best sampling performance with the functional purpose generated for it. Analysis of the imported sutures shows that VICRYL sutures had the highest tensile strength, toughness, knot tensile strength and knot toughness, followed by polypropylene and silk. As yarn counts, weight and diameter increase, its tensile strength and toughness increase while its elongation and knot tension decrease. The multifilament yarn construction (silk and VICRYL) scores higher compared to the monofilament construction (polypropylene), resulting in increases in tenacity, toughness, knot tensile strength and knot toughness.

Keywords: biodegradable yarns, braided sutures, irritation, knot tying, medical textiles, surgical sutures, wound healing

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Authors: Seyed Abbas Tabatabaei, Fereydoon Moghadas Nejad, Mohammad Saed

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The bleeding prediction of the asphalt is one of the most complex subjects in the pavement engineering. In this paper, an Adaptive Neuro Fuzzy Inference System (ANFIS) is used for modeling the effect of important parameters on bleeding is trained and tested with the experimental results. bleeding index based on the asphalt film thickness differential as target parameter,asphalt content, temperature depth of two centemeter, heavy traffic, dust to effective binder, Marshall strength, passing 3/4 sieves, passing 3/8 sieves,passing 3/16 sieves, passing NO8, passing NO50, passing NO100, passing NO200 as input parameters. Then, we randomly divided empirical data into train and test sections in order to accomplish modeling. We instructed ANFIS network by 72 percent of empirical data. 28 percent of primary data which had been considered for testing the approprativity of the modeling were entered into ANFIS model. Results were compared by two statistical criterions (R2, RMSE) with empirical ones. Considering the results, it is obvious that our proposed modeling by ANFIS is efficient and valid and it can also be promoted to more general states.

Keywords: bleeding, asphalt film thickness differential, Anfis Modeling

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Authors: Binger Lu

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It remains unclear whether second language (L2) speakers could use discourse context cues to predict upcoming information as native speakers do during online comprehension. Some researchers propose that L2 learners may have a reduced ability to generate predictions during discourse processing. At the same time, there is evidence that discourse-level cues are weighed more heavily in L2 processing than in L1. Previous studies showed that L1 prediction is sensitive to the global validity of predictive cues. The current study aims to explore whether and to what extent L2 learners can dynamically and strategically adjust their prediction in accord with the global validity of predictive cues in L2 discourse comprehension as native speakers do. In a self-paced reading experiment, Chinese native speakers (N=128), C-E bilinguals (N=128), and English native speakers (N=128) read high-predictable (e.g., Jimmy felt thirsty after running. He wanted to get some water from the refrigerator.) and low-predictable (e.g., Jimmy felt sick this morning. He wanted to get some water from the refrigerator.) discourses in two-sentence frames. The global validity of predictive cues was manipulated by varying the ratio of predictable (e.g., Bill stood at the door. He opened it with the key.) and unpredictable fillers (e.g., Bill stood at the door. He opened it with the card.), such that across conditions, the predictability of the final word of the fillers ranged from 100% to 0%. The dependent variable was reading time on the critical region (the target word and the following word), analyzed with linear mixed-effects models in R. C-E bilinguals showed reliable prediction across all validity conditions (β = -35.6 ms, SE = 7.74, t = -4.601, p< .001), and Chinese native speakers showed significant effect (β = -93.5 ms, SE = 7.82, t = -11.956, p< .001) in two of the four validity conditions (namely, the High-validity and MedLow conditions, where fillers ended with predictable words in 100% and 25% cases respectively), whereas English native speakers didn’t predict at all (β = -2.78 ms, SE = 7.60, t = -.365, p = .715). There was neither main effect (χ^²(3) = .256, p = .968) nor interaction (Predictability: Background: Validity, χ^²(3) = 1.229, p = .746; Predictability: Validity, χ^²(3) = 2.520, p = .472; Background: Validity, χ^²(3) = 1.281, p = .734) of Validity with speaker groups. The results suggest that prediction occurs in L2 discourse processing but to a much less extent in L1, witha significant effect in some conditions of L1 Chinese and anull effect in L1 English processing, consistent with the view that L2 speakers are more sensitive to discourse cues compared with L1 speakers. Additionally, the pattern of L1 and L2 predictive processing was not affected by the global validity of predictive cues. C-E bilinguals’ predictive processing could be partly transferred from their L1, as prior research showed that discourse information played a more significant role in L1 Chinese processing.

Keywords: bilingualism, discourse processing, global validity, prediction, self-paced reading

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Authors: Arash Poordana, Reza Ziaie Moayed

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Calcareous sands are found most commonly in areas adjacent to crude oil and gas, and particularly around water. These types of soil have high compressibility due to high inter-granular porosity, irregularity, fragility, and especially crushing. Also, based on experience, it has been shown that the behavior of these types of soil is not similar to silica sand in loading. Since the destructive effects of cement on the environment are obvious, other alternatives such as bentonite are popular to be used. Bentonite has always been used commercially in civil engineering projects and according to its low hydraulic conductivity, it is used for landfills, cut-off walls, and nuclear wastelands. In the present study, unconfined compression tests in five ageing periods (1, 3, 7, 14, and 28 days) after mixing different percentages of bentonite (5%, 7.5% and 10%) with Bushehr calcareous sand were performed. The relative density considered for the specimens is 50%. Optimum water content was then added to each specimen accordingly (19%, 18.5%, and 17.5%). The sample preparation method was wet tamping and the specimens were compacted in five layers. It can be concluded from the results that as the bentonite content increases, the unconfined compression strength of the soil increases. Based on the obtained results, 3-day and 7-day ageing periods showed 30% and 50% increase in the shear strength of soil, respectively.

Keywords: unconfined compression test, bentonite, Bushehr, calcareous sand

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Authors: Veronica Caprai, Katrin Schollbach, Miruna V. A. Florea, H. J. H. Brouwers

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Nowadays MSWI (Municipal Solid Waste Incineration) bottom ash (BA) produced by Waste-to-Energy (WtE) plants represents the majority of the solid residues derived from MSW incineration. Once processed, the BA is often landfilled resulting in possible environmental problems, additional costs for the plant and increasing occupation of public land. In order to limit this phenomenon, European countries such as the Netherlands aid the utilization of MSWI BA in the construction field, by providing standards about the leaching of contaminants into the environment (Dutch Soil Quality Decree). Commonly, BA has a particle size below 32 mm and a heterogeneous chemical composition, depending on its source. By washing coarser BA, an MSWI sludge is obtained. It is characterized by a high content of heavy metals, chlorides, and sulfates as well as a reduced particle size (below 0.25 mm). To lower its environmental impact, MSWI sludge is filtered or centrifuged for removing easily soluble contaminants, such as chlorides. However, the presence of heavy metals is not easily reduced, compromising its possible application. For lowering the leaching of those contaminants, the use of MSWI residues in combination with cement represents a precious option, due to the known retention of those ions into the hydrated cement matrix. Among the applications, the European standard for common cement EN 197-1:1992 allows the incorporation of up to 5% by mass of a minor additional constituent (MAC), such as fly ash or blast furnace slag but also an unspecified filler into cement. To the best of the author's knowledge, although it is widely available, it has the appropriate particle size and a chemical composition similar to cement, FC has not been investigated as possible MAC in cement production. Therefore, this paper will address the suitability of MSWI FC as MAC for CEM I 52.5 R, within a 5% maximum replacement by mass. After physical and chemical characterization of the raw materials, the crystal phases of the pastes are determined by XRD for 3 replacement levels (1%, 3%, and 5%) at different ages. Thereafter, the impact of FC on mechanical and environmental performances of cement is assessed according to EN 196-1 and the Dutch Soil Quality Decree, respectively. The investigation of the reaction products evidences the formation of layered double hydroxides (LDH), in the early stage of the reaction. Mechanically the presence of FC results in a reduction of 28 days compressive strength by 8% for a replacement of 5% wt., compared with the pure CEM I 52.5 R without any MAC. In contrast, the flexural strength is not affected by the presence of FC. Environmentally, the Dutch legislation for the leaching of contaminants for unshaped (granular) material is satisfied. Based on the collected results, FC represents a suitable candidate as MAC in cement production.

Keywords: environmental impact evaluation, Minor additional constituent, MSWI residues, X-ray diffraction crystallography

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Authors: Marcho Setiawan Handok, Samuel S. Lemma, Abdoulaye Fofana, Naseef Mansoor

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This paper is proposing a method to predict the outcome of the National Football League match with data from 2019 to 2022 and compare it with other popular models. The model uses open-source statistical data of each team, such as passing yards, rushing yards, fumbles lost, and scoring. Each statistical data has offensive and defensive. For instance, a data set of anticipated values for a specific matchup is created by comparing the offensive passing yards obtained by one team to the defensive passing yards given by the opposition. We evaluated the model’s performance by contrasting its result with those of established prediction algorithms. This research is using a neural network to predict the score of a National Football League match and then predict the winner of the game.

Keywords: game prediction, NFL, football, artificial neural network

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Authors: Obinna K. Ihesiulor, Krishna Shankar, Paul Smith, Alan Fien

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Excessive fretting wear at the taper-trunnion junction (trunnionosis) apparently contributes to the high failure rates of hip implants. Implant wear and corrosion lead to the release of metal particulate debris and subsequent release of metal ions at the taper-trunnion surface. This results in a type of metal poisoning referred to as metallosis. The consequences of metal poisoning include; osteolysis (bone loss), osteoarthritis (pain), aseptic loosening of the prosthesis and revision surgery. Follow up after revision surgery, metal debris particles are commonly found in numerous locations. Background: A stable connection between the femoral ball head (taper) and stem (trunnion) is necessary to prevent relative motions and corrosion at the taper junction. Hence, the importance of component assembly cannot be over-emphasized. Therefore, the aim of this study is to determine the influence of head-stem junction assembly by press fitting and the subsequent disengagement/disassembly on the connection strength between the taper ball head and stem. Methods: CoCr femoral heads were assembled with High stainless hydrogen steel stem (trunnion) by Push-in i.e. press fit; and disengaged by Pull-out test. The strength and stability of the two connections were evaluated by measuring the head pull-out forces according to ISO 7206-10 standards. Findings: The head-stem junction strength linearly increases with assembly forces.

Keywords: wear, modular hip prosthesis, taper head-stem, force assembly and disassembly

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Authors: Mohamed El Horri, Amine Mouden, Reda Messaoudi, Mohamed Chekkal, Driss Benlaldj, Malika Baghdadi, Lahcene Benmahdi, Fatima Seghier

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Background/aim: Recently, the Von Willebrand factor antigen (vWF-Ag)has been identified as a new marker of portal hypertension (PH) and its complications. Few studies talked about its role in the prediction of esophageal varices. VWF-Ag is considered a non-invasive approach, In order to avoid the endoscopic burden, cost, drawbacks, unpleasant and repeated examinations to the patients. In our study, we aimed to evaluate the ability of this marker in the prediction of another complication of portal hypertension, which is portal hypertensive gastropathy (PHG), the one that is diagnosed also by endoscopic tools. Patients and methods: It is about a prospective study, which include 124 cirrhotic patients with no history of bleeding who underwent screening endoscopy for PH-related complications like esophageal varices (EVs) and PHG. Routine biological tests were performed as well as the VWF-Ag testing by both ELFA and Immunoturbidimetric techniques. The diagnostic performance of our marker was assessed using sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and receiver operating characteristic curves. Results: 124 patients were enrolled in this study, with a mean age of 58 years [CI: 55 – 60 years] and a sex ratio of 1.17. Viral etiologies were found in 50% of patients. Screening endoscopy revealed the presence of PHG in 20.2% of cases, while for EVsthey were found in 83.1% of cases. VWF-Ag levels, were significantly increased in patients with PHG compared to those who have not: 441% [CI: 375 – 506], versus 279% [CI: 253 – 304], respectively (p <0.0001). Using the area under the receiver operating characteristic curve (AUC), vWF-Ag was a good predictor for the presence of PHG. With a value higher than 320% and an AUC of 0.824, VWF-Ag had an 84% sensitivity, 74% specificity, 44.7% positive predictive value, 94.8% negative predictive value, and 75.8% diagnostic accuracy. Conclusion: VWF-Ag is a good non-invasive low coast marker for excluding the presence of PHG in patients with liver cirrhosis. Using this marker as part of a selective screening strategy might reduce the need for endoscopic screening and the coast of the management of these kinds of patients.

Keywords: von willebrand factor, portal hypertensive gastropathy, prediction, liver cirrhosis

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Authors: N. H. Hamid, A. Azmi, M. I. Adiyanto

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This main purpose of this paper is to evaluate the seismic performance of double bay two-storey reinforced concrete frame under in-plane lateral cyclic loading which designed using Eurocode 8 (EC8) by taking into account of seismic loading. The prototype model of reinforced concrete frame was constructed in one-half scale tested under in-plane lateral cyclic loading starts with ±0.2% drift, ±0.25% up to ±3.0% drift with the increment of ±0.25%. The performance of the RC frame is evaluated in terms of the hysteresis loop (load vs. displacement), stiffness, ductility, lateral strength, stress-strain relationship and equivalent viscous damping. Visual observation of the crack pattern after testing were observed where the beam- column joint suffer the most severe damage as it is the critical part in moment resisting frame. Spalling of concrete starts occurred at ±2.0% drift and become worse at ±2.5% drift. The experimental result shows that the maximum lateral strength of specimen is 99.98 kN and ductility of the specimen is µ=4.07 which lies between 3≤µ≤6 in order to withstand moderate to severe earthquakes.

Keywords: ductility, equivalent viscous damping, hysteresis loops, lateral strength, stiffness

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Authors: Sungzoon Cho, Hye Jin Lee, Sungwhan Jeon, Dongyoung Min, Sungwon Lyu

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Major public corporations worldwide use conference calls to report their quarterly earnings. These 'earnings' conference calls allow for questions from stock analysts. We investigated if it is possible to identify sentiment from the call script and use it to predict stock price movement. We analyzed call scripts from six companies, two each from Korea, China and Indonesia during six years 2011Q1 – 2017Q2. Random forest with Frequency-based sentiment scores using Loughran MacDonald Dictionary did better than control model with only financial indicators. When the stock prices went up 20 days from earnings release, our model predicted correctly 77% of time. When the model predicted 'up,' actual stock prices went up 65% of time. This preliminary result encourages us to investigate advanced sentiment scoring methodologies such as topic modeling, auto-encoder, and word2vec variants.

Keywords: earnings call script, random forest, sentiment analysis, stock price prediction

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Authors: Marcel Meinhardt, Manfred Keuser, Thomas Braml

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Cracking of reinforced concrete is a complex phenomenon induced by direct loads or restraints affecting reinforced concrete structures as soon as the tensile strength of the concrete is exceeded. Hence it is important to predict where cracks will be located and how they will propagate. The bond theory and the crack formulas in the actual design codes, for example, DIN EN 1992-1-1, are all based on the assumption that the reinforcement bars are embedded in homogeneous concrete without taking into account the influence of transverse reinforcement and the real stress situation. However, it can often be observed that real structures such as walls, slabs or beams show a crack spacing that is orientated to the transverse reinforcement bars or to the stirrups. In most Finite Element Analysis studies, the smeared crack approach is used for crack prediction. The disadvantage of this model is that the typical strain localization of a crack on element level can’t be seen. The crack propagation in concrete is a discontinuous process characterized by different factors such as the initial random distribution of defects or the scatter of material properties. Such behavior presupposes the elaboration of adequate models and methods of simulation because traditional mechanical approaches deal mainly with average material parameters. This paper concerned with the modelling of the initiation and the propagation of cracks in reinforced concrete structures considering the influence of transverse reinforcement and the real stress distribution in reinforced concrete (R/C) beams/plates in bending action. Therefore, a parameter study was carried out to investigate: (I) the influence of the transversal reinforcement to the stress distribution in concrete in bending mode and (II) the crack initiation in dependence of the diameter and distance of the transversal reinforcement to each other. The numerical investigations on the crack initiation and propagation were carried out with a 2D reinforced concrete structure subjected to quasi static loading and given boundary conditions. To model the uncertainty in the tensile strength of concrete in the Finite Element Analysis correlated normally and lognormally distributed random filed with different correlation lengths were generated. The paper also presents and discuss different methods to generate random fields, e.g. the Covariance Matrix Decomposition Method. For all computations, a plastic constitutive law with softening was used to model the crack initiation and the damage of the concrete in tension. It was found that the distributions of crack spacing and crack widths are highly dependent of the used random field. These distributions are validated to experimental studies on R/C panels which were carried out at the Laboratory for Structural Engineering at the University of the German Armed Forces in Munich. Also, a recommendation for parameters of the random field for realistic modelling the uncertainty of the tensile strength is given. The aim of this research was to show a method in which the localization of strains and cracks as well as the influence of transverse reinforcement on the crack initiation and propagation in Finite Element Analysis can be seen.

Keywords: crack initiation, crack modelling, crack propagation, cracks, numerical simulation, random fields, reinforced concrete, stochastic

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Authors: Ahmed Kayad Abdourazak, Abderafi Souad, Zejli Driss, Idriss Abdoulkader Ibrahim

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In this paper Artificial Neural Network (ANN) is used to predict the solar irradiation in Djibouti for the first Time that is useful to the integration of Concentrating Solar Power (CSP) and sites selections for new or future solar plants as part of solar energy development. An ANN algorithm was developed to establish a forward/reverse correspondence between the latitude, longitude, altitude and monthly solar irradiation. For this purpose the German Aerospace Centre (DLR) data of eight Djibouti sites were used as training and testing in a standard three layers network with the back propagation algorithm of Lavenber-Marquardt. Results have shown a very good agreement for the solar irradiation prediction in Djibouti and proves that the proposed approach can be well used as an efficient tool for prediction of solar irradiation by providing so helpful information concerning sites selection, design and planning of solar plants.

Keywords: artificial neural network, solar irradiation, concentrated solar power, Lavenberg-Marquardt

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Authors: Paria Soleimani, Arezoo Neshati

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Myocardial infarction is one of the leading causes of ‎death in the world. Some of these deaths occur even before the patient ‎reaches the hospital. Myocardial infarction occurs as a result of ‎impaired blood supply. Because the most of these deaths are due to ‎coronary artery disease, hence the awareness of the warning signs of a ‎heart attack is essential. Some heart attacks are sudden and intense, but ‎most of them start slowly, with mild pain or discomfort, then early ‎detection and successful treatment of these symptoms is vital to save ‎them. Therefore, importance and usefulness of a system designing to ‎assist physicians in the early diagnosis of the acute heart attacks is ‎obvious.‎ The purpose of this study is to determine how well a predictive ‎model would perform based on the only patient-reportable clinical ‎history factors, without using diagnostic tests or physical exams. This ‎type of the prediction model might have application outside of the ‎hospital setting to give accurate advice to patients to influence them to ‎seek care in appropriate situations. For this purpose, the data were ‎collected on 711 heart patients in Iran hospitals. 28 attributes of clinical ‎factors can be reported by patients; were studied. Three logistic ‎regression models were made on the basis of the 28 features to predict ‎the risk of heart attacks. The best logistic regression model in terms of ‎performance had a C-index of 0.955 and with an accuracy of 94.9%. ‎The variables, severe chest pain, back pain, cold sweats, shortness of ‎breath, nausea, and vomiting were selected as the main features.‎

Keywords: Coronary heart disease, Acute heart attacks, Prediction, Logistic ‎regression‎

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Authors: Adel Ahmadi Hosseini, Fatemeh Tavanaei, Alessandro Navarra, Ferri Hassani

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Mining engineering, as a part of geoscience, must address modern concerns. Traditional mining methods incorporate drill and blast technologies, which are followed by different issues, including excessive noise, vibration, air pollution, and safety hazards. Over the past two decades, mining engineers have sought alternative solutions to move from drill and blast to continuous methods to prevent such issues and improve sustainability in mining. Among the suggested methods, microwave treatment has shown promising results by creating micro/macro cracks in the rock structure prior to the operations. This research utilizes an energy-based analysis methodology to evaluate the efficiency of the microwave treatment in improving mining operations. The data analysis shows that increasing the input microwave energy dosage intensifies the rock damage. However, this approach can decrease the energy efficiency of the method by more than 50% in some cases. In this study, rock samples were treated with three power levels (3 kW, 7 kW, and 12 kW) and two energy dosages (20 kWh/t and 50 kWh/t), resulting in six conditions. To evaluate the impact of microwave treatment on the geomechanical behavior of the rocks, Unconfined Compressive Strength (UCS) tests were conducted on the microwave-treated samples, yielding stress-strain curves. Using the stress-strain curves, the effect of the different powers and energy dosages of microwaves are discussed. This research shows the potential of using microwave treatment to lead the industry to more sustainable mining.

Keywords: microwave treatment, microwave energy dosage, sustainable mining, rock fragmentation

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Authors: Javad Sarvestan, Zdenek Svoboda

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Force-time (F-T) curvature characteristics are globally referenced as the main indicators of athletic jump performance. Nevertheless, to the best of authors’ knowledge, no investigation tried to deeply study the relationship between F-T curve variables and real-game jump performance among elite volleyball players. To this end, this study was designated to investigate the association between F-T curve variables, including movement timings, force, velocity, power, rate of force development (RFD), modified reactive strength index (RSImod), and net impulse with spike jump height during real-game circumstances. Twelve young elite volleyball players performed 3 countermovement jump (CMJ) and 3 spike jump in real-game circumstances with 1-minute rest intervals to prevent fatigue. Shapiro-Wilk statistical test illustrated the normality of data distribution, and Pearson’s product correlation test portrayed a significant correlation between CMJ height and peak RFD (0.85), average RFD (r=0.81), RSImod (r=0.88) and concentric net impulse (r=0.98), and also significant correlation between spike jump height and peak RFD (0.73), average RFD (r=0.80), RSImod (r=0.62) and concentric net impulse (r=0.71). Multiple regression analysis also reported that these factors have a strong contribution in predicting of CMJ (98%) and spike jump (77%) heights. Outcomes of this study confirm that the RFD, concentric net impulse, and RSImod values could precisely monitor and track the volleyball attackers’ explosive strength, muscular stretch-shortening cycle function efficiency, and ultimate spike jump height. To this effect, volleyball coaches and trainers are advised to have an in-depth focus on their athletes’ progression or the impacts of strength trainings by observing and chasing the F-T curve variables such as RFD, net impulse, and RSImod.

Keywords: net impulse, reactive strength index, rate of force development, stretch-shortening cycle

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Authors: Eiji Nakamachi, Tsuyoshi Eguchi, Sayo Yamamoto, Yusuke Morita, H. Sakamoto

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In this study, we aim to reveal the relationship between the meniscal tearing and the articular cartilage injury of knee joint by using the dynamic explicit finite element (FE) method. Meniscal injuries reduce its functional ability and consequently increase the load on the articular cartilage of knee joint. In order to prevent the induction of osteoarthritis (OA) caused by meniscal injuries, many medical treatment techniques, such as artificial meniscus replacement and meniscal regeneration, have been developed. However, it is reported that these treatments are not the comprehensive methods. In order to reveal the fundamental mechanism of OA induction, the mechanical characterization of meniscus under the condition of normal and injured states is carried out by using FE analyses. At first, a FE model of the human knee joint in the case of normal state – ‘intact’ - was constructed by using the magnetron resonance (MR) tomography images and the image construction code, Materialize Mimics. Next, two types of meniscal injury models with the radial tears of medial and lateral menisci were constructed. In FE analyses, the linear elastic constitutive law was adopted for the femur and tibia bones, the visco-hyperelastic constitutive law for the articular cartilage, and the visco-anisotropic hyperelastic constitutive law for the meniscus, respectively. Material properties of articular cartilage and meniscus were identified using the stress-strain curves obtained by our compressive and the tensile tests. The numerical results under the normal walking condition revealed how and where the maximum compressive stress occurred on the articular cartilage. The maximum compressive stress and its occurrence point were varied in the intact and two meniscal tear models. These compressive stress values can be used to establish the threshold value to cause the pathological change for the diagnosis. In this study, FE analyses of knee joint were carried out to reveal the influence of meniscal injuries on the cartilage injury. The following conclusions are obtained. 1. 3D FE model, which consists femur, tibia, articular cartilage and meniscus was constructed based on MR images of human knee joint. The image processing code, Materialize Mimics was used by using the tetrahedral FE elements. 2. Visco-anisotropic hyperelastic constitutive equation was formulated by adopting the generalized Kelvin model. The material properties of meniscus and articular cartilage were determined by curve fitting with experimental results. 3. Stresses on the articular cartilage and menisci were obtained in cases of the intact and two radial tears of medial and lateral menisci. Through comparison with the case of intact knee joint, two tear models show almost same stress value and higher value than the intact one. It was shown that both meniscal tears induce the stress localization in both medial and lateral regions. It is confirmed that our newly developed FE analysis code has a potential to be a new diagnostic system to evaluate the meniscal damage on the articular cartilage through the mechanical functional assessment.

Keywords: finite element analysis, hyperelastic constitutive law, knee joint injury, meniscal tear, stress concentration

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Authors: Pawandeep Kaur, Prashant Garg

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Red mud is a byproduct of aluminum extraction from Bauxite industry. It is dumped in a pond which not only uses thousands of acres of land but having very high pH, it pollutes the ground water and the soil also. Leaves are yet another big waste especially during autumn when they contribute immensely to the blockage of drains and can easily catch fire, among other risks hence also needs to be utilized effectively. The use of leaf ash and red mud in highway construction as a filling material may be an efficient way to dispose of leaf ash and red mud. In this study, leaf ash and lime were used as admixtures to improve the geotechnical engineering properties of red mud. The red mud was taken from National Aluminum Company Limited, Odisha, and leaf ash was locally collected. The aim of present study is to investigate the effect of lime and leaf ash on compaction characteristics and strength characteristics of red mud. California Bearing Ratio and Unconfined Compression Strength tests were performed on red mud by varying different percentages of lime and leaf ash. Leaf ash was added in proportion 2%,4%,6%,8% and 10% whereas lime was added in proportions of 5% to 15%. Optimized value of lime was decided with respect to maximum CBR (California Bearing Ratio) of red mud mixed with different proportions of lime. An increase of 300% in California Bearing ratio of red mud and an increase of 125% in Unconfined Compression Strength values were observed. It may, therefore, be concluded that red mud may be effectively utilized in the highway industry as a filler material.

Keywords: stabilization, lime, red mud, leaf ash

Procedia PDF Downloads 242

Authors: Jose Ruiz, Jose Velasquez, Holger Lovon

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Peruvian university buildings are critical structures for which very little research about its seismic vulnerability is available. This paper develops a probabilistic methodology that predicts seismic loss for university buildings with simulated fragility functions. Two university buildings located in the city of Cusco were analyzed. Fragility functions were developed considering seismic and structural parameters uncertainty. The fragility functions were generated with the Latin Hypercube technique, an improved Montecarlo-based method, which optimizes the sampling of structural parameters and provides at least 100 reliable samples for every level of seismic demand. Concrete compressive strength, maximum concrete strain and yield stress of the reinforcing steel were considered as the key structural parameters. The seismic demand is defined by synthetic records which are compatible with the elastic Peruvian design spectrum. Acceleration records are scaled based on the peak ground acceleration on rigid soil (PGA) which goes from 0.05g to 1.00g. A total of 2000 structural models were considered to account for both structural and seismic variability. These functions represent the overall building behavior because they give rational information regarding damage ratios for defined levels of seismic demand. The university buildings show an expected Mean Damage Factor of 8.80% and 19.05%, respectively, for the 0.22g-PGA scenario, which was amplified by the soil type coefficient and resulted in 0.26g-PGA. These ratios were computed considering a seismic demand related to 10% of probability of exceedance in 50 years which is a requirement in the Peruvian seismic code. These results show an acceptable seismic performance for both buildings.

Keywords: fragility functions, university buildings, loss assessment, Montecarlo simulation, latin hypercube

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Authors: Ainara Lopez-Ortega, Raquel Bayon, Elena Rodriguez, Amaya Igartua

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The materials used in offshore structural applications are continuously subjected to aggressive environmental conditions that accelerate their degradation, thus shortening their useful life. Wear, corrosion and the effect of marine microorganisms are the main processes taking place in marine environments, and whenever they occur simultaneously the durability of materials is strongly reduced. In the present work, the tribocorrosion behaviour of a High-Strength Low-Alloy (HSLA) steel and three coatings commonly used for protecting offshore components has been studied by means of unidirectional tribological tests in synthetic seawater. The coatings were found to enhance the tribological response of the uncoated steel and provide the system with improved corrosion resistance, in terms of smaller material losses and reduction of friction coefficients. The tests were repeated after ageing the materials in a salt-fog cabinet, and the aging process was found to slightly affect the performance of two of the coatings, in terms of higher material losses, meanwhile the third coating was not affected.

Keywords: coatings, corrosion, high-strength low-alloy steel, seawater, tribocorrosion

Procedia PDF Downloads 419

Authors: S. Candamano, A. Iorfida, F. Crea, A. Macario

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Recently, basalt fabric reinforced cementitious composites (FRCM) have attracted great attention because they result to be effective in structural strengthening and cost/environment efficient. In this study, authors investigate their mechanical behavior when an inorganic matrix, belonging to the family of alkali-activated binders, is used. In particular, the matrix has been designed to contain high amounts of industrial by-products and waste, such as Ground Granulated Blast Furnace Slag (GGBFS) and Fly Ash. Fresh state properties, such as workability, mechanical properties and shrinkage behavior of the matrix have been measured, while microstructures and reaction products were analyzed by Scanning Electron Microscopy and X-Ray Diffractometry. Reinforcement is made up of a balanced, coated bidirectional fabric made out of basalt fibres and stainless steel micro-wire, with a mesh size of 8x8 mm and an equivalent design thickness equal to 0.064 mm. Mortars mixes have been prepared by maintaining constant the water/(reactive powders) and sand/(reactive powders) ratios at 0.53 and 2.7 respectively. An appropriate experimental campaign based on direct tensile tests on composite specimens and single-lap shear bond test on brickwork substrate has been thus carried out to investigate their mechanical behavior under tension, the stress-transfer mechanism and failure modes. Tensile tests were carried out on composite specimens of nominal dimensions equal to 500 mm x 50 mm x 10 mm, with 6 embedded rovings in the loading direction. Direct shear tests (DST) were carried out on brickwork substrate using an externally bonded basalt-FRCM composite strip 10 mm thick, 50 mm wide and a bonded length of 300 mm. Mortars exhibit, after 28 days of curing, an average compressive strength of 32 MPa and flexural strength of 5.5 MPa. Main hydration product is a poorly crystalline aluminium-modified calcium silicate hydrate (C-A-S-H) gel. The constitutive behavior of the composite has been identified by means of direct tensile tests, with response curves showing a tri-linear behavior. Test results indicate that the behavior is mainly governed by cracks development (II) and widening (III) up to failure. The ultimate tensile strength and strain were respectively σᵤ = 456 MPa and ɛᵤ= 2.20%. The tensile modulus of elasticity in stage III was EIII= 41 GPa. All single-lap shear test specimens failed due to composite debonding. It occurred at the internal fabric-to-matrix interface, and it was the result of a fracture of the matrix between the fibre bundles. For all specimens, transversal cracks were visible on the external surface of the composite and involved only the external matrix layer. This cracking appears when the interfacial shear stresses increase and slippage of the fabric at the internal matrix layer interface occurs. Since the external matrix layer is bonded to the reinforcement fabric, it translates with the slipped fabric. Average peak load around 945 N, peak stress around 308 MPa and global slip around 6 mm were measured. The preliminary test results allow affirming that Alkali-Activated Materials can be considered a potentially valid alternative to traditional mortars in designing FRCM composites.

Keywords: Alkali-activated binders, Basalt-FRCM composites, direct shear tests, structural strengthening

Procedia PDF Downloads 129

Authors: Stephen Akong Takim

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This study focused on the optimization of the flexural strength of bio-composite samples of palm kernel, whelks, clams, periwinkles shells and bamboo fiber reinforced with resin for engineering applications. The aim of the study was to formulate different samples of bio-composite reinforced with resin for engineering applications and to evaluate the flexural strength of the fabricated composite. The hand lay-up technique was used for the composites produced by incorporating different percentage compositions of the shells/fiber (10%, 15%, 20%, 25% and 30%) into varied proportions of epoxy resin and catalyst. The cured samples, after 24 hours, were subjected to tensile, impact, flexural and water absorption tests. The experiments were conducted using the Taguchi optimization method L25 (5x5) with five design parameters and five level combinations in Minitab 18 statistical software. The results showed that the average value of flexural was 114.87MPa when compared to the unreinforced 72.33MPa bio-composite. The study recommended that agricultural waste, like palm kernel shells, whelk shells, clams, periwinkle shells and bamboo fiber, should be converted into important engineering applications.

Keywords: bio-composite, resin, palm kernel shells, welk shells, periwinkle shells, bamboo fiber, Taguchi techniques and engineering application

Procedia PDF Downloads 77

Authors: Piotr A. Kowalski, Kasper Sapala, Wiktor Warchalowski

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PM10 is a suspended dust that primarily has a negative effect on the respiratory system. PM10 is responsible for attacks of coughing and wheezing, asthma or acute, violent bronchitis. Indirectly, PM10 also negatively affects the rest of the body, including increasing the risk of heart attack and stroke. Unfortunately, Poland is a country that cannot boast of good air quality, in particular, due to large PM concentration levels. Therefore, based on the dense network of Airly sensors, it was decided to deal with the problem of prediction of suspended particulate matter concentration. Due to the very complicated nature of this issue, the Machine Learning approach was used. For this purpose, Convolution Neural Network (CNN) neural networks have been adopted, these currently being the leading information processing methods in the field of computational intelligence. The aim of this research is to show the influence of particular CNN network parameters on the quality of the obtained forecast. The forecast itself is made on the basis of parameters measured by Airly sensors and is carried out for the subsequent day, hour after hour. The evaluation of learning process for the investigated models was mostly based upon the mean square error criterion; however, during the model validation, a number of other methods of quantitative evaluation were taken into account. The presented model of pollution prediction has been verified by way of real weather and air pollution data taken from the Airly sensor network. The dense and distributed network of Airly measurement devices enables access to current and archival data on air pollution, temperature, suspended particulate matter PM1.0, PM2.5, and PM10, CAQI levels, as well as atmospheric pressure and air humidity. In this investigation, PM2.5, and PM10, temperature and wind information, as well as external forecasts of temperature and wind for next 24h served as inputted data. Due to the specificity of the CNN type network, this data is transformed into tensors and then processed. This network consists of an input layer, an output layer, and many hidden layers. In the hidden layers, convolutional and pooling operations are performed. The output of this system is a vector containing 24 elements that contain prediction of PM10 concentration for the upcoming 24 hour period. Over 1000 models based on CNN methodology were tested during the study. During the research, several were selected out that give the best results, and then a comparison was made with the other models based on linear regression. The numerical tests carried out fully confirmed the positive properties of the presented method. These were carried out using real ‘big’ data. Models based on the CNN technique allow prediction of PM10 dust concentration with a much smaller mean square error than currently used methods based on linear regression. What's more, the use of neural networks increased Pearson's correlation coefficient (R²) by about 5 percent compared to the linear model. During the simulation, the R² coefficient was 0.92, 0.76, 0.75, 0.73, and 0.73 for 1st, 6th, 12th, 18th, and 24th hour of prediction respectively.

Keywords: air pollution prediction (forecasting), machine learning, regression task, convolution neural networks

Procedia PDF Downloads 149

Authors: Rachnavy Pornthep, Khaothin Thawichai

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The purpose of this paper was to investigate the effects of rowing ergometer exercise on older persons health. The subjects were divided into two groups. Group 1 was control group (10 male and 10 female) Group 2 was experimental group (10 male and 10 female). The time for study was 12 week. Group 1 engage in normal daily activities Group 2 Training with rowing machine for 20 minutes three days a week. The average age of the experimental group was 73.7 years old, mean weight 55.4 kg, height 154.8 cm in the control group, mean age was 74.95 years, mean weight 48.6 kg, mean height 153.85 cm. Physical fitness test composted of body size, flexibility, Strength, muscle endurance and cardiovascular endurance. The comparison between the experimental and control groups before training showed that body weight, body mass index and waist to hip ratio were significantly different. The flexibility, strength, cardiovascular endurance was not significantly different. The comparison between the control group and the experimental group after training showed that body weight, body mass index and cardiovascular endurance were significantly different. The ratio of waist to hips, flexibility and muscular strength were not significantly different. Comparison of physical fitness before training and after training of the control group showed that body weight, flexibility (Sit and reach) and muscular strength (30 – Second chair stand) were significantly different. Body mass index, waist to hip ratio, muscles flexible (Shoulder girdle flexibility), muscle strength (30 – Second arm curl) and the cardiovascular endurance were not significantly difference. Comparison of physical fitness before training and after training the experimental group showed that waist to hip ratio, flexibility (sit and reach) muscle strength (30 – Second chair stand), cardiovascular endurance (Standing leg raises - up to 2 minutes) were significantly different. The Body mass index and the flexibility (Shoulder girdle flexibility) no significantly difference. The study found that exercising with rowing machine can improve the physical fitness of the elderly, especially the cardiovascular endurance, corresponding with the past research on the effects of exercise in the elderly with different exercise such as cycling, treadmill, walking on the elliptical machine. Therefore, we can conclude that exercise by using rowing machine can improve cardiovascular system and flexibility in the elderly.

Keywords: effect, rowing, exercise, elderly

Procedia PDF Downloads 495

Authors: M. N. Baig, F. N. Khan, M. Junaid

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Titanium alloys are widely employed in aerospace, medical, chemical, and marine applications. These alloys offer many advantages such as low specific weight, high strength to weight ratio, excellent corrosion resistance, high melting point and good fatigue behavior. These attractive properties make titanium alloys very unique and therefore they require special attention in all areas of processing, especially welding. In this work, 1.6 mm thick sheets of Ti-5Al-2,5Sn, an alpha titanium (α-Ti) alloy, were welded using electron beam (EBW) and laser beam (LBW) welding processes to achieve a full penetration Bead-on Plate (BoP) configuration. The weldments were studied using polarized optical microscope, SEM, EDS and XRD. Microhardness distribution across the weld zone and smooth and notch tensile strengths of the weldments were also recorded. Residual stresses using Hole-drill Strain Measurement (HDSM) method and deformation patterns of the weldments were measured for the purpose of comparison of the two welding processes. Fusion zone widths of both EBW and LBW weldments were found to be approximately equivalent owing to fairly similar high power densities of both the processes. Relatively less oxide content and consequently high joint quality were achieved in EBW weldment as compared to LBW due to vacuum environment and absence of any shielding gas. However, an increase in heat-affected zone width and partial ά-martensitic transformation infusion zone of EBW weldment were observed because of lesser cooling rates associated with EBW as compared with LBW. The microstructure infusion zone of EBW weldment comprised both acicular α and ά martensite within the prior β grains whereas complete ά martensitic transformation was observed within the fusion zone of LBW weldment. Hardness of the fusion zone in EBW weldment was found to be lower than the fusion zone of LBW weldment due to the observed microstructural differences. Notch tensile specimen of LBW exhibited higher load capacity, ductility, and absorbed energy as compared with EBW specimen due to the presence of high strength ά martensitic phase. It was observed that the sheet deformation and deformation angle in EBW weldment were more than LBW weldment due to relatively more heat retention in EBW which led to more thermal strains and hence higher deformations and deformation angle. The lowest residual stresses were found in LBW weldments which were tensile in nature. This was owing to high power density and higher cooling rates associated with LBW process. EBW weldment exhibited highest compressive residual stresses due to which the service life of EBW weldment is expected to improve.

Keywords: Laser and electron beam welding, Microstructure and mechanical properties, Residual stress and distortions, Titanium alloys

Procedia PDF Downloads 226

Authors: Amadou Wurry Jallow, Adama N. S. Bah, Karamo Bah, Shih-Ye Wang, Kuo-Chung Chu, Chien-Yeh Hsu

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Chronic kidney disease (CKD) is a major public health challenge with high prevalence, rising incidence, and serious adverse consequences. Developing effective risk prediction models is a cost-effective approach to predicting and preventing complications of chronic kidney disease (CKD). This study aimed to develop an accurate machine learning model that can dynamically identify individuals at risk of CKD using various kinds of diagnostic data, with or without laboratory data, at different follow-up points. Creatinine is a key component used to predict CKD. These models will enable affordable and effective screening for CKD even with incomplete patient data, such as the absence of creatinine testing. This retrospective cohort study included data on 19,429 adults provided by a private research institute and screening laboratory in Taiwan, gathered between 2001 and 2015. Univariate Cox proportional hazard regression analyses were performed to determine the variables with high prognostic values for predicting CKD. We then identified interacting variables and grouped them according to diagnostic data categories. Our models used three types of data gathered at three points in time: non-laboratory, laboratory, and metabolic indices data. Next, we used subgroups of variables within each category to train two machine learning models (Random Forest and XGBoost). Our machine learning models can dynamically discriminate individuals at risk for developing CKD. All the models performed well using all three kinds of data, with or without laboratory data. Using only non-laboratory-based data (such as age, sex, body mass index (BMI), and waist circumference), both models predict chronic kidney disease as accurately as models using laboratory and metabolic indices data. Our machine learning models have demonstrated the use of different categories of diagnostic data for CKD prediction, with or without laboratory data. The machine learning models are simple to use and flexible because they work even with incomplete data and can be applied in any clinical setting, including settings where laboratory data is difficult to obtain.

Keywords: chronic kidney disease, glomerular filtration rate, creatinine, novel metabolic indices, machine learning, risk prediction

Procedia PDF Downloads 105

Authors: Sivakumar Singaravelu, Giriprasath Ramanathan, M. D. Raja, Uma Tirichurapalli Sivagnanam

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The goal of the present study was to develop and evaluate composite film for tissue engineering application. The keratin was extracted from bovine horn and used for preparation of keratin (HK), physiologically clotted fibrin (PCF) and gelatin (G) blend films in different stoichiometric ratios (1:1:1, 1:1:2 and 1:1:3) by using solvent casting method. The composite films (HK-PCF-G) were characterized physiochemically using Fourier Transform Infrared Spectroscopy (FTIR), Differential Scanning Calorimetry (DSC), Thermogravimetric Analysis (TGA) and Scanning Electron Microscopy (SEM). The mechanical properties of the composite films were analyzed. The results of tensile strength show that ultimate strength and elongation were 10.72 Mpa and 4.83 MPA respectively for 1:1:3 ratio combination. The SEM image showed a slight smooth surface for 1:1:3 ratio combination compared to other films. In order to impart antibacterial activities, the composite films were loaded with Mupirocin (MP) to act against infection. The composite films acted as a suitable carrier to protect and release the drug in a controlled manner. This developed composite film would be a suitable alternative material for tissue engineering application.

Keywords: bovine horn, keratin, fibrin, gelatin, tensile strength

Procedia PDF Downloads 449

Authors: Omar Al Denali, Abdelaziz Badi

Abstract:

The ASTM A516 Grade 70 steel is a suitable material used for the fabrication of boiler pressure vessels working in moderate and lower temperature services, and it has good weldability and excellent notch toughness. The post-weld heat treatment (PWHT) or stress-relieving heat treatment has significant effects on avoiding the martensite transformation and resulting in high hardness, which can lead to cracking in the heat-affected zone (HAZ). An adaptive neuro-fuzzy inference system (ANFIS) was implemented to predict the material tensile strength of post-weld heat treatment (PWHT) experiments. The ANFIS models presented excellent predictions, and the comparison was carried out based on the mean absolute percentage error between the predicted values and the experimental values. The ANFIS model gave a Mean Absolute Percentage Error of 0.556 %, which confirms the high accuracy of the model.

Keywords: prediction, post-weld heat treatment, adaptive neuro-fuzzy inference system, mean absolute percentage error

Procedia PDF Downloads 153