Search results for: gel strength prediction
4353 From By-product To Brilliance: Transforming Adobe Brick Construction Using Meat Industry Waste-derived Glycoproteins
Authors: Amal Balila, Maria Vahdati
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Earth is a green building material with very low embodied energy and almost zero greenhouse gas emissions. However, it lacks strength and durability in its natural state. By responsibly sourcing stabilisers, it's possible to enhance its strength. This research draws inspiration from the robustness of termite mounds, where termites incorporate glycoproteins from their saliva during construction. Biomimicry explores the potential of these termite stabilisers in producing bio-inspired adobe bricks. The meat industry generates significant waste during slaughter, including blood, skin, bones, tendons, gastrointestinal contents, and internal organs. While abundant, many meat by-products raise concerns regarding human consumption, religious orders, cultural and ethical beliefs, and also heavily contribute to environmental pollution. Extracting and utilising proteins from this waste is vital for reducing pollution and increasing profitability. Exploring the untapped potential of meat industry waste, this research investigates how glycoproteins could revolutionize adobe brick construction. Bovine serum albumin (BSA) from cows' blood and mucin from porcine stomachs were the chosen glycoproteins used as stabilisers for adobe brick production. Despite their wide usage across various fields, they have very limited utilisation in food processing. Thus, both were identified as potential stabilisers for adobe brick production in this study. Two soil types were utilised to prepare adobe bricks for testing, comparing controlled unstabilised bricks with glycoprotein-stabilised ones. All bricks underwent testing for unconfined compressive strength and erosion resistance. The primary finding of this study is the efficacy of BSA, a glycoprotein derived from cows' blood and a by-product of the beef industry, as an earth construction stabiliser. Adding 0.5% by weight of BSA resulted in a 17% and 41% increase in the unconfined compressive strength for British and Sudanese adobe bricks, respectively. Further, adding 5% by weight of BSA led to a 202% and 97% increase in the unconfined compressive strength for British and Sudanese adobe bricks, respectively. Moreover, using 0.1%, 0.2%, and 0.5% by weight of BSA resulted in erosion rate reductions of 30%, 48%, and 70% for British adobe bricks, respectively, with a 97% reduction observed for Sudanese adobe bricks at 0.5% by weight of BSA. However, mucin from the porcine stomach did not significantly improve the unconfined compressive strength of adobe bricks. Nevertheless, employing 0.1% and 0.2% by weight of mucin resulted in erosion rate reductions of 28% and 55% for British adobe bricks, respectively. These findings underscore BSA's efficiency as an earth construction stabiliser for wall construction and mucin's efficacy for wall render, showcasing their potential for sustainable and durable building practices.Keywords: biomimicry, earth construction, industrial waste management, sustainable building materials, termite mounds.
Procedia PDF Downloads 514352 An Approach for Pattern Recognition and Prediction of Information Diffusion Model on Twitter
Authors: Amartya Hatua, Trung Nguyen, Andrew Sung
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In this paper, we study the information diffusion process on Twitter as a multivariate time series problem. Our model concerns three measures (volume, network influence, and sentiment of tweets) based on 10 features, and we collected 27 million tweets to build our information diffusion time series dataset for analysis. Then, different time series clustering techniques with Dynamic Time Warping (DTW) distance were used to identify different patterns of information diffusion. Finally, we built the information diffusion prediction models for new hashtags which comprise two phrases: The first phrase is recognizing the pattern using k-NN with DTW distance; the second phrase is building the forecasting model using the traditional Autoregressive Integrated Moving Average (ARIMA) model and the non-linear recurrent neural network of Long Short-Term Memory (LSTM). Preliminary results of performance evaluation between different forecasting models show that LSTM with clustering information notably outperforms other models. Therefore, our approach can be applied in real-world applications to analyze and predict the information diffusion characteristics of selected topics or memes (hashtags) in Twitter.Keywords: ARIMA, DTW, information diffusion, LSTM, RNN, time series clustering, time series forecasting, Twitter
Procedia PDF Downloads 3914351 Spillage Prediction Using Fluid-Structure Interaction Simulation with Coupled Eulerian-Lagrangian Technique
Authors: Ravi Soni, Irfan Pathan, Manish Pande
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The current product development process needs simultaneous consideration of different physics. The performance of the product needs to be considered under both structural and fluid loads. Examples include ducts and valves where structural behavior affects fluid motion and vice versa. Simulation of fluid-structure interaction involves modeling interaction between moving components and the fluid flow. In these scenarios, it is difficult to calculate the damping provided by fluid flow because of dynamic motions of components and the transient nature of the flow. Abaqus Explicit offers general capabilities for modeling fluid-structure interaction with the Coupled Eulerian-Lagrangian (CEL) method. The Coupled Eulerian-Lagrangian technique has been used to simulate fluid spillage through fuel valves during dynamic closure events. The technique to simulate pressure drops across Eulerian domains has been developed using stagnation pressure. Also, the fluid flow is calculated considering material flow through elements at the outlet section of the valves. The methodology has been verified on Eaton products and shows a good correlation with the test results.Keywords: Coupled Eulerian-Lagrangian Technique, fluid structure interaction, spillage prediction, stagnation pressure
Procedia PDF Downloads 3794350 Phase Optimized Ternary Alloy Material for Gas Turbines
Authors: Mayandi Ramanathan
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Gas turbine blades see the most aggressive thermal stress conditions within the engine, due to Turbine Entry Temperatures in the range of 1500 to 1600°C, but in synchronization with other functional components, they must readily deliver efficient performance, whilst incurring minimal overhaul and repair costs during its service life up to 5 million flying miles. The blades rotate at very high rotation rates and remove significant amount of thermal power from the gas stream. At high temperatures the major component failure mechanism is creep. During its service over time under high temperatures and loads, the blade will deform, lengthen and rupture. High strength and stiffness in the longitudinal direction up to elevated service temperatures are certainly the most needed properties of turbine blades. The proposed advanced Ti alloy material needs a process that provides strategic orientation of metallic ordering, uniformity in composition and high metallic strength. 25% Ta/(Al+Ta) ratio ensures TaAl3 phase formation, where as 51% Al/(Al+Ti) ratio ensures formation of α-Ti3Al and γ-TiAl mixed phases fand the three phase combination ensures minimal Al excess (~1.4% Al excess), unlike Ti-47Al-2Cr-2Nb which has significant excess Al (~5% Al excess) that could affect the service life of turbine blades. This presentation will involve the summary of additive manufacturing and heat treatment process conditions to fabricate turbine blade with Ti-43Al matrix alloyed with optimized amount of refractory Ta metal. Summary of thermo-mechanical test results such as high temperature tensile strength, creep strain rate, thermal expansion coefficient and fracture toughness will be presented. Improvement in service temperature of the turbine blades and corrosion resistance dependence on coercivity of the alloy material will be reported. Phase compositions will be quantified, and a summary of its correlation with creep strain rate will be presented.Keywords: gas turbine, aerospace, specific strength, creep, high temperature materials, alloys, phase optimization
Procedia PDF Downloads 1814349 High Performance Wood Shear Walls and Dissipative Anchors for Damage Limitation
Authors: Vera Wilden, Benno Hoffmeister, Georgios Balaskas, Lukas Rauber, Burkhard Walter
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Light-weight timber frame elements represent an efficient structural solution for wooden multistory buildings. The wall elements of such buildings – which act as shear diaphragms- provide lateral stiffness and resistance to wind and seismic loads. The tendency towards multi-story structures leads to challenges regarding the prediction of stiffness, strength and ductility of the buildings. Lightweight timber frame elements are built up of several structural parts (sheeting, fasteners, frame, support and anchorages); each of them contributing to the dynamic response of the structure. This contribution describes the experimental and numerical investigation and development of enhanced lightweight timber frame buildings. These developments comprise high-performance timber frame walls with the variable arrangements of sheathing planes and dissipative anchors at the base of the timber buildings, which reduce damages to the timber structure and can be exchanged after significant earthquakes. In order to prove the performance of the developed elements in the context of a real building a full-scale two-story building core was designed and erected in the laboratory and tested experimentally for its seismic performance. The results of the tests and a comparison of the test results to the predicted behavior are presented. Observation during the test also reveals some aspects of the design and details which need to consider in the application of the timber walls in the context of the complete building.Keywords: dissipative anchoring, full scale test, push-over-test, wood shear walls
Procedia PDF Downloads 2464348 Assessment of the Thermal and Mechanical Properties of Bio-based Composite Materials for Thermal Insulation
Authors: Nega Tesfie Asfaw, Rafik Absi, Labouda B. A, Ikram El Abbassi
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Composite materials have come to the fore a few decades ago because of their superior insulation performances. Recycling natural fiber composites and natural fiber reinforcement of waste materials are other steps for conserving resources and the environment. This paper reviewed the Thermal properties (Thermal conductivity, Effusivity, and Diffusivity) and Mechanical properties (Compressive strength, Flexural strength, and Tensile strength) of bio-composite materials for thermal insulation in the construction industry. For several years, the development of the building materials industry has placed a special emphasis on bio-source materials. According to recent studies, most natural fibers have good thermal insulating qualities and good mechanical properties. To determine the thermal and mechanical performance of bio-composite materials in construction most research used experimental methods. the results of the study show that these natural fibers have allowed us to optimize energy consumption in a building and state that density, porosity, percentage of fiber, the direction of heat flow orientation of the fiber, and the shape of the specimen are the main elements that limit the thermal performance and also showed that density, porosity, Type of Fiber, Fiber length, orientation and weight percentage loading, Fiber-matrix adhesion, Choice of the polymer matrix, Presence of void are the main elements that limit the mechanical performance of the insulation material. Based on the results of this reviewed paper Moss fibers (0.034W/ (m. K)), Wood Fiber (0.043 W/ (m. K)), Wheat straw (0.046 W/ (m. K), and corn husk fibers (0.046 W/ (m. K) are a most promising solution for energy efficiency for construction industry with interesting insulation properties and with good acceptable mechanical properties. Finally, depending on the best fibers used for insulation applications in the construction sector, the thermal performance rate of various fibers reviewed in this article are analyzed. Due to Typha's high porosity, the results indicated that Typha australis fiber had a better thermal performance rate of 89.03% with clay.Keywords: bio-based materials, thermal conductivity, compressive strength, thermal performance
Procedia PDF Downloads 274347 Geopolymer Concrete: A Review of Properties, Applications and Limitations
Authors: Abbas Ahmed Albu Shaqraa
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The concept of a safe environment and low greenhouse gas emissions is a common concern especially in the construction industry. The produced carbon dioxide (CO2) emissions are nearly a ton in producing only one ton of Portland cement, which is the primary ingredient of concrete. Current studies had investigated the utilization of several waste materials in producing a cement free concrete. The geopolymer concrete is a green material that results from the reaction of aluminosilicate material with an alkaline liquid. A summary of several recent researches in geopolymer concrete will be presented in this manuscript. In addition, the offered presented review considers the use of several waste materials including fly ash, granulated blast furnace slag, cement kiln dust, kaolin, metakaolin, and limestone powder as binding materials in making geopolymer concrete. Moreover, the mechanical, chemical and thermal properties of geopolymer concrete will be reviewed. In addition, the geopolymer concrete applications and limitations will be discussed as well. The results showed a high early compressive strength gain in geopolymer concrete when dry- heating or steam curing was performed. Also, it was stated that the outstanding acidic resistance of the geopolymer concrete made it possible to be used where the ordinary Portland cement concrete was doubtable. Thus, the commercial geopolymer concrete pipes were favored for sewer system in case of high acidic conditions. Furthermore, it was reported that the geopolymer concrete could stand up to 1200 °C in fire without losing its strength integrity whereas the Portland cement concrete was losing its function upon heating to some 100s °C only. However, the geopolymer concrete still considered as an emerging field and occupied mainly by the precast industries.Keywords: geopolymer concrete, Portland cement concrete, alkaline liquid, compressive strength
Procedia PDF Downloads 2214346 The Effect of the Low Plastic Fines on the Shear Strength and Mechanical Behavior of Granular Classes of Sand-Silt Mixtures
Authors: El Metmati Abdelhaq
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Shear strength of sandy soils has been considered as the important parameter to study the stability of different civil engineering structures when subjected to monotonic, cyclic and earthquake loading conditions. The objective of this laboratory investigation is to study the influence of the fraction of low plastic fines and gradation on the mechanical behavior of sand-silt mixtures reconstituted in the laboratory. For this purpose, a series of Casagrande shear box tests were carried out on different reconstituted samples of sand-silt mixtures with various gradations at two initial relative densities (Dr = 20 and 91 %) with different fines content ranging from 0 to 40 %. The soil samples were tested under different normal stresses (100, 200 and 300 kPa). The evaluation of the data indicates that the fines content and the gradation have significant influence on the friction angle and the cohesion.Keywords: mechanical behavior, silty sand, friction angle, cohesion, fines content
Procedia PDF Downloads 3724345 Study on the Mechanical Properties of Bamboo Fiber-Reinforced Polypropylene Based Composites: Effect of Gamma Radiation
Authors: Kamrun N. Keya, Nasrin A. Kona, Ruhul A. Khan
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Bamboo fiber (BF) reinforced polypropylene (PP) based composites were fabricated by a conventional compression molding technique. In this investigation, bamboo composites were manufactured using different percentages of fiber, which were varying from 25-65% on the total weight of the composites. To fabricate the BF/PP composites untreated and treated fibers were selected. A systematic study was done to observe the physical, mechanical, and interfacial behavior of the composites. In this study, mechanical properties of the composites such as tensile, impact, and bending properties were observed precisely. Maximum tensile strength (TS) and bending strength (BS) were found for 50 wt% fiber composites, 65 MPa, and 85.5 MPa respectively, whereas the highest tensile modulus (TM) and bending modulus (BM) was examined, 5.73 GPa and 7.85 GPa respectively. The BF/PP based composites were treated with irradiated under gamma radiation (the source strength 50 kCi Cobalt-60) of various doses (i.e. 10, 20, 30, 40, 50 and 60 kGy doses). The effect of gamma radiation on the composites was also investigated, and it found that the effect of 30.0 kGy (i.e. units for radiation measurement is 'gray', kGy=kilogray) gamma dose showed better mechanical properties than other doses. After flexural testing, fracture sides of the untreated and treated both composites were studied by scanning electron microscope (SEM). SEM results of the treated BF/PP based composites showed better fiber-matrix adhesion and interfacial bonding than untreated BF/PP based composites. Water uptake and soil degradation tests of untreated and treated composites were also investigated.Keywords: bamboo fiber, polypropylene, compression molding technique, gamma radiation, mechanical properties, scanning electron microscope
Procedia PDF Downloads 1334344 A Predictive Model for Turbulence Evolution and Mixing Using Machine Learning
Authors: Yuhang Wang, Jorg Schluter, Sergiy Shelyag
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The high cost associated with high-resolution computational fluid dynamics (CFD) is one of the main challenges that inhibit the design, development, and optimisation of new combustion systems adapted for renewable fuels. In this study, we propose a physics-guided CNN-based model to predict turbulence evolution and mixing without requiring a traditional CFD solver. The model architecture is built upon U-Net and the inception module, while a physics-guided loss function is designed by introducing two additional physical constraints to allow for the conservation of both mass and pressure over the entire predicted flow fields. Then, the model is trained on the Large Eddy Simulation (LES) results of a natural turbulent mixing layer with two different Reynolds number cases (Re = 3000 and 30000). As a result, the model prediction shows an excellent agreement with the corresponding CFD solutions in terms of both spatial distributions and temporal evolution of turbulent mixing. Such promising model prediction performance opens up the possibilities of doing accurate high-resolution manifold-based combustion simulations at a low computational cost for accelerating the iterative design process of new combustion systems.Keywords: computational fluid dynamics, turbulence, machine learning, combustion modelling
Procedia PDF Downloads 914343 Properties of Self-Compacting Concrete Mixed with Fly Ash
Authors: Abhinandan Singh Gill, Gurbir Kaur Jawanda
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Since the introduction of self-consolidating concrete (SCC) in Japan during the late 1980’s, acceptance and usage of this concrete in the construction industry has been steadily gaining momentum. In the United States, the usage of SCC has been spearheaded by the precast concrete industry. Good SCC must possess the following key fresh properties: filling ability, passing ability, and resistance to segregation. Self-compacting concrete is one of 'the most revolutionary developments' in concrete research; this concrete is able to flow and to fill the most restocked places of the form work without vibration. There are several methods for testing its properties. In the fresh state: the most frequently used are slump flow test, L box and V-funnel. This work presents properties of self-compacting concrete, mixed with fly ash. The test results for acceptance characteristics of self-compacting concrete such as slump flow; V-funnel and L-Box are presented. Further, the compressive strength at the ages of 7, 28 days was also determined and results are included here.Keywords: compressive strength, fly ash, self-compacting concrete, slump flow test, super plasticizer
Procedia PDF Downloads 4114342 Developing Sustainable Rammed Earth Material Using Pulp Mill Fly Ash as Cement Replacement
Authors: Amin Ajabi, Chinchu Cherian, Sumi Siddiqua
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Rammed earth (RE) is a traditional soil-based building material made by compressing a mixture of natural earth and binder ingredients such as chalk or lime, in temporary formworks. However, the modern RE uses 5 to 10% cement as a binder in order to meet the strength and durability requirements as per the standard specifications and guidelines. RE construction is considered to be an energy-efficient and environmental-friendly approach when compared to conventional concrete systems, which use 20 to 30% cement. The present study aimed to develop RE mix designs by utilizing non-hazardous wood-based fly ash generated by pulp and paper mills as a partial replacement for cement. The pulp mill fly ash (PPFA)-stabilized RE is considered to be a sustainable approach keeping in view of the massive carbon footprints associated with cement production as well as the adverse environmental impacts due to disposal of PPFA in landfills. For the experimental study, as-received PPFA, as well as PPFA-based geopolymer (synthesized by alkaline activation method), were incorporated as cement substitutes in the RE mixtures. Initially, local soil was collected and characterized by index and engineering properties. The PPFA was procured from a pulp manufacturing mill, and its physicochemical, mineralogical and morphological characterization, as well as environmental impact assessment, was conducted. Further, the various mix designs of RE material incorporating local soil and different proportions of cement, PPFA, and alkaline activator (a mixture of sodium silicate and sodium hydroxide solutions) were developed. The compacted RE specimens were cured and tested for 7-day and 28-day unconfined compressive strength (UCS) variations. Based on UCS results, the optimum mix design was identified corresponding to maximum strength improvement. Further, the cured RE specimens were subjected to freeze-thaw cycle testing for evaluating its performance and durability as a sustainable construction technique under extreme climatic conditions.Keywords: sustainability, rammed earth, stabilization, pulp mill fly ash, geopolymer, alkaline activation, strength, durability
Procedia PDF Downloads 994341 Effect of Forging Pressure on Mechanical Properties and Microstructure of Similar and Dissimilar Friction Welded Joints (Aluminium, Copper, Steel)
Authors: Sagar Pandit
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The present work focuses on the effect of various process parameters on the mechanical properties and microstructure of joints produced by continuous drive friction welding and linear friction welding. An attempt is made to investigate the feasibility of obtaining an acceptable weld joint between similar as well as dissimilar components and the microstructural changes have also been assessed once the good weld joints were considered (using Optical Microscopy and Scanning Electron Microscopy techniques). The impact of forging pressure in the microstructure of the weld joint has been studied and the variation in joint strength with varying forge pressure is analyzed. The weld joints were obtained two pair of dissimilar materials and one pair of similar materials, which are listed respectively as: Al-AA5083 & Cu-C101 (dissimilar), Aluminium alloy-3000 series & Mild Steel (dissimilar) and High Nitrogen Austenitic Stainless Steel pair (similar). Intermetallic phase formation was observed at the weld joints in the Al-Cu joint, which consequently harmed the properties of the joint (less tensile strength). It was also concluded that the increase in forging pressure led to both increment and decrement in the tensile strength of the joint depending on the similarity or dissimilarity of the components. The hardness was also observed to possess maximum as well as minimum values at the weld joint depending on the similarity or dissimilarity of workpieces. It was also suggested that a higher forging pressure is needed to obtain complete joining for the formation of the weld joint.Keywords: forging pressure, friction welding, mechanical properties, microstructure
Procedia PDF Downloads 1184340 The Prediction of Reflection Noise and Its Reduction by Shaped Noise Barriers
Authors: I. L. Kim, J. Y. Lee, A. K. Tekile
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In consequence of the very high urbanization rate of Korea, the number of traffic noise damages in areas congested with population and facilities is steadily increasing. The current environmental noise levels data in major cities of the country show that the noise levels exceed the standards set for both day and night times. This research was about comparative analysis in search for optimal soundproof panel shape and design factor that can minimize sound reflection noise. In addition to the normal flat-type panel shape, the reflection noise reduction of swelling-type, combined swelling and curved-type, and screen-type were evaluated. The noise source model Nord 2000, which often provides abundant information compared to models for the similar purpose, was used in the study to determine the overall noise level. Based on vehicle categorization in Korea, the noise levels for varying frequency from different heights of the sound source (directivity heights of Harmonize model) have been calculated for simulation. Each simulation has been made using the ray-tracing method. The noise level has also been calculated using the noise prediction program called SoundPlan 7.2, for comparison. The noise level prediction was made at 15m (R1), 30 m (R2) and at middle of the road, 2m (R3) receiving the point. By designing the noise barriers by shape and running the prediction program by inserting the noise source on the 2nd lane to the noise barrier side, among the 6 lanes considered, the reflection noise slightly decreased or increased in all noise barriers. At R1, especially in the cases of the screen-type noise barriers, there was no reduction effect predicted in all conditions. However, the swelling-type showed a decrease of 0.7~1.2 dB at R1, performing the best reduction effect among the tested noise barriers. Compared to other forms of noise barriers, the swelling-type was thought to be the most suitable for reducing the reflection noise; however, since a slight increase was predicted at R2, further research based on a more sophisticated categorization of related design factors is necessary. Moreover, as swellings are difficult to produce and the size of the modules are smaller than other panels, it is challenging to install swelling-type noise barriers. If these problems are solved, its applicable region will not be limited to other types of noise barriers. Hence, when a swelling-type noise barrier is installed at a downtown region where the amount of traffic is increasing every day, it will both secure visibility through the transparent walls and diminish any noise pollution due to the reflection. Moreover, when decorated with shapes and design, noise barriers will achieve a visual attraction than a flat-type one and thus will alleviate any psychological hardships related to noise, other than the unique physical soundproofing functions of the soundproof panels.Keywords: reflection noise, shaped noise barriers, sound proof panel, traffic noise
Procedia PDF Downloads 5094339 Using Soil Texture Field Observations as Ordinal Qualitative Variables for Digital Soil Mapping
Authors: Anne C. Richer-De-Forges, Dominique Arrouays, Songchao Chen, Mercedes Roman Dobarco
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Most of the digital soil mapping (DSM) products rely on machine learning (ML) prediction models and/or the use or pedotransfer functions (PTF) in which calibration data come from soil analyses performed in labs. However, many other observations (often qualitative, nominal, or ordinal) could be used as proxies of lab measurements or as input data for ML of PTF predictions. DSM and ML are briefly described with some examples taken from the literature. Then, we explore the potential of an ordinal qualitative variable, i.e., the hand-feel soil texture (HFST) estimating the mineral particle distribution (PSD): % of clay (0-2µm), silt (2-50µm) and sand (50-2000µm) in 15 classes. The PSD can also be measured by lab measurements (LAST) to determine the exact proportion of these particle-sizes. However, due to cost constraints, HFST are much more numerous and spatially dense than LAST. Soil texture (ST) is a very important soil parameter to map as it is controlling many of the soil properties and functions. Therefore, comes an essential question: is it possible to use HFST as a proxy of LAST for calibration and/or validation of DSM predictions of ST? To answer this question, the first step is to compare HFST with LAST on a representative set where both information are available. This comparison was made on ca 17,400 samples representative of a French region (34,000 km2). The accuracy of HFST was assessed, and each HFST class was characterized by a probability distribution function (PDF) of its LAST values. This enables to randomly replace HFST observations by LAST values while respecting the PDF previously calculated and results in a very large increase of observations available for the calibration or validation of PTF and ML predictions. Some preliminary results are shown. First, the comparison between HFST classes and LAST analyses showed that accuracies could be considered very good when compared to other studies. The causes of some inconsistencies were explored and most of them were well explained by other soil characteristics. Then we show some examples applying these relationships and the increase of data to several issues related to DSM. The first issue is: do the PDF functions that were established enable to use HSFT class observations to improve the LAST soil texture prediction? For this objective, we replaced all HFST for topsoil by values from the PDF 100 time replicates). Results were promising for the PTF we tested (a PTF predicting soil water holding capacity). For the question related to the ML prediction of LAST soil texture on the region, we did the same kind of replacement, but we implemented a 10-fold cross-validation using points where we had LAST values. We obtained only preliminary results but they were rather promising. Then we show another example illustrating the potential of using HFST as validation data. As in numerous countries, the HFST observations are very numerous; these promising results pave the way to an important improvement of DSM products in all the countries of the world.Keywords: digital soil mapping, improvement of digital soil mapping predictions, potential of using hand-feel soil texture, soil texture prediction
Procedia PDF Downloads 2244338 Mechanical Properties of the Palm Fibers Reinforced HDPE Composites
Authors: Daniella R. Mulinari, Araujo J. F. Marina, Gabriella S. Lopes
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Natural fibers are used in polymer composites to improve mechanical properties, substituting inorganic reinforcing agents produced by non-renewable resources. The present study investigates the tensile, flexural and impact behaviors of palm fibers-high density polyethylene (HDPE) composite as a function of volume fraction. The surface of the fibers was modified by mercerization treatments to improve the wetting behavior of the apolar HDPE. The treatment characterization was obtained by scanning electron microscopy, X-Ray diffraction and infrared spectroscopy. Results evidence that a good adhesion interfacial between fibers-matrix causing an increase strength and modulus flexural as well as impact strength in the modified fibers/HDPE composites when compared to the pure HDPE and unmodified fibers reinforced composites.Keywords: palm fibers, polymer composites, mechanical properties, high density polyethylene (HDPE)
Procedia PDF Downloads 3974337 Prediction of Coronary Artery Stenosis Severity Based on Machine Learning Algorithms
Authors: Yu-Jia Jian, Emily Chia-Yu Su, Hui-Ling Hsu, Jian-Jhih Chen
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Coronary artery is the major supplier of myocardial blood flow. When fat and cholesterol are deposit in the coronary arterial wall, narrowing and stenosis of the artery occurs, which may lead to myocardial ischemia and eventually infarction. According to the World Health Organization (WHO), estimated 740 million people have died of coronary heart disease in 2015. According to Statistics from Ministry of Health and Welfare in Taiwan, heart disease (except for hypertensive diseases) ranked the second among the top 10 causes of death from 2013 to 2016, and it still shows a growing trend. According to American Heart Association (AHA), the risk factors for coronary heart disease including: age (> 65 years), sex (men to women with 2:1 ratio), obesity, diabetes, hypertension, hyperlipidemia, smoking, family history, lack of exercise and more. We have collected a dataset of 421 patients from a hospital located in northern Taiwan who received coronary computed tomography (CT) angiography. There were 300 males (71.26%) and 121 females (28.74%), with age ranging from 24 to 92 years, and a mean age of 56.3 years. Prior to coronary CT angiography, basic data of the patients, including age, gender, obesity index (BMI), diastolic blood pressure, systolic blood pressure, diabetes, hypertension, hyperlipidemia, smoking, family history of coronary heart disease and exercise habits, were collected and used as input variables. The output variable of the prediction module is the degree of coronary artery stenosis. The output variable of the prediction module is the narrow constriction of the coronary artery. In this study, the dataset was randomly divided into 80% as training set and 20% as test set. Four machine learning algorithms, including logistic regression, stepwise regression, neural network and decision tree, were incorporated to generate prediction results. We used area under curve (AUC) / accuracy (Acc.) to compare the four models, the best model is neural network, followed by stepwise logistic regression, decision tree, and logistic regression, with 0.68 / 79 %, 0.68 / 74%, 0.65 / 78%, and 0.65 / 74%, respectively. Sensitivity of neural network was 27.3%, specificity was 90.8%, stepwise Logistic regression sensitivity was 18.2%, specificity was 92.3%, decision tree sensitivity was 13.6%, specificity was 100%, logistic regression sensitivity was 27.3%, specificity 89.2%. From the result of this study, we hope to improve the accuracy by improving the module parameters or other methods in the future and we hope to solve the problem of low sensitivity by adjusting the imbalanced proportion of positive and negative data.Keywords: decision support, computed tomography, coronary artery, machine learning
Procedia PDF Downloads 2294336 Influence of Low and Extreme Heat Fluxes on Thermal Degradation of Carbon Fibre-Reinforced Polymers
Authors: Johannes Bibinger, Sebastian Eibl, Hans-Joachim Gudladt
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This study considers the influence of different irradiation scenarios on the thermal degradation of carbon fiber-reinforced polymers (CFRP). Real threats are simulated, such as fires with long-lasting low heat fluxes and nuclear heat flashes with short-lasting high heat fluxes. For this purpose, coated and uncoated quasi-isotropic samples of the commercially available CFRP HexPly® 8552/IM7 are thermally irradiated from one side by a cone calorimeter and a xenon short-arc lamp with heat fluxes between 5 and 175 W/cm² at varying time intervals. The specimen temperature is recorded on the front and backside as well as at different laminate depths. The CFRP is non-destructively tested with ultrasonic testing, infrared spectroscopy (ATR-FTIR), scanning electron microscopy (SEM), and micro-focused computed X-Ray tomography (μCT). Destructive tests are performed to evaluate the mechanical properties in terms of interlaminar shear strength (ILSS), compressive and tensile strength. The irradiation scenarios vary significantly in heat flux and exposure time. Thus, different heating rates, radiation effects, and temperature distributions occur. This leads to unequal decomposition processes, which affect the sensitivity of the strength type and damage behaviour of the specimens. However, with the use of surface coatings, thermal degradation of composite materials can be delayed.Keywords: CFRP, one-sided thermal damage, high heat flux, heating rate, non-destructive and destructive testing
Procedia PDF Downloads 1124335 Factors Affecting Weld Line Movement in Tailor Welded Blank
Authors: Sanjay Patil, Shakil A. Kagzi, Harit K. Raval
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Tailor Welded Blanks (TWB) are utilized in automotive industries widely because of their advantage of weight and cost reduction and maintaining required strength and structural integrity. TWB consist of two or more sheet having dissimilar or similar material and thickness; welded together to form a single sheet before forming it to desired shape. Forming of the tailor welded blank is affected by ratio of thickness of blanks, ratio of their strength, etc. mainly due to in-homogeneity of material. In the present work the relative effect of these parameters on weld line movement is studied during deep drawing of TWB using FE simulation using HYPERWORKS. The simulation is validated with results from the literature. Simulations were than performed based on Taguchi orthogonal array followed by the ANOVA analysis to determine the significance of these parameters on forming of TWB.Keywords: ANOVA, deep drawing, Tailor Welded Blank (TWB), weld line movement
Procedia PDF Downloads 3124334 Comparing Effects of Supervised Exercise Therapy versus Home-Based Exercise Therapy on Low Back Pain Severity, Muscle Strength and Anthropometric Parameters in Patients with Nonspecific Chronic Low Back Pain
Authors: Haleh Dadgostar, Faramarz Akbari, Hosien Vahid Tari, Masoud Solaymani-Dodaran, Mohammad Razi
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Introduction: There are a number of exercises-protocols have been applied to improve low back pain. We compared the effect of supervised exercise therapy and home-based exercise therapy among patients with nonspecific chronic low back pain. Methods: 70 patients with nonspecific chronic low back pain were randomly (using a random number generator, excel) divided into two groups to compare the effects of two types of exercise therapy. After a common educational session to learn how to live with low back pain as well as to use core training protocols to strengthen the muscles, the subjects were randomly assigned to follow supervised exercise therapy (n = 31) or home-based exercise therapy (n = 34) for 20 weeks. Results: Although both types of exercise programs resulted in reduced pain, this factor decreased more significantly in supervised exercise program. All scores of fitness improved significantly in supervised exercise group. But only knee extensor strength score was increased in the home base exercise group. Conclusion: Comparing between two types of exercise, supervised group exercise showed more effective than the other one. Reduction in low back pain severity and improvement in muscle flexibility and strength can be more achieved by using a 20-week supervised exercise program compared to the home-based exercise program in patients with nonspecific chronic low back pain.Keywords: low back pain, anthropometric parameters, supervised exercise therapy, home-based exercise therapy
Procedia PDF Downloads 3284333 The Transport of Coexisting Nanoscale Zinc Oxide Particles, Cu(Ⅱ) and Cr(Ⅵ) Ions in Simulated Landfill Leachate
Authors: Xiaoyu Li, Wenchuan Ding, Yujia Yia
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As the nanoscale zinc oxide particles (nano-ZnO) accumulate in the landfill, nano-ZnO will enter the landfill leachate and come into contact with the heavy metal ions in leachate, which will change their transport process in the landfill and, furthermore, affect each other's environmental fate and toxicity. In this study, we explored the transport of co-existing nano-ZnO, Cu(II) and Cr(VI) ions by column experiments under different stages of landfill leachate conditions (flow rate, pH, ionic strength, humic acid). The results show that Cu(II) inhibits the transport of nano-ZnO in the quartz sand column by increasing the surface potential of nano-ZnO, and nano-ZnO increases the retention of Cu(II) in the quartz sand column by adsorbing Cu(II) ions. Cr(VI) promotes the transport of nano-ZnO in the quartz sand column by neutralizing the surface potential of the nano-ZnO which reduces electrostatic attraction between nZnO and quartz sand, but the nano-ZnO has no effect on the transport of Cr(VI). The nature of landfill leachates such as flow rate, pH, ionic strength (IS) and humic acid (HA) has a certain effect on the transport of coexisting nano-ZnO and heavy metal ions. For leachate containing Cu(II) and Cr(VI) ions, at the initial stage of landfilling, the pH of leachate is acidic, ionic strength value is high, the humic acid concentration is low, and the transportability of nano-ZnO is weak. As the landfill age increased, the pH value in the leachate gradually increases, when the ions are raised to alkaline, these ions are trending to precipitated or adsorbed to the solid wastes in landfill, which resulting in low IS value of leachate. At the same time, more refractory organic matter gradually increases such as HA, which provides repulsive steric effects, so the nano-ZnO is more likely to migrate. Overall, the Cr(VI) can promote the transport of nano-ZnO more than Cu(II).Keywords: heavy metal ions, landfill leachate, nano-ZnO, transport
Procedia PDF Downloads 1364332 Machine Learning Approaches to Water Usage Prediction in Kocaeli: A Comparative Study
Authors: Kasim Görenekli, Ali Gülbağ
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This study presents a comprehensive analysis of water consumption patterns in Kocaeli province, Turkey, utilizing various machine learning approaches. We analyzed data from 5,000 water subscribers across residential, commercial, and official categories over an 80-month period from January 2016 to August 2022, resulting in a total of 400,000 records. The dataset encompasses water consumption records, weather information, weekends and holidays, previous months' consumption, and the influence of the COVID-19 pandemic.We implemented and compared several machine learning models, including Linear Regression, Random Forest, Support Vector Regression (SVR), XGBoost, Artificial Neural Networks (ANN), Long Short-Term Memory (LSTM), and Gated Recurrent Units (GRU). Particle Swarm Optimization (PSO) was applied to optimize hyperparameters for all models.Our results demonstrate varying performance across subscriber types and models. For official subscribers, Random Forest achieved the highest R² of 0.699 with PSO optimization. For commercial subscribers, Linear Regression performed best with an R² of 0.730 with PSO. Residential water usage proved more challenging to predict, with XGBoost achieving the highest R² of 0.572 with PSO.The study identified key factors influencing water consumption, with previous months' consumption, meter diameter, and weather conditions being among the most significant predictors. The impact of the COVID-19 pandemic on consumption patterns was also observed, particularly in residential usage.This research provides valuable insights for effective water resource management in Kocaeli and similar regions, considering Turkey's high water loss rate and below-average per capita water supply. The comparative analysis of different machine learning approaches offers a comprehensive framework for selecting appropriate models for water consumption prediction in urban settings.Keywords: mMachine learning, water consumption prediction, particle swarm optimization, COVID-19, water resource management
Procedia PDF Downloads 154331 Stock Prediction and Portfolio Optimization Thesis
Authors: Deniz Peksen
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This thesis aims to predict trend movement of closing price of stock and to maximize portfolio by utilizing the predictions. In this context, the study aims to define a stock portfolio strategy from models created by using Logistic Regression, Gradient Boosting and Random Forest. Recently, predicting the trend of stock price has gained a significance role in making buy and sell decisions and generating returns with investment strategies formed by machine learning basis decisions. There are plenty of studies in the literature on the prediction of stock prices in capital markets using machine learning methods but most of them focus on closing prices instead of the direction of price trend. Our study differs from literature in terms of target definition. Ours is a classification problem which is focusing on the market trend in next 20 trading days. To predict trend direction, fourteen years of data were used for training. Following three years were used for validation. Finally, last three years were used for testing. Training data are between 2002-06-18 and 2016-12-30 Validation data are between 2017-01-02 and 2019-12-31 Testing data are between 2020-01-02 and 2022-03-17 We determine Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate as benchmarks which we should outperform. We compared our machine learning basis portfolio return on test data with return of Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate. We assessed our model performance with the help of roc-auc score and lift charts. We use logistic regression, Gradient Boosting and Random Forest with grid search approach to fine-tune hyper-parameters. As a result of the empirical study, the existence of uptrend and downtrend of five stocks could not be predicted by the models. When we use these predictions to define buy and sell decisions in order to generate model-based-portfolio, model-based-portfolio fails in test dataset. It was found that Model-based buy and sell decisions generated a stock portfolio strategy whose returns can not outperform non-model portfolio strategies on test dataset. We found that any effort for predicting the trend which is formulated on stock price is a challenge. We found same results as Random Walk Theory claims which says that stock price or price changes are unpredictable. Our model iterations failed on test dataset. Although, we built up several good models on validation dataset, we failed on test dataset. We implemented Random Forest, Gradient Boosting and Logistic Regression. We discovered that complex models did not provide advantage or additional performance while comparing them with Logistic Regression. More complexity did not lead us to reach better performance. Using a complex model is not an answer to figure out the stock-related prediction problem. Our approach was to predict the trend instead of the price. This approach converted our problem into classification. However, this label approach does not lead us to solve the stock prediction problem and deny or refute the accuracy of the Random Walk Theory for the stock price.Keywords: stock prediction, portfolio optimization, data science, machine learning
Procedia PDF Downloads 804330 Utilization of Fly Ash Amended Sewage Sludge as Sustainable Building Material
Authors: Kaling Taki, Rohit Gahlot, Manish Kumar
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Disposal of Sewage Sludge (SS) is a big issue especially in developing nation like India, where there is no control in the dynamicity of SS produced. The present research work demonstrates the potential application of SS amended with varying percentage (0-100%) of Fly Ash (FA) for brick manufacturing as an alternative of SS management. SS samples were collected from Jaspur sewage treatment plant (Ahmedabad, India) and subjected to different preconditioning treatments: (i) atmospheric drying (ii) pulverization (iii) heat treatment in oven (110°C, moisture removal) and muffle furnace (440°C, organic content removal). Geotechnical parameters of the SS were obtained as liquid limit (52%), plastic limit (24%), shrinkage limit (10%), plasticity index (28%), differential free swell index (DFSI, 47%), silt (68%), clay (27%), organic content (5%), optimum moisture content (OMC, 20%), maximum dry density (MDD, 1.55gm/cc), specific gravity (2.66), swell pressure (57kPa) and unconfined compressive strength (UCS, 207kPa). For FA liquid limit, plastic limit and specific gravity was 44%, 0% and 2.2 respectively. Initially, for brick casting pulverized SS sample was heat treated in a muffle furnace around 440℃ (5 hours) for removal of organic matter. Later, mixing of SS, FA and water by weight ratio was done at OMC. 7*7*7 cm3 sample mold was used for casting bricks at MDD. Brick samples were then first dried in room temperature for 24 hours, then in oven at 100℃ (24 hours) and finally firing in muffle furnace for 1000℃ (10 hours). The fired brick samples were then cured for 3 days according to Indian Standards (IS) common burnt clay building bricks- specification (5th revision). The Compressive strength of brick samples (0, 10, 20, 30, 40, 50 ,60, 70, 80, 90, 100%) of FA were 0.45, 0.76, 1.89, 1.83, 4.02, 3.74, 3.42, 3.19, 2.87, 0.78 and 4.95MPa when evaluated through compressive testing machine (CTM) for a stress rate of 14MPa/min. The highest strength was obtained at 40% FA mixture i.e. 4.02MPa which is much higher than the pure SS brick sample. According to IS 1077: 1992 this combination gives strength more than 3.5 MPa and can be utilized as common building bricks. The loss in weight after firing was much higher than the oven treatment, this might be due to degradation temperature higher than 100℃. The thermal conductivity of the fired brick was obtained as 0.44Wm-1K-1, indicating better insulation properties than other reported studies. TCLP (Toxicity characteristic leaching procedure) test of Cr, Cu, Co, Fe and Ni in raw SS was found as 69, 70, 21, 39502 and 47 mg/kg. The study positively concludes that SS and FA at optimum ratio can be utilized as common building bricks such as partitioning wall and other small strength requirement works. The uniqueness of the work is it emphasizes on utilization of FA for stabilizing SS as construction material as a replacement of natural clay as reported in existing studies.Keywords: Compressive strength, Curing, Fly Ash, Sewage Sludge.
Procedia PDF Downloads 1114329 Study of Mechanical Properties of Glutarylated Jute Fiber Reinforced Epoxy Composites
Authors: V. Manush Nandan, K. Lokdeep, R. Vimal, K. Hari Hara Subramanyan, C. Aswin, V. Logeswaran
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Natural fibers have attained the potential market in the composite industry because of the huge environmental impact caused by synthetic fibers. Among the natural fibers, jute fibers are the most abundant plant fibers which are manufactured mainly in countries like India. Even though there is a good motive to utilize the natural supplement, the strength of the natural fiber composites is still a topic of discussion. In recent days, many researchers are showing interest in the chemical modification of the natural fibers to increase various mechanical and thermal properties. In the present study, jute fibers have been modified chemically using glutaric anhydride at different concentrations of 5%, 10%, 20%, and 30%. The glutaric anhydride solution is prepared by dissolving the different quantity of glutaric anhydride in benzene and dimethyl-sulfoxide using sodium formate catalyst. The jute fiber mats have been treated by the method of retting at various time intervals of 3, 6, 12, 24, and 36 hours. The modification structure of the treated fibers has been confirmed with infrared spectroscopy. The degree of modification increases with an increase in retention time, but higher retention time has damaged the fiber structure. The unmodified fibers and glutarylated fibers at different retention times are reinforced with epoxy matrix under room temperature. The tensile strength and flexural strength of the composites are analyzed in detail. Among these, the composite made with glutarylated fiber has shown good mechanical properties when compared to those made of unmodified fiber.Keywords: flexural properties, glutarylation, glutaric anhydride, tensile properties
Procedia PDF Downloads 1924328 Gellan Gum/Gamma-Polyglutamic Acid and Glycerol Composited Membrane for Guiding Bone Regeneration
Authors: Chi-Chang Lin, Jiun-Yan Chiu
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Periodontal disease, oral cancer relating trauma is the prominent factor devastating bone tissue that is crucial to reestablishing in clinical. As we know, common symptom, osteoporosis, and infection limiting the ability of the bone tissue to recover cause difficulty before implantation therapy. Regeneration of bone tissue is the fundamental therapy before surgical processes. To promote the growth of bone tissue, many commercial products still have sophisticated problems that need to overcome. Regrettably, there is no available material which is apparently preferable for releasing and controlling of loading dosage, or mitigating inflammation. In our study, a hydrogel-based composite membrane has been prepared by using Gellan gum (GG), gamma-polyglutamic acid (γ-PGA) and glycerol with simple sol-gel method. GG is a natural material that is massively adopted in cartilage. Unfortunately, the strength of pure GG film is a manifest weakness especially under simulating body fluidic conditions. We utilize another biocompatible material, γ-PGA as cross-linker which can form tri-dimension structure that enhancing the strength. Our result indicated the strength of pure GG membrane can be obviously improved by cross-linked with γ-PGA (0.5, 0.6, 0.7, 0.8, 0.9, 1.0 w/v%). Besides, blending with glycerol (0, 1.0, 2.0, 3.0 w/v%) can significantly improve membrane toughness that corresponds to practical use. The innovative composited hydrogel made of GG, γ-PGA, and glycerol is attested with neat results including elongation and biocompatibility that take the advantage of extension covering major trauma. Recommendations are made for treatment to build up the foundation of bone tissue that would help patients to escape from the suffering and shorten the amount of time in recovery.Keywords: bone tissue, gellan gum, regeneration, toughness
Procedia PDF Downloads 1424327 Characterisation of the Physical Properties of Debris and Residual Soils Implications for the Possible Landslides Occurrence on Cililin West Java
Authors: Ikah Ning Prasetiowati Permanasari, Gunawan Handayani, Lilik Hendrajaya
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Landslide occurence at Mukapayung, Cililin West Java with material movement downward slope as far as 500m and hit residential areas of the village Nagrog cause eighteen people died and ten homes were destroyed and twenty-three heads of families evacuated. In order to test the hypothesis that soil at the landslides area is prone to landslides, we do drilling and the following tests were taken: particle size distribution, atterberg limits, shear strength, density, shringkage limits and triaxial unconsolidated and consolidated undrained test. Factor of safety was calculated to find out the possibility of subsequent landslides. The value of FOS of three layers is 1,05 which means that the soil in a critical condition and would be imminent to slide if there is disruption from the outside.Keywords: atterberg limits, particle size distribution, shear strength parameters, slope geometry, factor of safety
Procedia PDF Downloads 1494326 Iron Response Element-mRNA Binding to Iron Response Protein: Metal Ion Sensing
Authors: Mateen A. Khan, Elizabeth J. Theil, Dixie J. Goss
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Cellular iron homeostasis is accomplished by the coordinated regulated expression of iron uptake, storage, and export. Iron regulate the translation of ferritin and mitochondrial aconitase iron responsive element (IRE)-mRNA by interaction with an iron regulatory protein (IRPs). Iron increases protein biosynthesis encoded in iron responsive element. The noncoding structure IRE-mRNA, approximately 30-nt, folds into a stem loop to control synthesis of proteins in iron trafficking, cell cycling, and nervous system function. Fluorescence anisotropy measurements showed the presence of one binding site on IRP1 for ferritin and mitochondrial aconitase IRE-mRNA. Scatchard analysis revealed the binding affinity (Kₐ) and average binding sites (n) for ferritin and mitochondrial aconitase IRE-mRNA were 68.7 x 10⁶ M⁻¹ and 9.2 x 10⁶ M⁻¹, respectively. In order to understand the relative importance of equilibrium and stability, we further report the contribution of electrostatic interactions in the overall binding of two IRE-mRNA with IRP1. The fluorescence quenching of IRP1 protein was measured at different ionic strengths. The binding affinity of IRE-mRNA to IRP1 decreases with increasing ionic strength, but the number of binding sites was independent of ionic strength. Such results indicate a differential contribution of electrostatics to the interaction of IRE-mRNA with IRP1, possibly related to helix bending or stem interactions and an overall conformational change. Selective destabilization of ferritin and mitochondrial aconitase RNA/protein complexes as reported here explain in part the quantitative differences in signal response to iron in vivo and indicate possible new regulatory interactions.Keywords: IRE-mRNA, IRP1, binding, ionic strength
Procedia PDF Downloads 1284325 Analysis of Stress Concentration of a Hybrid Composite Material with Centre Circular Hole Subjected to Tensile Loading
Authors: C. Shalini Devi
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This work describes the stress concentration in a rectangular specimen with a circular hole made up of hybrid composite material with the combination of glass/carbon with epoxy. The arrangements of cross ply lamina in the sequence of alternative carbon and glass, using carbon fiber in panel, gives more strength to the structure as the carbon properties are higher when compared to glass. Typical aircraft and automobile components are with cut-outs, and such cut-outs reduce the weight of the aircraft according to the weight reduction law and also they reduce the bulking load carrying capacity. Experimental investigations were carried out using three specimens as per ASTM D5766 and three specimens as per ASTM D3039 in the Universal Testing Machine. Stress concentration in the rectangular specimen with a hole is also analysed using FEA and comparing the results.Keywords: composite, stress concentration, finite element analysis, tensile strength
Procedia PDF Downloads 4494324 Development of AA2024 Matrix Composites Reinforced with Micro Yttrium through Cold Compaction with Superior Mechanical Properties
Authors: C. H. S. Vidyasagar, D. B. Karunakar
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In this present work, five different composite samples with AA2024 as matrix and varying amounts of yttrium (0.1-0.5 wt.%) as reinforcement are developed through cold compaction. The microstructures of the developed composite samples revealed that the yttrium reinforcement caused grain refinement up to 0.3 wt.% and beyond which the refinement is not effective. The microstructure revealed Al2Cu precipitation which strengthened the composite up to 0.3 wt.% yttrium reinforcement. Upon further increase in yttrium reinforcement, the intermetallics and the precipitation coarsen and their corresponding strengthening effect decreases. The mechanical characterization revealed that the composite sample reinforced with 0.3 wt.% yttrium showed highest mechanical properties like 82 HV of hardness, 276 MPa Ultimate Tensile Strength (UTS), 229 MPa Yield Strength (YS) and an elongation (EL) of 18.9% respectively. However, the relative density of the developed composites decreased with the increase in yttrium reinforcement.Keywords: mechanical properties, AA 2024 matrix, yttrium reinforcement, cold compaction, precipitation
Procedia PDF Downloads 152