Search results for: strength prediction

Authors: Siddharth Vishwakarma, Danie Shajie A., Mishra H. N.

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Milk powder becomes very useful in the low milk supply area but the exact amount to add for one glass of milk and the handling is difficult. So, the idea of instant soluble milk tablet comes into existence for its high solubility and easy handling. The moisture content of milk tablets is increased by the direct addition of water with no additives for binding. The variation of the tensile strength of instant soluble milk tablets and the flowability of milk powder with the moisture content is analyzed and optimized for the highest tensile strength of instant soluble milk tablets and flowability, above a particular value of milk powder using response surface methodology. The flowability value is necessary for ease in quantifying the milk powder, as a feed, in the designed tablet making machine. The instant soluble nature of milk tablets purely depends upon the disintegration characteristic of tablets in water whose study is under progress. Conclusions: The optimization results are very useful in the commercialization of milk tablets.

Keywords: flowability, milk powder, response surface methodology, tablet making machine, tensile strength

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Authors: Hasan Taherkhani

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The performance of asphalt pavements is highly dependent on the mechanical properties of asphaltic layers. Improving the mechanical properties of asphaltic mixtures by fiber reinforcement is a common method. Randomly distribution of fibers in the bituminous mixtures and placing between the particles develop reinforcing property in all directions in the mixture and improve their engineering properties. In this research, the effects of the nylon fiber length and content on some engineering properties of a typical binder course asphalt concrete have been investigated. The fibers at different contents of 0.3, 0.4 and 0.5% (by the weight of total mixture), each at three different lengths of 10, 25 and 40 mm have been used, and the properties of the mixtures, such as, volumetric properties, Marshall stability, flow, Marshall quotient, indirect tensile strength and moisture damage have been studied. It is found that the highest Marshall quotient is obtained by using 0.4% of 25mm long nylon fibers. The results also show that the indirect tensile strength and tensile strength ratio, which is an indication of moisture damage of asphalt concrete, decreases with increasing the length of fibers and fiber content.

Keywords: asphalt concrete, moisture damage, nylon fiber, tensile strength,

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Authors: Soo-yeon Seo, Su-jin Jung

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In recent years, the need for remodeling of many apartments built 30 years ago is increasing. Therefore, researches on the structural reinforcement technology of existing apartments have been conducted. On the other hand, there is a growing need for research on the existing underground space expansion technology to expand the parking space required for remodeling. When expanding an existing underground space, for earthworks, an earth retaining wall must be installed between the existing apartment building and it. In order to maximize the possible underground space, it is necessary to minimize the thickness of the portion of earth retaining wall and underground basement wall. In this manner, the calculation procedure is studied for the evaluation of shear strength of the composite basement wall corresponding to shear span-to-depth ratio in this study. As a result, it was shown that the proposed calculation procedure can be used to evaluate the shear strength of the composite basement wall as safe. On the other hand, when shear span-to-depth ratio is small, shear strength is very underestimated.

Keywords: underground space expansion, combined structure, temporary retaining wall, basement wall, shear connectors

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Authors: Rashini Maduka, C. R. Wijesinghe, A. R. Weerasinghe

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Drug-drug interactions (DDIs) can happen when two or more drugs are taken together. Today DDIs have become a serious health issue due to adverse drug effects. In vivo and in vitro methods for identifying DDIs are time-consuming and costly. Therefore, in-silico-based approaches are preferred in DDI identification. Most machine learning models for DDI prediction are used chemical and biological drug properties as features. However, some drug features are not available and costly to extract. Therefore, it is better to make automatic feature engineering. Furthermore, people who have diabetes already suffer from other diseases and take more than one medicine together. Then adverse drug effects may happen to diabetic patients and cause unpleasant reactions in the body. In this study, we present a model with a graph convolutional autoencoder and a graph decoder using a dataset from DrugBank version 5.1.3. The main objective of the model is to identify unknown interactions between antidiabetic drugs and the drugs taken by diabetic patients for other diseases. We considered automatic feature engineering and used Known DDIs only as the input for the model. Our model has achieved 0.86 in AUC and 0.86 in AP.

Keywords: drug-drug interaction prediction, graph embedding, graph convolutional networks, adverse drug effects

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Authors: Neveen AlQasas, Daniel Johnson

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Membranes for water treatment are an established technology that attracts great attention due to its simplicity and cost effectiveness. However, membranes in operation suffer from the adverse effect of membrane fouling. Bio-fouling is a phenomenon that occurs at the water-membrane interface, and is a dynamic process that is initiated by the adsorption of dissolved organic material, including biomacromolecules, on the membrane surface. After initiation, attachment of microorganisms occurs, followed by biofilm growth. The biofilm blocks the pores of the membrane and consequently results in reducing the water flux. Moreover, the presence of a fouling layer can have a substantial impact on the membrane separation properties. Understanding the mechanism of the initiation phase of biofouling is a key point in eliminating the biofouling on membrane surfaces. The adhesion and attachment of different fouling materials is affected by the surface properties of the membrane materials. Therefore, surface properties of different polymeric materials had been studied in terms of their surface energies and Hansen solubility parameters (HSP). The difference between the combined HSP parameters (HSP distance) allows prediction of the affinity of two materials to each other. The possibilities of measuring the HSP of different polymer films via surface measurements, such as contact angle has been thoroughly investigated. Knowing the HSP of a membrane material and the HSP of a specific foulant, facilitate the estimation of the HSP distance between the two, and therefore the strength of attachment to the surface. Contact angle measurements using fourteen different solvents on five different polymeric films were carried out using the sessile drop method. Solvents were ranked as good or bad solvents using different ranking method and ranking was used to calculate the HSP of each polymeric film. Results clearly indicate the absence of a direct relation between contact angle values of each film and the HSP distance between each polymer film and the solvents used. Therefore, estimating HSP via contact angle alone is not sufficient. However, it was found if the surface tensions and viscosities of the used solvents are taken in to the account in the analysis of the contact angle values, a prediction of the HSP from contact angle measurements is possible. This was carried out via training of a neural network model. The trained neural network model has three inputs, contact angle value, surface tension and viscosity of solvent used. The model is able to predict the HSP distance between the used solvent and the tested polymer (material). The HSP distance prediction is further used to estimate the total and individual HSP parameters of each tested material. The results showed an accuracy of about 90% for all the five studied films

Keywords: surface characterization, hansen solubility parameter estimation, contact angle measurements, artificial neural network model, surface measurements

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Authors: Ravija Gunawardana, Banuka Athuraliya

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Machine learning has emerged as a powerful tool for disease diagnosis and prediction. The use of machine learning algorithms has the potential to improve the accuracy of disease prediction, thereby enabling medical professionals to provide more effective and personalized treatments. This study focuses on developing a machine-learning model for disease prediction using symptoms and X-ray images. The importance of this study lies in its potential to assist medical professionals in accurately diagnosing diseases, thereby improving patient outcomes. Respiratory diseases are a significant cause of morbidity and mortality worldwide, and chest X-rays are commonly used in the diagnosis of these diseases. However, accurately interpreting X-ray images requires significant expertise and can be time-consuming, making it difficult to diagnose respiratory diseases in a timely manner. By incorporating machine learning algorithms, we can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The study utilized the Mask R-CNN algorithm, which is a state-of-the-art method for object detection and segmentation in images, to process chest X-ray images. The model was trained and tested on a large dataset of patient information, which included both symptom data and X-ray images. The performance of the model was evaluated using a range of metrics, including accuracy, precision, recall, and F1-score. The results showed that the model achieved an accuracy rate of over 90%, indicating that it was able to accurately detect and segment regions of interest in the X-ray images. In addition to X-ray images, the study also incorporated symptoms as input data for disease prediction. The study used three different classifiers, namely Random Forest, K-Nearest Neighbor and Support Vector Machine, to predict diseases based on symptoms. These classifiers were trained and tested using the same dataset of patient information as the X-ray model. The results showed promising accuracy rates for predicting diseases using symptoms, with the ensemble learning techniques significantly improving the accuracy of disease prediction. The study's findings indicate that the use of machine learning algorithms can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The model developed in this study has the potential to assist medical professionals in diagnosing respiratory diseases more accurately and efficiently. However, it is important to note that the accuracy of the model can be affected by several factors, including the quality of the X-ray images, the size of the dataset used for training, and the complexity of the disease being diagnosed. In conclusion, the study demonstrated the potential of machine learning algorithms for disease prediction using symptoms and X-ray images. The use of these algorithms can improve the accuracy of disease diagnosis, ultimately leading to better patient care. Further research is needed to validate the model's accuracy and effectiveness in a clinical setting and to expand its application to other diseases.

Keywords: K-nearest neighbor, mask R-CNN, random forest, support vector machine

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Authors: Adnan F. Sheikh, Fayaz A. Mir

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After the recent devastating flood in Kashmir in 2014, dredging of the local water bodies, especially Jhelum River has become a priority for the government. Local government under the project name of 'Comprehensive Flood Management Programme' plans to undertake an increase in discharge of existing flood channels by removal of encroachments and acquisition of additional land, dredging and other works of the water bodies. The total quantity of soil to be dredged will be 16.15 lac cumecs. Dredged soil is a major component that would result from the project which requires disposal/utilization. This study analyses the effect of cement and sand on the engineering properties of soil. The tests were conducted with variable additions of sand (10%, 20% and 30%), whereas cement was added at 12%. Samples with following compositions: soil-cement (12%) and soil-sand (30%) were tested as well. Laboratory experiments were conducted to determine the engineering characteristics of soil, i.e., compaction, strength, and CBR characteristics. The strength characteristics of the soil were determined by unconfined compressive strength test and direct shear test. Unconfined compressive strength of the soil was tested immediately and for a curing period of seven days. CBR test was performed for unsoaked, soaked (worst condition- 4 days) and cured (4 days) samples.

Keywords: comprehensive flood management programme, dredge soil, strength characteristics, flood

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Authors: Nursah Kutuk, Sevil Cetinkaya

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Geopolymers are becoming new concrete materials to use alongside cement, which are formed due to reaction between alumino-silicates and oxides with alkaline media. Silicates obtained from natural minerals or industrial wastes are used for geopolymer synthesis. Geopolymers have recently received wide attention because of their advantages over other cementitious material like Portland cement. Some of the advantages are high compressive strength, low environmental impact, chemical and fire resistance and thermal stability. In this study, geopolymers were prepared by using inorganic materials such as kaolinite and calcite. The experiments were carried out by varying the concentration of NaOH as 5, 10, 15 and 20 M, and at cure temperature of 22, 45 and 65 °C. Compressive strengths for each mixes at each cure temperature were measured. Results of the analyses indicated that the compressive strength of geopolymers did not increase steadily with increasing concentration of NaOH, but did increase steadily with increasing cure temperature. We examined the effect Na2SiO3/NaOH weight ratio on the properties of the geopolymers, too. It was seen that Na2SiO3/NaOH weight ratio was also important to prepare geopolymers that can be applied to construction industry.

Keywords: geopolymers, compressive strength, kaolinite, calcite

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Authors: Ali A. Sayadi, Thomas R. Neitzert, G. Charles Clifton

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Lightweight concrete is being used in the construction industry as a building material in its own right. Ultra-lightweight concrete can be applied as a filler and support material for the manufacturing of composite building materials. This paper is about the development of a stable and reproducible ultra-lightweight concrete with the inclusion of poly-lactic acid (PLA) beads and assessing the feasibility of PLA as a lightweight aggregate that will deliver advantages such as a more eco-friendly concrete and a non-petroleum polymer aggregate. In total, sixty-three samples were prepared and the effectiveness of mineral admixture, curing conditions, water-cement ratio, PLA ratio, EPS ratio and perlite ratio on compressive strength of perlite concrete are studied. The results show that PLA particles are sensitive to alkali environment of cement paste and considerably shrank and lost their strength. A higher compressive strength and a lower density was observed when expanded polystyrene (EPS) particles replaced PLA beads. In addition, a set of equations is proposed to estimate the water-cement ratio, cement content and compressive strength of perlite concrete.

Keywords: perlite concrete, poly-lactic acid (pla), expanded polystyrene (eps), concrete

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Authors: Prochazka Jiri, Beranek Tomas, Podlena Milan, Zeidler Ales

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The poster deals with the issue of ISO shipping containers’ sheathing made of corrugated plywood instead of traditional corrugated metal sheets. It was found that the corrugated plywood is a suitable material for the sheathing due to its great flexural strength perpendicular to the course of the wave, sufficient impact resistance, surface compressive strength and low weight. Three sample sets of different thicknesses 5, 8 and 10 mm were tested in the experiments. The tests have shown that the 5 cm corrugated plywood is the most suitable thickness for sheathing. Experiments showed that to increase bending strength at needed value, it was necessary to increase the weight of the timber only by 1.6%. Flat cash test showed that 5 mm corrugated plywood is sufficient material for sheathing from a mechanical point of view. Angle of corrugation was found as a very important factor which massively affects the mechanical properties. The impact strength test has shown that plywood is relatively tough material in direction of corrugation. It was calculated that the use of corrugated plywood sheathing for the containers can reduce the weight of the walls up to 75%. Corrugated plywood is also suitable material for web of I-joists and wide interior design applications.

Keywords: corrugated plywood, veneer, beech plywood, ISO shipping container, I-joist

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Authors: M. Parvez Alam, M. Bilal Khan

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Concrete is the material of choice where strength, performance, durability, impermeability, fire resistance, and abrasion resistance are required. The hunger for the higher strength leads to other materials to achieve the desired results and thus, emerged the contribution of cementitious material for the strength of concrete In present day constructions, concrete is chosen as one of the best choices by civil engineers in construction materials. The concept of sustainability is touching new heights and many pozzolonic materials are tried and tested as partial replacement for the cement. In this paper, comprehensive review of available literatures are studied to evaluate the performance of pozzolonic materials such as ceramic waste powder, copper slag, silica fume on the strength of concrete by the partial replacement of ordinary materials such as cement, fine aggregate and coarse aggregate at different percentage of composition. From the study, we conclude that ceramic wastes are suitable to be used in the construction industry, and more significantly on the making of concrete. Ceramic wastes are found to be suitable for usage as substitution for fine and coarse aggregates and partial substitution in cement production. They were found to be performing better than normal concrete, in properties such as density, durability, permeability, and compressive strength. Copper slag is the waste material of matte smelting and refining of copper such that each ton of copper generates approximately 2.5 tons of copper slag. Copper slag is one of the materials that is considered as a waste which could have a promising future in construction Industry as partial or full substitute of aggregates. Silica fume, also known as micro silica or condensed silica fume, is a relatively new material compared to fly ash, It is another material that is used as an artificial pozzolonic admixture. High strength concrete made with silica fume provides high abrasion/corrosion resistance.

Keywords: concrete, pozzolonic materials, ceramic waste powder, copper slag

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Authors: Queen Suraajini Rajendran, Sai Hung Cheung

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Statistical down scaling models are required to connect the global climate model outputs and the local weather variables for climate change impact prediction. For reliable climate change impact studies, the uncertainty associated with the model including natural variability, uncertainty in the climate model(s), down scaling model, model inadequacy and in the predicted results should be quantified appropriately. In this work, a new approach is developed by the authors for statistical classification, statistical down scaling and uncertainty assessment and is applied to Singapore rainfall. It is a robust Bayesian uncertainty analysis methodology and tools based on coupling dependent modeling error with classification and statistical down scaling models in a way that the dependency among modeling errors will impact the results of both classification and statistical down scaling model calibration and uncertainty analysis for future prediction. Singapore data are considered here and the uncertainty and prediction results are obtained. From the results obtained, directions of research for improvement are briefly presented.

Keywords: statistical downscaling, global climate model, climate change, uncertainty

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Authors: Amar Patnaik, Pankaj Agarwal

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This paper investigates the experimental study of hardness and compressive strength of hybrid glass/steel fiber reinforced polymer composites by varying the glass and steel fiber layer in the epoxy matrix. The hybrid composites with four stacking sequences HSG-1, HSG-2, HSG-3, and HSG-4 were fabricated by the VARTM process under the controlled environment. The experimentally evaluated results of Vicker’s hardness of the fabricated composites increases with an increase in the fiber layers sequence showing the high resistance. The improvement of micro-structure ability has been observed from the SEM study, which governs in the enhancement of compressive strength. The finite element model was developed on ANSYS to predict the above said properties and further compared with experimental results. The results predicted by the numerical simulation are in good agreement with the experimental results. The hybrid composites developed in this study was identified as the preferred materials due to their excellent mechanical properties to replace the conventional materialsused in the marine structures.

Keywords: finite element method, interfacial strength, polymer composites, VARTM

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Authors: Farnia Nayar Parshi, Mohammad Shariful Islam

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Though earth construction is an ancient technology, researchers are working on increasing its strength by adding different types of stabilizers. Ordinary Portland cement for sandy soil and lime for clayey soil is very popular practice as well as recommended by various authorities for making stabilized blocks for satisfactory performance. The addition of these additives improves compressive strength but fails to improve ductility. The addition of both synthetic and natural fibers increases both compressive strength and ductility. Studies are conducted to make earth blocks more cost-effective, energy-efficient and sustainable. In this experiment, an agricultural waste banana fiber and biochar is used to study the compressive stress-strain behavior of earth blocks made with four types of soil low plastic clay, sandy low plastic clay, very fine sand and medium to fine sand. Biochar is a charcoal-like carbon usually produced from organic or agricultural waste in high temperatures through a controlled condition called pyrolysis. In this experimental study, biochar was collected from BBI (Bangladesh Biochar Initiative) produced from wood flakes around 400 deg. Celsius. Locally available PPC (Portland Pozzolana Cement) is used. 5 cm × 5 cm × 5 cm earth blocks were made with eight different combinations such as bare soil, soil with 6% cement, soil with 6% cement and 5% biochar, soil with 6% cement, 5% biochar and 1% fiber, soil with 1% fiber, soil with 5% biochar and 1% fiber and soil with 6% cement and 1% fiber. All samples were prepared with 10-12% water content. Uniaxial compressive strength tests were conducted on 21 days old earth blocks. Stress-strain diagram shows that the addition of banana fiber improved compressive strength drastically, but the combined effect of fiber and biochar is different based on different soil types. For clayey soil, 6% cement and 1% fiber give maximum compressive strength of 991 kPa, and for very fine sand, a combination of 5% biochar, 6% cement and 1% fiber gives maximum compressive strength of 522 kPa as well as ductility. For medium-to-find sand, 6% cement and 1% fiber give the best result, 1530 kPa, among other combinations. The addition of fiber increases not only ductility but also compressive strength as well. The effect of biochar with fiber varies with the soil type.

Keywords: banana fiber, biochar, cement, compressed stabilized earth blocks, compressive strength

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Authors: Cristian Păuna

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After the widespread release of electronic trading, automated trading systems have become a significant part of the business intelligence system of any modern financial investment company. An important part of the trades is made completely automatically today by computers using mathematical algorithms. The trading decisions are taken almost instantly by logical models and the orders are sent by low-latency automatic systems. This paper will present a real-time price prediction methodology designed especially for algorithmic trading. Based on the price cyclicality function, the methodology revealed will generate price cyclicality bands to predict the optimal levels for the entries and exits. In order to automate the trading decisions, the cyclicality bands will generate automated trading signals. We have found that the model can be used with good results to predict the changes in market behavior. Using these predictions, the model can automatically adapt the trading signals in real-time to maximize the trading results. The paper will reveal the methodology to optimize and implement this model in automated trading systems. After tests, it is proved that this methodology can be applied with good efficiency in different timeframes. Real trading results will be also displayed and analyzed in order to qualify the methodology and to compare it with other models. As a conclusion, it was found that the price prediction model using the price cyclicality function is a reliable trading methodology for algorithmic trading in the financial market.

Keywords: algorithmic trading, automated trading systems, financial markets, high-frequency trading, price prediction

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Authors: S. Boudali, A. M. Soliman, B. Abdulsalam, K. Ayed, D. E. Kerdal, S. Poncet

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This study investigates the potential of using crushed concrete as aggregates to produce green and sustainable concrete. Crushed concrete was sieved to powder fine recycled aggregate (PFRA) less than 80 µm and coarse recycled aggregates (CRA). Physical, mechanical, and microstructural properties for PFRA and CRA were evaluated. The effect of the additional rates of PFRA and CRA on strength development of recycled aggregate concrete (RAC) was investigated. Additionally, the characteristics of interfacial transition zone (ITZ) between cement paste and recycled aggregate were also examined. Results show that concrete mixtures made with 100% of CRA and 40% PFRA exhibited similar performance to that of the control mixture prepared with 100% natural aggregate (NA) and 40% natural pozzolan (NP). Moreover, concrete mixture incorporating recycled aggregate exhibited a slightly higher later compressive strength than that of the concrete with NA. This was confirmed by the very dense microstructure for concrete mixture incorporating recycled concrete aggregates compared to that of conventional concrete mixture.

Keywords: compressive strength, recycled concrete aggregates, microstructure, interfacial transition zone, powder fine recycled aggregate

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Authors: Man Fung Ho, Lap So, Jiaqi Zhang, Yuheng Zhao, Huiyang Lu, Tat Shing Choi, K. Y. Michael Wong

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Nowadays, a tremendous amount of data is available in the transportation system, enabling the development of various machine learning approaches to make short-term latency predictions. A natural question is then the choice of relevant information to enable accurate predictions. Using traffic data collected from the Taiwan Freeway System, we consider the prediction of short-term latency of a freeway segment with a length of 17 km covering 5 measurement points, each collecting vehicle-by-vehicle data through the electronic toll collection system. The processed data include the past latencies of the freeway segment with different time lags, the traffic conditions of the individual segments (the accumulations, the traffic fluxes, the entrance and exit rates), the total accumulations, and the weekday latency profiles obtained by Gaussian process regression of past data. We arrive at several important conclusions about how data should be refined to obtain accurate predictions, which have implications for future system-wide latency predictions. (1) We find that the prediction of median latency is much more accurate and meaningful than the prediction of average latency, as the latter is plagued by outliers. This is verified by machine-learning prediction using XGBoost that yields a 35% improvement in the mean square error of the 5-minute averaged latencies. (2) We find that the median latency of the segment 15 minutes ago is a very good baseline for performance comparison, and we have evidence that further improvement is achieved by machine learning approaches such as XGBoost and Long Short-Term Memory (LSTM). (3) By analyzing the feature importance score in XGBoost and calculating the mutual information between the inputs and the latencies to be predicted, we identify a sequence of inputs ranked in importance. It confirms that the past latencies are most informative of the predicted latencies, followed by the total accumulation, whereas inputs such as the entrance and exit rates are uninformative. It also confirms that the inputs are much less informative of the average latencies than the median latencies. (4) For predicting the latencies of segments composed of two or three sub-segments, summing up the predicted latencies of each sub-segment is more accurate than the one-step prediction of the whole segment, especially with the latency prediction of the downstream sub-segments trained to anticipate latencies several minutes ahead. The duration of the anticipation time is an increasing function of the traveling time of the upstream segment. The above findings have important implications to predicting the full set of latencies among the various locations in the freeway system.

Keywords: data refinement, machine learning, mutual information, short-term latency prediction

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Authors: Humphrey Danso, Seth Adu

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The high cost of cement and its greenhouse effect on the environment have led to the use of alternative building materials in the production of block and bricks. This study seeks to investigate the properties of compressed earth blocks (CEBs) enhanced with clay pozzolana. CEBs of size 290 × 140 × 100 mm were prepared with 10, 20 and 30 % weight of clay pozzolana. The CEBs were compressed at a constant pressure of 5 MPa and cured for 28 days. The blocks, after 7, 14, 21 and 28 days of curing were tested for density, water absorption, compressive strength and erosion. It was found that amount of pozzolana content did not have much influence on blocks’ density. There was a decline in water absorption of the stabilised blocks ranged between 32.8% and 252.2% over the unstabilised blocks. The highest compressive strength (3.75MPa) of the stabilized blocks was achieved at 28th day of curing with 30% clay pozzolana content, which showed an improvement of 116.8% strength over the unstabilised blocks. Furthermore, there was a statistically significant difference in the erosion resistance between the stabilized blocks and the unstabilised blocks. The study concludes that the inclusion of the clay pozzolana increased the properties of the CEBs, and therefore recommended for use in the building of houses.

Keywords: clay pozzolana, compressed earth blocks (CEBs), compressive strength, erosion test

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Authors: Mostafa Rezaee Saraji, Ali Keshavarz Panahi

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In this work, the processing steps for producing alumina parts using powder injection molding (PIM) technique and nano-powder were investigated and the thermal conductivity and flexural strength of samples were determined as a function of sintering temperature and holding time. In the first step, the feedstock with 58 vol. % of alumina nano-powder with average particle size of 100nm was prepared using Extrumixing method to obtain appropriate homogeneity. This feedstock was injection molded into the two cavity mold with rectangular shape. After injection molding step, thermal and solvent debinding methods were used for debinding of molded samples and then these debinded samples were sintered in different sintering temperatures and holding times. From the results, it was found that the flexural strength and thermal conductivity of samples increased by increasing sintering temperature and holding time; in sintering temperature of 1600ºC and holding time of 5h, the flexural strength and thermal conductivity of sintered samples reached to maximum values of 488MPa and 40.8 W/mK, respectively.

Keywords: alumina nano-powder, thermal conductivity, flexural strength, powder injection molding

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Authors: Barry Hojjatie

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Uniaxial (e.g., three-point bending) and biaxial flexure tests are used frequently for determining the strength of ceramics. It is generally believed that the biaxial test has an advantage as compared to uniaxial test because it produces a state of pure tension on the lower surface of the specimen and the maximum tensile stress, which is usually responsible for crack initiation and failure is unaffected by the edge condition. However, inconsistent strength values have been reported for the same material and testing conditions. The objective of this study was to analyze the strength of dental porcelain materials using the two different test methods and evaluate the main contributions to variability in biaxial testing and to analyze the relative influence of variables such as specimen geometric conditions and loading conditions on calculated strength of porcelain subjected to biaxial testing. Porcelain disks (16 mm dia x 2 mm thick) were subjected to biaxial flexure (pin-on-three-ball), and flexure strength values were calculated. A 3-D finite element model was developed to simulate various biaxial flexure test conditions. Stresses were analyzed for ceramic thickness in the range of 1.0-3.0 mm. For a 2-mm-thick disk subjected to a point load of 200 N, the maximum tensile stress at the lower surface was 180 MPa. This stress decreased to 95, 77, 68, and 59 MPa for the radius of the load values of 0.15, 0.3, 0.6, and 1.0 mm, respectively. Tensile stresses which developed at the top surface near the site of loading were small for the radius of the load ≥ 0.6 mm.

Keywords: ceramis, biaxial, flexure test, uniaxial

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Authors: Jagdeep Nayak, Biswajit Paul, Anup Gupta

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Characterization of coal refuses to fly ash, and steel slag from steel industries have been performed to develop a mixture of both these materials to enhance strength properties of their utilization in other sectors like mine fill, construction work, etc. A large amount of Linz-Donawitz (LD) slag and fly ash waste are generated from steel and thermal power industries respectively. Management of these wastes is problematic, and their reutilization may provide a sustainable waste management option. LD slag and fly ash mixed in different proportions were tested to analyse the micro structural improvement and hardening rate of the matrix. Mixing of activators such as sodium hydroxide and potassium silicate with silica-alumina of LD slag-fly ash mixture, geopolymeric structure were found to be developed. The effect of geo-polymerization behaviour and subsequent structural rearrangement has been studied using compressibility; shear strength and permeability tests followed by micro-graphical analysis. Densification in the mixture was observed along with an improvement of geotechnical properties due to the addition of LD slag. Due to suitable strength characteristics of these two waste materials as mixture, it can be used in the various construction field or may be used as a filling material in mine voids.

Keywords: LD slag, fly-ash, geopolymer, strength property, compressibility

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Authors: Ezgi Yurdakul, Klaus-Alexander Rieder, Richard Sibbick

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Most of the shotcrete projects require compliance with meeting a specified early-age strength target (e.g., reaching 1 MPa in 1 hour) that is selected based on the underground conditions. To meet the desired early-age performance characteristics, accelerators are commonly used as they increase early-age strength development rate and accelerate the setting thereby reducing sagging and rebound. The selection of accelerator type and its dosage is made by the setting time and strength required for the shotcrete application. While alkaline and alkali-free accelerators are the two main types used in wet-mix shotcrete; alkali-free admixtures increasingly substitute the alkaline accelerators to improve the performance and working safety. This paper aims to evaluate the impact of alkali-free accelerators in wet-mix on various tests including set time, early and later-age compressive strength, boiled absorption, and electrical resistivity. Furthermore, the comparison between accelerated and non-accelerated samples will be made to demonstrate the interaction between cement and accelerators. Scanning electron microscopy (SEM), fluorescent resin impregnated thin section and cut and polished surface images will be used to understand the microstructure characterization of mixes in the presence of accelerators.

Keywords: accelerators, chemical admixtures, shotcrete, sprayed concrete

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Authors: Marian Sorin Ionescu, Olivia Negoita, Cosmin Dobrin

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This scientific communication reports and discusses learning models adaptable to modern business problems and models specific to digital concepts and paradigms. In the PAC (probably approximately correct) learning model approach, in which the learning process begins by receiving a batch of learning examples, the set of learning processes is used to acquire a hypothesis, and when the learning process is fully used, this hypothesis is used in the prediction of new operational examples. For complex business models, a lot of models should be introduced and evaluated to estimate the induced results so that the totality of the results are used to develop a predictive rule, which anticipates the choice of new models. In opposition, for online learning-type processes, there is no separation between the learning (training) and predictive phase. Every time a business model is approached, a test example is considered from the beginning until the prediction of the appearance of a model considered correct from the point of view of the business decision. After choosing choice a part of the business model, the label with the logical value "true" is known. Some of the business models are used as examples of learning (training), which helps to improve the prediction mechanisms for future business models.

Keywords: machine learning, business models, convex analysis, online learning

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Authors: Imad Eddine Charif, Wafaa Benchouk, Sidi Mohamed Mekelleche

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The regioselectivity of a series of 16 1,3-dipolar cycloaddition reactions of nitrile oxides with 2(5H)-furanones has been analysed by means of global and local electrophilic and nucleophilic reactivity indices using density functional theory at the B3LYP level together with the 6-31G(d) basis set. The local electrophilicity and nucleophilicity indices, based on Fukui and Parr functions, have been calculated for the terminal sites, namely the C1 and O3 atoms of the 1,3-dipole and the C4 and C5 atoms of the dipolarophile. These local indices were calculated using both Mulliken and natural charges and spin densities. The results obtained show that the C5 atom of the 2(5H)-furanones is the most electrophilic site whereas the O3 atom of the nitrile oxides is the most nucleophilic centre. It turns out that the experimental regioselectivity is correctly reproduced, indicating that both Fukui- and Parr-based indices are efficient tools for the prediction of the regiochemistry of the studied reactions and could be used for the prediction of newly designed reactions of the same kind.

Keywords: 1, 3-dipolar cycloaddition, density functional theory, nitrile oxides, regioselectivity, reactivity indices

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Authors: S. A. Naeini, M. Mortezaee

Abstract:

The purpose of this paper is to investigate the effect of fine grain content in soil and its plastic properties on soil liquefaction potential. For this purpose, the conditions for considering the fine grains effect and percentage of plastic fine on the liquefaction resistance of saturated sand presented by researchers has been investigated. Then, some comprehensive results of all the issues raised by some researchers are stated. From these investigations it was observed that by increasing the percentage of cohesive fine grains in the sandy soil (up to 20%), the maximum shear strength decreases and by adding more fine- grained percentage, the maximum shear strength of the resulting soil increases but never reaches the amount of clean sand.

Keywords: fine-grained, liquefaction, plasticity, shear strength, sand

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Authors: Samiha Ramdani, Abdelhamid Geuttala

Abstract:

There is no doubt that the batteries increasingly used tires create environmental concerns. Algeria generates large amounts of by industrial and household waste, such as used tires and colored glass bottles and dishes, whose valuation in cementitious materials could be an interesting ecological and economical alternative for broadening eliminating cumbersome landfills. This work is a contribution to the promotion of local materials with the use of waste tires and glass bottle in the development of a new cementitious composite having the acceptable compressive strength and a capacity of improved strains. For this purpose, rubber crumb (GC) from shredding used tires were used as partial replacement of quarry sand with 10%, 20%, 40, 60%. In addition, some mixtures also contain glass powder at15% cement replacement by volume. The compressive strength, tensile strength, deformability, the water permeability and penetration Inions chlorides are studied. As results; an acceptable compressive strength was obtained with the substitution rate of 10% and 20% by volume, the deformability of the composite increases with increased replacement rate. The addition of finely ground glass as a partial replacement of cement concrete increases the resistance to penetration of Inions chloride and reduce the water permeability thereof; then increases their durability.

Keywords: crumb rubber, deformability, compressive strength, finely ground glass, durability, behavior law

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Authors: Jason Dellatolla, Scott Thomas

Abstract:

Much of the current literature pertaining to resistance training (RT) volume prescription lacks ecological validity, and very few studies investigate true high-volume ranges. Purpose: The present study sought to investigate the effects of ecologically-valid high- vs low-volume RT on muscular size and strength in trained men. Methods: This study systematically randomized trained, college-aged men into two groups: low-volume (LV; n = 4) and high-volume (HV; n = 5). The sample size was affected by COVID-19 limitations. Subjects followed an ecologically-valid 6-week RT program targeting both muscle size and strength. RT occurred 3x/week on non-consecutive days. Over the course of six weeks, LVR and HVR gradually progressed from 15 to 23 sets/week and 30 to 46 sets/week of lower-body RT, respectively. Muscle strength was assessed via 3RM tests in the squat, stiff-leg deadlift (SL DL), and leg press. Muscle hypertrophy was evaluated through a combination of DXA, BodPod, and ultrasound (US) measurements. Results: Two-way repeated-measures ANOVAs indicated that strength in all 3 compound lifts increased significantly among both groups (p < 0.01); between-group differences only occurred in the squat (p = 0.02) and SL DL (p = 0.03), both of which favored HVR. Significant pre-to-post-study increases in indicators of hypertrophy were discovered for lean body mass in the legs via DXA, overall fat-free mass via BodPod, and US measures of muscle thickness (MT) for the rectus femoris, vastus intermedius, vastus medialis, vastus lateralis, long-head of the biceps femoris, and total MT. Between-group differences were only found for MT of the vastus medialis – favoring HVR. Moreover, each additional weekly set of lower-body RT was associated with an average increase in MT of 0.39% in the thigh muscles. Conclusion: We conclude that ecologically-valid RT regimens significantly improve muscular strength and indicators of hypertrophy. When HVR is compared to LVR, HVR provides significantly greater gains in muscular strength but has no greater effect on hypertrophy over the course of 6 weeks in trained, college-aged men.

Keywords: ecological validity, hypertrophy, resistance training, strength

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Authors: Hasan Keshavarzian, Tayebeh Nesari

Abstract:

Bolted rail joint is one of the most vulnerable areas in railway track. A comprehensive approach was developed for studying the reliability of fatigue crack initiation of railroad bolt hole under random axle loads and random material properties. The operation condition was also considered as stochastic variables. In order to obtain the comprehensive probability model of fatigue crack initiation life prediction in railroad bolt hole, we used FEM, response surface method (RSM), and reliability analysis. Combined energy-density based and critical plane based fatigue concept is used for the fatigue crack prediction. The dynamic loads were calculated according to the axle load, speed, and track properties. The results show that axle load is most sensitive parameter compared to Poisson’s ratio in fatigue crack initiation life. Also, the reliability index decreases slowly due to high cycle fatigue regime in this area.

Keywords: rail-wheel tribology, rolling contact mechanic, finite element modeling, reliability analysis

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Authors: Mamata Mohanty, J. T. Shahu

Abstract:

The in-situ deep mixing is an effective ground improvement technique which involves columnar inclusion into soft ground to increase its bearing capacity and reduce settlement. The first part of the study presents the results of unconfined compression on cement-admixed clay prepared at different cement content and subjected to varying curing periods. It is found that cement content is a prime factor controlling the strength of the cement-admixed clay. Besides cement content, curing period is important parameter that adds to the strength of cement-admixed clay. Increase in cement content leads to significant increase in Unconfined Compressive Strength (UCS) values especially at cement contents greater than 8%. The second part of the study investigated the bearing capacity of the clay ground improved by a group of end-bearing column using model tests under plain-strain condition. This study mainly focus to examine the effect of cement contents on the ultimate bearing capacity and failure stress of the improved clay ground. The study shows that the bearing capacity of the improved ground increases significantly with increase in cement contents of the soil-cement columns. A considerable increase in the stiffness of the model ground and failure stress was observed with increase in cement contents.

Keywords: bearing capacity, cement content, curing time, unconfined compressive strength, undrained shear strength

Procedia PDF Downloads 161

Authors: Leong Tatt Loh, Ming Kun Yew, Ming Chian Yew, Lip Huat Saw, Jing Han Beh, Siong Kang Lim, Foo Wei Lee

Abstract:

Oil palm shell (OPS) is the solid waste product from the palm oil sector of the agricultural industry and can be used as alternative coarse aggregates to substitute depleting conventional raw materials. This research aims to investigate the incorporation of various high-performance polypropylene (HPP) fibres with different geometry to enhance the mechanical properties and thermal conductivity of OPS lightweight concrete. The effect of different volume fractions (Vf) (0.05%, 0.10% and 0.15%) were studied for each fibre. The results reveal that the effectiveness of HPP fibres to increase the compressive strength at later ages was more pronounced than at early age. It is found that the use of HPP fibres reinforced OPS lightweight concrete (LWC) induced the advantageous of improving mechanical properties (compressive strength, flexural strength and splitting tensile strength) and thermal conductivity. Hence, this HPP fibres is a promising alternative solution to compensate lower mechanical properties as well as contribute to energy efficiency building material in the construction industry.

Keywords: oil palm shell, high performance polypropylene fibre, lightweight concrete, mechanical properties, thermal conductivity

Procedia PDF Downloads 189