Search results for: column reinforcement

Authors: Lahlou Dahmani, Warda Mekiri, Ahmed Boudjemia

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This scientific paper explores the comparison between the ultimate buckling load obtained through the Eurocode 3 methodology and the ultimate buckling load obtained through finite element simulations for steel columns under compression. The study aims to provide insights into the adequacy of the design rules proposed in Eurocode 3 for different slenderness ratios. The finite element simulations with the Ansys commercial program involve a geometrical and material non-linear analysis of the columns with imperfections. The loss of equilibrium is generally caused by the geometrically nonlinear effects where the column begins to buckle and lose its stability when the load reaches a certain critical value. The linear buckling analysis predicts the theoretical buckling strength of an elastic structure but the nonlinear one is more accurate with taking into account the initial imperfection.

Keywords: Ansys, linear buckling, eigen value, nonlinear buckling, slenderness ratio, Eurocode 3

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Authors: Opeyemi A. Oyewo, Seshibe Makgato

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This paper presents the synthesis, characterization, and application of pelletized chitosan immobilized sawdust cellulose nanocrystals (PCCN) in a fixed-bed column for the continuous adsorption of methyl blue (MB) from water. The product was characterized using FT-IR, XRD, and SEM analysis. Microstructural examination revealed that the pellets are porous and spherical. XRD examination revealed phases that can be attributed to the presence of chitosan in PCCN. The effects of starting concentration, bed depth, and flow rate on synthetic water were explored. To identify MB breakthrough behaviour, performance indices such as bed volume, adsorbent exhaustion rate, and service time were investigated. Furthermore, the breakthrough data were incorporated into both the Thomas and Bohart-Adams models. The Thomas model was suitable for describing MB breakthrough curves. However, more research with diverse water matrices may be required to assess the resilience of PCCN.

Keywords: adsorption, dynamic, methyl blue, pelletization

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Authors: Mohammad Khalid, Mariya Munir, Jacelyn Rice Boyaue

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Highways are considered a major source of pollution to storm-water, and its runoff can introduce various contaminants, including nutrients, Indicator bacteria, heavy metals, chloride, and phosphorus compounds, which can have negative impacts on receiving waters. This study assessed the ability of biochar for contaminants removal and to improve the water holding capacity of soil biochar mixture. For this, ten commercially available biochar has been strategically selected. Lab scale batch testing was done at 3% and 6% by the weight of the soil to find the preliminary estimate of contaminants removal along with hydraulic conductivity and water retention capacity. Furthermore, from the above-conducted studies, six best performing candidate and an application rate of 6% has been selected for the column studies. Soil biochar mixture was filled in 7.62 cm assembled columns up to a fixed height of 76.2 cm based on hydraulic conductivity. A total of eight column experiments have been conducted for nutrient, heavy metal, and indicator bacteria analysis over a period of one year, which includes a drying as well as a deicing period. The saturated hydraulic conductivity was greatly improved, which is attributed to the high porosity of the biochar soil mixture. Initial data from the column testing shows that biochar may have the ability to significantly remove nutrients, indicator bacteria, and heavy metals. The overall study demonstrates that biochar could be efficiently applied with clay soil to improve the soil's hydraulic characteristics as well as remove the pollutants from the stormwater runoff.

Keywords: biochar, nutrients, indicator bacteria, storm-water treatment, sustainability

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Authors: Muneerah Jeludin, V. Sivakumar

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Numerous laboratory-based research studies on the behavior of ground improved with granular columns with respect to bearing capacity have been well-documented. However, information on its settlement performance is still scarce. Laboratory model study on the settlement behavior of soft clay reinforced with granular columns was conducted and results are presented. The investigation uses a soft kaolin clay sample of 300 mm in diameter and 400 mm in length. The clay samples were reinforced with single and multiple granular columns of various lengths using the displacement and replacement installation method. The results indicated that that no settlement reduction was achieved for a short single floating column. The settlement reduction factors reported for L/d ratios of 5.0, 7.5 and 10.0 are in the range of 1 to 2. The findings obtained in this research showed that the reduction factors are considerably less and that load-sharing mechanism between columns and surrounding clay is complex, particularly for column groups and is affected by other factors such as negative skin friction.

Keywords: ground improvement, model test, reinforced soil, settlement

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Authors: A. Bouhaloufa, T. Kadri, S. Zouaoui, A. Belhacene

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To put more durable bridges, it is important to maintain existing structures, rather than investing in new structures. Instead of demolishing the old bridge and replace them with new, we must preserve and upgrade using better methods of diagnosis, auscultation and repair, the interest of this work is to increase the bearing capacity bridges damaged by additional prestressing, this type of reinforcement is growing continuously. In addition to excellent static strength, prestressing also has a very high resistance to fatigue, so it is suitable to solve the problem of failure of the bearing capacity of the bridges. This failure often comes to the development of overloads in quantity and quality, that is our daily traffic has increased and become very complicated, on the other hand its constituents are advanced in weight and speed and therefore almost all old bridges became unable to support the movement of the latter and remain disabled to all these problems. The main purpose of this work includes the following three aspects: - Determination of the main diseases and factors affecting the deterioration of bridges in Algeria, - Evaluation of the bearing capacity of bridges, - Proposal technical reinforcement to improve the bearing capacity of a degraded structure.

Keywords: bridges, repair, auscultation, diagnosis, pathology, additional prestressing

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Authors: Zandi Ahmad, Sokhanguei Yahya, Saboonchi Reza

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Objective: The new and modern lifestyle, especially in the twenty-first century and lack of movement in spinal structure have made patients and the physicians in the field of health and also other insurance companies in the developed and developing countries worry more than before about the abnormalities of spinal column- this great healthcare problem. The high prevalence of spinal column in all age groups -from children to adults- and in all professions have led the researchers to the idea of giving an opportunity to all those who worry about the dangers threatening the spinal column. Therefore, one of the corrective methods for these patients is using SEAS exercises. Materials and Methods: This study aims at investigating the effect of one-period of SEAS exercises on some spinal biomechanical and postural parameters in the students with idiopathic scoliosis. According to the nature of the study and research objectives as well as the data collection methods, the current research is a semi-empirical survey. The research population is comprised of students with idiopathic scoliosis. A total number of 30 students were selected using available sampling and divided into two groups of control and SEAS exercises. Scoliometer was used for data collection. Descriptive statistics were used to categorize the findings. Kolmogorov-Smirnov statistical models were used to confirm that the distribution of the data is normal and T-test was used for effectiveness. Hypothesis testing was done using SPSS21. Conclusion: Results show that SEAS exercises have a significant effect in Adam’s Test. Therefore, according to the obtained results, SEAS exercises can be used to recover idiopathic scoliosis among the students. Further studies in larger samples and treatment, periods as well as more follow-up investigations appear to be essential to prove these effects.

Keywords: SEAS exercises, idiopathic scoliosis, Adam’s test, exercise

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Authors: Shuyuan Lin, Zhaohui Huang, Mizi Fan

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In the majority of previous research into modelling large scale composite floor subjected to fire, the beam-to-column and beam-to-beam connections were assumed to behave either as pinned or rigid for simplicity, and the vertical shear and axial tension failures of the connection were not taken into account. We have recently developed robust two-noded connection models for modeling endplate and partial endplate steel connections under fire conditions. The main objective of this research is to systematically investigate the impact of the connections of protected beams, on the tensile membrane actions of supported floor slabs in which the failures of the connections, such as, axial tension, vertical shear and bending are accounted for. The models developed have very good numerical stability under a static solver condition, and can be used for large scale modelling of composite buildings in fire.

Keywords: fire, steel structure, component-based model, beam-to-column connections

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Authors: Mahdi Sadeghian, Mahmoud Hassanlourad, Alireza Ardakani, Reza Dinarvand

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In this research, the behavior of monopiles, under lateral loads, was investigated with vertical and oblique piles by Finite Element Method. In engineering practice when soil-pile interaction comes to the picture some simplifications are applied to reduce the design time. As a simplified replacement of soil and pile interaction analysis, pile could be replaced by a column. The height of the column would be equal to the free length of the pile plus a portion of the embedded length of it. One of the important factors studied in this study was that columns with an equivalent length (free length plus a part of buried depth) could be used instead of soil and pile modeling. The results of the analysis show that the more internal friction angle of the soil increases, the more the bearing capacity of the soil is achieved. This additional length is 6 to 11 times of the pile diameter in dense soil although in loose sandy soil this range might increase.

Keywords: Depth of fixity, Lateral bearing capacity, Oblique pile, Pile group, Soil-structure interaction

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Authors: Li Xu, Yang Hong, T. Zhao Wen

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Experimental results of many RC beam-column subassemblage indicate that slippage of longitudinal beam rebar within the joint and the shear deformation of joint core have significant influence on seismic behavior of the subassemblage. However, rigid joint assumption has been generally used in the seismic response analysis of RC frames, in which two kinds of inelastic deformation of joint have been ignored. Based on OpenSees platform, ‘Super Joint Element Model’ with more detailed inelastic mechanism is used to simulate the inelastic response of joints. Two finite element models of typical RC plane frame, namely considering or ignoring the inelastic deformation of joint respectively, were established and analyzed under seven strong earthquake waves. The simulated global and local inelastic deformations of the RC plane frame is shown and discussed. The analyses also confirm the security of the earthquake-resistant frame designed according to Chinese codes.

Keywords: frame structure, beam-column joint, longitudinal bar slippage, shear deformation, nonlinear analysis

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Authors: Sani Abubakar, Oumar Al-Mubarak Adoum

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The leaves extracts of Cassia sieberiana D. C. were screened for antimicrobial bioassay against Staphylococcus aureus, Salmonella typhi, and Escherichia coli and cytotoxicity using Brine Shrimp Test (BST). The crude ethanol extract, Chloroform soluble fraction, aqueous soluble fraction, ethyl acetate soluble fraction, methanol soluble fraction, and n-hexane soluble fraction were tested against antimicrobial and cytotoxicity. The Ethyl acetate fraction obtained proved to be most active in inducing complete lethality at minimum doses in BST and also active on Salmonella typhi. The bioactivity result was used to guide the column chromatography, which led to the isolation of pure compound CSB-8, which was found active in the BST with an LC₅₀ value of 34(722-182)µg/ml and showed remarkable activity on Salmonella typhi (zone of inhibition 25mm) at 10,000µg/ml. The ¹H-NMR, ¹³C NMR, FTIR, and GC-MS spectra of the compound suggested the proposed structure to be 2-pentadecanone.

Keywords: antimicrobial bioassay, cytotoxicity, column chromatagraphy, Cassia sieberiana D.C.

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Authors: Vivian A. Galindo, Maria C. Galvis, Jaime R. Obando, Alvaro Guarin

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In Colombia, most of the roads of the national tertiary road network are unpaved roads with granular rolling surface. These are very important ways of guaranteeing the mobility of people, products, and inputs from the agricultural sector from the most remote areas to urban centers; however, it has not paid much attention to the search for alternatives to avoid the occurrence of deteriorations that occur shortly after its commissioning. In recent years, geosynthetics have been used satisfactorily to reinforce unpaved roads on soft soils, with geotextiles and geogrids being the most widely used. The interaction of the geogrid and the aggregate minimizes the lateral movement of the aggregate particles and increases the load capacity of the material, which leads to a better distribution of the vertical stresses, consequently reducing the vertical deformations in the subgrade. Taking into account the above, the research aimed at the mechanical behavior of the granular material, used in unpaved roads with and without the presence of geogrids, from the development of laboratory tests through the loaded wheel tester (LWT). For comparison purposes, the reinforced conditions and traffic conditions to which this type of material can be accessed in practice were simulated. In total four types of geogrids, were tested with granular material; this means that five test sets, the reinforced material and the non-reinforced control sample were evaluated. The results of the numbers of load cycles and depth rutting supported by each test body showed the influence of the properties of the reinforcement on the mechanical behavior of the assembly and the significant increases in the number of load cycles of the reinforced specimens in relation to those without reinforcement.

Keywords: geosynthetics, load wheel tester LWT, tertiary roads, unpaved road, vertical deformation

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Authors: Masato Nishi, Tetsushi Kaburagi, Masashi Kurose, Tei Hirashima, Tetsusei Kurasiki

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The process of thermoforming a carbon fiber reinforced thermoplastic (CFRTP) has increased its presence in the automotive industry for its wide applicability to the mass production car. A non-isothermal forming for CFRTP can shorten its cycle time to less than 1 minute. In this paper, the textile reinforcement FE model which the authors proposed in a previous work is extended to the CFRTP model for non-isothermal forming simulation. The effect of thermoplastic is given by adding shell elements which consider thermal effect to the textile reinforcement model. By applying Reuss model to the stress calculation of thermoplastic, the proposed model can accurately predict in-plane shear behavior, which is the key deformation mode during forming, in the range of the process temperature. Using the proposed model, thermoforming simulation was conducted and the results are in good agreement with the experimental results.

Keywords: carbon fiber reinforced thermoplastic, finite element analysis, pre-impregnated textile composite, non-isothermal forming

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Authors: Riya Roy, Anjana Bhasi

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Column-supported embankments provide a practical and efficient solution for construction on soft soil due to the low cost and short construction times. In the recent years, geosynthetic have been used in combination with column systems to support embankments. The load transfer mechanism in these systems is a combination of soil arching effect, which occurs between columns and membrane effect of the geosynthetic. This paper aims at the study of soil arching effect on columnar embankments using finite element software, ABAQUS. An axisymmetric finite element model is generated and using this model, parametric studies are carried out. Thus the effects of various factors such as height of embankment fill, elastic modulus of pile and tensile stiffness of geosynthetic, on soil arching have been studied. The development of negative skin friction along the pile-soil interface have also been studied and the results obtained from this study are compared with the current design methods.

Keywords: ABAQUS, geosynthetic, negative skin friction, soil arching

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Authors: Nihal Murali, Kunal Gupta, Surekha Bhanot

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Training of artificial neural networks (ANNs) using reinforcement learning (RL) techniques is being widely discussed in the robot learning literature. The high model complexity of ANNs along with the model-free nature of RL algorithms provides a desirable combination for many robotics applications. There is a huge need for algorithms that generalize using raw sensory inputs, such as vision, without any hand-engineered features or domain heuristics. In this paper, the standard control problem of line following robot was used as a test-bed, and an ANN controller for the robot was trained on images from a live video feed using Q-learning. A virtual agent was first trained in simulation environment and then deployed onto a robot’s hardware. The robot successfully learns to traverse a wide range of curves and displays excellent generalization ability. Qualitative analysis of the evolution of policies, performance and weights of the network provide insights into the nature and convergence of the learning algorithm.

Keywords: artificial neural networks, q-learning, reinforcement learning, robot learning

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Authors: Szymon Rutkowski, Tomasz Korbak

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We present a reinforcement-learning-based method of training neural machine translation models without parallel corpora. The standard encoder-decoder approach to machine translation suffers from two problems we aim to address. First, it needs parallel corpora, which are scarce, especially for low-resource languages. Second, it lacks psychological plausibility of learning procedure: learning a foreign language is about learning to communicate useful information, not merely learning to transduce from one language’s 'encoding' to another. We instead pose the problem of learning to translate as learning a policy in a communication game between two agents: the translator and the classifier. The classifier is trained beforehand on a natural language inference task (determining the entailment relation between a premise and a hypothesis) in the target language. The translator produces a sequence of actions that correspond to generating translations of both the hypothesis and premise, which are then passed to the classifier. The translator is rewarded for classifier’s performance on determining entailment between sentences translated by the translator to disciple’s native language. Translator’s performance thus reflects its ability to communicate useful information to the classifier. In effect, we train a machine translation model without the need for parallel corpora altogether. While similar reinforcement learning formulations for zero-shot translation were proposed before, there is a number of improvements we introduce. While prior research aimed at grounding the translation task in the physical world by evaluating agents on an image captioning task, we found that using a linguistic task is more sample-efficient. Natural language inference (also known as recognizing textual entailment) captures semantic properties of sentence pairs that are poorly correlated with semantic similarity, thus enforcing basic understanding of the role played by compositionality. It has been shown that models trained recognizing textual entailment produce high-quality general-purpose sentence embeddings transferrable to other tasks. We use stanford natural language inference (SNLI) dataset as well as its analogous datasets for French (XNLI) and Polish (CDSCorpus). Textual entailment corpora can be obtained relatively easily for any language, which makes our approach more extensible to low-resource languages than traditional approaches based on parallel corpora. We evaluated a number of reinforcement learning algorithms (including policy gradients and actor-critic) to solve the problem of translator’s policy optimization and found that our attempts yield some promising improvements over previous approaches to reinforcement-learning based zero-shot machine translation.

Keywords: agent-based language learning, low-resource translation, natural language inference, neural machine translation, reinforcement learning

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Authors: Mohammad Reza Koushki Ardestani, Saeed Daneshmand, Mohammad Heydari Vini

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In the present study, AA7075/SiO2 composites have been fabricated via liquid metallurgy process. Using the degassing process, the wet ability of the molten aluminum alloys increased which improved the bonding between aluminum matrix and reinforcement (SiO2) particles. AA7075 alloy and SiO2 particles were taken as the base matrix and reinforcements, respectively. Then, contents of 2.5 and 5 wt. % of SiO2 subdivisions were added into the AA7075 matrix. To improve wettability and distribution, reinforcement particles were pre-heated to a temperature of 550°C for each composite sample. A uniform distribution of SiO2 particles was observed through the matrix alloy in the microstructural study. A hardened EN32 steel disc as the counter face was used to evaluate the wear rate pin-on-disc, a wear testing machine containing. The results showed that the wear rate of the AA/SiO2 composites was lesser than that of the monolithic AA7075 samples. Finally, The SEM worn surfaces of samples were investigated.

Keywords: Al7075, SiO₂, wear, composites, stir casting

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Authors: Parisa Ahmadi Oliaei, Seyed Abolhassan Naeini

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The knowledge of soil–reinforcement interaction parameters is particularly important in the design of reinforced soil structures. The pull-out test is one of the most widely used tests in this regard. The results of tensile tests may be very sensitive to boundary conditions, and more research is needed for a better understanding of the Pull-out response of reinforcement, so numerical analysis using the finite element method can be a useful tool for the understanding of the Pull-out response of soil-geogrid interaction. The main objective of the present study is to compare the numerical and experimental results of Pull- out a test on geogrid-reinforced sandy soils interactions. Plaxis 2D finite element software is used for simulation. In the present study, the pull-out test modeling has been done on sandy soil. The effect of geogrid hardness was also investigated by considering two different types of geogrids. The numerical results curve had a good agreement with the pull-out laboratory results.

Keywords: plaxis, pull-out test, sand, soil- geogrid interaction

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Authors: Ziying Wu, Danfeng Yan

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Multi-Access Edge Computing (MEC) is one of the key technologies of the future 5G network. By deploying edge computing centers at the edge of wireless access network, the computation tasks can be offloaded to edge servers rather than the remote cloud server to meet the requirements of 5G low-latency and high-reliability application scenarios. Meanwhile, with the development of IOV (Internet of Vehicles) technology, various delay-sensitive and compute-intensive in-vehicle applications continue to appear. Compared with traditional internet business, these computation tasks have higher processing priority and lower delay requirements. In this paper, we design a 5G-based Vehicle-Aware Multi-Access Edge Computing Network (VAMECN) and propose a joint optimization problem of minimizing total system cost. In view of the problem, a deep reinforcement learning-based joint computation offloading and task migration optimization (JCOTM) algorithm is proposed, considering the influences of multiple factors such as concurrent multiple computation tasks, system computing resources distribution, and network communication bandwidth. And, the mixed integer nonlinear programming problem is described as a Markov Decision Process. Experiments show that our proposed algorithm can effectively reduce task processing delay and equipment energy consumption, optimize computing offloading and resource allocation schemes, and improve system resource utilization, compared with other computing offloading policies.

Keywords: multi-access edge computing, computation offloading, 5th generation, vehicle-aware, deep reinforcement learning, deep q-network

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Authors: M. Kakavand, S. A. Naeini

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Dynamic properties of soil in small strains, especially for geotechnical engineers, are important for describing the behavior of soil and estimation of the earth structure deformations and structures, especially significant structures. This paper presents the effect of density on the shear modulus and damping ratio of saturated clean sand at various isotropic confining pressures. For this purpose, the specimens were compared with two different relative densities, loose Dr = 30% and dense Dr = 70%. Dynamic parameters were attained from a series of consolidated undrained fixed – free type torsional resonant column tests in small strain. Sand No. 161 is selected for this paper. The experiments show that by increasing sand density and confining pressure, the shear modulus increases and the damping ratio decreases.

Keywords: dynamic properties, shear modulus, damping ratio, clean sand, density, confining pressure, resonant column/torsional simple shear, TSS

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Authors: M. Jerold, V. Sivasubramanian

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In this study, nano zero valent iron Sargassum swartzii (nZVI-SS) biocomposite a marine algal based biosorbent was used for the removal of simulated crystal violet (CV) in batch and continuous fixed bed operation. The Box-Behnen design (BBD) experimental results revealed the biosoprtion was maximum at pH 7.5, biosorbent dosage 0.1 g/L and initial CV concentration of 100 mg/L. The effect of various column parameters like bed depth (3, 6 and 9 cm), flow rate (5, 10 and 15 mL/min) and influent CV concentration (5, 10 and 15 mg/L) were investigated. The exhaustion time increased with increase of bed depth, influent CV concentration and decrease of flow rate. Adam-Bohart, Thomas and Yoon-Nelson models were used to predict the breakthrough curve and to evaluate the model parameters. Out of these models, Thomas and Yoon-Nelson models well described the experimental data. Therefore, the result implies that nZVI-SS biocomposite is a cheap and most promising biosorbent for the removal of CV from wastewater.

Keywords: algae, biosorption, zero-valent, dye, wastewater

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Authors: Alica Höpken, Hergen Pargmann

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The resource-efficient planning of the complex production planning processes in the meat industry and the reduction of food waste is a permanent challenge. The complexity of the production planning process occurs in every part of the supply chain, from agriculture to the end consumer. It arises from long and uncertain planning phases. Uncertainties such as stochastic yields, fluctuations in demand, and resource variability are part of this process. In the meat industry, waste mainly relates to incorrect storage, technical causes in production, or overproduction. The high amount of food waste along the complex supply chain in the meat industry could not be reduced by simple solutions until now. Therefore, resource-efficient production planning by conventional methods is currently only partially feasible. The realization of intelligent, automated production planning is basically possible through the application of machine learning algorithms, such as those of reinforcement learning. By applying the adapted design thinking method, machine learning methods (especially reinforcement learning algorithms) are used for the complex production planning process in the meat industry. This method represents a concretization to the application area. A resource-efficient production planning process is made available by adapting the design thinking method. In addition, the complex processes can be planned efficiently by using this method, since this standardized approach offers new possibilities in order to challenge the complexity and the high time consumption. It represents a tool to support the efficient production planning in the meat industry. This paper shows an elegant adaption of the design thinking method to apply the reinforcement learning method for a resource-efficient production planning process in the meat industry. Following, the steps that are necessary to introduce machine learning algorithms into the production planning of the food industry are determined. This is achieved based on a case study which is part of the research project ”REIF - Resource Efficient, Economic and Intelligent Food Chain” supported by the German Federal Ministry for Economic Affairs and Climate Action of Germany and the German Aerospace Center. Through this structured approach, significantly better planning results are achieved, which would be too complex or very time consuming using conventional methods.

Keywords: change management, design thinking method, machine learning, meat industry, reinforcement learning, resource-efficient production planning

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Authors: Mohamed H. Sorour, Hayam F. Shaalan, Heba A. Hani, Eman S. Sayed, Amany A. El-Mansoup

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Heavy metals (HMs) present an increasing threat to aquatic and soil environment. Thus, techniques should be developed for the removal and/or recovery of those HMs from point sources in the generating industries. This paper reports our endeavors concerning the development of in-house developed weak cation exchange polyacrylate hydrogel kaolin composites for heavy metals removal. This type of composite enables desirable characteristics and functions including mechanical strength, bed porosity and cost advantages. This paper emphasizes the effect of varying crosslinker (methylenebis(acrylamide)) concentration. The prepared cation exchanger has been subjected to intensive characterization using X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), X-ray fluorescence (XRF) and Brunauer Emmett and Teller (BET) method. Moreover, the performance was investigated using synthetic and real wastewater for an industrial complex east of Cairo. Simulated and real wastewater compositions addressed; Cr, Co, Ni, and Pb are in the range of (92-115), (91-103), (86-88) and (99-125), respectively. Adsorption experiments have been conducted in both batch and column modes. In general, batch tests revealed enhanced cation exchange capacities of 70, 72, 78.2 and 99.9 mg/g from single synthetic wastes while, removal efficiencies of 82.2, 86.4, 44.4 and 96% were obtained for Cr, Co, Ni and Pb, respectively from mixed synthetic wastes. It is concluded that the mixed synthetic and real wastewaters have lower adsorption capacities than single solutions. It is worth mentioned that Pb attained higher adsorption capacities with comparable results in all tested concentrations of synthetic and real wastewaters. Pilot scale experiments were also conducted for mixed synthetic waste in a fluidized bed column for 48 hour cycle time which revealed 86.4%, 58.5%, 66.8% and 96.9% removal efficiency for Cr, Co, Ni, and Pb, respectively with maximum regeneration was also conducted using saline and acid regenerants. Maximum regeneration efficiencies for the column studies higher than the batch ones about by about 30% to 60%. Studies are currently under way to enhance the regeneration efficiency to enable successful scaling up of the adsorption column.

Keywords: polyacrylate hydrogel kaolin, ultrasonic irradiation, heavy metals, adsorption and regeneration

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Authors: Vara Prasad Vemu

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The aim of the present work is to investigate the mechanical properties and water absorption capacity of carbon and basalt fibers mixed with matrix epoxy. At present, there is demand for nature friendly products. Basalt reinforced composites developed recently, and these mineral amorphous fibres are a valid alternative to carbon fibres for their lower cost and to glass fibres for their strength. The present paper describes briefly on basalt and carbon fibres (uni-directional) which are used as reinforcement materials for composites. The matrix epoxy (LY 556-HY 951) is taken into account to assess its influence on the evaluated parameters. In order to use reinforced composites for structural applications, it is necessary to perform a mechanical characterization. With this aim experiments like tensile strength, flexural strength, hardness and water absorption are performed. Later the mechanical properties obtained from experiments are compared with ANSYS software results.

Keywords: carbon fibre, basalt fibre, uni-directional, reinforcement, mechanical tests, water absorption test, ANSYS

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Authors: Rahul Paul, Kedar Nath Das

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The paradigm of Reinforcement Learning (RL) has become prominent in training intelligent agents to make decisions in environments that are both dynamic and uncertain. The primary objective of RL is to optimize the policy of an agent in order to maximize the cumulative reward it receives throughout a given period. Nevertheless, the process of optimization presents notable difficulties as a result of the inherent trade-off between exploration and exploitation, the presence of extensive state-action spaces, and the intricate nature of the dynamics involved. Evolutionary Optimization Methods (EOMs) have garnered considerable attention as a supplementary approach to tackle these challenges, providing distinct capabilities for optimizing RL policies and value functions. The ongoing advancement of research in both RL and EOMs presents an opportunity for significant advancements in autonomous decision-making systems. The convergence of these two fields has the potential to have a transformative impact on various domains of artificial intelligence (AI) applications. This article highlights the considerable influence of EOMs in enhancing the capabilities of RL. Taking advantage of evolutionary principles enables RL algorithms to effectively traverse extensive action spaces and discover optimal solutions within intricate environments. Moreover, this paper emphasizes the practical implementations of EOMs in the field of RL, specifically in areas such as robotic control, autonomous systems, inventory problems, and multi-agent scenarios. The article highlights the utilization of EOMs in facilitating RL agents to effectively adapt, evolve, and uncover proficient strategies for complex tasks that may pose challenges for conventional RL approaches.

Keywords: machine learning, reinforcement learning, loss function, optimization techniques, evolutionary optimization methods

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Authors: M. Gangadharappa, M. Ravi Kumar, H. N. Reddappa

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The mechanical properties and morphological analysis of Al6061-Red mud particulate composites were investigated. The compositions of the composite include a matrix of Al6061 and the red mud particles of 53-75 micron size as reinforcement ranging from 0% to 12% at an interval of 2%. Stir casting technique was used to fabricate Al6061-Red mud composites. Density measurement, estimation of percentage porosity, tensile properties, fracture toughness, hardness value, impact energy, percentage elongation and percentage reduction in area. Further, the microstructures and SEM examinations were investigated to characterize the composites produced. The result shows that a uniform dispersion of the red mud particles along the grain boundaries of the Al6061 alloy. The tensile strength and hardness values increases with the addition of Red mud particles, but there is a slight decrease in the impact energy values, values of percentage elongation and percentage reduction in area as the reinforcement increases. From these results of investigation, we concluded that the red mud, an industrial waste can be used to enhance the properties of Al6061 alloy for engineering applications.

Keywords: Al6061, red mud, tensile strength, hardness and microstructures

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Authors: Hanifeh Imanian, Morteza Kolahdoozan

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The purpose of this study is to present a mathematical phrase for calculating the dispersion rate of spilled oil in water column under non-breaking waves. In this regard, a multiphase numerical model is applied for which waves and oil phase were computed concurrently, and accuracy of its hydraulic calculations have been proven. More than 200 various scenarios of oil spilling in wave waters were simulated using the multiphase numerical model and its outcome were collected in a database. The recorded results were investigated to identify the major parameters affected vertical oil dispersion and finally 6 parameters were identified as main independent factors. Furthermore, some statistical tests were conducted to identify any relationship between the dependent variable (dispersed oil mass in the water column) and independent variables (water wave specifications containing height, length and wave period and spilled oil characteristics including density, viscosity and spilled oil mass). Finally, a mathematical-statistical relationship is proposed to predict dispersed oil in marine waters. To verify the proposed relationship, a laboratory example available in the literature was selected. Oil mass rate penetrated in water body computed by statistical regression was in accordance with experimental data was predicted. On this occasion, it was necessary to verify the proposed mathematical phrase. In a selected laboratory case available in the literature, mass oil rate penetrated in water body computed by suggested regression. Results showed good agreement with experimental data. The validated mathematical-statistical phrase is a useful tool for oil dispersion prediction in oil spill events in marine areas.

Keywords: dispersion, marine environment, mathematical-statistical relationship, oil spill

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Authors: Precious Ehiomogue, Ifechukwude Israel Ahuchaogu, Isiguzo Edwin Ahaneku

Abstract:

Vermicompost is the product of the decomposition process using various species of worms, to create a mixture of decomposing vegetable or food waste, bedding materials, and vemicast. This process is called vermicomposting, while the rearing of worms for this purpose is called vermiculture. Several works have verified the adsorption of toxic metals using vermicompost but the application is still scarce for the retention of organic compounds. This research brings to knowledge the effectiveness of earthworm waste (vermicompost) for the remediation of crude oil contaminated soils. The remediation methods adopted in this study were two soil washing methods namely, batch and column process which represent laboratory and in-situ remediation. Characterization of the vermicompost and crude oil contaminated soil were performed before and after the soil washing using Fourier transform infrared (FTIR), scanning electron microscopy (SEM), X-ray fluorescence (XRF), X-ray diffraction (XRD) and Atomic adsorption spectrometry (AAS). The optimization of washing parameters, using response surface methodology (RSM) based on Box-Behnken Design was performed on the response from the laboratory experimental results. This study also investigated the application of machine learning models [Artificial neural network (ANN), Adaptive neuro fuzzy inference system (ANFIS). ANN and ANFIS were evaluated using the coefficient of determination (R²) and mean square error (MSE)]. Removal efficiency obtained from the Box-Behnken design experiment ranged from 29% to 98.9% for batch process remediation. Optimization of the experimental factors carried out using numerical optimization techniques by applying desirability function method of the response surface methodology (RSM) produce the highest removal efficiency of 98.9% at absorbent dosage of 34.53 grams, adsorbate concentration of 69.11 (g/ml), contact time of 25.96 (min), and pH value of 7.71, respectively. Removal efficiency obtained from the multilevel general factorial design experiment ranged from 56% to 92% for column process remediation. The coefficient of determination (R²) for ANN was (0.9974) and (0.9852) for batch and column process, respectively, showing the agreement between experimental and predicted results. For batch and column precess, respectively, the coefficient of determination (R²) for RSM was (0.9712) and (0.9614), which also demonstrates agreement between experimental and projected findings. For the batch and column processes, the ANFIS coefficient of determination was (0.7115) and (0.9978), respectively. It can be concluded that machine learning models can predict the removal of crude oil from polluted soil using vermicompost. Therefore, it is recommended to use machines learning models to predict the removal of crude oil from contaminated soil using vermicompost.

Keywords: ANFIS, ANN, crude-oil, contaminated soil, remediation and vermicompost

Procedia PDF Downloads 111

Authors: Mohammad S. Rouhi, Magdalena Juntikka

Abstract:

Processing of polymer fiber composites has a remarkable influence on their mechanical performance. These mechanical properties are even more influenced when using recycled reinforcement. Therefore, we place particular attention on the evaluation of micromechanical models to estimate the mechanical properties and compare them against the experimental results of the manufactured composites. For the manufacturing process, an epoxy matrix and carbon fiber production cut-offs as reinforcing material are incorporated using a vacuum infusion process. In addition, continuous textile reinforcement in combination with the epoxy matrix is used as reference material to evaluate the kick-down in mechanical performance of the recycled composite. The experimental results show less degradation of the composite stiffness compared to the strength properties. Observations from the modeling also show the same trend as the error between the theoretical and experimental results is lower for stiffness comparisons than the strength calculations. Yet still, good mechanical performance for specific applications can be expected from these materials.

Keywords: composite recycling, carbon fibers, mechanical properties, micromechanics

Procedia PDF Downloads 161

Authors: Mohammadreza Akbari, Pooya Soleimani Besheli, Reza Khalili, Sara Akbari

Abstract:

In this study, we investigate building structures nonlinear behavior also solving analytic of nonlinear differential at vibrations. As we know most of engineering systems behavior in practical are non- linear process (especial at structural) and analytical solving (no numerical) these problems are complex, difficult and sometimes impossible (of course at form of analytical solving). In this symposium, we are going to exposure one method in engineering, that can solve sets of nonlinear differential equations with high accuracy and simple solution and so this issue will emerge after comparing the achieved solutions by Numerical Method (Runge-Kutte 4th) and exact solutions. Finally, we can proof AGM method could be created huge evolution for researcher and student (engineering and basic science) in whole over the world, because of AGM coding system, so by using this software, we can analytical solve all complicated linear and nonlinear differential equations, with help of that there is no difficulty for solving nonlinear differential equations.

Keywords: new method AGM, vibrations, beam-column, angular frequency, energy dissipated, critical load

Procedia PDF Downloads 391

Authors: Lian Song, Shao-Bo Kang, Bo Yang

Abstract:

Concrete filled steel tubular (CFST) structure has been widely used in construction practices due to its superior performances under various loading conditions. However, limited studies are available when this type of structure is subjected to impact or explosive loads. Current methods in relevant design codes are not specific for preventing progressive collapse of CFST structures. Therefore, it is necessary to carry out numerical simulations on CFST structure under impact loads. In this study, finite element analyses are conducted on the mechanical behaviour of composite frames which composed of CFST columns and steel beams subject to impact loading. In the model, CFST columns are simulated using finite element software ABAQUS. The model is verified by test results of solid and hollow CFST columns under lateral impacts, and reasonably good agreement is obtained through comparisons. Thereafter, a multi-scale finite element modelling technique is developed to evaluate the behaviour of a five-storey three-span planar composite frame. Alternate path method and direct simulation method are adopted to perform the dynamic response of the frame when a supporting column is removed suddenly. In the former method, the reason for column removal is not considered and only the remaining frame is simulated, whereas in the latter, a specific impact load is applied to the frame to take account of the column failure induced by vehicle impact. Comparisons are made between these two methods in terms of displacement history and internal force redistribution, and design recommendations are provided for the design of CFST structures under impact loads.

Keywords: planar composite frame, collapse analysis, impact loading, direct simulation method, alternate path method

Procedia PDF Downloads 519