Search results for: mechanical strength prediction

Authors: Bencheikh Messaouda, Aidoud Assia, Salima Boukour, Benamara Fatima Zohra, Boukhatem Ghania, Zegueur Chaouki Salah Eddine

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The utilization of waste materials in civil engineering has gained widespread attention in recent years due to their adverse effects on the environment. One such waste material is coffee grounds, a black residue generated daily across the country after coffee brewing. Instead of disposing of it, there is a growing interest in repurposing it for various agricultural and industrial applications. Utilizing coffee grounds in geotechnical engineering, such as in road embankments, presents an opportunity for its valorization. The study aims to contribute to the valorization of coffee grounds by enhancing the physical and mechanical properties of clayey soils through their incorporation at varying weight percentages (3%, 6%, 9%, 12%) as partial replacements in these soils. This not only addresses the issue of coffee ground waste but also makes a tangible contribution to sustainable development. The findings demonstrate that incorporating coffee grounds generally has positive effects on the physical and mechanical properties of clayey soil. However, the extent of these effects depends on factors such as the quantity of coffee grounds added, the particle size of the grounds, and the characteristics of the soil. Additionally, coffee grounds can improve the compression and tensile strength of clayey soil, resulting in increased stability and reduced susceptibility to deformation under external forces.

Keywords: clay soil, coffee grounds, optimizing, improvement, valorization, waste

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Authors: Ajit Brindhaban

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Background and Purpose: Computed Tomography (CT) scans have become the largest source of radiation in radiological imaging. The purpose of this study was to compare the quality of pediatric Computed Tomography (CT) images reconstructed using Filtered Back Projection (FBP) with images reconstructed using different strengths of Iterative Reconstruction (IR) technique, and to perform a feasibility study to assess the use of IR techniques as a dose reduction tool. Materials and Methods: An anthropomorphic phantom representing a 5-year old child was scanned, in two stages, using a Siemens Somatom CT unit. In stage one, scans of the head, chest and abdomen were performed using standard protocols recommended by the scanner manufacturer. Images were reconstructed using FBP and 5 different strengths of IR. Contrast-to-Noise Ratios (CNR) were calculated from average CT number and its standard deviation measured in regions of interest created in the lungs, bone, and soft tissues regions of the phantom. Paired t-test and the one-way ANOVA were used to compare the CNR from FBP images with IR images, at p = 0.05 level. The lowest strength value of IR that produced the highest CNR was identified. In the second stage, scans of the head was performed with decreased mA(s) values relative to the increase in CNR compared to the standard FBP protocol. CNR values were compared in this stage using Paired t-test at p = 0.05 level. Results: Images reconstructed using IR technique had higher CNR values (p < 0.01.) in all regions compared to the FBP images, at all strengths of IR. The CNR increased with increasing IR strength of up to 3, in the head and chest images. Increases beyond this strength were insignificant. In abdomen images, CNR continued to increase up to strength 5. The results also indicated that, IR techniques improve CNR by a up to factor of 1.5. Based on the CNR values at strength 3 of IR images and CNR values of FBP images, a reduction in mA(s) of about 20% was identified. The images of the head acquired at 20% reduced mA(s) and reconstructed using IR at strength 3, had similar CNR as FBP images at standard mA(s). In the head scans of the phantom used in this study, it was demonstrated that similar CNR can be achieved even when the mA(s) is reduced by about 20% if IR technique with strength of 3 is used for reconstruction. Conclusions: The IR technique produced better image quality at all strengths of IR in comparison to FBP. IR technique can provide approximately 20% dose reduction in pediatric head CT while maintaining the same image quality as FBP technique.

Keywords: filtered back projection, image quality, iterative reconstruction, pediatric computed tomography imaging

Procedia PDF Downloads 148

Authors: Chayan Gupta, Arun Prasad

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The quick evolution of industrialization causes the scarcity of precious land. Thus, it is vital need to influence the R&D societies to achieve sustainable, economic and social benefits from huge utilization of waste for universal aids. The current study promotes the influence of steel industries waste i.e. ground granulated blast furnace slag (GGBS) in geotechnical properties of jarosite waste (solid waste residues produced from hydrometallurgy operations involved in extraction of Zinc). Numerous strengths tests (unconfined compression (qu) and splitting tensile strength (qt)) are conducted on jarosite-GGBS blends (GGBS, 10-30%) with different curing periods (7, 28 & 90 days). The results indicate that both qu and qt increase with the increase in GGBS content along with curing periods. The increased strength with the addition of GGBS is also observed from microstructural study, which illustrates the occurrence of larger agglomeration of jarosite-GGBS blend particles. The Freezing-Thawing (F-T) durability analysis is also conducted for all the jarosite-GGBS blends and found that the reduction in unconfined compressive strength after five successive F-T cycles enhanced from 62% (natural jarosite) to 48, 42 and 34% at 7, 14 and 28 days curing periods respectively for stabilized jarosite-GGBS samples containing 30% GGBS content. It can be concluded from this study that blending of cementing additives (GGBS) with jarosite waste resulted in a significant improvement in geotechnical characteristics.

Keywords: jarosite, GGBS, strength characteristics, microstructural study, durability analysis

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Authors: Zhenhua Wei, Gabriel Falzone, Bu Wang, Laurent Pilon, Gaurav Sant

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The production of ordinary Portland cement (OPC) is a CO₂ intensive process. Specifically, cement clinkering reactions require not only substantial energy in the form of heat, but also result in the release of CO₂, from limestone decarbonation and the combustion of fuel. To overcome this CO₂ intensive process, clinkering-free cementation is demonstrated by the carbonation of fly ash; i.e., a by-product of coal combustion. It is shown that in moist environments and at sub-boiling temperatures, calcium-rich fly ashes readily react with gas-phase CO₂ to provide cementation. After seven days of CO₂ exposure at 75°C, such formulations achieve a compressive strength on the order of 35 MPa and take-up 9% CO₂ (by mass of the solid). On the other hand, calcium-deficient fly ashes, due to their lack of alkalinity (i.e., abundance of mobile Ca or Mg), show little if any potential for CO₂ uptake and strength gain. The role of the CO₂ concentration and processing temperature are discussed and linked to the progress of reactions, and the development of microstructure. The outcomes demonstrate a means for enabling clinkering-free cementation while enabling beneficial utilization of CO₂ and fly ash; i.e., two abundant but underutilized industrial by-products.

Keywords: fly ash, carbonation, concrete, strength

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Authors: Erik Vassøy Olsen, Hirpa G. Lemu

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Inspired by the Formula-1 competition, IMechE (Institute of Mechanical Engineers) and Formula SAE (Society of Mechanical Engineers) organize annual competitions for University and College students worldwide to compete with a single-seat race car they have designed and built. The design of the chassis or the frame is a key component of the competition because the weight and stiffness properties are directly related with the performance of the car and the safety of the driver. In addition, a reduced weight of the chassis has a direct influence on the design of other components in the car. Among others, it improves the power to weight ratio and the aerodynamic performance. As the power output of the engine or the battery installed in the car is limited to 80 kW, increasing the power to weight ratio demands reduction of the weight of the chassis, which represents the major part of the weight of the car. In order to reduce the weight of the car, ION Racing team from the University of Stavanger, Norway, opted for a monocoque design. To ensure fulfilment of the above-mentioned requirements of the chassis, the monocoque design should provide sufficient torsional stiffness and absorb the impact energy in case of a possible collision. The study reported in this article is based on the requirements for Formula Student competition. As part of this study, diverse mechanical tests were conducted to determine the mechanical properties and performances of the monocoque design. Upon a comprehensive theoretical study of the mechanical properties of sandwich composite materials and the requirements of monocoque design in the competition rules, diverse tests were conducted including 3-point bending test, perimeter shear test and test for absorbed energy. The test panels were homemade and prepared with an equivalent size of the side impact zone of the monocoque, i.e. 275 mm x 500 mm so that the obtained results from the tests can be representative. Different layups of the test panels with identical core material and the same number of layers of carbon fibre were tested and compared. Influence of the core material thickness was also studied. Furthermore, analytical calculations and numerical analysis were conducted to check compliance to the stated rules for Structural Equivalency with steel grade SAE/AISI 1010. The test results were also compared with calculated results with respect to bending and torsional stiffness, energy absorption, buckling, etc. The obtained results demonstrate that the material composition and strength of the composite material selected for the monocoque design has equivalent structural properties as a welded frame and thus comply with the competition requirements. The developed analytical calculation algorithms and relations will be useful for future monocoque designs with different lay-ups and compositions.

Keywords: composite material, Formula student, ION racing, monocoque design, structural equivalence

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Authors: Armenuhi Ghazaryan, Qnarik Poghosyan, Tadevos Markosyan

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We have considered the high-order harmonic generation in-plane graphene quantum dots of hexagonal shape by the independent quasiparticle approximation-tight binding model. We have investigated how such a nonlinear effect is affected by a strong optical wave field, quantum dot typical band gap and lateral size, and dephasing processes. The equation of motion for the density matrix is solved by performing the time integration with the eight-order Runge-Kutta algorithm. If the optical wave frequency is much less than the quantum dot intrinsic band gap, the main aspects of multiphoton high harmonic emission in quantum dots are revealed. In such a case, the dependence of the cutoff photon energy on the strength of the optical pump wave is almost linear. But when the wave frequency is comparable to the bandgap of the quantum dot, the cutoff photon energy shows saturation behavior with an increase in the wave field strength.

Keywords: strong wave field, multiphoton, bandgap, wave field strength, nanostructure

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Authors: Pradeep Joshi, Prashant Dhiman, Shiv Dayal Dhakad

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Inconel 718 is a family if Nickel-Chromium based Superalloy; it has very high oxidation and corrosion resistance. Inconel 718 is widely being used in aerospace, engine, turbine etc. due to its high mechanical strength and creep resistance. Being widely used, its machining should be easy but in real its machining is very difficult, especially by using traditional machining methods. It becomes easy to machine only by using non Traditional machining such as EDM. During EDM machining there is wear of both tool and workpiece, the tool wear is undesired because it changes tool shape, geometry. To reduce the tool wear rate (TWR) cryogenic treatment is performed on tool before the machining operation. The machining performances of the process are to be evaluated in terms of MRR, TWR which are functions of Discharge current, Pulse on-time, Pulse Off-time.

Keywords: EDM, cyrogenic, TWR, MRR

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Authors: Jitrawadee Meerasri, Rungsinee Sothornvit

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Pectin is a structural polysaccharide from plant cell walls and can be used as a stabilizer, gelling and film-forming agents to improve many food products. Moreover, pectin film as a natural biopolymer can be a carrier of several active ingredients such as antioxidant and antimicrobial to provide an active or functional film. Gamma-aminobutyric acid (GABA) is a well-known agent to reduce neuronal excitability throughout the nervous system and it is interesting to investigate the GABA effect as a substitute of normal plasticizer (glycerol) on edible film properties. Therefore, the objective of this study was to determine the effect of GABA concentrations (5-15% of pectin) on film mechanical properties, moisture content, water vapor permeability, and solubility compared with those from glycerol (10% of pectin) plasticized pectin film including a control film (pectin film without any plasticizer). It was found that an increase in GABA concentrations decreased film tensile strength, modulus, solubility and water vapor permeability, but elongation was increased without a change in the moisture content. The smaller amount of GABA showed the equivalent film properties as using a higher amount of glycerol. Consequently, GABA can act as an alternative plasticizer substitute of glycerol at the lower amount used. Moreover, GABA provides the nutritional high value in the food products when the edible packaging material is consumed with products.

Keywords: gamma-aminobutyric acid, pectin, plasticizer, edible film

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Authors: Chaiyaporn Yuksen

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Backgroud: Supraventricular tachycardia (SVT) is an abnormally fast atrial tachycardia characterized by narrow (≤ 120 ms) and constant QRS. Adenosine was the drug of choice; the first dose was 6 mg. It can be repeated with the second and third doses of 12 mg, with greater than 90% success. The study found that patients observed at 4 hours after normal sinus rhythm was no recurrence within 24 hours. The objective of this study was to investigate the factors that influence the recurrence of SVT after adenosine in the emergency department (ED). Method: The study was conducted retrospectively exploratory model, prognostic study at the Emergency Department (ED) in Faculty of Medicine, Ramathibodi Hospital, a university-affiliated super tertiary care hospital in Bangkok, Thailand. The study was conducted for ten years period between 2010 and 2020. The inclusion criteria were age > 15 years, visiting the ED with SVT, and treating with adenosine. Those patients were recorded with the recurrence SVT in ED. The multivariable logistic regression model developed the predictive model and prediction score for recurrence PSVT. Result: 264 patients met the study criteria. Of those, 24 patients (10%) had recurrence PSVT. Five independent factors were predictive of recurrence PSVT. There was age>65 years, heart rate (after adenosine) > 100 per min, structural heart disease, and dose of adenosine. The clinical risk score to predict recurrence PSVT is developed accuracy 74.41%. The score of >6 had the likelihood ratio of recurrence PSVT by 5.71 times Conclusion: The clinical predictive score of > 6 was associated with recurrence PSVT in ED.

Keywords: clinical prediction score, SVT, recurrence, emergency department

Procedia PDF Downloads 155

Authors: A. Hocine, A. Ghouaoula, S. M. Medjdoub, M. Cherifi

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The present paper proposed a meso–macro model describing the mechanical behaviour composite laminates of staking sequence [+θ/-θ]s under tensil loading. The behaviour of a layer is ex-pressed through elasticity coupled to damage. The elastic strain is due to the elasticity of the layer and can be modeled by using the classical laminate theory, and the laminate is considered as an orthotropic material. This means that no coupling effect between strain and curvature is considered. In the present work, the damage is associated to cracking of the matrix and parallel to the fibers and it being taken into account by the changes in the stiffness of the layers. The anisotropic damage is completely described by a single scalar variable and its evolution law is specified from the principle of maximum dissipation. The stress/strain relationship is investigated in plane stress loading.

Keywords: damage, behavior modeling, meso-macro model, composite laminate, membrane loading

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Authors: Okafor C. Uche, Agbo P. Ejiofor, Okezie C. Eziuche

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This study provides a regeneration protocol for Treculia africana Decne (an endangered plant) through embryo culture. Mature zygotic embryos of T. africana were excised from the seeds aseptically and cultured on varied strengths (full, half and quarter) of Murashige and Skoog (MS) basal medium supplemented. All treatments experienced 100±0.00 percent sprouting except for half and quarter strengths. Plantlets in MS full strength had the highest fresh weight, leaf area, and longest shoot length when compared to other treatments. All explants in full, half, quarter strengths and control had the same number of leaves and sprout rate. Between the treatments, there was a significant difference (P>0.05) in their effect on the length of shoot and root, number of adventitious root, leaf area, and fresh weight. Full strength had the highest mean value in all the above-mentioned parameters and differed significantly (P>0.05) from others except in shoot length, number of adventitious roots, and root length where it did not differ (P<0.05) from half strength. The result of this study indicates that full strength MS basal medium offers a better option for the optimum growth for Treculia africana regeneration in vitro.

Keywords: medium strengths, Murashige and Skoog, Treculia africana, zygotic embryos

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Authors: S. A. Naeini, A. Mahigir

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Naturally occurring cohesive soil deposits are inherently anisotropic with respect to different properties amongst which is the shear strength. The anisotropy is primary due to the process of sedimentation followed by predominantly one-dimensional consolidation. However, most soils in their natural states exhibit some anisotropy with respect to shear strength and some non-homogeneity with respect to depth. In this paper the standard Mohr-Coulomb yield criterion was modified to consider the anisotropic shear strength properties. The term non-homogeneity used in this paper refers to only the cohesion intercept which is assumed to vary linearly with depth. The effect of both anisotropy and deterministic non-homogeneity on bearing capacity of shallow foundation was investigated using finite difference method. Result of numerical analysis indicates that the cohesion anisotropy has a significant effect on bearing capacity of shallow foundation. Furthermore, the linear and bilinear heterogeneity affects the bearing capacity in a similar way although the anisotropy issue emerges to be more important as far as shallow foundations are considered.

Keywords: anisotropic ratio, finite difference analysis, bearing capacity, heterogeneity

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Authors: Vinod B. Suryawanshi, Ajit D. Kelkar

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Glass fiber reinforced composites materials, due their unique properties such as high mechanical strength to weight ratio, corrosion resistance, and impact resistance have huge potential as structural materials in automotive, construction and transportation applications. However, these properties often come at higher cost owing to complex design methods, difficult manufacturing processes and raw material cost. In this paper, a cost effective design and manufacturing approach for a composite cantilever beam structure is presented. A constant stress (variable cross section) beam concept has been used to design and optimize the shape of composite cantilever beam and thus obtain the reduction in material used. The variable cross section beam was fabricated from the glass epoxy prepregs using cost effective out of autoclave process. The drop ply technique has been successfully used to obtain the variation in the cross section along the span of the beam. In order to test the beam and validate the design, the beam was subjected to different end loads. Strain gauges were mounted along the length of the beam to obtain strains in the beam at different sections and loads. The strain values were used to calculate the flexural strength and bending stresses in the beam. The stresses obtained through strain measurements from the experiment were found to be uniform along the span of the beam, and thus validates the design. Finally, the finite element model for the constant stress beam was developed using commercial finite element simulation software. It was observed that the simulation results agreed very well with the experimental results.

Keywords: beams, composites, constant cross-section, structures

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Authors: S. Girish, N. Ajay

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Permeation properties have been widely used to quantify durability characteristics of concrete for assessing long term performance and sustainability. The processes of deterioration in concrete are mediated largely by water. There is a strong interest in finding a better way of assessing the material properties of concrete in terms of durability. Water sorptivity is a useful single material property which can be one of the measures of durability useful in service life planning and prediction, especially in severe environmental conditions. This paper presents the results of the comparative study of sorptivity of Self-Compacting Concrete (SCC) with conventionally vibrated concrete. SCC is a new, special type of concrete mixture, characterized by high resistance to segregation that can flow through intricate geometrical configuration in the presence of reinforcement, under its own mass, without vibration and compaction. SCC mixes were developed for the paste contents of 0.38, 0.41 and 0.43 with fly ash as the filler for different cement contents ranging from 300 to 450 kg/m3. The study shows better performance by SCC in terms of capillary absorption. The sorptivity value decreased as the volume of paste increased. The use of higher paste content in SCC can make the concrete robust with better densification of the micro-structure, improving the durability and making the concrete more sustainable with improved long term performance. The sorptivity based on secondary absorption can be effectively used as a durability index to predict the time duration required for the ingress of water to penetrate the concrete, which has practical significance.

Keywords: self-compacting concrete, service life prediction, sorptivity, volume of paste

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Authors: Alireza Barari, Saeed Shirali

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The etiology of obesity is heterogeneous with several factors, and the pathophysiology of obesity has recently related to leptin, oxidative damage, and inflammation. Silybum marianum have a health-promoting perspective and has shown that bioactive molecules of silymarin have the antioxidant and antitumor properties and can affect secretion of hormones and enzyme activity in animal. This study aimed to evaluate the antioxidant effects and changes in hormonal levels and body composition after silymarin consumption. Forty-five healthy untrained colleges male take part in the 4-week investigation. The subjects were assigned to 5 groups: endurance training, Silymarin with endurance training, strength training with placebo, Silymarin with strength training or placebo. Body fat percentage and Blood sample analysis were measured before and after the intervention to assay leptin, adiponectin and paraoxonase in the sample of subject's serum. There was a considerable decrease in body fat percent and a significant increase in VO2 max in 'Strength training' and 'Strength training with Silymarin' groups. But, no significant changes in levels of leptin, adiponectinin, and paraoxanase (PON) that were observed between exercise and exercise with Silymarin in these groups. We observed reduction in body fat% and increase in adiponectin induced by exercise for 4 weeks in untrained healthy men. Silybin, could not effectively improve all parameters and don’t prevent the progression of cell damage by antioxidant activity of PON.

Keywords: anti-inflammatory activity, antioxidant activity, silymarin, body composition, paraoxonase (PON)

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Authors: Filip Stojcevski, Tim Hilditch, Luke Henderson

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Although carbon fibre composites are becoming ever more prominent in the engineering industry, interfacial failure still remains one of the most common limitations to material performance. Carbon fiber surface treatments have played a major role in advancing composite properties however research into the influence of manufacturing variables on a fiber manufacturing line is lacking. This project investigates the impact of altering carbon fiber manufacturing conditions on a production line (specifically electrochemical oxidization and sizing variables) to assess fiber-matrix adhesion. Pristine virgin fibers were manufactured and interfacial adhesion systematically assessed from a microscale (single fiber) to a mesoscale (12k tow), and ultimately a macroscale (laminate). Correlations between interfacial shear strength (IFSS) at each level is explored as a function of known interfacial bonding mechanisms; namely mechanical interlocking, chemical adhesion and fiber wetting. Impact of these bonding mechanisms is assessed through extensive mechanical, topological and chemical characterisation. They are correlated to performance as a function of IFSS. Ultimately this study provides a bottoms up approach to improving composite laminates. By understanding the scaling effects from a singular fiber to a composite laminate and linking this knowledge to specific bonding mechanisms, material scientists can make an informed decision on the manufacturing conditions most beneficial for interfacial adhesion.

Keywords: carbon fibers, interfacial adhesion, surface treatment, sizing

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Authors: Arpit Patil, Atharav Bhagwat, Rajas Bhope, Pramod Bide

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This research integrates IoT and ML to predict heart failure risks, utilizing the Framingham dataset. IoT devices gather real-time physiological data, focusing on heart rate dynamics, while ML, specifically Random Forest, predicts heart failure. Rigorous feature selection enhances accuracy, achieving over 90% prediction rate. This amalgamation marks a transformative step in proactive healthcare, highlighting early detection's critical role in cardiovascular risk mitigation. Challenges persist, necessitating continual refinement for improved predictive capabilities.

Keywords: cardiovascular diseases, internet of things, machine learning, cardiac risk assessment, heart failure prediction, early detection, cardio data analysis

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Authors: Marthin Dody Josias Sumajouw, Bryan Wijaya, Servie O. Dapas, Ronny E. Pandaleke, Banu Handono, Fabian J. Manoppo

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Ordinary Portland Cement (OPC) takes a big role as a concrete binder in infrastructure construction purposes, nevertheless, it produces CO2 emissions abundantly. To reduce the CO2 emissions produced by OPC concrete, nowadays, geopolymer material become one of the solutions due to it being a binder made from waste with pozzolan material. In concrete industries, geopolymer concrete has evolved as a more environmentally friendly material than OPC concrete. The geopolymer concrete was created without the usage of OPC known as cementless concrete materials. Geopolymer concrete obtains silicon and aluminum from industrial by-products such as fly ash, ground granulated blast furnace slag, and kaolinite. A highly alkaline solution chemically activates Si and Al, forming a matrix that holds together the loose aggregates as well as additional unreacted components in the mixture. They are then dissolved in alkaline activating solutions, where they polymerize into molecular chains, resulting in rigid binders. This research aims to get an eco-friendly material that can reduce the use of OPC as a binder and be used for infrastructure development end-products such as Curbs, Pavement Bricks, and Wall Bricks. This research was conducted as applied research to develop new products of environmentally friendly materials by utilizing fly ash and employed for infrastructure development, particularly for the production of end products such as Curbs, Pavement Bricks, and Wall Bricks. Three types of end products with various dimensions and mix designs have been made and tested in the laboratory, resulting in quantitative datasets to be used for identifying patterns and relationships among density, compressive strength, flexural strength, and water absorption. The result found that geopolymer binders can be used for the production of curbs, pavement bricks, and wall bricks. Geopolymer curbs have an average compressive strength of 19,36 MPa, which can be determined as K-233 concrete. Geopolymer pavement bricks have an average compressive strength of 20,79 MPa. It can be used in parking areas and determined as the grade B of pavement bricks according to SNI 03-0691-1996. Geopolymer wall bricks have an average compressive strength of 11,24 MPa, which can be determined as the grade I of Wall Bricks according to SNI 03-0349-1989.

Keywords: absorption, compressive strength, curbs, end products, geopolymer, pavement bricks, wall bricks

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Authors: D. Varadaradjou, H. Kebir, J. Mespoulet, D. Tingaud, S. Bouvier, P. Deconick, K. Ameyama, G. Dirras

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The development of new architecture metallic alloys with controlled microstructures is one of the strategic ways for designing materials with high innovation potential and, particularly, with improved mechanical properties as required for structural materials. Indeed, unlike conventional counterparts, metallic materials having so-called harmonic structure displays strength and ductility synergy. The latter occurs due to a unique microstructure design: a coarse grain structure surrounded by a 3D continuous network of ultra-fine grain known as “core” and “shell,” respectively. In the present study, pure harmonic-structured (HS) Nickel samples were processed via controlled mechanical milling and followed by spark plasma sintering (SPS). The present work aims at characterizing the mechanical properties of HS pure Nickel under room temperature dynamic loading through a Split Hopkinson Pressure Bar (SHPB) test and the underlying microstructure evolution. A stopper ring was used to maintain the strain at a fixed value of about 20%. Five samples (named B1 to B5) were impacted using different striker bar velocities from 14 m/s to 28 m/s, yielding strain rate in the range 4000-7000 s-1. Results were considered until a 10% deformation value, which is the deformation threshold for the constant strain rate assumption. The non-deformed (INIT – post-SPS process) and post-SHPB microstructure (B1 to B5) were investigated by EBSD. It was observed that while the strain rate is increased, the average grain size within the core decreases. An in-depth analysis of grains and grain boundaries was made to highlight the thermal (such as dynamic recrystallization) or mechanical (such as grains fragmentation by dislocation) contribution within the “core” and “shell.” One of the most widely used methods for determining the dynamic behavior of materials is the SHPB technique developed by Kolsky. A 3D simulation of the SHPB test was created through ABAQUS in dynamic explicit. This 3D simulation allows taking into account all modes of vibration. An inverse approach was used to identify the material parameters from the equation of Johnson-Cook (JC) by minimizing the difference between the numerical and experimental data. The JC’s parameters were identified using B1 and B5 samples configurations. Predictively, identified parameters of JC’s equation shows good result for the other sample configuration. Furthermore, mean rise of temperature within the harmonic Nickel sample can be obtained through ABAQUS and show an elevation of about 35°C for all fives samples. At this temperature, a thermal mechanism cannot be activated. Therefore, grains fragmentation within the core is mainly due to mechanical phenomena for a fixed final strain of 20%.

Keywords: 3D simulation, fragmentation, harmonic structure, high strain rate, Johnson-cook model, microstructure

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Authors: Behnaz Baghaei, Mikael Skrifvars

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Sustainability is today a trend that is seen everywhere, with no exception for the textiles 31 industry. However, there is a rather significant downside regarding how the textile industry currently operates, namely the huge amount of end-of-life textiles coming along with it. Approximately 73% of the 53 million tonnes of fibres used annually for textile production is landfilled or incinerated, while only 12% is recycled as secondary products. Mechanical recycling of end-of-life textile fabrics into yarns and fabrics was before very common, but due to the low costs for virgin man-made fibres, the current textile material composition diversity, the fibre material quality variations and the high recycling costs this route is not feasible. Another way to decrease the ever-growing pile of textile waste is to repurpose the textile. If a feasible methodology can be found to reuse end-of life textiles as secondary market products including a manufacturing process that requires rather low investment costs, then this can be highly beneficial to counteract the increasing textile waste volumes. In structural composites, glass fibre textiles are used as reinforcements, but today there is a growing interest in biocomposites where the reinforcement and/or the resin are from a biomass resource. All-cellulose composites (ACCs) are monocomponent or single polymer composites, and they are entirely made from cellulose, ideally leading to a homogeneous biocomposite. Since the matrix and the reinforcement are both made from cellulose, and therefore chemically identical, they are fully compatible with each other which allow efficient stress transfer and adhesion at their interface. Apart from improving the mechanical performance of the final products, the recycling of the composites will be facilitated. This paper reports the recycling of end-of-life cellulose containing textiles by fabrication of all-cellulose composites (ACCs). Composite laminates were prepared by using an ionic liquid (IL) in a hot process, involving a partial dissolving of the cellulose fibres. Discharged denim fabrics were used as the reinforcement while dissolved cellulose from two different cellulose resources was used as the matrix phase. Virgin cotton staple fibres and recovered cotton from polyester/cotton (polycotton) waste fabrics were used to form the matrix phase. The process comprises the dissolving 6 wt.% cellulose solution in the ionic liquid 1-butyl-3-methyl imidazolium acetate ([BMIM][Ac]), this solution acted as a precursor for the matrix component. The denim fabrics were embedded in the cellulose/IL solution after which laminates were formed, which also involved removal of the IL by washing. The effect of reuse of the recovered IL was also investigated. The mechanical properties of the obtained ACCs were determined regarding tensile, impact and flexural properties. Mechanical testing revealed that there are no clear differences between the values measured for mechanical strength and modulus of the manufactured ACCs from denim/cotton-fresh IL, denim/recovered cotton-fresh IL and denim/cotton-recycled IL. This could be due to the low weight fraction of the cellulose matrix in the final ACC laminates and presumably the denim as cellulose reinforcement strongly influences and dominates the mechanical properties. Fabricated ACC composite laminates were further characterized regarding scanning electron microscopy.

Keywords: all-cellulose composites, denim fabrics, ionic liquid, mechanical properties

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Authors: Maxim A. Kadatskiy, Konstantin V. Khishchenko

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Iron alloys are widespread components in various types of structural materials which are exposed to intensive thermal and mechanical loads. Various quantum-statistical cell models with the approximation of self-consistent field can be used for the prediction of the behavior of these materials under extreme conditions. The application of these models is even more valid, the higher the temperature and the density of matter. Results of Hugoniot calculation for iron alloys in the framework of three quantum-statistical (the Thomas–Fermi, the Thomas–Fermi with quantum and exchange corrections and the Hartree–Fock–Slater) models are presented. Results of quantum-statistical calculations are compared with results from other reliable models and available experimental data. It is revealed a good agreement between results of calculation and experimental data for terra pascal pressures. Advantages and disadvantages of this approach are shown.

Keywords: alloy, Hugoniot, iron, terapascal pressure

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Authors: Caihong Sun, Xizi Zhang

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Rating prediction is an important problem for recommender systems. The task is to predict the rating for an item that a user would give. Most of the existing algorithms for the task ignore the effect of negative ratings rated by users on items, but the negative ratings have a significant impact on users’ purchasing decisions in practice. In this paper, we present a rating prediction algorithm based on factorization machines that consider the effect of negative ratings inspired by Loss Aversion theory. The aim of this paper is to develop a concave and a convex negative disgust function to evaluate the negative ratings respectively. Experiments are conducted on MovieLens dataset. The experimental results demonstrate the effectiveness of the proposed methods by comparing with other four the state-of-the-art approaches. The negative ratings showed much importance in the accuracy of ratings predictions.

Keywords: factorization machines, feature engineering, negative ratings, recommendation systems

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Authors: Khashayar Jafari, Mostafa Jafarian Abyaneh, Vahab Toufigh

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Polymer concrete (PC) is a distinct concrete with superior characteristics in comparison to ordinary cement concrete. It has become well-known for its applications in thin overlays, floors and precast components. In this investigation, the mechanical properties of PC with different epoxy resin contents, ordinary cement concrete (OCC) and lightweight concrete (LC) have been studied under uniaxial compression test. The study involves five types of concrete, with each type being tested four times. Their complete elastic-plastic behavior was compared with each other through the measurement of volumetric strain during the tests. According to the results, PC showed higher strength, ductility and energy absorption with respect to OCC and LC.

Keywords: polymer concrete, ordinary cement concrete, lightweight concrete, uniaxial compression test, volumetric strain

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Authors: Frank Jaksoni Mweta, Nozomu Adachi, Yoshikazu Todaka, Hirokazu Sato, Yuta Sato, Hiromi Miura, Masakazu Kobayashi, Chihiro Watanabe, Yoshiteru Aoyagi

Abstract:

Advances in the consumption of hydrogen fuel increase demands of high strength steel pipes and storage tanks. However, high strength steels are highly sensitive to hydrogen embrittlement. Because the introduction of hydrogen into steel during the fabrication process or from the environment is unavoidable, it is essential to improve hydrogen embrittlement resistance of high strength steels through microstructural control. In the present study, the heterogeneous nanostructure with a tensile strength of about 1.8 GPa and the homogeneous nanostructure with a tensile strength of about 2.0 GPa of 316LN steels were generated after 92% heavy cold rolling and high-pressure torsion straining, respectively. The heterogeneous nanostructure is composed of twin domains, shear bands, and lamellar grains. The homogeneous nanostructure is composed of uniformly distributed ultrafine nanograins. The influence of heterogeneous and homogenous nanostructures on the hydrogen embrittlement resistance was investigated. The specimen for each nanostructure was electrochemically charged with hydrogen for 3, 6, 12, and 24 hours, respectively. Under the same hydrogen charging time, both nanostructures show almost the same concentration of the diffusible hydrogen based on the thermal desorption analysis. The tensile properties of the homogenous nanostructure were severely affected by the diffusible hydrogen. However, the diffusible hydrogen shows less impact on the tensile properties of the heterogeneous nanostructure. The difference in embrittlement behavior between the heterogeneous and homogeneous nanostructures was elucidated based on the mechanism of the cracks' growth observed in the tensile fractography. The hydrogen embrittlement was suppressed in the heterogeneous nanostructure because the twin domain became an obstacle for crack growth. The homogeneous nanostructure was not consisting an obstacle such as a twin domain; thus, the crack growth resistance was low in this nanostructure.

Keywords: diffusible hydrogen, heterogeneous nanostructure, homogeneous nanostructure, hydrogen embrittlement

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Authors: Mohammed T. Hayajneh

Abstract:

Machining of Metal Matrix Composites (MMCs) is very significant process and has been a main problem that draws many researchers to investigate the characteristics of MMCs during different machining process. The poor machining properties of hard particles reinforced MMCs make drilling process a rather interesting task. Unlike drilling of conventional materials, many problems can be seriously encountered during drilling of MMCs, such as tool wear and cutting forces. Cutting tool wear is a very significant concern in industries. Cutting tool wear not only influences the quality of the drilled hole, but also affects the cutting tool life. Prediction the cutting tool life during drilling is essential for optimizing the cutting conditions. However, the relationship between tool life and cutting conditions, tool geometrical factors and workpiece material properties has not yet been established by any machining theory. In this research work, fuzzy subtractive clustering system has been used to model the cutting tool life in drilling of Al₂O₃ particle reinforced aluminum alloy composite to investigate of the effect of cutting conditions on cutting tool life. This investigation can help in controlling and optimizing of cutting conditions when the process parameters are adjusted. The built model for prediction the tool life is identified by using drill diameter, cutting speed, and cutting feed rate as input data. The validity of the model was confirmed by the examinations under various cutting conditions. Experimental results have shown the efficiency of the model to predict cutting tool life.

Keywords: composite, fuzzy, tool life, wear

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Authors: Soheila Sadeghi

Abstract:

Accurate cost prediction is essential for effective project management and decision-making in the construction industry. This study aims to develop a cost prediction model for construction projects using Machine Learning techniques and Particle Swarm Optimization (PSO). The research utilizes a comprehensive dataset containing project cost estimates, actual costs, resource details, and project performance metrics from a road reconstruction project. The methodology involves data preprocessing, feature selection, and the development of an Artificial Neural Network (ANN) model optimized using PSO. The study investigates the impact of various input features, including cost estimates, resource allocation, and project progress, on the accuracy of cost predictions. The performance of the optimized ANN model is evaluated using metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and R-squared. The results demonstrate the effectiveness of the proposed approach in predicting project costs, outperforming traditional benchmark models. The feature selection process identifies the most influential variables contributing to cost variations, providing valuable insights for project managers. However, this study has several limitations. Firstly, the model's performance may be influenced by the quality and quantity of the dataset used. A larger and more diverse dataset covering different types of construction projects would enhance the model's generalizability. Secondly, the study focuses on a specific optimization technique (PSO) and a single Machine Learning algorithm (ANN). Exploring other optimization methods and comparing the performance of various ML algorithms could provide a more comprehensive understanding of the cost prediction problem. Future research should focus on several key areas. Firstly, expanding the dataset to include a wider range of construction projects, such as residential buildings, commercial complexes, and infrastructure projects, would improve the model's applicability. Secondly, investigating the integration of additional data sources, such as economic indicators, weather data, and supplier information, could enhance the predictive power of the model. Thirdly, exploring the potential of ensemble learning techniques, which combine multiple ML algorithms, may further improve cost prediction accuracy. Additionally, developing user-friendly interfaces and tools to facilitate the adoption of the proposed cost prediction model in real-world construction projects would be a valuable contribution to the industry. The findings of this study have significant implications for construction project management, enabling proactive cost estimation, resource allocation, budget planning, and risk assessment, ultimately leading to improved project performance and cost control. This research contributes to the advancement of cost prediction techniques in the construction industry and highlights the potential of Machine Learning and PSO in addressing this critical challenge. However, further research is needed to address the limitations and explore the identified future research directions to fully realize the potential of ML-based cost prediction models in the construction domain.

Keywords: cost prediction, construction projects, machine learning, artificial neural networks, particle swarm optimization, project management, feature selection, road reconstruction

Procedia PDF Downloads 59

Authors: R. Burahee, B. Chassinat, T. de Laclos, A. Dépée, A. Sastim

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The purpose of this paper is to propose a solution to detect, predict and reconstitute rain drops in real time – during the night – using an embedded material with an infrared camera. To prevent the system from needing too high hardware resources, simple models are considered in a powerful image treatment algorithm reducing considerably calculation time in OpenCV software. Using a smart model – drops will be matched thanks to a process running through two consecutive pictures for implementing a sophisticated tracking system. With this system drops computed trajectory gives information for predicting their future location. Thanks to this technique, treatment part can be reduced. The hardware system composed by a Raspberry Pi is optimized to host efficiently this code for real time execution.

Keywords: reconstitution, prediction, detection, rain drop, real time, raspberry, infrared

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Authors: J. K. Alhassan, B. Attah, S. Misra

Abstract:

Human beings have the ability to make logical decisions. Although human decision - making is often optimal, it is insufficient when huge amount of data is to be classified. medical dataset is a vital ingredient used in predicting patients health condition. In other to have the best prediction, there calls for most suitable machine learning algorithms. This work compared the performance of Artificial Neural Network (ANN) and Decision Tree Algorithms (DTA) as regards to some performance metrics using diabetes data. The evaluations was done using weka software and found out that DTA performed better than ANN. Multilayer Perceptron (MLP) and Radial Basis Function (RBF) were the two algorithms used for ANN, while RegTree and LADTree algorithms were the DTA models used. The Root Mean Squared Error (RMSE) of MLP is 0.3913,that of RBF is 0.3625, that of RepTree is 0.3174 and that of LADTree is 0.3206 respectively.

Keywords: artificial neural network, classification, decision tree algorithms, diabetes mellitus

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Authors: Sirwan Kamal, Hsein Kew, Hamid Jahromi

Abstract:

This paper reports results of a study conducted to investigate strength, sorptivity, and permeability under pressure of concrete specimens, cured using a water-based curing compound. The specimens are treated with waterproofing admixtures or surface treatments to enhance performance while exposed to water. Four types of concrete specimens were prepared in the laboratory, Portland cement (CEM I), Portland-fly ash (CEM II/A-V), Blast-furnace cement (CEM III) and Portland-silica fume (CEM II/A-D). Concrete cubes were de-molded three hours after casting, and sprayed with a curing compound. Admixtures were added to the mix during batching, whereas surface treatments were applied on concrete after 28 days. Compressive strength test was carried out to assess the efficiency of curing compound to develop required strength. In addition, sorptivity and permeability tests were conducted to evaluate the performance of treated specimens with respect to water ingress. Results show that strength development in specimens cured with curing compound achieved up to 96% and 90% at 7 and 28 days respectively, compared to cubes cured in water. Moreover, specimens treated with waterproofing admixtures or surface treatments materials characterized by hydrophobic impregnation considerably reduced water penetration compared to untreated control cubes. On the other hand, cubes treated with admixtures or surface treatments materials characterized by crystalline effect were ineffective in reducing water penetration.

Keywords: admixtures, concrete, curing compound, surface treatments

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Authors: Ali Jahanfar, Brajesh Dubey, Bahram Gharabaghi, Saber Bayat Movahed

Abstract:

Ever increasing population growth of major urban centers and environmental challenges in siting new landfills have resulted in a growing trend in design of mega-landfills some with extraordinary heights and dangerously steep slopes. Landfill failure mobility risk analysis is one of the most uncertain types of dynamic rheology models due to very large inherent variabilities in the heterogeneous solid waste material shear strength properties. The waste flow of three historic dumpsite and two landfill failures were back-analyzed using run-out modeling with DAN-W model. The travel distances of the waste flow during landfill failures were calculated approach by taking into account variability in material shear strength properties. The probability distribution function for shear strength properties of the waste material were grouped into four major classed based on waste material compaction (landfills versus dumpsites) and composition (high versus low quantity) of high shear strength waste materials such as wood, metal, plastic, paper and cardboard in the waste. This paper presents a probabilistic method for estimation of the spatial extent of waste avalanches, after a potential landfill failure, to create maps of vulnerability scores to inform property owners and residents of the level of the risk.

Keywords: landfill failure, waste flow, Voellmy rheology, friction coefficient, waste compaction and type

Procedia PDF Downloads 290