Search results for: defect prediction

Authors: Abdelkarim M. Ertiame, D. W. Yu, D. L. Yu, J. B. Gomm

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In this paper, a new robust fault detection and isolation (FDI) scheme is developed to monitor a multivariable nonlinear chemical process called the Chylla-Haase polymerization reactor when it is under the cascade PI control. The scheme employs a radial basis function neural network (RBFNN) in an independent mode to model the process dynamics and using the weighted sum-squared prediction error as the residual. The recursive orthogonal Least Squares algorithm (ROLS) is employed to train the model to overcome the training difficulty of the independent mode of the network. Then, another RBFNN is used as a fault classifier to isolate faults from different features involved in the residual vector. The several actuator and sensor faults are simulated in a nonlinear simulation of the reactor in Simulink. The scheme is used to detect and isolate the faults on-line. The simulation results show the effectiveness of the scheme even the process is subjected to disturbances and uncertainties including significant changes in the monomer feed rate, fouling factor, impurity factor, ambient temperature and measurement noise. The simulation results are presented to illustrate the effectiveness and robustness of the proposed method.

Keywords: Robust fault detection, cascade control, independent RBF model, RBF neural networks, Chylla-Haase reactor, FDI under closed-loop control

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Authors: Sri Sai Ramya Bojedla, Falguni Pati

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Nature provides the best of solutions to humans. One such incredible gift to regenerative medicine is silk. The literature has publicized a long appreciation for silk owing to its incredible physical and biological assets. Its bioactive nature, unique mechanical strength, and processing flexibility make us curious to explore further to apply it in the clinics for the welfare of mankind. In this study, Antheraea mylitta and Bombyx mori silk fibroin microfibers are developed by two economical and straightforward steps via degumming and hydrolysis for the first time, and a bioactive composite is manufactured by mixing silk fibroin microfibers at various concentrations with polycaprolactone (PCL), a biocompatible, aliphatic semi-crystalline synthetic polymer. Reconstructive surgery in any part of the body except for the maxillofacial region deals with replacing its function. But answering both the aesthetics and function is of utmost importance when it comes to facial reconstruction as it plays a critical role in the psychological and social well-being of the patient. The main concern in developing adequate bone graft substitutes or a scaffold is the noteworthy variation in each patient's bone anatomy. Additionally, the anatomical shape and size will vary based on the type of defect. The advent of additive manufacturing (AM) or 3D printing techniques to bone tissue engineering has facilitated overcoming many of the restraints of conventional fabrication techniques. The acquired patient's CT data is converted into a stereolithographic (STL)-file which is further utilized by the 3D printer to create a 3D scaffold structure in an interconnected layer-by-layer fashion. This study aims to address the limitations of currently available materials and fabrication technologies and develop a customized biomaterial implant via 3D printing technology to reconstruct complex form, function, and aesthetics of the facial anatomy. These composite scaffolds underwent structural and mechanical characterization. Atomic force microscopic (AFM) and field emission scanning electron microscopic (FESEM) images showed the uniform dispersion of the silk fibroin microfibers in the PCL matrix. With the addition of silk, there is improvement in the compressive strength of the hybrid scaffolds. The scaffolds with Antheraea mylitta silk revealed higher compressive modulus than that of Bombyx mori silk. The above results of PCL-silk scaffolds strongly recommend their utilization in bone regenerative applications. Successful completion of this research will provide a great weapon in the maxillofacial reconstructive armamentarium.

Keywords: compressive modulus, 3d printing, maxillofacial reconstruction, natural fiber reinforced composites, silk fibroin microfibers

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Authors: N. Renuka, R. Ramesh Babu, N. Vijayan

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Ion beams play a significant role in the process of tuning the properties of materials. Based on the radiation behavior, the engineering materials are categorized into two different types. The first one comprises organic solids which are sensitive to the energy deposited in their electronic system and the second one comprises metals which are insensitive to the energy deposited in their electronic system. However, exposure to swift heavy ions alters this general behavior. Depending on the mass, kinetic energy and nuclear charge, an ion can produce modifications within a thin surface layer or it can penetrate deeply to produce long and narrow distorted area along its path. When a high energetic ion beam impinges on a material, it causes two different types of changes in the material due to the columbic interaction between the target atom and the energetic ion beam: (i) inelastic collisions of the energetic ion with the atomic electrons of the material; and (ii) elastic scattering from the nuclei of the atoms of the material, which is extremely responsible for relocating the atoms of matter from their lattice position. The exposure of the heavy ions renders the material return to equilibrium state during which the material undergoes surface and bulk modifications which depends on the mass of the projectile ion, physical properties of the target material, its energy, and beam dimension. It is well established that electronic stopping power plays a major role in the defect creation mechanism provided it exceeds a threshold which strongly depends on the nature of the target material. There are reports available on heavy ion irradiation especially on crystalline materials to tune their physical and chemical properties. L-Arginine Acetate [LAA] is a potential semi-organic nonlinear optical crystal and its optical, mechanical and thermal properties have already been reported The main objective of the present work is to enhance or tune the structural and optical properties of LAA single crystals by heavy ion irradiation. In the present study, a potential nonlinear optical single crystal, L-arginine acetate (LAA) was grown by slow evaporation solution growth technique. The grown LAA single crystal was irradiated with oxygen ions at the dose rate of 600 krad and 1M rad in order to tune the structural and optical properties. The structural properties of pristine and oxygen ions irradiated LAA single crystals were studied using Powder X- ray diffraction and Fourier Transform Infrared spectral studies which reveal the structural changes that are generated due to irradiation. Optical behavior of pristine and oxygen ions irradiated crystals is studied by UV-Vis-NIR and photoluminescence analyses. From this investigation we can concluded that oxygen ions irradiation modifies the structural and optical properties of LAA single crystals.

Keywords: heavy ion irradiation, NLO single crystal, photoluminescence, X-ray diffractometer

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Authors: Hygreeva Kiran Namburi, Anna Hojna, Edita Lecianova, Fencl Zdenek

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Irradiation Assisted Stress Corrosion Cracking [IASCC] is one of the most significant environmental degradation in the internal components made from Austenitic stainless steel. This mechanism is still not fully understood and there are no suitable criteria for prediction of the damage during operation. In this work, core basket material 08Ch18N10T austenitic stainless steel acquired from decommissioned NPP Nord / Greifswald Unit 1, VVER 440-230 type, operated for 15 years and irradiated at 5.2 dpa is studied. This material was tensile tested at two different test temperatures and strain rates in air and at the elevated temperature under the water environment. SEM observations of the fracture surface documented ductile fracture of the samples tested in air, but areas of IASCC tested in water. This paper emphasizes on the microscopic examination results from the mechanically tested samples to determine the underlying IASCC physical damage process. TEM observations of thin foils made from the gauge sections that are closer to the fractured surface of the specimen aimed to find variances in interaction of dislocations and grain boundaries owing to different test conditions.

Keywords: irradiation assisted stress corrosion cracking, core basket material, SEM observations of the fracture surface, microscopic examination results

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Authors: Thomas Okechukwu Onah, Onyekachi Marcel Egwuagu

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Zero-surface temperature, which controlled the cooling profile, was modeled and used to investigate the effect of process parameters on the hot-rolled steel plates. The parameters include impingement gaps of 40mm to 70mm; pipe diameters of 20mm to 45mm feeding jet nozzle with 30 holes of 8mm diameters each; and flow rates within 2.896x10-⁶m³/s and 3.13x10-⁵m³/s. The developed simulation model of the Zero-Surface Temperature, upon validation, showed 99% prediction accuracy with dimensional homogeneity established. The evaluated Zero-Surface temperature of Controlled Water Jet Impingement Steel plates showed a high cooling rate of 36.31 Celsius degree/sec at an optimal cooling nozzle diameter of 20mm, impingement gap of 70mm and a flow rate of 1.77x10-⁵m³/s resulting in Reynold's number 2758.586, in the turbulent regime was obtained. It was also deduced that as the nozzle diameter was increasing, the impingement gap was reducing. This achieved a faster rate of cooling to an optimum temperature of 300oC irrespective of the starting surface cooling temperature. The results additionally showed that with a tested-plate initial temperature of 550oC, a controlled cooling temperature of about 160oC produced a film and nucleated boiling heat extraction that was particularly beneficial at the end of controlled cooling and influenced the microstructural properties of the test plates.

Keywords: temperature, mechanistic-model, plates, impingements, dimensionless-numbers

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Authors: Drago Bratkovic, Curtis Gravance, David Ketteridge, Ravi Krishnan, Michael Imperiale

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The mucopolysaccharidoses (MPSs) are a group of lysosomal storage diseases that have a common defect in the catabolism of glycosaminoglycans (GAGs). MPS I is the most common of the MPS diseases. Manifestations of MPS I include coarsening of facial features, corneal clouding, developmental delay, short stature, skeletal manifestations, hearing loss, cardiac valve disease, hepatosplenomegaly, and umbilical and inguinal hernias. Treatments for MPS I restore or activate the missing or deficient enzyme in the case of enzyme replacement therapy (ERT) and haematopoietic stem cell transplantation (HSCT). Pentosan polysulfate sodium (PPS) is a potential treatment to improve bone and joint manifestations of MPS I. The mechanisms of action of PPS that are relevant to the treatment of MPS I are the ability to: (i) Reduce systemic and accumulated GAG, (ii) Reduce inflammatory effects via the inhibition of NF-kB, resulting in the reduction in pro-inflammatory mediators. (iii) Reduce the expression of the pain mediator nerve growth factor in osteocytes from degenerating joints. (iv) Inhibit the cartilage degrading enzymes related to joint dysfunction in MPS I. PPS is being evaluated as an adjunctive therapy to ERT and/or HSCT in an open-label, single-centre, phase 2 study. Patients are ≥ 5 years of age with a diagnosis of MPS I and previously received HSCT and/or ERT. Three white, female, patients with MPS I-Hurler, ages 14, 15, and 19 years, and one, white male patient aged 15 years are enrolled. All were diagnosed at ≤2 years of age. All patients received HSCT ≤ 6 months after diagnosis. Two of the patients were treated with ERT prior to HSCT, and 1 patient received ERT commencing 3 months prior to HSCT. Two patients received 0.75mg/kg and 2 patients received 1.5mg/kg of PPS. PPS was well tolerated at doses of 0.75 and 1.5 mg/kg to 47 weeks of continuous dosing. Of the 19 adverse events (AEs), 2 were related to PPS. One AE was moderate (pre-syncope) and 1 was mild (injection site bruising), experienced in the same patient. All AEs were reported as mild or moderate. There have been no SAEs. One subject experienced a COVID-19 infection and PPS was interrupted. The MPS I signature GAG fragments, sulfated disaccharide and UA-HNAc S, tended to decrease in 3 patients from baseline through Week 25. Week 25 GAG data are pending for the 4th patient. Overall, most biomarkers (inflammatory, cartilage degeneration, and bone turnover) evaluated in the 3 patients with 25-week assessments have indicated either no change or a reduction in levels compared to baseline. In 3 patients, there was a trend toward improvement in the 2MWT from baseline to Week 48 with > 100% increase in 1 patient (01-201). In the 3 patients that had Week 48 assessments, patients and proxies reported improvement in PGIC, including “worthwhile difference” (n=1), or “made all the difference” (n=2).

Keywords: MPS I, pentosan polysulfate sodium, clinical study, 2MWT, QoL

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Authors: Peter Modregger, Özgül Öztürk

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Glass fabric reinforced thermoplastic (GFRT) are composite materials, which combine low weight and resilient mechanical properties rendering them especially suitable for automobile construction. However, defects in the glass fabric as well as in the polymer matrix can occur during manufacturing, which may compromise component lifetime or even safety. One type of these defects is local fiber shifts, which can be difficult to detect. Recently, we have experimentally demonstrated the reliable detection of local fiber shifts by X-ray scattering based on the edge-illumination (EI) principle. EI constitutes a novel X-ray imaging technique that utilizes two slit masks, one in front of the sample and one in front of the detector, in order to simultaneously provide absorption, phase, and scattering contrast. The principle of contrast formation is as follows. The incident X-ray beam is split into smaller beamlets by the sample mask, resulting in small beamlets. These are distorted by the interaction with the sample, and the distortions are scaled up by the detector masks, rendering them visible to a pixelated detector. In the experiment, the sample mask is laterally scanned, resulting in Gaussian-like intensity distributions in each pixel. The area under the curves represents absorption, the peak offset refraction, and the width of the curve represents the scattering occurring in the sample. Here, scattering is caused by the numerous glass fiber/polymer matrix interfaces. In our recent publication, we have shown that the standard deviation of the absorption and scattering values over a selected field of view can be used to distinguish between intact samples and samples with local fiber shift defects. The quantification of defect detection performance was done by using p-values (p=0.002 for absorption and p=0.009 for scattering) and contrast-to-noise ratios (CNR=3.0 for absorption and CNR=2.1 for scattering) between the two groups of samples. This was further improved for the scattering contrast to p=0.0004 and CNR=4.2 by utilizing a harmonic decomposition analysis of the images. Thus, we concluded that local fiber shifts can be reliably detected by the X-ray scattering contrasts provided by EI. However, a potential application in, for example, production monitoring requires fast data acquisition times. For the results above, the scanning of the sample masks was performed over 50 individual steps, which resulted in long total scan times. In this paper, we will demonstrate that reliable detection of local fiber shift defects is also possible by using single images, which implies a speed up of total scan time by a factor of 50. Additional performance improvements will also be discussed, which opens the possibility for real-time acquisition. This contributes a vital step for the translation of EI to industrial applications for a wide variety of materials consisting of numerous interfaces on the micrometer scale.

Keywords: defects in composites, X-ray scattering, local fiber shifts, X-ray edge Illumination

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Authors: A.Chen Chao-Chang, Phong Pham-Quoc

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Chemical-mechanical polishing (CMP) process has been widely applied on fabricating integrated circuits (IC) with a soft polishing pad combined with slurry composed of micron or nano-scaled abrasives for generating chemical reaction to remove substrate or film materials from wafer. During CMP process, pad uniformity usually works as a datum surface of wafer planarization and pad asperities can dominate the microscopic pad-slurry-wafer interaction. However, pad topography can be changed by related mechanism factors of CMP and it needs to be re-conditioned or dressed by a diamond dresser of well-distributed diamond grits on a disc surface. It is still very complicated to analyze and understand kinematic of diamond dressing process under the effects of input variables including oscillatory of diamond dresser and rotation speed ratio between the pad and the diamond dresser. This paper has developed a generic geometric model to clarify the kinematic modeling of diamond dressing processes such as dresser/pad motion, pad cutting locus, the relative velocity of the diamond abrasive grits on pad surface, and overlap of cutting for prediction of pad surface topography. Simulation results focus on comparing and analysis kinematics of the diamond dressing on certain CMP tools. Results have shown the significant parameters for diamond dressing process and also discussed. Future study can apply on diamond dresser design and experimental verification of pad dressing process.

Keywords: kinematic modeling, diamond dresser, pad cutting locus, CMP

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Authors: Abadou Yacine, Faid Hayette

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Significant investigations were performed on the use and impact on physical properties along with the mechanical strength of the recycled and reused E-glass waste powder. However, it has been modelled how recycled display e-waste glass may affect the characteristics and qualities of dune sand mortar. To be involved in this field, an investigation has been done with the substitution of dune sand for recycled E-glass waste and constant water-cement ratios. The linear relationship between the dune sand mortar and E-glass mortar mix % contributes to the model's reliability. The experimental data was exposed to regression analysis using JMP Statistics software. The regression model with one predictor presented the general form of the equation for the prediction of the five properties' characteristics of dune sand mortar from the substitution ratio of E-waste glass and curing age. The results illustrate that curing a long-term process produced an E-glass waste mortar specimen with the highest compressive strength of 68 MPa in the laboratory environment. Anova analysis indicated that the curing at long-term has the utmost importance on the sorptivity level and ultrasonic pulse velocity loss. Furthermore, the E-glass waste powder percentage has the utmost importance on the compressive strength and improvement in dynamic elasticity modulus. Besides, a significant enhancement of radiation-shielding applications.

Keywords: ANOVA analysis, E-glass waste, durability and sustainability, radiation-shielding

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Authors: Shiuh-Jer Huang, Chen-Zon Yan, C. K. Huang, Chun-Chien Ting

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Since the vision system application in industrial environment for autonomous purposes is required intensely, the image recognition technique becomes an important research topic. Here, deep learning algorithm is employed in image system to recognize the industrial object and integrate with a 7A6 Series Manipulator for object automatic gripping task. PC and Graphic Processing Unit (GPU) are chosen to construct the 3D Vision Recognition System. Depth Camera (Intel RealSense SR300) is employed to extract the image for object recognition and coordinate derivation. The YOLOv2 scheme is adopted in Convolution neural network (CNN) structure for object classification and center point prediction. Additionally, image processing strategy is used to find the object contour for calculating the object orientation angle. Then, the specified object location and orientation information are sent to robotic controller. Finally, a six-axis manipulator can grasp the specific object in a random environment based on the user command and the extracted image information. The experimental results show that YOLOv2 has been successfully employed to detect the object location and category with confidence near 0.9 and 3D position error less than 0.4 mm. It is useful for future intelligent robotic application in industrial 4.0 environment.

Keywords: deep learning, image processing, convolution neural network, YOLOv2, 7A6 series manipulator

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Authors: T. Davitashvili

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At present impact of global climate change on the territory of Georgia is evident at least on the background of the Caucasus glaciers melting which during the last century have decreased to half their size. Glaciers are early indicators of ongoing global and regional climate change. Knowledge of the Caucasus glaciers fluctuation (melting) is an extremely necessary tool for planning hydro-electric stations and water reservoir, for development tourism and agriculture, for provision of population with drinking water and for prediction of water supplies in more arid regions of Georgia. Otherwise, the activity of anthropogenic factors has resulted in decreasing of the mowing, arable, unused lands, water resources, shrubs and forests, owing to increasing the production and building. Transformation of one type structural unit into another one has resulted in local climate change and its directly or indirectly impacts on different components of water resources on the territory of Georgia. In the present paper, some hydrological specifications of Georgian water resources and its potential pollutants on the background of regional climate change are presented. Some results of Georgian’s glaciers pollution and its melting process are given. The possibility of surface and subsurface water pollution owing to accidents at oil pipelines or railway routes are discussed. The specific properties of regional climate warming process in the eastern Georgia are studied by statistical methods. The effect of the eastern Georgian climate change upon water resources is investigated.

Keywords: climate, droughts, pollution, water resources

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Authors: Abdul Mannan Akhtar

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In this paper a novel concept of a self learning smart personalized computer assistant (ACPCA) is established which is a context aware system. Based on user habits, moods, and other routines/situational reactions the system will manage various services and suggestions at appropriate times including what schedule to follow, what to watch, what software to be used, what should be deleted etc. This system will utilize a hybrid fuzzyNeural model to predict what the user will do next and support his actions. This will be done by establishing fuzzy sets of user activities, choices, preferences etc. and utilizing their combinations to predict his moods and immediate preferences. Various application of context aware systems exist separately e.g. on certain websites for music or multimedia suggestions but a personalized autonomous system that could adapt to user’s personality does not exist at present. Due to the novelty and massiveness of this concept, this paper will primarily focus on the problem establishment, product features and its functionality; however a small mini case is also implemented on MATLAB to demonstrate some of the aspects of ACPCA. The mini case involves prediction of user moods, activity, routine and food preference using a hybrid fuzzy-Neural soft computing technique.

Keywords: context aware systems, APCPCA, soft computing techniques, artificial intelligence, fuzzy logic, neural network, mood detection, face detection, activity detection

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Authors: Joseph Amponsah

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This research proposes an equation to predict and determine the momentum source equation term after factoring in the radial friction between the fluid and the blades and the impeller's propulsive power. This research aims to look at how CFD software can be used to predict the effect of flows in nuclear reactor stirred tanks through a momentum source equation and the concentration distribution of tracers that have been introduced in reactor tanks. The estimated findings, including the dimensionless concentration curves, power, and pumping numbers, dimensionless velocity profiles, and mixing times 4, were contrasted with results from tests in stirred containers. The investigation was carried out in Part I for vessels that were agitated by one impeller on a central shaft. The two types of impellers employed were an ordinary Rushton turbine and a 6-bladed 45° pitched blade turbine. The simulations made use of numerous reference frame techniques and the common k-e turbulence model. The impact of the grid type was also examined; unstructured, structured, and unique user-defined grids were looked at. The CFD model was used to simulate the flow field within the Rushton turbine nuclear reactor stirred tank. This method was validated using experimental data that were available close to the impeller tip and in the bulk area. Additionally, analyses of the computational efficiency and time using MRF and SM were done.

Keywords: Ansys fluent, momentum equation, CFD, prediction

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Authors: Oseni Taiwo Amoo, Bloodless Dzwairo

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In this paper, we extend the versatility and usefulness of GIS as a methodology for any river basin hydrologic characteristics analysis (HCA). The Gurara River basin located in North-Central Nigeria is presented in this study. It is an on-going research using spatial Digital Elevation Model (DEM) and Arc-Hydro tools to take inventory of the basin characteristics in order to predict water abstraction quantification on streamflow regime. One of the main concerns of hydrological modelling is the quantification of runoff from rainstorm events. In practice, the soil conservation service curve (SCS) method and the Conventional procedure called rational technique are still generally used these traditional hydrological lumped models convert statistical properties of rainfall in river basin to observed runoff and hydrograph. However, the models give little or no information about spatially dispersed information on rainfall and basin physical characteristics. Therefore, this paper synthesizes morphometric parameters in generating runoff. The expected results of the basin characteristics such as size, area, shape, slope of the watershed and stream distribution network analysis could be useful in estimating streamflow discharge. Water resources managers and irrigation farmers could utilize the tool for determining net return from available scarce water resources, where past data records are sparse for the aspect of land and climate.

Keywords: hydrological characteristic, stream flow, runoff discharge, land and climate

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Authors: Ndidi Ofole

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Ongoing Boko Haram crisis and instability in North-Eastern Nigeria has placed additional stress on academic resilience of female undergraduates who are already challenged by gender discrimination in educational opportunities. Students without resilience lack stress hardiness to cope with academic challenges. There is a limited study on academic resilience targeting this disadvantaged population in Nigeria. Consequently, survey research design was employed to investigate the contextual and personal factors that could predict academic resilience among female undergraduates in Boko Haram Neighbourhood in North-Eastern, Nigeria. Five hundred and thirty female students with age range of 18 to 24 years ( = 19.2; SD=6.9) were randomly drawn from 3 Universities in North-Eastern Nigeria. They responded to five instruments, namely; Academic Resilience scale (r=0.72); Social Support questionnaire (r=0. 64); Social Connectedness questionnaire (r=0.75); Self-Efficacy scale (r=0. 68) and Emotional Regulation questionnaire (r=78). Results showed that there was significant positive relationship between the four independent variables and academic resilience. The variables jointly contributed 5.9% variance in the prediction of academic resilience. In terms of magnitude, social support was most potent while self-efficacy was the least. It concluded that the factors considered in this study are academic resilience facilitators. The outcomes of the study have both theoretical and practical implications.

Keywords: academic resilience, emotional regulation, school connectedness, self-efficacy , social support

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Authors: Anas Rao, Hao Duan, Fanhua Ma

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The dependency on the fossil fuels can be minimized by using the hydrogen enriched compressed natural gas (HCNG) in the transportation vehicles. However, the NOx emissions of HCNG engines are significantly higher, and this turned to be its major drawback. Therefore, the study of NOx emission of HCNG engines is a very important area of research. In this context, the experiments have been performed at the different hydrogen percentage, ignition timing, air-fuel ratio, manifold-absolute pressure, load and engine speed. Afterwards, the simulation has been accomplished by the quasi-dimensional combustion model of HCNG engine. In order to investigate the NOx emission, the NO mechanism has been coupled to the quasi-dimensional combustion model of HCNG engine. The three NOx mechanism: the thermal NOx, prompt NOx and N2O mechanism have been used to predict NOx emission. For the validation purpose, NO curve has been transformed into NO packets based on the temperature difference of 100 K for the lean-burn and 60 K for stoichiometric condition. While, the width of the packet has been taken as the ratio of crank duration of the packet to the total burnt duration. The combustion chamber of the engine has been divided into three zones, with the zone equal to the product of summation of NO packets and space. In order to check the accuracy of the model, the percentage error of NOx emission has been evaluated, and it lies in the range of ±6% and ±10% for the lean-burn and stoichiometric conditions respectively. Finally, the percentage contribution of each NO formation has been evaluated.

Keywords: quasi-dimensional combustion , thermal NO, prompt NO, NO packet

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Authors: Thamer Kubat, Riadh Al Mahiadi, Ahmad Shayan

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The alkali-aggregate reaction (AAR) in concrete has a negative influence on the mechanical properties and durability of concrete. Confinement by carbon fiber reinforced polymer (CFRP) is an effective method of treatment for some AAR-affected elements. Eighteen reinforced columns affected by different levels of expansion due to AAR were confined using CFRP to evaluate the effect of expansion level on confinement efficiency. Strength and strain capacities (axial and circumferential) were measured using photogrammetry under uniaxial compressive loading to evaluate the efficiency of CFRP wrapping for the rehabilitation of affected columns. In relation to uniaxial compression capacity, the results indicated that the confinement of AAR-affected columns by one layer of CFRP is sufficient to reach and exceed the load capacity of unaffected sound columns. Parallel to the experimental study, finite element (FE) modeling using ATENA software was employed to predict the behavior of CFRP-confined damaged concrete and determine the possibility of using the model in a parametric study by simulating the number of CFRP layers. A comparison of the experimental results with the results of the theoretical models showed that FE modeling could be used for the prediction of the behavior of confined AAR-damaged concrete.

Keywords: ATENA, carbon fiber reinforced polymer (CFRP), confinement efficiency, finite element (FE)

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Authors: Boukhadia Karima

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The fluid mechanics is the study of fluid motion laws and their interaction with solid bodies, this project leads to illustrate this interaction with depth studies and approved by experiments on the wind tunnel TE44, ensuring the efficiency, accuracy and reliability of these tests on a NACA0015 profile. A symmetric NACA0015 was placed in a subsonic wind tunnel, and measurements were made of the pressure on the upper and lower surface of the wing and of the velocity across the vortex trailing downstream from the tip of the wing. The aim of this work is to investigate experimentally the scattered pressure profile in a free airflow and the aerodynamic forces acting on this profile. The addition of around-lateral edge to the wing tip was found to eliminate the secondary vortex near the wing tip, but had little effect on the downstream characteristics of the trailing vortex. The increase in wing lift near the tip because of the presence of the trailing vortex was evident in the surface pressure, but was not captured by circulation-box measurements. The circumferential velocity within the vortex was found to reach free-stream values and produce core rotational speeds. Near the wing, the trailing vortex is asymmetric and contains definite zones where the stream wise velocity both exceeds and falls behind the free-stream value. When referenced to the free stream velocity, the maximum vertical velocity of the vortex is directly dependent on α and is independent of Re. A numerical study was conducted through a CFD code called FLUENT 6.0, and the results are compared with experimental.

Keywords: CFD code, NACA Profile, detachment, angle of incidence, wind tunnel

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Authors: Emmanuel Osaze Oshoiribhor, Adetokunbo MacGregor John-Otumu

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In recent years, there has been a desire to forecast student academic achievement prior to graduation. This is to help them improve their grades, particularly for individuals with poor performance. The goal of this study is to employ supervised learning techniques to construct a predictive model for student academic achievement. Many academics have already constructed models that predict student academic achievement based on factors such as smoking, demography, culture, social media, parent educational background, parent finances, and family background, to name a few. This feature and the model employed may not have correctly classified the students in terms of their academic performance. This model is built using a logistic regression classifier with basic features such as the previous semester's course score, attendance to class, class participation, and the total number of course materials or resources the student is able to cover per semester as a prerequisite to predict if the student will perform well in future on related courses. The model outperformed other classifiers such as Naive bayes, Support vector machine (SVM), Decision Tree, Random forest, and Adaboost, returning a 96.7% accuracy. This model is available as a desktop application, allowing both instructors and students to benefit from user-friendly interfaces for predicting student academic achievement. As a result, it is recommended that both students and professors use this tool to better forecast outcomes.

Keywords: artificial intelligence, ML, logistic regression, performance, prediction

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Authors: Sai Sankalp Vemavarapu

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This paper discusses the application of machine learning in the field of transportation engineering for predicting engineering properties of pavement more accurately and efficiently. Predicting the elastic properties aid us in assessing the current road conditions and taking appropriate measures to avoid any inconvenience to commuters. This improves the longevity and sustainability of the pavement layer while reducing its overall life-cycle cost. As an example, we have implemented differential evolution (DE) in the back-calculation of the elastic modulus of multi-layered pavement. The proposed DE global optimization back-calculation approach is integrated with a forward response model. This approach treats back-calculation as a global optimization problem where the cost function to be minimized is defined as the root mean square error in measured and computed deflections. The optimal solution which is elastic modulus, in this case, is searched for in the solution space by the DE algorithm. The best DE parameter combinations and the most optimum value is predicted so that the results are reproducible whenever the need arises. The algorithm’s performance in varied scenarios was analyzed by changing the input parameters. The prediction was well within the permissible error, establishing the supremacy of DE.

Keywords: cost function, differential evolution, falling weight deflectometer, genetic algorithm, global optimization, metaheuristic algorithm, multilayered pavement, pavement condition assessment, pavement layer moduli back calculation

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Authors: Juhee Lee, Yongjun Lee

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In designing a low-energy-consuming buildings, the heat transfer through a large glass or wall becomes critical. Multiple layers of the window glasses and walls are employed for the high insulation. The gravity driven air flow between window glasses or wall layers is a natural heat convection phenomenon being a key of the heat transfer. For the first step of the natural heat transfer analysis, in this study the development and application of a finite volume method for the numerical computation of viscous incompressible flows is presented. It will become a part of the natural convection analysis with high-order scheme, multi-grid method, and dual-time step in the future. A finite volume method based on a fully-implicit second-order is used to discretize and solve the fluid flow on unstructured grids composed of arbitrary-shaped cells. The integrations of the governing equation are discretised in the finite volume manner using a collocated arrangement of variables. The convergence of the SIMPLE segregated algorithm for the solution of the coupled nonlinear algebraic equations is accelerated by using a sparse matrix solver such as BiCGSTAB. The method used in the present study is verified by applying it to some flows for which either the numerical solution is known or the solution can be obtained using another numerical technique available in the other researches. The accuracy of the method is assessed through the grid refinement.

Keywords: finite volume method, fluid flow, laminar flow, unstructured grid

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Authors: Jiao Sun, Li Pan, Shijun Liu

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Recommender systems have been widely used in contemporary industry, and plenty of work has been done in this field to help users to identify items of interest. Collaborative Filtering (CF, for short) algorithm is an important technology in recommender systems. However, less work has been done in automobile recommendation system with the sharp increase of the amount of automobiles. What’s more, the computational speed is a major weakness for collaborative filtering technology. Therefore, using MapReduce framework to optimize the CF algorithm is a vital solution to this performance problem. In this paper, we present a recommendation of the users’ comment on industrial automobiles with various properties based on real world industrial datasets of user-automobile comment data collection, and provide recommendation for automobile providers and help them predict users’ comment on automobiles with new-coming property. Firstly, we solve the sparseness of matrix using previous construction of score matrix. Secondly, we solve the data normalization problem by removing dimensional effects from the raw data of automobiles, where different dimensions of automobile properties bring great error to the calculation of CF. Finally, we use the MapReduce framework to optimize the CF algorithm, and the computational speed has been improved times. UV decomposition used in this paper is an often used matrix factorization technology in CF algorithm, without calculating the interpolation weight of neighbors, which will be more convenient in industry.

Keywords: collaborative filtering, recommendation, data normalization, mapreduce

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Authors: Amin Amani, Masomeh Reihany Shirvan, Mahla Nabizadeh Mashizi, Mohadese Khoshtinat, Mohammad Elyas Ansarinia

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The purpose of this study is the relationship between a healthy lifestyle and risky behavior in physical education students of Bojnourd schools. The study sample consisted of teenagers studying in second and third grade of Bojnourd's high schools. According to level sampling, 604 students studying in the second grade, and 600 students studying in third grade were tested from physical education schools in Bojnourd. For sample selection, populations were divided into 4 area including north, East, West and South. Then according to the number of students of each area, sample size of each level was determined. Two questionnaires were used to collect data in this study which were consisted of three parts: The demographic data, Iranian teenagers' risk taking (IARS) and prevention methods with emphasize on the importance of family role were examined. The Central and dispersion indices, such as standard deviation, multiple variance analysis, and multivariate regression analysis were used. Results showed that the observed F is significant (P ≤ 0.01) and 21% of variance related to risky behavior is explained by the lack of awareness. Given the significance of the regression, the coefficients of risky behavior in teenagers in prediction equation showed that each of teenagers' risky behavior can have an impact on healthy lifestyle.

Keywords: healthy lifestyle, high-risk behavior, students, physical education

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Authors: Neda Valizadeh, Mani Mofidi, Sama Haghighi, Ali Hashemaghaee, Soudabeh Shafiee Ardestani

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Background: There are many systems and parameters to evaluate trauma patients in the emergency department. Most of these evaluations are to distinguish patients with worse conditions so that the care systems have a better prediction of condition for a better care-giving. The purpose of this study is to determine the relationship between axillary body temperature and mortality in patients hospitalized in the intensive care unit (ICU) with multiple traumas and with other clinical and para-clinical factors. Methods: All patients between 16 and 75 years old with multiple traumas who were admitted into Emergency Department then hospitalized in the ICU were included in our study. An axillary temperature in the first and the second day of admission, Glasgow cola scale (GCS), systolic blood pressure, Serum glucose levels, and white blood cell counts of all patients at the admission day were recorded and their relationship with mortality were analyzed by SPSS software with suitable statistical tests. Results: Axillary body temperatures in the first and second day were statistically lower in expired traumatic patients (p=0.001 and p<0,001 respectively). Patients with lower GCS had a significantly lower first-day temperature and a significantly higher mortality. (p=0.006 and p=0.006 respectively). Furthermore, the first-day axillary temperature was significantly lower in patients with a lower first-day systolic blood pressure (p=0.014). Conclusion: Our results showed that lower axillary body temperature in the first day is associated with higher mortality, lower GCS, and lower systolic blood pressure. Thus, this could be used as a predictor of mortality in evaluation of traumatic patients in emergency settings.

Keywords: fever, trauma, mortality, emergency

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Authors: Boris Kolev, Matt Kokan, Mohammad Deriszadeh, Farshid Bateni

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Due to the increasing demand for real estate and the need for efficient land utilization in Greater Vancouver, developers have been increasingly considering the construction of high-rise structures with multiple below-grade parking. The temporary excavations required to allow for the construction of underground levels have recently reached up to 40 meters in depth. One of the challenges with deep excavations is the prediction of wall displacements and ground settlements due to their effect on the integrity of City utilities, infrastructure, and adjacent buildings. A large database of survey monitoring data has been collected for deep excavations in various soil conditions and shoring systems. The majority of the data collected is for tie-back anchors and shotcrete lagging systems. The data were categorized, analyzed and the results were evaluated to find a relationship between the most dominant parameters controlling the displacement, such as depth of excavation, soil properties, and the tie-back anchor loading and arrangement. For a select number of deep excavations, finite element modeling was considered for analyses. The lateral displacements from the simulation results were compared to the recorded survey monitoring data. The study concludes with a discussion and comparison of the available empirical and numerical modeling methodologies for evaluating lateral displacements in deep excavations.

Keywords: deep excavations, lateral displacements, numerical modeling, shoring walls, tieback anchors

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Authors: Schadrack Mwizerwa

Abstract:

The characterization and prediction of landslides are crucial for assessing geological hazards and mitigating risks to infrastructure and communities. This research aims to develop a probabilistic framework for analyzing excavation-induced landslides, which is fundamental for assessing geological hazards and mitigating risks to infrastructure and communities. The study uses Hermite polynomial chaos, a non-stationary random process, to analyze the stability of a slope and characterize the failure probability of a real landslide induced by highway construction excavation. The correlation within the data is captured using the Karhunen-Loève (KL) expansion theory, and the finite element method is used to analyze the slope's stability. The research contributes to the field of landslide characterization by employing advanced random field approaches, providing valuable insights into the complex nature of landslide behavior and the effectiveness of advanced probabilistic models for risk assessment and management. The data collected from the Baiyuzui landslide, induced by highway construction, is used as an illustrative example. The findings highlight the importance of considering the probabilistic nature of landslides and provide valuable insights into the complex behavior of such hazards.

Keywords: Hermite polynomial chaos, Karhunen-Loeve, slope stability, probabilistic analysis

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Authors: Spandan Sahu, Amiya Kumar Pati, Kishanjit Kumar Khatua

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River is the main source of water. It is a form of natural open channel which gives rise to many complex phenomenon of sciences that needs to be tackled such as the critical flow conditions, boundary shear stress and depth averaged velocity. The development of society more or less solely depends upon the flow of rivers. The rivers are major sources of many sediments and specific ingredients which are much essential for human beings. During floods, part of a river is carried by the simple main channel and rest is carried by flood plains. For such compound asymmetric channels, the flow structure becomes complicated due to momentum exchange between main channel and adjoining flood plains. Distribution of boundary shear in subsections provides us with the concept of momentum transfer between the interface of main channel and the flood plains. Experimentally, to get better data with accurate results are very complex because of the complexity of the problem. Hence, Conveyance Estimation System (CES) software has been used to tackle the complex processes to determine the shear stresses at different sections of an open channel having asymmetric flood plains on both sides of the main channel and the results are compared with the symmetric flood plains for various geometrical shapes and flow conditions. Error analysis is also performed to know the degree of accuracy of the model implemented.

Keywords: depth average velocity, non prismatic compound channel, relative flow depth , velocity distribution

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Authors: Olaf Visker, Arnout De Vries, Lambert Schomaker

Abstract:

Predictive policing refers to the usage of analytical techniques to identify potential criminal activity. It has been widely implemented by various police departments. Being a relatively new area of research, there are, to the author’s knowledge, no absolute tried, and true methods and they still exhibit a variety of potential problems. One of those problems is closely related to the lack of understanding of how acting on these prediction influence crime itself. The goal of law enforcement is ultimately crime reduction. As such, a policy needs to be established that best facilitates this goal. This research aims to find such a policy by using adversarial agent-based modeling in combination with modern reinforcement learning techniques. It is presented here that a baseline model for both law enforcement and criminal agents and compare their performance to their respective reinforcement models. The experiments show that our smart law enforcement model is capable of reducing crime by making more deliberate choices regarding the locations of potential criminal activity. Furthermore, it is shown that the smart criminal model presents behavior consistent with popular crime theories and outperforms the baseline model in terms of crimes committed and time to capture. It does, however, still suffer from the difficulties of capturing long term rewards and learning how to handle multiple opposing goals.

Keywords: adversarial, agent based modelling, predictive policing, reinforcement learning

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Authors: Mohamed Al-Badrashiny, Abdelghani Bellaachia

Abstract:

This paper presents a classifier ensemble approach for predicting the survivability of the breast cancer patients using the latest database version of the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute. The system consists of two main components; features selection and classifier ensemble components. The features selection component divides the features in SEER database into four groups. After that it tries to find the most important features among the four groups that maximizes the weighted average F-score of a certain classification algorithm. The ensemble component uses three different classifiers, each of which models different set of features from SEER through the features selection module. On top of them, another classifier is used to give the final decision based on the output decisions and confidence scores from each of the underlying classifiers. Different classification algorithms have been examined; the best setup found is by using the decision tree, Bayesian network, and Na¨ıve Bayes algorithms for the underlying classifiers and Na¨ıve Bayes for the classifier ensemble step. The system outperforms all published systems to date when evaluated against the exact same data of SEER (period of 1973-2002). It gives 87.39% weighted average F-score compared to 85.82% and 81.34% of the other published systems. By increasing the data size to cover the whole database (period of 1973-2014), the overall weighted average F-score jumps to 92.4% on the held out unseen test set.

Keywords: classifier ensemble, breast cancer survivability, data mining, SEER

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Authors: J. S. Rudas, J. M. Gutiérrez Cabeza, A. Corz Rodríguez, L. M. Gómez, A. O. Toro

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The prediction of the wear rate of rubbing pairs has attracted the interest of many researchers for years. It has been recently proposed that the sliding wear rate can be inferred from the calculation of the energy rate dissipated by the tribological pair. In this paper some of the dissipative mechanisms present in a pin-on-disc configuration are discussed and both analytical and numerical calculations are carried out. Three dissipative mechanisms were studied: First, the energy release due to temperature gradients within the solid; second, the heat flow from the solid to the environment, and third, the energy loss due to abrasive damage of the surface. The Finite Element Method was used to calculate the dynamics of heat transfer within the solid, with the aid of commercial software. Validation the FEM model was assisted by virtual and laboratory experimentation using different operating points (sliding velocity and geometry contact). The materials for the experiments were Ti6Al4V alloy and Tungsten Carbide (WC-Co). The results showed that the sliding wear rate has a linear relationship with the energy dissipation flow. It was also found that energy loss due to micro-cutting is relevant for the system. This mechanism changes if the sliding velocity and pin geometry are modified though the degradation coefficient continues to present a linear behavior. We found that the less relevant dissipation mechanism for all the cases studied is the energy release by temperature gradients in the solid.

Keywords: degradation, dissipative mechanism, dry sliding, entropy, friction, wear

Procedia PDF Downloads 490