Search results for: prediction models
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8146

Search results for: prediction models

3676 Removal of Copper(II) and Lead(II) from Aqueous Phase by Plum Stone Activated Carbon

Authors: Serife Parlayici, Erol Pehlivan

Abstract:

In this study, plum stone shell activated carbon (PS-AC) was prepared to adsorb Cu(II) and Pb(II) ions in aqueous solutions. Some important parameters that influence the adsorption of metal ions such as pH, contact time and metal concentration have been systematically investigated in batch type reactors. The characterization of adsorbent is carried out by means of FTIR and SEM. It was found that the adsorption capacities of PS-AC were pH-dependent, and the optimal pH values were 4.5 and 5.0 for Cu(II) and Pb(II), respectively. The adsorption was rapid and the equilibrium was reached within 60 minutes to remove of Cu(II) and Pb(II) ions. The adsorption stability was studied in various doses of adsorbent. Langmuir, Freundlich and D-R adsorption models were used to describe adsorption equilibrium studies of PS-AC. Adsorption data showed that the adsorption of Cu(II) and Pb(II) is compatible with Langmuir isotherm model. The result showed that adsorption capacities calculated from the Langmuir isotherm were 33.22 mg/g and 57.80 mg/g for Cu(II) and Pb(II), respectively.

Keywords: plum-stone, activated carbon, copper and lead, isotherms

Procedia PDF Downloads 364
3675 Ganga Rejuvenation through Forestation and Conservation Measures in Riverscape

Authors: Ombir Singh

Abstract:

In spite of the religious and cultural pre-dominance of the river Ganga in the Indian ethos, fragmentation and degradation of the river continued down the ages. Recognizing the national concern on environmental degradation of the river and its basin, Ministry of Water Resources, River Development & Ganga Rejuvenation (MoWR,RD&GR), Government of India has initiated a number of pilot schemes for the rejuvenation of river Ganga under the ‘Namami Gange’ Programme. Considering the diversity, complexity, and intricacies of forest ecosystems and pivotal multiple functions performed by them and their inter-connectedness with highly dynamic river ecosystems, forestry interventions all along the river Ganga from its origin at Gaumukh, Uttarakhand to its mouth at Ganga Sagar, West Bengal has been planned by the ministry. For that Forest Research Institute (FRI) in collaboration with National Mission for Clean Ganga (NMCG) has prepared a Detailed Project Report (DPR) on Forestry Interventions for Ganga. The Institute has adopted an extensive consultative process at the national and state levels involving various stakeholders relevant in the context of river Ganga and employed a science-based methodology including use of remote sensing and GIS technologies for geo-spatial analysis, modeling and prioritization of sites for proposed forestation and conservation interventions. Four sets of field data formats were designed to obtain the field based information for forestry interventions, mainly plantations and conservation measures along the river course. In response, five stakeholder State Forest Departments had submitted more than 8,000 data sheets to the Institute. In order to analyze a voluminous field data received from five participating states, the Institute also developed a software to collate, analyze and generation of reports on proposed sites in Ganga basin. FRI has developed potential plantation and treatment models for the proposed forestry and other conservation measures in major three types of landscape components visualized in the Ganga riverscape. These are: (i) Natural, (ii) Agriculture, and (iii) Urban Landscapes. Suggested plantation models broadly varied for the Uttarakhand Himalayas and the Ganga Plains in five participating states. Besides extensive plantations in three type of landscapes within the riverscape, various conservation measures such as soil and water conservation, riparian wildlife management, wetland management, bioremediation and bio-filtration and supporting activities such as policy and law intervention, concurrent research, monitoring and evaluation, and mass awareness campaigns have been envisioned in the DPR. The DPR also incorporates the details of the implementation mechanism, budget provisioned for different components of the project besides allocation of budget state-wise to five implementing agencies, national partner organizations and the Nodal Ministry.

Keywords: conservation, Ganga, river, water, forestry interventions

Procedia PDF Downloads 145
3674 Reduction of Content of Lead and Zinc from Wastewater by Using of Metallurgical Waste

Authors: L. Rozumová, J. Seidlerová

Abstract:

The aim of this paper was to study the sorption properties of a blast furnace sludge used as the sorbent. The sorbent was utilized for reduction of content of lead and zinc ions. Sorbent utilized in this work was obtained from metallurgical industry from process of wet gas treatment in iron production. The blast furnace sludge was characterized by X-Ray diffraction, scanning electron microscopy, and XRFS spectroscopy. Sorption experiments were conducted in batch mode. The sorption of metal ions in the sludge was determined by correlation of adsorption isotherm models. The adsorption of lead and zinc ions was best fitted with Langmuir adsorption isotherms. The adsorption capacity of lead and zinc ions was 53.8 mg.g-1 and 10.7 mg.g-1, respectively. The results indicated that blast furnace sludge could be effectively used as secondary material and could be also employed as a low-cost alternative for the removal of heavy metals ions from wastewater.

Keywords: blast furnace sludge, lead, zinc, sorption

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3673 Optimisation of Extraction of Phenolic Compounds in Algerian Lavandula multifida, Algeria, NW

Authors: Mustapha Mahmoud Dif, Fouzia Benali-Toumi, Mohamed Benyahia, Sofiane Bouazza, Abbes Dellal, Slimane Baha

Abstract:

L. multifida is applied to treat rheumatism and cold and has hypoglycemic and anti-inflammatory properties. The present study is to optimize the extraction of phenolic compounds in Algerian Lavandula multifida. The influences of parameters including temperature (decoction and maceration) and extraction time (15min to 45 min) on the flavonoids concentration are studied. The optimal conditions are determined and the quadratic response surfaces draw from the mathematical models. Total phenols were evaluated using Folin sicaltieu methods, total flavonoids were estimated using the Tri chloral aluminum method. The maximum concentration extracted, for total flavonoids, equal to 0.043 mg/g was achieved with decoction and extraction time of 41.55 min. However, for total phenol compounds highest concentration of 0.218 mg/g, is obtained with 45 min at 49.99°C.

Keywords: L multifidi, phenolic content, optimization, time, temperature

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3672 Influence of Improved Roughage Quality and Period of Meal Termination on Digesta Load in the Digestive Organs of Goats

Authors: Rasheed A. Adebayo, Mehluli M. Moyo, Ignatius V. Nsahlai

Abstract:

Ruminants are known to relish roughage for productivity but the effect of its quality on digesta load in rumen, omasum, abomasum and other distal organs of the digestive tract is yet unknown. Reticulorumen fill is a strong indicator for long-term control of intake in ruminants. As such, the measurement and prediction of digesta load in these compartments may be crucial to productivity in the ruminant industry. The current study aimed at determining the effect of (a) diet quality on digesta load in digestive organs of goats, and (b) period of meal termination on the reticulorumen fill and digesta load in other distal compartments of the digestive tract of goats. Goats were fed with urea-treated hay (UTH), urea-sprayed hay (USH) and non-treated hay (NTH). At the end of eight weeks of a feeding trial period, upon termination of a meal in the morning, afternoon or evening, all goats were slaughtered in random groups of three per day to measure reticulorumen fill and digesta loads in other distal compartments of the digestive tract. Both diet quality and period affected (P < 0.05) the measure of reticulorumen fill. However, reticulorumen fill in the evening was larger (P < 0.05) than afternoon, while afternoon was similar (P > 0.05) to morning. Also, diet quality affected (P < 0.05) the wet omasal digesta load, wet abomasum, dry abomasum and dry caecum digesta loads but did not affect (P > 0.05) both wet and dry digesta loads in other compartments of the digestive tract. Period of measurement did not affect (P > 0.05) the wet omasal digesta load, and both wet and dry digesta loads in other compartments of the digestive tract except wet abomasum digesta load (P < 0.05) and dry caecum digesta load (P < 0.05). Both wet and dry reticulorumen fill were correlated (P < 0.05) with omasum (r = 0.623) and (r = 0.723), respectively. In conclusion, reticulorumen fill of goats decreased by improving the roughage quality; and the period of meal termination and measurement of the fill is a key factor to the quantity of digesta load.

Keywords: digesta, goats, meal termination, reticulo-rumen fill

Procedia PDF Downloads 367
3671 Application of Artificial Neural Network for Single Horizontal Bare Tube and Bare Tube Bundles (Staggered) of Large Particles: Heat Transfer Prediction

Authors: G. Ravindranath, S. Savitha

Abstract:

This paper presents heat transfer analysis of single horizontal bare tube and heat transfer analysis of staggered arrangement of bare tube bundles bare tube bundles in gas-solid (air-solid) fluidized bed and predictions are done by using Artificial Neural Network (ANN) based on experimental data. Fluidized bed provide nearly isothermal environment with high heat transfer rate to submerged objects i.e. due to through mixing and large contact area between the gas and the particle, a fully fluidized bed has little temperature variation and gas leaves at a temperature which is close to that of the bed. Measurement of average heat transfer coefficient was made by local thermal simulation technique in a cold bubbling air-fluidized bed of size 0.305 m. x 0.305 m. Studies were conducted for single horizontal Bare Tube of length 305mm and 28.6mm outer diameter and for bare tube bundles of staggered arrangement using beds of large (average particle diameter greater than 1 mm) particle (raagi and mustard). Within the range of experimental conditions influence of bed particle diameter ( Dp), Fluidizing Velocity (U) were studied, which are significant parameters affecting heat transfer. Artificial Neural Networks (ANNs) have been receiving an increasing attention for simulating engineering systems due to some interesting characteristics such as learning capability, fault tolerance, and non-linearity. Here, feed-forward architecture and trained by back-propagation technique is adopted to predict heat transfer analysis found from experimental results. The ANN is designed to suit the present system which has 3 inputs and 2 out puts. The network predictions are found to be in very good agreement with the experimental observed values of bare heat transfer coefficient (hb) and nusselt number of bare tube (Nub).

Keywords: fluidized bed, large particles, particle diameter, ANN

Procedia PDF Downloads 362
3670 A Machine Learning Approach to Detecting Evasive PDF Malware

Authors: Vareesha Masood, Ammara Gul, Nabeeha Areej, Muhammad Asif Masood, Hamna Imran

Abstract:

The universal use of PDF files has prompted hackers to use them for malicious intent by hiding malicious codes in their victim’s PDF machines. Machine learning has proven to be the most efficient in identifying benign files and detecting files with PDF malware. This paper has proposed an approach using a decision tree classifier with parameters. A modern, inclusive dataset CIC-Evasive-PDFMal2022, produced by Lockheed Martin’s Cyber Security wing is used. It is one of the most reliable datasets to use in this field. We designed a PDF malware detection system that achieved 99.2%. Comparing the suggested model to other cutting-edge models in the same study field, it has a great performance in detecting PDF malware. Accordingly, we provide the fastest, most reliable, and most efficient PDF Malware detection approach in this paper.

Keywords: PDF, PDF malware, decision tree classifier, random forest classifier

Procedia PDF Downloads 86
3669 Turbulence Modeling and Wave-Current Interactions

Authors: A. C. Bennis, F. Dumas, F. Ardhuin, B. Blanke

Abstract:

The mechanics of rip currents are complex, involving interactions between waves, currents, water levels and the bathymetry, that present particular challenges for numerical models. Here, the effects of a grid-spacing dependent horizontal mixing on the wave-current interactions are studied. Near the shore, wave rays diverge from channels towards bar crests because of refraction by topography and currents, in a way that depends on the rip current intensity which is itself modulated by the horizontal mixing. At low resolution with the grid-spacing dependent horizontal mixing, the wave motion is the same for both coupling modes because the wave deviation by the currents is weak. In high-resolution case, however, classical results are found with the stabilizing effect of the flow by feedback of waves on currents. Lastly, wave-current interactions and the horizontal mixing strongly affect the intensity of the three-dimensional rip velocity.

Keywords: numerical modeling, wave-current interactions, turbulence modeling, rip currents

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3668 Temperature and Admixtures Effects on the Maturity of Normal and Super Fine Ground Granulated Blast Furnace Slag Mortars for the Precast Concrete Industry

Authors: Matthew Cruickshank, Chaaruchandra Korde, Roger P. West, John Reddy

Abstract:

Precast concrete element exports are growing in importance in Ireland’s concrete industry and with the increased global focus on reducing carbon emissions, the industry is exploring more sustainable alternatives such as using ground granulated blast-furnace slag (GGBS) as a partial replacement of Portland cement. It is well established that GGBS, with low early age strength development, has limited use in precast manufacturing due to the need for early de-moulding, cutting of pre-stressed strands and lifting. In this dichotomy, the effects of temperature, admixture, are explored to try to achieve the required very early age strength. Testing of the strength of mortars is mandated in the European cement standard, so here with 50% GGBS and Super Fine GGBS, with three admixture conditions (none, conventional accelerator, novel accelerator) and two early age curing temperature conditions (20°C and 35°C), standard mortar strengths are measured at six ages (16 hours, 1, 2, 3, 7, 28 days). The present paper will describe the effort towards developing maturity curves to aid in understanding the effect of these accelerating admixtures and GGBS fineness on slag cement mortars, allowing prediction of their strength with time and temperature. This study is of particular importance to the precast industry where concrete temperature can be controlled. For the climatic conditions in Ireland, heating of precast beds for long hours will amount to an additional cost and also contribute to the carbon footprint of the products. When transitioned from mortar to concrete, these maturity curves are expected to play a vital role in predicting the strength of the GGBS concrete at a very early age prior to demoulding.

Keywords: accelerating admixture, early age strength, ground granulated blast-furnace slag, GGBS, maturity, precast concrete

Procedia PDF Downloads 154
3667 TNFRSF11B Gene Polymorphisms A163G and G11811C in Prediction of Osteoporosis Risk

Authors: I. Boroňová, J.Bernasovská, J. Kľoc, Z. Tomková, E. Petrejčíková, D. Gabriková, S. Mačeková

Abstract:

Osteoporosis is a complex health disease characterized by low bone mineral density, which is determined by an interaction of genetics with metabolic and environmental factors. Current research in genetics of osteoporosis is focused on identification of responsible genes and polymorphisms. TNFRSF11B gene plays a key role in bone remodeling. The aim of this study was to investigate the genotype and allele distribution of A163G (rs3102735) osteoprotegerin gene promoter and G1181C (rs2073618) osteoprotegerin first exon polymorphisms in the group of 180 unrelated postmenopausal women with diagnosed osteoporosis and 180 normal controls. Genomic DNA was isolated from peripheral blood leukocytes using standard methodology. Genotyping for presence of different polymorphisms was performed using the Custom Taqman®SNP Genotyping assays. Hardy-Weinberg equilibrium was tested for each SNP in the groups of participants using the chi-square (χ2) test. The distribution of investigated genotypes in the group of patients with osteoporosis were as follows: AA (66.7%), AG (32.2%), GG (1.1%) for A163G polymorphism; GG (19.4%), CG (44.4%), CC (36.1%) for G1181C polymorphism. The distribution of genotypes in normal controls were follows: AA (71.1%), AG (26.1%), GG (2.8%) for A163G polymorphism; GG (22.2%), CG (48.9%), CC (28.9%) for G1181C polymorphism. In A163G polymorphism the variant G allele was more common among patients with osteoporosis: 17.2% versus 15.8% in normal controls. Also, in G1181C polymorphism the phenomenon of more frequent occurrence of C allele in the group of patients with osteoporosis was observed (58.3% versus 53.3%). Genotype and allele distributions showed no significant differences (A163G: χ2=0.270, p=0.605; χ2=0.250, p=0.616; G1181C: χ2= 1.730, p=0.188; χ2=1.820, p=0.177). Our results represents an initial study, further studies of more numerous file and associations studies will be carried out. Knowing the distribution of genotypes is important for assessing the impact of these polymorphisms on various parameters associated with osteoporosis. Screening for identification of “at-risk” women likely to develop osteoporosis and initiating subsequent early intervention appears to be most effective strategy to substantially reduce the risks of osteoporosis.

Keywords: osteoporosis, real-time PCR method, SNP polymorphisms

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3666 A Consideration on the Offset Frontal Impact Modeling Using Spring-Mass Model

Authors: Jaemoon Lim

Abstract:

To construct the lumped spring-mass model considering the occupants for the offset frontal crash, the SISAME software and the NHTSA test data were used. The data on 56 kph 40% offset frontal vehicle to deformable barrier crash test of a MY2007 Mazda 6 4-door sedan were obtained from NHTSA test database. The overall behaviors of B-pillar and engine of simulation models agreed very well with the test data. The trends of accelerations at the driver and passenger head were similar but big differences in peak values. The differences of peak values caused the large errors of the HIC36 and 3 ms chest g’s. To predict well the behaviors of dummies, the spring-mass model for the offset frontal crash needs to be improved.

Keywords: chest g’s, HIC36, lumped spring-mass model, offset frontal impact, SISAME

Procedia PDF Downloads 456
3665 Variational Explanation Generator: Generating Explanation for Natural Language Inference Using Variational Auto-Encoder

Authors: Zhen Cheng, Xinyu Dai, Shujian Huang, Jiajun Chen

Abstract:

Recently, explanatory natural language inference has attracted much attention for the interpretability of logic relationship prediction, which is also known as explanation generation for Natural Language Inference (NLI). Existing explanation generators based on discriminative Encoder-Decoder architecture have achieved noticeable results. However, we find that these discriminative generators usually generate explanations with correct evidence but incorrect logic semantic. It is due to that logic information is implicitly encoded in the premise-hypothesis pairs and difficult to model. Actually, logic information identically exists between premise-hypothesis pair and explanation. And it is easy to extract logic information that is explicitly contained in the target explanation. Hence we assume that there exists a latent space of logic information while generating explanations. Specifically, we propose a generative model called Variational Explanation Generator (VariationalEG) with a latent variable to model this space. Training with the guide of explicit logic information in target explanations, latent variable in VariationalEG could capture the implicit logic information in premise-hypothesis pairs effectively. Additionally, to tackle the problem of posterior collapse while training VariaztionalEG, we propose a simple yet effective approach called Logic Supervision on the latent variable to force it to encode logic information. Experiments on explanation generation benchmark—explanation-Stanford Natural Language Inference (e-SNLI) demonstrate that the proposed VariationalEG achieves significant improvement compared to previous studies and yields a state-of-the-art result. Furthermore, we perform the analysis of generated explanations to demonstrate the effect of the latent variable.

Keywords: natural language inference, explanation generation, variational auto-encoder, generative model

Procedia PDF Downloads 148
3664 Foodborne Outbreak Calendar: Application of Time Series Analysis

Authors: Ryan B. Simpson, Margaret A. Waskow, Aishwarya Venkat, Elena N. Naumova

Abstract:

The Centers for Disease Control and Prevention (CDC) estimate that 31 known foodborne pathogens cause 9.4 million cases of these illnesses annually in US. Over 90% of these illnesses are associated with exposure to Campylobacter, Cryptosporidium, Cyclospora, Listeria, Salmonella, Shigella, Shiga-Toxin Producing E.Coli (STEC), Vibrio, and Yersinia. Contaminated products contain parasites typically causing an intestinal illness manifested by diarrhea, stomach cramping, nausea, weight loss, fatigue and may result in deaths in fragile populations. Since 1998, the National Outbreak Reporting System (NORS) has allowed for routine collection of suspected and laboratory-confirmed cases of food poisoning. While retrospective analyses have revealed common pathogen-specific seasonal patterns, little is known concerning the stability of those patterns over time and whether they can be used for preventative forecasting. The objective of this study is to construct a calendar of foodborne outbreaks of nine infections based on the peak timing of outbreak incidence in the US from 1996 to 2017. Reported cases were abstracted from FoodNet for Salmonella (135115), Campylobacter (121099), Shigella (48520), Cryptosporidium (21701), STEC (18022), Yersinia (3602), Vibrio (3000), Listeria (2543), and Cyclospora (758). Monthly counts were compiled for each agent, seasonal peak timing and peak intensity were estimated, and the stability of seasonal peaks and synchronization of infections was examined. Negative Binomial harmonic regression models with the delta-method were applied to derive confidence intervals for the peak timing for each year and overall study period estimates. Preliminary results indicate that five infections continue to lead as major causes of outbreaks, exhibiting steady upward trends with annual increases in cases ranging from 2.71% (95%CI: [2.38, 3.05]) in Campylobacter, 4.78% (95%CI: [4.14, 5.41]) in Salmonella, 7.09% (95%CI: [6.38, 7.82]) in E.Coli, 7.71% (95%CI: [6.94, 8.49]) in Cryptosporidium, and 8.67% (95%CI: [7.55, 9.80]) in Vibrio. Strong synchronization of summer outbreaks were observed, caused by Campylobacter, Vibrio, E.Coli and Salmonella, peaking at 7.57 ± 0.33, 7.84 ± 0.47, 7.85 ± 0.37, and 7.82 ± 0.14 calendar months, respectively, with the serial cross-correlation ranging 0.81-0.88 (p < 0.001). Over 21 years, Listeria and Cryptosporidium peaks (8.43 ± 0.77 and 8.52 ± 0.45 months, respectively) have a tendency to arrive 1-2 weeks earlier, while Vibrio peaks (7.8 ± 0.47) delay by 2-3 weeks. These findings will be incorporated in the forecast models to predict common paths of the spread, long-term trends, and the synchronization of outbreaks across etiological agents. The predictive modeling of foodborne outbreaks should consider long-term changes in seasonal timing, spatiotemporal trends, and sources of contamination.

Keywords: foodborne outbreak, national outbreak reporting system, predictive modeling, seasonality

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3663 Estimation and Forecasting with a Quantile AR Model for Financial Returns

Authors: Yuzhi Cai

Abstract:

This talk presents a Bayesian approach to quantile autoregressive (QAR) time series model estimation and forecasting. We establish that the joint posterior distribution of the model parameters and future values is well defined. The associated MCMC algorithm for parameter estimation and forecasting converges to the posterior distribution quickly. We also present a combining forecasts technique to produce more accurate out-of-sample forecasts by using a weighted sequence of fitted QAR models. A moving window method to check the quality of the estimated conditional quantiles is developed. We verify our methodology using simulation studies and then apply it to currency exchange rate data. An application of the method to the USD to GBP daily currency exchange rates will also be discussed. The results obtained show that an unequally weighted combining method performs better than other forecasting methodology.

Keywords: combining forecasts, MCMC, quantile modelling, quantile forecasting, predictive density functions

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3662 Market-Power, Stability, and Risk-Taking: An Analysis Surrounding the Riba-Free Banking

Authors: Louati Salma, Louhichi Awatef, Boujelbene Younes

Abstract:

Analysis of the trade-off between competition and financial stability has been at the center of academic and policy debate for over two decades and especially since the 2007-2008 global financial crises. We use information on 10 OIC countries from 2005 to 2014 to investigate the influence of bank competition on individual bank stability and risk-taking. Alternatively, we explore whether the quality of prudential regulation may affect the nexus between competition and banking stability/risk-taking. We provide a particular attention to the Islamic banking system which principally involves with the Riba-free instruments as compared to the conventional interest-based system. We first run a dynamic panel regression (GMM), and then we apply a panel vector autoregressive (PVAR) methodology to compare both banking business models.

Keywords: Lerner index, Islamic banks, non-performing loans, prudential regulations, z-score

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3661 Prediction of Positive Cloud-to-Ground Lightning Striking Zones for Charged Thundercloud Based on Line Charge Model

Authors: Surajit Das Barman, Rakibuzzaman Shah, Apurv Kumar

Abstract:

Bushfire is known as one of the ascendant factors to create pyrocumulus thundercloud that causes the ignition of new fires by pyrocumulonimbus (pyroCb) lightning strikes and creates major losses of lives and property worldwide. A conceptual model-based risk planning would be beneficial to predict the lightning striking zones on the surface of the earth underneath the pyroCb thundercloud. PyroCb thundercloud can generate both positive cloud-to-ground (+CG) and negative cloud-to-ground (-CG) lightning in which +CG tends to ignite more bushfires and cause massive damage to nature and infrastructure. In this paper, a simple line charge structured thundercloud model is constructed in 2-D coordinates using the method of image charge to predict the probable +CG lightning striking zones on the earth’s surface for two conceptual thundercloud charge configurations: titled dipole and conventional tripole structure with excessive lower positive charge regions that lead to producing +CG lightning. The electric potential and surface charge density along the earth’s surface for both structures via continuously adjusting the position and the charge density of their charge regions is investigated. Simulation results for tilted dipole structure confirm the down-shear extension of the upper positive charge region in the direction of the cloud’s forward flank by 4 to 8 km, resulting in negative surface density, and would expect +CG lightning to strike within 7.8 km to 20 km around the earth periphery in the direction of the cloud’s forward flank. On the other hand, the conceptual tripole charge structure with enhanced lower positive charge region develops negative surface charge density on the earth’s surface in the range |x| < 6.5 km beneath the thundercloud and highly favors producing +CG lightning strikes.

Keywords: pyrocumulonimbus, cloud-to-ground lightning, charge structure, surface charge density, forward flank

Procedia PDF Downloads 108
3660 Numerical Investigation the Effect of Adjustable Guide Vane for Improving the Airflow Rate in Axial Fans

Authors: Behzad Shahizare, N. Nik-Ghazali, Kannan M. Munisamy, Seyedsaeed Tabatabaeikia

Abstract:

The main objective of this study is to clarify the effect of the adjustable outlet guide vane (OGV) on the axial fan. Three-dimensional Numerical study was performed to analyze the effect of adjustable guide vane for improving the airflow rate in axial fans. Grid independence test was done between five different meshes in order to choose the reliable mesh. In flow analyses, Reynolds averaged Navier-Stokes (RANS) equations was solved using three types of turbulence models named k-ɛ, k-ω and k-ω SST. The aerodynamic performances of the fan and guide vane were evaluated. Numerical method was validated by comparing with experimental test according to AMECA 210 standard. Results showed that, by using the adjustable guide vane the airflow rate is increased around 3% to 6 %. The maximum enhancement of the airflow rate was achieved when pressure was 374pa.

Keywords: axial fan, adjustable guide vane, CFD, turbo machinery

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3659 Improvement of Brige Weigh-In-Motion Technique Considering the Driving Conditions of Vehicles

Authors: Changgil Lee, Jooyoung Park, Seunghee Park

Abstract:

In this study, bridge weigh-in-motion (BWIM) system was simulated under various driving conditions of vehicles to improve the performance of the BWIM system. Two driving conditions were considered. One was the number of the axle of the vehicles. Since the vehicles have different number of axle according to the types of the vehicle, the vehicles were modeled considering the number of the axle. The other was the speed of the vehicles because the speed of the vehicles is not consistent on the bridge. To achieve the goal, the dynamic characteristics of a bridge such as modal parameters were considered in numerical simulation by analyzing precision models. Also, the driving vehicles were modeled as mass-spring-damping systems reflecting the axle information.

Keywords: bridge weigh-in-motion (BWIM) system, driving conditions, precision analysis model, the number of axle, the speed of vehicle

Procedia PDF Downloads 463
3658 Hypergraph Models of Metabolism

Authors: Nicole Pearcy, Jonathan J. Crofts, Nadia Chuzhanova

Abstract:

In this paper, we employ a directed hypergraph model to investigate the extent to which environmental variability influences the set of available biochemical reactions within a living cell. Such an approach avoids the limitations of the usual complex network formalism by allowing for the multilateral relationships (i.e. connections involving more than two nodes) that naturally occur within many biological processes. More specifically, we extend the concept of network reciprocity to complex hyper-networks, thus enabling us to characterize a network in terms of the existence of mutual hyper-connections, which may be considered a proxy for metabolic network complexity. To demonstrate these ideas, we study 115 metabolic hyper-networks of bacteria, each of which can be classified into one of 6 increasingly varied habitats. In particular, we found that reciprocity increases significantly with increased environmental variability, supporting the view that organism adaptability leads to increased complexities in the resultant biochemical networks.

Keywords: complexity, hypergraphs, reciprocity, metabolism

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3657 Role of Spatial Variability in the Service Life Prediction of Reinforced Concrete Bridges Affected by Corrosion

Authors: Omran M. Kenshel, Alan J. O'Connor

Abstract:

Estimating the service life of Reinforced Concrete (RC) bridge structures located in corrosive marine environments of a great importance to their owners/engineers. Traditionally, bridge owners/engineers relied more on subjective engineering judgment, e.g. visual inspection, in their estimation approach. However, because financial resources are often limited, rational calculation methods of estimation are needed to aid in making reliable and more accurate predictions for the service life of RC structures. This is in order to direct funds to bridges found to be the most critical. Criticality of the structure can be considered either form the Structural Capacity (i.e. Ultimate Limit State) or from Serviceability viewpoint whichever is adopted. This paper considers the service life of the structure only from the Structural Capacity viewpoint. Considering the great variability associated with the parameters involved in the estimation process, the probabilistic approach is most suited. The probabilistic modelling adopted here used Monte Carlo simulation technique to estimate the Reliability (i.e. Probability of Failure) of the structure under consideration. In this paper the authors used their own experimental data for the Correlation Length (CL) for the most important deterioration parameters. The CL is a parameter of the Correlation Function (CF) by which the spatial fluctuation of a certain deterioration parameter is described. The CL data used here were produced by analyzing 45 chloride profiles obtained from a 30 years old RC bridge located in a marine environment. The service life of the structure were predicted in terms of the load carrying capacity of an RC bridge beam girder. The analysis showed that the influence of SV is only evident if the reliability of the structure is governed by the Flexure failure rather than by the Shear failure.

Keywords: Chloride-induced corrosion, Monte-Carlo simulation, reinforced concrete, spatial variability

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3656 MarginDistillation: Distillation for Face Recognition Neural Networks with Margin-Based Softmax

Authors: Svitov David, Alyamkin Sergey

Abstract:

The usage of convolutional neural networks (CNNs) in conjunction with the margin-based softmax approach demonstrates the state-of-the-art performance for the face recognition problem. Recently, lightweight neural network models trained with the margin-based softmax have been introduced for the face identification task for edge devices. In this paper, we propose a distillation method for lightweight neural network architectures that outperforms other known methods for the face recognition task on LFW, AgeDB-30 and Megaface datasets. The idea of the proposed method is to use class centers from the teacher network for the student network. Then the student network is trained to get the same angles between the class centers and face embeddings predicted by the teacher network.

Keywords: ArcFace, distillation, face recognition, margin-based softmax

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3655 An Experimental Investigation of the Surface Pressure on Flat Plates in Turbulent Boundary Layers

Authors: Azadeh Jafari, Farzin Ghanadi, Matthew J. Emes, Maziar Arjomandi, Benjamin S. Cazzolato

Abstract:

The turbulence within the atmospheric boundary layer induces highly unsteady aerodynamic loads on structures. These loads, if not accounted for in the design process, will lead to structural failure and are therefore important for the design of the structures. For an accurate prediction of wind loads, understanding the correlation between atmospheric turbulence and the aerodynamic loads is necessary. The aim of this study is to investigate the effect of turbulence within the atmospheric boundary layer on the surface pressure on a flat plate over a wide range of turbulence intensities and integral length scales. The flat plate is chosen as a fundamental geometry which represents structures such as solar panels and billboards. Experiments were conducted at the University of Adelaide large-scale wind tunnel. Two wind tunnel boundary layers with different intensities and length scales of turbulence were generated using two sets of spires with different dimensions and a fetch of roughness elements. Average longitudinal turbulence intensities of 13% and 26% were achieved in each boundary layer, and the longitudinal integral length scale within the three boundary layers was between 0.4 m and 1.22 m. The pressure distributions on a square flat plate at different elevation angles between 30° and 90° were measured within the two boundary layers with different turbulence intensities and integral length scales. It was found that the peak pressure coefficient on the flat plate increased with increasing turbulence intensity and integral length scale. For example, the peak pressure coefficient on a flat plate elevated at 90° increased from 1.2 to 3 with increasing turbulence intensity from 13% to 26%. Furthermore, both the mean and the peak pressure distribution on the flat plates varied with turbulence intensity and length scale. The results of this study can be used to provide a more accurate estimation of the unsteady wind loads on structures such as buildings and solar panels.

Keywords: atmospheric boundary layer, flat plate, pressure coefficient, turbulence

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3654 Deorbiting Performance of Electrodynamic Tethers to Mitigate Space Debris

Authors: Giulia Sarego, Lorenzo Olivieri, Andrea Valmorbida, Carlo Bettanini, Giacomo Colombatti, Marco Pertile, Enrico C. Lorenzini

Abstract:

International guidelines recommend removing any artificial body in Low Earth Orbit (LEO) within 25 years from mission completion. Among disposal strategies, electrodynamic tethers appear to be a promising option for LEO, thanks to the limited storage mass and the minimum interface requirements to the host spacecraft. In particular, recent technological advances make it feasible to deorbit large objects with tether lengths of a few kilometers or less. To further investigate such an innovative passive system, the European Union is currently funding the project E.T.PACK – Electrodynamic Tether Technology for Passive Consumable-less Deorbit Kit in the framework of the H2020 Future Emerging Technologies (FET) Open program. The project focuses on the design of an end of life disposal kit for LEO satellites. This kit aims to deploy a taped tether that can be activated at the spacecraft end of life to perform autonomous deorbit within the international guidelines. In this paper, the orbital performance of the E.T.PACK deorbiting kit is compared to other disposal methods. Besides, the orbital decay prediction is parametrized as a function of spacecraft mass and tether system performance. Different values of length, width, and thickness of the tether will be evaluated for various scenarios (i.e., different initial orbital parameters). The results will be compared to other end-of-life disposal methods with similar allocated resources. The analysis of the more innovative system’s performance with the tape coated with a thermionic material, which has a low work-function (LWT), for which no active component for the cathode is required, will also be briefly discussed. The results show that the electrodynamic tether option can be a competitive and performant solution for satellite disposal compared to other deorbit technologies.

Keywords: deorbiting performance, H2020, spacecraft disposal, space electrodynamic tethers

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3653 Classifying Turbomachinery Blade Mode Shapes Using Artificial Neural Networks

Authors: Ismail Abubakar, Hamid Mehrabi, Reg Morton

Abstract:

Currently, extensive signal analysis is performed in order to evaluate structural health of turbomachinery blades. This approach is affected by constraints of time and the availability of qualified personnel. Thus, new approaches to blade dynamics identification that provide faster and more accurate results are sought after. Generally, modal analysis is employed in acquiring dynamic properties of a vibrating turbomachinery blade and is widely adopted in condition monitoring of blades. The analysis provides useful information on the different modes of vibration and natural frequencies by exploring different shapes that can be taken up during vibration since all mode shapes have their corresponding natural frequencies. Experimental modal testing and finite element analysis are the traditional methods used to evaluate mode shapes with limited application to real live scenario to facilitate a robust condition monitoring scheme. For a real time mode shape evaluation, rapid evaluation and low computational cost is required and traditional techniques are unsuitable. In this study, artificial neural network is developed to evaluate the mode shape of a lab scale rotating blade assembly by using result from finite element modal analysis as training data. The network performance evaluation shows that artificial neural network (ANN) is capable of mapping the correlation between natural frequencies and mode shapes. This is achieved without the need of extensive signal analysis. The approach offers advantage from the perspective that the network is able to classify mode shapes and can be employed in real time including simplicity in implementation and accuracy of the prediction. The work paves the way for further development of robust condition monitoring system that incorporates real time mode shape evaluation.

Keywords: modal analysis, artificial neural network, mode shape, natural frequencies, pattern recognition

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3652 A Continuous Real-Time Analytic for Predicting Instability in Acute Care Rapid Response Team Activations

Authors: Ashwin Belle, Bryce Benson, Mark Salamango, Fadi Islim, Rodney Daniels, Kevin Ward

Abstract:

A reliable, real-time, and non-invasive system that can identify patients at risk for hemodynamic instability is needed to aid clinicians in their efforts to anticipate patient deterioration and initiate early interventions. The purpose of this pilot study was to explore the clinical capabilities of a real-time analytic from a single lead of an electrocardiograph to correctly distinguish between rapid response team (RRT) activations due to hemodynamic (H-RRT) and non-hemodynamic (NH-RRT) causes, as well as predict H-RRT cases with actionable lead times. The study consisted of a single center, retrospective cohort of 21 patients with RRT activations from step-down and telemetry units. Through electronic health record review and blinded to the analytic’s output, each patient was categorized by clinicians into H-RRT and NH-RRT cases. The analytic output and the categorization were compared. The prediction lead time prior to the RRT call was calculated. The analytic correctly distinguished between H-RRT and NH-RRT cases with 100% accuracy, demonstrating 100% positive and negative predictive values, and 100% sensitivity and specificity. In H-RRT cases, the analytic detected hemodynamic deterioration with a median lead time of 9.5 hours prior to the RRT call (range 14 minutes to 52 hours). The study demonstrates that an electrocardiogram (ECG) based analytic has the potential for providing clinical decision and monitoring support for caregivers to identify at risk patients within a clinically relevant timeframe allowing for increased vigilance and early interventional support to reduce the chances of continued patient deterioration.

Keywords: critical care, early warning systems, emergency medicine, heart rate variability, hemodynamic instability, rapid response team

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3651 A Resilience Process Model of Natural Gas Pipeline Systems

Authors: Zhaoming Yang, Qi Xiang, Qian He, Michael Havbro Faber, Enrico Zio, Huai Su, Jinjun Zhang

Abstract:

Resilience is one of the key factors for system safety assessment and optimization, and resilience studies of natural gas pipeline systems (NGPS), especially in terms of process descriptions, are still being explored. Based on the three main stages, which are function loss process, recovery process, and waiting process, the paper has built functions and models which are according to the practical characteristics of NGPS and mainly analyzes the characteristics of deterministic interruptions. The resilience of NGPS also considers the threshold of the system function or users' satisfaction. The outcomes, which quantify the resilience of NGPS in different evaluation views, can be combined with the max flow and shortest path methods, help with the optimization of extra gas supplies and gas routes as well as pipeline maintenance strategies, the quick analysis of disturbance effects and the improvement of NGPS resilience evaluation accuracy.

Keywords: natural gas pipeline system, resilience, process modeling, deterministic disturbance

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3650 Investigation of Polar Atmospheric Response to the Intense Geo-Space Activities

Authors: Jayanta K. Behera, Ashwini K. Sinha

Abstract:

The study has pointed out the relationship of energetic particle precipitation (EPP) during high speed solar wind streams (HSS) to the ionization characteristics and subsequent NOx production in the polar atmosphere. Over the last few decades, it has been shown that production of NOx in the mesosphere region during the precipitation of charged particles (with energy range >30 KeV to 1 MeV) is directly related to the ozone loss in the polar middle atmosphere, extending from mesosphere to upper stratosphere. This study has dealt with the analysis of the interplanetary parameters such as interplanetary magnetic field (IMF), solar wind velocity (Vs), charged particle density (Ns), convection field enhancement (Ec) during such HSS events and their link to the rate of production of NOx in the mesosphere. Moreover, the analysis will be used to validate or, to modify the current ion-chemistry models which describe the ionization rate and NOx production in the polar atmosphere due to EPP.

Keywords: energetic particle precipitation (EPP), NOx, ozone depletion, polar vortex

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3649 Evaluation of Progressive Collapse of Transmission Tower

Authors: Jeong-Hwan Choi, Hyo-Sang Park, Tae-Hyung Lee

Abstract:

The transmission tower is one of the crucial lifeline structures in a modern society, and it needs to be protected against extreme loading conditions. However, the transmission tower is a very complex structure and, therefore, it is very difficult to simulate the actual damage and the collapse behavior of the tower structure. In this study, the actual collapse behavior of the transmission tower due to lateral loading conditions such as wind load is evaluated through the computational simulation. For that, a progressive collapse procedure is applied to the simulation. In this procedure, after running the simulation, if a member of the tower structure fails, the failed member is removed and the simulation run again. The 154kV transmission tower is selected for this study. The simulation is performed by nonlinear static analysis procedure, namely pushover analysis, using OpenSEES, an earthquake simulation platform. Three-dimensional finite element models of those towers are developed.

Keywords: transmission tower, OpenSEES, pushover, progressive collapse

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3648 Difference between Riding a Bicycle on a Sidewalk or in the Street by Usual Traveling Means

Authors: Ai Fujii, Kan Shimazaki

Abstract:

Bicycle users must ride on the street according the law in Japan, but in practice, many bicycle users ride on the sidewalk. Drivers generally feel that bicycles riding in the street are in the way. In contrast, pedestrians generally feel that bicycles riding on the sidewalk are in the way. That seems to make sense. What, then, is the difference between riding a bicycle on the sidewalk or in the street by usual traveling means. We made 3D computer graphics models of pedestrians, a car, and a bicycle at an intersection. The bicycle was positioned to choose between advancing to the sidewalk or the street after a few seconds. We then made a 2D stimulus picture by changing the point of view of the 3DCG model pictures. Attitudes were surveyed using this 2D stimulus picture, and we compared attitudes between three groups, people traveling by car, on foot, or by bicycle. Here we report the survey result.

Keywords: bicycle, sidewalk, pedestrians, driver, intersection, safety

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3647 Evaluating the Feasibility of Magnetic Induction to Cross an Air-Water Boundary

Authors: Mark Watson, J.-F. Bousquet, Adam Forget

Abstract:

A magnetic induction based underwater communication link is evaluated using an analytical model and a custom Finite-Difference Time-Domain (FDTD) simulation tool. The analytical model is based on the Sommerfeld integral, and a full-wave simulation tool evaluates Maxwell’s equations using the FDTD method in cylindrical coordinates. The analytical model and FDTD simulation tool are then compared and used to predict the system performance for various transmitter depths and optimum frequencies of operation. To this end, the system bandwidth, signal to noise ratio, and the magnitude of the induced voltage are used to estimate the expected channel capacity. The models show that in seawater, a relatively low-power and small coils may be capable of obtaining a throughput of 40 to 300 kbps, for the case where a transmitter is at depths of 1 to 3 m and a receiver is at a height of 1 m.

Keywords: magnetic induction, FDTD, underwater communication, Sommerfeld

Procedia PDF Downloads 123