Search results for: compressive strength prediction
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6001

Search results for: compressive strength prediction

2671 Traction Behavior of Linear Piezo-Viscous Lubricants in Rough Elastohydrodynamic Lubrication Contacts

Authors: Punit Kumar, Niraj Kumar

Abstract:

The traction behavior of lubricants with the linear pressure-viscosity response in EHL line contacts is investigated numerically for smooth as well as rough surfaces. The analysis involves the simultaneous solution of Reynolds, elasticity and energy equations along with the computation of lubricant properties and surface temperatures. The temperature modified Doolittle-Tait equations are used to calculate viscosity and density as functions of fluid pressure and temperature, while Carreau model is used to describe the lubricant rheology. The surface roughness is assumed to be sinusoidal and it is present on the nearly stationary surface in near-pure sliding EHL conjunction. The linear P-V oil is found to yield much lower traction coefficients and slightly thicker EHL films as compared to the synthetic oil for a given set of dimensionless speed and load parameters. Besides, the increase in traction coefficient attributed to surface roughness is much lower for the former case. The present analysis emphasizes the importance of employing realistic pressure-viscosity response for accurate prediction of EHL traction.

Keywords: EHL, linear pressure-viscosity, surface roughness, traction, water/glycol

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2670 Gender Differences in the Prediction of Smartphone Use While Driving: Personal and Social Factors

Authors: Erez Kita, Gil Luria

Abstract:

This study examines gender as a boundary condition for the relationship between the psychological variable of mindfulness and the social variable of income with regards to the use of smartphones by young drivers. The use of smartphones while driving increases the likelihood of a car accident, endangering young drivers and other road users. The study sample included 186 young drivers who were legally permitted to drive without supervision. The subjects were first asked to complete questionnaires on mindfulness and income. Next, their smartphone use while driving was monitored over a one-month period. This study is unique as it used an objective smartphone monitoring application (rather than self-reporting) to count the number of times the young participants actually touched their smartphones while driving. The findings show that gender moderates the effects of social and personal factors (i.e., income and mindfulness) on the use of smartphones while driving. The pattern of moderation was similar for both social and personal factors. For men, mindfulness and income are negatively associated with the use of smartphones while driving. These factors are not related to the use of smartphones by women drivers. Mindfulness and income can be used to identify male populations that are at risk of using smartphones while driving. Interventions that improve mindfulness can be used to reduce the use of smartphones by male drivers.

Keywords: mindfulness, using smartphones while driving, income, gender, young drivers

Procedia PDF Downloads 170
2669 High School Gain Analytics From National Assessment Program – Literacy and Numeracy and Australian Tertiary Admission Rankin Linkage

Authors: Andrew Laming, John Hattie, Mark Wilson

Abstract:

Nine Queensland Independent high schools provided deidentified student-matched ATAR and NAPLAN data for all 1217 ATAR graduates since 2020 who also sat NAPLAN at the school. Graduating cohorts from the nine schools contained a mean 100 ATAR graduates with previous NAPLAN data from their school. Excluded were vocational students (mean=27) and any ATAR graduates without NAPLAN data (mean=20). Based on Index of Community Socio-Educational Access (ICSEA) prediction, all schools had larger that predicted proportions of their students graduating with ATARs. There were an additional 173 students not releasing their ATARs to their school (14%), requiring this data to be inferred by schools. Gain was established by first converting each student’s strongest NAPLAN domain to a statewide percentile, then subtracting this result from final ATAR. The resulting ‘percentile shift’ was corrected for plausible ATAR participation at each NAPLAN level. Strongest NAPLAN domain had the highest correlation with ATAR (R2=0.58). RESULTS School mean NAPLAN scores fitted ICSEA closely (R2=0.97). Schools achieved a mean cohort gain of two ATAR rankings, but only 66% of students gained. This ranged from 46% of top-NAPLAN decile students gaining, rising to 75% achieving gains outside the top decile. The 54% of top-decile students whose ATAR fell short of prediction lost a mean 4.0 percentiles (or 6.2 percentiles prior to correction for regression to the mean). 71% of students in smaller schools gained, compared to 63% in larger schools. NAPLAN variability in each of the 13 ICSEA1100 cohorts was 17%, with both intra-school and inter-school variation of these values extremely low (0.3% to 1.8%). Mean ATAR change between years in each school was just 1.1 ATAR ranks. This suggests consecutive school cohorts and ICSEA-similar schools share very similar distributions and outcomes over time. Quantile analysis of the NAPLAN/ATAR revealed heteroscedasticity, but splines offered little additional benefit over simple linear regression. The NAPLAN/ATAR R2 was 0.33. DISCUSSION Standardised data like NAPLAN and ATAR offer educators a simple no-cost progression metric to analyse performance in conjunction with their internal test results. Change is expressed in percentiles, or ATAR shift per student, which is layperson intuitive. Findings may also reduce ATAR/vocational stream mismatch, reveal proportions of cohorts meeting or falling short of expectation and demonstrate by how much. Finally, ‘crashed’ ATARs well below expectation are revealed, which schools can reasonably work to minimise. The percentile shift method is neither value-add nor a growth percentile. In the absence of exit NAPLAN testing, this metric is unable to discriminate academic gain from legitimate ATAR-maximizing strategies. But by controlling for ICSEA, ATAR proportion variation and student mobility, it uncovers progression to ATAR metrics which are not currently publicly available. However achieved, ATAR maximisation is a sought-after private good. So long as standardised nationwide data is available, this analysis offers useful analytics for educators and reasonable predictivity when counselling subsequent cohorts about their ATAR prospects.  

Keywords: NAPLAN, ATAR, analytics, measurement, gain, performance, data, percentile, value-added, high school, numeracy, reading comprehension, variability, regression to the mean

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2668 Environmental Impacts on Urban Agriculture in Algiers

Authors: Sara Bouzekri, Said Madani

Abstract:

In many Mediterranean cities such as Algiers, the human activity, the strong mobility the urban sprawl, the air pollution, the problems of waste management, the wasting of the resources and the degradation of the environment weaken in an unquestionable way the farming. The question of sustainable action vis-a-vis these threats arises then in order to maintain a level of desired local development. The methodology is based on a multi-criteria method based on the AFOM diagnosis, which classifies agricultural strength indicators and those of threat, according to an analytical approach. In a sustainable development perspective, it will be appropriate to link the threat factors of the case study with the factors of climate change to see their impact on the future of agriculture. This will be accompanied by a SWOT analysis, which crosses the most significant criteria to arrive at the necessary recommendations based on future projects for urban agriculture.

Keywords: Algiers, environment, urban agriculture, threat factors

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2667 Mechanical Characterization of Brain Tissue in Compression

Authors: Abbas Shafiee, Mohammad Taghi Ahmadian, Maryam Hoviattalab

Abstract:

The biomechanical behavior of brain tissue is needed for predicting the traumatic brain injury (TBI). Each year over 1.5 million people sustain a TBI in the USA. The appropriate coefficients for injury prediction can be evaluated using experimental data. In this study, an experimental setup on brain soft tissue was developed to perform unconfined compression tests at quasistatic strain rates ∈0.0004 s-1 and 0.008 s-1 and 0.4 stress relaxation test under unconfined uniaxial compression with ∈ 0.67 s-1 ramp rate. The fitted visco-hyperelastic parameters were utilized by using obtained stress-strain curves. The experimental data was validated using finite element analysis (FEA) and previous findings. Also, influence of friction coefficient on unconfined compression and relaxation test and effect of ramp rate in relaxation test is investigated. Results of the findings are implemented on the analysis of a human brain under high acceleration due to impact.

Keywords: brain soft tissue, visco-hyperelastic, finite element analysis (FEA), friction, quasistatic strain rate

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2666 Automated Machine Learning Algorithm Using Recurrent Neural Network to Perform Long-Term Time Series Forecasting

Authors: Ying Su, Morgan C. Wang

Abstract:

Long-term time series forecasting is an important research area for automated machine learning (AutoML). Currently, forecasting based on either machine learning or statistical learning is usually built by experts, and it requires significant manual effort, from model construction, feature engineering, and hyper-parameter tuning to the construction of the time series model. Automation is not possible since there are too many human interventions. To overcome these limitations, this article proposed to use recurrent neural networks (RNN) through the memory state of RNN to perform long-term time series prediction. We have shown that this proposed approach is better than the traditional Autoregressive Integrated Moving Average (ARIMA). In addition, we also found it is better than other network systems, including Fully Connected Neural Networks (FNN), Convolutional Neural Networks (CNN), and Nonpooling Convolutional Neural Networks (NPCNN).

Keywords: automated machines learning, autoregressive integrated moving average, neural networks, time series analysis

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2665 Flood Early Warning and Management System

Authors: Yogesh Kumar Singh, T. S. Murugesh Prabhu, Upasana Dutta, Girishchandra Yendargaye, Rahul Yadav, Rohini Gopinath Kale, Binay Kumar, Manoj Khare

Abstract:

The Indian subcontinent is severely affected by floods that cause intense irreversible devastation to crops and livelihoods. With increased incidences of floods and their related catastrophes, an Early Warning System for Flood Prediction and an efficient Flood Management System for the river basins of India is a must. Accurately modeled hydrological conditions and a web-based early warning system may significantly reduce economic losses incurred due to floods and enable end users to issue advisories with better lead time. This study describes the design and development of an EWS-FP using advanced computational tools/methods, viz. High-Performance Computing (HPC), Remote Sensing, GIS technologies, and open-source tools for the Mahanadi River Basin of India. The flood prediction is based on a robust 2D hydrodynamic model, which solves shallow water equations using the finite volume method. Considering the complexity of the hydrological modeling and the size of the basins in India, it is always a tug of war between better forecast lead time and optimal resolution at which the simulations are to be run. High-performance computing technology provides a good computational means to overcome this issue for the construction of national-level or basin-level flash flood warning systems having a high resolution at local-level warning analysis with a better lead time. High-performance computers with capacities at the order of teraflops and petaflops prove useful while running simulations on such big areas at optimum resolutions. In this study, a free and open-source, HPC-based 2-D hydrodynamic model, with the capability to simulate rainfall run-off, river routing, and tidal forcing, is used. The model was tested for a part of the Mahanadi River Basin (Mahanadi Delta) with actual and predicted discharge, rainfall, and tide data. The simulation time was reduced from 8 hrs to 3 hrs by increasing CPU nodes from 45 to 135, which shows good scalability and performance enhancement. The simulated flood inundation spread and stage were compared with SAR data and CWC Observed Gauge data, respectively. The system shows good accuracy and better lead time suitable for flood forecasting in near-real-time. To disseminate warning to the end user, a network-enabled solution is developed using open-source software. The system has query-based flood damage assessment modules with outputs in the form of spatial maps and statistical databases. System effectively facilitates the management of post-disaster activities caused due to floods, like displaying spatial maps of the area affected, inundated roads, etc., and maintains a steady flow of information at all levels with different access rights depending upon the criticality of the information. It is designed to facilitate users in managing information related to flooding during critical flood seasons and analyzing the extent of the damage.

Keywords: flood, modeling, HPC, FOSS

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2664 The Ontology of Assurance

Authors: Odd Ivar Haugen

Abstract:

This paper explores the ontology of assurance in safety-critical systems, emphasising the importance of knowledge and confidence in system behaviour. Assurance is defined as providing grounds for justified confidence in system properties, such as safety and security. The paper discusses the main concepts of assurance, including system requirements, confidence, and justification. It discusses the CESM metamodel for understanding system behaviour and emergent properties. The paper also highlights the importance of objectivity in assessing the strength of knowledge and the role of verification in generating evidence as a part of the argumentation. The assurance case is presented as a systematic way to represent knowledge and support decision-making.

Keywords: assurance, CESM metamodel, confidence, emergent properties, knowledge, objectivity, risk, system behaviour, system safety

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2663 Estimation of Fourier Coefficients of Flux Density for Surface Mounted Permanent Magnet (SMPM) Generators by Direct Search Optimization

Authors: Ramakrishna Rao Mamidi

Abstract:

It is essential for Surface Mounted Permanent Magnet (SMPM) generators to determine the performance prediction and analyze the magnet’s air gap flux density wave shape. The flux density wave shape is neither a pure sine wave or square wave nor a combination. This is due to the variation of air gap reluctance between the stator and permanent magnets. The stator slot openings and the number of slots make the wave shape highly complicated. To reduce the complexity of analysis, approximations are made to the wave shape using Fourier analysis. In contrast to the traditional integration method, the Fourier coefficients, an and bn, are obtained by direct search method optimization. The wave shape with optimized coefficients gives a wave shape close to the desired wave shape. Harmonics amplitudes are worked out and compared with initial values. It can be concluded that the direct search method can be used for estimating Fourier coefficients for irregular wave shapes.

Keywords: direct search, flux plot, fourier analysis, permanent magnets

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2662 The Maldistribution of Doctors and the Responsibility of Medical Education: A Literature Review

Authors: Catherine Bernard

Abstract:

The maldistribution of clinicians within countries is well documented. It is a common theme throughout the world that rural areas often struggle to recruit and retain health workers resulting in inadequate healthcare for many. This paper will concentrate on the responsibilities that medical schools may have in addressing this shortage of rural health workers. Recommendations are made with regards to targeted rural student admissions, rurally-based medical schools, rural clinical rotations and a curriculum orientated towards rural health issues. The evidence gathered suggests that individual factors are positive in encouraging health workers to practice in rural locations. However, there is strength in numbers, and combining all the recommendations will likely result in a synergistic effect, thereby increasing numbers of rural health workers and achieving accessible healthcare for those living in rural populations.

Keywords: medical education, medical education design, public health, rural health

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2661 Comparison of Silica-Filled Rubber Compound Prepared from Unmodified and Modified Silica

Authors: Thirawudh Pongprayoon, Watcharin Rassamee

Abstract:

Silica-filled natural rubber compounds were prepared from unmodified and surface-modified silica. The modified silica was coated by ultrathin film of polyisoprene by admicellar polymerization. FTIR and SEM were applied to characterize the modified silica. The cure, mechanic, and dynamics properties were investigated with the comparison of the compounds. Cure characterization of modified silica rubber compound was shorter than that of unmodified silica compound. Strength and abrasion resistance of modified silica compound were better than those of unmodified silica rubber compound. Wet grip and rolling resistance analyzed by DMA from tanδ at 0°C and 60°C using 5 Hz were also better than those of unmodified silica rubber compound.

Keywords: silica, admicellar polymerization, rubber compounds, mechanical properties, dynamic properties

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2660 Prediction of Structural Response of Reinforced Concrete Buildings Using Artificial Intelligence

Authors: Juan Bojórquez, Henry E. Reyes, Edén Bojórquez, Alfredo Reyes-Salazar

Abstract:

This paper addressed the use of Artificial Intelligence to obtain the structural reliability of reinforced concrete buildings. For this purpose, artificial neuronal networks (ANN) are developed to predict seismic demand hazard curves. In order to have enough input-output data to train the ANN, a set of reinforced concrete buildings (low, mid, and high rise) are designed, then a probabilistic seismic hazard analysis is made to obtain the seismic demand hazard curves. The results are then used as input-output data to train the ANN in a feedforward backpropagation model. The predicted values of the seismic demand hazard curves found by the ANN are then compared. Finally, it is concluded that the computer time analysis is significantly lower and the predictions obtained from the ANN were accurate in comparison to the values obtained from the conventional methods.

Keywords: structural reliability, seismic design, machine learning, artificial neural network, probabilistic seismic hazard analysis, seismic demand hazard curves

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2659 Determination of Elastic Constants for Scots Pine Grown in Turkey Using Ultrasound

Authors: Ergun Guntekin

Abstract:

This study investigated elastic constants of scots pine (Pinus sylvestris L.) grown in Turkey by means of ultrasonic waves. Three Young’s modulus, three shear modulus and six Poisson ratios were determined at constant moisture content (12 %). Three longitudinal and six shear wave velocities propagating along the principal axes of anisotropy, and additionally, three quasi-shear wave velocities at 45° with respect to the principal axes of anisotropy were measured using EPOCH 650 ultrasonic flaw detector. The measured average longitudinal wave velocities for the sapwood in L, R, T directions were 4795, 1713 and 1117 m/s, respectively. The measured average shear wave velocities ranged from 682 to 1382 m/s. The measured quasi-shear wave velocities varied between 642 and 1280 m/s. The calculated average modulus of elasticity values for the sapwood in L, R, T directions were 11913, 1565 and 663 N/mm2, respectively. The calculated shear modulus in LR, LT and RT planes were 1031, 541, 415 N/mm2. Comparing with available literature, the predicted elastic constants are acceptable.

Keywords: elastic constants, prediction, Scots pine, ultrasound

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2658 Comparison of the Effect of Nano Calcium Carbonate and CaCO₃ on Egg Production, Egg Traits and Calcium Retention in Laying Japanese Quail

Authors: Farhad Ahmadi, Hammed Kimiaee

Abstract:

Context: This research study focuses on the effect of different levels and sources of calcium on egg production, egg traits, and calcium retention in laying Japanese quail. The study aims to determine the impact of nano calcium carbonate (NCC) and calcium carbonate (CC) on these factors. Research Aim: The main objective of this research is to investigate the effect of different levels and sources of calcium on egg production, egg traits, and calcium retention in laying Japanese quail. Specifically, the study aims to compare the effects of NCC and CC on these parameters. Methodology: The research was conducted using a total of 280 laying quail with an average age of 8 weeks. The quails were randomly distributed in a completely randomized design (CRD) with 7 treatments, 4 replications, and 10 quails in each pen. The study lasted for 90 days. The experimental diets included a control group (T1) with a basal diet consisting of 3.17% CaCO₃, and other groups supplemented with different levels (0.5%, 0.1%, and 0.15%) of either calcium carbonate (CC) or nano calcium carbonate (NCC). The quails had free access to water and feed throughout the study period. Findings: The results of the study showed that NCC at the levels of 0.1% and 0.15% (T6 and T7) improved eggshell thickness, shell thickness, and shell breaking strength compared to the control group. Although not statistically significant, there was an increasing trend in quail egg production and calcium retention in the calcareous shell of the egg in birds that consumed the experimental diets containing different levels of NCC compared to the control and other treatment groups. Theoretical Importance: This research contributes to our understanding of the effect of NCC and CC on egg production, egg traits, and calcium retention in laying Japanese quail. It highlights the potential benefits of using NCC as a calcium source in quail diets, specifically in improving the quantity and quality of eggs and calcium retention. Data Collection and Analysis Procedures: Quail egg production was recorded monthly for each treatment group. At the end of the study, a total of 40 eggs (10 eggs/replicate) from each treatment group were randomly selected for analysis. Parameters such as eggshell thickness, shell thickness, shell breaking strength, and calcium retention were measured. Statistical analysis was performed to compare the results between the different treatment groups. Questions Addressed: This research aimed to answer the following questions: What is the effect of different levels and sources of calcium on egg production, egg traits, and calcium retention in laying Japanese quail? How does nano calcium carbonate compare to calcium carbonate in terms of these parameters? Conclusion: In conclusion, this study suggests that NCC at the levels of 0.1% and 0.15% can improve the quantity and quality of eggs and calcium retention in laying Japanese quail. These findings highlight the potential benefits of using NCC as a calcium source in quail diets. Further research could be conducted to explore the mechanisms behind these improvements and optimize the dosage of NCC for maximum effect.

Keywords: egg, calcium, nanoparticles, retention

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2657 Representative Concentration Pathways Approach on Wolbachia Controlling Dengue Virus in Aedes aegypti

Authors: Ida Bagus Mandhara Brasika, I Dewa Gde Sathya Deva

Abstract:

Wolbachia is recently developed as the natural enemy of Dengue virus (DENV). It inhibits the replication of DENV in Aedes aegypti. Both DENV and its vector, Aedes aegypty, are sensitive to climate factor especially temperature. The changing of climate has a direct impact on temperature which means changing the vector transmission. Temperature has been known to effect Wolbachia density as it has an ideal temperature to grow. Some scenarios, which are known as Representative Concentration Pathways (RCPs), have been developed by Intergovernmental Panel on Climate Change (IPCC) to predict the future climate based on greenhouse gases concentration. These scenarios are applied to mitigate the future change of Aedes aegypti migration and how Wolbachia could control the virus. The prediction will determine the schemes to release Wolbachia-injected Aedes aegypti to reduce DENV transmission.

Keywords: Aedes aegypti, climate change, dengue virus, Intergovernmental Panel on Climate Change, representative concentration pathways, Wolbachia

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2656 Femtocell Stationed Flawless Handover in High Agility Trains

Authors: S. Dhivya, M. Abirami, M. Farjana Parveen, M. Keerthiga

Abstract:

The development of high-speed railway makes people’s lives more and more convenient; meanwhile, handover is the major problem on high-speed railway communication services. In order to overcome that drawback the architecture of Long-Term Evolution (LTE) femtocell networks is used to improve network performance, and the deployment of a femtocell is a key for bandwidth limitation and coverage issues in conventional mobile network system. To increase the handover performance this paper proposed a multiple input multiple output (MIMO) assisted handoff (MAHO) algorithm. It is a technique used in mobile telecom to transfer a mobile phone to a new radio channel with stronger signal strength and improved channel quality.

Keywords: flawless handover, high-speed train, home evolved Node B, LTE, mobile femtocell, RSS

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2655 Properties Optimization of Keratin Films Produced by Film Casting and Compression Moulding

Authors: Mahamad Yousif, Eoin Cunningham, Beatrice Smyth

Abstract:

Every year ~6 million tonnes of feathers are produced globally. Due to feathers’ low density and possible contamination with pathogens, their disposal causes health and environmental problems. The extraction of keratin, which represents >90% of feathers’ dry weight, could offer a solution due to its wide range of applications in the food, medical, cosmetics, and biopolymer industries. One of these applications is the production of biofilms which can be used for packaging, edible films, drug delivery, wound healing etc. Several studies in the last two decades investigated keratin film production and its properties. However, the effects of many parameters on the properties of the films remain to be investigated including the extraction method, crosslinker type and concentration, and the film production method. These parameters were investigated in this study. Keratin was extracted from chicken feathers using two methods, alkaline extraction with 0.5 M NaOH at 80 °C or sulphitolysis extraction with 0.5 M sodium sulphite, 8 M urea, and 0.25-1 g sodium dodecyl sulphate (SDS) at 100 °C. The extracted keratin was mixed with different types and concentrations of plasticizers (glycerol and polyethylene glycol) and crosslinkers (formaldehyde (FA), glutaraldehyde, cinnamaldehyde, glyoxal, and 1,4-Butanediol diglycidyl ether (BDE)). The mixtures were either cast in a mould or compression moulded to produce films. For casting, keratin powder was initially dissolved in water to form a 5% keratin solution and the mixture was dried in an oven at 60 °C. For compression moulding, 10% water was added and the compression moulding temperature and pressure were in the range of 60-120 °C and 10-30 bar. Finally, the tensile properties, solubility, and transparency of the films were analysed. The films prepared using the sulphitolysis keratin had superior tensile properties to the alkaline keratin and formed successfully with lower plasticizer concentrations. Lowering the SDS concentration from 1 to 0.25 g/g feathers improved all the tensile properties. All the films prepared without crosslinkers were 100% water soluble but adding crosslinkers reduced solubility to as low as 21%. FA and BDE were found to be the best crosslinkers increasing the tensile strength and elongation at break of the films. Higher compression moulding temperature and pressure lowered the tensile properties of the films; therefore, 80 °C and 10 bar were considered to be the optimal compression moulding temperature and pressure. Nevertheless, the films prepared by casting had higher tensile properties than compression moulding but were less transparent. Two optimal films, prepared by film casting, were identified and their compositions were: (a) Sulphitolysis keratin, 20% glycerol, 10% FA, and 10% BDE. (b) Sulphitolysis keratin, 20% glycerol, and 10% BDE. Their tensile strength, elongation at break, Young’s modulus, solubility, and transparency were: (a) 4.275±0.467 MPa, 86.12±4.24%, 22.227±2.711 MPa, 21.34±1.11%, and 8.57±0.94* respectively. (b) 3.024±0.231 MPa, 113.65±14.61%, 10±1.948 MPa, 25.03±5.3%, and 4.8±0.15 respectively. A higher value indicates that the film is less transparent. The extraction method, film composition, and production method had significant influence on the properties of keratin films and should therefore be tailored to meet the desired properties and applications.

Keywords: compression moulding, crosslinker, film casting, keratin, plasticizer, solubility, tensile properties, transparency

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2654 Experimental Networks Synchronization of Chua’s Circuit in Different Topologies

Authors: Manuel Meranza-Castillon, Rolando Diaz-Castillo, Adrian Arellano-Delgado, Cesar Cruz-Hernandez, Rosa Martha Lopez-Gutierrez

Abstract:

In this work, we deal with experimental network synchronization of chaotic nodes with different topologies. Our approach is based on complex system theory, and we use a master-slave configuration to couple the nodes in the networks. In particular, we design and implement electronically complex dynamical networks composed by nine coupled chaotic Chua’s circuits with topologies: in nearest-neighbor, small-world, open ring, star, and global. Also, network synchronization is evaluated according to a particular coupling strength for each topology. This study is important by the possible applications to private transmission of information in a chaotic communication network of multiple users.

Keywords: complex networks, Chua's circuit, experimental synchronization, multiple users

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2653 Bending and Shear Characteristics of Hollowcore Slab with Polystyrene Forms

Authors: Kang Kun Lee

Abstract:

New I-slab system with polystyrene forms and precast concrete deck is proposed to reduce the construction period and the self-weight of the slab. This paper presents experimental works on the bending and shear of the I-slabs. Five specimens were tested. The main parameters of experiments are diameters of the holes made by polystyrene form and the thickness of slab. Structural performance of I-slab is evaluated on the basis of failure mode, load-displacement curve, and ultimate strengths. Based on the test results, it is found that the critical punching shear sections are changed as the test variables are different, hence resulting in the varied punching shear strengths. Test results indicate that the developed I-slab is very effective to increase the strength due to self-weight reduction.

Keywords: hollowcore slab, section force-deformation response, precast concrete deck

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2652 A Dynamic Approach for Evaluating the Climate Change Risks on Building Performance

Authors: X. Lu, T. Lu, S. Javadi

Abstract:

A simple dynamic approach is presented for analyzing thermal and moisture dynamics of buildings, which is of particular relevance to understanding climate change impacts on buildings, including assessment of risks and applications of resilience strategies. With the goal to demonstrate the proposed modeling methodology, to verify the model, and to show that wooden materials provide a mechanism that can facilitate the reduction of moisture risks and be more resilient to global warming, a wooden church equipped with high precision measurement systems was taken as a test building for full-scale time-series measurements. Sensitivity analyses indicate a high degree of accuracy in the model prediction regarding the indoor environment. The model is then applied to a future projection of climate indoors aiming to identify significant environmental factors, the changing temperature and humidity, and effective response to the climate change impacts. The paper suggests that wooden building materials offer an effective and resilient response to anticipated future climate changes.

Keywords: dynamic model, forecast, climate change impact, wooden structure, buildings

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2651 Hexagonal Honeycomb Sandwich Plate Optimization Using Gravitational Search Algorithm

Authors: A. Boudjemai, A. Zafrane, R. Hocine

Abstract:

Honeycomb sandwich panels are increasingly used in the construction of space vehicles because of their outstanding strength, stiffness and light weight properties. However, the use of honeycomb sandwich plates comes with difficulties in the design process as a result of the large number of design variables involved, including composite material design, shape and geometry. Hence, this work deals with the presentation of an optimal design of hexagonal honeycomb sandwich structures subjected to space environment. The optimization process is performed using a set of algorithms including the gravitational search algorithm (GSA). Numerical results are obtained and presented for a set of algorithms. The results obtained by the GSA algorithm are much better compared to other algorithms used in this study.

Keywords: optimization, gravitational search algorithm, genetic algorithm, honeycomb plate

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2650 Kinematic Hardening Parameters Identification with Respect to Objective Function

Authors: Marina Franulovic, Robert Basan, Bozidar Krizan

Abstract:

Constitutive modelling of material behaviour is becoming increasingly important in prediction of possible failures in highly loaded engineering components, and consequently, optimization of their design. In order to account for large number of phenomena that occur in the material during operation, such as kinematic hardening effect in low cycle fatigue behaviour of steels, complex nonlinear material models are used ever more frequently, despite of the complexity of determination of their parameters. As a method for the determination of these parameters, genetic algorithm is good choice because of its capability to provide very good approximation of the solution in systems with large number of unknown variables. For the application of genetic algorithm to parameter identification, inverse analysis must be primarily defined. It is used as a tool to fine-tune calculated stress-strain values with experimental ones. In order to choose proper objective function for inverse analysis among already existent and newly developed functions, the research is performed to investigate its influence on material behaviour modelling.

Keywords: genetic algorithm, kinematic hardening, material model, objective function

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2649 Stress Analysis of Hexagonal Element for Precast Concrete Pavements

Authors: J. Novak, A. Kohoutkova, V. Kristek, J. Vodicka, M. Sramek

Abstract:

While the use of cast-in-place concrete for an airfield and highway pavement overlay is very common, the application of precast concrete elements is very limited today. The main reasons consist of high production costs and complex structural behavior. Despite that, several precast concrete systems have been developed and tested with the aim to provide a system with rapid construction. The contribution deals with the reinforcement design of a hexagonal element developed for a proposed airfield pavement system. The sub-base course of the system is composed of compacted recycled concrete aggregates and fiber reinforced concrete with recycled aggregates place on top of it. The selected element belongs to a group of precast concrete elements which are being considered for the construction of a surface course. Both high costs of full-scale experiments and the need to investigate various elements force to simulate their behavior in a numerical analysis software by using finite element method instead of performing expensive experiments. The simulation of the selected element was conducted on a nonlinear model in order to obtain such results which could fully compensate results from experiments. The main objective was to design reinforcement of the precast concrete element subject to quasi-static loading from airplanes with respect to geometrical imperfections, manufacturing imperfections, tensile stress in reinforcement, compressive stress in concrete and crack width. The obtained findings demonstrate that the position and the presence of imperfection in a pavement highly affect the stress distribution in the precast concrete element. The precast concrete element should be heavily reinforced to fulfill all the demands. Using under-reinforced concrete elements would lead to the formation of wide cracks and cracks permanently open.

Keywords: imperfection, numerical simulation, pavement, precast concrete element, reinforcement design, stress analysis

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2648 An Experimental Investigation on the Droplet Behavior Impacting a Hot Surface above the Leidenfrost Temperature

Authors: Khaleel Sami Hamdan, Dong-Eok Kim, Sang-Ki Moon

Abstract:

An appropriate model to predict the size of the droplets resulting from the break-up with the structures will help in a better understanding and modeling of the two-phase flow calculations in the simulation of a reactor core loss-of-coolant accident (LOCA). A droplet behavior impacting on a hot surface above the Leidenfrost temperature was investigated. Droplets of known size and velocity were impacted to an inclined plate of hot temperature, and the behavior of the droplets was observed by a high-speed camera. It was found that for droplets of Weber number higher than a certain value, the higher the Weber number of the droplet the smaller the secondary droplets. The COBRA-TF model over-predicted the measured secondary droplet sizes obtained by the present experiment. A simple model for the secondary droplet size was proposed using the mass conservation equation. The maximum spreading diameter of the droplets was also compared to previous correlations and a fairly good agreement was found. A better prediction of the heat transfer in the case of LOCA can be obtained with the presented model.

Keywords: break-up, droplet, impact, inclined hot plate, Leidenfrost temperature, LOCA

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2647 Neural Network Approaches for Sea Surface Height Predictability Using Sea Surface Temperature

Authors: Luther Ollier, Sylvie Thiria, Anastase Charantonis, Carlos E. Mejia, Michel Crépon

Abstract:

Sea Surface Height Anomaly (SLA) is a signature of the sub-mesoscale dynamics of the upper ocean. Sea Surface Temperature (SST) is driven by these dynamics and can be used to improve the spatial interpolation of SLA fields. In this study, we focused on the temporal evolution of SLA fields. We explored the capacity of deep learning (DL) methods to predict short-term SLA fields using SST fields. We used simulated daily SLA and SST data from the Mercator Global Analysis and Forecasting System, with a resolution of (1/12)◦ in the North Atlantic Ocean (26.5-44.42◦N, -64.25–41.83◦E), covering the period from 1993 to 2019. Using a slightly modified image-to-image convolutional DL architecture, we demonstrated that SST is a relevant variable for controlling the SLA prediction. With a learning process inspired by the teaching-forcing method, we managed to improve the SLA forecast at five days by using the SST fields as additional information. We obtained predictions of a 12 cm (20 cm) error of SLA evolution for scales smaller than mesoscales and at time scales of 5 days (20 days), respectively. Moreover, the information provided by the SST allows us to limit the SLA error to 16 cm at 20 days when learning the trajectory.

Keywords: deep-learning, altimetry, sea surface temperature, forecast

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2646 The Affect of Ethnic Minority People: A Prediction by Gender and Marital Status

Authors: A. K. M. Rezaul Karim, Abu Yusuf Mahmud, S. H. Mahmud

Abstract:

The study aimed to investigate whether the affect (experience of feeling or emotion) of ethnic minority people can be predicted by gender and marital status. Toward this end, positive affect and negative affect of 103 adult indigenous persons were measured. Analysis of data in multiple regressions demonstrated that both gender and marital status are significantly associated with positive affect (Gender: β=.318, p < .001; Marital status: β=.201, p < .05), but not with negative affect. Results indicated that the indigenous males have 0.32 standard deviations increased positive affect as compared to the indigenous females and that married individuals have 0.20 standard deviations increased positive affect as compared to their unmarried counterparts. These findings advance our understanding that gender and marital status inequalities in the experience of emotion are not specific to the mainstream society; rather it is a generalized picture of all societies. In general, men possess more positive affect than females; married persons possess more positive affect than the unmarried persons.

Keywords: positive affect, negative affect, ethnic minority, gender, marital status

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2645 Utilization of Coconut Husk and Sugarcane Bagasse as a Natural Component in Making Water Resistance Tote Bags

Authors: Cyril Mae B. Mationg, Alexa T. Belizar, Vethany B. Bellen

Abstract:

This study aims to determine the use of coconut husks and sugarcane bagasse as natural components in making water-resistant tote bags. The study consists of three concentrations: 70% Coconut Husk - 30% Sugarcane Bagasse, 70% cellulose, and 30% cellulose. The results of these tests revealed that, out of the three concentration concentrations, the one consisting of 70% Coconut Husk and 30% sugarcane bagasse exhibited superior performance in breaking capacity and water penetration. During tensile strength testing, the coconut husk and sugarcane bagasse withstood a force of 207.7 Newtons (N) in the machine direction and 216.5 N in the cross-machine direction.

Keywords: coconut husk, sugarcane bagasse, tote bags, water resistance

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2644 The Resource-Base View of Organization and Innovation: Recognition of Significant Relationship in an Organization

Authors: Francis Deinmodei W. Poazi, Jasmine O. Tamunosiki-Amadi, Maurice Fems

Abstract:

In recent times the resource-based view (RBV) of strategic management has recorded a sizeable attention yet there has not been a considerable scholarly and managerial discourse, debate and attention. As a result, this paper gives special bit of critical reasoning as well as top-notch analyses and relationship between RBV and organizational innovation. The study examines those salient aspects of RBV that basically have the will power in ensuring the organization's capacity to go for innovative capability. In achieving such fit and standpoint, the paper joins other relevant academic discourse and empirical evidence. To this end, a reasonable amount of contributions in setting the ground running for future empirical researches would have been provided. More so, the study is guided and built on the following strength and significance: Firstly, RBV sees resources as heterogeneity which forms a strong point of strength and allows organisations to gain competitive advantage. In order words, competitive advantage can be achieved or delivered to the organization when resources are distinctively utilized in a valuable manner more than the envisaged competitors of the organization. Secondly, RBV is significantly influential in determining the real resources that are available in the organization with a view to locate capabilities within in order to attract more profitability into the organization when applied. Thus, there will be more sustainable growth and success in the ever competitive and emerging market. Thus, to have succinct description of the basic methodologies, the study adopts both qualitative as well as quantitative approach with a view to have a broad samples of opinion in establishing and identifying key and strategic organizational resources to enable managers of resources to gain a competitive advantage as well as generating a sustainable increase and growth in profit. Furthermore, a comparative approach and analysis was used to examine the performance of RBV within the organization. Thus, the following are some of the findings of the study: it is clear that there is a nexus between RBV and growth of competitively viable organizations. More so, in most parts, organizations have heterogeneous resources domiciled in their organizations but not all organizations as it was specifically and intelligently adopting the tenets of RBV to strengthen heterogeneity of resources which allows organisations to gain competitive advantage. Other findings of this study reveal that of managerial perception of RBV with respect to application and transformation of resources to achieve a profitable end. It is against this backdrop, the importance of RBV cannot be overemphasized; the study is strongly convinced and think that RBV view is one focal and distinct approach that is focused on internal to outside strategy which engenders sourcing or generating resources internally as well as having the quest to apply such internally sourced resources diligently to increase or gain competitive advantage.

Keywords: resource-based view, innovation, organisation, recognition significant relationship and theoretical perspective

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2643 An Analytical Survey of Construction Changes: Gaps and Opportunities

Authors: Ehsan Eshtehardian, Saeed Khodaverdi

Abstract:

This paper surveys the studies on construction change and reveals some of the potential future works. A full-scale investigation of change literature, including change definitions, types, causes and effects, and change management systems, is accomplished to explore some of the coming change trends. It is tried to pick up the critical works in each section to deduct a true timeline of construction changes. The findings show that leaping from best practice guides in late 1990s and generic process models in the early 2000s to very advanced modeling environments in the mid-2000s and the early 2010s have made gaps along with opportunities for change researchers in order to develop some more easy and applicable models. Another finding is that there is a compelling similarity between the change and risk prediction models. Therefore, integrating these two concepts, specifically from proactive management point of view, may lead to a synergy and help project teams avoid rework. Also, the findings show that exploitation of cause-effect relationship models, in order to facilitate the dispute resolutions, seems to be an interesting field for future works.

Keywords: construction change, change management systems, dispute resolutions, change literature

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2642 Developing an Accurate AI Algorithm for Histopathologic Cancer Detection

Authors: Leah Ning

Abstract:

This paper discusses the development of a machine learning algorithm that accurately detects metastatic breast cancer (cancer has spread elsewhere from its origin part) in selected images that come from pathology scans of lymph node sections. Being able to develop an accurate artificial intelligence (AI) algorithm would help significantly in breast cancer diagnosis since manual examination of lymph node scans is both tedious and oftentimes highly subjective. The usage of AI in the diagnosis process provides a much more straightforward, reliable, and efficient method for medical professionals and would enable faster diagnosis and, therefore, more immediate treatment. The overall approach used was to train a convolution neural network (CNN) based on a set of pathology scan data and use the trained model to binarily classify if a new scan were benign or malignant, outputting a 0 or a 1, respectively. The final model’s prediction accuracy is very high, with 100% for the train set and over 70% for the test set. Being able to have such high accuracy using an AI model is monumental in regard to medical pathology and cancer detection. Having AI as a new tool capable of quick detection will significantly help medical professionals and patients suffering from cancer.

Keywords: breast cancer detection, AI, machine learning, algorithm

Procedia PDF Downloads 91