Search results for: steel frame ground structure optimization

Authors: B. Bouadjemi, S. Bentata, W. Benstaali, A. Souidi, A. Abbad, T. Lantri, Z. Aziz, A. Zitouni

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The electronic and magnetic structures of double perovskite Ba2MnMoO6 are systematically investigated using the first principle method of the Full Potential Linear Augmented Plane Waves Plus the Local Orbitals (FP-LAPW+LO) within the Local Spin Density Approximation (LSDA) and the Generalized Gradient Approximation (GGA). In order to take into account the strong on-site Coulomb interaction, we included the Hubbard correlation terms: LSDA+U and GGA+U approaches. Whereas half-metallic ferromagnetic character is observed due to dominant Mn spin-up and Mo spin-down contributions insulating ground state is obtained. The LSDA+U and GGA+U calculations yield better agreement with the theoretical and the experimental results than LSDA and GGA do.

Keywords: electronic structure, double perovskite, first principles, Ba2MnMoO6, half-metallic

Procedia PDF Downloads 441

Authors: Zahra Abdolkarimi, Naser Zourikalatehsamad,

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Up to 40 years ago, after recognition of epilepsy, it was generally believed that these attacks occurred randomly and suddenly. However, thanks to the advance of mathematics and engineering, such attacks can be predicted within a few minutes or hours. In this way, various algorithms for long-term prediction of the time and frequency of the first attack are presented. In this paper, by considering the nonlinear nature of brain signals and dynamic recorded brain signals, ANFIS model is presented to predict the brain signals, since according to physiologic structure of the onset of attacks, more complex neural structures can better model the signal during attacks. Contribution of this work is the co-evolution algorithm for optimization of ANFIS network parameters. Our objective is to predict brain signals based on time series obtained from brain signals of the people suffering from epilepsy using ANFIS. Results reveal that compared to other methods, this method has less sensitivity to uncertainties such as presence of noise and interruption in recorded signals of the brain as well as more accuracy. Long-term prediction capacity of the model illustrates the usage of planted systems for warning medication and preventing brain signals.

Keywords: co-evolution algorithms, brain signals, time series, neural networks, ANFIS model, physiologic structure, time prediction, epilepsy suffering, illustrates model

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Authors: Lokendra Kumar Devangan, Ajay Mishra

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This paper describes the implementation of a large-scale SAS/OR model with significant pre-processing, scenario analysis, and post-processing work done using SAS. A large cement manufacturer with ten geographically distributed manufacturing plants for two variants of cement, around 400 warehouses serving as transshipment points, and several thousand distributor locations generating demand needed to optimize this multi-echelon, multi-modal transport supply chain separately for planning and allocation purposes. For monthly planning as well as daily allocation, the demand is deterministic. Rail and road networks connect any two points in this supply chain, creating tens of thousands of such connections. Constraints include the plant’s production capacity, transportation capacity, and rail wagon batch size constraints. Each demand point has a minimum and maximum for shipments received. Price varies at demand locations due to local factors. A large mixed integer programming model built using proc OPTMODEL decides production at plants, demand fulfilled at each location, and the shipment route to demand locations to maximize the profit contribution. Using base SAS, we did significant pre-processing of data and created inputs for the optimization. Using outputs generated by OPTMODEL and other processing completed using base SAS, we generated several reports that went into their enterprise system and created tables for easy consumption of the optimization results by operations.

Keywords: production planning, mixed integer optimization, network model, network optimization

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Authors: Haifa Saleh, Kamiran Abduka, Robin Kalfat, Riadh Al-Mahaidi

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The effectiveness of using pre-stressing steel bars for shear strengthening of high strength reinforced concrete (RC) slabs was assessed. Two large-scale RC slabs were tested, one without shear reinforcement and the second strengthened against punching shear failure using pre-stressing steel bars. The two slabs had the same dimensions, flexural reinforcement ratio, loading and support arrangements. The experimental program including the method of strengthening, set up and instrumentation are described in this paper. The experimental results are analyzed and discussed in terms of the structural behavior of the RC slabs, the performance of pre-stressing steel bolts and failure modes. The results confirmed that the shear strengthening technique increased the shear capacity, ductility and yield capacity of the slab by up to 15%, 44%, and 22%, respectively compared to the unstrengthened slab. The strengthening technique also successfully contributed to changing the failure mode from a brittle punching shear mode to ductile flexural failure mode. Vic3D digital image correlation system (photogrammetry) was also used in this research. This technique holds several advantages over traditional contact instrumentations including that it is inexpensive, it produces results that are simple to analyze and it is remote visualization technique. The displacement profile along the span of the slab and rotation has been found and compared with the results obtained from traditional sensors. The performance of the photogrammetry technique was very good and the results of both measurements were in very close agreement.

Keywords: flat slab, photogrammetry, punching shear, strengthening

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Authors: Rebecca Hafner, Daniel Read, David Elmes

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The persuasive potential of normative and feedback (financial vs. environmental) information in ‘nudging’ people towards making environmentally sound decisions was explored in a hypothetical choice experiment. The research was specifically focused on determining how subtle variations in the decision frame could be used to increase the selection of energy efficient vs. standard technologies, using the context of home heating choice. Participants were given a choice of a standard heating system (a gas boiler) and a relatively more-energy efficient option (a heat pump). The experiment had a 2 (normative vs. no normative information) by 3 feedback type (financial, environmental, none) design. The last group constituted the control. Half of the participants were given normative information about what the majority of others in their neighbourhood had opted to do when faced with the same choice set, prior to making their decision. The other half received no such information. Varying feedback frames were incorporated by providing participants with information on either financial or environmental savings that could be achieved by choosing the heat pump. No such information was provided in the control group. A significant interaction was found between normative information and feedback frame type. Specifically, the impact of feedback frames was found to be reduced when normative information was provided; illustrating the overriding influence of normative information on option preference. Participants were significantly more likely to select the heat pump if they were vs. were not given normative information. Yet when no normative information was provided, the persuasive influence of the financial frame was increased – highlighting this as an effective means of encouraging uptake of new technologies in this instance. Conversely, the environmental frame was not found to differ significantly from the control. Marginal carryover effects were also found for stated future real-life decision-making behaviour, with participants who were versus were not given normative information being marginally more likely to state they would consider installing a heat pump when they next need to replace their heating system in real life. We conclude that normative and financial feedback framing techniques are highly effective in increasing uptake of new, energy efficient heating technologies involving significant upfront financial outlay. The implications for researchers looking to promote ‘green’ choice in the context of new technology adoption are discussed.

Keywords: energy-efficient technology adoption, environmental decision making, financial vs. environmental feedback framing techniques, social norms

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Authors: Sabina-Adriana Floria, Marius Gavrilescu, Florin Leon, Silvia Curteanu, Costel Anton

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Neuroevolution is a subfield of artificial intelligence used to solve various problems in different application areas. Specifically, neuroevolution is a technique that applies biologically inspired methods to generate neural network architectures and optimize their parameters automatically. In this paper, we use different biologically inspired optimization algorithms in an ensemble strategy with the aim of training multilayer perceptron neural networks, resulting in regression models used to simulate the industrial chemical process of obtaining bricks from silicone-based materials. Installations in the raw ceramics industry, i.e., bricks, are characterized by significant energy consumption and large quantities of emissions. In addition, the initial conditions that were taken into account during the design and commissioning of the installation can change over time, which leads to the need to add new mixes to adjust the operating conditions for the desired purpose, e.g., material properties and energy saving. The present approach follows the study by simulation of a process of obtaining bricks from silicone-based materials, i.e., the modeling and optimization of the process. Optimization aims to determine the working conditions that minimize the emissions represented by nitrogen monoxide. We first use a search procedure to find the best values for the parameters of various biologically inspired optimization algorithms. Then, we propose an adaptive ensemble strategy that uses only a subset of the best algorithms identified in the search stage. The adaptive ensemble strategy combines the results of selected algorithms and automatically assigns more processing capacity to the more efficient algorithms. Their efficiency may also vary at different stages of the optimization process. In a given ensemble iteration, the most efficient algorithms aim to maintain good convergence, while the less efficient algorithms can improve population diversity. The proposed adaptive ensemble strategy outperforms the individual optimizers and the non-adaptive ensemble strategy in convergence speed, and the obtained results provide lower error values.

Keywords: optimization, biologically inspired algorithm, neuroevolution, ensembles, bricks, emission minimization

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Authors: A. A. Behroozpoor, M. M. Mazarei

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In this paper, a fuzzy recurrent neural network is proposed for solving the classical quadratic control problem subject to linear equality and bound constraints. The convergence of the state variables of the proposed neural network to achieve solution optimality is guaranteed.

Keywords: REFERENCES [1] Xia, Y, A new neural network for solving linear and quadratic programming problems. IEEE Transactions on Neural Networks, 7(6), 1996, pp.1544–1548. [2] Xia, Y., & Wang, J, A recurrent neural network for solving nonlinear convex programs subject to linear constraints. IEEE Transactions on Neural Networks, 16(2), 2005, pp. 379–386. [3] Xia, Y., H, Leung, & J, Wang, A projection neural network and its application to constrained optimization problems. IEEE Transactions Circuits and Systems-I, 49(4), 2002, pp.447–458.B. [4] Q. Liu, Z. Guo, J. Wang, A one-layer recurrent neural network for constrained seudoconvex optimization and its application for dynamic portfolio optimization. Neural Networks, 26, 2012, pp. 99-109.

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Authors: Sani M. Lawal, Idris Musa, Aliyu D. Usman

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The Pareto approach of optimal solutions in a search space that evolved in multi-objective optimization problems is adopted in this paper, which stands for a set of solutions in the search space. This paper aims at presenting an optimal placement of Distributed Generation (DG) in radial distribution networks with an optimal size for minimization of power loss and voltage deviation as well as maximizing voltage profile of the networks. And these problems are formulated using particle swarm optimization (PSO) as a constraint nonlinear optimization problem with both locations and sizes of DG being continuous. The objective functions adopted are the total active power loss function and voltage deviation function. The multiple nature of the problem, made it necessary to form a multi-objective function in search of the solution that consists of both the DG location and size. The proposed PSO algorithm is used to determine optimal placement and size of DG in a distribution network. The output indicates that PSO algorithm technique shows an edge over other types of search methods due to its effectiveness and computational efficiency. The proposed method is tested on the standard IEEE 34-bus and validated with 33-bus test systems distribution networks. Results indicate that the sizing and location of DG are system dependent and should be optimally selected before installing the distributed generators in the system and also an improvement in the voltage profile and power loss reduction have been achieved.

Keywords: distributed generation, pareto, particle swarm optimization, power loss, voltage deviation

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Authors: Manuela Villani, Anila Xhahysa, Christopher Brooks, Marco Pagani

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The geological structure of Western Balkans is strongly affected by the collision between Adria microplate and the southwestern Euroasia margin, resulting in a considerably active seismic region. The Harmonization of Seismic Hazard Maps in the Western Balkan Countries Project (BSHAP) (2007-2011, 2012-2015) by NATO supported the preparation of new seismic hazard maps of the Western Balkan, but when inspecting the seismic hazard models produced later by these countries on a national scale, significant differences in design PGA values are observed in the border, for instance, North Albania-Montenegro, South Albania- Greece, etc. Considering the fact that the catalogues were unified and seismic sources were defined within BSHAP framework, obviously, the differences arise from the Ground Motion Prediction Equations selection, which are generally the component with highest impact on the seismic hazard assessment. At the time of the project, a modest database was present, namely 672 three-component records, whereas nowadays, this strong motion database has increased considerably up to 20,939 records with Mw ranging in the interval 3.7-7 and epicentral distance distribution from 0.47km to 490km. Statistical analysis of the strong motion database showed the lack of recordings in the moderate-to-large magnitude and short distance ranges; therefore, there is need to re-evaluate the Ground Motion Prediction Equation in light of the recently updated database and the new generations of GMMs. In some cases, it was observed that some events were more extensively documented in one database than the other, like the 1979 Montenegro earthquake, with a considerably larger number of records in the BSHAP Analogue SM database when compared to ESM23. Therefore, the strong motion flat-file provided from the Harmonization of Seismic Hazard Maps in the Western Balkan Countries Project was merged with the ESM23 database for the polygon studied in this project. After performing the preliminary residual analysis, the candidate GMPE-s were identified. This process was done using the GMPE performance metrics available within the SMT in the OpenQuake Platform. The Likelihood Model and Euclidean Distance Based Ranking (EDR) were used. Finally, for this study, a GMPE logic tree was selected and following the selection of candidate GMPEs, model weights were assigned using the average sample log-likelihood approach of Scherbaum.

Keywords: residual analysis, GMPE, western balkan, strong motion, openquake

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Authors: Yasser Aldali

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The scope of this paper is to evaluate and compare the potential of LS-PV (Large Scale Photovoltaic Power Plant) power generation systems in the southern region of Libya at Al-Kufra for both stationary and tracking systems. A Microsoft Excel-VBA program has been developed to compute slope radiation, dew-point, sky temperature, and then cell temperature, maximum power output and module efficiency of the system for stationary system and for tracking system. The results for energy production show that the total energy output is 114GWh/year for stationary system and 148 GWh/year for tracking system. The average module efficiency for the stationary system is 16.6% and 16.2% for the tracking system. The values of electricity generation capacity factor (CF) and solar capacity factor (SCF) for stationary system were found to be 26% and 62.5% respectively and 34% and 82% for tracking system. The GCR (Ground Cover Ratio) for a stationary system is 0.7, which corresponds to a tilt angle of 24°. The GCR for tracking system was found to be 0.12. The estimated ground area needed to build a 50MW PV plant amounts to approx. 0.55 km2 for a stationary PV field constituted by HIT PV arrays and approx. 91 MW/km2. In case of a tracker PV field, the required ground area amounts approx. 2.4k m2 and approx. 20.5 MW/km2.

Keywords: large scale photovoltaic power plant, two-axis tracking system, stationary system, landscape impact

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Authors: Ceyhun Aksoylu, Rifat Sezer

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In this study, a strengthening method applicable without any evacuation process was investigated. In this analytical study, the pushover analysis results carry out by using the software of SAP2000. For this purpose, 1/3 scaled, 1-bay and 2-story R/C seven frames having usual deficiencies faults produced, one of which were not strengthened, but having brick-infill wall and the other 3 frames with infill walls strengthened with various shaped of high strength-precast diagonal concrete panels. The prepared analytical models investigated under reversed-cyclic loading that resembles the seismic effect. As a result of the analytical study, the properties of the reinforced concrete frames, such as strength, rigidity, energy dissipation capacity, etc. were determined and the strengthened models were compared with the unstrengthened one having the same properties. As a result of this study, the contributions of precast diagonal concrete applied on the infill walls of the existing frame systems against seismic effects were introduced with its advantages and disadvantages.

Keywords: RC frame, seismic effect, infill wall, strengthening, precast diagonal concrete panel, pushover analysis

Procedia PDF Downloads 347

Authors: Wei-Hwa Chiang, Yu-Ching Cheng, Pei-Hsien Kao, Yu-Chi Lai

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A smart sustainable university campus is multi-dimensional. The success requires intensive inter-disciplinary coordination among all users and the expert group and long-term optimization. This paper reported the design and realization process of the dense and campus NTUST campus where space sharing is essential. Two-phase web-based interviews with students were conducted regarding where they study between classes as well as how they move within the campus. Efficient and active utilization of public and semi-public spaces, in particular, the ones near the ground, were progressively designed and realized where lobbies, corridors, reading rooms, and classrooms not in use were considered. Most of the spaces were equipped with smart monitoring and controls in terms of access, lighting, ceiling fans, air condition, and energy use. Mobile device apps were developed regarding the management of the spaces while information about energy use, environmental quality, and the smart sustainable campus project itself were provided to stimulate the awareness of sustainability and active participation in optimizing the campus.

Keywords: smart, sustainability, campus, space utilization

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Authors: Priya Bajaj, Baby Tabassum

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Arsenic is a poisonous metalloid, naturally occurring in soil, air, rocks and ground water. This dreadful metalloid commonly exists as inorganic compound, arsenic trioxide. WHO permitted maximum limit for arsenic in water is 0.01 mg/L, but some affected areas show ground water level of arsenic up to 3 mg/L even. Ground water arsenic pollution has created a number of health problems, viz. keratosis, melanosis, lesions and even skin cancers. The key objective of our nested study was to characterize arsenic induced hepatotoxicity and to find out some herbal protection against it. For the purpose, we selected albino rat (Rattus norvegicus) as model for arsenic induced liver injury and wild turmeric (Curcuma aromatica) leaf extract as remedy for it. The study was performed at acute (1 day) and subacute (7, 14 & 21 days) levels. The LD50 estimated for arsenic trioxide was 14.98 mg/kg body weight. In our investigation, we observed a significant restoration of altered hepatic lipid, cholesterol, protein and glycogen contents as well as liver weight, body-weight and hepato-somatic index by Curcuma aromatica leaf extract before arsenic intoxication. The results reveal excellent protective efficacy of Curcuma aromatica leaf extract that further can be exploited in remediation programme in heavy metal affected areas.

Keywords: arsenic, Curcuma aromatica, glycogen, lipids

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Authors: Tejaswi Agarwal, Amritansh Agarwal

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Forest ecosystem plays very important role in the global carbon cycle. It stores about 80% of all above ground and 40% of all below ground terrestrial organic carbon. There is much interest in the extent of tropical forests and their rates of deforestation for two reasons: greenhouse gas contributions and the impact of profoundly negative biodiversity. Deforestation has many ecological, social and economic consequences, one of which is the loss of biological diversity. The rapid deployment of remote sensing (RS) satellites and development of RS analysis techniques in the past three decades have provided a reliable, effective, and practical way to characterize terrestrial ecosystem properties. Global estimates of tropical deforestation vary widely and range from 50,000 to 170,000km2 /yr Recent FAO tropical deforestation estimates for 1990–1995 cite 116,756km2 / yr globally. Remote Sensing can prove to be a very useful tool in monitoring of forests and associated deforestation to a sufficient level of accuracy without the need of physically surveying the forest areas as many of them are physically inaccessible. The methodology for the assessment of forest cover using digital image processing (ERDAS) has been followed. The satellite data for the study was procured from Indian institute of remote Sensing (IIRS), Dehradoon in the digital format. While procuring the satellite data, care was taken to ensure that the data was cloud free and did not belong to dry and leafless season. The Normalized Difference Vegetation Index (NDVI) has been used as a numerical indicator of the reduction in ground biomass. NDVI = (near I.R - Red)/ (near I.R + Red). After calculating the NDVI variations and associated mean, we have analysed the change in ground biomass. Through this paper, we have tried to indicate the rate of deforestation over a given period of time by comparing the forest cover at different time intervals. With the help of remote sensing and GIS techniques, it is clearly shown that the total forest cover is continuously degrading and transforming into various land use/land cover category.

Keywords: remote sensing, deforestation, supervised classification, NDVI, change detection

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Authors: Saul A. Torres Z., Eduardo Liceaga C., Alfredo Arias M.

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Agriculture in the world falls within the main sources of economic and global needs, so care of crop is extremely important for owners and workers; one of the major causes of loss of product is the pest infection of different types of organisms. We seek to develop a UAV for agricultural spraying at a maximum altitude of 5000 meters above sea level, with a payload of 100 liters of fumigant. For the developing the aerodynamic design of the aircraft is using computational tools such as the "Vortex Lattice Athena" software, "MATLAB"," ANSYS FLUENT"," XFoil " package among others. Also methods are being used structured programming, exhaustive analysis of optimization methods and search. The results have a very low margin of error, and the multi- objective problems can be helpful for future developments. The program has 10 functions developed in MATLAB, these functions are related to each other to enable the development of design, and all these functions are controlled by the principal code "Master.m".

Keywords: aerodynamics design, optimization, algorithm genetic, multi-objective problem, stability, vortex

Procedia PDF Downloads 532

Authors: Amritansh Agarwal, Tejaswi Agarwal

Abstract:

Forest ecosystem plays very important role in the global carbon cycle. It stores about 80% of all above ground and 40% of all below ground terrestrial organic carbon. There is much interest in the extent of tropical forests and their rates of deforestation for two reasons: greenhouse gas contributions and the impact of profoundly negative biodiversity. Deforestation has many ecological, social and economic consequences, one of which is the loss of biological diversity. The rapid deployment of remote sensing (RS) satellites and development of RS analysis techniques in the past three decades have provided a reliable, effective, and practical way to characterize terrestrial ecosystem properties. Global estimates of tropical deforestation vary widely and range from 50,000 to 170,000 km2 /yr Recent FAO tropical deforestation estimates for 1990–1995 cite 116,756km2 / yr globally. Remote Sensing can prove to be a very useful tool in monitoring of forests and associated deforestation to a sufficient level of accuracy without the need of physically surveying the forest areas as many of them are physically inaccessible. The methodology for the assessment of forest cover using digital image processing (ERDAS) has been followed. The satellite data for the study was procured from USGS website in the digital format. While procuring the satellite data, care was taken to ensure that the data was cloud and aerosol free by making using of FLAASH atmospheric correction technique. The Normalized Difference Vegetation Index (NDVI) has been used as a numerical indicator of the reduction in ground biomass. NDVI = (near I.R - Red)/ (near I.R + Red). After calculating the NDVI variations and associated mean we have analysed the change in ground biomass. Through this paper we have tried to indicate the rate of deforestation over a given period of time by comparing the forest cover at different time intervals. With the help of remote sensing and GIS techniques it is clearly shows that the total forest cover is continuously degrading and transforming into various land use/land cover category.

Keywords: remote sensing, deforestation, supervised classification, NDVI change detection

Procedia PDF Downloads 402

Authors: Shuge Lei, Haonan Hu, Dasheng Sun, Huabin Zhang, Kehong Yuan, Jian Dai, Yan Tong

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It remains challenging to measure reliability from classification results from different machine learning models. This paper proposes a reliable soup optimization algorithm based on the model weight fusion algorithm Model Soup, aiming to improve reliability by using dual-channel reliability as the objective function to fuse a series of weights in the breast ultrasound classification models. Experimental results on breast ultrasound clinical datasets demonstrate that reliable soup significantly enhances the reliability of breast ultrasound image classification tasks. The effectiveness of the proposed approach was verified via multicenter trials. The results from five centers indicate that the reliability optimization algorithm can enhance the reliability of the breast ultrasound image classification model and exhibit low multicenter correlation.

Keywords: breast ultrasound image classification, feature attribution, reliability assessment, reliability optimization

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Authors: Mahmoud F. Awad-Allah, Mohammed Rabeih, Eman Abdel Baseer

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Soft to very soft soil deposits are widely speared in some areas of Egypt such as East Port Said, Damietta, Kafr El-Sheik, Alexandria, etc. The construction projects in these areas have faced the challenge of the presence of extended deep layers of soft and very soft clays which reach to depths of 40 to 60 m from the ground level. Stone columns are commonly used to support structures overlying soft ground soils and surcharged by embankment type loading. Therefore, this paper introduces a wide comparison numerical study between the ordinary stone columns (OSC) versus the geosynthetic encased stone columns (ESC) installed in soft clay soil deposit using finite element method (FEM). Parametric study of an embankment on soft soils reinforced with stone columns is performed using commercial computer program based on the finite element technique (PLAXIS 2D). The investigation will present the influence of the following parameters: diameter of stone columns, stiffness of geosynthetic encasement, embedded depth of stone column from ground level, and the length encasement of the stone column on the consolidation time, vertical settlement, and lateral displacement of soft clay soil formations.

Keywords: finite element method, geosynthetic, lateral displacement, settlement, soft clay

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Authors: S. Behnam Asl, H. Sadeghi Naeini, L. Sadat Ensaniat, R. Khorshidian, S. Alipour, S. Behnam Asl

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Nowadays, the construction industry is growing, especially among developing countries. Iran also has a critical role in these industries in terms of workers disorders. Work-related musculoskeletal disorders (WMSDs) account for 7% of the whole diseases in the society, which makes some limitations. One of the main factors which causes WMSDs is awkward posture. Steel bar bending is considered as one of the prominent performance among construction workers. In this case study, we aimed to find the major tasks of bar benders and the most important risk factors related to it. This study was carried out among twenty workers (18-45 years) as our volunteer samples in some construction sites with less than 6 floors in two regions of Tehran municipality. The data was gathered through in depth observation, interview and questionnaire. Also postural analysis was done by OWAS method. In another part of study we used NMQ for gathering some data about psychosocial effects of work related disorders. Our findings show that 64% of workers were not aware of work risks, about 59% of workers had troubles in their wrists, hands, especially workers who worked in steel bar bending. In 46% cases lower back pain was in prevalence. Considering gathered data and results, awkward postures and long term tasks and their duration are known as the main risk factors of WMSDs among construction workers, meaning that work-rest schedule and tools design should be reconsidered to make an ergonomic condition for the mentioned workers.

Keywords: bar benders, construction workers, musculoskeletal disorders (WMSDs), OWAS method

Procedia PDF Downloads 312

Authors: Ahmed Usman

Abstract:

This paper attempts to examine the relevance of an Electoral Commission in the democratic process of governance in Nigeria. However, democratic system and governance present a clear indication of responsive and responsible governments. The idea of a government being responsive and responsible is based on the premise of conventional principles of democracy such as freedom of political, economic and social rights of and individual. More so, upholding of the Rule of Law based on the ground of constitutionalism is a clear manifestation of the democratic governance. The burdens of ascertaining theses democratic ethos rely solely on the constituted election management body known as Independent National Electoral Commission (INEC) for the case of Nigeria. This body is however, saddled with the responsibility of organizing and conducting periodic regular credible election known as free and fair election. The body also, is expected to be neutral, and independent to ensure fair treatment to all. It is on the basis of this fair treatment that credible leaders emerged. To this end, the paper examines the powers, functions and features of Independent National Electoral Commission. More so, the concepts of election and democracy have been operationalized. It is obvious that electoral process in Nigeria is marred with series of problems of which the paper identified and solutions were proffered towards credible, free and fair elections for sustainable democratic governance. In order to succinctly discuss and analyze the issues at stake, Structural Functional Analysis theory is adopted as a theoretical frame work for the paper.

Keywords: election, electoral commission, democracy, governance

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Authors: Emily Kambalame

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Water distribution networks necessitate many investments for construction, prompting researchers to seek cost reduction and efficient design solutions. Optimization techniques are employed in this regard to address these challenges. In this context, the penalty-free multi-objective evolutionary algorithm (PFMOEA) coupled with pressure-dependent analysis (PDA) was utilized to develop a multi-objective evolutionary search for the optimization of water distribution systems (WDSs). The aim of this research was to find out if the computational efficiency of the PFMOEA for WDS optimization could be enhanced. This was done by applying real coding representation and retaining different percentages of feasible and infeasible solutions close to the Pareto front in the elitism step of the optimization. Two benchmark network problems, namely the Two-looped and Hanoi networks, were utilized in the study. A comparative analysis was then conducted to assess the performance of the real-coded PFMOEA in relation to other approaches described in the literature. The algorithm demonstrated competitive performance for the two benchmark networks by implementing real coding. The real-coded PFMOEA achieved the novel best-known solutions ($419,000 and $6.081 million) and a zero-pressure deficit for the two networks, requiring fewer function evaluations than the binary-coded PFMOEA. In previous PFMOEA studies, elitism applied a default retention of 30% of the least cost-feasible solutions while excluding all infeasible solutions. It was found in this study that by replacing 10% and 15% of the feasible solutions with infeasible ones that are close to the Pareto front with minimal pressure deficit violations, the computational efficiency of the PFMOEA was significantly enhanced. The configuration of 15% feasible and 15% infeasible solutions outperformed other retention allocations by identifying the optimal solution with the fewest function evaluation

Keywords: design optimization, multi-objective evolutionary, penalty-free, water distribution systems

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Authors: A. Chatel, I. S. Torreguitart, T. Verstraete

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The paper deals with a single point optimization of the LS89 turbine using an adjoint optimization and defining the design variables within a CAD system. The advantage of including the CAD model in the design system is that higher level constraints can be imposed on the shape, allowing the optimized model or component to be manufactured. However, CAD-based approaches restrict the design space compared to node-based approaches where every node is free to move. In order to preserve a rich design space, we develop a methodology to refine the CAD model during the optimization and to create the best parameterization to use at each time. This study presents a methodology to progressively refine the design space, which combines parametric effectiveness with a differential evolutionary algorithm in order to create an optimal parameterization. In this manuscript, we show that by doing the parameterization at the CAD level, we can impose higher level constraints on the shape, such as the axial chord length, the trailing edge radius and G2 geometric continuity between the suction side and pressure side at the leading edge. Additionally, the adjoint sensitivities are filtered out and only smooth shapes are produced during the optimization process. The use of algorithmic differentiation for the CAD kernel and grid generator allows computing the grid sensitivities to machine accuracy and avoid the limited arithmetic precision and the truncation error of finite differences. Then, the parametric effectiveness is computed to rate the ability of a set of CAD design parameters to produce the design shape change dictated by the adjoint sensitivities. During the optimization process, the design space is progressively enlarged using the knot insertion algorithm which allows introducing new control points whilst preserving the initial shape. The position of the inserted knots is generally assumed. However, this assumption can hinder the creation of better parameterizations that would allow producing more localized shape changes where the adjoint sensitivities dictate. To address this, we propose using a differential evolutionary algorithm to maximize the parametric effectiveness by optimizing the location of the inserted knots. This allows the optimizer to gradually explore larger design spaces and to use an optimal CAD-based parameterization during the course of the optimization. The method is tested on the LS89 turbine cascade and large aerodynamic improvements in the entropy generation are achieved whilst keeping the exit flow angle fixed. The trailing edge and axial chord length, which are kept fixed as manufacturing constraints. The optimization results show that the multilevel optimizations were more efficient than the single level optimization, even though they used the same number of design variables at the end of the multilevel optimizations. Furthermore, the multilevel optimization where the parameterization is created using the optimal knot positions results in a more efficient strategy to reach a better optimum than the multilevel optimization where the position of the knots is arbitrarily assumed.

Keywords: adjoint, CAD, knots, multilevel, optimization, parametric effectiveness

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Authors: E. A. Krasikov

Abstract:

As the service life of an operating nuclear power plant (NPP) increases, the potential misunderstanding of the degradation of aging components must receive more attention. Integrity assurance analysis contributes to the effective maintenance of adequate plant safety margins. In essence, the reactor pressure vessel (RPV) is the key structural component determining the NPP lifetime. Environmentally induced cracking in the stainless steel corrosion-preventing cladding of RPV’s has been recognized to be one of the technical problems in the maintenance and development of light-water reactors. Extensive cracking leading to failure of the cladding was found after 13000 net hours of operation in JPDR (Japan Power Demonstration Reactor). Some of the cracks have reached the base metal and further penetrated into the RPV in the form of localized corrosion. Failures of reactor internal components in both boiling water reactors and pressurized water reactors have increased after the accumulation of relatively high neutron fluences (5´1020 cm–2, E>0,5MeV). Therefore, in the case of cladding failure, the problem arises of hydrogen (as a corrosion product) embrittlement of irradiated RPV steel because of exposure to the coolant. At present when notable progress in plasma physics has been obtained practical energy utilization from fusion reactors (FR) is determined by the state of material science problems. The last includes not only the routine problems of nuclear engineering but also a number of entirely new problems connected with extreme conditions of materials operation – irradiation environment, hydrogenation, thermocycling, etc. Limiting data suggest that the combined effect of these factors is more severe than any one of them alone. To clarify the possible influence of the in-service synergistic phenomena on the FR structural materials properties we have studied hydrogen-irradiated steel interaction including alternating hydrogenation and heat treatment (annealing). Available information indicates that the life of the first wall could be expanded by means of periodic in-place annealing. The effects of neutron fluence and irradiation temperature on steel/hydrogen interactions (adsorption, desorption, diffusion, mechanical properties at different loading velocities, post-irradiation annealing) were studied. Experiments clearly reveal that the higher the neutron fluence and the lower the irradiation temperature, the more hydrogen-radiation defects occur, with corresponding effects on the steel mechanical properties. Hydrogen accumulation analyses and thermal desorption investigations were performed to prove the evidence of hydrogen trapping at irradiation defects. Extremely high susceptibility to hydrogen embrittlement was observed with specimens which had been irradiated at relatively low temperature. However, the susceptibility decreases with increasing irradiation temperature. To evaluate methods for the RPV’s residual lifetime evaluation and prediction, more work should be done on the irradiated metal–hydrogen interaction in order to monitor more reliably the status of irradiated materials.

Keywords: hydrogen, radiation, stability, structural steel

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Authors: Nozar Kishi, Babak Kamrani, Filmon Habte

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Natural hazards such as earthquakes and tropical storms, are very frequent and highly destructive in Japan. Japan experiences, every year on average, more than 10 tropical cyclones that come within damaging reach, and earthquakes of moment magnitude 6 or greater. We have developed stochastic catastrophe models to address the risk associated with the entire suite of damaging events in Japan, for use by insurance, reinsurance, NGOs and governmental institutions. KCC’s (Karen Clark and Company) catastrophe models are procedures constituted of four modular segments: 1) stochastic events sets that would represent the statistics of the past events, hazard attenuation functions that could model the local intensity, vulnerability functions that would address the repair need for local buildings exposed to the hazard, and financial module addressing policy conditions that could estimates the losses incurring as result of. The events module is comprised of events (faults or tracks) with different intensities with corresponding probabilities. They are based on the same statistics as observed through the historical catalog. The hazard module delivers the hazard intensity (ground motion or wind speed) at location of each building. The vulnerability module provides library of damage functions that would relate the hazard intensity to repair need as percentage of the replacement value. The financial module reports the expected loss, given the payoff policies and regulations. We have divided Japan into regions with similar typhoon climatology, and earthquake micro-zones, within each the characteristics of events are similar enough for stochastic modeling. For each region, then, a set of stochastic events is developed that results in events with intensities corresponding to annual occurrence probabilities that are of interest to financial communities; such as 0.01, 0.004, etc. The intensities, corresponding to these probabilities (called CE, Characteristics Events) are selected through a superstratified sampling approach that is based on the primary uncertainty. Region specific hazard intensity attenuation functions followed by vulnerability models leads to estimation of repair costs. Extensive economic exposure model addresses all local construction and occupancy types, such as post-linter Shinand Okabe wood, as well as concrete confined in steel, SRC (Steel-Reinforced Concrete), high-rise.

Keywords: typhoon, earthquake, Japan, catastrophe modelling, stochastic modeling, stratified sampling, loss model, ERM

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Authors: Katharina Ninaus, Ralf Terlutter, Sandra Diehl

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Information and communication technologies (ICT) have become pervasive in all areas of modern life, both in work and leisure. Technological developments and particularly the ubiquity of smartphones have made it possible for ICT consumers to be constantly connected to work, fostering an always-on mentality and increasing the pressure to be accessible at all times. However, performing work tasks outside of working hours using ICT results in a lack of mental detachment and recovery from work. It is, therefore, necessary to develop effective behavioral interventions to increase risk awareness of a constant connection to the workplace in the employed population. Drawing on regulatory focus theory, this study aims to investigate the persuasiveness of tailoring messages to individuals’ chronic regulatory focus in order to encourage ICT consumers to set boundaries by defining fixed times for professional accessibility outside of working hours in order to contribute to the well-being of ICT consumers with high ICT involvement in their work life. The experimental study examines the interaction effect between consumers’ chronic regulatory focus (i.e. promotion focus versus prevention focus) and positive or negative message framing (i.e. gain frame versus loss frame) on consumers’ intention to perform the advocated behavior. Based on the assumption that congruent messages create regulatory fit and increase message effectiveness, it is hypothesized that behavioral intention will be higher in the condition of regulatory fit compared to regulatory non-fit. It is further hypothesized that ad believability and attitude toward the ad will mediate the effect of regulatory fit on behavioral intention given that ad believability and ad attitude both determine consumer behavioral responses. Results confirm that the interaction between regulatory focus and message frame emerged as a predictor of behavioral intention such as that consumers’ intentions to set boundaries by defining fixed times for professional accessibility outside of working hours increased as congruency with their regulatory focus increased. The loss-framed ad was more effective for consumers with a predominant prevention focus, while the gain-framed ad was more effective for consumers with a predominant promotion focus. Ad believability and attitude toward the ad both emerged as predictors of behavioral intention. Mediation analysis revealed that the direct effect of the interaction between regulatory focus and message frame on behavioral intention was no longer significant when including ad believability and ad attitude as mediators in the model, indicating full mediation. However, while the indirect effect through ad believability was significant, the indirect effect through attitude toward the ad was not significant. Hence, regulatory fit increased ad believability, which then increased behavioral intention. Ad believability appears to have a superior effect indicating that behavioral intention does not depend on attitude toward the ad, but it depends on whether or not the ad is perceived as believable. The study shows that the principle of regulatory fit holds true in the context of ICT consumption and responds to calls for more research on mediators of health message framing effects.

Keywords: always-on mentality, Information and communication technologies (ICT) consumption, message framing, regulatory focus

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Authors: James M. Wakiru, Liliane Pintelon, Peter Muchiri, Stanley Mburu

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Maintenance performance measurement (MPM) represents an integrated aspect that considers both operational and maintenance related aspects while evaluating the effectiveness and efficiency of maintenance to ensure assets are working as they should. Three salient issues require to be addressed for an asset-intensive organization to employ an MPM-based framework to optimize maintenance. Firstly, the organization should establish important perfomance metric(s), in this case the maintenance objective(s), which they will be focuss on. The second issue entails aligning the maintenance objective(s) with maintenance optimization. This is achieved by deriving maintenance performance indicators that subsequently form an objective function for the optimization program. Lastly, the objective function is employed in an optimization program to derive maintenance decision support. In this study, we develop a framework that initially identifies the crucial maintenance performance measures, and employs them to derive maintenance decision support. The proposed framework is demonstrated in a case study of a geothermal drilling rig, where the objective function is evaluated utilizing a simulation-based model whose parameters are derived from empirical maintenance data. Availability, reliability and maintenance inventory are depicted as essential objectives requiring further attention. A simulation model is developed mimicking a drilling rig operations and maintenance where the sub-systems are modelled undergoing imperfect maintenance, corrective (CM) and preventive (PM), with the total cost as the primary performance measurement. Moreover, three maintenance spare inventory policies are considered; classical (retaining stocks for a contractual period), vendor-managed inventory with consignment stock and periodic monitoring order-to-stock (s, S) policy. Optimization results infer that the adoption of (s, S) inventory policy, increased PM interval and reduced reliance of CM actions offers improved availability and total costs reduction.

Keywords: maintenance, vendor-managed, decision support, performance, optimization

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Authors: Byeongcheol Kang, Junyi Kim, Hyungsik Jung, Hyungjun Yang, Jaewoo An, Jonggeun Choe

Abstract:

It is important to figure out reservoir properties for better production management. Due to the limited information, there are geological uncertainties on very heterogeneous or channel reservoir. One of the solutions is to generate multiple equi-probable realizations using geostatistical methods. However, some models have wrong properties, which need to be excluded for simulation efficiency and reliability. We propose a novel method of model selection scheme, based on distance-based clustering for reliable application of production optimization algorithm. Distance is defined as a degree of dissimilarity between the data. We calculate Hausdorff distance to classify the models based on their similarity. Hausdorff distance is useful for shape matching of the reservoir models. We use multi-dimensional scaling (MDS) to describe the models on two dimensional space and group them by K-means clustering. Rather than simulating all models, we choose one representative model from each cluster and find out the best model, which has the similar production rates with the true values. From the process, we can select good reservoir models near the best model with high confidence. We make 100 channel reservoir models using single normal equation simulation (SNESIM). Since oil and gas prefer to flow through the sand facies, it is critical to characterize pattern and connectivity of the channels in the reservoir. After calculating Hausdorff distances and projecting the models by MDS, we can see that the models assemble depending on their channel patterns. These channel distributions affect operation controls of each production well so that the model selection scheme improves management optimization process. We use one of useful global search algorithms, particle swarm optimization (PSO), for our production optimization. PSO is good to find global optimum of objective function, but it takes too much time due to its usage of many particles and iterations. In addition, if we use multiple reservoir models, the simulation time for PSO will be soared. By using the proposed method, we can select good and reliable models that already matches production data. Considering geological uncertainty of the reservoir, we can get well-optimized production controls for maximum net present value. The proposed method shows one of novel solutions to select good cases among the various probabilities. The model selection schemes can be applied to not only production optimization but also history matching or other ensemble-based methods for efficient simulations.

Keywords: distance-based clustering, geological uncertainty, particle swarm optimization (PSO), production optimization

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Authors: Zhuoran Shan, Li Wan, Xianchun Zhang

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With an increasing trend of regionalization and polycentricity in Chinese contemporary big cities, “sub-region life circle” turns to be an effective method on rational organization of urban function and spatial structure. By the method of questionnaire, network big data, route inversion on internet map, GIS spatial analysis and logistic regression, this article makes research on characteristic and formation mechanism of “sub-region life circle” based on human high-probability daily activity in Chinese big cities. Firstly, it shows that “sub-region life circle” has been a new general spatial sphere of residents' high-probability daily activity and mobility in China. Unlike the former analysis of the whole metropolitan or the micro community, “sub-region life circle” has its own characteristic on geographical sphere, functional element, spatial morphology and land distribution. Secondly, according to the analysis result with Binary Logistic Regression Model, the research also shows that seven factors including land-use mixed degree and bus station density impact the formation of “sub-region life circle” most, and then analyzes the index critical value of each factor. Finally, to establish a smarter “sub-region life circle”, this paper indicates that several strategies including jobs-housing fit, service cohesion and space reconstruction are the keys for its spatial organization optimization. This study expands the further understanding of cities' inner sub-region spatial structure based on human daily activity, and contributes to the theory of “life circle” in urban's meso-scale.

Keywords: sub-region life circle, characteristic, formation mechanism, human activity, spatial structure

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Authors: Arminder Singh Walia, Vineet Srivastava, Vivek Jain

Abstract:

In Electrical Discharge Machining (EDM) operations, the workpiece confers to the shape of the tool. Further, the cost of the tool contributes the maximum effect on total operation cost. Therefore, the shape and profile of the tool become highly significant. Thus, in this work, an attempt has been made to study the effect of process parameters on the shape of the tool. Copper has been used as the tool material for the machining of AISI 52100 die steel. The shape of the tool has been evaluated by determining the difference in out of roundness of tool before and after machining. Statistical model has been developed and significant process parameters have been identified which affect the shape of the tool. Optimum process parameters have been identified which minimizes the shape distortion.

Keywords: discharge current, flushing pressure, pulse-on time, pulse-off time, out of roundness, electrical discharge machining

Procedia PDF Downloads 285

Authors: Dace Grauda, Gunta Cekstere, Inta Belogrudova, Andis Karlsons, Isaak Rashal

Abstract:

Trifolium repens L. (white or Dutch clover) is a perennial herb, belongs to legume family (Leguminosae Juss.), spread extensively by stolons and seeds. The species is cultivated worldwide and was naturalized in many countries in meadows, yards, gardens, along roads and streets etc., especially in temperate regions. It is widespread also in grasslands throughout Riga, the capital of Latvia. The goal of this study was to investigate genetic structure of white clover population in Riga and to evaluate influence of different salt concentration on plants. For this purpose universal retrotranspozone based IRAP (Inter-Retrotransposon Amplified Polymorphism) method was used. The plant material was collected in different regions of Riga and in several urban areas of Latvia. Plant DNA was isolated from in silicogel dried leaves of using 1% CTAB (cetyltrimet-ammonium bromide) buffer DNA extraction procedure. Genetic structure of city population and wild populations were compared. Soil salinization is an important issue associated with low water resources and highly urbanized areas in aride and semi-aride climate conditions, as well as de-icing salt application to prevent ice formation on roads in winter. The T. repens variety ‘Daile’ (form giganteum), one of the often used component of urban greeneries, was studied in this investigation. Plants were grown from seeds and cultivated in the light conditions (18-25 C, 16h/8h of day/night, light intensity 3000 lx) in plastic pots (200 ml), filled with commercial neutralized (pH 5.9 ± 0.3) peat substrate with mineral nutrients. To analyse the impact of increased soil salinity treatments with gradually rising NaCl (0; 20; 40; 60; 80; 100 mM) levels were arranged. Plants were watered when necessary with deionised water to provide optimum substrate moisture 60-70%. The experiment was terminated six weeks after establishment. For analysis of mineral nutrients, dry plant material (above ground part and roots) was used. Decrease of Na content can be significant under elevated salinity till 20 mM NaCl. High NaCl concentrations in the substrate increase Na, Cl, Cu, Fe, and Mn accumulation, but reduce S, Mg, K content in the plant above ground parts. Abiotic stresses generally changes the levels of DNA metilation. Several candidate gene for salt tolerance will be analysed for DNA metilation level using Pyromark-Q24 advanced.

Keywords: DNA metilation, IRAP, soil salinization, white clover

Procedia PDF Downloads 364