Search results for: load priority selection

Authors: Shivarudraswamy, Anubhav Shrivastava, Lakshya Bhat

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Distributed generation has indeed become a major area of interest in recent years. Distributed Generation can address large number of loads in a power line and hence has better efficiency over the conventional methods. However there are certain drawbacks associated with it, increase in voltage being the major one. This paper addresses the voltage control at the buses for an IEEE 30 bus system by regulating reactive power. For carrying out the analysis, the suitable location for placing distributed generators (DG) is identified through load flow analysis and seeing where the voltage profile is dipping. MATLAB programming is used to regulate the voltage at all buses within +/-5% of the base value even after the introduction of DG’s. Three methods for regulation of voltage are discussed. A sensitivity based analysis is later carried out to determine the priority among the various methods listed in the paper.

Keywords: distributed generators, distributed system, reactive power, voltage control

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Authors: Seon Soon Choi

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It is necessary to predict a fatigue crack propagation life for estimation of structural integrity. Because of an uncertainty and a randomness of a structural behavior, it is also required to analyze stochastic characteristics of the fatigue crack propagation life at a specified fatigue crack size. The essential purpose of this study is to present the good probability distribution fit for the fatigue crack propagation life at a specified fatigue crack size in magnesium alloys under various fatigue load ratio conditions. To investigate a stochastic crack growth behavior, fatigue crack propagation experiments are performed in laboratory air under several conditions of fatigue load ratio using AZ31. By Anderson-Darling test, a goodness-of-fit test for probability distribution of the fatigue crack propagation life is performed and the good probability distribution fit for the fatigue crack propagation life is presented. The effect of load ratio on variability of fatigue crack propagation life is also investigated.

Keywords: fatigue crack propagation life, load ratio, magnesium alloys, probability distribution

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Authors: Sevilay Çankaya

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The detection of deception in children’s interviews is essential for statement veracity. The widely used method for deception detection is building cognitive load, which is the logic of the cognitive interview (CI), and its effectiveness for adults is approved. This meta-analysis delves into the effectiveness of inducing cognitive load as a means of enhancing veracity detection during interviews with children. Additionally, the effectiveness of cognitive load on children's total number of events recalled is assessed as a second part of the analysis. The current meta-analysis includes ten effect sizes from search using databases. For the effect size calculation, Hedge’s g was used with a random effect model by using CMA version 2. Heterogeneity analysis was conducted to detect potential moderators. The overall result indicated that cognitive load had no significant effect on veracity outcomes (g =0.052, 95% CI [-.006,1.25]). However, a high level of heterogeneity was found (I² = 92%). Age, participants’ characteristics, interview setting, and characteristics of the interviewer were coded as possible moderators to explain variance. Age was significant moderator (β = .021; p = .03, R2 = 75%) but the analysis did not reveal statistically significant effects for other potential moderators: participants’ characteristics (Q = 0.106, df = 1, p = .744), interview setting (Q = 2.04, df = 1, p = .154), and characteristics of interviewer (Q = 2.96, df = 1, p = .086). For the second outcome, the total number of events recalled, the overall effect was significant (g =4.121, 95% CI [2.256,5.985]). The cognitive load was effective in total recalled events when interviewing with children. All in all, while age plays a crucial role in determining the impact of cognitive load on veracity, the surrounding context, interviewer attributes, and inherent participant traits may not significantly alter the relationship. These findings throw light on the need for more focused, age-specific methods when using cognitive load measures. It may be possible to improve the precision and dependability of deceit detection in children's interviews with the help of more studies in this field.

Keywords: deceit detection, cognitive load, memory recall, children interviews, meta-analysis

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Authors: Seon Soon Choi

Abstract:

The essential purpose is to present the good fatigue crack propagation model describing a stochastic fatigue crack growth behavior in a rolled magnesium alloy, AZ31, under various load ratio conditions. Fatigue crack propagation experiments were carried out in laboratory air under four conditions of load ratio, R, using AZ31 to investigate the crack growth behavior. The stochastic fatigue crack growth behavior was analyzed using an interpolation of random variable, Z, introduced to an empirical fatigue crack propagation model. The empirical fatigue models used in this study are Paris-Erdogan model, Walker model, Forman model, and modified Forman model. It was found that the random variable is useful in describing the stochastic fatigue crack growth behaviors under various load ratio conditions. The good probabilistic model describing a stochastic fatigue crack growth behavior under various load ratio conditions was also proposed.

Keywords: magnesium alloys, fatigue crack propagation model, load ratio, interpolation of random variable

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Authors: Jiayuan Wu. Lu Hu

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With the development of the sharing economy and mobile technology, carsharing becomes more popular. In this paper, we focus on the joint optimization of one-way station-based carsharing systems. We model the problem as an integer linear program with six elements: station locations, station capacity, fleet size, initial vehicle allocation, vehicle relocation, and demand selection. A greedy-based heuristic is proposed to address the model. Firstly, initialization based on the location variables relaxation using Gurobi solver is conducted. Then, according to the profit margin and demand satisfaction of each station, the number of stations is downsized iteratively. This method is applied to real data from Chengdu, Sichuan taxi data, and it’s efficient when dealing with a large scale of candidate stations. The result shows that with vehicle relocation and demand selection, the profit and demand satisfaction of carsharing systems are increased.

Keywords: one-way carsharing, location, vehicle relocation, demand selection, greedy algorithm

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Authors: Malika Yaici, Assia Arab, Betitra Yakouben, Samia Zermani

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Ubiquitous computing is nowadays a reality through the networking of a growing number of computing devices. It allows providing users with context aware information and services in a heterogeneous environment, anywhere and anytime. Selection of the best context-aware service, between many available services and providers, is a tedious problem. In this paper, a service selection method based on Constraint Satisfaction Problem (CSP) formalism is proposed. The services are considered as variables and domains; and the user context, preferences and providers characteristics are considered as constraints. The Backtrack algorithm is used to solve the problem to find the best service and provider which matches the user requirements. Even though this algorithm has an exponential complexity, but its use guarantees that the service, that best matches the user requirements, will be found. A comparison of the proposed method with the existing solutions finishes the paper.

Keywords: ubiquitous computing, services selection, constraint satisfaction problem, backtrack algorithm

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Authors: Gamalath M. B. P. Abeysekara

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Primary objective of any organization is to enhance the bottom line profit. Strategic procurement is one of the prominent aspects in view of receiving this ultimate objective. Strategic procurement is an activity used in each and every organization in their operations. Pharmaceutical procurement is an especially significant task for any organizations, particularly state sector concerned. The whole pharmaceutical procurement requirement of the country is procured through the State Pharmaceutical Corporation (SPC) of Sri Lanka. They follow Pharmaceutical Procurement Guideline of 2006 as the procurement principle. The main objective of this project is to identify the importance of State Pharmaceutical Corporation supplier selection criteria and critical analysis of pharmaceutical procurement procedure. State Pharmaceutical Corporations applied net price, product quality, past performance, and delivery of suppliers’ as main criteria for the selection suppliers. Data collection for this study was taken place through a questionnaire, given to fifty doctors within the Colombo district attached to five main state hospitals. Data analysis is carried out with mean and standard deviation functions. The ultimate outcomes indicated product quality, net price, and delivery of suppliers’ are the most important criteria behind the selection of suppliers. Critical analysis proved State Pharmaceutical Corporation should focus on net price reduction, improving laboratory testing facilities and effective communication between up and down stream of supply chain.

Keywords: government procurement procedure, pharmaceutical procurement supplier selection criteria, importance of SPC supplier selection criteria

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Authors: Mohammad Reza Ameri, Ali Massumi, Mohammad Haghbin

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Non-linear static analysis, commonly referred to as pushover analysis, is a powerful tool for assessing the seismic response of structures. A suitable lateral load pattern for pushover analysis can bring the results of this simple, quick and low-cost analysis close to the realistic results of nonlinear dynamic analyses. In this research, four samples of 10- and 15 story (two- and four-bay) reinforced concrete frames were studied. The lateral load distribution patterns recommended in FEMA 273/356 guidelines were applied to the sample models in order to perform pushover analyses. The results were then compared to the results obtained from several nonlinear incremental dynamic analyses for a range of earthquakes. Finally, a lateral load distribution pattern was proposed for pushover analysis of medium-rise reinforced concrete buildings based on the results of nonlinear static and dynamic analyses.

Keywords: lateral load pattern, nonlinear static analysis, incremental dynamic analysis, medium-rise reinforced concrete frames, performance based design

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Authors: Jaime A. Palma-Mendoza

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A supply chain consists of different processes and when conducting supply chain re-design is necessary to identify the relevant processes and select a target for re-design. A solution was developed which consists to identify first the relevant processes using the Supply Chain Operations Reference (SCOR) model, then to use Analytical Hierarchy Process (AHP) for target process selection. An application was conducted in an Airline MRO supply chain re-design project which shows this combination can clearly aid the identification of relevant supply chain processes and the selection of a target process for re-design.

Keywords: decision support systems, multiple criteria analysis, supply chain management

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Authors: Priyashri Kamlesh Sridhar, Suranga Nanayakkara

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Current frameworks in assessment follow lesson delivery and rely heavily on test performance or teacher’s observations. This, however, neglects the underlying cognitive load during the learning process. Identifying the pivotal points when the load occurs helps design effective pedagogies and tools that respond to learners’ cognitive state. There has been limited research on quantifying cognitive load in preschoolers, real-time. In this study, we recorded electrodermal activity and heart rate variability (HRV) from 10 kindergarteners performing executive function tasks and Johnson Woodcock test of cognitive abilities. Preliminary findings suggest that there are indeed sensitive task-dependent markers in skin conductance (number of SCRs and average amplitude of SCRs) and HRV (mean heart rate and low frequency component) captured during the learning process.

Keywords: early childhood, learning, methodologies, pedagogies

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Authors: Supanitayanon Lalita, Dechkunakorn Surachai, Anuwongnukroh Niwat, Srikhirin Toemsak, Roongrujimek Pitchaya, Tua-Ngam Peerapong

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Objective: To compare maximum load, percentage of elongation, physical characteristics of 4 types of dental floss: (1) Thai Silk Floss (silk, waxed), (2) Oral B® Essential Floss (nylon, waxed), (3) Experimental Floss Xu (nylon, unwaxed), (4) Experimental Floss Xw (nylon, waxed). Materials & method: Four types of floss were tested (n=30) with a Universal Testing Machine (Instron®). Each sample (30 cm long, 5 cm segment) was fixed, and pulled apart with load cell of 100 N and a test speed of 100 mm/min. Physical characteristics were investigated by digital microscope under 2.5×10 magnification, and scanning electron microscope under 1×100 and 5×100 magnification. The size of the filaments was measured in micron (μm) and the fineness were measured in Denier. Statistical analysis: For mechanical properties, the maximum load and the percentage of elongation were presented as mean ± SD. The distribution of the data was calculated by the Kolmogorov-Smirnov test. One-way ANOVA and multiple comparison (Tukey HSD) were used to analyze the differences among the groups with the level of a statistical difference at p < 0.05. Results: The maximum load of Floss Xu, Floss Xw, Oral B and Thai Silk were 47.39, 46.46, 25.38, and 23.70 N, respectively. The percentage of elongation of Oral B, Floss Xw, Floss Xu and Thai Silk were 72.43, 44.62, 31.25, and 16.44%, respectively. All 4 types of dental floss showed statistically differences in both the maximum load and percentage of elongation at p < 0.05, except for maximum load between Floss Xw and Floss Xu that showed no statistically significant difference. Physical characteristics of Thai silk revealed the most disintegrated, the smallest, and the least fine filaments. Conclusion: Floss Xu had the highest maximum load. Oral B had the highest percentage of elongation. Wax coating on Floss X increased the elongation but had no significant effect on the maximum load. The physical characteristics of Thai Silk resulted in the lowest mechanical properties values.

Keywords: dental floss, maximum load, mechanical property, percentage of elongation, physical property

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Authors: A. Porshnev, A. Zaporozhtchuk

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Motivation regarded as a key factor of labor turnover, is especially important for volunteers working on an altruistic basis in NGO. Despite the motivational letter, candidate selection depends on the impression of the selection committee, which can be subject to human bias. We expect that structured and unstructured information provided in motivation letters could be used to improve candidate selection procedures. In our paper, we perform qualitative and quantitative analysis of 2280 motivation letters, create logistic regression, and build a decision tree to improve selection procedures. Our analysis showed that motivation factors are significant and enable human resources department to forecast labor turnover and provide extra information to demographic, professional and timing questions. In spite of the average level of accuracy the model demonstrates the selection procedures of company of under consideration can be improved. We also discuss interrelation between answers to open and closed motivation questions, recommend changes in motivational letter templates to ensure more relevant information about applicants and further steps to create more accurate model.

Keywords: decision trees, logistic regression, model, motivational letter, non-governmental organization, retention, turnover

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Authors: Mehdi Naserian, Mohammad Jooshaki, Mahmud Fotuhi-Firuzabad, Mohammad Hossein Mohammadi Sanjani, Ashknaz Oraee

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In recent years, the development of communication infrastructure and smart meters have facilitated the utilization of demand-side resources which can enhance stability and economic efficiency of power systems. Direct load control programs can play an important role in the utilization of demand-side resources in the residential sector. However, investments required for installing control equipment can be a limiting factor in the development of such demand response programs. Thus, selection of consumers with higher potentials is crucial to the success of a direct load control program. Heating, ventilation, and air conditioning (HVAC) systems, which due to the heat capacity of buildings feature relatively high flexibility, make up a major part of household consumption. Considering that the consumption of HVAC systems depends highly on the ambient temperature and bearing in mind the high investments required for control systems enabling direct load control demand response programs, in this paper, a recent solution is presented to uncover consumers with high air conditioner demand among large number of consumers and to measure the demand response potential of such consumers. This can pave the way for estimating the investments needed for the implementation of direct load control programs for residential HVAC systems and for estimating the demand response potentials in a distribution system. In doing so, we first cluster consumers into several groups based on the correlation coefficients between hourly consumption data and hourly temperature data using K-means algorithm. Then, by applying a recent algorithm to the hourly consumption and temperature data, consumers with high air conditioner consumption are identified. Finally, demand response potential of such consumers is estimated based on the equivalent desired temperature setpoint changes.

Keywords: communication infrastructure, smart meters, power systems, HVAC system, residential HVAC systems

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Authors: Eyad Almaita

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In this paper, a novel adaptive Radial Basis Function Neural Networks (RBFNN) algorithm is used to forecast the hour by hour electrical load demand in Jordan. A small and effective RBFNN model is used to forecast the hourly total load demand based on a small number of features. These features are; the load in the previous day, the load in the same day in the previous week, the temperature in the same hour, the hour number, the day number, and the day type. The proposed adaptive RBFNN model can enhance the reliability of the conventional RBFNN after embedding the network in the system. This is achieved by introducing an adaptive algorithm that allows the change of the weights of the RBFNN after the training process is completed, which will eliminates the need to retrain the RBFNN model again. The data used in this paper is real data measured by National Electrical Power co. (Jordan). The data for the period Jan./2012-April/2013 is used train the RBFNN models and the data for the period May/2013- Sep. /2013 is used to validate the models effectiveness.

Keywords: load forecasting, adaptive neural network, radial basis function, short-term, electricity consumption

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Authors: Charline David, Alexandre Blondin Massé, Arnaud Zinflou

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In 2016, Clements, Hurn, and Li proposed a multiple equation time series approach for the short-term load forecasting, reporting an average mean absolute percentage error (MAPE) of 1.36% on an 11-years dataset for the Queensland region in Australia. We present an adaptation of their model to the electrical power load consumption for the whole Quebec province in Canada. More precisely, we take into account two additional meteorological variables — cloudiness and wind speed — on top of temperature, as well as the use of multiple meteorological measurements taken at different locations on the territory. We also consider other minor improvements. Our final model shows an average MAPE score of 1:79% over an 8-years dataset.

Keywords: short-term load forecasting, special days, time series, multiple equations, parallelization, clustering

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Authors: Weng Jiantao, Wu Yiqun

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The efficiency of natural ventilation, wind pressure distribution on building surface, wind comfort for pedestrians and buildings’ wind tolerance in traditional settlements are closely related to the pattern of terrain. On the basis of field research on the typical island terrain in China, the physical and mathematical models are established by using CFD software, and then the simulation results of the wind field are exported. We discuss the relationship between wind direction and wind field results. Furthermore simulation results are imported into ArcGIS platform. The evaluation model of island site selection is established with considering slope factor. We realize the visual model of site selection on complex island terrain. The multi-plans of certain residential are discussed based on wind simulation; at last the optimal project is selected. Results can provide the theory guidance for settlement planning and construction in China's traditional island.

Keywords: CFD, island terrain, site selection, construction mechanism

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Authors: Alireza Alizadeh, Hossein Ghadimi, Oveis Abedinia, Noradin Ghadimi

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A Particle Swarm Optimization with Time Varying Acceleration Coefficients (PSO-TVAC) is proposed to determine optimal economic load dispatch (ELD) problem in this paper. The proposed methodology easily takes care of solving non-convex economic load dispatch problems along with different constraints like transmission losses, dynamic operation constraints and prohibited operating zones. The proposed approach has been implemented on the 3-machines 6-bus, IEEE 5-machines 14-bus, IEEE 6-machines 30-bus systems and 13 thermal units power system. The proposed technique is compared to solve the ELD problem with hybrid approach by using the valve-point effect. The comparison results prove the capability of the proposed method giving significant improvements in the generation cost for the economic load dispatch problem.

Keywords: PSO-TVAC, economic load dispatch, non-convex cost function, prohibited operating zone, transmission losses

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Authors: K. Yathish, K. G. Binu, B. S. Shenoy, D. S. Rao, R. Pai

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Load carrying capacity of an oil lubricated two-axial groove journal bearing is simulated by taking into account the viscosity variations in lubricant due to the addition of TiO2 nanoparticles as lubricant additive. Shear viscosities of TiO2 nanoparticle dispersions in oil are measured for various nanoparticle additive concentrations. The viscosity model derived from the experimental viscosities is employed in a modified Reynolds equation to obtain the pressure profiles and load carrying capacity of two-axial groove journal bearing. Results reveal an increase in load carrying capacity of bearings operating on nanoparticle dispersions as compared to plain oil

Keywords: journal bearing, TiO2 nanoparticles, viscosity model, Reynold's equation, load carrying capacity

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Authors: Sourabh Joshi, Geetinder Kaur, Sarabjit Kaur, Gulwatanpreet Singh, Geetika Mannan

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In this paper, we have use an algorithm that able to obtain an optimal solution to travelling salesman problem from a huge search space, quickly. This algorithm is based upon the ant colony optimization technique and employees roulette wheel selection mechanism. To illustrate it more clearly, a program has been implemented which is based upon this algorithm, that presents the changing process of route iteration in a more intuitive way. In the event, we had find the optimal path between hundred cities and also calculate the distance between two cities.

Keywords: ant colony, optimization, travelling salesman problem, roulette wheel selection

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Authors: Ali A. Al-Jazaairry, Tahsin T. Sabbagh

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One of the important concerns within the field of geotechnical engineering is the presence of cavities in soils. This present work is an attempt to understand the behaviour of strip footing subjected to inclined load and constructed on cavitied soil. The failure mechanism of strip footing located above such soils was studied analytically. The capability of analytical model to correctly expect the system behaviour is assessed by carrying out verification analysis on available studies. The study was prepared by finite element software (PLAXIS) in which an elastic-perfectly plastic soil model was used. It was indicated, from the results of the study, that the load carrying capacity of foundation constructed on cavity can be analysed well using such analysis. The research covered many foundation cases, and in each foundation case, there occurs a critical depth under which the presence of cavities has shown minimum impact on the foundation performance. When cavities are found above this critical depth, the load carrying capacity of the foundation differs with many influences, such as the location and size of the cavity and footing depth. Figures involving the load carrying capacity with the affecting factors studied are presented. These figures offer information beneficial for the design of strip footings rested on underground cavities. Moreover, the results might be used to design a shallow foundation constructed on cavitied soil, whereas the obtained failure mechanisms may be employed to improve numerical solutions for this kind of problems.

Keywords: axial load, cavity, inclined load, strip footing

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Authors: Bharatendra Rai

Abstract:

Predictive data analysis and modeling involving machine learning techniques become challenging in presence of too many explanatory variables or features. Presence of too many features in machine learning is known to not only cause algorithms to slow down, but they can also lead to decrease in model prediction accuracy. This study involves housing dataset with 79 quantitative and qualitative features that describe various aspects people consider while buying a new house. Boruta algorithm that supports feature selection using a wrapper approach build around random forest is used in this study. This feature selection process leads to 49 confirmed features which are then used for developing predictive random forest models. The study also explores five different data partitioning ratios and their impact on model accuracy are captured using coefficient of determination (r-square) and root mean square error (rsme).

Keywords: housing data, feature selection, random forest, Boruta algorithm, root mean square error

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Authors: Eyob Hundessa Gose

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Nowadays, it is obviously known that the construction of different infrastructures is one measurement of the development of a country; infrastructures like buildings, bridges, roads, and railways are among them. In the capital city of Ethiopia, the so-called Addis Ababa, the Light Rail Train (LRT), was built Four years ago to satisfy the demand for transportation among the people in the city. The lane of the Train and vehicle separation Media was built with a curb and rail guard installation system to show the right-of-way and for protection of vehicles entering the Train Lane, but this Rail guard fails easily when impacted by vehicles and found that the impact load response of the Rail guard is weak and the Rail guard cannot withstand impact load. This study investigates the effect of variation of parameters such as vehicle speed and different mass effects and assesses the failure mode FRP and Steel reinforcement bar rail guards of deflection and damage state.

Keywords: impact load, fiber reinforced polymer, rail guard, LS-DYNA

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Authors: Khalaf Khatatneh, Nabeel Al-Milli, Amjad Hudaib, Monther Ali Tarawneh

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Software fault prediction identify potential faults in software modules during the development process. In this paper, we present a novel approach for software fault prediction by combining a feedforward neural network with particle swarm optimization (PSO). The PSO algorithm is employed as a feature selection technique to identify the most relevant metrics as inputs to the neural network. Which enhances the quality of feature selection and subsequently improves the performance of the neural network model. Through comprehensive experiments on software fault prediction datasets, the proposed hybrid approach achieves better results, outperforming traditional classification methods. The integration of PSO-based feature selection with the neural network enables the identification of critical metrics that provide more accurate fault prediction. Results shows the effectiveness of the proposed approach and its potential for reducing development costs and effort by detecting faults early in the software development lifecycle. Further research and validation on diverse datasets will help solidify the practical applicability of the new approach in real-world software engineering scenarios.

Keywords: feature selection, neural network, particle swarm optimization, software fault prediction

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Authors: Abdinasir Mohamed, Ashraf El-Hamalawi, Steven Yeomans, Matthew Frost, Andy Connell

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The evaluation and selection of appropriate software solutions to meet with an organisation’s inherent business requirements can be a problematic software engineering process that if done incorrectly can have a significant, costly and adverse effect on the business and its processes. The aim of this paper is to show the process and evaluation criteria followed to select the right engineering solution for the identified business requirement. The research adopted an action research method within an organisation in the oil and gas industry, which required a solution suitable for conducting stress analysis for soil-pipeline interaction analysis (SPIA). Through the use of the presented software selection and evaluation approach, to capture and measure key requirements, it was possible to determine a suitable software for the organisation. This paper investigates methodologies for selecting software packages, software evaluation techniques, and software evaluation criteria in evaluating software packages before providing an explanation of the developed methodology adopted. The key findings of the study are: (1) that there is a need to create a framework for software selection methodologies, (2) there are no universal selection criteria in the engineering industry, and (3) there is a need to validate the findings by creating an application based on the evaluation technique and evaluation criteria for selecting software packages for the engineering industry. The findings of the study are offered to support organisations in the oil and gas sector improve software selection methodologies for SPIA.

Keywords: software evaluation, end user programs, soil pipeline analysis, software selection

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Authors: Javad Shamsi Soosahab, Reza Ziaie Moayed

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The compressive and tensile bearing capacity of helical piles in sand is investigated by means of numerical modeling. The analyses are carried out using two-dimensional finite-element software, Optum G2. The load–displacement behavior under compression and tension is compared in different relative densities for constant and various elastic modulus. The criterion used to find the ultimate axial load is the load corresponding to 5% of the helical diameter. The results show that relative density of sand plays an essential role in the response of ultimate capacities towards various condition. Increase in elastic modulus with depth is found to play a relatively more significant role to the increase in ultimate compressive load capacities, however tension bearing capacity decreases.

Keywords: helical piles, Optum G2, relative density, constant and various elastic modulus

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Authors: Youji Miyake

Abstract:

In aircraft assembly, a large number of preparatory holes are required for screw and rivet joints. Currently, many holes are drilled manually because it is difficult to machine the holes using conventional computerized numerical control(CNC) machines. The application of industrial robots to drill the hole has been considered as an alternative to the CNC machines. However, the rigidity of robot arms is so low that vibration is likely to occur during drilling. In this study, it is proposed constant-load feed machining as a method to perform high-precision drilling while minimizing the thrust force, which is considered to be the cause of vibration. In this method, the drill feed is realized by a constant load applied onto the tool so that the thrust force is theoretically kept below the applied load. The performance of the proposed method was experimentally examined through the deep hole drilling of plastic and simultaneous drilling of metal/plastic stack plates. It was confirmed that the deep hole drilling and simultaneous drilling could be performed without generating vibration by controlling the tool feed rate in the appropriate range.

Keywords: constant load feed machining, robotic drilling, deep hole, simultaneous drilling

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Authors: Xiaolei Hu, Enrico Ferrera, Riccardo Tomasi, Claudio Pastrone

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Load Forecasting plays a key role in making today's and future's Smart Energy Grids sustainable and reliable. Accurate power consumption prediction allows utilities to organize in advance their resources or to execute Demand Response strategies more effectively, which enables several features such as higher sustainability, better quality of service, and affordable electricity tariffs. It is easy yet effective to apply Load Forecasting at larger geographic scale, i.e. Smart Micro Grids, wherein the lower available grid flexibility makes accurate prediction more critical in Demand Response applications. This paper analyses the application of short-term load forecasting in a concrete scenario, proposed within the EU-funded GreenCom project, which collect load data from single loads and households belonging to a Smart Micro Grid. Three short-term load forecasting techniques, i.e. linear regression, artificial neural networks, and radial basis function network, are considered, compared, and evaluated through absolute forecast errors and training time. The influence of weather conditions in Load Forecasting is also evaluated. A new definition of Gain is introduced in this paper, which innovatively serves as an indicator of short-term prediction capabilities of time spam consistency. Two models, 24- and 1-hour-ahead forecasting, are built to comprehensively compare these three techniques.

Keywords: short-term load forecasting, smart micro grid, linear regression, artificial neural networks, radial basis function network, gain

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Authors: Mohammad Shams Esfand Abadi, Mehrdad Zalaghi, Reza ebrahimpour

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In this paper, we propose a sign adaptive filter algorithm with the ability of dynamic selection of subband filters which leads to low computational complexity compared with conventional sign subband adaptive filter (SSAF) algorithm. Dynamic selection criterion is based on largest reduction of the mean square deviation at each adaption. We demonstrate that this simple proposed algorithm has the same performance of the conventional SSAF and somewhat faster than it. In the presence of impulsive interferences robustness of the simple proposed algorithm as well as the conventional SSAF and outperform the conventional normalized subband adaptive filter (NSAF) algorithm. Therefore, it is preferred for environments under impulsive interferences. Simulation results are presented to verify these above considerations very well have been achieved.

Keywords: acoustic echo cancellation (AEC), normalized subband adaptive filter (NSAF), dynamic selection subband adaptive filter (DS-NSAF), sign subband adaptive filter (SSAF), impulsive noise, robust filtering

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Authors: M. Khoukhi

Abstract:

Accurate prediction of the cooling/heating load and consequently, the sizing of the heating, ventilating, and air-conditioning equipment require precise calculation of the heat transfer mainly by conduction through envelope components of a building. The thermal resistance of most thermal insulation materials depends on the operating temperature. The temperature to which the insulation materials are exposed varies, depending on the thermal resistance of the materials, the location of the insulation layer within the assembly system, and the effective temperature which depends on the amount of solar radiation received on the surface of the assembly. The main objective of this paper is to investigate the change of the thermal conductivity of polystyrene insulation material in terms of the temperature at the mid-thickness of the material and its effect on the cooling load required by the building.

Keywords: operating temperature, polystyrene insulation, thermal conductivity, cooling load

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Authors: A. H. Elkholy, A. H. Falah

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A new approach has been developed to estimate the load share and stress distribution of worm gear sets. The approach is based upon considering the instantaneous tooth meshing stiffness where the worm gear drive was modelled as a series of spur gear slices, and each slice was analyzed separately using the well established formulae of spur gears. By combining the results obtained for all slices, the entire envolute worm gear set loading and stressing was obtained. The geometric modelling method presented, allows tooth elastic deformation and tooth root stresses of worm gear drives under different load conditions to be investigated. On the basis of the method introduced in this study, the instantaneous meshing stiffness and load share were obtained. In comparison with existing methods, this approach has both good analysis accuracy and less computing time.

Keywords: gear, load/stress distribution, worm, wheel, tooth stiffness, contact line

Procedia PDF Downloads 319