Search results for: Root mean squared error
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2914

Search results for: Root mean squared error

664 Software Transactional Memory in a Dynamic Programming Language at Virtual Machine Level

Authors: Szu-Kai Hsu, Po-Ching Lin

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As more and more multi-core processors emerge, traditional sequential programming paradigm no longer suffice. Yet only few modern dynamic programming languages can leverage such advantage. Ruby, for example, despite its wide adoption, only includes threads as a simple parallel primitive. The global virtual machine lock of official Ruby runtime makes it impossible to exploit full parallelism. Though various alternative Ruby implementations do eliminate the global virtual machine lock, they only provide developers dated locking mechanism for data synchronization. However, traditional locking mechanism error-prone by nature. Software Transactional Memory is one of the promising alternatives among others. This paper introduces a new virtual machine: GobiesVM to provide a native software transactional memory based solution for dynamic programming languages to exploit parallelism. We also proposed a simplified variation of Transactional Locking II algorithm. The empirical results of our experiments show that support of STM at virtual machine level enables developers to write straightforward code without compromising parallelism or sacrificing thread safety. Existing source code only requires minimal or even none modi cation, which allows developers to easily switch their legacy codebase to a parallel environment. The performance evaluations of GobiesVM also indicate the difference between sequential and parallel execution is significant.

Keywords: global interpreter lock, ruby, software transactional memory, virtual machine

Procedia PDF Downloads 259
663 Medication Errors in a Juvenile Justice Youth Development Center

Authors: Tanja Salary

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This paper discusses a study conducted in a juvenile justice facility regarding medication errors. It includes an introduction to data collected about medication errors in a juvenile justice facility from 2011 - 2019 and explores contributing factors that relate to those errors. The data was obtained from electronic incident records of medication errors that were documented from the years 2011 through 2019. In addition, the presentation reviews both current and historical research of empirical data about patient safety standards and quality care comparing traditional health care facilities to juvenile justice residential facilities and acknowledges a gap in research. The theoretical/conceptual framework for the research study was Bandura and Adams’s self-efficacy theory of behavioral change and Mark Friedman’s results-based accountability theory. Despite the lack of evidence in previous studies addressing medication errors in juvenile justice facilities, this presenter will share information that adds to the body of knowledge, including the potential relationship of medication errors and contributing factors of race and age. Implications for future research include the effect that education and training will have on the communication among juvenile justice staff, including nurses, who administer medications to juveniles to ensure adherence to patient safety standards. There are several opportunities for future research concerning other characteristics about factors that may affect medication administration errors within the residential juvenile justice facility.

Keywords: Juvenile justice, medication errors, juveniles, error reduction strategies

Procedia PDF Downloads 44
662 Merits and Demerits of Participation of Fellow Examinee as Subjects in Observed Structured Practical Examination in Physiology

Authors: Mohammad U. A. Khan, Md. D. Hossain

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Background: Department of Physiology finds difficulty in managing ‘subjects’ in practical procedure. To avoid this difficulty fellow examinees of other group may be used as subjects. Objective: To find out the merits and demerits of using fellow examinees as subjects in the practical procedure. Method: This cross-sectional descriptive study was conducted in the Department of Physiology, Noakhali Medical College, Bangladesh during May-June’14. Forty-two 1st year undergraduate medical students from a selected public medical college of Bangladesh were enrolled for the study purposively. Consent of students and authority was taken. Eighteen of them were selected as subjects and designated as subject-examinees. Other fellow examinees (non-subject) examined their blood pressure and pulse as part of ‘observed structured practical examination’ (OSPE). The opinion of all examinees regarding the merits and demerits of using fellow examinee as subjects in the practical procedure was recorded. Result: Examinees stated that they could perform their practical procedure without nervousness (24/42, 57.14%), accurately and comfortably (14/42, 33.33%) and subjects were made available without wasting time (2/42, 4.76%). Nineteen students (45.24%) found no disadvantage and 2 (4.76%) felt embracing when the subject was of opposite sex. The subject-examinees narrated that they could learn from the errors done by their fellow examinee (11/18, 61.1%). 75% non-subject examinees expressed their willingness to be subject so that they can learn from their fellows’ error. Conclusion: Using fellow examinees as subjects is beneficial for both the non-subject and subject examinees. Funding sources: Navana, Beximco, Unihealth, Square & Acme Pharma, Bangladesh Ltd.

Keywords: physiology, teaching, practical, OSPE

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661 The Study of the Absorption and Translocation of Chromium by Lygeum spartum in the Mining Region of Djebel Hamimat and Soil-Plant Interaction

Authors: H. Khomri, A. Bentellis

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Since century of the Development Activities extraction and a dispersed mineral processing Toxic metals and much more contaminated vast areas occupied by what they natural outcrops. New types of metalliferous habitats are so appeared. A species that is Lygeum spartum attracted our curiosity because apart from its valuable role in desertification, it is apparently able to exclude antimony and other metals can be. This species, green leaf blades which are provided as cattle feed, would be a good subject for phytoremediation of mineral soils. The study of absorption and translocation of chromium by the Lygeum spartum in the mining region of Djebel Hamimat and the interaction soil-plant, revealed that soils of this species living in this region are alkaline, calcareous majority in their fine texture medium and saline in their minority. They have normal levels of organic matter. They are moderately rich in nitrogen. They contain total chromium content reaches a maximum of 66,80 mg Kg^(-1) and a total absence of soluble chromium. The results of the analysis of variance of the difference between bare soils and soils appear Lygeum spartum made a significant difference only for the silt and organic matter. But for the other variables analyzed this difference is not significant. Thus, this plant has only one action on the amendment, only the levels of silt and organic matter in soils. The results of the multiple regression of the chromium content of the roots according to all soil variables studied did appear that among the studied variables included in the model, only the electrical conductivity and clay occur in the explanation of contents chromium in roots. The chromium content of the aerial parts analyzed by regression based on all studied soil variables allows us to see only the variables: electrical conductivity and content of chromium in the root portion involved in the explanation of the content chromium in the aerial part.

Keywords: absorption, translocation, analysis of variance, chrome, Lygeum spartum, multiple regression, the soil variables

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660 Coordinated Interference Canceling Algorithm for Uplink Massive Multiple Input Multiple Output Systems

Authors: Messaoud Eljamai, Sami Hidouri

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Massive multiple-input multiple-output (MIMO) is an emerging technology for new cellular networks such as 5G systems. Its principle is to use many antennas per cell in order to maximize the network's spectral efficiency. Inter-cellular interference remains a fundamental problem. The use of massive MIMO will not derogate from the rule. It improves performances only when the number of antennas is significantly greater than the number of users. This, considerably, limits the networks spectral efficiency. In this paper, a coordinated detector for an uplink massive MIMO system is proposed in order to mitigate the inter-cellular interference. The proposed scheme combines the coordinated multipoint technique with an interference-cancelling algorithm. It requires the serving cell to send their received symbols, after processing, decision and error detection, to the interfered cells via a backhaul link. Each interfered cell is capable of eliminating intercellular interferences by generating and subtracting the user’s contribution from the received signal. The resulting signal is more reliable than the original received signal. This allows the uplink massive MIMO system to improve their performances dramatically. Simulation results show that the proposed detector improves system spectral efficiency compared to classical linear detectors.

Keywords: massive MIMO, COMP, interference canceling algorithm, spectral efficiency

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659 Evaluation of Vehicle Classification Categories: Florida Case Study

Authors: Ren Moses, Jaqueline Masaki

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This paper addresses the need for accurate and updated vehicle classification system through a thorough evaluation of vehicle class categories to identify errors arising from the existing system and proposing modifications. The data collected from two permanent traffic monitoring sites in Florida were used to evaluate the performance of the existing vehicle classification table. The vehicle data were collected and classified by the automatic vehicle classifier (AVC), and a video camera was used to obtain ground truth data. The Federal Highway Administration (FHWA) vehicle classification definitions were used to define vehicle classes from the video and compare them to the data generated by AVC in order to identify the sources of misclassification. Six types of errors were identified. Modifications were made in the classification table to improve the classification accuracy. The results of this study include the development of updated vehicle classification table with a reduction in total error by 5.1%, a step by step procedure to use for evaluation of vehicle classification studies and recommendations to improve FHWA 13-category rule set. The recommendations for the FHWA 13-category rule set indicate the need for the vehicle classification definitions in this scheme to be updated to reflect the distribution of current traffic. The presented results will be of interest to States’ transportation departments and consultants, researchers, engineers, designers, and planners who require accurate vehicle classification information for planning, designing and maintenance of transportation infrastructures.

Keywords: vehicle classification, traffic monitoring, pavement design, highway traffic

Procedia PDF Downloads 164
658 Local Differential Privacy-Based Data-Sharing Scheme for Smart Utilities

Authors: Veniamin Boiarkin, Bruno Bogaz Zarpelão, Muttukrishnan Rajarajan

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The manufacturing sector is a vital component of most economies, which leads to a large number of cyberattacks on organisations, whereas disruption in operation may lead to significant economic consequences. Adversaries aim to disrupt the production processes of manufacturing companies, gain financial advantages, and steal intellectual property by getting unauthorised access to sensitive data. Access to sensitive data helps organisations to enhance the production and management processes. However, the majority of the existing data-sharing mechanisms are either susceptible to different cyber attacks or heavy in terms of computation overhead. In this paper, a privacy-preserving data-sharing scheme for smart utilities is proposed. First, a customer’s privacy adjustment mechanism is proposed to make sure that end-users have control over their privacy, which is required by the latest government regulations, such as the General Data Protection Regulation. Secondly, a local differential privacy-based mechanism is proposed to ensure the privacy of the end-users by hiding real data based on the end-user preferences. The proposed scheme may be applied to different industrial control systems, whereas in this study, it is validated for energy utility use cases consisting of smart, intelligent devices. The results show that the proposed scheme may guarantee the required level of privacy with an expected relative error in utility.

Keywords: data-sharing, local differential privacy, manufacturing, privacy-preserving mechanism, smart utility

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657 Molecular Interactions between Vicia Faba L. Cultivars and Plant Growth Promoting Rhizobacteria (PGPR), Utilized as Yield Enhancing 'Plant Probiotics'

Authors: Eleni Stefanidou, Nikolaos Katsenios, Ioanna Karamichali, Aspasia Efthimiadou, Panagiotis Madesis

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The excessive use of pesticides and fertilizers has significant environmental and human health-related negative effects. In the frame of the development of sustainable agriculture practices, especially in the context of extreme environmental changes (climate change), it is important to develop alternative practices to increase productivity and biotic and abiotic stress tolerance. Beneficial bacteria, such as symbiotic bacteria in legumes (rhizobia) and symbiotic or free-living Plant Growth Promoting Rhizobacteria (PGPR), which could act as "plant probiotics", can promote plant growth and significantly increase the resistance of crops under adverse environmental conditions. In this study, we explored the symbiotic relationships between Faba bean (Vicia faba L.) cultivars with different PGPR bacteria, aiming to identify the possible influence on yield and biotic-abiotic phytoprotection benefits. Transcriptomic analysis of root and whole plant samples was executed for two Vicia faba L. cultivars (Polikarpi and Solon) treated with selected PGPR bacteria (6 treatments: B. subtilis + Rhizobium-mixture, A. chroococcum + Rhizobium-mixture, B. subtilis, A. chroococcum and Rhizobium-mixture). Preliminary results indicate a significant yield (Seed weight and Total number of pods) increase in both varieties, ranging around 25%, in comparison to the control, especially for the Solon cultivar. The increase was observed for all treatments, with the B. subtilis + Rhizobium-mixture treatment being the highest performing. The correlation of the physiological and morphological data with the transcriptome analysis revealed molecular mechanisms and molecular targets underlying the observed yield increase, opening perspectives for the use of nitrogen-fixing bacteria as a natural, more ecological enhancer of legume crop productivity.

Keywords: plant probiotics, PGPR, legumes, sustainable agriculture

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656 Integration of Virtual Learning of Induction Machines for Undergraduates

Authors: Rajesh Kumar, Puneet Aggarwal

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In context of understanding problems faced by undergraduate students while carrying out laboratory experiments dealing with high voltages, it was found that most of the students are hesitant to work directly on machine. The reason is that error in the circuitry might lead to deterioration of machine and laboratory instruments. So, it has become inevitable to include modern pedagogic techniques for undergraduate students, which would help them to first carry out experiment in virtual system and then to work on live circuit. Further advantages include that students can try out their intuitive ideas and perform in virtual environment, hence leading to new research and innovations. In this paper, virtual environment used is of MATLAB/Simulink for three-phase induction machines. The performance analysis of three-phase induction machine is carried out using virtual environment which includes Direct Current (DC) Test, No-Load Test, and Block Rotor Test along with speed torque characteristics for different rotor resistances and input voltage, respectively. Further, this paper carries out computer aided teaching of basic Voltage Source Inverter (VSI) drive circuitry. Hence, this paper gave undergraduates a clearer view of experiments performed on virtual machine (No-Load test, Block Rotor test and DC test, respectively). After successful implementation of basic tests, VSI circuitry is implemented, and related harmonic distortion (THD) and Fast Fourier Transform (FFT) of current and voltage waveform are studied.

Keywords: block rotor test, DC test, no load test, virtual environment, voltage source inverter

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655 Neurofeedback for Anorexia-RelaxNeuron-Aimed in Dissolving the Root Neuronal Cause

Authors: Kana Matsuyanagi

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Anorexia Nervosa (AN) is a psychiatric disorder characterized by a relentless pursuit of thinness and strict restriction of food. The current therapeutic approaches for AN predominantly revolve around outpatient psychotherapies, which create significant financial barriers for the majority of affected patients, hindering their access to treatment. Nonetheless, AN exhibit one of the highest mortality and relapse rates among psychological disorders, underscoring the urgent need to provide patients with an affordable self-treatment tool, enabling those unable to access conventional medical intervention to address their condition autonomously. To this end, a neurofeedback software, termed RelaxNeuron, was developed with the objective of providing an economical and portable means to aid individuals in self-managing AN. Electroencephalography (EEG) was chosen as the preferred modality for RelaxNeuron, as it aligns with the study's goal of supplying a cost-effective and convenient solution for addressing AN. The primary aim of the software is to ameliorate the negative emotional responses towards food stimuli and the accompanying aberrant eye-tracking patterns observed in AN patient, ultimately alleviating the profound fear towards food an elemental symptom and, conceivably, the fundamental etiology of AN. The core functionality of RelaxNeuron hinges on the acquisition and analysis of EEG signals, alongside an electrocardiogram (ECG) signal, to infer the user's emotional state while viewing dynamic food-related imagery on the screen. Moreover, the software quantifies the user's performance in accurately tracking the moving food image. Subsequently, these two parameters undergo further processing in the subsequent algorithm, informing the delivery of either negative or positive feedback to the user. Preliminary test results have exhibited promising outcomes, suggesting the potential advantages of employing RelaxNeuron in the treatment of AN, as evidenced by its capacity to enhance emotional regulation and attentional processing through repetitive and persistent therapeutic interventions.

Keywords: Anorexia Nervosa, fear conditioning, neurofeedback, BCI

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654 Anomaly Detection in Financial Markets Using Tucker Decomposition

Authors: Salma Krafessi

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The financial markets have a multifaceted, intricate environment, and enormous volumes of data are produced every day. To find investment possibilities, possible fraudulent activity, and market oddities, accurate anomaly identification in this data is essential. Conventional methods for detecting anomalies frequently fail to capture the complex organization of financial data. In order to improve the identification of abnormalities in financial time series data, this study presents Tucker Decomposition as a reliable multi-way analysis approach. We start by gathering closing prices for the S&P 500 index across a number of decades. The information is converted to a three-dimensional tensor format, which contains internal characteristics and temporal sequences in a sliding window structure. The tensor is then broken down using Tucker Decomposition into a core tensor and matching factor matrices, allowing latent patterns and relationships in the data to be captured. A possible sign of abnormalities is the reconstruction error from Tucker's Decomposition. We are able to identify large deviations that indicate unusual behavior by setting a statistical threshold. A thorough examination that contrasts the Tucker-based method with traditional anomaly detection approaches validates our methodology. The outcomes demonstrate the superiority of Tucker's Decomposition in identifying intricate and subtle abnormalities that are otherwise missed. This work opens the door for more research into multi-way data analysis approaches across a range of disciplines and emphasizes the value of tensor-based methods in financial analysis.

Keywords: tucker decomposition, financial markets, financial engineering, artificial intelligence, decomposition models

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653 Computational Modeling of Heat Transfer from a Horizontal Array Cylinders for Low Reynolds Numbers

Authors: Ovais U. Khan, G. M. Arshed, S. A. Raza, H. Ali

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A numerical model based on the computational fluid dynamics (CFD) approach is developed to investigate heat transfer across a longitudinal row of six circular cylinders. The momentum and energy equations are solved using the finite volume discretization technique. The convective terms are discretized using a second-order upwind methodology, whereas diffusion terms are discretized using a central differencing scheme. The second-order implicit technique is utilized to integrate time. Numerical simulations have been carried out for three different values of free stream Reynolds number (ReD) 100, 200, 300 and two different values of dimensionless longitudinal pitch ratio (SL/D) 1.5, 2.5 to demonstrate the fluid flow and heat transfer behavior. Numerical results are validated with the analytical findings reported in the literature and have been found to be in good agreement. The maximum percentage error in values of the average Nusselt number obtained from the numerical and analytical solutions is in the range of 10% for the free stream Reynolds number up to 300. It is demonstrated that the average Nusselt number for the array of cylinders increases with increasing the free stream Reynolds number and dimensionless longitudinal pitch ratio. The information generated would be useful in the design of more efficient heat exchangers or other fluid systems involving arrays of cylinders.

Keywords: computational fluid dynamics, array of cylinders, longitudinal pitch ratio, finite volume method, incompressible navier-stokes equations

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652 Utilizing Computational Fluid Dynamics in the Analysis of Natural Ventilation in Buildings

Authors: A. W. J. Wong, I. H. Ibrahim

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Increasing urbanisation has driven building designers to incorporate natural ventilation in the designs of sustainable buildings. This project utilises Computational Fluid Dynamics (CFD) to investigate the natural ventilation of an academic building, SIT@SP, using an assessment criterion based on daily mean temperature and mean velocity. The areas of interest are the pedestrian level of first and fourth levels of the building. A reference case recommended by the Architectural Institute of Japan was used to validate the simulation model. The validated simulation model was then used for coupled simulations on SIT@SP and neighbouring geometries, under two wind speeds. Both steady and transient simulations were used to identify differences in results. Steady and transient results are agreeable with the transient simulation identifying peak velocities during flow development. Under a lower wind speed, the first level was sufficiently ventilated while the fourth level was not. The first level has excessive wind velocities in the higher wind speed and the fourth level was adequately ventilated. Fourth level flow velocity was consistently lower than those of the first level. This is attributed to either simulation model error or poor building design. SIT@SP is concluded to have a sufficiently ventilated first level and insufficiently ventilated fourth level. Future works for this project extend to modifying the urban geometry, simulation model improvements, evaluation using other assessment metrics and extending the area of interest to the entire building.

Keywords: buildings, CFD Simulations, natural ventilation, urban airflow

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651 Prediction of Distillation Curve and Reid Vapor Pressure of Dual-Alcohol Gasoline Blends Using Artificial Neural Network for the Determination of Fuel Performance

Authors: Leonard D. Agana, Wendell Ace Dela Cruz, Arjan C. Lingaya, Bonifacio T. Doma Jr.

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The purpose of this paper is to study the predict the fuel performance parameters, which include drivability index (DI), vapor lock index (VLI), and vapor lock potential using distillation curve and Reid vapor pressure (RVP) of dual alcohol-gasoline fuel blends. Distillation curve and Reid vapor pressure were predicted using artificial neural networks (ANN) with macroscopic properties such as boiling points, RVP, and molecular weights as the input layers. The ANN consists of 5 hidden layers and was trained using Bayesian regularization. The training mean square error (MSE) and R-value for the ANN of RVP are 91.4113 and 0.9151, respectively, while the training MSE and R-value for the distillation curve are 33.4867 and 0.9927. Fuel performance analysis of the dual alcohol–gasoline blends indicated that highly volatile gasoline blended with dual alcohols results in non-compliant fuel blends with D4814 standard. Mixtures of low-volatile gasoline and 10% methanol or 10% ethanol can still be blended with up to 10% C3 and C4 alcohols. Intermediate volatile gasoline containing 10% methanol or 10% ethanol can still be blended with C3 and C4 alcohols that have low RVPs, such as 1-propanol, 1-butanol, 2-butanol, and i-butanol. Biography: Graduate School of Chemical, Biological, and Materials Engineering and Sciences, Mapua University, Muralla St., Intramuros, Manila, 1002, Philippines

Keywords: dual alcohol-gasoline blends, distillation curve, machine learning, reid vapor pressure

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650 Mitigation of Interference in Satellite Communications Systems via a Cross-Layer Coding Technique

Authors: Mario A. Blanco, Nicholas Burkhardt

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An important problem in satellite communication systems which operate in the Ka and EHF frequency bands consists of the overall degradation in link performance of mobile terminals due to various types of degradations in the link/channel, such as fading, blockage of the link to the satellite (especially in urban environments), intentional as well as other types of interference, etc. In this paper, we focus primarily on the interference problem, and we develop a very efficient and cost-effective solution based on the use of fountain codes. We first introduce a satellite communications (SATCOM) terminal uplink interference channel model that is classically used against communication systems that use spread-spectrum waveforms. We then consider the use of fountain codes, with focus on Raptor codes, as our main mitigation technique to combat the degradation in link/receiver performance due to the interference signal. The performance of the receiver is obtained in terms of average probability of bit and message error rate as a function of bit energy-to-noise density ratio, Eb/N0, and other parameters of interest, via a combination of analysis and computer simulations, and we show that the use of fountain codes is extremely effective in overcoming the effects of intentional interference on the performance of the receiver and associated communication links. We then show this technique can be extended to mitigate other types of SATCOM channel degradations, such as those caused by channel fading, shadowing, and hard-blockage of the uplink signal.

Keywords: SATCOM, interference mitigation, fountain codes, turbo codes, cross-layer

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649 Trip Reduction in Turbo Machinery

Authors: Pranay Mathur, Carlo Michelassi, Simi Karatha, Gilda Pedoto

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Industrial plant uptime is top most importance for reliable, profitable & sustainable operation. Trip and failed start has major impact on plant reliability and all plant operators focussed on efforts required to minimise the trips & failed starts. The performance of these CTQs are measured with 2 metrics, MTBT(Mean time between trips) and SR (Starting reliability). These metrics helps to identify top failure modes and identify units need more effort to improve plant reliability. Baker Hughes Trip reduction program structured to reduce these unwanted trip 1. Real time machine operational parameters remotely available and capturing the signature of malfunction including related boundary condition. 2. Real time alerting system based on analytics available remotely. 3. Remote access to trip logs and alarms from control system to identify the cause of events. 4. Continuous support to field engineers by remotely connecting with subject matter expert. 5. Live tracking of key CTQs 6. Benchmark against fleet 7. Break down to the cause of failure to component level 8. Investigate top contributor, identify design and operational root cause 9. Implement corrective and preventive action 10. Assessing effectiveness of implemented solution using reliability growth models. 11. Develop analytics for predictive maintenance With this approach , Baker Hughes team is able to support customer in achieving their Reliability Key performance Indicators for monitored units, huge cost savings for plant operators. This Presentation explains these approach while providing successful case studies, in particular where 12nos. of LNG and Pipeline operators with about 140 gas compressing line-ups has adopted these techniques and significantly reduce the number of trips and improved MTBT

Keywords: reliability, availability, sustainability, digital infrastructure, weibull, effectiveness, automation, trips, fail start

Procedia PDF Downloads 55
648 Concrete Mix Design Using Neural Network

Authors: Rama Shanker, Anil Kumar Sachan

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Basic ingredients of concrete are cement, fine aggregate, coarse aggregate and water. To produce a concrete of certain specific properties, optimum proportion of these ingredients are mixed. The important factors which govern the mix design are grade of concrete, type of cement and size, shape and grading of aggregates. Concrete mix design method is based on experimentally evolved empirical relationship between the factors in the choice of mix design. Basic draw backs of this method are that it does not produce desired strength, calculations are cumbersome and a number of tables are to be referred for arriving at trial mix proportion moreover, the variation in attainment of desired strength is uncertain below the target strength and may even fail. To solve this problem, a lot of cubes of standard grades were prepared and attained 28 days strength determined for different combination of cement, fine aggregate, coarse aggregate and water. An artificial neural network (ANN) was prepared using these data. The input of ANN were grade of concrete, type of cement, size, shape and grading of aggregates and output were proportions of various ingredients. With the help of these inputs and outputs, ANN was trained using feed forward back proportion model. Finally trained ANN was validated, it was seen that it gave the result with/ error of maximum 4 to 5%. Hence, specific type of concrete can be prepared from given material properties and proportions of these materials can be quickly evaluated using the proposed ANN.

Keywords: aggregate proportions, artificial neural network, concrete grade, concrete mix design

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647 Effect of Nanoparticles on Wheat Seed Germination and Seedling Growth

Authors: Pankaj Singh Rawat, Rajeew Kumar, Pradeep Ram, Priyanka Pandey

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Wheat is an important cereal crop for food security. Boosting the wheat production and productivity is the major challenge across the nation. Good quality of seed is required for maintaining optimum plant stand which ultimately increases grain yield. Ensuring a good germination is one of the key steps to ensure proper plant stand and moisture assurance during seed germination may help to speed up the germination. The tiny size of nanoparticles may help in entry of water into seed without disturbing their internal structure. Considering above, a laboratory experiment was conducted during 2012-13 at G.B. Pant University of Agriculture and Technology, Pantnagar, India. The completely randomized design was used for statistical analysis. The experiment was conducted in two phases. In the first phase, the appropriate concentration of nanoparticles for seed treatment was screened. In second phase seed soaking hours of nanoparticles for better seed germination were standardized. Wheat variety UP2526 was taken as test crop. Four nanoparticles (TiO2, ZnO, nickel and chitosan) were taken for study. The crop germination studies were done in petri dishes and standard package and practices were used to raise the seedlings. The germination studies were done by following standard procedure. In first phase of the experiment, seeds were treated with 50 and 300 ppm of nanoparticles and control was also maintained for comparison. In the second phase of experiment, seeds were soaked for 4 hours, 6 hours and 8 hours with 50 ppm nanoparticles of TiO2, ZnO, nickel and chitosan along with control treatment to identify the soaking time for better seed germination. Experiment revealed that the application of nanoparticles help to enhance seed germination. The study revealed that seed treatment with  nanoparticles at 50 ppm concentration increases root length, shoot length, seedling length, shoot dry weight, seedling dry weight, seedling vigour index I and seedling vigour index II as compared to seed soaking at 300 ppm concentration. This experiment showed that seed soaking up to 4 hr was better as compared to 6 and 8 hrs. Seed soaking with nanoparticles specially TiO2, ZnO, and chitosan proved to enhance germination and seedling growth indices of wheat crop.

Keywords: nanoparticles, seed germination, seed soaking, wheat

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646 Dust Particle Removal from Air in a Self-Priming Submerged Venturi Scrubber

Authors: Manisha Bal, Remya Chinnamma Jose, B.C. Meikap

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Dust particles suspended in air are a major source of air pollution. A self-priming submerged venturi scrubber proven very effective in cases of handling nuclear power plant accidents is an efficient device to remove dust particles from the air and thus aids in pollution control. Venturi scrubbers are compact, have a simple mode of operation, no moving parts, easy to install and maintain when compared to other pollution control devices and can handle high temperatures and corrosive and flammable gases and dust particles. In the present paper, fly ash particles recognized as a high air pollutant substance emitted mostly from thermal power plants is considered as the dust particle. Its exposure through skin contact, inhalation and indigestion can lead to health risks and in severe cases can even root to lung cancer. The main focus of this study is on the removal of fly ash particles from polluted air using a self-priming venturi scrubber in submerged conditions using water as the scrubbing liquid. The venturi scrubber comprising of three sections: converging section, throat and diverging section is submerged inside a water tank. The liquid enters the throat due to the pressure difference composed of the hydrostatic pressure of the liquid and static pressure of the gas. The high velocity dust particles atomize the liquid droplets at the throat and this interaction leads to its absorption into water and thus removal of fly ash from the air. Detailed investigation on the scrubbing of fly ash has been done in this literature. Experiments were conducted at different throat gas velocities, water levels and fly ash inlet concentrations to study the fly ash removal efficiency. From the experimental results, the highest fly ash removal efficiency of 99.78% is achieved at the throat gas velocity of 58 m/s, water level of height 0.77m with fly ash inlet concentration of 0.3 x10⁻³ kg/Nm³ in the submerged condition. The effect of throat gas velocity, water level and fly ash inlet concentration on the removal efficiency has also been evaluated. Furthermore, experimental results of removal efficiency are validated with the developed empirical model.

Keywords: dust particles, fly ash, pollution control, self-priming venturi scrubber

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645 The Relationship Between Hourly Compensation and Unemployment Rate Using the Panel Data Regression Analysis

Authors: S. K. Ashiquer Rahman

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the paper concentrations on the importance of hourly compensation, emphasizing the significance of the unemployment rate. There are the two most important factors of a nation these are its unemployment rate and hourly compensation. These are not merely statistics but they have profound effects on individual, families, and the economy. They are inversely related to one another. When we consider the unemployment rate that will probably decline as hourly compensations in manufacturing rise. But when we reduced the unemployment rates and increased job prospects could result from higher compensation. That’s why, the increased hourly compensation in the manufacturing sector that could have a favorable effect on job changing issues. Moreover, the relationship between hourly compensation and unemployment is complex and influenced by broader economic factors. In this paper, we use panel data regression models to evaluate the expected link between hourly compensation and unemployment rate in order to determine the effect of hourly compensation on unemployment rate. We estimate the fixed effects model, evaluate the error components, and determine which model (the FEM or ECM) is better by pooling all 60 observations. We then analysis and review the data by comparing 3 several countries (United States, Canada and the United Kingdom) using panel data regression models. Finally, we provide result, analysis and a summary of the extensive research on how the hourly compensation effects on the unemployment rate. Additionally, this paper offers relevant and useful informational to help the government and academic community use an econometrics and social approach to lessen on the effect of the hourly compensation on Unemployment rate to eliminate the problem.

Keywords: hourly compensation, Unemployment rate, panel data regression models, dummy variables, random effects model, fixed effects model, the linear regression model

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644 Empirical Modeling and Spatial Analysis of Heat-Related Morbidity in Maricopa County, Arizona

Authors: Chuyuan Wang, Nayan Khare, Lily Villa, Patricia Solis, Elizabeth A. Wentz

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Maricopa County, Arizona, has a semi-arid hot desert climate that is one of the hottest regions in the United States. The exacerbated urban heat island (UHI) effect caused by rapid urbanization has made the urban area even hotter than the rural surroundings. The Phoenix metropolitan area experiences extremely high temperatures in the summer from June to September that can reach the daily highest of 120 °F (48.9 °C). Morbidity and mortality due to the environmental heat is, therefore, a significant public health issue in Maricopa County, especially because it is largely preventable. Public records from the Maricopa County Department of Public Health (MCDPH) revealed that between 2012 and 2016, there were 10,825 incidents of heat-related morbidity incidents, 267 outdoor environmental heat deaths, and 173 indoor heat-related deaths. A lot of research has examined heat-related death and its contributing factors around the world, but little has been done regarding heat-related morbidity issues, especially for regions that are naturally hot in the summer. The objective of this study is to examine the demographic, socio-economic, housing, and environmental factors that contribute to heat-related morbidity in Maricopa County. We obtained heat-related morbidity data between 2012 and 2016 at census tract level from MCDPH. Demographic, socio-economic, and housing variables were derived using 2012-2016 American Community Survey 5-year estimate from the U.S. Census. Remotely sensed Landsat 7 ETM+ and Landsat 8 OLI satellite images and Level-1 products were acquired for all the summer months (June to September) from 2012 and 2016. The National Land Cover Database (NLCD) 2016 percent tree canopy and percent developed imperviousness data were obtained from the U.S. Geological Survey (USGS). We used ordinary least squares (OLS) regression analysis to examine the empirical relationship between all the independent variables and heat-related morbidity rate. Results showed that higher morbidity rates are found in census tracts with higher values in population aged 65 and older, population under poverty, disability, no vehicle ownership, white non-Hispanic, population with less than high school degree, land surface temperature, and surface reflectance, but lower values in normalized difference vegetation index (NDVI) and housing occupancy. The regression model can be used to explain up to 59.4% of total variation of heat-related morbidity in Maricopa County. The multiscale geographically weighted regression (MGWR) technique was then used to examine the spatially varying relationships between heat-related morbidity rate and all the significant independent variables. The R-squared value of the MGWR model increased to 0.691, that shows a significant improvement in goodness-of-fit than the global OLS model, which means that spatial heterogeneity of some independent variables is another important factor that influences the relationship with heat-related morbidity in Maricopa County. Among these variables, population aged 65 and older, the Hispanic population, disability, vehicle ownership, and housing occupancy have much stronger local effects than other variables.

Keywords: census, empirical modeling, heat-related morbidity, spatial analysis

Procedia PDF Downloads 105
643 Analysis of Accurate Direct-Estimation of the Maximum Power Point and Thermal Characteristics of High Concentration Photovoltaic Modules

Authors: Yan-Wen Wang, Chu-Yang Chou, Jen-Cheng Wang, Min-Sheng Liao, Hsuan-Hsiang Hsu, Cheng-Ying Chou, Chen-Kang Huang, Kun-Chang Kuo, Joe-Air Jiang

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Performance-related parameters of high concentration photovoltaic (HCPV) modules (e.g. current and voltage) are required when estimating the maximum power point using numerical and approximation methods. The maximum power point on the characteristic curve for a photovoltaic module varies when temperature or solar radiation is different. It is also difficult to estimate the output performance and maximum power point (MPP) due to the special characteristics of HCPV modules. Based on the p-n junction semiconductor theory, a brand new and simple method is presented in this study to directly evaluate the MPP of HCPV modules. The MPP of HCPV modules can be determined from an irradiated I-V characteristic curve, because there is a non-linear relationship between the temperature of a solar cell and solar radiation. Numerical simulations and field tests are conducted to examine the characteristics of HCPV modules during maximum output power tracking. The performance of the presented method is evaluated by examining the dependence of temperature and irradiation intensity on the MPP characteristics of HCPV modules. These results show that the presented method allows HCPV modules to achieve their maximum power and perform power tracking under various operation conditions. A 0.1% error is found between the estimated and the real maximum power point.

Keywords: energy performance, high concentrated photovoltaic, maximum power point, p-n junction semiconductor

Procedia PDF Downloads 554
642 The Effectiveness of Energy-related Tax in Curbing Transport-related Carbon Emissions: The Role of Green Finance and Technology in OECD Economies

Authors: Hassan Taimoor, Piotr Krajewski, Piotr Gabrielzcak

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Being responsible for the largest source of energy-related emissions, the transportation sector is driven by more than half of global oil demand and total energy consumption, making it a crucial factor in tackling climate change and environmental degradation. The present study empirically tests the effectives of the energy-related tax (TXEN) in curbing transport-related carbon emissions (CO2TRANSP) in Organization for Economic Cooperation and Development (OECD) economies over the period of 1990-2020. Moreover, Green Finance (GF), Technology (TECH), and Gross domestic product (GDP) have also been added as explanatory factors which might affect CO2TRANSP emissions. The study employs the Method of Moment Quantile Regression (MMQR), an advance econometric technique to observe the variations along each quantile. Based on the results of the preliminary test, we confirm the presence of cross-sectional dependence and slope heterogeneity. Whereas the result of the panel unit root test report mixed order of variables’ integration. The findings reveal that rise in income level activates CO2TRANSP, confirming the first stage of Environmental Kuznet Hypothesis. Surprisingly, the present TXEN policies of OECD member states are not mature enough to tackle the CO2TRANSP emissions. However, the findings confirm that GF and TECH are solely responsible for the reduction in the CO2TRANSP. The outcomes of Bootstrap Quantile Regression (BSQR) further validate and support the earlier findings of MMQR. Based on the findings of this study, it is revealed that the current TXEN policies are too moderate, and an incremental and progressive rise in TXEN may help in a transition toward a cleaner and sustainable transportation sector in the study region.

Keywords: transport-related CO2 emissions, energy-related tax, green finance, technological development, oecd member states

Procedia PDF Downloads 58
641 Multi-Temporal Mapping of Built-up Areas Using Daytime and Nighttime Satellite Images Based on Google Earth Engine Platform

Authors: S. Hutasavi, D. Chen

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The built-up area is a significant proxy to measure regional economic growth and reflects the Gross Provincial Product (GPP). However, an up-to-date and reliable database of built-up areas is not always available, especially in developing countries. The cloud-based geospatial analysis platform such as Google Earth Engine (GEE) provides an opportunity with accessibility and computational power for those countries to generate the built-up data. Therefore, this study aims to extract the built-up areas in Eastern Economic Corridor (EEC), Thailand using day and nighttime satellite imagery based on GEE facilities. The normalized indices were generated from Landsat 8 surface reflectance dataset, including Normalized Difference Built-up Index (NDBI), Built-up Index (BUI), and Modified Built-up Index (MBUI). These indices were applied to identify built-up areas in EEC. The result shows that MBUI performs better than BUI and NDBI, with the highest accuracy of 0.85 and Kappa of 0.82. Moreover, the overall accuracy of classification was improved from 79% to 90%, and error of total built-up area was decreased from 29% to 0.7%, after night-time light data from the Visible and Infrared Imaging Suite (VIIRS) Day Night Band (DNB). The results suggest that MBUI with night-time light imagery is appropriate for built-up area extraction and be utilize for further study of socioeconomic impacts of regional development policy over the EEC region.

Keywords: built-up area extraction, google earth engine, adaptive thresholding method, rapid mapping

Procedia PDF Downloads 106
640 Agency Cost, Firm Performance, Corporate Governance: Evidence from Indonesia

Authors: Arnold Sanda Layuk

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Fraud in the disclosure of financial statements by management shows that agency conflict is an important issue in the company. The conflict has consequences for the agency costs that must be borne and has an impact on the firm's performance. The effect of agency costs on firm performance is investigated in this study, as well as whether several variables such as corporate governance mechanisms can positively moderate the agency cost and firm performance relationship. The agency cost is measured by the asset utilization ratio and discretionary expenditure ratio. The firm's performance is represented by the return on equity. Data was collected from the manufacturing companies listed on the Indonesia Stock Exchange from 2015 to 2019, then regressed on the panel data using the panel corrected standard error model (PCSE). According to the findings, agency costs are negatively related to firm performance, which supports previous empirical research findings. It also found that the agency cost and firm performance relationship is significantly moderated by board size and ownership concentration as the representatives of corporate governance mechanisms. It suggests that corporate governance can become tools to reduce agency costs and increase firm performance as well. The empirical evidence adds to previous research on agency conflict, particularly in emerging markets. These findings are expected to supplement previous research and provide additional information to shareholders in order to control opportunistic management decisions that affect their investments and discretionary operational expenses.

Keywords: agency cost, corporate governance, asset utilization ratio, firm performance

Procedia PDF Downloads 174
639 Comparative Performance Analysis for Selected Behavioral Learning Systems versus Ant Colony System Performance: Neural Network Approach

Authors: Hassan M. H. Mustafa

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This piece of research addresses an interesting comparative analytical study. Which considers two concepts of diverse algorithmic computational intelligence approaches related tightly with Neural and Non-Neural Systems. The first algorithmic intelligent approach concerned with observed obtained practical results after three neural animal systems’ activities. Namely, they are Pavlov’s, and Thorndike’s experimental work. Besides a mouse’s trial during its movement inside figure of eight (8) maze, to reach an optimal solution for reconstruction problem. Conversely, second algorithmic intelligent approach originated from observed activities’ results for Non-Neural Ant Colony System (ACS). These results obtained after reaching an optimal solution while solving Traveling Sales-man Problem (TSP). Interestingly, the effect of increasing number of agents (either neurons or ants) on learning performance shown to be similar for both introduced systems. Finally, performance of both intelligent learning paradigms shown to be in agreement with learning convergence process searching for least mean square error LMS algorithm. While its application for training some Artificial Neural Network (ANN) models. Accordingly, adopted ANN modeling is a relevant and realistic tool to investigate observations and analyze performance for both selected computational intelligence (biological behavioral learning) systems.

Keywords: artificial neural network modeling, animal learning, ant colony system, traveling salesman problem, computational biology

Procedia PDF Downloads 449
638 Sustainable Agriculture Practices Using Bacterial-mediated Alleviation of Salinity Stress in Crop Plants

Authors: Mohamed Trigui, Fatma Masmoudi, Imen Zouari

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Massive utilizations of chemical fertilizer and chemical pesticides in agriculture sector to improve the farming productivity have created increasing environmental damages. Then, agriculture must become sustainable, focusing on production systems that respect the environment and help to reduce climate change. Isolation and microbial identification of new bacterial strains from naturally saline habitats and compost extracts could be a prominent way in pest management and crop production under saline conditions. In this study, potential mechanisms involved in plant growth promotion and suppressive activity against fungal diseases of a compost extract produced from poultry manure/olive husk compost and halotolerant and halophilic bacterial strains under saline stress were investigated. On the basis of the antimicrobial tests, different strains isolated from Sfax solar saltern (Tunisia) and from compost extracts were selected and tested for their plant growth promoting traits, such as siderophores production, nitrogen fixation, phosphate solubilization and the production of extracellular hydrolytic enzymes (protease and lipase) under in-vitro conditions. Among 450 isolated bacterial strains, 16 isolates showed potent antifungal activity against the tested plant pathogenic fungi. Their identification based on 16S rRNA gene sequence revealed they belonged to different species. Some of these strains were also characterized for their plant growth promoting capacities. Obtained results showed the ability of four strains belonging to Bacillus genesis to ameliorate germination rate and root elongation compared to the untreated positive controls. Combinatorial capacity of halotolerant bacteria with antimicrobial activity and plant growth promoting traits could be promising sources of interesting bioactive substances under saline stress.

Keywords: abiotic stress, biofertilizer, biotic stress, compost extract, halobacteria, plant growth promoting (PGP), soil fertility

Procedia PDF Downloads 71
637 Numerical Modeling of Determination of in situ Rock Mass Deformation Modulus Using the Plate Load Test

Authors: A. Khodabakhshi, A. Mortazavi

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Accurate determination of rock mass deformation modulus, as an important design parameter, is one of the most controversial issues in most engineering projects. A 3D numerical model of standard plate load test (PLT) using the FLAC3D code was carried to investigate the mechanism governing the test process. Five objectives were the focus of this study. The first goal was to employ 3D modeling in the interpretation of PLT conducted at the Bazoft dam site, Iran. The second objective was to investigate the effect of displacements measuring depth from the loading plates on the calculated moduli. The magnitude of rock mass deformation modulus calculated from PLT depends on anchor depth, and in practice, this may be a cause of error in the selection of realistic deformation modulus for the rock mass. The third goal of the study was to investigate the effect of testing plate diameter on the calculated modulus. Moreover, a comparison of the calculated modulus from ISRM formula, numerical modeling and calculated modulus from the actual PLT carried out at right abutment of the Bazoft dam site was another objective of the study. Finally, the effect of plastic strains on the calculated moduli in each of the loading-unloading cycles for three loading plates was investigated. The geometry, material properties, and boundary conditions on the constructed 3D model were selected based on the in-situ conditions of PLT at Bazoft dam site. A good agreement was achieved between numerical model results and the field tests results.

Keywords: deformation modulus, numerical model, plate loading test, rock mass

Procedia PDF Downloads 147
636 Design and Implementation Wireless System by Using Microcontrollers.Application for Drive Acquisition System with Multiple Sensors

Authors: H. Fekhar

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Design and implementation acquisition system using radio frequency (RF) ASK module and micro controllers PIC is proposed in this work. The paper includes hardware and software design. The design tools are divided into two units , namely the sender MCU and receiver.The system was designed to measure temperatures of two furnaces and pressure pneumatic process. The wireless transmitter unit use the 433.95 MHz band directly interfaced to micro controller PIC18F4620. The sender unit consists of temperatures-pressure sensors , conditioning circuits , keypad GLCD display and RF module.Signal conditioner converts the output of the sensors into an electric quantity suitable for operation of the display and recording system.The measurements circuits are connected directly to 10 bits multiplexed A/D converter.The graphic liquid crystal display (GLCD) is used . The receiver (RF) module connected to a second microcontroller ,receive the signal via RF receiver , decode the Address/data and reproduces the original data . The strategy adopted for establishing communication between the sender MCU and receiver uses the specific protocol “Header, Address and data”.The communication protocol dealing with transmission and reception have been successfully implemented . Some experimental results are provided to demonstrate the effectiveness of the proposed wireless system. This embedded system track temperatures – pressure signal reasonably well with a small error.

Keywords: microcontrollers, sensors, graphic liquid cristal display, protocol, temperature, pressure

Procedia PDF Downloads 441
635 Optimized Design, Material Selection, and Improvement of Liners, Mother Plate, and Stone Box of a Direct Charge Transfer Chute in a Sinter Plant: A Computational Approach

Authors: Anamitra Ghosh, Neeladri Paul

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The present work aims at investigating material combinations and thereby improvising an optimized design of liner-mother plate arrangement and that of the stone box, such that it has low cost, high weldability, sufficiently capable of withstanding the increased amount of corrosive shear and bending loads, and having reduced thermal expansion coefficient at temperatures close to 1000 degrees Celsius. All the above factors have been preliminarily examined using a computational approach via ANSYS Thermo-Structural Computation, a commercial software that uses the Finite Element Method to analyze the response of simulated design specimens of liner-mother plate arrangement and the stone box, to varied bending, shear, and thermal loads as well as to determine the temperature gradients developed across various surfaces of the designs. Finally, the optimized structural designs of the liner-mother plate arrangement and that of the stone box with improved material and better structural and thermal properties are selected via trial-and-error method. The final improvised design is therefore considered to enhance the overall life and reliability of a Direct Charge Transfer Chute that transfers and segregates the hot sinter onto the cooler in a sinter plant.

Keywords: shear, bending, thermal, sinter, simulated, optimized, charge, transfer, chute, expansion, computational, corrosive, stone box, liner, mother plate, arrangement, material

Procedia PDF Downloads 91