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Sample records for machining parameter study

  1. Comparative study for different statistical models to optimize cutting parameters of CNC end milling machines

    International Nuclear Information System (INIS)

    El-Berry, A.; El-Berry, A.; Al-Bossly, A.

    2010-01-01

    In machining operation, the quality of surface finish is an important requirement for many work pieces. Thus, that is very important to optimize cutting parameters for controlling the required manufacturing quality. Surface roughness parameter (Ra) in mechanical parts depends on turning parameters during the turning process. In the development of predictive models, cutting parameters of feed, cutting speed, depth of cut, are considered as model variables. For this purpose, this study focuses on comparing various machining experiments which using CNC vertical machining center, work pieces was aluminum 6061. Multiple regression models are used to predict the surface roughness at different experiments.

  2. Pre-segmented 2-Step IMRT with subsequent direct machine parameter optimisation – a planning study

    International Nuclear Information System (INIS)

    Bratengeier, Klaus; Meyer, Jürgen; Flentje, Michael

    2008-01-01

    Modern intensity modulated radiotherapy (IMRT) mostly uses iterative optimisation methods. The integration of machine parameters into the optimisation process of step and shoot leaf positions has been shown to be successful. For IMRT segmentation algorithms based on the analysis of the geometrical structure of the planning target volumes (PTV) and the organs at risk (OAR), the potential of such procedures has not yet been fully explored. In this work, 2-Step IMRT was combined with subsequent direct machine parameter optimisation (DMPO-Raysearch Laboratories, Sweden) to investigate this potential. In a planning study DMPO on a commercial planning system was compared with manual primary 2-Step IMRT segment generation followed by DMPO optimisation. 15 clinical cases and the ESTRO Quasimodo phantom were employed. Both the same number of optimisation steps and the same set of objective values were used. The plans were compared with a clinical DMPO reference plan and a traditional IMRT plan based on fluence optimisation and consequent segmentation. The composite objective value (the weighted sum of quadratic deviations of the objective values and the related points in the dose volume histogram) was used as a measure for the plan quality. Additionally, a more extended set of parameters was used for the breast cases to compare the plans. The plans with segments pre-defined with 2-Step IMRT were slightly superior to DMPO alone in the majority of cases. The composite objective value tended to be even lower for a smaller number of segments. The total number of monitor units was slightly higher than for the DMPO-plans. Traditional IMRT fluence optimisation with subsequent segmentation could not compete. 2-Step IMRT segmentation is suitable as starting point for further DMPO optimisation and, in general, results in less complex plans which are equal or superior to plans generated by DMPO alone

  3. A comparative study on optimization of machining parameters by turning aerospace materials according to Taguchi method

    Directory of Open Access Journals (Sweden)

    Altin Abdullah

    2017-01-01

    Full Text Available The effects of cutting tool coating material and cutting speed on cutting forces and surface roughness were investigated by Taguchi experimental design. Main cutting force, Fz is considered as a criterion. The effects of machining parameters were investigated using Taguchi L18 orthogonal array. Optimal cutting conditions were determined using the signal-to-noise (S/N ratio which is calculated for average surface roughness and cutting force according to the “the smaller is better” approach. Using results of analysis of variance (ANOVA and signal-to-noise (S/N ratio, effects of parameters on both average surface roughness and cutting forces were statistically investigated. It was observed that feed rate and cutting speed had higher effect on cutting force in Hastelloy X, while the feed rate and cutting tool had higher effect on cutting force in Inconel 625. According to average surface roughness the cutting tool and feed rate had higher effect in Hastelloy X and Inconel 625.

  4. Machine parameters and characteristic features

    International Nuclear Information System (INIS)

    Le Duff, J.

    1979-01-01

    The design and operating characteristics of LEP are presented. Its probable performance, possible improvements and cost are discussed and some comparisons are drawn with machines currently in operation. (W.D.L.)

  5. Experimental study on Response Parameters of Ni-rich NiTi Shape Memory Alloy during Wire Electric Discharge Machining

    Science.gov (United States)

    Bisaria, Himanshu; Shandilya, Pragya

    2018-03-01

    Nowadays NiTi SMAs are gaining more prominence due to their unique properties such as superelasticity, shape memory effect, high fatigue strength and many other enriched physical and mechanical properties. The current studies explore the effect of machining parameters namely, peak current (Ip), pulse off time (TOFF), and pulse on time (TON) on wire wear ratio (WWR), and dimensional deviation (DD) in WEDM. It was found that high discharge energy was mainly ascribed to high WWR and DD. The WWR and DD increased with the increase in pulse on time and peak current whereas high pulse off time was favourable for low WWR and DD.

  6. A Comparative Experimental Study on the Use of Machine Learning Approaches for Automated Valve Monitoring Based on Acoustic Emission Parameters

    Science.gov (United States)

    Ali, Salah M.; Hui, K. H.; Hee, L. M.; Salman Leong, M.; Al-Obaidi, M. A.; Ali, Y. H.; Abdelrhman, Ahmed M.

    2018-03-01

    Acoustic emission (AE) analysis has become a vital tool for initiating the maintenance tasks in many industries. However, the analysis process and interpretation has been found to be highly dependent on the experts. Therefore, an automated monitoring method would be required to reduce the cost and time consumed in the interpretation of AE signal. This paper investigates the application of two of the most common machine learning approaches namely artificial neural network (ANN) and support vector machine (SVM) to automate the diagnosis of valve faults in reciprocating compressor based on AE signal parameters. Since the accuracy is an essential factor in any automated diagnostic system, this paper also provides a comparative study based on predictive performance of ANN and SVM. AE parameters data was acquired from single stage reciprocating air compressor with different operational and valve conditions. ANN and SVM diagnosis models were subsequently devised by combining AE parameters of different conditions. Results demonstrate that ANN and SVM models have the same results in term of prediction accuracy. However, SVM model is recommended to automate diagnose the valve condition in due to the ability of handling a high number of input features with low sampling data sets.

  7. QSPR studies for predicting polarity parameter of organic compounds in methanol using support vector machine and enhanced replacement method.

    Science.gov (United States)

    Golmohammadi, H; Dashtbozorgi, Z

    2016-12-01

    In the present work, enhanced replacement method (ERM) and support vector machine (SVM) were used for quantitative structure-property relationship (QSPR) studies of polarity parameter (p) of various organic compounds in methanol in reversed phase liquid chromatography based on molecular descriptors calculated from the optimized structures. Diverse kinds of molecular descriptors were calculated to encode the molecular structures of compounds, such as geometric, thermodynamic, electrostatic and quantum mechanical descriptors. The variable selection method of ERM was employed to select an optimum subset of descriptors. The five descriptors selected using ERM were used as inputs of SVM to predict the polarity parameter of organic compounds in methanol. The coefficient of determination, r 2 , between experimental and predicted polarity parameters for the prediction set by ERM and SVM were 0.952 and 0.982, respectively. Acceptable results specified that the ERM approach is a very effective method for variable selection and the predictive aptitude of the SVM model is superior to those obtained by ERM. The obtained results demonstrate that SVM can be used as a substitute influential modeling tool for QSPR studies.

  8. Foam application from a closed system – a study of machine and foam parameters

    NARCIS (Netherlands)

    Lemmen, Jacques T.E.; Groot Wassink, Jan

    1990-01-01

    An attempt has been made to gain a greater insight into the interaction between foam and a moving textile substrate. The effects of changing wet pick–up, fabric velocity, liquid viscosity, foam density and mode of application on penetration have been studied. Application from a closed system makes

  9. ANALYSIS OF PARAMETERS AFFECTING THE QUALITY OF A CUTTING MACHINE

    Directory of Open Access Journals (Sweden)

    Iveta Onderová

    2014-02-01

    Full Text Available The quality of cutting machines is affected by several factors that can be directly or indirectly influenced by manufacturers, technicians and users of machine tools. The most critical qualitative evaluation parameters of machine tools include accuracy and stability. Investigations of accuracy and repeatable positioning accuracy were essential for the research presented in this paper. The aim was to develop and experimentally verify the design of a methodology for cutting centers aimed at achieving the desired working precision. Before working on the topic described here, it was necessary to make several scientific analyses, which are summarized in this paper. We can build on the initial working hypothesis that by improving the technological parameters (e.g. by increasing the working speed of the machine, or by improving the precision of the positioning the quality of the cutting machine will also be improved. For the purposes of our study, several investigated parameters were set affecting positioning accuracy, such as rigidity, positioning speed, etc. First, the stiffness of the portal structure of the cutting machine was analyzed. FEM analysis was used to investigate several alternative structures of the cutting machine, and also an innovative solution for beam mounting. The second step was to integrate two types of drives into the design of the cutting machine. The first drive is a classic rack and pinion drive for cutting machines. To increase (improve the working speed of the machine, linear motors were designed as an alternative drive. The portal of the cutting machine was designed for a working speed of 260mmin−1 and acceleration of 25 m. s−2. The third step was based on the results of the analysis. In collaboration with Microstep, an experimental cutting machine in a portal version was produced using linear synchronous motors driving the portal on both sides, and with direct linear metering of its position. In the fourth step, an

  10. Online State Space Model Parameter Estimation in Synchronous Machines

    Directory of Open Access Journals (Sweden)

    Z. Gallehdari

    2014-06-01

    The suggested approach is evaluated for a sample synchronous machine model. Estimated parameters are tested for different inputs at different operating conditions. The effect of noise is also considered in this study. Simulation results show that the proposed approach provides good accuracy for parameter estimation.

  11. ASCERTAINMENT OF THE EQUIVALENT CIRCUIT PARAMETERS OF THE ASYNCHRONOUS MACHINE

    Directory of Open Access Journals (Sweden)

    V. S. Safaryan

    2015-01-01

    Full Text Available The article considers experimental and analytical determination of the asynchronous machine equivalent-circuit parameters with application of the reference data. Transient processes investigation of the asynchronous machines necessitates the equivalent circuit parameters (resistance impedance, inductances and coefficient of the stator-rotor contours mutual inductance that help form the transitory-process mathematical simulation model. The reference books do not provide those parameters; they instead give the rated ones (active power, voltage, slide, coefficient of performance and capacity coefficient as well as the ratio of starting and nominal currents and torques. The noted studies on the asynchronous machine equivalent-circuits parametrization fail to solve the problems ad finem or solve them with admissions. The paper presents experimental and analytical determinations of the asynchronous machine equivalent-circuit parameters: the experimental one based on the results of two measurements and the analytical one where the problem boils down to solving a system of nonlineal algebraic equations. The authors investigate the equivalent asynchronous machine input-resistance properties and adduce the dependence curvatures of the input-resistances on the slide. They present a symbolic model for analytical parameterization of the asynchronous machine equivalent-circuit that represents a system of nonlineal equations and requires one of the rotor-parameters arbitrary assignment. The article demonstrates that for the asynchronous machine equivalent-circuit experimental parameterization the measures are to be conducted of the stator-circuit voltage, current and active power with two different slides and arbitrary assignment of one of the rotor parameters. The paper substantiates the fact that additional measurement does not discard the rotor-parameter choice arbitrariness. The authors establish that in motoring mode there is a critical slide by which the

  12. Precision Parameter Estimation and Machine Learning

    Science.gov (United States)

    Wandelt, Benjamin D.

    2008-12-01

    I discuss the strategy of ``Acceleration by Parallel Precomputation and Learning'' (AP-PLe) that can vastly accelerate parameter estimation in high-dimensional parameter spaces and costly likelihood functions, using trivially parallel computing to speed up sequential exploration of parameter space. This strategy combines the power of distributed computing with machine learning and Markov-Chain Monte Carlo techniques efficiently to explore a likelihood function, posterior distribution or χ2-surface. This strategy is particularly successful in cases where computing the likelihood is costly and the number of parameters is moderate or large. We apply this technique to two central problems in cosmology: the solution of the cosmological parameter estimation problem with sufficient accuracy for the Planck data using PICo; and the detailed calculation of cosmological helium and hydrogen recombination with RICO. Since the APPLe approach is designed to be able to use massively parallel resources to speed up problems that are inherently serial, we can bring the power of distributed computing to bear on parameter estimation problems. We have demonstrated this with the CosmologyatHome project.

  13. Synchronous machine parameter identification in frequency and time domain

    Directory of Open Access Journals (Sweden)

    Hasni M.

    2007-01-01

    Full Text Available This paper presents the results of a frequency and time-domain identification procedure to estimate the linear parameters of a salient-pole synchronous machine at standstill. The objective of this study is to use several input signals to identify the model structure and parameters of a salient-pole synchronous machine from standstill test data. The procedure consists to define, to conduct the standstill tests and also to identify the model structure. The signals used for identification are the different excitation voltages at standstill and the flowing current in different windings. We estimate the parameters of operational impedances, or in other words the reactance and the time constants. The tests were carried out on synchronous machine of 1.5 kVA 380V 1500 rpm.

  14. Machinability study of Carbon Fiber Reinforced Polymer in the longitudinal and transverse direction and optimization of process parameters using PSO–GSA

    Directory of Open Access Journals (Sweden)

    K. Shunmugesh

    2016-09-01

    Full Text Available Carbon Fiber Reinforced Polymer (CFRP composites are widely used in aerospace industry in lieu of its high strength to weight ratio. This study is an attempt to evaluate the machinability of Bi-Directional Carbon Fiber–Epoxy composite and optimize the process parameters of cutting speed, feed rate and drill tool material. Machining trials were carried using drill bits made of high speed steel, TiN and TiAlN at different cutting speeds and feed rates. Output parameters of thrust force and torque were monitored using Kistler multicomponent dynamometer 9257B and vibrations occurring during machining normal to the work surface were measured by a vibration sensor (Dytran 3055B. Linear regression analysis was carried out by using Response Surface Methodology (RSM, to correlate the input and output parameters in drilling of the composite in the longitudinal and transverse directions. The optimization of process parameters were attempted using Genetic Algorithm (GA and Particle Swarm Optimization–Gravitational Search Algorithm (PSO–GSA techniques.

  15. Numerical identifiability of the parameters of induction machines

    Energy Technology Data Exchange (ETDEWEB)

    Corcoles, F.; Pedra, J.; Salichs, M. [Dep. d' Eng. Electrica ETSEIB. UPC, Barcelona (Spain)

    2000-08-01

    This paper analyses the numerical identifiability of the electrical parameters of induction machines. Relations between parameters and the impossibility to estimate all of them - when only external measures are used: voltage, current, speed and torque - are shown. Formulations of the single and double-cage induction machine, with and without core losses in both models, are developed. The proposed solution is the formulation of machine equations by using the minimum number of parameters (which are identifiable parameters). As an application example, the parameters of a double-cage induction machine are identified using steady-state measurements corresponding to different angular speeds. (orig.)

  16. Parameter optimization of electrochemical machining process using black hole algorithm

    Science.gov (United States)

    Singh, Dinesh; Shukla, Rajkamal

    2017-12-01

    Advanced machining processes are significant as higher accuracy in machined component is required in the manufacturing industries. Parameter optimization of machining processes gives optimum control to achieve the desired goals. In this paper, electrochemical machining (ECM) process is considered to evaluate the performance of the considered process using black hole algorithm (BHA). BHA considers the fundamental idea of a black hole theory and it has less operating parameters to tune. The two performance parameters, material removal rate (MRR) and overcut (OC) are considered separately to get optimum machining parameter settings using BHA. The variations of process parameters with respect to the performance parameters are reported for better and effective understanding of the considered process using single objective at a time. The results obtained using BHA are found better while compared with results of other metaheuristic algorithms, such as, genetic algorithm (GA), artificial bee colony (ABC) and bio-geography based optimization (BBO) attempted by previous researchers.

  17. Multi-Parameter Analysis of Surface Finish in Electro-Discharge Machining of Tool Steels

    Directory of Open Access Journals (Sweden)

    Cornelia Victoria Anghel

    2006-10-01

    Full Text Available The paper presents a multi- parameter analysis of surface finish imparted to tool-steel plates by electro-discharge machining (EDM is presented. The interrelationship between surface texture parameters and process parameters is emphasized. An increased number of parameters is studied including amplitude, spacing, hybrid and fractal parameters,, as well. The correlation of these parameters with the machining conditions is investigated. Observed characteristics become more pronounced, when intensifying machining conditions. Close correlation exists between certain surface finish parameters and EDM input variables and single and multiple statistical regression models are developed.

  18. Operation and machine studies

    International Nuclear Information System (INIS)

    1992-01-01

    This annual report describes the GANIL (Grand accelerateur national d'ions lourds, Caen, France) operation and the machine studies realized in 1992. Metallic ions have been accelerated during 36 pc of the time; some were produced for the first time at GANIL: 125 Te, 52 Cr with ECR3, 181 Ta with ECR4. The various machine studies are: comparison of lifetimes of carbon sheets, charge exchange of very heavy ions in carbon foils and in the residual gas of the Ganil cyclotrons, commissioning of the new high intensity axial injection system for Ganil, tantalum acceleration with the new injector, a cyclotron as a mass spectrometer; other studies concerned: implementing the new control system, gettering flux measurement, energy deposited by neutrons and gamma rays in the cryogenic system of SISSI; latest developments on multicharged ECR ion sources, and an on-line isotopic separator test bench at Ganil

  19. Optimization of machining parameters of hard porcelain on a CNC ...

    African Journals Online (AJOL)

    Optimization of machining parameters of hard porcelain on a CNC machine by Taguchi-and RSM method. ... Journal Home > Vol 10, No 1 (2018) > ... The conduct of experiments was made by employing the Taguchi's L27 Orthogonal array to ...

  20. Session 2: Machine studies

    International Nuclear Information System (INIS)

    Assmann, R.W.; Papotti, G.

    2012-01-01

    This document summarizes the talks and discussion that took place in the second session of the Chamonix 2012 workshop concerning results from machine studies performed in 2011. The session consisted of the following presentations: -) LHC experience with different bunch spacings by G. Rumolo; -) Observations of beam-beam effects in MDs in 2011 by W. Herr; -) Beam-induced heating/ bunch length/RF and lessons for 2012 by E. Metral; -) Lessons in beam diagnostics by R. Jones; -) Quench margins by M. Sapinski; and -) First demonstration with beam of the Achromatic Telescopic Squeeze (ATS) by S. Fartoukh. (authors)

  1. Peak thrust operation of linear induction machines from parameter identification

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Z.; Eastham, T.R.; Dawson, G.E. [Queen`s Univ., Kingston, Ontario (Canada). Dept. of Electrical and Computer Engineering

    1995-12-31

    Various control strategies are being used to achieve high performance operation of linear drives. To maintain minimum volume and weight of the power supply unit on board the transportation vehicle, peak thrust per unit current operation is a desirable objective. True peak thrust per unit current through slip control is difficult to achieve because the parameters of linear induction machines vary during normal operation. This paper first develops a peak thrust per unit current control law based on the per-phase equivalent circuit for linear induction machines. The algorithm for identification of the variable parameters in induction machines is then presented. Application to an operational linear induction machine (LIM) demonstrates the utility of this algorithm. The control strategy is then simulated, based on an operational transit LIM, to show the capability of achieving true peak thrust operation for linear induction machines.

  2. Machine learning action parameters in lattice quantum chromodynamics

    Science.gov (United States)

    Shanahan, Phiala E.; Trewartha, Daniel; Detmold, William

    2018-05-01

    Numerical lattice quantum chromodynamics studies of the strong interaction are important in many aspects of particle and nuclear physics. Such studies require significant computing resources to undertake. A number of proposed methods promise improved efficiency of lattice calculations, and access to regions of parameter space that are currently computationally intractable, via multi-scale action-matching approaches that necessitate parametric regression of generated lattice datasets. The applicability of machine learning to this regression task is investigated, with deep neural networks found to provide an efficient solution even in cases where approaches such as principal component analysis fail. The high information content and complex symmetries inherent in lattice QCD datasets require custom neural network layers to be introduced and present opportunities for further development.

  3. Selection of parameters for advanced machining processes using firefly algorithm

    Directory of Open Access Journals (Sweden)

    Rajkamal Shukla

    2017-02-01

    Full Text Available Advanced machining processes (AMPs are widely utilized in industries for machining complex geometries and intricate profiles. In this paper, two significant processes such as electric discharge machining (EDM and abrasive water jet machining (AWJM are considered to get the optimum values of responses for the given range of process parameters. The firefly algorithm (FA is attempted to the considered processes to obtain optimized parameters and the results obtained are compared with the results given by previous researchers. The variation of process parameters with respect to the responses are plotted to confirm the optimum results obtained using FA. In EDM process, the performance parameter “MRR” is increased from 159.70 gm/min to 181.6723 gm/min, while “Ra” and “REWR” are decreased from 6.21 μm to 3.6767 μm and 6.21% to 6.324 × 10−5% respectively. In AWJM process, the value of the “kerf” and “Ra” are decreased from 0.858 mm to 0.3704 mm and 5.41 mm to 4.443 mm respectively. In both the processes, the obtained results show a significant improvement in the responses.

  4. Effect of machining parameters on surface finish of Inconel 718 in end milling

    Directory of Open Access Journals (Sweden)

    Sarkar Bapi

    2017-01-01

    Full Text Available Surface finish is an important criteria in machining process and selection of proper machining parameters is important to obtain good surface finish. In the present work effects of the machining parameters in end milling of Inconel 718 were investigated. Central composite design was used to design the total number of experiments. A Mathematical model for surface roughness has been developed using response surface methodology. In this study, the influence of cutting parameters such as cutting speed, feed rate and depth of cut on surface roughness was analyzed. The study includes individual effect of cutting parameters on surface roughness as well as their interaction. The analysis of variance (ANOVA was employed to find the validity of the developed model. The results show that depth of cut mostly affected the surface roughness. It is also observed that surface roughness values are comparable in both dry and wet machining conditions.

  5. Catalytic aided electrical discharge machining of polycrystalline diamond - parameter analysis of finishing condition

    Science.gov (United States)

    Haikal Ahmad, M. A.; Zulafif Rahim, M.; Fauzi, M. F. Mohd; Abdullah, Aslam; Omar, Z.; Ding, Songlin; Ismail, A. E.; Rasidi Ibrahim, M.

    2018-01-01

    Polycrystalline diamond (PCD) is regarded as among the hardest material in the world. Electrical Discharge Machining (EDM) typically used to machine this material because of its non-contact process nature. This investigation was purposely done to compare the EDM performances of PCD when using normal electrode of copper (Cu) and newly proposed graphitization catalyst electrode of copper nickel (CuNi). Two level full factorial design of experiment with 4 center points technique was used to study the influence of main and interaction effects of the machining parameter namely; pulse-on, pulse-off, sparking current, and electrode materials (categorical factor). The paper shows interesting discovery in which the newly proposed electrode presented positive impact to the machining performance. With the same machining parameters of finishing, CuNi delivered more than 100% better in Ra and MRR than ordinary Cu electrode.

  6. AC machine control : robust and sensorless control by parameter independency

    Energy Technology Data Exchange (ETDEWEB)

    Samuelsen, Dag Andreas Hals

    2009-06-15

    In this thesis it is first presented how robust control can be used to give AC motor drive systems competitive dynamic performance under parameter variations. These variations are common to all AC machines, and are a result of temperature change in the machine, and imperfect machine models. This robust control is, however, dependent on sensor operation in the sense that the rotor position is needed in the control loop. Elimination of this control loop has been for many years, and still is, a main research area of AC machines control systems. An integrated PWM modulator and sampler unit has been developed and tested. The sampler unit is able to give current and voltage measurements with a reduced noise component. It is further used to give the true derivative of currents and voltages in the machine and the power converter, as an average over a PWM period, and as separate values for all states of the power converter. In this way, it can give measurements of the currents as well as the derivative of the currents, at the start and at the end of a single power inverter state. This gave a large degree of freedom in parameter and state identification during uninterrupted operation of the induction machine. The special measurement scheme of the system achieved three main goals: By avoiding the time frame where the transistors commutate and the noise in the measurement of the current is large, filtering of the current measurement is no longer needed. The true derivative of the current in the machine is can be measured with far less noise components. This was extended to give any separate derivative in all three switching states of the power converter. Using the computational resources of the FPGA, more advanced information was supplied to the control system, in order to facilitate sensor less operation, with low computational demands on the DSP. As shown in the papers, this extra information was first used to estimate some of the states of the machine, in some or all of the

  7. Machine-learned and codified synthesis parameters of oxide materials

    Science.gov (United States)

    Kim, Edward; Huang, Kevin; Tomala, Alex; Matthews, Sara; Strubell, Emma; Saunders, Adam; McCallum, Andrew; Olivetti, Elsa

    2017-09-01

    Predictive materials design has rapidly accelerated in recent years with the advent of large-scale resources, such as materials structure and property databases generated by ab initio computations. In the absence of analogous ab initio frameworks for materials synthesis, high-throughput and machine learning techniques have recently been harnessed to generate synthesis strategies for select materials of interest. Still, a community-accessible, autonomously-compiled synthesis planning resource which spans across materials systems has not yet been developed. In this work, we present a collection of aggregated synthesis parameters computed using the text contained within over 640,000 journal articles using state-of-the-art natural language processing and machine learning techniques. We provide a dataset of synthesis parameters, compiled autonomously across 30 different oxide systems, in a format optimized for planning novel syntheses of materials.

  8. Study on spectral parameters and the support vector machine in surface enhanced Raman spectroscopy of serum for the detection of colon cancer

    International Nuclear Information System (INIS)

    Li, Xiaozhou; Yang, Tianyue; Yao, Jun; Wang, Deli; Li, Siqi; Song, Youtao; Ding, Jianhua

    2015-01-01

    Surface enhanced Raman spectroscopy (SERS) has been recognized as an effective tool for the analysis of tissue samples and biofluids. In this work, a total of 27 spectral parameters were chosen and compared using SERS. Four parameters with the highest prediction ability were selected for further support vector machine (SVM) analysis. As a comparison, principal component analysis (PCA) was used on the same dataset for feature extraction. SVM was used with the above two data reduction methods separately to differentiate colon cancer and the control groups. Serum taken from 52 colon cancer patients and 60 healthy volunteers were collected and tested by SERS. The accuracy for Parameter-SVM was 95.0%, the sensitivity was 96.2%, and the specificity was 95.5%, which was much higher than the results using only one parameter, while for PCA-SVM, the results are 93.3%, 92.3%, and 92.9%, respectively. These results demonstrate that the SERS analysis method can be used to identify serum differences between colon cancer patients and normal people. (letter)

  9. Influence of TiB2 particles on machinability and machining parameter optimization of TiB2/Al MMCs

    Directory of Open Access Journals (Sweden)

    Ruisong JIANG

    2018-01-01

    Full Text Available In situ formed TiB2 particle reinforced aluminum matrix composites (TiB2/Al MMCs have some extraordinary properties which make them be a promising material for high performance aero-engine blade. Due to the influence of TiB2 particles, the machinability is still a problem which restricts the application of TiB2/Al MMCs. In order to meet the industrial requirements, the influence of TiB2 particles on the machinability of TiB2/Al MMCs was investigated experimentally. Moreover, the optimal machining conditions for this kind of MMCs were investigated in this study. The major conclusions are: (1 the machining force of TiB2/Al MMCs is bigger than that of non-reinforced alloy and mainly controlled by feed rate; (2 the residual stress of TiB2/Al MMCs is compressive while that of non-reinforced alloy is nearly neutral; (3 the surface roughness of TiB2/Al MMCs is smaller than that of non-reinforced alloy under the same cutting speed, but reverse result was observed when the feed rate increased; (4 a multi-objective optimization model for surface roughness and material removal rate (MRR was established, and a set of optimal parameter combinations of the machining was obtained. The results show a great difference from SiC particle reinforced MMCs and provide a useful guide for a better control of machining process of this material.

  10. Machine learning of the reactor core loading pattern critical parameters

    International Nuclear Information System (INIS)

    Trontl, K.; Pevec, D.; Smuc, T.

    2007-01-01

    The usual approach to loading pattern optimization involves high degree of engineering judgment, a set of heuristic rules, an optimization algorithm and a computer code used for evaluating proposed loading patterns. The speed of the optimization process is highly dependent on the computer code used for the evaluation. In this paper we investigate the applicability of a machine learning model which could be used for fast loading pattern evaluation. We employed a recently introduced machine learning technique, Support Vector Regression (SVR), which has a strong theoretical background in statistical learning theory. Superior empirical performance of the method has been reported on difficult regression problems in different fields of science and technology. SVR is a data driven, kernel based, nonlinear modelling paradigm, in which model parameters are automatically determined by solving a quadratic optimization problem. The main objective of the work reported in this paper was to evaluate the possibility of applying SVR method for reactor core loading pattern modelling. The starting set of experimental data for training and testing of the machine learning algorithm was obtained using a two-dimensional diffusion theory reactor physics computer code. We illustrate the performance of the solution and discuss its applicability, i.e., complexity, speed and accuracy, with a projection to a more realistic scenario involving machine learning from the results of more accurate and time consuming three-dimensional core modelling code. (author)

  11. Machine Learning of the Reactor Core Loading Pattern Critical Parameters

    Directory of Open Access Journals (Sweden)

    Krešimir Trontl

    2008-01-01

    Full Text Available The usual approach to loading pattern optimization involves high degree of engineering judgment, a set of heuristic rules, an optimization algorithm, and a computer code used for evaluating proposed loading patterns. The speed of the optimization process is highly dependent on the computer code used for the evaluation. In this paper, we investigate the applicability of a machine learning model which could be used for fast loading pattern evaluation. We employ a recently introduced machine learning technique, support vector regression (SVR, which is a data driven, kernel based, nonlinear modeling paradigm, in which model parameters are automatically determined by solving a quadratic optimization problem. The main objective of the work reported in this paper was to evaluate the possibility of applying SVR method for reactor core loading pattern modeling. We illustrate the performance of the solution and discuss its applicability, that is, complexity, speed, and accuracy.

  12. Machine Learning of the Reactor Core Loading Pattern Critical Parameters

    International Nuclear Information System (INIS)

    Trontl, K.; Pevec, D.; Smuc, T.

    2008-01-01

    The usual approach to loading pattern optimization involves high degree of engineering judgment, a set of heuristic rules, an optimization algorithm, and a computer code used for evaluating proposed loading patterns. The speed of the optimization process is highly dependent on the computer code used for the evaluation. In this paper, we investigate the applicability of a machine learning model which could be used for fast loading pattern evaluation. We employ a recently introduced machine learning technique, support vector regression (SVR), which is a data driven, kernel based, nonlinear modeling paradigm, in which model parameters are automatically determined by solving a quadratic optimization problem. The main objective of the work reported in this paper was to evaluate the possibility of applying SVR method for reactor core loading pattern modeling. We illustrate the performance of the solution and discuss its applicability, that is, complexity, speed, and accuracy

  13. Determination of Machining Parameters of Corn Byproduct Filled Plastics

    Science.gov (United States)

    In a collaborative project between the USDA and Northern Illinois University, the use of ethanol corn processing by-products as bio-filler materials in the compression molding of phenolic plastics has been studied. This paper reports on the results of a machinability study in the milling of various ...

  14. Determining Machining Parameters of Corn Byproduct Filled Plastics

    Science.gov (United States)

    In a collaborative project between the USDA and Northern Illinois University, the use of corn ethanol processing byproducts (i.e., DDGS) as bio-filler materials in the compression molding of phenolic plastics has been studied. This paper reports on the results of a machinability study in the milling...

  15. Influence of electrical resistivity and machining parameters on electrical discharge machining performance of engineering ceramics.

    Science.gov (United States)

    Ji, Renjie; Liu, Yonghong; Diao, Ruiqiang; Xu, Chenchen; Li, Xiaopeng; Cai, Baoping; Zhang, Yanzhen

    2014-01-01

    Engineering ceramics have been widely used in modern industry for their excellent physical and mechanical properties, and they are difficult to machine owing to their high hardness and brittleness. Electrical discharge machining (EDM) is the appropriate process for machining engineering ceramics provided they are electrically conducting. However, the electrical resistivity of the popular engineering ceramics is higher, and there has been no research on the relationship between the EDM parameters and the electrical resistivity of the engineering ceramics. This paper investigates the effects of the electrical resistivity and EDM parameters such as tool polarity, pulse interval, and electrode material, on the ZnO/Al2O3 ceramic's EDM performance, in terms of the material removal rate (MRR), electrode wear ratio (EWR), and surface roughness (SR). The results show that the electrical resistivity and the EDM parameters have the great influence on the EDM performance. The ZnO/Al2O3 ceramic with the electrical resistivity up to 3410 Ω·cm can be effectively machined by EDM with the copper electrode, the negative tool polarity, and the shorter pulse interval. Under most machining conditions, the MRR increases, and the SR decreases with the decrease of electrical resistivity. Moreover, the tool polarity, and pulse interval affect the EWR, respectively, and the electrical resistivity and electrode material have a combined effect on the EWR. Furthermore, the EDM performance of ZnO/Al2O3 ceramic with the electrical resistivity higher than 687 Ω·cm is obviously different from that with the electrical resistivity lower than 687 Ω·cm, when the electrode material changes. The microstructure character analysis of the machined ZnO/Al2O3 ceramic surface shows that the ZnO/Al2O3 ceramic is removed by melting, evaporation and thermal spalling, and the material from the working fluid and the graphite electrode can transfer to the workpiece surface during electrical discharge

  16. Justification for parameters of a dynamic stabilizer of the experimental stand mobile unit in studying of active rotational working tools of tiller machines

    Directory of Open Access Journals (Sweden)

    Vladimir F. Kupryashkin

    2017-03-01

    Full Text Available Introduction: The article deals with design options and technological modes of the dynamic stabilizer of the experimental stand mobile unit for studying tillage machine active rotating work tools. Based on theoretical and experimental studies, the possibility the movable module instability was discovered. This negatively affects on implementing the experiment program trough the especific method. The need in engineering solutions for the defect correction is shown. In addition, the authors consider the structural features and characteristics of the used devices for providing the stabilization of the movable module in the study of active rotating work tools of tillage machines. An electromagnetic brake dynamic stabilizer in the structure of the existing rolling module was proposed as an engineering device. Materials and Methods: A theoretical study of rolling module stability, based on synthesis of basic regulations and laws of mechanics related to active rotating work tools was conducted. As a result of the theoretical research, a design scheme of movable module loading was created. This scheme includes the design features and structural power factors. Results: A database representing the settings of power specification in the motion stability determining the mobile unit was created. Further use of the database values allow supporting the most optimal location of the electromagnetic brake with its design options. Discussion and Conclusions: The research of the electromagnetic brake in a mobile unit promoted stabilizing the unit movement, increased the frequency of its use and provided data that are more precise during experiments.

  17. Optimization of the Machining parameter of LM6 Alminium alloy in CNC Turning using Taguchi method

    Science.gov (United States)

    Arunkumar, S.; Muthuraman, V.; Baskaralal, V. P. M.

    2017-03-01

    Due to widespread use of highly automated machine tools in the industry, manufacturing requires reliable models and methods for the prediction of output performance of machining process. In machining of parts, surface quality is one of the most specified customer requirements. In order for manufactures to maximize their gains from utilizing CNC turning, accurate predictive models for surface roughness must be constructed. The prediction of optimum machining conditions for good surface finish plays an important role in process planning. This work deals with the study and development of a surface roughness prediction model for machining LM6 aluminum alloy. Two important tools used in parameter design are Taguchi orthogonal arrays and signal to noise ratio (S/N). Speed, feed, depth of cut and coolant are taken as process parameter at three levels. Taguchi’s parameters design is employed here to perform the experiments based on the various level of the chosen parameter. The statistical analysis results in optimum parameter combination of speed, feed, depth of cut and coolant as the best for obtaining good roughness for the cylindrical components. The result obtained through Taguchi is confirmed with real time experimental work.

  18. Optimal Parameter Selection for Support Vector Machine Based on Artificial Bee Colony Algorithm: A Case Study of Grid-Connected PV System Power Prediction

    Directory of Open Access Journals (Sweden)

    Xiang-ming Gao

    2017-01-01

    Full Text Available Predicting the output power of photovoltaic system with nonstationarity and randomness, an output power prediction model for grid-connected PV systems is proposed based on empirical mode decomposition (EMD and support vector machine (SVM optimized with an artificial bee colony (ABC algorithm. First, according to the weather forecast data sets on the prediction date, the time series data of output power on a similar day with 15-minute intervals are built. Second, the time series data of the output power are decomposed into a series of components, including some intrinsic mode components IMFn and a trend component Res, at different scales using EMD. The corresponding SVM prediction model is established for each IMF component and trend component, and the SVM model parameters are optimized with the artificial bee colony algorithm. Finally, the prediction results of each model are reconstructed, and the predicted values of the output power of the grid-connected PV system can be obtained. The prediction model is tested with actual data, and the results show that the power prediction model based on the EMD and ABC-SVM has a faster calculation speed and higher prediction accuracy than do the single SVM prediction model and the EMD-SVM prediction model without optimization.

  19. Optimal Parameter Selection for Support Vector Machine Based on Artificial Bee Colony Algorithm: A Case Study of Grid-Connected PV System Power Prediction.

    Science.gov (United States)

    Gao, Xiang-Ming; Yang, Shi-Feng; Pan, San-Bo

    2017-01-01

    Predicting the output power of photovoltaic system with nonstationarity and randomness, an output power prediction model for grid-connected PV systems is proposed based on empirical mode decomposition (EMD) and support vector machine (SVM) optimized with an artificial bee colony (ABC) algorithm. First, according to the weather forecast data sets on the prediction date, the time series data of output power on a similar day with 15-minute intervals are built. Second, the time series data of the output power are decomposed into a series of components, including some intrinsic mode components IMFn and a trend component Res, at different scales using EMD. The corresponding SVM prediction model is established for each IMF component and trend component, and the SVM model parameters are optimized with the artificial bee colony algorithm. Finally, the prediction results of each model are reconstructed, and the predicted values of the output power of the grid-connected PV system can be obtained. The prediction model is tested with actual data, and the results show that the power prediction model based on the EMD and ABC-SVM has a faster calculation speed and higher prediction accuracy than do the single SVM prediction model and the EMD-SVM prediction model without optimization.

  20. Kernel methods for interpretable machine learning of order parameters

    Science.gov (United States)

    Ponte, Pedro; Melko, Roger G.

    2017-11-01

    Machine learning is capable of discriminating phases of matter, and finding associated phase transitions, directly from large data sets of raw state configurations. In the context of condensed matter physics, most progress in the field of supervised learning has come from employing neural networks as classifiers. Although very powerful, such algorithms suffer from a lack of interpretability, which is usually desired in scientific applications in order to associate learned features with physical phenomena. In this paper, we explore support vector machines (SVMs), which are a class of supervised kernel methods that provide interpretable decision functions. We find that SVMs can learn the mathematical form of physical discriminators, such as order parameters and Hamiltonian constraints, for a set of two-dimensional spin models: the ferromagnetic Ising model, a conserved-order-parameter Ising model, and the Ising gauge theory. The ability of SVMs to provide interpretable classification highlights their potential for automating feature detection in both synthetic and experimental data sets for condensed matter and other many-body systems.

  1. SU-E-T-113: Dose Distribution Using Respiratory Signals and Machine Parameters During Treatment

    International Nuclear Information System (INIS)

    Imae, T; Haga, A; Saotome, N; Kida, S; Nakano, M; Takeuchi, Y; Shiraki, T; Yano, K; Yamashita, H; Nakagawa, K; Ohtomo, K

    2014-01-01

    Purpose: Volumetric modulated arc therapy (VMAT) is a rotational intensity-modulated radiotherapy (IMRT) technique capable of acquiring projection images during treatment. Treatment plans for lung tumors using stereotactic body radiotherapy (SBRT) are calculated with planning computed tomography (CT) images only exhale phase. Purpose of this study is to evaluate dose distribution by reconstructing from only the data such as respiratory signals and machine parameters acquired during treatment. Methods: Phantom and three patients with lung tumor underwent CT scans for treatment planning. They were treated by VMAT while acquiring projection images to derive their respiratory signals and machine parameters including positions of multi leaf collimators, dose rates and integrated monitor units. The respiratory signals were divided into 4 and 10 phases and machine parameters were correlated with the divided respiratory signals based on the gantry angle. Dose distributions of each respiratory phase were calculated from plans which were reconstructed from the respiratory signals and the machine parameters during treatment. The doses at isocenter, maximum point and the centroid of target were evaluated. Results and Discussion: Dose distributions during treatment were calculated using the machine parameters and the respiratory signals detected from projection images. Maximum dose difference between plan and in treatment distribution was −1.8±0.4% at centroid of target and dose differences of evaluated points between 4 and 10 phases were no significant. Conclusion: The present method successfully evaluated dose distribution using respiratory signals and machine parameters during treatment. This method is feasible to verify the actual dose for moving target

  2. Numerical approach for optimum electromagnetic parameters of electrical machines used in vehicle traction applications

    International Nuclear Information System (INIS)

    Fodorean, D.; Giurgea, S.; Djerdir, A.; Miraoui, A.

    2009-01-01

    A large speed variation is an essential request in the automobile industry. In order to compete with diesel engines, the flux weakening technique has to be employed on the electrical machines. In this way, appropriate electromagnetic and geometrical parameters can give the desired speed. Using the inverse problem method coupled with numerical analysis by finite element method (FEM), the authors propose an optimum parameters configuration that maximizes the speed domain operation. Several types of electrical machines are under study: induction, synchronous permanent magnet, variable reluctance and transverse flux machines, respectively. With a proper non-linear model, by using analytical and numerical calculation, the authors propose an optimum solution for the speed variation of the studied drives, which will be standing for a final comparison.

  3. Stellar Parameters in an Instant with Machine Learning

    Directory of Open Access Journals (Sweden)

    Bellinger Earl P.

    2017-01-01

    Full Text Available With the advent of dedicated photometric space missions, the ability to rapidly process huge catalogues of stars has become paramount. Bellinger and Angelou et al. [1] recently introduced a new method based on machine learning for inferring the stellar parameters of main-sequence stars exhibiting solar-like oscillations. The method makes precise predictions that are consistent with other methods, but with the advantages of being able to explore many more parameters while costing practically no time. Here we apply the method to 52 so-called “LEGACY“ main-sequence stars observed by the Kepler space mission. For each star, we present estimates and uncertainties of mass, age, radius, luminosity, core hydrogen abundance, surface helium abundance, surface gravity, initial helium abundance, and initial metallicity as well as estimates of their evolutionary model parameters of mixing length, overshooting coeffcient, and diffusion multiplication factor. We obtain median uncertainties in stellar age, mass, and radius of 14.8%, 3.6%, and 1.7%, respectively. The source code for all analyses and for all figures appearing in this manuscript can be found electronically at https://github.com/earlbellinger/asteroseismology

  4. Machine learning of parameters for accurate semiempirical quantum chemical calculations

    International Nuclear Information System (INIS)

    Dral, Pavlo O.; Lilienfeld, O. Anatole von; Thiel, Walter

    2015-01-01

    We investigate possible improvements in the accuracy of semiempirical quantum chemistry (SQC) methods through the use of machine learning (ML) models for the parameters. For a given class of compounds, ML techniques require sufficiently large training sets to develop ML models that can be used for adapting SQC parameters to reflect changes in molecular composition and geometry. The ML-SQC approach allows the automatic tuning of SQC parameters for individual molecules, thereby improving the accuracy without deteriorating transferability to molecules with molecular descriptors very different from those in the training set. The performance of this approach is demonstrated for the semiempirical OM2 method using a set of 6095 constitutional isomers C 7 H 10 O 2 , for which accurate ab initio atomization enthalpies are available. The ML-OM2 results show improved average accuracy and a much reduced error range compared with those of standard OM2 results, with mean absolute errors in atomization enthalpies dropping from 6.3 to 1.7 kcal/mol. They are also found to be superior to the results from specific OM2 reparameterizations (rOM2) for the same set of isomers. The ML-SQC approach thus holds promise for fast and reasonably accurate high-throughput screening of materials and molecules

  5. Multi criteria decision making of machining parameters for Die Sinking EDM Process

    Directory of Open Access Journals (Sweden)

    G. K. Bose

    2015-04-01

    Full Text Available Electrical Discharge Machining (EDM is one of the most basic non-conventional machining processes for production of complex geometries and process of hard materials, which are difficult to machine by conventional process. It is capable of machining geometrically complex or hard material components, that are precise and difficult-to-machine such as heat-treated tool steels, composites, super alloys, ceramics, carbides, heat resistant steels etc. The present study is focusing on the die sinking electric discharge machining (EDM of AISI H 13, W.-Nr. 1.2344 Grade: Ovar Supreme for finding out the effect of machining parameters such as discharge current (GI, pulse on time (POT, pulse off time (POF and spark gap (SG on performance response like Material removal rate (MRR, Surface Roughness (Ra & Overcut (OC using Square-shaped Cu tool with Lateral flushing. A well-designed experimental scheme is used to reduce the total number of experiments. Parts of the experiment are conducted with the L9 orthogonal array based on the Taguchi methodology and significant process parameters are identified using Analysis of Variance (ANOVA. It is found that MRR is affected by gap current & Ra is affected by pulse on time. Moreover, the signal-to-noise ratios associated with the observed values in the experiments are determined by which factor is most affected by the responses of MRR, Ra and OC. These experimental data are further investigated using Grey Relational Analysis to optimize multiple performances in which different levels combination of the factors are ranked based on grey relational grade. The analysis reveals that substantial improvement in machining performance takes place following this technique.

  6. Reliability of measuring abductor hallucis muscle parameters using two different diagnostic ultrasound machines

    Directory of Open Access Journals (Sweden)

    Cameron Alyse FM

    2009-11-01

    Full Text Available Abstract Background Diagnostic ultrasound provides a method of analysing soft tissue structures of the musculoskeletal system effectively and reliably. The aim of this study was to evaluate within and between session reliability of measuring muscle dorso-plantar thickness, medio-lateral length and cross-sectional area, of the abductor hallucis muscle using two different ultrasound machines, a higher end Philips HD11 Ultrasound machine and clinically orientated Chison 8300 Deluxe Digital Portable Ultrasound System. Methods The abductor hallucis muscle of both the left and right feet of thirty asymptomatic participants was imaged and then measured using both ultrasound machines. Interclass correlation coefficients (ICC with 95% confidence intervals (CI were used to calculate both within and between session intra-tester reliability. Standard error of the measurement (SEM calculations were undertaken to assess difference between the actual measured score across trials and the smallest real difference (SRD was calculated from the SEM to indicate the degree of change that would exceed the expected trial to trial variability. Results The ICCs, SEM and SRD for dorso-plantar thickness and medial-lateral length were shown to have excellent to high within and between-session reliability for both ultrasound machines. The between-session reliability indices for cross-sectional area were acceptable for both ultrasound machines. Conclusion The results of the current study suggest that regardless of the type ultrasound machine, intra-tester reliability for the measurement the abductor hallucis muscle parameters is very high.

  7. Effect of processing parameters of rotary ultrasonic machining on surface integrity of potassium dihydrogen phosphate crystals

    Directory of Open Access Journals (Sweden)

    Jianfu Zhang

    2015-09-01

    Full Text Available Potassium dihydrogen phosphate is an important optical crystal. However, high-precision processing of large potassium dihydrogen phosphate crystal workpieces is difficult. In this article, surface roughness and subsurface damage characteristics of a (001 potassium dihydrogen phosphate crystal surface produced by traditional and rotary ultrasonic machining are studied. The influence of process parameters, including spindle speed, feed speed, type and size of sintered diamond wheel, ultrasonic power, and selection of cutting fluid on potassium dihydrogen phosphate crystal surface integrity, was analyzed. The surface integrity, especially the subsurface damage depth, was affected significantly by the ultrasonic power. Metal-sintered diamond tools with high granularity were most suitable for machining potassium dihydrogen phosphate crystal. Cutting fluid played a key role in potassium dihydrogen phosphate crystal machining. A more precise surface can be obtained in machining with a higher spindle speed, lower feed speed, and using kerosene as cutting fluid. Based on the provided optimized process parameters for machining potassium dihydrogen phosphate crystal, a processed surface quality with Ra value of 33 nm and subsurface damage depth value of 6.38 μm was achieved.

  8. Characterization of cutting parameters in the minimum quantity lubricant (MQL) machining process of a gearbox

    OpenAIRE

    Travieso Rodriguez, Jose Antonio; Gómez Gras, David; García Vilana, Silvia; Mainau Noguer, Ferran; Jerez Mesa, Ramón

    2015-01-01

    This paper aims to find the key process parameters for machining different parts of an automobile gearbox, commissioned by a company that needs to replace with the MQL lubrication system their current machining process based on cutting fluids. It particularly focuses on the definition of appropriate cutting parameters for machining under the MQL condition through a statistical method of Design of Experiments (DOE). Using a combination of recommended parameters, significant improvements in the...

  9. Optimization of machining parameters of turning operations based on multi performance criteria

    Directory of Open Access Journals (Sweden)

    N.K.Mandal

    2013-01-01

    Full Text Available The selection of optimum machining parameters plays a significant role to ensure quality of product, to reduce the manufacturing cost and to increase productivity in computer controlled manufacturing process. For many years, multi-objective optimization of turning based on inherent complexity of process is a competitive engineering issue. This study investigates multi-response optimization of turning process for an optimal parametric combination to yield the minimum power consumption, surface roughness and frequency of tool vibration using a combination of a Grey relational analysis (GRA. Confirmation test is conducted for the optimal machining parameters to validate the test result. Various turning parameters, such as spindle speed, feed and depth of cut are considered. Experiments are designed and conducted based on full factorial design of experiment.

  10. Parameters optimization for wavelet denoising based on normalized spectral angle and threshold constraint machine learning

    Science.gov (United States)

    Li, Hao; Ma, Yong; Liang, Kun; Tian, Yong; Wang, Rui

    2012-01-01

    Wavelet parameters (e.g., wavelet type, level of decomposition) affect the performance of the wavelet denoising algorithm in hyperspectral applications. Current studies select the best wavelet parameters for a single spectral curve by comparing similarity criteria such as spectral angle (SA). However, the method to find the best parameters for a spectral library that contains multiple spectra has not been studied. In this paper, a criterion named normalized spectral angle (NSA) is proposed. By comparing NSA, the best combination of parameters for a spectral library can be selected. Moreover, a fast algorithm based on threshold constraint and machine learning is developed to reduce the time of a full search. After several iterations of learning, the combination of parameters that constantly surpasses a threshold is selected. The experiments proved that by using the NSA criterion, the SA values decreased significantly, and the fast algorithm could save 80% time consumption, while the denoising performance was not obviously impaired.

  11. Characteristics of laser assisted machining for silicon nitride ceramic according to machining parameters

    International Nuclear Information System (INIS)

    Kim, Jong Do; Lee, Su Jin; Suh, Jeong

    2011-01-01

    This paper describes the Laser Assisted Machining (LAM) that cuts and removes softened parts by locally heating the ceramic with laser. Silicon nitride ceramics can be machined with general machining tools as well, because YSiAlON, which was made up ceramics, is soften at about 1,000 .deg. C. In particular, the laser, which concentrates on highly dense energy, can locally heat materials and very effectively control the temperature of the heated part of specimen. Therefore, this paper intends to propose an efficient machining method of ceramic by deducing the machining governing factors of laser assisted machining and understanding its mechanism. While laser power is the machining factor that controls the temperature, the CBN cutting tool could cut the material more easily as the material gets deteriorated from the temperature increase by increasing the laser power, but excessive oxidation can negatively affect the quality of the material surface after machining. As the feed rate and cutting depth increase, the cutting force increases and tool lifespan decreases, but surface oxidation also decreases. In this experiment, the material can be cut to 3 mm of cutting depth. And based on the results of the experiment, the laser assisted machining mechanism is clarified

  12. A Parameter Communication Optimization Strategy for Distributed Machine Learning in Sensors.

    Science.gov (United States)

    Zhang, Jilin; Tu, Hangdi; Ren, Yongjian; Wan, Jian; Zhou, Li; Li, Mingwei; Wang, Jue; Yu, Lifeng; Zhao, Chang; Zhang, Lei

    2017-09-21

    In order to utilize the distributed characteristic of sensors, distributed machine learning has become the mainstream approach, but the different computing capability of sensors and network delays greatly influence the accuracy and the convergence rate of the machine learning model. Our paper describes a reasonable parameter communication optimization strategy to balance the training overhead and the communication overhead. We extend the fault tolerance of iterative-convergent machine learning algorithms and propose the Dynamic Finite Fault Tolerance (DFFT). Based on the DFFT, we implement a parameter communication optimization strategy for distributed machine learning, named Dynamic Synchronous Parallel Strategy (DSP), which uses the performance monitoring model to dynamically adjust the parameter synchronization strategy between worker nodes and the Parameter Server (PS). This strategy makes full use of the computing power of each sensor, ensures the accuracy of the machine learning model, and avoids the situation that the model training is disturbed by any tasks unrelated to the sensors.

  13. Identification of Mechanical parameters for Resistance Welding Machines

    DEFF Research Database (Denmark)

    Wu, Pei; Zhang, Wenqi; Bay, Niels

    2003-01-01

    Mechanical dynamic responses of resistance welding machine have a significant influence on weld quality and electrode service life, it must be considered when the real welding production is carried out or the welding process is simulated. The mathematical models for characterizing the mechanical...

  14. Deriving global parameter estimates for the Noah land surface model using FLUXNET and machine learning

    Science.gov (United States)

    Chaney, Nathaniel W.; Herman, Jonathan D.; Ek, Michael B.; Wood, Eric F.

    2016-11-01

    With their origins in numerical weather prediction and climate modeling, land surface models aim to accurately partition the surface energy balance. An overlooked challenge in these schemes is the role of model parameter uncertainty, particularly at unmonitored sites. This study provides global parameter estimates for the Noah land surface model using 85 eddy covariance sites in the global FLUXNET network. The at-site parameters are first calibrated using a Latin Hypercube-based ensemble of the most sensitive parameters, determined by the Sobol method, to be the minimum stomatal resistance (rs,min), the Zilitinkevich empirical constant (Czil), and the bare soil evaporation exponent (fxexp). Calibration leads to an increase in the mean Kling-Gupta Efficiency performance metric from 0.54 to 0.71. These calibrated parameter sets are then related to local environmental characteristics using the Extra-Trees machine learning algorithm. The fitted Extra-Trees model is used to map the optimal parameter sets over the globe at a 5 km spatial resolution. The leave-one-out cross validation of the mapped parameters using the Noah land surface model suggests that there is the potential to skillfully relate calibrated model parameter sets to local environmental characteristics. The results demonstrate the potential to use FLUXNET to tune the parameterizations of surface fluxes in land surface models and to provide improved parameter estimates over the globe.

  15. The relationships between ceramic tool life and different machining parameters

    International Nuclear Information System (INIS)

    El-Axir, M.H.; El-Masry, A.A.; Mashal, Y.A.H.

    2001-01-01

    With the increasing use of ceramic tool materials in applications, has come an increasing need for experimental data to assign the behavior of the life of these tool materials. Experimental results during turning operation show that it is possible to increase cutting tool life substantially by a proper variation of the cutting parameters used in this work. The tool lives (tool flank wear land length) of three different ceramic materials, namely; Silicon carbide (SiC), Alumina (Al/sub 2/O/sub 3/) and partially stabilized zirconia (PSZ) in addition to, Titanium carbide and high speed steel tools are investigated in this work. Also, The effect of varying the cutting speed, feed rate and tool rake angle on tool life of each tool material is studied. The experimental work was carried out utilizing one of the experimental design techniques based on response surface methodology. It was found that the SiC cutting tool showed the highest tool life among all materials tested in this work. It was also noticed that increasing the cutting speed has led to an increase in tool life for ceramic tools only. However, increasing the feed rate and tool rake angle resulted in a reduction in tool life in all materials examined in the present study. Further analysis conducted on SiC tool material to examine the effect of the interaction of cutting parameters on the tool life. (author)

  16. Process parameter optimization based on principal components analysis during machining of hardened steel

    Directory of Open Access Journals (Sweden)

    Suryakant B. Chandgude

    2015-09-01

    Full Text Available The optimum selection of process parameters has played an important role for improving the surface finish, minimizing tool wear, increasing material removal rate and reducing machining time of any machining process. In this paper, optimum parameters while machining AISI D2 hardened steel using solid carbide TiAlN coated end mill has been investigated. For optimization of process parameters along with multiple quality characteristics, principal components analysis method has been adopted in this work. The confirmation experiments have revealed that to improve performance of cutting; principal components analysis method would be a useful tool.

  17. Parameter Optimization of Black Tea Fermentation Machine Based on RSM and BP-AdaBoost-GA

    DEFF Research Database (Denmark)

    Dong, Chunwang; Zhao, Jiewen; Zhu, Hongkai

    2017-01-01

    Fermentation is the key procedure in processing of congou black tea, which directly decides the quality and flavor of tea products. Fermentation experiments were conducted on a novel drum-type fermentation machine as the platform, the performance parameters of fermentation machine were clarified...... of black tea, moderate rotation and mixing material can enhance the quality of black tea and shorten the fermentation time....

  18. Development of an Empirical Model for Optimization of Machining Parameters to Minimize Power Consumption

    Science.gov (United States)

    Kant Garg, Girish; Garg, Suman; Sangwan, K. S.

    2018-04-01

    The manufacturing sector consumes huge energy demand and the machine tools used in this sector have very less energy efficiency. Selection of the optimum machining parameters for machine tools is significant for energy saving and for reduction of environmental emission. In this work an empirical model is developed to minimize the power consumption using response surface methodology. The experiments are performed on a lathe machine tool during the turning of AISI 6061 Aluminum with coated tungsten inserts. The relationship between the power consumption and machining parameters is adequately modeled. This model is used for formulation of minimum power consumption criterion as a function of optimal machining parameters using desirability function approach. The influence of machining parameters on the energy consumption has been found using the analysis of variance. The validation of the developed empirical model is proved using the confirmation experiments. The results indicate that the developed model is effective and has potential to be adopted by the industry for minimum power consumption of machine tools.

  19. Optimizing friction stir weld parameters of aluminum and copper using conventional milling machine

    Science.gov (United States)

    Manisegaran, Lohappriya V.; Ahmad, Nurainaa Ayuni; Nazri, Nurnadhirah; Noor, Amirul Syafiq Mohd; Ramachandran, Vignesh; Ismail, Muhammad Tarmizizulfika; Ahmad, Ku Zarina Ku; Daruis, Dian Darina Indah

    2018-05-01

    The joining of two of any particular materials through friction stir welding (FSW) are done by a rotating tool and the work piece material that generates heat which causes the region near the FSW tool to soften. This in return will mechanically intermix the work pieces. The first objective of this study is to join aluminum plates and copper plates by means of friction stir welding process using self-fabricated tools and conventional milling machine. This study also aims to investigate the optimum process parameters to produce the optimum mechanical properties of the welding joints for Aluminum plates and Copper plates. A suitable tool bit and a fixture is to be fabricated for the welding process. A conventional milling machine will be used to weld the aluminum and copper. The most important parameters to enable the process are speed and pressure of the tool (or tool design and alignment of the tool onto the work piece). The study showed that the best surface finish was produced from speed of 1150 rpm and tool bit tilted to 3°. For a 200mm × 100mm Aluminum 6061 with plate thickness of 2 mm at a speed of 1 mm/s, the time taken to complete the welding is only 200 seconds or equivalent to 3 minutes and 20 seconds. The Copper plates was successfully welded using FSW with tool rotation speed of 500 rpm, 700 rpm, 900 rpm, 1150 rpm and 1440 rpm and with welding traverse rate of 30 mm/min, 60 mm/min and 90 mm/min. As the conclusion, FSW using milling machine can be done on both Aluminum and Copper plates, however the weld parameters are different for the two types of plates.

  20. Comparative analysis of partial imaging performance parameters of home and imported X-ray machines

    International Nuclear Information System (INIS)

    Cao Yunxi; Wang Xianyun; Liu Huiqin; Guo Yongxin

    2002-01-01

    Objective: To compare and analyze the performance indexes and the imaging quality of the home and imported X-ray machines through testing their partial imaging performance parameters. Methods: By separate sampling from 10 home and 10 imported X-ray machines, the parameters including tube current, time of exposure, machine total exposure, and repeatability were tested, and the imaging performance was evaluated according to the national standard. Results: All the performance indexes met the standard of GB4505-84. The first sampling tests showed the maximum changing coefficient of imaging performance repeatability of the home X-ray machines was Δmax1 = 0.025, while that of the imported X-ray machine was Δmax1 = 0.016. In the second sampling tests, the maximum changing coefficients of the two were Δmax2 = 0.048 and Δmax2 = 0.022, respectively. Conclusion: The 2 years' follow-up tests indicate that there is no significant difference between the above-mentioned parameters of the elaborately adjusted home X-ray machines and imported ones, but the home X-ray machines are no better than the imported X-ray machines in stability and consistency

  1. ATLAS parameter study

    International Nuclear Information System (INIS)

    Adler, R.J.

    1994-01-01

    The purpose of this study is to make an independent assessment on the parameters chosen for the ATLAS capacitor bank at LANL. The contractor will perform a study of the basic pulsed power parameters of the ATLAS device with baseline functional parameters of >25 MA implosion current and <2.5 microsecond current risetime. Nominal circuit parameters held fixed will be the 14 nH from the vacuum interface to the load, and the nominal load impedances of 1 milliohm for slow loads and 10 milliohms for fast loads. Single Ended designs, as opposed to bipolar designs, will be studied in detail. The ATLAS pulsed power design problem is about inductance. The reason that a 36 MJ bank is required is that such a bank has enough individual capacitors so that the parallel inductance is acceptably low. Since about half the inductance is in the bank, and the inductance and time constant of the submodules is fixed, the variation of output with a given parameter will generally be a weak one. In general, the dl/dt calculation demonstrates that for the real system inductances, 700 kV is the optimum voltage for the bank to drive X-ray loads. The optimum is broad, and there is little reduction in performance at voltages as low as 450 kV. The direct drive velocity analysis also shows that the optimum velocity is between 480 and 800 kV for a variety of assumptions, and that there is less than a 10% variation in velocity over this range. Voltages in the 120 kV--600 kV range are desirable for driving heavy liners. A compromise optimum operating point might be 480 kV, at which all X-ray operation scenarios are within 10% of their velocity optimum, and heavy liners can be configured to be near optimum if small enough. Based on very preliminary studies the author believes that the choice of a single operating voltage point (say, 480 kV) is unnecessary, and that a bank engineered for dual operation at 480 and 240 kV will be the best solution to the ATLAS problem

  2. Predictive Models for Different Roughness Parameters During Machining Process of Peek Composites Using Response Surface Methodology

    Directory of Open Access Journals (Sweden)

    Mata-Cabrera Francisco

    2013-10-01

    Full Text Available Polyetheretherketone (PEEK composite belongs to a group of high performance thermoplastic polymers and is widely used in structural components. To improve the mechanical and tribological properties, short fibers are added as reinforcement to the material. Due to its functional properties and potential applications, it’s impor- tant to investigate the machinability of non-reinforced PEEK (PEEK, PEEK rein- forced with 30% of carbon fibers (PEEK CF30, and reinforced PEEK with 30% glass fibers (PEEK GF30 to determine the optimal conditions for the manufacture of the parts. The present study establishes the relationship between the cutting con- ditions (cutting speed and feed rate and the roughness (Ra , Rt , Rq , Rp , by develop- ing second order mathematical models. The experiments were planned as per full factorial design of experiments and an analysis of variance has been performed to check the adequacy of the models. These state the adequacy of the derived models to obtain predictions for roughness parameters within ranges of parameters that have been investigated during the experiments. The experimental results show that the most influence of the cutting parameters is the feed rate, furthermore, proved that glass fiber reinforcements produce a worse machinability.

  3. Exploring the influence of constitutive models and associated parameters for the orthogonal machining of Ti6Al4V

    Science.gov (United States)

    Pervaiz, S.; Anwar, S.; Kannan, S.; Almarfadi, A.

    2018-04-01

    Ti6Al4V is known as difficult-to-cut material due to its inherent properties such as high hot hardness, low thermal conductivity and high chemical reactivity. Though, Ti6Al4V is utilized by industrial sectors such as aeronautics, energy generation, petrochemical and bio-medical etc. For the metal cutting community, competent and cost-effective machining of Ti6Al4V is a challenging task. To optimize cost and machining performance for the machining of Ti6Al4V, finite element based cutting simulation can be a very useful tool. The aim of this paper is to develop a finite element machining model for the simulation of Ti6Al4V machining process. The study incorporates material constitutive models namely Power Law (PL) and Johnson – Cook (JC) material models to mimic the mechanical behaviour of Ti6Al4V. The study investigates cutting temperatures, cutting forces, stresses, and plastic strains with respect to different PL and JC material models with associated parameters. In addition, the numerical study also integrates different cutting tool rake angles in the machining simulations. The simulated results will be beneficial to draw conclusions for improving the overall machining performance of Ti6Al4V.

  4. Parameter identification and optimization of slide guide joint of CNC machine tools

    Science.gov (United States)

    Zhou, S.; Sun, B. B.

    2017-11-01

    The joint surface has an important influence on the performance of CNC machine tools. In order to identify the dynamic parameters of slide guide joint, the parametric finite element model of the joint is established and optimum design method is used based on the finite element simulation and modal test. Then the mode that has the most influence on the dynamics of slip joint is found through harmonic response analysis. Take the frequency of this mode as objective, the sensitivity analysis of the stiffness of each joint surface is carried out using Latin Hypercube Sampling and Monte Carlo Simulation. The result shows that the vertical stiffness of slip joint surface constituted by the bed and the slide plate has the most obvious influence on the structure. Therefore, this stiffness is taken as the optimization variable and the optimal value is obtained through studying the relationship between structural dynamic performance and stiffness. Take the stiffness values before and after optimization into the FEM of machine tool, and it is found that the dynamic performance of the machine tool is improved.

  5. Analyzing the effect of cutting parameters on surface roughness and tool wear when machining nickel based hastelloy - 276

    International Nuclear Information System (INIS)

    Khidhir, Basim A; Mohamed, Bashir

    2011-01-01

    Machining parameters has an important factor on tool wear and surface finish, for that the manufacturers need to obtain optimal operating parameters with a minimum set of experiments as well as minimizing the simulations in order to reduce machining set up costs. The cutting speed is one of the most important cutting parameter to evaluate, it clearly most influences on one hand, tool life, tool stability, and cutting process quality, and on the other hand controls production flow. Due to more demanding manufacturing systems, the requirements for reliable technological information have increased. For a reliable analysis in cutting, the cutting zone (tip insert-workpiece-chip system) as the mechanics of cutting in this area are very complicated, the chip is formed in the shear plane (entrance the shear zone) and is shape in the sliding plane. The temperature contributed in the primary shear, chamfer and sticking, sliding zones are expressed as a function of unknown shear angle on the rake face and temperature modified flow stress in each zone. The experiments were carried out on a CNC lathe and surface finish and tool tip wear are measured in process. Machining experiments are conducted. Reasonable agreement is observed under turning with high depth of cut. Results of this research help to guide the design of new cutting tool materials and the studies on evaluation of machining parameters to further advance the productivity of nickel based alloy Hastelloy - 276 machining.

  6. Grinding, Machining Morphological Studies on C/SiC Composites

    Science.gov (United States)

    Xiao, Chun-fang; Han, Bing

    2018-05-01

    C/SiC composite is a typical material difficult to machine. It is hard and brittle. In machining, the cutting force is large, the material removal rate is low, the edge is prone to collapse, and the tool wear is serious. In this paper, the grinding of C/Si composites material along the direction of fiber distribution is studied respectively. The surface microstructure and mechanical properties of C/SiC composites processed by ultrasonic machining were evaluated. The change of surface quality with the change of processing parameters has also been studied. By comparing the performances of conventional grinding and ultrasonic grinding, the surface roughness and functional characteristics of the material can be improved by optimizing the processing parameters.

  7. Investigation of the influential parameters of machining of AISI 304 ...

    Indian Academy of Sciences (India)

    application of cutting fluid results in longer tool life and better surface finish. ... parameters for turning of AISI 304 stainless steel by considering the process ... In the design of experiments (DOE) the full factorial method was used in .... Esme U 2009 Application of Taguchi method for the optimization of resistance spot welding.

  8. Effect of cutting parameters on sustainable machining performance of coated carbide tool in dry turning process of stainless steel 316

    Science.gov (United States)

    Bagaber, Salem A.; Yusoff, Ahmed Razlan

    2017-04-01

    The manufacturing industry aims to produce many products of high quality with relatively less cost and time. Different cutting parameters affect the machining performance of surface roughness, cutting force, and material removal rate. Nevertheless, a few studies reported on the effects of sustainable factors such as power consumed, cycle time during machining, and tool life on the dry turning of AISI 316. The present study aims to evaluate the machining performance of coated carbide in the machining of hard steel AISI 316 under the dry turning process. The influence of cutting parameters of cutting speed, feed rate, and depth of cut with their five (5) levels is established by a central composite design. Highly significant parameters were determined by analysis of variance (ANOVA), and the main effects of power consumed and time during machining, surface roughness, and tool wear were observed. Results showed that the cutting speed was proportional to power consumption and tool wear. Meanwhile, insignificant to surface roughness, feed rate most significantly affected surface roughness and power consumption followed by depth of cut.

  9. Identification of Technological Parameters of Ni-Alloys When Machining by Monolithic Ceramic Milling Tool

    Science.gov (United States)

    Czán, Andrej; Kubala, Ondrej; Danis, Igor; Czánová, Tatiana; Holubják, Jozef; Mikloš, Matej

    2017-12-01

    The ever-increasing production and the usage of hard-to-machine progressive materials are the main cause of continual finding of new ways and methods of machining. One of these ways is the ceramic milling tool, which combines the pros of conventional ceramic cutting materials and pros of conventional coating steel-based insert. These properties allow to improve cutting conditions and so increase the productivity with preserved quality known from conventional tools usage. In this paper, there is made the identification of properties and possibilities of this tool when machining of hard-to-machine materials such as nickel alloys using in airplanes engines. This article is focused on the analysis and evaluation ordinary technological parameters and surface quality, mainly roughness of surface and quality of machined surface and tool wearing.

  10. Analysis and optimization of machining parameters of laser cutting for polypropylene composite

    Science.gov (United States)

    Deepa, A.; Padmanabhan, K.; Kuppan, P.

    2017-11-01

    Present works explains about machining of self-reinforced Polypropylene composite fabricated using hot compaction method. The objective of the experiment is to find optimum machining parameters for Polypropylene (PP). Laser power and Machining speed were the parameters considered in response to tensile test and Flexure test. Taguchi method is used for experimentation. Grey Relational Analysis (GRA) is used for multiple process parameter optimization. ANOVA (Analysis of Variance) is used to find impact for process parameter. Polypropylene has got the great application in various fields like, it is used in the form of foam in model aircraft and other radio-controlled vehicles, thin sheets (∼2-20μm) used as a dielectric, PP is also used in piping system, it is also been used in hernia and pelvic organ repair or protect new herrnis in the same location.

  11. Phase Modulation Method for Control Systems of Rotary Machine Parameters

    Directory of Open Access Journals (Sweden)

    V. V. Sychev

    2014-01-01

    Full Text Available Traditionally, vibration-based diagnostics takes the main place in a large complex of technical control means of rotary machine operation. It allows us to control the onset of extreme limit states of operating construction and its elements. However, vibration-based diagnostics is incapable to provide differentiated information about the condition of particular units, type of fault and point of its occurrence.From the practical experience of optoelectronic sensors development, methods of phase coding information about the behavior of the investigated object are known. They allow us to overcome the abovementioned disadvantage of vibration-based diagnostics through the modulation of the reflected radiation from the object. This phase modulation is performed with the image analyzers, in which the modulating raster (alternating transparent and nontransparent sectors is designed so, that the carrier frequency of oscillations is absent (suppressed in frequency spectrum, and all useful information can be found in the side frequencies.Carrier frequency suppression appears for two complete turns of the modulating raster. Each time during this process oscillations have a 180° phase shift (hop relatively to the initial oscillation on the boundary of each turn. It leads to a substantial increase in signal/noise ratio and possibility to conduct high-accuracy diagnostics.The principle of the pseudo inversion is used for measurements to suppress an adverse effect of various factors in dynamic control system. For this principle the leaving and returned beams practically go on the same way with small spatial shift. This shift occurs then the leaving beam reflects from a basic surface and the reflected – from the measured surface of the object. Therefore the measurements become insensitive to any other errors of system, except relative position of system «model-object».The main advantages of such measurements are the following:- system steadiness to error

  12. Review of the Tandem Mirror Experiment-Upgrade (TMX-U) machine-parameter-instrumentation system

    International Nuclear Information System (INIS)

    Kane, R.J.; Coffield, F.E.; Coutts, G.W.; Hornady, R.S.

    1983-01-01

    The Tandem Mirror Experiment-Upgrade (TMX-U) machine consists of seven major machine subsystems: magnet system, neutral beam system, microwave heating (ECRH), ion heating (ICRH), gas fueling, stream guns, and vacuum system. Satisfactory performance of these subsystems is necessary to achieve the experimental objectives planned for TMX-U operations. Since the performance quality of the subsystem is important and can greatly affect plasma parameters, a 233-channel instrumentation system has been installed. Data from the instrumentation system are acquired and stored with the plasma diagnostic information. Thus, the details of the machine performance are available during post-shot analysis. This paper describes all the machine-parameter-instrumentation hardware, presents some typical data, and outlines how the data are used

  13. Beam interlock system and safe machine parameters system 2010 and beyond

    CERN Document Server

    Todd, B

    2010-01-01

    The Beam Interlock System (BIS) and Safe Machine Parameters (SMP) system are central to the protection of the Large Hadron Collider (LHC) machine. The BIS has been critical for the safe operation of LHC from the first day of operation. It has been installed and commissioned, only minor enhancements are required in order to accommodate all future LHC machine protection requirements. At reduced intensity, the SMP system is less critical for LHC operation. As such, the current system satisfies the 2010 operational requirements. Further developments are required, both at the SMP Controller level, and at the system level, in order to accommodate the requirements of the LHC beyond 2010.

  14. Optimization of cutting parameters for machining time in turning process

    Science.gov (United States)

    Mavliutov, A. R.; Zlotnikov, E. G.

    2018-03-01

    This paper describes the most effective methods for nonlinear constraint optimization of cutting parameters in the turning process. Among them are Linearization Programming Method with Dual-Simplex algorithm, Interior Point method, and Augmented Lagrangian Genetic Algorithm (ALGA). Every each of them is tested on an actual example – the minimization of production rate in turning process. The computation was conducted in the MATLAB environment. The comparative results obtained from the application of these methods show: The optimal value of the linearized objective and the original function are the same. ALGA gives sufficiently accurate values, however, when the algorithm uses the Hybrid function with Interior Point algorithm, the resulted values have the maximal accuracy.

  15. Calibration of diagnostic x-ray machines using radiation exposure and radiographic parameters

    International Nuclear Information System (INIS)

    Agba, E.H.; Uloko, P. I.; Tyovenda, A. A.

    2011-01-01

    Calibration of diagnostic x-ray machines using radiation exposure and radiographic parameters of the x-ray machines has been carried out. Three phase diagnostic x-ray machines situated at Federal Medical Centre, Makurdi, General Hospital, Otukpo and Christian Hospital, Mkar were used for the calibration work. The radiation meter was used to measure x-ray radiation exposure. The result of this work demonstrates mR/mAs=C(KV p ) that there exist a power law relation of the form between the radiation exposure and the radiographic parameters of diagnostic x-ray machines, which can be used to estimate patient exposure during routine x-ray diagnostic examinations for wide range of operating parameters. The values of the power exponent n, constant c and total filtrations of the diagnostic x-ray machines have been estimated. These values for the diagnostic x-ray machines at the Federal Medical Centre, Makurdi are: 2.14, 0.88 and 2.77 respectively, for the one at the General Hospital, Otukpo are: 2.07, 0.76 and 2.68 respectively and that of the Christian Hospital, Mkar are: 2.01,0.69 and 2.61 respectively.

  16. Effect of operational conditions of electroerosion machining on the surface microgeometry parameters of steels and alloys

    International Nuclear Information System (INIS)

    Foteev, N.K.

    1976-01-01

    Studies the influence of pulse duration and a series of operating conditions of a ShGI-40-440 spark-machining generator on changes in the basic surface microgeometry characteristics of components of stainless steel 1Kh18N10T, steel St 45 and hard alloy T14K8. The microgeometry characteristics of spark-machined surfaces differ significantly from the corresponding characteristics of surfaces machined by cutting and vibro-rolling

  17. Influence of Wire Electrical Discharge Machining (WEDM) process parameters on surface roughness

    Science.gov (United States)

    Yeakub Ali, Mohammad; Banu, Asfana; Abu Bakar, Mazilah

    2018-01-01

    In obtaining the best quality of engineering components, the quality of machined parts surface plays an important role. It improves the fatigue strength, wear resistance, and corrosion of workpiece. This paper investigates the effects of wire electrical discharge machining (WEDM) process parameters on surface roughness of stainless steel using distilled water as dielectric fluid and brass wire as tool electrode. The parameters selected are voltage open, wire speed, wire tension, voltage gap, and off time. Empirical model was developed for the estimation of surface roughness. The analysis revealed that off time has a major influence on surface roughness. The optimum machining parameters for minimum surface roughness were found to be at a 10 V open voltage, 2.84 μs off time, 12 m/min wire speed, 6.3 N wire tension, and 54.91 V voltage gap.

  18. Relationship of goat milk flow emission variables with milking routine, milking parameters, milking machine characteristics and goat physiology.

    Science.gov (United States)

    Romero, G; Panzalis, R; Ruegg, P

    2017-11-01

    The aim of this paper was to study the relationship between milk flow emission variables recorded during milking of dairy goats with variables related to milking routine, goat physiology, milking parameters and milking machine characteristics, to determine the variables affecting milking performance and help the goat industry pinpoint farm and milking practices that improve milking performance. In total, 19 farms were visited once during the evening milking. Milking parameters (vacuum level (VL), pulsation ratio and pulsation rate, vacuum drop), milk emission flow variables (milking time, milk yield, maximum milk flow (MMF), average milk flow (AVMF), time until 500 g/min milk flow is established (TS500)), doe characteristics of 8 to 10 goats/farm (breed, days in milk and parity), milking practices (overmilking, overstripping, pre-lag time) and milking machine characteristics (line height, presence of claw) were recorded on every farm. The relationships between recorded variables and farm were analysed by a one-way ANOVA analysis. The relationships of milk yield, MMF, milking time and TS500 with goat physiology, milking routine, milking parameters and milking machine design were analysed using a linear mixed model, considering the farm as the random effect. Farm was significant (Pfarms, being similar to those recommended in scientific studies. Few milking parameters and milking machine characteristics affected the tested variables: average vacuum level only showed tendency on MMF, and milk pipeline height on TS500. Milk yield (MY) was mainly affected by parity, as the interaction of days in milk with parity was also significant. Milking time was mainly affected by milk yield and breed. Also significant were parity, the interaction of days in milk with parity and overstripping, whereas overmilking showed a slight tendency. We concluded that most of the studied variables were mainly related to goat physiology characteristics, as the effects of milking parameters and

  19. A Fault Alarm and Diagnosis Method Based on Sensitive Parameters and Support Vector Machine

    Science.gov (United States)

    Zhang, Jinjie; Yao, Ziyun; Lv, Zhiquan; Zhu, Qunxiong; Xu, Fengtian; Jiang, Zhinong

    2015-08-01

    Study on the extraction of fault feature and the diagnostic technique of reciprocating compressor is one of the hot research topics in the field of reciprocating machinery fault diagnosis at present. A large number of feature extraction and classification methods have been widely applied in the related research, but the practical fault alarm and the accuracy of diagnosis have not been effectively improved. Developing feature extraction and classification methods to meet the requirements of typical fault alarm and automatic diagnosis in practical engineering is urgent task. The typical mechanical faults of reciprocating compressor are presented in the paper, and the existing data of online monitoring system is used to extract fault feature parameters within 15 types in total; the inner sensitive connection between faults and the feature parameters has been made clear by using the distance evaluation technique, also sensitive characteristic parameters of different faults have been obtained. On this basis, a method based on fault feature parameters and support vector machine (SVM) is developed, which will be applied to practical fault diagnosis. A better ability of early fault warning has been proved by the experiment and the practical fault cases. Automatic classification by using the SVM to the data of fault alarm has obtained better diagnostic accuracy.

  20. Running and machine studies in 1990

    International Nuclear Information System (INIS)

    1991-03-01

    This annual report described the GANIL performance and machine studies. During the year 1990, the machine has been operated for 36 weeks divided into periods of 5, 6 or 7 weeks; consequently the number of beam setting up has been reduced. From 5682 hours of scheduled beam 3239 hours have been delivered on target. Very heavy ions (Pb, U) are now accelerated owing to the OAE modification. Many experiments have been completed with the new medium energy beam facility. The machine studies were devoted to the development ot the following items: production of 157 Gd 19+ ions, acceleration of 238 U 59+ at 24 MeV/u, SSC1 orbit precession, charge state distribution and energy spread after stripping [fr

  1. Research of influence of technological parameters on the noise characteristics of the machine for grinding meat

    Directory of Open Access Journals (Sweden)

    A. K. Pil’nenko

    2016-01-01

    Full Text Available Noise characteristics (NC machine is one of the main indicators of its quality and competitiveness on the world markets. Scientific and technical work to improve the noise characteristics are relevant and modern. Work focuses on the study of the emergence of the technological equipment of acoustic phenomena. Was selected method of determination and equipment, according to the international standards ISO “Acoustics” taking into account the acoustic properties of the surrounding space. Been established NC machines for grinding meat and fish under operating conditions the in various modes. The maximum value for the characteristic A sound power level (SPL machines produced at idling 79,7 dBA. When the machine comes with the product decline USM on the characteristics A 7.3 dB. It was found exceeding the maximum allowable sound power level at medium frequencies on 2 dB. Impact the components of machines on its NC depending on variables technological factors - the module of elasticity of the product and the effort on the pushrod. Increase modulus of elasticity SPL machines decreases and increase efforts on the pusher Machines USM increases. It was found negative impact construction machines part sat USM. Should be increased rigidity design of the machine.

  2. Materials study for reacting plasma machine

    International Nuclear Information System (INIS)

    Kamada, Kohji; Hamada, Yasuji

    1982-01-01

    A new reacting plasma machine is designed, and will be constructed at the Institute of Plasma Physics, Nagoya University. It is important to avoid the activation of the materials for the machine, accordingly, aluminum alloy has been considered as the material since the induced activity of aluminum due to 14 MeV neutrons is small. The vacuum chamber of the new machine consists of four modules, and the remote control of each module is considered. However, the cost of the remote control of modules is expensive. To minimize the dependence on the remote control, the use of aluminum alloy is considered as the first step. The low electrical resistivity, over-ageing, weak mechanical strength and eddy current characteristics of aluminum alloy must be improved. The physical and electrical properties of various aluminum alloys have been investigated. Permeability of hydrogen through aluminum, the recycling characteristics and surface coating materials have been also studied. (Kato, T.)

  3. The effect of machining parameters on surface roughness during turning of stainless steel

    International Nuclear Information System (INIS)

    El-Belazi, Khalid M.

    1991-03-01

    Surface roughness is a direct consequence of the cutting tool action, its assessment and control represent an effective way by which the machining process can be studied. The control of surface roughness has become increasingly important during the last thirty years, because the quality of surface is extremely important for machined components that have been designed to stand to static and cyclic loads. This work has two major goals. The first is to develop a new theoretical model based on the assumption that the shape of the cutting tool nose is elliptical to evaluate the surface roughness parameters. The second is to investigate the effect of cutting speed, feed rate, overhang length, tool nose radius (circular sharp), and depth of cut on surface roughness of turned surfaces of austenitic stainless steel grade 12X18H10T. It was found from the theoretical part that the surface roughness values obtained from the elliptical model are much better than those obtained from the other models. It was found from the experimental work that the surface roughness values increase by increasing cutting speed, feed rate, depth of cut, and overhang length, and fluctuates when using cutting tools with various nose radii, during turning of the above mentioned steel by using a brazed carbide cutting tool. (author)

  4. Learning Machine Learning: A Case Study

    Science.gov (United States)

    Lavesson, N.

    2010-01-01

    This correspondence reports on a case study conducted in the Master's-level Machine Learning (ML) course at Blekinge Institute of Technology, Sweden. The students participated in a self-assessment test and a diagnostic test of prerequisite subjects, and their results on these tests are correlated with their achievement of the course's learning…

  5. Parameter Identification of Ship Maneuvering Models Using Recursive Least Square Method Based on Support Vector Machines

    Directory of Open Access Journals (Sweden)

    Man Zhu

    2017-03-01

    Full Text Available Determination of ship maneuvering models is a tough task of ship maneuverability prediction. Among several prime approaches of estimating ship maneuvering models, system identification combined with the full-scale or free- running model test is preferred. In this contribution, real-time system identification programs using recursive identification method, such as the recursive least square method (RLS, are exerted for on-line identification of ship maneuvering models. However, this method seriously depends on the objects of study and initial values of identified parameters. To overcome this, an intelligent technology, i.e., support vector machines (SVM, is firstly used to estimate initial values of the identified parameters with finite samples. As real measured motion data of the Mariner class ship always involve noise from sensors and external disturbances, the zigzag simulation test data include a substantial quantity of Gaussian white noise. Wavelet method and empirical mode decomposition (EMD are used to filter the data corrupted by noise, respectively. The choice of the sample number for SVM to decide initial values of identified parameters is extensively discussed and analyzed. With de-noised motion data as input-output training samples, parameters of ship maneuvering models are estimated using RLS and SVM-RLS, respectively. The comparison between identification results and true values of parameters demonstrates that both the identified ship maneuvering models from RLS and SVM-RLS have reasonable agreements with simulated motions of the ship, and the increment of the sample for SVM positively affects the identification results. Furthermore, SVM-RLS using data de-noised by EMD shows the highest accuracy and best convergence.

  6. Pavement Subgrade Performance Study in the Danish Road Testing Machine

    DEFF Research Database (Denmark)

    Ullidtz, Per; Ertman Larsen, Hans Jørgen

    1997-01-01

    Most existing pavement subgrade criteria are based on the AASHO Road Test, where only one material was tested and for only one climatic condition. To study the validity of these criteria and to refine the criteria a co-operative research program entitled the "International Pavement Subgrade...... Performance Study" was sponsored by the FHWA with American, Finnish and Danish partners. This paper describes the first test series which was carried out in the Danish Road Testing Machine (RTM).The first step in this program is a full scale test on an instrumented pavement in the Danish Road Testing Machine....... Pressure gauges and strain cells were installed in the upper part of the subgrade, for measuring stresses and strains in all three directions. During and after construction FWD testing was carried out to evaluate the elastic parameters of the materials. These parameters were then used with the theory...

  7. A Hybrid Least Square Support Vector Machine Model with Parameters Optimization for Stock Forecasting

    Directory of Open Access Journals (Sweden)

    Jian Chai

    2015-01-01

    Full Text Available This paper proposes an EMD-LSSVM (empirical mode decomposition least squares support vector machine model to analyze the CSI 300 index. A WD-LSSVM (wavelet denoising least squares support machine is also proposed as a benchmark to compare with the performance of EMD-LSSVM. Since parameters selection is vital to the performance of the model, different optimization methods are used, including simplex, GS (grid search, PSO (particle swarm optimization, and GA (genetic algorithm. Experimental results show that the EMD-LSSVM model with GS algorithm outperforms other methods in predicting stock market movement direction.

  8. Study of on-machine error identification and compensation methods for micro machine tools

    International Nuclear Information System (INIS)

    Wang, Shih-Ming; Yu, Han-Jen; Lee, Chun-Yi; Chiu, Hung-Sheng

    2016-01-01

    Micro machining plays an important role in the manufacturing of miniature products which are made of various materials with complex 3D shapes and tight machining tolerance. To further improve the accuracy of a micro machining process without increasing the manufacturing cost of a micro machine tool, an effective machining error measurement method and a software-based compensation method are essential. To avoid introducing additional errors caused by the re-installment of the workpiece, the measurement and compensation method should be on-machine conducted. In addition, because the contour of a miniature workpiece machined with a micro machining process is very tiny, the measurement method should be non-contact. By integrating the image re-constructive method, camera pixel correction, coordinate transformation, the error identification algorithm, and trajectory auto-correction method, a vision-based error measurement and compensation method that can on-machine inspect the micro machining errors and automatically generate an error-corrected numerical control (NC) program for error compensation was developed in this study. With the use of the Canny edge detection algorithm and camera pixel calibration, the edges of the contour of a machined workpiece were identified and used to re-construct the actual contour of the work piece. The actual contour was then mapped to the theoretical contour to identify the actual cutting points and compute the machining errors. With the use of a moving matching window and calculation of the similarity between the actual and theoretical contour, the errors between the actual cutting points and theoretical cutting points were calculated and used to correct the NC program. With the use of the error-corrected NC program, the accuracy of a micro machining process can be effectively improved. To prove the feasibility and effectiveness of the proposed methods, micro-milling experiments on a micro machine tool were conducted, and the results

  9. Design of Parameter Independent, High Performance Sensorless Controllers for Permanent Magnet Synchronous Machines

    DEFF Research Database (Denmark)

    Xie, Ge

    . The transient fluctuation of the estimated rotor position error is around 20 degrees with a step load torque change from 0% to 100% of the rated torque. The position error in steady state is within ±2 electrical degrees for the best case. The proposed method may also be used for e.g. online machine parameter......The Permanent Magnet Synchronous Machine (PMSM) has become an attractive candidate for various industrial applications due to its high efficiency and torque density. In the PMSM drive system, simple and robust control methods play an important role in achieving satisfactory drive performances....... For reducing the cost and increasing the reliability of the drive system, eliminating the mechanical sensor brings a lot advantages to the PMSM drive system. Therefore, sensorless control was developed and has been increasingly used in different PMSM drive systems in the last 20 years. However, machine...

  10. Evaluating the electrical discharge machining (EDM) parameters with using carbon nanotubes

    Science.gov (United States)

    Sari, M. M.; Noordin, M. Y.; Brusa, E.

    2012-09-01

    Electrical discharge machining (EDM) is one of the most accurate non traditional manufacturing processes available for creating tiny apertures, complex or simple shapes and geometries within parts and assemblies. Performance of the EDM process is usually evaluated in terms of surface roughness, existence of cracks, voids and recast layer on the surface of product, after machining. Unfortunately, the high heat generated on the electrically discharged material during the EDM process decreases the quality of products. Carbon nanotubes display unexpected strength and unique electrical and thermal properties. Multi-wall carbon nanotubes are therefore on purpose added to the dielectric used in the EDM process to improve its performance when machining the AISI H13 tool steel, by means of copper electrodes. Some EDM parameters such as material removal rate, electrode wear rate, surface roughness and recast layer are here first evaluated, then compared to the outcome of EDM performed without using nanotubes mixed to the dielectric. Independent variables investigated are pulse on time, peak current and interval time. Experimental evidences show that EDM process operated by mixing multi-wall carbon nanotubes within the dielectric looks more efficient, particularly if machining parameters are set at low pulse of energy.

  11. Evaluating the electrical discharge machining (EDM) parameters with using carbon nanotubes

    International Nuclear Information System (INIS)

    Sari, M M; Brusa, E; Noordin, M Y

    2012-01-01

    Electrical discharge machining (EDM) is one of the most accurate non traditional manufacturing processes available for creating tiny apertures, complex or simple shapes and geometries within parts and assemblies. Performance of the EDM process is usually evaluated in terms of surface roughness, existence of cracks, voids and recast layer on the surface of product, after machining. Unfortunately, the high heat generated on the electrically discharged material during the EDM process decreases the quality of products. Carbon nanotubes display unexpected strength and unique electrical and thermal properties. Multi-wall carbon nanotubes are therefore on purpose added to the dielectric used in the EDM process to improve its performance when machining the AISI H13 tool steel, by means of copper electrodes. Some EDM parameters such as material removal rate, electrode wear rate, surface roughness and recast layer are here first evaluated, then compared to the outcome of EDM performed without using nanotubes mixed to the dielectric. Independent variables investigated are pulse on time, peak current and interval time. Experimental evidences show that EDM process operated by mixing multi-wall carbon nanotubes within the dielectric looks more efficient, particularly if machining parameters are set at low pulse of energy.

  12. SU-F-T-521: Flattening-Filter-Free Beam Parameters Comparison From Different Linac Machine Types

    Energy Technology Data Exchange (ETDEWEB)

    Hussain, A [King Faisal Specialist Hospital, Riyadh, Saudi Arabia, Arkansas Cancer Institute, Pine Bluff, AR (Saudi Arabia)

    2016-06-15

    Purpose: Novel linac machines, TrueBeam (TB) and Elekta Versa have updated head designing and software control system, include flattening-filter-free (FFF) photon and electron beams. Later on FFF beams were also introduced on C-Series machines. In this work FFF beams for same energy 6MV but from different machine versions were studied with reference to beam data parameters. Methods: The 6MV-FFF percent depth doses, profile symmetry and flatness, dose rate tables, and multi-leaf collimator (MLC) transmission factors were measured during commissioning process of both C-series and Truebeam machines. The scanning and dosimetric data for 6MV-FFF beam from Truebeam and C-Series linacs was compared. A correlation of 6MV-FFF beam from Elekta Versa with that of Varian linacs was also found. Results: The scanning files were plotted for both qualitative and quantitative analysis. The dosimetric leaf gap (DLG) for C-Series 6MV-FFF beam is 1.1 mm. Published values for Truebeam dosimetric leaf gap is 1.16 mm. 6MV MLC transmission factor varies between 1.3 % and 1.4 % in two separate measurements and measured DLG values vary between 1.32 mm and 1.33 mm on C-Series machine. MLC transmission factor from C-Series machine varies between 1.5 % and 1.6 %. Some of the measured data values from C-Series FFF beam are compared with Truebeam representative data. 6MV-FFF beam parameter values like dmax, OP factors, beam symmetry and flatness and additional parameters for C-Series and Truebeam liancs will be presented and compared in graphical form and tabular data form if selected. Conclusion: The 6MV flattening filter (FF) beam data from C-Series & Truebeam and 6MV-FFF beam data from Truebeam has already presented. This particular analysis to compare 6MV-FFF beam from C-Series and Truebeam provides opportunity to better elaborate FFF mode on novel machines. It was found that C-Series and Truebeam 6MV-FFF dosimetric and beam data was quite similar.

  13. Application of a virtual coordinate measuring machine for measurement uncertainty estimation of aspherical lens parameters

    International Nuclear Information System (INIS)

    Küng, Alain; Meli, Felix; Nicolet, Anaïs; Thalmann, Rudolf

    2014-01-01

    Tactile ultra-precise coordinate measuring machines (CMMs) are very attractive for accurately measuring optical components with high slopes, such as aspheres. The METAS µ-CMM, which exhibits a single point measurement repeatability of a few nanometres, is routinely used for measurement services of microparts, including optical lenses. However, estimating the measurement uncertainty is very demanding. Because of the many combined influencing factors, an analytic determination of the uncertainty of parameters that are obtained by numerical fitting of the measured surface points is almost impossible. The application of numerical simulation (Monte Carlo methods) using a parametric fitting algorithm coupled with a virtual CMM based on a realistic model of the machine errors offers an ideal solution to this complex problem: to each measurement data point, a simulated measurement variation calculated from the numerical model of the METAS µ-CMM is added. Repeated several hundred times, these virtual measurements deliver the statistical data for calculating the probability density function, and thus the measurement uncertainty for each parameter. Additionally, the eventual cross-correlation between parameters can be analyzed. This method can be applied for the calibration and uncertainty estimation of any parameter of the equation representing a geometric element. In this article, we present the numerical simulation model of the METAS µ-CMM and the application of a Monte Carlo method for the uncertainty estimation of measured asphere parameters. (paper)

  14. Optimizing Support Vector Machine Parameters with Genetic Algorithm for Credit Risk Assessment

    Science.gov (United States)

    Manurung, Jonson; Mawengkang, Herman; Zamzami, Elviawaty

    2017-12-01

    Support vector machine (SVM) is a popular classification method known to have strong generalization capabilities. SVM can solve the problem of classification and linear regression or nonlinear kernel which can be a learning algorithm for the ability of classification and regression. However, SVM also has a weakness that is difficult to determine the optimal parameter value. SVM calculates the best linear separator on the input feature space according to the training data. To classify data which are non-linearly separable, SVM uses kernel tricks to transform the data into a linearly separable data on a higher dimension feature space. The kernel trick using various kinds of kernel functions, such as : linear kernel, polynomial, radial base function (RBF) and sigmoid. Each function has parameters which affect the accuracy of SVM classification. To solve the problem genetic algorithms are proposed to be applied as the optimal parameter value search algorithm thus increasing the best classification accuracy on SVM. Data taken from UCI repository of machine learning database: Australian Credit Approval. The results show that the combination of SVM and genetic algorithms is effective in improving classification accuracy. Genetic algorithms has been shown to be effective in systematically finding optimal kernel parameters for SVM, instead of randomly selected kernel parameters. The best accuracy for data has been upgraded from kernel Linear: 85.12%, polynomial: 81.76%, RBF: 77.22% Sigmoid: 78.70%. However, for bigger data sizes, this method is not practical because it takes a lot of time.

  15. Field tests and machine learning approaches for refining algorithms and correlations of driver's model parameters.

    Science.gov (United States)

    Tango, Fabio; Minin, Luca; Tesauri, Francesco; Montanari, Roberto

    2010-03-01

    This paper describes the field tests on a driving simulator carried out to validate the algorithms and the correlations of dynamic parameters, specifically driving task demand and drivers' distraction, able to predict drivers' intentions. These parameters belong to the driver's model developed by AIDE (Adaptive Integrated Driver-vehicle InterfacE) European Integrated Project. Drivers' behavioural data have been collected from the simulator tests to model and validate these parameters using machine learning techniques, specifically the adaptive neuro fuzzy inference systems (ANFIS) and the artificial neural network (ANN). Two models of task demand and distraction have been developed, one for each adopted technique. The paper provides an overview of the driver's model, the description of the task demand and distraction modelling and the tests conducted for the validation of these parameters. A test comparing predicted and expected outcomes of the modelled parameters for each machine learning technique has been carried out: for distraction, in particular, promising results (low prediction errors) have been obtained by adopting an artificial neural network.

  16. OPTIMIZATION OF MACHINING PARAMETERS USING TAGUCHI APPROACH DURING HARD TURNING OF ALLOY STEEL WITH UNCOATED CARBIDE UNDER DRY CUTTING ENVIRONMENT

    Directory of Open Access Journals (Sweden)

    A. Das

    2015-12-01

    Full Text Available In today’s world of manufacturing by machining process two things are very important, one is productivity and the other one is quality. Quality of a product generally depends upon the surface finish and dimensional deviations. The productivity can be seen as a key economic indicator of innovation in terms of higher material removal rate with a less time and cost in machining industries. Taguchi method is a popular statistical technique for optimization of input parameters to get the best output results. Dry machining is a popular methodology for machining hard material and it has been accepted by many researchers to a great extent because of its low cost and safety. Many scientists have taken various input parameters and studied their effects on different output responses. In the present paper an attempt has been made to study the effect of input parameters such as cutting speed, feed rate and depth of cut on Surface roughness, Tool wear, Power consumption and Chip reduction co-efficient under dry condition using uncoated carbide insert. Signal to noise ratio has been used to select the optimal condition for various output responses. ANOVA table has been drawn for each output responses and finally mathematical model of multiple regression analysis has been prepared and authenticity of the statistical model have been checked by normal probability plot. It has been found from the experimental result that the power consumption and flank wear both were minimum at the cutting speed of 250 rpm and 400 rpm respectively. Chip reduction coefficient has been found minimum at a depth of cut of 0.3 mm and surface roughness was minimum at 0.1 mm/rev. feed rate.

  17. Summary of Session 2 "Machine Studies"

    CERN Document Server

    Assmann, R W

    2012-01-01

    This document summarizes the talks and discussion that took place in the second session of the Chamonix 2012 workshop concerning results from machine studies performed in 2011. The session consisted of the following presentations: “LHC experience with different bunch spacings” by G. Rumolo; “Observations of beam-beam effects in MDs in 2011” by W. Herr; “Beam-induced heating/ bunch length/RF and lessons for 2012” by E. Metral; “Lessons in beam diagnostics” by R. Jones; “Quench margins” by M. Sapinski; “First demonstration with beam of the Achromatic Telescopic Squeeze (ATS)” by S. Fartoukh.

  18. Summary of Session 2 'Machine Studies'

    Energy Technology Data Exchange (ETDEWEB)

    Assmann, R W; Papotti, G [European Organization for Nuclear Research, Geneva (Switzerland)

    2012-07-01

    This document summarizes the talks and discussion that took place in the second session of the Chamonix 2012 workshop concerning results from machine studies performed in 2011. The session consisted of the following presentations: “LHC experience with different bunch spacings” by G. Rumolo; “Observations of beam-beam effects in MDs in 2011” by W. Herr; “Beam-induced heating/ bunch length/RF and lessons for 2012” by E. Metral; “Lessons in beam diagnostics” by R. Jones; “Quench margins” by M. Sapinski; “First demonstration with beam of the Achromatic Telescopic Squeeze (ATS)” by S. Fartoukh. (author)

  19. Feature Selection and Parameter Optimization of Support Vector Machines Based on Modified Artificial Fish Swarm Algorithms

    Directory of Open Access Journals (Sweden)

    Kuan-Cheng Lin

    2015-01-01

    Full Text Available Rapid advances in information and communication technology have made ubiquitous computing and the Internet of Things popular and practicable. These applications create enormous volumes of data, which are available for analysis and classification as an aid to decision-making. Among the classification methods used to deal with big data, feature selection has proven particularly effective. One common approach involves searching through a subset of the features that are the most relevant to the topic or represent the most accurate description of the dataset. Unfortunately, searching through this kind of subset is a combinatorial problem that can be very time consuming. Meaheuristic algorithms are commonly used to facilitate the selection of features. The artificial fish swarm algorithm (AFSA employs the intelligence underlying fish swarming behavior as a means to overcome optimization of combinatorial problems. AFSA has proven highly successful in a diversity of applications; however, there remain shortcomings, such as the likelihood of falling into a local optimum and a lack of multiplicity. This study proposes a modified AFSA (MAFSA to improve feature selection and parameter optimization for support vector machine classifiers. Experiment results demonstrate the superiority of MAFSA in classification accuracy using subsets with fewer features for given UCI datasets, compared to the original FASA.

  20. Correlating neutron yield and reliability for selecting experimental parameters for a plasma focus machine

    International Nuclear Information System (INIS)

    Pross, G.

    Possibilities of optimizing focus machines with a given energy content in the sense of high neutron yield and high reliability of the discharges are investigated experimentally. For this purpose, a focus machine of the Mather type with an energy content of 12 kJ was constructed. The following experimental parameters were varied: the material of the insulator in the ignition zone, the structure of the outside electrode, the length of the inside electrode, the filling pressure and the amount and polarity of the battery voltage. An important part of the diagnostic program consists of measurements of the azimuthal and axial current distribution in the accelerator, correlated with short-term photographs of the luminous front as a function of time. The results are given. A functional schematic has been drafted for focus discharge as an aid in extensive optimization of focus machines, combining findings from theory and experiments. The schematic takes into account the multiparameter character of the discharge and clarifies relationships between the experimental parameters and the target variables neutron yield and reliability

  1. Using Perturbed Physics Ensembles and Machine Learning to Select Parameters for Reducing Regional Biases in a Global Climate Model

    Science.gov (United States)

    Li, S.; Rupp, D. E.; Hawkins, L.; Mote, P.; McNeall, D. J.; Sarah, S.; Wallom, D.; Betts, R. A.

    2017-12-01

    This study investigates the potential to reduce known summer hot/dry biases over Pacific Northwest in the UK Met Office's atmospheric model (HadAM3P) by simultaneously varying multiple model parameters. The bias-reduction process is done through a series of steps: 1) Generation of perturbed physics ensemble (PPE) through the volunteer computing network weather@home; 2) Using machine learning to train "cheap" and fast statistical emulators of climate model, to rule out regions of parameter spaces that lead to model variants that do not satisfy observational constraints, where the observational constraints (e.g., top-of-atmosphere energy flux, magnitude of annual temperature cycle, summer/winter temperature and precipitation) are introduced sequentially; 3) Designing a new PPE by "pre-filtering" using the emulator results. Steps 1) through 3) are repeated until results are considered to be satisfactory (3 times in our case). The process includes a sensitivity analysis to find dominant parameters for various model output metrics, which reduces the number of parameters to be perturbed with each new PPE. Relative to observational uncertainty, we achieve regional improvements without introducing large biases in other parts of the globe. Our results illustrate the potential of using machine learning to train cheap and fast statistical emulators of climate model, in combination with PPEs in systematic model improvement.

  2. Effect of different parameters on machining of SiC/SiC composites via pico-second laser

    Energy Technology Data Exchange (ETDEWEB)

    Li, Weinan; Zhang, Ruoheng [State Key Laboratory of Transient Optics and Photonics, Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi’an, Shaanxi 10068 (China); Liu, Yongsheng, E-mail: yongshengliu@nwpu.edu.cn [Science and technology on Thermostructure Composite Materials Laboratory, Northwestern Polytechnical University, Xi’an, Shaanxi 710072 (China); Wang, Chunhui; Wang, Jing [Science and technology on Thermostructure Composite Materials Laboratory, Northwestern Polytechnical University, Xi’an, Shaanxi 710072 (China); Yang, Xiaojun [State Key Laboratory of Transient Optics and Photonics, Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi’an, Shaanxi 10068 (China); Cheng, Laifei [Science and technology on Thermostructure Composite Materials Laboratory, Northwestern Polytechnical University, Xi’an, Shaanxi 710072 (China)

    2016-02-28

    Graphical abstract: - Highlights: • The highlights of the manuscript include the following two aspects. • First, we found that the different machining modes (helical line scanning and single ring line scanning) and processing power of machining have remarkable effect on the surface morphology of the machined area, such as the shape, depth and the formation of different surface structures. • Secondly, we investigated that the debris consisted of C, Si and O was observed on the machined surface. • Some of the Si–C bonds of the SiC matrix and fibers would be transformed into Si–O bonds after machined, depending on the processing power. - Abstract: Pico-second laser plays an important role in modern machining technology, especially in machining high hardness materials. In this article, pico-second laser was utilized for irradiation on SiC/SiC composites, and effects of different processing parameters including the machining modes and laser power were discussed in detail. The results indicated that the machining modes and laser power had great effect on machining of SiC/SiC composites. Different types of surface morphology and structure were observed under helical line scanning and single ring line scanning, and the analysis of their formulation was discussed in detail. It was believed that the machining modes would be responsible to the different shapes of machining results at the same parameters. The processing power shall also influence the surface morphology and quality of machining results. In micro-hole drilling process, large amount of debris and fragments were observed within the micro-holes, and XPS analysis showed that there existed Si–O bonds and Si–C bonds, indicating that the oxidation during processing was incomplete. Other surface morphology, such as pores and pits were discussed as well.

  3. Parameters identification of the compound cage rotor induction machine based on linearized Kalman filtering

    Institute of Scientific and Technical Information of China (English)

    王铁成; 李伟力; 孙建伟

    2003-01-01

    A mathematical model has been built up for compound cage rotor induction machine with the rotor re-sistance and leakage inductance in the model identified through Kalman filtering method. Using the identifiedparameters, simulation studies are performed, and simulation results are compared with testing results.

  4. Evaluation of Empirical and Machine Learning Algorithms for Estimation of Coastal Water Quality Parameters

    Directory of Open Access Journals (Sweden)

    Majid Nazeer

    2017-11-01

    Full Text Available Coastal waters are one of the most vulnerable resources that require effective monitoring programs. One of the key factors for effective coastal monitoring is the use of remote sensing technologies that significantly capture the spatiotemporal variability of coastal waters. Optical properties of coastal waters are strongly linked to components, such as colored dissolved organic matter (CDOM, chlorophyll-a (Chl-a, and suspended solids (SS concentrations, which are essential for the survival of a coastal ecosystem and usually independent of each other. Thus, developing effective remote sensing models to estimate these important water components based on optical properties of coastal waters is mandatory for a successful coastal monitoring program. This study attempted to evaluate the performance of empirical predictive models (EPM and neural networks (NN-based algorithms to estimate Chl-a and SS concentrations, in the coastal area of Hong Kong. Remotely-sensed data over a 13-year period was used to develop regional and local models to estimate Chl-a and SS over the entire Hong Kong waters and for each water class within the study area, respectively. The accuracy of regional models derived from EPM and NN in estimating Chl-a and SS was 83%, 93%, 78%, and 97%, respectively, whereas the accuracy of local models in estimating Chl-a and SS ranged from 60–94% and 81–94%, respectively. Both the regional and local NN models exhibited a higher performance than those models derived from empirical analysis. Thus, this study suggests using machine learning methods (i.e., NN for the more accurate and efficient routine monitoring of coastal water quality parameters (i.e., Chl-a and SS concentrations over the complex coastal area of Hong Kong and other similar coastal environments.

  5. Detecting epileptic seizure with different feature extracting strategies using robust machine learning classification techniques by applying advance parameter optimization approach.

    Science.gov (United States)

    Hussain, Lal

    2018-06-01

    Epilepsy is a neurological disorder produced due to abnormal excitability of neurons in the brain. The research reveals that brain activity is monitored through electroencephalogram (EEG) of patients suffered from seizure to detect the epileptic seizure. The performance of EEG detection based epilepsy require feature extracting strategies. In this research, we have extracted varying features extracting strategies based on time and frequency domain characteristics, nonlinear, wavelet based entropy and few statistical features. A deeper study was undertaken using novel machine learning classifiers by considering multiple factors. The support vector machine kernels are evaluated based on multiclass kernel and box constraint level. Likewise, for K-nearest neighbors (KNN), we computed the different distance metrics, Neighbor weights and Neighbors. Similarly, the decision trees we tuned the paramours based on maximum splits and split criteria and ensemble classifiers are evaluated based on different ensemble methods and learning rate. For training/testing tenfold Cross validation was employed and performance was evaluated in form of TPR, NPR, PPV, accuracy and AUC. In this research, a deeper analysis approach was performed using diverse features extracting strategies using robust machine learning classifiers with more advanced optimal options. Support Vector Machine linear kernel and KNN with City block distance metric give the overall highest accuracy of 99.5% which was higher than using the default parameters for these classifiers. Moreover, highest separation (AUC = 0.9991, 0.9990) were obtained at different kernel scales using SVM. Additionally, the K-nearest neighbors with inverse squared distance weight give higher performance at different Neighbors. Moreover, to distinguish the postictal heart rate oscillations from epileptic ictal subjects, and highest performance of 100% was obtained using different machine learning classifiers.

  6. Study of the stiffness for predicting the accuracy of machine tools

    International Nuclear Information System (INIS)

    Ortega, N.; Campa, F.J.; Fernandez Valdivielso, A.; Alonso, U.; Olvera, D.; Compean, F.I.

    2010-01-01

    Machining processes are frequently faced with the challenge of achieving more and more precision and surface qualities. These requirements are usually attained taking into account some process variables, including the cutting parameters and the use or not of refrigerant, leaving aside the mechanical aspects associated with the influence of machine tool itself. There are many sources of error linked with machine-workpiece interaction, but, in general, we can summarize them into two types of error: quasi-static and dynamic. This paper shows the influence of quasi-static error caused by low machine rigidity on the accuracy applied on two very different processes: turning and grinding. For the study of the static stiffness of these two machines, two different methods are proposed, both of them equally valid. The first one is based on separated parameters and the second one on finite elements. (Author).

  7. A feasability study of possible machine options

    International Nuclear Information System (INIS)

    Asner, A.; Baconnier, Y.; Barbalat, O.; Bassetti, M.; Benvenuti, C.; Billinge, R.; Boussard, D.; Brandt, D.; Brianti, G.; Calder, R.; Evans, L.R.; Fasso, A.; Gareyte, J.; Garoby, R.; Goebel, K.; Groebner, O.; Haebel, E.; Hagedorn, D.; Henke, H.; Hilleret, N.; Hoefert, M.; Huebner, K.; Hutton, A.; Johnson, K.; Jowett, J.; Keil, E.; Laurent, J.M.; Lebrun, P.; Leroy, D.; Morpurgo, M.; Myers, S.; Perin, R.; Picasso, E.; Poncet, A.; Reinhardt, H.P.; Resegotti, L.; Rubbia, C.; Scandale, W.; Schmid, J.; Schnell, W.; Schoenbacher, H.; Stevenson, G.; Tortschanoff, T.; Vos, L.; Weisse, E.; Wilson, I.; Wolf, R.; Zotter, B.

    1984-01-01

    This feasibility study deals with proton-proton and proton-antiproton colliders with centre-of-mass energies from 10 to 18 TeV, which could be installed in the tunnel after the completion of LEP. Since the main purpose of the study is to determine the influence of limitations in space and technology, most of the work has been devoted to the proton-proton option at the higher energy which, while being the most demanding holds the promise of best performance (luminosity up to approx.= 10 33 cm -2 s -1 ) and greatest reliability. It turns out that the space in the tunnel above LEP will be quite adequate. Proton-antiproton operation would also be possible in such a machine at lower luminosity. Of course the tunnel could also house a single-channel proton-antiproton collider, operating up to the highest energy but at a lower luminosity. (orig.)

  8. Automated valve fault detection based on acoustic emission parameters and support vector machine

    Directory of Open Access Journals (Sweden)

    Salah M. Ali

    2018-03-01

    Full Text Available Reciprocating compressors are one of the most used types of compressors with wide applications in industry. The most common failure in reciprocating compressors is always related to the valves. Therefore, a reliable condition monitoring method is required to avoid the unplanned shutdown in this category of machines. Acoustic emission (AE technique is one of the effective recent methods in the field of valve condition monitoring. However, a major challenge is related to the analysis of AE signal which perhaps only depends on the experience and knowledge of technicians. This paper proposes automated fault detection method using support vector machine (SVM and AE parameters in an attempt to reduce human intervention in the process. Experiments were conducted on a single stage reciprocating air compressor by combining healthy and faulty valve conditions to acquire the AE signals. Valve functioning was identified through AE waveform analysis. SVM faults detection model was subsequently devised and validated based on training and testing samples respectively. The results demonstrated automatic valve fault detection model with accuracy exceeding 98%. It is believed that valve faults can be detected efficiently without human intervention by employing the proposed model for a single stage reciprocating compressor. Keywords: Condition monitoring, Faults detection, Signal analysis, Acoustic emission, Support vector machine

  9. Optimal Machining Parameters for Achieving the Desired Surface Roughness in Turning of Steel

    Directory of Open Access Journals (Sweden)

    LB Abhang

    2012-06-01

    Full Text Available Due to the widespread use of highly automated machine tools in the metal cutting industry, manufacturing requires highly reliable models and methods for the prediction of output performance in the machining process. The prediction of optimal manufacturing conditions for good surface finish and dimensional accuracy plays a very important role in process planning. In the steel turning process the tool geometry and cutting conditions determine the time and cost of production which ultimately affect the quality of the final product. In the present work, experimental investigations have been conducted to determine the effect of the tool geometry (effective tool nose radius and metal cutting conditions (cutting speed, feed rate and depth of cut on surface finish during the turning of EN-31 steel. First and second order mathematical models are developed in terms of machining parameters by using the response surface methodology on the basis of the experimental results. The surface roughness prediction model has been optimized to obtain the surface roughness values by using LINGO solver programs. LINGO is a mathematical modeling language which is used in linear and nonlinear optimization to formulate large problems concisely, solve them, and analyze the solution in engineering sciences, operation research etc. The LINGO solver program is global optimization software. It gives minimum values of surface roughness and their respective optimal conditions.

  10. Factors affecting the laser processing of wood, 2: Effects of material parameters on machinability

    International Nuclear Information System (INIS)

    Arai, T.; Hayashi, D.

    1994-01-01

    Material parameters of wood were investigated. Factors relating to the workpiece include cutting direction, specific gravity, and components of the wood such as resin-like materials. Also studies of the effects of irregular tissue on machinability were made. The interactions between laser beam and materials are often greatly complex. They depend on the characteristics of the laser beam, the thermal constants of the woods, and the optical surface properties of the woods. Therefore, high quality beam mode and carefully selected materials were used. The following laser cutting properties became clear after studying the experimental results. Slow speed cutting and softwoods make slight differences, regarding cutting section and fiber direction. However, it can beconsidered that there is not very much change except in cross-section. Because of the high power density of laser, cutting speed makes no big difference. The irregular tissue of wood cannot maintain normal cutting speed and accuracy. The factor of genuine density eta, which is thought to be entirely independent of each specific gravity, is definedas the concept of density in general. It can be obtained by applying a simple rule, that is, the eta is the ratio of r(u)/rho(s) where rho(s) is the wood substance as the characteristic value of wood, and r(u)is specific gravity. An experimental formula shows that the depth of cut decreases in proportion to the value of eta. However, in the strict sense of the word, data of wood material as a natural resources mustbe treated qualitatively, because there are deviations from regularity due to various reasons. (author)

  11. EXPERIMENTAL STUDY OF THE DYNAMICS OF CENTRIFUGAL CASTING MACHINES FOR PRODUCTION OF MILL ROLLS

    Directory of Open Access Journals (Sweden)

    P. G. Anofriev

    2017-06-01

    Full Text Available Purpose. The main purpose of experimental studies is to establish the adequacy of the developed mathematical models of machine fluctuations and the actual parameters of machine vibration. Almost all casting machines for the production of mill rolls have a unique design and performances. The additional aim of this work is to compare the vibration level of the casting machine with the requirements of the current vibration standards for new technological machines. Frequency analysis of the oscillations allows establishing defects in workmanship, errors of rotating parts installation and their influence on the dynamics of the machine. Methodology. Measurement of vibration parameters was performed on the moving parts of roller bearings of the machine. To measure the amplitudes of accelerations in three mutually perpendicular directions piezoelectric sensors with magnetic mount were used. Electrical signals from the sensors were recorded on magnetic tape. Further analysis of the oscillations was carried out and visualized using specialized frequency analyzer. The frequency analyzer implements the algorithm of fast Fourier transformation and/or integration of sensor input signal. After the first integration the data for plotting the vibration velocity spectrogram were obtained and as a result of the second integration there are the data of vibration displacements spectrogram of the machine supports. Findings. The results of experimental studies of centrifugal casting machine vibrations for the production of two-layer rolls were presented. There were obtained and analyzed the spectrograms of accelerations, velocities and displacements of moving parts of the upper and lower roller supports. The work of the machine is associated with the calculated values passing of critical frequencies and the short-term development of resonance oscillations of the rotor and roller bearings. Originality. For the first time the author obtained the frequency spectra of

  12. Using Phun to Study "Perpetual Motion" Machines

    Science.gov (United States)

    Kores, Jaroslav

    2012-01-01

    The concept of "perpetual motion" has a long history. The Indian astronomer and mathematician Bhaskara II (12th century) was the first person to describe a perpetual motion (PM) machine. An example of a 13th-century PM machine is shown in Fig. 1. Although the law of conservation of energy clearly implies the impossibility of PM construction, over…

  13. Recovery studies for plutonium machining oil coolant

    International Nuclear Information System (INIS)

    Navratil, J.D.; Baldwin, C.E.

    1977-01-01

    Lathe coolant oil, contaminated with plutonium and having a carbon tetrachloride diluent, is generated in plutonium machining areas at Rocky Flats. A research program was initiated to determine the nature of plutonium in this mixture of oil and carbon tetrachloride. Appropriate methods then could be developed to remove the plutonium and to recycle the oil and carbon tetrachloride. Studies showed that the mixtures of spent oil and carbon tetrachloride contained particulate plutonium and plutonium species that are soluble in water or in oil and carbon tetrachloride. The particulate plutonium was removed by filtration; the nonfilterable plutonium was removed by adsorption on various materials. Laboratory-scale tests indicated the lathe-coolant oil mixture could be separated by distilling the carbon tetrachloride to yield recyclable products

  14. Beam homogeneity and dependence of a Thomson ionic microetching machine on the variation in the working parameters

    International Nuclear Information System (INIS)

    Pere, J.F.

    1974-01-01

    The specific use of ion beam machining in selective etching of superposed thin films requires a rigourous control of the process. This control entails the two following requirements: a perfect etching uniformity on a large duty surface, an excellent reproducibility in etching velocities. Such performance can be obtained only from a systematic optimization study for the various discharge and neutralization parameters. Results obtained give information on the role and criticality of each of them, the mutual influences appearing at use, as well as improvements to be done [fr

  15. Using Phun to Study ``Perpetual Motion'' Machines

    Science.gov (United States)

    Koreš, Jaroslav

    2012-05-01

    The concept of "perpetual motion" has a long history. The Indian astronomer and mathematician Bhaskara II (12th century) was the first person to describe a perpetual motion (PM) machine. An example of a 13th- century PM machine is shown in Fig. 1. Although the law of conservation of energy clearly implies the impossibility of PM construction, over the centuries numerous proposals for PM have been made, involving ever more elements of modern science in their construction. It is possible to test a variety of PM machines in the classroom using a program called Phun2 or its commercial version Algodoo.3 The programs are designed to simulate physical processes and we can easily simulate mechanical machines using them. They provide an intuitive graphical environment controlled with a mouse; a programming language is not needed. This paper describes simulations of four different (supposed) PM machines.4

  16. Advances in three-dimensional field analysis and evaluation of performance parameters of electrical machines

    Science.gov (United States)

    Sivasubramaniam, Kiruba

    This thesis makes advances in three dimensional finite element analysis of electrical machines and the quantification of their parameters and performance. The principal objectives of the thesis are: (1)the development of a stable and accurate method of nonlinear three-dimensional field computation and application to electrical machinery and devices; and (2)improvement in the accuracy of determination of performance parameters, particularly forces and torque computed from finite elements. Contributions are made in two general areas: a more efficient formulation for three dimensional finite element analysis which saves time and improves accuracy, and new post-processing techniques to calculate flux density values from a given finite element solution. A novel three-dimensional magnetostatic solution based on a modified scalar potential method is implemented. This method has significant advantages over the traditional total scalar, reduced scalar or vector potential methods. The new method is applied to a 3D geometry of an iron core inductor and a permanent magnet motor. The results obtained are compared with those obtained from traditional methods, in terms of accuracy and speed of computation. A technique which has been observed to improve force computation in two dimensional analysis using a local solution of Laplace's equation in the airgap of machines is investigated and a similar method is implemented in the three dimensional analysis of electromagnetic devices. A new integral formulation to improve force calculation from a smoother flux-density profile is also explored and implemented. Comparisons are made and conclusions drawn as to how much improvement is obtained and at what cost. This thesis also demonstrates the use of finite element analysis to analyze torque ripples due to rotor eccentricity in permanent magnet BLDC motors. A new method for analyzing torque harmonics based on data obtained from a time stepping finite element analysis of the machine is

  17. Estimates of the atmospheric parameters of M-type stars: a machine-learning perspective

    Science.gov (United States)

    Sarro, L. M.; Ordieres-Meré, J.; Bello-García, A.; González-Marcos, A.; Solano, E.

    2018-05-01

    Estimating the atmospheric parameters of M-type stars has been a difficult task due to the lack of simple diagnostics in the stellar spectra. We aim at uncovering good sets of predictive features of stellar atmospheric parameters (Teff, log (g), [M/H]) in spectra of M-type stars. We define two types of potential features (equivalent widths and integrated flux ratios) able to explain the atmospheric physical parameters. We search the space of feature sets using a genetic algorithm that evaluates solutions by their prediction performance in the framework of the BT-Settl library of stellar spectra. Thereafter, we construct eight regression models using different machine-learning techniques and compare their performances with those obtained using the classical χ2 approach and independent component analysis (ICA) coefficients. Finally, we validate the various alternatives using two sets of real spectra from the NASA Infrared Telescope Facility (IRTF) and Dwarf Archives collections. We find that the cross-validation errors are poor measures of the performance of regression models in the context of physical parameter prediction in M-type stars. For R ˜ 2000 spectra with signal-to-noise ratios typical of the IRTF and Dwarf Archives, feature selection with genetic algorithms or alternative techniques produces only marginal advantages with respect to representation spaces that are unconstrained in wavelength (full spectrum or ICA). We make available the atmospheric parameters for the two collections of observed spectra as online material.

  18. Tunnel Boring Machine Performance Study. Final Report

    Science.gov (United States)

    1984-06-01

    Full face tunnel boring machine "TBM" performance during the excavation of 6 tunnels in sedimentary rock is considered in terms of utilization, penetration rates and cutter wear. The construction records are analyzed and the results are used to inves...

  19. Photoelectron studies of machined brass surfaces

    Science.gov (United States)

    Potts, A. W.; Merrison, J. P.; Tournas, A. D.; Yacoot, A.

    UV photoelectron spectroscopy has been used to determine the surface composition of machined brass. The results show a considerable change between the photoelectron surface composition and the bulk composition of the same sample determined by energy-dispersive X-ray fluorescence. On the surface the lead composition is increased by ˜900 G. This is consistent with the important part that lead is believed to play in improving the machinability of this alloy.

  20. Depth analysis of mechanically machined flaws on steam generator tubings using multi-parameter algorithm

    International Nuclear Information System (INIS)

    Nam Gung, Chan; Lee, Yoon Sang; Hwang, Seong Sik; Kim, Hong Pyo

    2004-01-01

    The eddy current testing (ECT) is a nondestructive technique. It is used for evaluation of material's integrity, especially, steam generator (SG) tubing in nuclear plants, due to their rapid inspection, safe and easy operation. For depth measurement of defects, we prepared Electro Discharge Machined (EDM) notches that have several of defects and applied multi-parameter (MP) algorithm. It is a crack shape estimation program developed in Argonne National Laboratory (ANL). To evaluate the MP algorithm, we compared defect profile with fractography of the defects. In the following sections, we described the basic structure of a computer-aided data analysis algorithm used as means of more accurate and efficient processing of ECT data, and explained the specification of a standard calibration. Finally, we discussed the accuracy of estimated depth profile compared with conventional ECT method

  1. Parameters selection in gene selection using Gaussian kernel support vector machines by genetic algorithm

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    In microarray-based cancer classification, gene selection is an important issue owing to the large number of variables and small number of samples as well as its non-linearity. It is difficult to get satisfying results by using conventional linear statistical methods. Recursive feature elimination based on support vector machine (SVM RFE) is an effective algorithm for gene selection and cancer classification, which are integrated into a consistent framework. In this paper, we propose a new method to select parameters of the aforementioned algorithm implemented with Gaussian kernel SVMs as better alternatives to the common practice of selecting the apparently best parameters by using a genetic algorithm to search for a couple of optimal parameter. Fast implementation issues for this method are also discussed for pragmatic reasons. The proposed method was tested on two representative hereditary breast cancer and acute leukaemia datasets. The experimental results indicate that the proposed method performs well in selecting genes and achieves high classification accuracies with these genes.

  2. Beam Dynamics Studies in Recirculating Machines

    CERN Document Server

    Pellegrini, Dario; Latina, A

    The LHeC and the CLIC Drive Beam share not only the high-current beams that make them prone to show instabilities, but also unconventional lattice topologies and operational schemes in which the time sequence of the bunches varies along the machine. In order to asses the feasibility of these projects, realistic simulations taking into account the most worrisome effects and their interplays, are crucial. These include linear and non-linear optics with time dependent elements, incoherent and coherent synchrotron radiation, short and long-range wakefields, beam-beam effect and ion cloud. In order to investigate multi-bunch effects in recirculating machines, a new version of the tracking code PLACET has been developed from scratch. PLACET2, already integrates most of the effects mentioned before and can easily receive additional physics. Its innovative design allows to describe complex lattices and track one or more bunches accordingly to the machine operation, reproducing the bunch train splitting and recombinat...

  3. Some new machine projects studied at LNS

    International Nuclear Information System (INIS)

    Tkatchenko, A.

    1983-01-01

    In front of the increasing interest for the synchrotron radiation uses, the electron storage rings have been gradually transformed in light sources. Yet, those machines had not been optimized for this use. So, in the last 10 years, numerous optimized machines have been defined and destinated to sole synchrotron light production up to the X domain. In the French domain, several projects have been elaborated, to satisfy the national needs in far UV and X radiation. - SUPER-ACO project (0,8 GeV) from Orsay. Its realisation is in progress. - SIREM project (1,2 GeV) from Grenoble CEN. - European ESRF project (5 GeV) optimized for X radiation, and for which a work group has been installed at CERN. - A X radiation national machine project (3 or 4 GeV) derived from the ESRF one. - At last, the Mars project, concerning a X radiation source storage ring aimed to a industrial use: the microlithographie [fr

  4. Jacks--A Study of Simple Machines.

    Science.gov (United States)

    Parsons, Ralph

    This vocational physics individualized student instructional module on jacks (simple machines used to lift heavy objects) contains student prerequisites and objectives, an introduction, and sections on the ratchet bumper jack, the hydraulic jack, the screw jack, and load limitations. Designed with a laboratory orientation, each section consists of…

  5. Effects of cutting parameters on machinability characteristics of Ni-based superalloys: a review

    Directory of Open Access Journals (Sweden)

    Kaya Eren

    2017-12-01

    Full Text Available Nickel based superalloys offer high strength, corrosion resistance, thermal stability and superb thermal fatigue properties. However, they have been one of the most difficult materials to machine due to these properties. Although we are witnessing improved machining strategies with the developing machining, tooling and inspection technologies, machining of nickel based superalloys is still a challenging task due to in-process strains and post process part quality demands.

  6. A MACHINE-LEARNING METHOD TO INFER FUNDAMENTAL STELLAR PARAMETERS FROM PHOTOMETRIC LIGHT CURVES

    International Nuclear Information System (INIS)

    Miller, A. A.; Bloom, J. S.; Richards, J. W.; Starr, D. L.; Lee, Y. S.; Butler, N. R.; Tokarz, S.; Smith, N.; Eisner, J. A.

    2015-01-01

    A fundamental challenge for wide-field imaging surveys is obtaining follow-up spectroscopic observations: there are >10 9 photometrically cataloged sources, yet modern spectroscopic surveys are limited to ∼few× 10 6 targets. As we approach the Large Synoptic Survey Telescope era, new algorithmic solutions are required to cope with the data deluge. Here we report the development of a machine-learning framework capable of inferring fundamental stellar parameters (T eff , log g, and [Fe/H]) using photometric-brightness variations and color alone. A training set is constructed from a systematic spectroscopic survey of variables with Hectospec/Multi-Mirror Telescope. In sum, the training set includes ∼9000 spectra, for which stellar parameters are measured using the SEGUE Stellar Parameters Pipeline (SSPP). We employed the random forest algorithm to perform a non-parametric regression that predicts T eff , log g, and [Fe/H] from photometric time-domain observations. Our final optimized model produces a cross-validated rms error (RMSE) of 165 K, 0.39 dex, and 0.33 dex for T eff , log g, and [Fe/H], respectively. Examining the subset of sources for which the SSPP measurements are most reliable, the RMSE reduces to 125 K, 0.37 dex, and 0.27 dex, respectively, comparable to what is achievable via low-resolution spectroscopy. For variable stars this represents a ≈12%-20% improvement in RMSE relative to models trained with single-epoch photometric colors. As an application of our method, we estimate stellar parameters for ∼54,000 known variables. We argue that this method may convert photometric time-domain surveys into pseudo-spectrographic engines, enabling the construction of extremely detailed maps of the Milky Way, its structure, and history

  7. The Effect of Operational Cutting Parameters on Nitinol-60 in Wire Electrodischarge Machining

    Directory of Open Access Journals (Sweden)

    Ali Akbar LotfiNeyestanak

    2013-01-01

    Full Text Available Shape memory alloys are a kind of active materials, which have significant characteristics in comparison with other alloys. Since these materials are applicable in different fields such as aerospace, automobile industry, medicine, and dentistry, the effects of wire electrodischarge machining on the properties of these alloys have been studied. In this paper, changes in the shape recovery ability and microhardness of the machined surface of Nitonol-60 shape memory alloy have been studied considering recasting and formation of resolidificated layer on the shape memory alloy surface. XRD and EDXA analyses of the surface layer of the sample besides a microscopic study of the shape memory alloy layer by SEM and a study of the changes in mechanical properties of the surface layer were done by performing microhardness and tension tests on the work piece surface. Considering the surface layer, reversible strain has been studied according to the shape recovery percentage of Nitinol-60 shape memory alloy. Results show that the surface layer formed on the surface of the samples has caused changes in both physical and mechanical properties of the cut surface because of the penetration of the separated materials in comparison with deeper layers of the piece.

  8. Revisit of Machine Learning Supported Biological and Biomedical Studies.

    Science.gov (United States)

    Yu, Xiang-Tian; Wang, Lu; Zeng, Tao

    2018-01-01

    Generally, machine learning includes many in silico methods to transform the principles underlying natural phenomenon to human understanding information, which aim to save human labor, to assist human judge, and to create human knowledge. It should have wide application potential in biological and biomedical studies, especially in the era of big biological data. To look through the application of machine learning along with biological development, this review provides wide cases to introduce the selection of machine learning methods in different practice scenarios involved in the whole biological and biomedical study cycle and further discusses the machine learning strategies for analyzing omics data in some cutting-edge biological studies. Finally, the notes on new challenges for machine learning due to small-sample high-dimension are summarized from the key points of sample unbalance, white box, and causality.

  9. Fundamental Study on Electrical Discharge Machining

    OpenAIRE

    Uno, Yoshiyuki; Nakajima, Toshikatsu; Endo, Osamu

    1989-01-01

    The generation mechanism of crater in electrical discharge machining is analyzed with a single pulse discharge device for alloy tool steel, black alumina ceramics, cermet and cemented carbide, investigating the gap voltage, the discharge current, the shape of crater, the wear of electrode and so on. The experimental analysis makes it clear that the shape of crater has a characteristic feature for the kind of workpiece. The shape of electrode, which changes with the wear by an electric spark, ...

  10. Optimization of machining parameters in dry EDM of EN31 steel

    Science.gov (United States)

    Brar, G. S.

    2018-03-01

    Dry electric discharge machining (Dry EDM) is one of the novel EDM technology in which gases namely helium, argon, oxygen, nitrogen etc. are used as a dielectric medium at high pressure instead of oil based liquid dielectric. The present study investigates dry electric discharge machining (with rotary tool) of EN-31 steel to achieve lower tool wear rate (TWR) and better surface roughness (Ra) by performing a set of exploratory experiments with oxygen gas as dielectric. The effect of polarity, discharge current, gas flow pressure, pulse-on time, R.P.M. and gap voltage on the MRR, TWR and surface roughness (Ra) in dry EDM was studied with copper as rotary tool. The significant factors affecting MRR are discharge current and pulse on time. The significant factors affecting TWR are gas flow pressure, pulse on time and R.P.M. TWR was found close to zero in most of the experiments. The significant factors affecting Ra are pulse on time, gas flow pressure and R.P.M. It was found that polarity has nearly zero effect on all the three output variables.

  11. Studying depression using imaging and machine learning methods

    Directory of Open Access Journals (Sweden)

    Meenal J. Patel

    2016-01-01

    Full Text Available Depression is a complex clinical entity that can pose challenges for clinicians regarding both accurate diagnosis and effective timely treatment. These challenges have prompted the development of multiple machine learning methods to help improve the management of this disease. These methods utilize anatomical and physiological data acquired from neuroimaging to create models that can identify depressed patients vs. non-depressed patients and predict treatment outcomes. This article (1 presents a background on depression, imaging, and machine learning methodologies; (2 reviews methodologies of past studies that have used imaging and machine learning to study depression; and (3 suggests directions for future depression-related studies.

  12. Studying depression using imaging and machine learning methods.

    Science.gov (United States)

    Patel, Meenal J; Khalaf, Alexander; Aizenstein, Howard J

    2016-01-01

    Depression is a complex clinical entity that can pose challenges for clinicians regarding both accurate diagnosis and effective timely treatment. These challenges have prompted the development of multiple machine learning methods to help improve the management of this disease. These methods utilize anatomical and physiological data acquired from neuroimaging to create models that can identify depressed patients vs. non-depressed patients and predict treatment outcomes. This article (1) presents a background on depression, imaging, and machine learning methodologies; (2) reviews methodologies of past studies that have used imaging and machine learning to study depression; and (3) suggests directions for future depression-related studies.

  13. Toolpath Strategy and Optimum Combination of Machining Parameter during Pocket Mill Process of Plastic Mold Steels Material

    Science.gov (United States)

    Wibowo, Y. T.; Baskoro, S. Y.; Manurung, V. A. T.

    2018-02-01

    Plastic based products spread all over the world in many aspects of life. The ability to substitute other materials is getting stronger and wider. The use of plastic materials increases and become unavoidable. Plastic based mass production requires injection process as well Mold. The milling process of plastic mold steel material was done using HSS End Mill cutting tool that is widely used in a small and medium enterprise for the reason of its ability to be re sharpened and relatively inexpensive. Study on the effect of the geometry tool states that it has an important effect on the quality improvement. Cutting speed, feed rate, depth of cut and radii are input parameters beside to the tool path strategy. This paper aims to investigate input parameter and cutting tools behaviors within some different tool path strategy. For the reason of experiments efficiency Taguchi method and ANOVA were used. Response studied is surface roughness and cutting behaviors. By achieving the expected quality, no more additional process is required. Finally, the optimal combination of machining parameters will deliver the expected roughness and of course totally reduced cutting time. However actually, SMEs do not optimally use this data for cost reduction.

  14. Modeling PM2.5 Urban Pollution Using Machine Learning and Selected Meteorological Parameters

    Directory of Open Access Journals (Sweden)

    Jan Kleine Deters

    2017-01-01

    Full Text Available Outdoor air pollution costs millions of premature deaths annually, mostly due to anthropogenic fine particulate matter (or PM2.5. Quito, the capital city of Ecuador, is no exception in exceeding the healthy levels of pollution. In addition to the impact of urbanization, motorization, and rapid population growth, particulate pollution is modulated by meteorological factors and geophysical characteristics, which complicate the implementation of the most advanced models of weather forecast. Thus, this paper proposes a machine learning approach based on six years of meteorological and pollution data analyses to predict the concentrations of PM2.5 from wind (speed and direction and precipitation levels. The results of the classification model show a high reliability in the classification of low (25 µg/m3 and low (<10 µg/m3 versus moderate (10–25 µg/m3 concentrations of PM2.5. A regression analysis suggests a better prediction of PM2.5 when the climatic conditions are getting more extreme (strong winds or high levels of precipitation. The high correlation between estimated and real data for a time series analysis during the wet season confirms this finding. The study demonstrates that the use of statistical models based on machine learning is relevant to predict PM2.5 concentrations from meteorological data.

  15. Preliminary study on AC superconducting machines

    International Nuclear Information System (INIS)

    Yamamoto, M.; Ishigohka, T.; Shimohka, T.; Mizukami, N.; Yamaguchi, M.

    1988-01-01

    This paper describes the issues involved in developing AC superconducting machines. In the first phase, as a preliminary experiment, a 4kVa AC superconducting coil which employs 100A class 50/60Hz superconductors is made and tested. And, in the second phase, as an extension of the 4kVa coil, a model superconducting transformer is made and examined. The transformer has a novel quench protection system with an auxiliary coil only in the low voltage side. The behavior of the overcurrent protection system is confirmed

  16. Optimization of electrical parameters of windings used in axial flux electrical machines

    International Nuclear Information System (INIS)

    Uhrik, M.

    2012-01-01

    This paper deals with shape optimization of windings used in electrical machines with disc type construction. These machines have short axial length what makes them suitable for use in small wind-power turbines or in-wheel traction drives. Disc type construction of stator offers more possibilities for winding arrangements than are available in classical machines with cylindrical construction. To find out the best winding arrangement for the novel disc type machine construction a series of analytical calculations, simulations and experimental measurements were performed. (Authors)

  17. The effects of machine parameters on residual stress determined using micro-Raman spectroscopy

    Energy Technology Data Exchange (ETDEWEB)

    Sparks, R.G.; Enloe, W.S.; Paesler, M.A.

    1988-12-01

    The effects of machine parameters on residual stresses in single point diamond turned silicon and germanium have been investigated using micro-Raman spectroscopy. Residual stresses were sampled across ductile feed cuts in < 100 > silicon and germanium which were single point diamond turned using a variety of feed rates, rake angles and clearance angles. High spatial resolution micro-Raman spectra (1{mu}m spot) were obtained in regions of ductile cutting where no visible surface damage was present. The use of both 514-5nm and 488.0nm excitation wavelengths, by virtue of their differing characteristic penetration depths in the materials, allowed determinations of stress profiles as a function of depth into the sample. Previous discussions have demonstrated that such Raman spectra will exhibit asymmetrically broadened peaks which are characteristic of the superposition of a continuum of Raman scatterers from the various depths probed. Depth profiles of residual stress were obtained using computer deconvolution of the resulting asymmetrically broadened raman spectra.

  18. Effect of cutting parameters on machinability characteristics in milling of magnesium alloy with carbide tool

    Directory of Open Access Journals (Sweden)

    Kaining Shi

    2016-01-01

    Full Text Available Magnesium alloy has attracted more attentions due to its excellent mechanical properties. However, in process of dry cutting operation, many problems restrict its further development. In this article, the effect of cutting parameters on machinabilities of magnesium alloy is explored under dry milling condition. This research is an attempt to investigate the impact of cutting speed at multiple feed rates on cutting force and surface roughness, while a statistical analysis is adopted to determine the influential intensities accurately. The results showed that cutting force is affected by the positively constant intensity from feed rate and the increasingly negative intensity from cutting speed. In contrast, surface roughness is determined by the gradually increasing negative tendency from feed rate and the positive effect with constant intensity from cutting speed. Within the range of the experiments, feed rate is the leading contribution for cutting force while the cutting speed is the dominant factor for surface roughness according to the absolute intensity values. Meanwhile, the trends of influencing intensities between cutting force and surface roughness are opposite. Besides, it is also found that in milling magnesium alloy, chip morphology is highly sensitive to cutting speed while the chip quality mainly depends on feed rate.

  19. Taguchi design optimization of machining parameters on the CNC end milling process of halloysite nanotube with aluminium reinforced epoxy matrix (HNT/Al/Ep hybrid composite

    Directory of Open Access Journals (Sweden)

    J.S. Pang

    2014-08-01

    Full Text Available This paper introduces the application of Taguchi optimization methodology in optimizing the cutting parameters of end-milling process for machining the halloysite nanotubes (HNTs with aluminium reinforced epoxy hybrid composite material under dry condition. The machining parameters which are chosen to be evaluated in this study are the depth of cut (d, cutting speed (S and feed rate (f. While, the response factors to be measured are the surface roughness of the machined composite surface and the cutting force. An orthogonal array of the Taguchi method was set-up and used to analyse the effect of the milling parameters on the surface roughness and cutting force. The result from this study shows that the application of the Taguchi method can determine the best combination of machining parameters that can provide the optimal machining response conditions which are the lowest surface roughness and lowest cutting force value. For the best surface finish, A1–B3–C3 (d = 0.4 mm, S = 1500 rpm, f = 60 mmpm is found to be the optimized combination of levels for all the three control factors from the analysis. Meanwhile, the optimized combination of levels for all the three control factors from the analysis which provides the lowest cutting force was found to be A2–B2–C2 (d = 0.6 mm, S = 1000 rpm, f = 40 mmpm.

  20. Comparison of effects of machine performance parameters and energy indices of soybean production in conservation and conventional tillage systems

    Directory of Open Access Journals (Sweden)

    A Sharifi

    2016-09-01

    Full Text Available Introduction Nowadays, agricultural systems are seeking economic, ecological and bioenvironmental goals for production of agricultural crops with protection and sustainability of the environment. Therefore, there is need to extend sustainable agricultural systems such as conservation agriculture. One of the principles of conservation agriculture is conservation tillage. Conservation tillage is a kind of tillage that retains crop residues on the soil surface or mixes it with soil using related machines. It could also affect on machine performance parameters. Energy consumption for producing one kilogram crop could be studied for conservation tillage. Several researchers have conducted studies on this issue for production of different crops including wheat, sunflower and forage crops. This study conducted to assess machine performance parameters and energy indices of conservation tillage systems for soybean cultivation in Golestan province. Materials and Methods This study was conducted to investigate the effects of conservation tillage systems on machine performance and energy indices in soybean production at the Gorgan research station of Golestan Agricultural and Natural Resource Research Center in 2012. The precipitation was 450 mm. Soil texture was silty clay loam. Treatments were four tillage methods, including no-till using row crop direct planter, no-till using grain direct drill, conventional tillage usin a disk harrow with working depth of 10-15 cm and minimum tillage using chisel packer with a working depth of 20 cm. Machine performance parameters and energy indices studied in a farm covered by wheat residues in a randomized complete block design (RCBD with four treatments and four replications. Machine performance parameters consisted of field efficiency, field capacity, total field capacity and planting uniformity index were measured. Energy indices such as energy ratio, energy productivity, energy intensity and net energy gain were

  1. Study of a variable mass Atwood's machine using a smartphone

    Science.gov (United States)

    Lopez, Dany; Caprile, Isidora; Corvacho, Fernando; Reyes, Orfa

    2018-03-01

    The Atwood machine was invented in 1784 by George Atwood and this system has been widely studied both theoretically and experimentally over the years. Nowadays, it is commonplace that many experimental physics courses include both Atwood's machine and variable mass to introduce more complex concepts in physics. To study the dynamics of the masses that compose the variable Atwood's machine, laboratories typically use a smart pulley. Now, the first work that introduced a smartphone as data acquisition equipment to study the acceleration in the Atwood's machine was the one by M. Monteiro et al. Since then, there has been no further information available on the usage of smartphones in variable mass systems. This prompted us to do a study of this kind of system by means of data obtained with a smartphone and to show the practicality of using smartphones in complex experimental situations.

  2. Case study of virtual reality in CNC machine tool exhibition

    Directory of Open Access Journals (Sweden)

    Kao Yung-Chou

    2017-01-01

    Full Text Available Exhibition and demonstration are generally used in the promotion and sale-assistance of manufactured products. However, the transportation cost of the real goods from the vender factory to the exposition venue is generally expensive for huge and heavy commodity. With the advancement of computing, graphics, mobile apps, and mobile hardware the 3D visibility technology is getting more and more popular to be adopted in visual-assisted communication such as amusement games. Virtual reality (VR technology has therefore being paid great attention in emulating expensive small and/or huge and heavy equipment. Virtual reality can be characterized as 3D extension with Immersion, Interaction and Imagination. This paper was then be focused on the study of virtual reality in the assistance of CNC machine tool demonstration and exhibition. A commercial CNC machine tool was used in this study to illustrate the effectiveness and usability of using virtual reality for an exhibition. The adopted CNC machine tool is a large and heavy mill-turn machine with the width up to eleven meters and weighted about 35 tons. A head-mounted display (HMD was attached to the developed VR CNC machine tool for the immersion viewing. A user can see around the 3D scene of the large mill-turn machine and the operation of the virtual CNC machine can be actuated by bare hand. Coolant was added to demonstrate more realistic operation while collision detection function was also added to remind the operator. The developed VR demonstration system has been presented in the 2017 Taipei International Machine Tool Show (TIMTOS 2017. This case study has shown that young engineers and/or students are very impressed by the VR-based demonstration while elder persons could not adapt themselves easily to the VR-based scene because of eyesight issues. However, virtual reality has successfully being adopted and integrated with the CNC machine tool in an international show. Another machine tool on

  3. Machinability study of Al-TiC metal matrix composite

    Directory of Open Access Journals (Sweden)

    Siddappa P. N.

    2018-01-01

    Full Text Available Aluminum Metal Matrix Composites have emerged as an advanced class of structural materials have a combination of different, superior properties compared to an unreinforced matrix, which can result in a number of service benefits such as increased strength, higher elastic moduli, higher service temperature, low CTE, improved wear resistance, high toughness, etc. The excellent mechanical properties of these materials together with weight saving makes them very attractive for a variety of engineering applications in aerospace, automotive, electronic industries, etc. Hence, these materials provide as alternative substitutes for conventional engineering materials when specific mechanical properties necessary for required applications. In this work an attempt is made to study the machining parameters of Al6061/TiC MMC. The composite is developed by reinforcing TiC particles in varying proportions of 3, 6, 9 and 12 % weight fractions to the Al6061 matric alloy through stir casting technique. Cutting forces were measured by varying cutting speed and feed rate with constant depth of cut for different % weight fractions. The results showed that the cutting force increases with the increase of feed rate and decreases with the increase of cutting speed for all the weight fractions. Cutting parameters were optimized using Taguchi technique.

  4. Evaluation of parameter sensitivities for flux-switching permanent magnet machines based on simplified equivalent magnetic circuit

    Directory of Open Access Journals (Sweden)

    Gan Zhang

    2017-05-01

    Full Text Available Most of the published papers regarding the design of flux-switching permanent magnet machines are focused on the analysis and optimization of electromagnetic or mechanical behaviors, however, the evaluate of the parameter sensitivities have not been covered, which contrarily, is the main contribution of this paper. Based on the finite element analysis (FEA and simplified equivalent magnetic circuit, the method proposed in this paper enables the influences of parameters on the electromagnetic performances, i.e. the parameter sensitivities, to be given by equations. The FEA results are also validated by experimental measurements.

  5. Defining difficult laryngoscopy findings by using multiple parameters: A machine learning approach

    Directory of Open Access Journals (Sweden)

    Moustafa Abdelaziz Moustafa

    2017-04-01

    Conclusion: “Alex Difficult Laryngoscopy Software” (ADLS is a machine learning program for prediction of difficult laryngoscopy. New cases can be entered to the training set thus improving the accuracy of the software.

  6. Optimization of AVR Parameters of a Multi-machine Power System ...

    African Journals Online (AJOL)

    user1

    Keywords: multi-machine power system stability, AVR system, power system stabilizer, PID controller ... The proposed controller was a fuzzy-logic-based stabilizer that has the capability to ..... Computer methods in power system analysis.

  7. Impact of Clinical Parameters in the Intrahost Evolution of HIV-1 Subtype B in Pediatric Patients: A Machine Learning Approach

    Science.gov (United States)

    Rojas Sánchez, Patricia; Cobos, Alberto; Navaro, Marisa; Ramos, José Tomas; Pagán, Israel

    2017-01-01

    Abstract Determining the factors modulating the genetic diversity of HIV-1 populations is essential to understand viral evolution. This study analyzes the relative importance of clinical factors in the intrahost HIV-1 subtype B (HIV-1B) evolution and in the fixation of drug resistance mutations (DRM) during longitudinal pediatric HIV-1 infection. We recovered 162 partial HIV-1B pol sequences (from 3 to 24 per patient) from 24 perinatally infected patients from the Madrid Cohort of HIV-1 infected children and adolescents in a time interval ranging from 2.2 to 20.3 years. We applied machine learning classification methods to analyze the relative importance of 28 clinical/epidemiological/virological factors in the HIV-1B evolution to predict HIV-1B genetic diversity (d), nonsynonymous and synonymous mutations (dN, dS) and DRM presence. Most of the 24 HIV-1B infected pediatric patients were Spanish (91.7%), diagnosed before 2000 (83.3%), and all were antiretroviral therapy experienced. They had from 0.3 to 18.8 years of HIV-1 exposure at sampling time. Most sequences presented DRM. The best-predictor variables for HIV-1B evolutionary parameters were the age of HIV-1 diagnosis for d, the age at first antiretroviral treatment for dN and the year of HIV-1 diagnosis for ds. The year of infection (birth year) and year of sampling seemed to be relevant for fixation of both DRM at large and, considering drug families, to protease inhibitors (PI). This study identifies, for the first time using machine learning, the factors affecting more HIV-1B pol evolution and those affecting DRM fixation in HIV-1B infected pediatric patients. PMID:29044435

  8. Study of discharge in quiescent plasma machine of the INPE

    International Nuclear Information System (INIS)

    Ferreira, J.G.; Ferreira, J.L.; Ludwig, G.O.; Maciel, H.S.

    1988-12-01

    Measurements of principal plasma parameters produced by quiescent plasma machine of the Instituto de Pesquisas Espaciais (INPE) for current of 500 mA and several values of pressure and discharge power are presented. A qualitative interpretation for obtained results is done and a simple model for plasma density is compared with experimental values. The conditions of cathode operation are also investigated. (M.C.K.)

  9. Effects of cutting parameters and machining environments on surface roughness in hard turning using design of experiment

    Science.gov (United States)

    Mia, Mozammel; Bashir, Mahmood Al; Dhar, Nikhil Ranjan

    2016-07-01

    Hard turning is gradually replacing the time consuming conventional turning process, which is typically followed by grinding, by producing surface quality compatible to grinding. The hard turned surface roughness depends on the cutting parameters, machining environments and tool insert configurations. In this article the variation of the surface roughness of the produced surfaces with the changes in tool insert configuration, use of coolant and different cutting parameters (cutting speed, feed rate) has been investigated. This investigation was performed in machining AISI 1060 steel, hardened to 56 HRC by heat treatment, using coated carbide inserts under two different machining environments. The depth of cut, fluid pressure and material hardness were kept constant. The Design of Experiment (DOE) was performed to determine the number and combination sets of different cutting parameters. A full factorial analysis has been performed to examine the effect of main factors as well as interaction effect of factors on surface roughness. A statistical analysis of variance (ANOVA) was employed to determine the combined effect of cutting parameters, environment and tool configuration. The result of this analysis reveals that environment has the most significant impact on surface roughness followed by feed rate and tool configuration respectively.

  10. A 3D Dynamic Lumped Parameter Thermal Network of Air-Cooled YASA Axial Flux Permanent Magnet Synchronous Machine

    Directory of Open Access Journals (Sweden)

    Abdalla Hussein Mohamed

    2018-03-01

    Full Text Available To find the temperature rise for high power density yokeless and segmented armature (YASA axial flux permanent magnet synchronous (AFPMSM machines quickly and accurately, a 3D lumped parameter thermal model is developed and validated experimentally and by finite element (FE simulations on a 4 kW YASA machine. Additionally, to get insight in the thermal transient response of the machine, the model accounts for the thermal capacitance of different machine components. The model considers the stator, bearing, and windage losses, as well as eddy current losses in the magnets on the rotors. The new contribution of this work is that the thermal model takes cooling via air channels between the magnets on the rotor discs into account. The model is parametrized with respect to the permanent magnet (PM angle ratio, the PM thickness ratio, the air gap length, and the rotor speed. The effect of the channels is incorporated via convection equations based on many computational fluid dynamics (CFD computations. The model accuracy is validated at different values of parameters by FE simulations in both transient and steady state. The model takes less than 1 s to solve for the temperature distribution.

  11. PARAMETER DETERMINATION FOR ADDITIONAL OPERATING FORCE MECHANISM IN DEVICE FOR PNEUMO-CENTRIFUGAL MACHINING OF BALL-SHAPED WORKPIECES

    Directory of Open Access Journals (Sweden)

    A. A. Sukhotsky

    2014-01-01

    Full Text Available The paper describes development of the methodology for optimization of parameters for an additional operating force mechanism in a device for pneumo-centrifugal machining of glass balls. Specific feature in manufacturing glass balls for micro-optics in accordance with technological process for obtaining ball-shaped workpieces is grinding and polishing of spherical surface in a free state. In this case component billets of future balls are made in the form of cubes and the billets are given preliminary a form of ball with the help of rough grinding. An advanced method for obtaining ball-shaped work-pieces from brittle materials is a pneumocentrifugal machining. This method presupposes an application of two conic rings with abrasive working surfaces which are set coaxially with large diameters to each other and the billets are rolled along these rings. Rotation of the billets is conveyed by means of pressure medium.The present devices for pneumo-centrifugal machining are suitable for obtaining balls up to 6 mm. Machining of the work-pieces with full spherical surfaces and large diameter is non-productive due to impossibility to ensure a sufficient force on the billet in the working zone. For this reason the paper proposes a modified device where an additional force on the machined billet is created by upper working disc that is making a reciprocating motion along an axis of abrasive conic rings. The motion is realized with the help of a cylindrical camshaft mechanism in the form of a ring with a profile working end face and the purpose of present paper is to optimize parameters of the proposed device.The paper presents expressions for calculation of constitutive parameters of the additional operating force mechanism including parameters of loading element motion, main dimensions of the additional operating force mechanism and parameters of a profile element in the additional operating force mechanism.Investigation method is a mathematical

  12. DETERMINATION AND ANALYSIS OF CHANGE POWER CHARACTER AND POWER PARAMETERS OF EARTHMOVING- TRANSPORT WORKING PROCESS MACHINES OF CYCLIC ACTION

    Directory of Open Access Journals (Sweden)

    KHMARA L. A.

    2017-05-01

    Full Text Available Summary. Raising of problem. Efficiency of implementation working process an earthmoving-transport machine on digging of soil depends on complete realization of power equipment and hauling properties working equipment during implementation this operation. Most effective will be the mode of digging when from his beginning to the final stage a power equipment will realize nominal power, and working equipment maximal KKD at that skidding of mover does not exceed the defined possible value. However, for the traditional constructions of earthmoving-transport machines cyclic action, for such, as a drag shovel, bulldozer, realizing these terms is heavy. The feature of process digging consists in the increase of resistance to digging soil from the ego of the initial stage to eventual when hauling possibilities of machine will be maximally realized. Therefore the calculation of power equipment takes into account the power indexes of machine on the final stage of digging. Thus the unstationarity of working process results in the under exploitation of power equipment machine and hereupon appearance her bits and pieces. The size of bits and pieces power depends on the stage digging of soil, his physical and mechanical properties, terms cooperation of working equipment with the surface of motion. One of methods realization surplus power, this use it for the drive intensifiers working process of earthmoving-transport machines. Therefore for the effective choice parameters of intensifier, his office hours it is necessary to know the size of bits and pieces of power and character her change during digging of soil. The purpose of the article. Development of methodology determination remaining power equipment an earthmoving-transport machine on the example self-propelled drags hovel, character her change at digging of soil taking into account physical and mechanical properties of soil and terms cooperation working equipment with the surface of motion. Conclusion

  13. Comet Halley, parameter study I

    International Nuclear Information System (INIS)

    Huebner, W.F.; Fikani, M.M.

    1982-06-01

    To aid in defining a mission to comet P/Halley, its inner coma is simulated by a computer program that models time-dependent chemical reactions in a radially and isentropically expanding gas, taking into account attenuation of solar ultraviolet radiation in the subsolar direction. Column density predictions are based on intelligently selected combinations of poorly known values for nucleus parameters that include size, visual albedo, and infrared emissivity. Only one chemical composition and a minor modification of it are considered here; the dust-to-gas ratio in this model is zero. Although the somewhat optimistically volatile composition chosen here favors a smaller nucleus, a mean nuclear radius of only 0.5 km is unlikely. No significant increase of molecular column density is predicted by this model as a spacecraft approaches, once it is less than a few 10 4 km from the nucleus. Predictions are made for various heliocentric distances of interest for comet missions and for ground observations

  14. Support vector machine to predict diesel engine performance and emission parameters fueled with nano-particles additive to diesel fuel

    Science.gov (United States)

    Ghanbari, M.; Najafi, G.; Ghobadian, B.; Mamat, R.; Noor, M. M.; Moosavian, A.

    2015-12-01

    This paper studies the use of adaptive Support Vector Machine (SVM) to predict the performance parameters and exhaust emissions of a diesel engine operating on nanodiesel blended fuels. In order to predict the engine parameters, the whole experimental data were randomly divided into training and testing data. For SVM modelling, different values for radial basis function (RBF) kernel width and penalty parameters (C) were considered and the optimum values were then found. The results demonstrate that SVM is capable of predicting the diesel engine performance and emissions. In the experimental step, Carbon nano tubes (CNT) (40, 80 and 120 ppm) and nano silver particles (40, 80 and 120 ppm) with nanostructure were prepared and added as additive to the diesel fuel. Six cylinders, four-stroke diesel engine was fuelled with these new blended fuels and operated at different engine speeds. Experimental test results indicated the fact that adding nano particles to diesel fuel, increased diesel engine power and torque output. For nano-diesel it was found that the brake specific fuel consumption (bsfc) was decreased compared to the net diesel fuel. The results proved that with increase of nano particles concentrations (from 40 ppm to 120 ppm) in diesel fuel, CO2 emission increased. CO emission in diesel fuel with nano-particles was lower significantly compared to pure diesel fuel. UHC emission with silver nano-diesel blended fuel decreased while with fuels that contains CNT nano particles increased. The trend of NOx emission was inverse compared to the UHC emission. With adding nano particles to the blended fuels, NOx increased compared to the net diesel fuel. The tests revealed that silver & CNT nano particles can be used as additive in diesel fuel to improve complete combustion of the fuel and reduce the exhaust emissions significantly.

  15. Study of axial protections of unloading machines of graphite piles

    International Nuclear Information System (INIS)

    Duco, Jacques; Pepin, Pierre; Cabaret, Guy; Dubor, Monique

    1969-10-01

    As previous studies resulted in the development of a simple calculation formula based on experimental results for the calculation of neutron protection thicknesses for loading machines, this study aimed at determining axial protections of these machines which represent a specific problem: scattering of delayed neutrons in the machine inner cavity may result in an important neutron leakage through the upper part, at the level of the winch enclosure. In an experimental part, this study comprises the measurement of the neutron dose in a 2.60 m long and 54 cm diameter cylindrical cavity, and in the thickness of the surrounding concrete protection. In the second part, the authors present a calculation method which uses the Zeus and Mercure codes to interpret the results [fr

  16. Quality Evaluation for Appearance of Needle Green Tea Based on Machine Vision and Process Parameters

    DEFF Research Database (Denmark)

    Dong, Chunwang; Zhu, Hongkai; Zhou, Xiaofen

    2017-01-01

    ), extreme learning machine (ELM) and strong predictor integration algorithm (ELM-AdaBoost). The comparison of the results showed that the ELM-AdaBoost model based on image characteristics had the best performance (RPD was more than 2). Its predictive performance was superior to other models, with smaller......, and modeling faster (0.014~0.281 s). AdaBoost method, which was a hybrid integrated algorithm, can further promote the accuracy and generalization capability of the model. The above conclusions indicated that it was feasible to evaluate the quality of appearance of needle green tea based on machine vision...

  17. Study on the machinability characteristics of superalloy Inconel 718 during high speed turning

    International Nuclear Information System (INIS)

    Thakur, D.G.; Ramamoorthy, B.; Vijayaraghavan, L.

    2009-01-01

    The present paper is an attempt of an experimental investigation on the machinability of superalloy, Inconel 718 during high speed turning using tungsten carbide insert (K20) tool. The effect of machining parameters on the cutting force, specific cutting pressure, cutting temperature, tool wear and surface finish criteria were investigated during the experimentation. The machining parameters have been optimized by measuring forces. The effect of machining parameters on the tool wear was examined through SEM micrographs. During high speed turning acoustic emission signal were collected and analyzed to understand the effect of cutting parameters during online. The research work findings will also provide useful economic machining solution by utilizing economical tungsten carbide tooling during high speed processing of Inconel 718, which is otherwise usually machined by costly PCD or CBN tools. The present approach and results will be helpful for understanding the machinability of Inconel 718 during high speed turning for the manufacturing engineers

  18. Optimal Design of the Transverse Flux Machine Using a Fitted Genetic Algorithm with Real Parameters

    DEFF Research Database (Denmark)

    Argeseanu, Alin; Ritchie, Ewen; Leban, Krisztina Monika

    2012-01-01

    This paper applies a fitted genetic algorithm (GA) to the optimal design of transverse flux machine (TFM). The main goal is to provide a tool for the optimal design of TFM that is an easy to use. The GA optimizes the analytic basic design of two TFM topologies: the C-core and the U-core. First...

  19. A Method for Identifying the Mechanical Parameters in Resistance Spot Welding Machines

    DEFF Research Database (Denmark)

    Wu, Pei; Zhang, Wenqi; Bay, Niels

    2003-01-01

    Mechanical dynamic responses of resistance welding machine have a significant influence on weld quality and electrode service life, it must be considered when the real welding production is carried out or the welding process is stimulated. The mathematical models for characterizing the mechanical...

  20. A comparative study of machine learning models for ethnicity classification

    Science.gov (United States)

    Trivedi, Advait; Bessie Amali, D. Geraldine

    2017-11-01

    This paper endeavours to adopt a machine learning approach to solve the problem of ethnicity recognition. Ethnicity identification is an important vision problem with its use cases being extended to various domains. Despite the multitude of complexity involved, ethnicity identification comes naturally to humans. This meta information can be leveraged to make several decisions, be it in target marketing or security. With the recent development of intelligent systems a sub module to efficiently capture ethnicity would be useful in several use cases. Several attempts to identify an ideal learning model to represent a multi-ethnic dataset have been recorded. A comparative study of classifiers such as support vector machines, logistic regression has been documented. Experimental results indicate that the logical classifier provides a much accurate classification than the support vector machine.

  1. Machinability studies of infrared window materials and metals

    International Nuclear Information System (INIS)

    Arnold, J.B.; Morris, T.O.; Sladky, R.E.; Steger, P.J.

    1976-01-01

    Diamond machining of materials for optical applications is becoming an important fabrication process. Development work in material-removal technology to better understand the mechanics of the diamond-turning process, its limitations, and applications is described. The technique is presently limited to a select group of metals, most of which are of a face-center-cubic crystal structure. Machinability studies were done which were designed to better understand diamond compatibility and thus expand the range of applicable materials. Nonconventional methods such as ultrasonic tool stimulation were investigated. Work done to determine the machinability of infrared window materials indicates that this is a viable fabrication technique for many materials, although additional effort is needed to optimize the process for particular materials

  2. Parameter Estimation of the Thermal Network Model of a Machine Tool Spindle by Self-made Bluetooth Temperature Sensor Module

    Directory of Open Access Journals (Sweden)

    Yuan-Chieh Lo

    2018-02-01

    Full Text Available Thermal characteristic analysis is essential for machine tool spindles because sudden failures may occur due to unexpected thermal issue. This article presents a lumped-parameter Thermal Network Model (TNM and its parameter estimation scheme, including hardware and software, in order to characterize both the steady-state and transient thermal behavior of machine tool spindles. For the hardware, the authors develop a Bluetooth Temperature Sensor Module (BTSM which accompanying with three types of temperature-sensing probes (magnetic, screw, and probe. Its specification, through experimental test, achieves to the precision ±(0.1 + 0.0029|t| °C, resolution 0.00489 °C, power consumption 7 mW, and size Ø40 mm × 27 mm. For the software, the heat transfer characteristics of the machine tool spindle correlative to rotating speed are derived based on the theory of heat transfer and empirical formula. The predictive TNM of spindles was developed by grey-box estimation and experimental results. Even under such complicated operating conditions as various speeds and different initial conditions, the experiments validate that the present modeling methodology provides a robust and reliable tool for the temperature prediction with normalized mean square error of 99.5% agreement, and the present approach is transferable to the other spindles with a similar structure. For realizing the edge computing in smart manufacturing, a reduced-order TNM is constructed by Model Order Reduction (MOR technique and implemented into the real-time embedded system.

  3. Study of Environmental Data Complexity using Extreme Learning Machine

    Science.gov (United States)

    Leuenberger, Michael; Kanevski, Mikhail

    2017-04-01

    The main goals of environmental data science using machine learning algorithm deal, in a broad sense, around the calibration, the prediction and the visualization of hidden relationship between input and output variables. In order to optimize the models and to understand the phenomenon under study, the characterization of the complexity (at different levels) should be taken into account. Therefore, the identification of the linear or non-linear behavior between input and output variables adds valuable information for the knowledge of the phenomenon complexity. The present research highlights and investigates the different issues that can occur when identifying the complexity (linear/non-linear) of environmental data using machine learning algorithm. In particular, the main attention is paid to the description of a self-consistent methodology for the use of Extreme Learning Machines (ELM, Huang et al., 2006), which recently gained a great popularity. By applying two ELM models (with linear and non-linear activation functions) and by comparing their efficiency, quantification of the linearity can be evaluated. The considered approach is accompanied by simulated and real high dimensional and multivariate data case studies. In conclusion, the current challenges and future development in complexity quantification using environmental data mining are discussed. References - Huang, G.-B., Zhu, Q.-Y., Siew, C.-K., 2006. Extreme learning machine: theory and applications. Neurocomputing 70 (1-3), 489-501. - Kanevski, M., Pozdnoukhov, A., Timonin, V., 2009. Machine Learning for Spatial Environmental Data. EPFL Press; Lausanne, Switzerland, p.392. - Leuenberger, M., Kanevski, M., 2015. Extreme Learning Machines for spatial environmental data. Computers and Geosciences 85, 64-73.

  4. A Parameter Study of Localization

    Directory of Open Access Journals (Sweden)

    Sandor Stephen Mester

    1996-01-01

    Full Text Available Extensive work has been done on the vibration characteristics of perfectly periodic structures. Disorder in the periodic pattern has been found to lead to localization in one-dimensional periodic structures. It is important to understand localization because it causes energy to be concentrated near the disorder and may cause an overestimation of structural damping. A numerical study is conducted to obtain a better understanding of localization. It is found that any mode, even the first, can localize due to the presence of small imperfections.

  5. Effect of machining parameters on surface textures in EDM of Fe-Mn-Al alloy

    International Nuclear Information System (INIS)

    Guu, Y.H.; Hou, Max Ti-Kuang

    2007-01-01

    In this work, the surface characteristics caused by EDM were analyzed by means of the atomic force microscopy (AFM) technique. An empirical model of Fe-Mn-Al alloy was proposed based on the experimental data. A qualitative energy dispersive spectroscopic analyzer was used to measure the chemical composition of the specimen. Surface hardness was determined with a microhardness tester. Experimental results indicate that the EDM process causes a ridged surface and induces machining damage in the surface layer, and increases the surface roughness. The depth of micro-cracks, micro-voids and machined damage increase with an increase in the amount of pulsed current and pulse-on duration. The effect of the magnitude of the pulse-on duration on the surface texture of the specimen is more significant than the pulsed current. Furthermore, the AFM method reveals the 3D surface textures of the EDM specimen with a nanometer scale

  6. Abreu system - A dosimetric system to evaluate basic parameters of photofluorographic X-ray machine

    International Nuclear Information System (INIS)

    Feital, J.C.

    1987-01-01

    In Brazil, photofluorographic X-ray machines are used for cuberculosis mass screening throughout the country. The exact number of these X-ray equipment is unknown but it is estimated to be around 1000 operating units. Twelve million miniature chest radiographs are taken per year. In order to make local inspections speedier and also aiming at its postal use, a system has been developed wich evaluates the entrace exposure of the patient, the X-ray beam half-value layer ( leading to the evaluation of the tube's total filtration ) and the beam's field size. It consists of a piece of cardboard where filters, TLDs and X-ray films are inserted. So far the system has been tested in 53 X-ray machines in Rio de Janeiro. The results show that it can be used in a national survey program. (Author) [pt

  7. ELFE at DESY, status of machine studies

    Energy Technology Data Exchange (ETDEWEB)

    Tkatchenko, A.

    1996-12-31

    In this paper, the main outlines of the ELFE at DESY project are describes and the problems associated with the scenario proposed in july 1995 are reviewed. The results of the feasibility study recently carried out are presented and the achievable performances of the extracted beam in terms of emittance, energy spread and duty factor are given. (author).

  8. ELFE at DESY, status of machine studies

    International Nuclear Information System (INIS)

    Tkatchenko, A.

    1996-01-01

    In this paper, the main outlines of the ELFE at DESY project are describes and the problems associated with the scenario proposed in july 1995 are reviewed. The results of the feasibility study recently carried out are presented and the achievable performances of the extracted beam in terms of emittance, energy spread and duty factor are given. (author)

  9. Preliminary study on rotary ultrasonic machining of Bk-7 optical glass rod

    International Nuclear Information System (INIS)

    Hamzah, E.; Izman, S.; Khoo, C.Y.; Zainal Abidin, N.N.

    2007-01-01

    This paper presents an experimental observation on rotary ultrasonic machining (RUM) of BK7 optical glass rod. BK7 is a common technical optical glass for high quality optical components due to its high linear optical transmission in the visible range and is chemically stable. RUM is a hybrid machining process that combines the material removal mechanisms of diamond grinding and ultrasonic machining (USM) and it is non-thermal, non-chemical, creates no change in the microstructure, chemical or physical properties of the work piece. In the RUM, a controlled static load is applied to the rotating core drill with metal bonded diamond abrasive and is ultrasonically vibrated in the axial direction. A water-soluble coolant was used to cool the tool and sample during machining processes. By using DOE (Design of Experiment) approach, the effect of spindle speed and feed rate to the ultrasonic machinability had been developed. The main effects and two-factor interactions of process parameters (spindle speed) and feed rate) on output variables (MRR, surface roughness, opaqueness, chipping thickness and chipping size) are studied. (author)

  10. Feasibility Studies of Alpha-Channeling in Mirror Machines

    International Nuclear Information System (INIS)

    Zhmoginov, A.I.; Fisch, N.J.

    2010-01-01

    The linear magnetic trap is an attractive concept both for fusion reactors and for other plasma applications due to its relative engineering simplicity and high-beta operation. Applying the α-channeling technique to linear traps, such as mirror machines, can benefit this concept by efficiently redirecting α particle energy to fuel ion heating or by otherwise sustaining plasma confinement, thus increasing the effective fusion reactivity. To identify waves suitable for α-channeling a rough optimization of the energy extraction rate with respect to the wave parameters is performed. After the optimal regime is identified, a systematic search for modes with similar parameters in mirror plasmas is performed, assuming quasi-longitudinal or quasi-transverse wave propagation. Several modes suitable for α particle energy extraction are identified for both reactor designs and for proof- of-principle experiments.

  11. Multi-criteria decision making in the selection of machining parameters for Inconel 718

    International Nuclear Information System (INIS)

    Thirumalai, R.; Senthilkumaar, J. S.

    2013-01-01

    Taguchi's methods and design of experiments are invariably used and adopted as quality improvement techniques in several manufacturing industries as tools for offline quality control. These methods optimize single-response processes. However, Taguchi's method is not appropriate for optimizing a multi-response problem. In other situations, multi-responses need to be optimized simultaneously. This paper presents multi-response optimization techniques. A set of non-dominated solutions are obtained using non-sorted genetic algorithm for multi-objective functions. Multi-criteria decision making (MCDM) is proposed in this work for selecting a single solution from nondominated solutions. This paper addresses a new method of MCDM concept based on technique for order preference by similarity to ideal solution (TOPSIS). TOPSIS determines the shortest distance to the positive-ideal solution and the greatest distance from the negative-ideal solution. This work involves the high-speed machining of Inconel 718 using carbide cutting tool with six objective functions that are considered as attributes against the process variables of cutting speed, feed, and depth of cut. The higher-ranked solution is selected as the best solution for the machining of Inconel 718 in its respective environment.

  12. Multi-criteria decision making in the selection of machining parameters for Inconel 718

    Energy Technology Data Exchange (ETDEWEB)

    Thirumalai, R. [SNS College of Technology, Coimbatore (India); Senthilkumaar, J. S. [Bharathithasan Engineering College, Nattrampalli (India)

    2013-04-15

    Taguchi's methods and design of experiments are invariably used and adopted as quality improvement techniques in several manufacturing industries as tools for offline quality control. These methods optimize single-response processes. However, Taguchi's method is not appropriate for optimizing a multi-response problem. In other situations, multi-responses need to be optimized simultaneously. This paper presents multi-response optimization techniques. A set of non-dominated solutions are obtained using non-sorted genetic algorithm for multi-objective functions. Multi-criteria decision making (MCDM) is proposed in this work for selecting a single solution from nondominated solutions. This paper addresses a new method of MCDM concept based on technique for order preference by similarity to ideal solution (TOPSIS). TOPSIS determines the shortest distance to the positive-ideal solution and the greatest distance from the negative-ideal solution. This work involves the high-speed machining of Inconel 718 using carbide cutting tool with six objective functions that are considered as attributes against the process variables of cutting speed, feed, and depth of cut. The higher-ranked solution is selected as the best solution for the machining of Inconel 718 in its respective environment.

  13. Momentum transport studies from multi-machine comparisons

    International Nuclear Information System (INIS)

    Yoshida, M.; Kamada, Y.; Sakamoto, Y.; Kaye, S.; Solomon, W.; Bell, R.E.; Rice, J.; Podpaly, Y.; Reinke, M.L.; Tala, T.; Salmi, A.; Burrell, K.H.; Ferreira, J.; McDonald, D.; Mantica, P.

    2012-01-01

    A database of toroidal momentum transport on five tokamaks, Alcator C-Mod, DIII-D, JET, NSTX and JT-60U, has been constructed under a wide range of conditions in order to understand the characteristics of toroidal momentum transport coefficients, namely the toroidal momentum diffusivity (χ φ ) and the pinch velocity (V pinch ). Through an inter-machine comparison, the similarities and differences in the properties of χ φ and V pinch among the machines have been clarified. Parametric dependences of these momentum transport coefficients have been investigated over a wide range of plasma parameters taking advantage of the different operation regimes in machines. The approach offers insights into the parametric dependences as follows. The toroidal momentum diffusivity (χ φ ) generally increases with increasing heat diffusivity (χ i ). The correlation is observed over a wide range of χ φ , covering roughly two orders of magnitude, and within each of the machines over the whole radius. Through the inter-machine comparison, it is found that χ φ becomes larger in the outer region of the plasma. Also observed is a general trend for V pinch in tokamaks; the inward pinch velocity (−V pinch ) increases with increasing χ φ . The results that are commonly observed in machines will support a toroidal rotation prediction in future devices. On the other hand, differences among machines have been observed. The toroidal momentum diffusivity, χ φ , is larger than or equal to χ i in JET and JT-60U; on the other hand, χ φ is smaller than or equal to χ i in NSTX, DIII-D and Alcator C-Mod. In DIII-D, the ratio −RV pinch /χ φ at r/a = 0.5–0.6 is about 2, which is small compared with that in other tokamaks (−RV pinch /χ φ ≈ 5). Based on these different observations, parametric dependences of χ φ /χ i , RV pinch /χ φ and χ φ have been investigated in H-mode plasmas. Across the dataset from all machines, the ratio χ φ /χ i tends to be larger in low

  14. Qualitative Parameters of Practice during University Studies

    Science.gov (United States)

    Stasiunaitiene, Egle; Norkute, Odeta

    2011-01-01

    In this article, relevance of practice during university studies is highlighted, as well as the main stages of its organisation, qualitative parameters, as well as criteria and indicators that validate them are defined. Discussion on the idea that taking into consideration qualitative parameters of organising practice as a component of studies…

  15. Comparative implementation of Handwritten and Machine written Gurmukhi text utilizing appropriate parameters

    Science.gov (United States)

    Kaur, Jaswinder; Jagdev, Gagandeep, Dr.

    2018-01-01

    Optical character recognition is concerned with the recognition of optically processed characters. The recognition is done offline after the writing or printing has been completed, unlike online recognition where the computer has to recognize the characters instantly as they are drawn. The performance of character recognition depends upon the quality of scanned documents. The preprocessing steps are used for removing low-frequency background noise and normalizing the intensity of individual scanned documents. Several filters are used for reducing certain image details and enabling an easier or faster evaluation. The primary aim of the research work is to recognize handwritten and machine written characters and differentiate them. The language opted for the research work is Punjabi Gurmukhi and tool utilized is Matlab.

  16. Deep learning: Using machine learning to study biological vision

    OpenAIRE

    Majaj, Najib; Pelli, Denis

    2017-01-01

    Today most vision-science presentations mention machine learning. Many neuroscientists use machine learning to decode neural responses. Many perception scientists try to understand recognition by living organisms. To them, machine learning offers a reference of attainable performance based on learned stimuli. This brief overview of the use of machine learning in biological vision touches on its strengths, weaknesses, milestones, controversies, and current directions.

  17. Effect of machining parameters on surface integrity of silicon carbide ceramic using end electric discharge milling and mechanical grinding hybrid machining

    International Nuclear Information System (INIS)

    Ji, Renjie; Liu, Yonghong; Zhang, Yanzhen; Cai, Baoping; Li, Xiaopeng; Zheng, Chao

    2013-01-01

    A novel hybrid process that integrates end electric discharge (ED) milling and mechanical grinding is proposed. The process is able to effectively machine a large surface area on SiC ceramic with good surface quality and fine working environmental practice. The polarity, pulse on-time, and peak current are varied to explore their effects on the surface integrity, such as surface morphology, surface roughness, micro-cracks, and composition on the machined surface. The results show that positive tool polarity, short pulse on-time, and low peak current cause a fine surface finish. During the hybrid machining of SiC ceramic, the material is mainly removed by end ED milling at rough machining mode, whereas it is mainly removed by mechanical grinding at finish machining mode. Moreover, the material from the tool can transfer to the workpiece, and a combination reaction takes place during machining.

  18. Combination of Machining Parameters to Optimize Surface Roughness and Chip Thickness during End Milling Process on Aluminium 6351-T6 Alloy Using Taguchi Design Method

    Directory of Open Access Journals (Sweden)

    Reddy Sreenivasulu

    2016-12-01

    Full Text Available In any machining operations, quality is the important conflicting objective. In order to give assurance for high productivity, some extent of quality has to be compromised. Similarly productivity will be decreased while the efforts are channelized to enhance quality. In this study,  the experiments were carried out on a CNC vertical machining center  to perform 10mm slots on Al 6351-T6 alloy work piece by K10 carbide, four flute end milling cutter. Furthermore the cutting speed, the feed rate and depth of cut are regulated in this experiment. Each experiment was conducted three times and the surface roughness and chip thickness was measured by a surface analyser of Surf Test-211 series (Mitutoyo and Digital Micrometer (Mitutoyo with least count 0.001 mm respectively. The selection of orthogonal array is concerned with the total degree of freedom of process parameters. Total degree of freedom (DOF associated with three parameters is equal to 6 (3X2.The degree of freedom for the orthogonal array should be greater than or at least equal to that of the process parameters. There by, a L9 orthogonal array having degree of freedom equal to (9-1= 8 8 has been considered .But in present case each experiment is conducted three times, therefore total degree of freedom (9X3-1=26 26 has been considered. Finally, confirmation test (ANOVA was conducted to compare the predicted values with the experimental values confirm its effectiveness in the analysis of surface roughness and chip thickness. Surface Roughness (Ra is greatly reduced from 0.145 µm to 0.1326 µm and the chip thickness (Ct is slightly reduced from 0.1 mm to 0.085 mm, because of in the measurement collected the chips after machining of every experiment, from that randomly selected a few chips for measuring of their thickness using digital micrometer.

  19. Fall detection using supervised machine learning algorithms: A comparative study

    KAUST Repository

    Zerrouki, Nabil; Harrou, Fouzi; Houacine, Amrane; Sun, Ying

    2017-01-01

    Fall incidents are considered as the leading cause of disability and even mortality among older adults. To address this problem, fall detection and prevention fields receive a lot of intention over the past years and attracted many researcher efforts. We present in the current study an overall performance comparison between fall detection systems using the most popular machine learning approaches which are: Naïve Bayes, K nearest neighbor, neural network, and support vector machine. The analysis of the classification power associated to these most widely utilized algorithms is conducted on two fall detection databases namely FDD and URFD. Since the performance of the classification algorithm is inherently dependent on the features, we extracted and used the same features for all classifiers. The classification evaluation is conducted using different state of the art statistical measures such as the overall accuracy, the F-measure coefficient, and the area under ROC curve (AUC) value.

  20. Studies on Nb3Sn field coils for superconducting machine

    International Nuclear Information System (INIS)

    Fujino, H.; Nose, S.

    1981-01-01

    This paper describes experimental studies on several coils wound with multifilamentary (MF) Nb 3 Sn cables with reinforcing strip for superconducting rotating machine application. To use a Nb 3 Sn superconductor to field winding of a rotating machine, several coil performances of pre-reacted, bronze processed and stranded MF Nb 3 Sn cables were investigated, mainly in relation to stress effect. Bending strain up to 0.64% in strand and winding stress of 5 kg/mm 2 have resulted in nondegradation in coil performance. A pair of impregnated race-track coils designed for a 30 MVA synchronous condenser was energized successfully up to 80% of critical current without quench. 8 refs

  1. Fall detection using supervised machine learning algorithms: A comparative study

    KAUST Repository

    Zerrouki, Nabil

    2017-01-05

    Fall incidents are considered as the leading cause of disability and even mortality among older adults. To address this problem, fall detection and prevention fields receive a lot of intention over the past years and attracted many researcher efforts. We present in the current study an overall performance comparison between fall detection systems using the most popular machine learning approaches which are: Naïve Bayes, K nearest neighbor, neural network, and support vector machine. The analysis of the classification power associated to these most widely utilized algorithms is conducted on two fall detection databases namely FDD and URFD. Since the performance of the classification algorithm is inherently dependent on the features, we extracted and used the same features for all classifiers. The classification evaluation is conducted using different state of the art statistical measures such as the overall accuracy, the F-measure coefficient, and the area under ROC curve (AUC) value.

  2. Simple mechanical parameters identification of induction machine using voltage sensor only

    International Nuclear Information System (INIS)

    Horen, Yoram; Strajnikov, Pavel; Kuperman, Alon

    2015-01-01

    Highlights: • A simple low cost algorithm for induction motor mechanical parameters estimation is proposed. • Voltage sensing only is performed; speed sensor is not required. • The method is suitable for both wound rotor and squirrel cage motors. - Abstract: A simple low cost algorithm for induction motor mechanical parameters estimation without speed sensor is presented in this paper. Estimation is carried out by recording stator terminal voltage during natural braking and subsequent offline curve fitting. The algorithm allows accurately reconstructing mechanical time constant as well as loading torque speed dependency. Although the mathematical basis of the presented method is developed for wound rotor motors, it is shown to be suitable for squirrel cage motors as well. The algorithm is first tested by reconstruction of simulation model parameters and then by processing measurement results of several motors. Simulation and experimental results support the validity of the proposed algorithm

  3. Using machine learning to predict soil bulk density on the basis of visual parameters

    NARCIS (Netherlands)

    Bondi, Giulia; Creamer, Rachel; Ferrari, Alessio; Fenton, Owen; Wall, David

    2018-01-01

    Soil structure is a key factor that supports all soil functions. Extracting intact soil cores and horizon specific samples for determination of soil physical parameters (e.g. bulk density (Bd) or particle size distribution) is a common practice for assessing indicators of soil structure. However,

  4. Optimization and Simulation of Machining Parameters in Radial-axial Ring Rolling Process

    Directory of Open Access Journals (Sweden)

    Shuiyuan Tang

    2011-05-01

    Full Text Available Ring rolling is a complicated process, in which rolling parameters influence directly the quality of ring. It is a process method with high productivity and few waste of material, widely used in transportation industry including automotive, shipbuilding, aerospace etc. During the rolling process of large-sized parts, crinkle and hollows often appear on surface, due to inconsistence of rolling motions with the deformation of ring part. Based on radial-axial ring rolling system configuration, motions and forces in rolling process are analyzed, and a dynamic model is formulated. Error of ring's end flatness and roundness are defined as the characteristic parameters of ring quality. The relationship between core roller feed speed, drive roller speed, the upper taper roller feed speed, and quality of ring part are analyzed. The stress and strain of the part are simulated in the Finite Element Method by DEFORM software. The simulation results provide a reference for the definition of ring rolling process parameters. It is able to make the deformation of the part be consistent with the process parameters, and improve product quality considerably.

  5. Machine self-teaching methods for parameter optimization. Final report, October 1984-August 1986

    Energy Technology Data Exchange (ETDEWEB)

    Dillard, R.A.

    1986-12-01

    The problem of determining near-optimum parameter-control logic is addressed for cases where a sensor or communication system is highly flexible and the logic cannot be determined analytically. A system that supports human-like learning of optimum parameters is outlined. The major subsystems are (1) a simulation system (described for a radar example), (2) a performance monitoring system, (3) the learning system, and (4) the initial knowledge used by all subsystems. The initial knowledge is expressed modularly as specifications (e.g., radar constraints, performance measures, and target characteristics), relationships (among parameters, intermediate measures, and component performance measures), and formulas. The intent of the learning system is to relieve the human from the very tedious trial-and-error process of examining performance, selecting and applying curve-fitting methods, and selecting the next trial set of parameters. A learning system to design a simple radar meeting specific performance constraints is described in detail, for experimental purposes, in generic object-based code.

  6. Mathematical modeling and design parameters of crushing machines with variable-pitch helix of the screw

    Directory of Open Access Journals (Sweden)

    Pelenko V. V.

    2017-11-01

    Full Text Available From the point of view of the effectiveness of the top cutting unit, the helix angle in the end portion of the screw is the most important and characteristic parameter, as it determines the pressure of the meat material in the zone of interaction of a knife and grate. The importance of solving the problem of mathematical modeling of geometry is due to the need to address the problem of minimizing the reverse flow of the food material when injecting into the cutting zone, as the specified effect of "locking" significantly reduces the performance of the transfer process, increases energy consumption of the equipment and entails the deterioration of the quality of the raw materials output. The problem of determining the length of the helix variable pitch for screw chopper food materials has been formulated and solved by methods of differential geometry. The task of correct description of the law of changing the angle of helix inclination along its length has been defined in this case as a key to provide the required dependence of this angle tangent on the angle of the radius-vector of the circle. It has been taken into account that the reduction in the pitch of the screw in the direction of the product delivery should occur at a decreasing rate. The parametric equation of the helix has been written in the form of three functional dependencies of the corresponding cylindrical coordinates. Based on the wide range analysis and significant number of models of tops from different manufacturers the boundaries of possible changes in the angles of inclination of the helical line of the first and last turns of the screw have been identified. The auger screw length is determined mathematically in the form of an analytical relationship and both as a function of the variable angle of its rise, and as a function of the rotation angle of the radius-vector of the circle generatrix, which makes it possible to expand the design possibilities of this node. Along

  7. MATHEMATICAL MODEL FOR THE STUDY AND DESIGN OF A ROTARY-VANE GAS REFRIGERATION MACHINE

    Directory of Open Access Journals (Sweden)

    V. V. Trandafilov

    2016-08-01

    Full Text Available This paper presents a mathematical model of calculating the main parameters the operating cycle, rotary-vane gas refrigerating machine that affect installation, machine control and working processes occurring in it at the specified criteria. A procedure and a graphical method for the rotary-vane gas refrigerating machine (RVGRM are proposed. A parametric study of the main geometric variables and temperature variables on the thermal behavior of the system is analyzed. The model considers polytrope index for the compression and expansion in the chamber. Graphs of the pressure and temperature in the chamber of the angle of rotation of the output shaft are received. The possibility of inclusion in the cycle regenerative heat exchanger is appreciated. The change of the coefficient of performance machine after turning the cycle regenerative heat exchanger is analyzed. It is shown that the installation of a regenerator RVGRM cycle results in increased COP more than 30%. The simulation results show that the proposed model can be used to design and optimize gas refrigerator Stirling.

  8. A Study of the Resolution of Dental Intraoral X-Ray Machines

    International Nuclear Information System (INIS)

    Kim, Seon Ju; Chung, Hyon De

    1990-01-01

    The purpose of this study was to assess the resolution and focal spot size of dental X-ray machines. Fifty dental X-ray machines were selected for measuring resolution and focal spot size. These machines were used in general dental clinics. The time on installation of the X-ray machine varies from 1 years to 10 years. The resolution of these machines was measured with the test pattern. The focal spot size of these machines was measured with the star test pattern. The following results were obtained: 1. The resolution of dental intraoral X-ray machines was not significantly changed in ten years. 2. The focal spot size of dental intraoral X-ray machines was not significantly increased in ten years. The statistical analysis between the mean focal spot size and nominal focal spot size was significant at the 0.05 level about the more than 3 years used machines.

  9. Study on ultra-fine w-EDM with on-machine measurement-assisted

    International Nuclear Information System (INIS)

    Chen Shuntong; Yang Hongye

    2011-01-01

    The purpose of this study was to develop the on-machine measurement techniques so as to precisely fabricate micro intricate part using ultra-fine w-EDM. The measurement-assisted approach which employs an automatic optical inspection (AOI) is incorporated to ultra-fine w-EDM process to on-machine detect the machining error for next re-machining. The AOI acquires the image through a high resolution CCD device from the contour of the workpiece after roughing in order to further process and recognize the image for determining the residual. This facilitates the on-machine error detection and compensation re-machining. The micro workpiece and electrode are not repositioned during machining. A fabrication for a micro probe of 30-μm diameter is rapidly machined and verified successfully. Based on the proposed technique, on-machine measurement with AOI has been realized satisfactorily.

  10. The 1989 progress report of GANIL: Operations and machine studies

    International Nuclear Information System (INIS)

    1990-03-01

    The 1989 progress report of the GANIL (French acronym for National Large Accelerator of Heavy Ions) is presented. The studies and the operations performed on the accelerator during the 10th July to the 18th December are summarized. The machine's operating time, the time required in the starting step and the time available for the users are examined. Several technical studies performed are reported. The results obtained after the energy increase operation are satisfactory. The beam intensity was increased of about a factor of 10 [fr

  11. comparative study of moore and mealy machine models adaptation

    African Journals Online (AJOL)

    user

    automata model was developed for ABS manufacturing process using Moore and Mealy Finite State Machines. Simulation ... The simulation results showed that the Mealy Machine is faster than the Moore ..... random numbers from MATLAB.

  12. Key Performance Parameter Driven Technology Goals for Electric Machines and Power Systems

    Science.gov (United States)

    Bowman, Cheryl; Jansen, Ralph; Brown, Gerald; Duffy, Kirsten; Trudell, Jeffrey

    2015-01-01

    Transitioning aviation to low carbon propulsion is one of the crucial strategic research thrust and is a driver in the search for alternative propulsion system for advanced aircraft configurations. This work requires multidisciplinary skills coming from multiple entities. The feasibility of scaling up various electric drive system technologies to meet the requirements of a large commercial transport is discussed in terms of key parameters. Functional requirements are identified that impact the power system design. A breakeven analysis is presented to find the minimum allowable electric drive specific power and efficiency that can preserve the range, initial weight, operating empty weight, and payload weight of the base aircraft.

  13. Monte Carlo study of MLC fields for cobalt therapy machine

    Directory of Open Access Journals (Sweden)

    Komanduri M Ayyangar

    2014-01-01

    Full Text Available An automated Multi-Leaf Collimator (MLC system has been developed as add-on for the cobalt-60 teletherapy machines available in India. The goal of the present computational study is to validate the MLC design using Monte Carlo (MC modeling. The study was based on the Kirloskar-supplied Phoenix model machines that closely match the Atomic Energy of Canada Limited (AECL theratron-80 machine. The MLC is a retrofit attachment to the collimator assembly, with 14 non-divergent leaf pairs of 40 mm thick, 7 mm wide, and 150 mm long tungsten alloy plates with rounded edges and 20 mm tongue and 2 mm groove in each leaf. In the present work, the source and collimator geometry has been investigated in detail to arrive at a model that best represents the measured dosimetric data. The authors have studied in detail the proto-I MLC built for cobalt-60. The MLC field sizes were MC simulated for 2 × 2 cm 2 to 14 × 14 cm 2 square fields as well as irregular fields, and the percent depth dose (PDD and profile data were compared with ROPS† treatment planning system (TPS. In addition, measured profiles using the IMATRIXX system‡ were also compared with the MC simulations. The proto-I MLC can define radiation fields up to 14 × 14 cm΂ within 3 mm accuracy. The maximum measured leakage through the leaf ends in closed condition was 3.4% and interleaf leakage observed was 7.3%. Good agreement between MC results, ROPS and IMATRIXX results has been observed. The investigation also supports the hypothesis that optical and radiation field coincidence exists for the square fields studied with the MLC. Plots of the percent depth dose (PDD data and profile data for clinically significant irregular fields have also been presented. The MC model was also investigated to speed up the calculations to allow calculations of clinically relevant conformal beams.

  14. Predicting Complexation Thermodynamic Parameters of β-Cyclodextrin with Chiral Guests by Using Swarm Intelligence and Support Vector Machines

    Directory of Open Access Journals (Sweden)

    Luckhana Lawtrakul

    2009-05-01

    Full Text Available The Particle Swarm Optimization (PSO and Support Vector Machines (SVMs approaches are used for predicting the thermodynamic parameters for the 1:1 inclusion complexation of chiral guests with β-cyclodextrin. A PSO is adopted for descriptor selection in the quantitative structure-property relationships (QSPR of a dataset of 74 chiral guests due to its simplicity, speed, and consistency. The modified PSO is then combined with SVMs for its good approximating properties, to generate a QSPR model with the selected features. Linear, polynomial, and Gaussian radial basis functions are used as kernels in SVMs. All models have demonstrated an impressive performance with R2 higher than 0.8.

  15. Identification of constitutive theory parameters using a tensile machine for deposited filaments of microcrystalline ink by the direct-write method

    International Nuclear Information System (INIS)

    Lourdel, N; Therriault, D; Lévesque, M

    2009-01-01

    A custom-designed tensile machine is developed to characterize the mechanical properties of ink micro-filaments deposited by the direct-write method. The direct-write method has been used for the fabrication of a wide variety of micro-systems such as microvascular networks, chaotic mixers and laboratory on chips. The tensile machine was used to measure the induced force in ink filaments during tensile and tension-relaxation tests as a function of the applied strain rate, the ink composition and the filament diameter. Experimental data were fitted by a linearly viscoelastic model using a data reduction procedure in order to identify the constitutive theory parameters of the deposited ink filaments. The model predictions based on the linearly viscoelastic model and the defined constitutive theory parameters give a close approximation of all experimental data generated in this study. Such models will be useful for the development and optimization of future 3D complex structures made by the direct-write method

  16. Study on electromagnetism force of CARR control rod drive mechanism experimental machine

    International Nuclear Information System (INIS)

    Zhu Xuewei; Zhen Jianxiao; Wang Yulin; Jia Yueguang; Yang Kun; Yin Haozhe

    2015-01-01

    With the aim of acquiring electromagnetic force and electromagnetic field distributions of control rod drive mechanism (CRDM) in China Advanced Research Reactor (CARR), the force analysis on the CRDM was taken. Manufacturing the experimental machine, the electromagnetic force experiment was taken on it. The electromagnetic field and electromagnetic force simulation analyses of experimental machine were taken, working out distribution data of electromagnetic force and magnetic induction intensity distribution curve, and the effects of permanent magnetic field on electromagnetic field and structure parameters on electromagnetic force. The simulation value is accord with experiment value, the research results provide a reference to electromagnetic force study on CRDM in CARR, and also provide a reference to design of the same type CRDM. (authors)

  17. Comparative Study of Powdered Ginger Drink Processed by Different Method:Traditional and using Evaporation Machine

    Science.gov (United States)

    Apriyana, Wuri; Taufika Rosyida, Vita; Nur Hayati, Septi; Darsih, Cici; Dewi Poeloengasih, Crescentiana

    2017-12-01

    Ginger drink is one of the traditional beverage that became one of the products of interest by consumers in Indonesia. This drink is believed to have excellent properties for the health of the body. In this study, we have compared the moisture content, ash content, metal content and the identified compound of product which processed with traditional technique and using an evaporator machine. The results show that both of products fulfilled some parameters of the Indonesian National Standard for the traditional powdered drink. GC-MS analysis data showed the identified compound of both product. The major of hydrocarbon groups that influenced the flavor such as zingiberene, camphene, beta-phelladrine, beta-sesquepelladrine, curcumene, and beta-bisabolene were found higher in ginger drink powder treated with a machine than those processed traditionally.

  18. A review on feasibility study of ultrasonic assisted machining on aircraft component manufacturing

    Science.gov (United States)

    Hafiz, M. S. A.; Kawaz, M. H. A.; Mohamad, W. N. F.; Kasim, M. S.; Izamshah, R.; Saedon, J. B.; Mohamed, S. B.

    2017-12-01

    Inconel 718 has been widely used in aerospace because of its excellent mechanical properties such as good corrosion resistance, strong creep resistance and high fatigue strength. However, these excellent properties also lead to heavy tool damage and high cutting force in the milling process. There is no reported investigation on ultrasonic assisted machining (UAM) of Inconel 718 parts. In this paper, UAM is proposed as the potential technique to reduce tool damage and the cutting force of Inconel 718 parts. This review paper provides an overview of UAM to investigate the relationship between the tool wear and the cutting force with ultrasonic vibration compared to without ultrasonic vibration assisted. Throughout the study, the UAM scopes are related to the tool life of coated carbide insert, the force generated during the cutting process and also the final surface finish of the workpiece by using various parameters during the machining activity.

  19. Evaluation influence of machining parameters on shape form errors in turning of machine parts clamped in the chuck with adaptive jaws

    Directory of Open Access Journals (Sweden)

    I.V. Lutsiv

    2017-12-01

    Full Text Available The paper deals with the derivation problem of the dependence of machine part geometric form deviation in cross section area on clamping diameter as well as cutting speed, feed and cutting depth in semi finish machining. The analysis of single factor circular deviation dependences on machining conditions values is performed. Using the special software application package the laboratory conditions experiment results are analyzed. The dispersion analysis including options for main linear and quadratic effects evaluation is given and the simplification model of experiment results is obtained. It presents the evaluation empiric dependence of cutting conditions and clamping diameter influence on shape error forming (dynamic error. It is found that to obtain the necessary form accuracy in machining with lathe chuck equipped with the adaptive clamping jaws it is desirable to control the most statistically significant factors that actually are the cutting depth and feed.

  20. Manufacturing tungsten monocrystal tubes by electro-spark machining and study of machined surface structure

    International Nuclear Information System (INIS)

    Abdukarimov, Eh.T.; Ismailov, L.R.; Krakhmalev, V.A.; Fershtat, L.N.

    1981-01-01

    A technique to manufacture tubes from tungsten monocrystals with low consumption of electrodes has been developed. Regimes of obtaining deep and through holes of different diameters with the productivity of 1 mm/min and with the minimum deviation from cylindrical shape are worked out using a specially designed electric pulse installation. X-ray and metallographical analyses have shown that as a result of electrospark machining a cold hardened layer is formed up to hundreds micrometers thick, pierced by the network of microcracks. Simultaneous use of electrospark and electrochemical machining permitted to manufacture tubes from tungsten monocrystals with non-distorted monocrystal surface and without a network of microcracks

  1. Machine Imperfection Studies of the RAON Superconducting Linac

    Science.gov (United States)

    Jeon, D.; Jang, J.-H.; Jin, H.

    2018-05-01

    Studies of the machine imperfections in the RAON superconducting linac (SCL) that employs normal conducting (NC) quadrupoles were done to assess the tolerable error budgets of the machine imperfections that ensure operation of the beam. The studies show that the beam loss requirement is met even before the orbit correction and that the beam loss requirement is met even without the MHB (multi-harmonic buncher) and VE (velocity equalizer) thanks to the RAON's radio-frequency quadrupole (RFQ) design feature. For the low energy section of the linac (SCL3), a comparison is made between the two superconducting linac lattice types: one lattice that employs NC quadrupoles and the other that employs SC solenoids. The studies show that both lattices meet the beam loss requirement after the orbit correction. However, before the orbit correction, the lattice employing SC solenoids does not meet the beam loss requirement and can cause a significant beam loss, while the lattice employing NC quadrupoles meets the requirement. For the lattice employing SC solenoids, care must be taken during the beam commissioning.

  2. Program for parameter studies of steam generators

    International Nuclear Information System (INIS)

    Mathisen, R.P.

    1982-11-01

    R2-GEN is a computer code for stationary thermal parameter studies of steam generators. The geometry and data are valid for Ringhals-2 generators. Subroutines and relevant calculations are included. The program is based on a heterogeneous flow model and some applications on tubes with varying contamination are presented. (G.B.)

  3. Machinability study of steels in precision orthogonal cutting

    Directory of Open Access Journals (Sweden)

    Leonardo Roberto Silva

    2012-08-01

    Full Text Available The miniaturization of components and systems is advancing steadily in many areas of engineering. Consequently, micro-machining is becoming an important manufacture technology due to the increasing demand for miniaturized products in recent years. Precision machining aims the production of advanced components with high dimensional accuracy and acceptable surface integrity. This work presents an experimental study based on Merchant and Lee & Shaffer theories applied to precision radial turning of AISI D2 cold work tool and AISI 1045 medium carbon steels with uncoated carbide tools ISO grade K15. The aim of this study is to evaluate the influence of feed rate on chip compression ratio (Rc, chip deformation (ε, friction angle (ρ, shear angle (Φ, normal stress (σ and shear stress (• for both work materials. The results indicated that the shear angle decreased and chip deformation increased as the chip compression ratio was elevated without significant differences between both materials. Additionally, higher cutting and thrust forces and normal and shear stresses were observed for the tool steel. Finally, the Lee & Shaffer model gave shear plane angle values closer to the experimental data.

  4. Optimization of Parameters for Manufacture Nanopowder Bioceramics at Machine Pulverisette 6 by Taguchi and ANOVA Method

    Science.gov (United States)

    Van Hoten, Hendri; Gunawarman; Mulyadi, Ismet Hari; Kurniawan Mainil, Afdhal; Putra, Bismantoloa dan

    2018-02-01

    This research is about manufacture nanopowder Bioceramics from local materials used Ball Milling for biomedical applications. Source materials for the manufacture of medicines are plants, animal tissues, microbial structures and engineering biomaterial. The form of raw material medicines is a powder before mixed. In the case of medicines, research is to find sources of biomedical materials that will be in the nanoscale powders can be used as raw material for medicine. One of the biomedical materials that can be used as raw material for medicine is of the type of bioceramics is chicken eggshells. This research will develop methods for manufacture nanopowder material from chicken eggshells with Ball Milling using the Taguchi method and ANOVA. Eggshell milled using a variation of Milling rate on 150, 200 and 250 rpm, the time variation of 1, 2 and 3 hours and variations the grinding balls to eggshell powder weight ratio (BPR) 1: 6, 1: 8, 1: 10. Before milled with Ball Milling crushed eggshells in advance and calcinate to a temperature of 900°C. After the milled material characterization of the fine powder of eggshell using SEM to see its size. The result of this research is optimum parameter of Taguchi Design analysis that is 250 rpm milling rate, 3 hours milling time and BPR is 1: 6 with the average eggshell powder size is 1.305 μm. Milling speed, milling time and ball to powder weight of ratio have contribution successively equal to 60.82%, 30.76% and 6.64% by error equal to 1.78%.

  5. A self-centering active probing technique for kinematic parameter identification and verification of articulated arm coordinate measuring machines

    International Nuclear Information System (INIS)

    Santolaria, J; Brau, A; Velázquez, J; Aguilar, J J

    2010-01-01

    A crucial task in the procedure of identifying the parameters of a kinematic model of an articulated arm coordinate measuring machine (AACMM) or robot arm is the process of capturing data. In this paper a capturing data method is analyzed using a self-centering active probe, which drastically reduces the capture time and the required number of positions of the gauge as compared to the usual standard and manufacturer methods. The mathematical models of the self-centering active probe and AACMM are explained, as well as the mathematical model that links the AACMM global reference system to the probe reference system. We present a self-calibration method that will allow us to determine a homogeneous transformation matrix that relates the probe's reference system to the AACMM last reference system from the probing of a single sphere. In addition, a comparison between a self-centering passive probe and self-centering active probe is carried out to show the advantages of the latter in the procedures of kinematic parameter identification and verification of the AACMM

  6. A Machine Learning Approach to Estimate Riverbank Geotechnical Parameters from Sediment Particle Size Data

    Science.gov (United States)

    Iwashita, Fabio; Brooks, Andrew; Spencer, John; Borombovits, Daniel; Curwen, Graeme; Olley, Jon

    2015-04-01

    Assessing bank stability using geotechnical models traditionally involves the laborious collection of data on the bank and floodplain stratigraphy, as well as in-situ geotechnical data for each sedimentary unit within a river bank. The application of geotechnical bank stability models are limited to those sites where extensive field data has been collected, where their ability to provide predictions of bank erosion at the reach scale are limited without a very extensive and expensive field data collection program. Some challenges in the construction and application of riverbank erosion and hydraulic numerical models are their one-dimensionality, steady-state requirements, lack of calibration data, and nonuniqueness. Also, numerical models commonly can be too rigid with respect to detecting unexpected features like the onset of trends, non-linear relations, or patterns restricted to sub-samples of a data set. These shortcomings create the need for an alternate modelling approach capable of using available data. The application of the Self-Organizing Maps (SOM) approach is well-suited to the analysis of noisy, sparse, nonlinear, multidimensional, and scale-dependent data. It is a type of unsupervised artificial neural network with hybrid competitive-cooperative learning. In this work we present a method that uses a database of geotechnical data collected at over 100 sites throughout Queensland State, Australia, to develop a modelling approach that enables geotechnical parameters (soil effective cohesion, friction angle, soil erodibility and critical stress) to be derived from sediment particle size data (PSD). The model framework and predicted values were evaluated using two methods, splitting the dataset into training and validation set, and through a Bootstrap approach. The basis of Bootstrap cross-validation is a leave-one-out strategy. This requires leaving one data value out of the training set while creating a new SOM to estimate that missing value based on the

  7. Behavioral study of cnc-retrofitting kits for lathe machine

    International Nuclear Information System (INIS)

    Ahmad, I.

    1999-01-01

    The aim of this project is to develop a Computerized Numerical Controlled (CNC) retrofitting kit for a lathe machine, study its behavior and compare its performance with the retrofitting kit already designed and fabricated at (Pakistan Institute of Engineering and Applied Sciences (PIEAS). Design calculations were performed assuming 100 mm work piece diameter and 800 mm length of stock using tool materials HSS, uncoated carbide, coated carbide, ceramic and cermet tools for different materials. Also cutting, thrust and radial forces on a single point cutting tool were determined. Stepper motors of torque 972 oz-in were selected to drive the carriage and cross-slide in Z and X-directions respectively. Power screws were replaced with ball screws of 0.63 inch dia. (x-direction) and 1.26 in. dia. (Z-direction) which were locally manufactured in the workshop. Deep groove and Angular contact ball bearings were used to support the ball screw shafts against axial and radial loads. Flexible and plain couplings were developed to couple encoders and motors to the ball screw shafts respectively. Panel mount optical rotary encoders are being used for feedback control. Mechanical assembly is complete but due to unavailability of wiring diagram for motors, control electronics could not be accomplished. Therefore, machine could not be evaluated in terms of accuracy, repeatability and resolution using computer software. (author)

  8. Study of Acrylamide Level in Food from Vending Machines.

    Science.gov (United States)

    Haouet, Naceur; Pistolese, Simona; Branciari, Raffaella; Ranucci, David; Altissimi, Maria Serena

    2016-09-20

    Acrylamide is a by-product of the Maillard reaction and is potentially carcinogenic to humans. It is found in a number of foods with higher concentrations in carbohydrate-rich foods and moderate levels of protein-rich foods such as meat, fish and seafood. Acrylamide levels in food distributed in vending machines placed in public areas of the city of Perugia were analysed by high-performance liquid chromatography. Samples included five different categories, depending on the characteristics of the products: i) potato chips; ii) salted bakery products; iii) biscuits and wafers; iv) sweet bakery products; v) sandwiches. A high variability in acrylamide level among different foods and within the same category was detected. Potato chips showed the highest amount of acrylamide (1781±637 μg/kg) followed by salted bakery products (211 ±245 μg/kg), biscuits and wafers (184±254 μg/kg), sweet bakery products (100±72 μg/kg) and sandwiches (42±10 μg/kg). In the potato chips and sandwiches categories, all of the samples revealed the presence of acrylamide, while different prevalence was registered in the other foods considered. The data of this study highlight the presence of acrylamide in different foods sold in vending machines and this data could be useful to understand the contribution of this type of consumption to human exposure to this compound.

  9. Study of acrylamide level in food from vending machines

    Directory of Open Access Journals (Sweden)

    Naceur Haouet

    2016-11-01

    Full Text Available Acrylamide is a by-product of the Maillard reaction and is potentially carcinogenic to humans. It is found in a number of foods with higher concentrations in carbohydrate-rich foods and moderate levels of protein-rich foods such as meat, fish and seafood. Acrylamide levels in food distributed in vending machines placed in public areas of the city of Perugia were analysed by high-performance liquid chromatography. Samples included five different categories, depending on the characteristics of the products: i potato chips; ii salted bakery products; iii biscuits and wafers; iv sweet bakery products; v sandwiches. A high variability in acrylamide level among different foods and within the same category was detected. Potato chips showed the highest amount of acrylamide (1781±637 μg/kg followed by salted bakery products (211±245 μg/kg, biscuits and wafers (184±254 μg/kg, sweet bakery products (100±72 μg/kg and sandwiches (42±10 μg/kg. In the potato chips and sandwiches categories, all of the samples revealed the presence of acrylamide, while different prevalence was registered in the other foods considered. The data of this study highlight the presence of acrylamide in different foods sold in vending machines and this data could be useful to understand the contribution of this type of consumption to human exposure to this compound.

  10. Empirical Studies On Machine Learning Based Text Classification Algorithms

    OpenAIRE

    Shweta C. Dharmadhikari; Maya Ingle; Parag Kulkarni

    2011-01-01

    Automatic classification of text documents has become an important research issue now days. Properclassification of text documents requires information retrieval, machine learning and Natural languageprocessing (NLP) techniques. Our aim is to focus on important approaches to automatic textclassification based on machine learning techniques viz. supervised, unsupervised and semi supervised.In this paper we present a review of various text classification approaches under machine learningparadig...

  11. Intellectual Property and Machine Learning: An exploratory study

    OpenAIRE

    Øverlier, Lasse

    2017-01-01

    Our research makes a contribution by exemplifying what controls the freedom-to-operate for a company operating in the area of machine learning. Through interviews we demonstrate the industry’s alternating viewpoints to whether copyrighted data used as input to machine learning systems should be viewed differently than copying the data for storage or reproduction. In addition we show that unauthorized use of copyrighted data in machine learning systems is hard to detect with the burden of proo...

  12. Comparison of direct machine parameter optimization versus fluence optimization with sequential sequencing in IMRT of hypopharyngeal carcinoma

    International Nuclear Information System (INIS)

    Dobler, Barbara; Pohl, Fabian; Bogner, Ludwig; Koelbl, Oliver

    2007-01-01

    To evaluate the effects of direct machine parameter optimization in the treatment planning of intensity-modulated radiation therapy (IMRT) for hypopharyngeal cancer as compared to subsequent leaf sequencing in Oncentra Masterplan v1.5. For 10 hypopharyngeal cancer patients IMRT plans were generated in Oncentra Masterplan v1.5 (Nucletron BV, Veenendal, the Netherlands) for a Siemens Primus linear accelerator. For optimization the dose volume objectives (DVO) for the planning target volume (PTV) were set to 53 Gy minimum dose and 59 Gy maximum dose, in order to reach a dose of 56 Gy to the average of the PTV. For the parotids a median dose of 22 Gy was allowed and for the spinal cord a maximum dose of 35 Gy. The maximum DVO to the external contour of the patient was set to 59 Gy. The treatment plans were optimized with the direct machine parameter optimization ('Direct Step & Shoot', DSS, Raysearch Laboratories, Sweden) newly implemented in Masterplan v1.5 and the fluence modulation technique ('Intensity Modulation', IM) which was available in previous versions of Masterplan already. The two techniques were compared with regard to compliance to the DVO, plan quality, and number of monitor units (MU) required per fraction dose. The plans optimized with the DSS technique met the DVO for the PTV significantly better than the plans optimized with IM (p = 0.007 for the min DVO and p < 0.0005 for the max DVO). No significant difference could be observed for compliance to the DVO for the organs at risk (OAR) (p > 0.05). Plan quality, target coverage and dose homogeneity inside the PTV were superior for the plans optimized with DSS for similar dose to the spinal cord and lower dose to the normal tissue. The mean dose to the parotids was lower for the plans optimized with IM. Treatment plan efficiency was higher for the DSS plans with (901 ± 160) MU compared to (1151 ± 157) MU for IM (p-value < 0.05). Renormalization of the IM plans to the mean of the

  13. Study of the stiffness for predicting the accuracy of machine tools; Estudio de la rigidez para la prediccion de la precision de las maquinas-herramientas

    Energy Technology Data Exchange (ETDEWEB)

    Ortega, N.; Campa, F.J.; Fernandez Valdivielso, A.; Alonso, U.; Olvera, D.; Compean, F.I.

    2010-07-01

    Machining processes are frequently faced with the challenge of achieving more and more precision and surface qualities. These requirements are usually attained taking into account some process variables, including the cutting parameters and the use or not of refrigerant, leaving aside the mechanical aspects associated with the influence of machine tool itself. There are many sources of error linked with machine-workpiece interaction, but, in general, we can summarize them into two types of error: quasi-static and dynamic. This paper shows the influence of quasi-static error caused by low machine rigidity on the accuracy applied on two very different processes: turning and grinding. For the study of the static stiffness of these two machines, two different methods are proposed, both of them equally valid. The first one is based on separated parameters and the second one on finite elements. (Author).

  14. Disruption Warning Database Development and Exploratory Machine Learning Studies on Alcator C-Mod

    Science.gov (United States)

    Montes, Kevin; Rea, Cristina; Granetz, Robert

    2017-10-01

    A database of about 1800 shots from the 2015 campaign on the Alcator C-Mod tokamak is assembled, including disruptive and non-disruptive discharges. The database consists of 40 relevant plasma parameters with data taken from 160k time slices. In order to investigate the possibility of developing a robust disruption prediction algorithm that is tokamak-independent, we focused machine learning studies on a subset of dimensionless parameters such as βp, n /nG , etc. The Random Forests machine learning algorithm provides insight on the available data set by ranking the relative importance of the input features. Its application on the C-Mod database, however, reveals that virtually no one parameter has more importance than any other, and that its classification algorithm has a low rate of successfully predicted samples, as well as poor false positive and false negative rates. Comparing the analysis of this algorithm on the C-Mod database with its application to a similar database on DIII-D, we conclude that disruption prediction may not be feasible on C-Mod. This conclusion is supported by empirical observations that most C-Mod disruptions are caused by radiative collapse due to molybdenum from the first wall, which happens on just a 1-2ms timescale. Supported by the US Dept. of Energy under DE-FC02-99ER54512 and DE-FC02-04ER54698.

  15. Multi-parameter machine learning approach to the neuroanatomical basis of developmental dyslexia.

    Science.gov (United States)

    Płoński, Piotr; Gradkowski, Wojciech; Altarelli, Irene; Monzalvo, Karla; van Ermingen-Marbach, Muna; Grande, Marion; Heim, Stefan; Marchewka, Artur; Bogorodzki, Piotr; Ramus, Franck; Jednoróg, Katarzyna

    2017-02-01

    Despite decades of research, the anatomical abnormalities associated with developmental dyslexia are still not fully described. Studies have focused on between-group comparisons in which different neuroanatomical measures were generally explored in isolation, disregarding potential interactions between regions and measures. Here, for the first time a multivariate classification approach was used to investigate grey matter disruptions in children with dyslexia in a large (N = 236) multisite sample. A variety of cortical morphological features, including volumetric (volume, thickness and area) and geometric (folding index and mean curvature) measures were taken into account and generalizability of classification was assessed with both 10-fold and leave-one-out cross validation (LOOCV) techniques. Classification into control vs. dyslexic subjects achieved above chance accuracy (AUC = 0.66 and ACC = 0.65 in the case of 10-fold CV, and AUC = 0.65 and ACC = 0.64 using LOOCV) after principled feature selection. Features that discriminated between dyslexic and control children were exclusively situated in the left hemisphere including superior and middle temporal gyri, subparietal sulcus and prefrontal areas. They were related to geometric properties of the cortex, with generally higher mean curvature and a greater folding index characterizing the dyslexic group. Our results support the hypothesis that an atypical curvature pattern with extra folds in left hemispheric perisylvian regions characterizes dyslexia. Hum Brain Mapp 38:900-908, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  16. Study on the effect of thermal property of metals in ultrasonic-assisted laser machining

    International Nuclear Information System (INIS)

    Lee, Hu Seung; Kim, Gun Woo; Park, Jong Eun; Cho, Sung Hak; Yang, Min Yang; Park, Jong Kweon

    2015-01-01

    The laser machining process has been proposed as an advanced process for the selective fabrication of electrodes without a mask. In this study, we adapt laser machining to metals that have different thermal properties. Based on the results, the metals exhibit a different surface morphology, heat-affected zone (HAZ), and a recast layer around the machined surface according to their thermal conductivity, boiling point, and thermal diffusivity. Then, we apply ultrasonic-assisted laser machining to remove the recast layer. The ultrasonic-assisted laser machining exhibits a better surface quality in metals with higher diffusivity than those having lower diffusivity

  17. Employing Machine-Learning Methods to Study Young Stellar Objects

    Science.gov (United States)

    Moore, Nicholas

    2018-01-01

    Vast amounts of data exist in the astronomical data archives, and yet a large number of sources remain unclassified. We developed a multi-wavelength pipeline to classify infrared sources. The pipeline uses supervised machine learning methods to classify objects into the appropriate categories. The program is fed data that is already classified to train it, and is then applied to unknown catalogues. The primary use for such a pipeline is the rapid classification and cataloging of data that would take a much longer time to classify otherwise. While our primary goal is to study young stellar objects (YSOs), the applications extend beyond the scope of this project. We present preliminary results from our analysis and discuss future applications.

  18. Electron-beam welding of 21-6-9 (Cr--Ni--Mn) stainless steel: effect of machine parameters on weldability

    International Nuclear Information System (INIS)

    Casey, H.

    1975-04-01

    The high-manganese, nitrogen-strengthened 21-6-9 (Cr--Ni--Mn) austenitic stainless steel has a weldability rating similar to that of more common austenitic stainless steels in terms of cracking, porosity, etc. However, weld pool disruption problems may occur with this alloy that can be related to instability within the molten weld pool. Selection of machine parameters is critical to achieving weld pool quiescence as this report confirms from recent tests. Test samples came from heats of air-melted, vacuum-arc remelted, and electroslag remelted material. Low- and high-voltage machine parameters are discussed, and effects of parameter variation on weld pool behavior are given. Data relate weld pool behavior to weld fusion-zone geometry. Various weld parameters are recommended for the 21-6-9 alloy, regardless of its source or chemistry. (auth)

  19. Effect of nose radius on forces, and process parameters in hot machining of Inconel 718 using finite element analysis

    Directory of Open Access Journals (Sweden)

    Asit Kumar Parida

    2017-04-01

    Full Text Available In the present work, the variation of nose radius on forces, cutting temperature, stress, has been studied using finite element modeling in hot turning operation of Inconel 718. Three values of nose radius were taken (0.4, 0.8 and 1.2 mm. Cutting force, thrust force, stress, and cutting temperature have been predicted using commercial DEFORM™ software at different cutting tool nose radius in both room and heated conditions. With the increase of tool nose radius in both room and elevated machining conditions the cutting force and thrust force increased. The cutting temperature, chip thickness and chip tool contact length also have been studied. In order to validate the numerical results an experimental analysis has been performed and good agreement between them has been observed

  20. Effect of Machining Velocity in Nanoscale Machining Operations

    International Nuclear Information System (INIS)

    Islam, Sumaiya; Khondoker, Noman; Ibrahim, Raafat

    2015-01-01

    The aim of this study is to investigate the generated forces and deformations of single crystal Cu with (100), (110) and (111) crystallographic orientations at nanoscale machining operation. A nanoindenter equipped with nanoscratching attachment was used for machining operations and in-situ observation of a nano scale groove. As a machining parameter, the machining velocity was varied to measure the normal and cutting forces. At a fixed machining velocity, different levels of normal and cutting forces were generated due to different crystallographic orientations of the specimens. Moreover, after machining operation percentage of elastic recovery was measured and it was found that both the elastic and plastic deformations were responsible for producing a nano scale groove within the range of machining velocities from 250-1000 nm/s. (paper)

  1. Comparative Study of White Layer Characteristics for Static and Rotating Workpiece during Electric Discharge Machining

    Directory of Open Access Journals (Sweden)

    SHAHID MEHMOOD

    2017-10-01

    Full Text Available EDMed (Electric Discharge Machined surfaces are unique in their appearance and metallurgical characteristics, which depend on different parameter such as electric parameters, flushing method, and dielectric type. Conventionally, in static workpiece method the EDM (Electric Discharge Machining is performed by submerging both of the tool and workpiece in dielectric liquid and side flushing is provided by impinging pressurized dielectric liquid into the gap. Another flushing method has been investigated in this study, in which, instead of side flushing the rotation motion is provided to the workpiece. Surface characteristics for both flushing methods are determined and compared in this study. The investigated surface characteristics are: surface roughness, crater size, surface morphology, white layer thickness and composition. These investigations are performed using optical and SEM (Scanning Electron Microscope. Statistical confidence limits are determined for scattered data of surface roughness. It is found that the white layer thickness and surface roughness are directly proportional to discharge current for both flushing methods. The comparison has shown that the side flushing of statics workpiece gives thicker white layer and lower surface finish as compared to the flushing caused by the rotation of workpiece

  2. Comparative study of white layer characteristics for static and rotating workpiece during electric discharge machining

    International Nuclear Information System (INIS)

    Mehmood, S.; Shah, M.; Anjum, N.A.

    2017-01-01

    EDMed (Electric Discharge Machined) surfaces are unique in their appearance and metallurgical characteristics, which depend on different parameter such as electric parameters, flushing method, and dielectric type. Conventionally, in static workpiece method the EDM (Electric Discharge Machining) is performed by submerging both of the tool and workpiece in dielectric liquid and side flushing is provided by impinging pressurized dielectric liquid into the gap. Another flushing method has been investigated in this study, in which, instead of side flushing the rotation motion is provided to the workpiece. Surface characteristics for both flushing methods are determined and compared in this study. The investigated surface characteristics are: surface roughness, crater size, surface morphology, white layer thickness and composition. These investigations are performed using optical and SEM (Scanning Electron Microscope). Statistical confidence limits are determined for scattered data of surface roughness. It is found that the white layer thickness and surface roughness are directly proportional to discharge current for both flushing methods. The comparison has shown that the side flushing of statics workpiece gives thicker white layer and lower surface finish as compared to the flushing caused by the rotation of workpiece. (author)

  3. A Study of the Interaction between Batting Cage Baseballs and Pitching Machine

    Directory of Open Access Journals (Sweden)

    Patrick Drane

    2018-02-01

    Full Text Available Batting cage pitching machines are widely used across the sports of baseball and softball for training and recreation purposes. The balls are specifically designed for the machines and for the environment to ensure high durability and typically do not have seams. Polymeric foam balls are widely used in these automated pitching machines for batting practice in a cage environment and are similar in weight and size compared with the regulation balls used in leagues. The primary objective of this paper is to characterize the polymeric balls and their interaction with the pitching machine. The paper will present measured ball properties and measured relationships between various pitching machine parameters such as wheel speed, and the ratio of wheel speeds on the ball exit velocity and rotation. This paper will also characterize some of the effects of wear on the baseballs and wheels from their prolonged use.

  4. Analysis of Effects of Cutting Parameters of Wire Electrical Discharge Machining on Material Removal Rate and Surface Integrity

    International Nuclear Information System (INIS)

    Tonday, H. R.; Tigga, A. M.

    2016-01-01

    As wire electrical discharge machining is pioneered as a vigorous, efficient and precise and complex nontraditional machining technique, research is needed in this area for efficient machining. In this paper, the influence of various input factors of wire electrical discharge machining (WEDM) on output variable has been analyzed by using Taguchi technique and analysis of variance. The design of experiments has been done and by applying L8 orthogonal arrays method and experiments have been conducted and collected required data. The objectives of the research are to maximize the material removal rate and to minimize the surface roughness value (Ra). Surface morphology of machined workpiece has been obtained and examined by employing scanning electron microscopy (SEM) technique. (paper)

  5. Analysis of Effects of Cutting Parameters of Wire Electrical Discharge Machining on Material Removal Rate and Surface Integrity

    Science.gov (United States)

    Tonday, H. R.; Tigga, A. M.

    2016-02-01

    As wire electrical discharge machining is pioneered as a vigorous, efficient and precise and complex nontraditional machining technique, research is needed in this area for efficient machining. In this paper, the influence of various input factors of wire electrical discharge machining (WEDM) on output variable has been analyzed by using Taguchi technique and analysis of variance. The design of experiments has been done and by applying L8 orthogonal arrays method and experiments have been conducted and collected required data. The objectives of the research are to maximize the material removal rate and to minimize the surface roughness value (Ra). Surface morphology of machined workpiece has been obtained and examined by employing scanning electron microscopy (SEM) technique.

  6. Using machine learning to assess covariate balance in matching studies.

    Science.gov (United States)

    Linden, Ariel; Yarnold, Paul R

    2016-12-01

    In order to assess the effectiveness of matching approaches in observational studies, investigators typically present summary statistics for each observed pre-intervention covariate, with the objective of showing that matching reduces the difference in means (or proportions) between groups to as close to zero as possible. In this paper, we introduce a new approach to distinguish between study groups based on their distributions of the covariates using a machine-learning algorithm called optimal discriminant analysis (ODA). Assessing covariate balance using ODA as compared with the conventional method has several key advantages: the ability to ascertain how individuals self-select based on optimal (maximum-accuracy) cut-points on the covariates; the application to any variable metric and number of groups; its insensitivity to skewed data or outliers; and the use of accuracy measures that can be widely applied to all analyses. Moreover, ODA accepts analytic weights, thereby extending the assessment of covariate balance to any study design where weights are used for covariate adjustment. By comparing the two approaches using empirical data, we are able to demonstrate that using measures of classification accuracy as balance diagnostics produces highly consistent results to those obtained via the conventional approach (in our matched-pairs example, ODA revealed a weak statistically significant relationship not detected by the conventional approach). Thus, investigators should consider ODA as a robust complement, or perhaps alternative, to the conventional approach for assessing covariate balance in matching studies. © 2016 John Wiley & Sons, Ltd.

  7. Early failure analysis of machining centers: a case study

    International Nuclear Information System (INIS)

    Wang Yiqiang; Jia Yazhou; Jiang Weiwei

    2001-01-01

    To eliminate the early failures and improve the reliability, nine ex-factory machining centers are traced under field conditions in workshops. Their early failure information throughout the ex-factory run-in test is collected. The field early failure database is constructed based on the collection of field early failure data and the codification of data. Early failure mode and effects analysis is performed to indicate the weak subsystem of a machining center or the troublemaker. The distribution of the time between early failures is analyzed and the optimal ex-factory run-in test time for machining center that may expose sufficiently the early failures and cost minimum is discussed. Suggestions how to arrange ex-factory run-in test and how to take actions to reduce early failures for machining center is proposed

  8. Support vector machine for diagnosis cancer disease: A comparative study

    Directory of Open Access Journals (Sweden)

    Nasser H. Sweilam

    2010-12-01

    Full Text Available Support vector machine has become an increasingly popular tool for machine learning tasks involving classification, regression or novelty detection. Training a support vector machine requires the solution of a very large quadratic programming problem. Traditional optimization methods cannot be directly applied due to memory restrictions. Up to now, several approaches exist for circumventing the above shortcomings and work well. Another learning algorithm, particle swarm optimization, Quantum-behave Particle Swarm for training SVM is introduced. Another approach named least square support vector machine (LSSVM and active set strategy are introduced. The obtained results by these methods are tested on a breast cancer dataset and compared with the exact solution model problem.

  9. EXPERIMENTAL EVALUATION OF WEDM MACHINED SURFACE WAVINESS

    Directory of Open Access Journals (Sweden)

    Katerina Mouralova

    2016-10-01

    Full Text Available Wire Electrical Discharge Machining (WEDM an unconventional machining technology which has become indispensable in many industries. The typical morphology of a surface machined using the electrical discharge technology is characterized with a large number of craters caused by electro-spark discharges produced during the machining process. The study deals with an evaluation of the machine parameter setting on the profile parameters of surface waviness on samples made of two metal materials Al 99.5 and Ti-6Al-4V. Attention was also paid to an evaluation of the surface morphology using 3D colour filtered and non-filtered images.

  10. The Influence Study of Ultrasonic honing parameters to workpiece surface temperature

    Directory of Open Access Journals (Sweden)

    Zhang Xiaoqiang

    2016-01-01

    Full Text Available Ultrasonic vibration honing(UVH, a machine technology, has a lot of advantages. Lower grinding temperature is a significant character and is beneficial for both processing and workpiece surface. But the high temperature caused by big honing pressure becomes the main factor to produce workpiece heat damage in grinding zone. In various honing parameter combinations, the showing effect is different. Based on the thermodynamics classical theory, established the heat transfer equation for grinding zone, simplified the model and obtained the two-dimenssion temperature field expression for workpiece, then simulated the temperature changing trend in a variety of conditions. It is shown that themain temp is in a range of 700K to 1200K. In addition, the variation is huge for every parameter. The study provides a theoretical basis for deeply seeking reasonable machining parameter and obtaining better workpiece quality.

  11. Body machine interfaces for neuromotor rehabilitation: a case study.

    Science.gov (United States)

    Pierella, Camilla; Abdollahi, Farnaz; Farshchiansadegh, Ali; Pedersen, Jessica; Chen, David; Mussa-Ivaldi, Ferdinando A; Casadio, Maura

    2014-01-01

    High-level spinal cord injury (SCI) survivors face every day two related problems: recovering motor skills and regaining functional independence. Body machine interfaces (BoMIs) empower people with sever motor disabilities with the ability to control an external device, but they also offer the opportunity to focus concurrently on achieving rehabilitative goals. In this study we developed a portable, and low-cost BoMI that addresses both problems. The BoMI remaps the user's residual upper body mobility to the two coordinates of a cursor on a computer monitor. By controlling the cursor, the user can perform functional tasks, such as entering text and playing games. This framework also allows the mapping between the body and the cursor space to be modified, gradually challenging the user to exercise more impaired movements. With this approach, we were able to change the behavior of our SCI subject, who initially used almost exclusively his less impaired degrees of freedom - on the left side - for controlling the BoMI. At the end of the few practice sessions he had restored symmetry between left and right side of the body, with an increase of mobility and strength of all the degrees of freedom involved in the control of the interface. This is the first proof of concept that our BoMI can be used to control assistive devices and reach specific rehabilitative goals simultaneously.

  12. Study of electroweak parameters at LEP

    International Nuclear Information System (INIS)

    Blum, W.

    1991-10-01

    The measurement of the line shape and asymmetry parameters of the Z 0 in its leptonic and hadronic decays are reviewed. Progress is reported about a considerable increase in measurement accuracy. Several tests of the Standard Model confirm it to better than one per cent. New values for the effective mixing parameter are derived from the line shape parameters averaged over the four LEP experiments. The corresponding limits on the top mass are presented. (orig.)

  13. In vivo and in vitro performance of a China-made hemodialysis machine: a multi-center prospective controlled study.

    Science.gov (United States)

    Wang, Yong; Chen, Xiang-Mei; Cai, Guang-Yan; Li, Wen-Ge; Zhang, Ai-Hua; Hao, Li-Rong; Shi, Ming; Wang, Rong; Jiang, Hong-Li; Luo, Hui-Min; Zhang, Dong; Sun, Xue-Feng

    2017-08-02

    To evaluate the in vivo and in vitro performance of a China-made dialysis machine (SWS-4000). This was a multi-center prospective controlled study consisting of both long-term in vitro evaluations and cross-over in vivo tests in 132 patients. The China-made SWS-4000 dialysis machine was compared with a German-made dialysis machine (Fresenius 4008) with regard to Kt/V values, URR values, and dialysis-related adverse reactions in patients on maintenance hemodialysis, as well as the ultrafiltration rate, the concentration of electrolytes in the proportioned dialysate, the rate of heparin injection, the flow rate of the blood pump, and the rate of malfunction. The Kt/V and URR values at the 1st and 4th weeks of dialysis as well as the incidence of adverse effects did not differ between the two groups in cross-over in vivo tests (P > 0.05). There were no significant differences between the two groups in the error values of the ultrafiltration rate, the rate of heparin injection or the concentrations of electrolytes in the proportioned dialysate at different time points under different parameter settings. At weeks 2 and 24, with the flow rate of the blood pump set at 300 mL/min, the actual error of the SWS-4000 dialysis machine was significantly higher than that of the Fresenius 4008 dialysis machine (P  0.05). The malfunction rate was higher in the SWS-4000 group than in the Fresenius 4008 group (P Fresenius 4008 dialysis machine; however, the malfunction rate of the former is higher than that of the latter in in vitro tests. The stability and long-term accuracy of the SWS-4000 dialysis machine remain to be improved.

  14. Preliminary Development of Real Time Usage-Phase Monitoring System for CNC Machine Tools with a Case Study on CNC Machine VMC 250

    Science.gov (United States)

    Budi Harja, Herman; Prakosa, Tri; Raharno, Sri; Yuwana Martawirya, Yatna; Nurhadi, Indra; Setyo Nogroho, Alamsyah

    2018-03-01

    The production characteristic of job-shop industry at which products have wide variety but small amounts causes every machine tool will be shared to conduct production process with dynamic load. Its dynamic condition operation directly affects machine tools component reliability. Hence, determination of maintenance schedule for every component should be calculated based on actual usage of machine tools component. This paper describes study on development of monitoring system to obtaining information about each CNC machine tool component usage in real time approached by component grouping based on its operation phase. A special device has been developed for monitoring machine tool component usage by utilizing usage phase activity data taken from certain electronics components within CNC machine. The components are adaptor, servo driver and spindle driver, as well as some additional components such as microcontroller and relays. The obtained data are utilized for detecting machine utilization phases such as power on state, machine ready state or spindle running state. Experimental result have shown that the developed CNC machine tool monitoring system is capable of obtaining phase information of machine tool usage as well as its duration and displays the information at the user interface application.

  15. Experimental works in plasma developed in INPE (Brazil). 1. Double plasma machine for longitudinal wave study. 2. Plasma centrifuge

    International Nuclear Information System (INIS)

    Ferreira, J.L.; Ludwig, G.O.; Del Bosco, E.

    1982-01-01

    This work describes some experiments done at the Plasma Physics Laboratory at INPE. In the first part, the double plasma machine used for the study of ion acoustic wave propagation is described, and the results obtained so far are shown. The second part consists in the description of a plasma centrifuge project. It contains some basic parameters of our apparatus used for isotope separation, throuth electromagtnetic rotation of the plasma. (Author) [pt

  16. Study of a Variable Mass Atwood's Machine Using a Smartphone

    Science.gov (United States)

    Lopez, Dany; Caprile, Isidora; Corvacho, Fernando; Reyes, Orfa

    2018-01-01

    The Atwood machine was invented in 1784 by George Atwood and this system has been widely studied both theoretically and experimentally over the years. Nowadays, it is commonplace that many experimental physics courses include both Atwood's machine and variable mass to introduce more complex concepts in physics. To study the dynamics of the masses…

  17. Impact of the HEALTHY Study on Vending Machine Offerings in Middle Schools

    Science.gov (United States)

    Hartstein, Jill; Cullen, Karen W.; Virus, Amy; El Ghormli, Laure; Volpe, Stella L.; Staten, Myrlene A.; Bridgman, Jessica C.; Stadler, Diane D.; Gillis, Bonnie; McCormick, Sarah B.; Mobley, Connie C.

    2011-01-01

    Purpose/Objectives: The purpose of this study is to report the impact of the three-year middle school-based HEALTHY study on intervention school vending machine offerings. There were two goals for the vending machines: serve only dessert/snack foods with 200 kilocalories or less per single serving package, and eliminate 100% fruit juice and…

  18. Impact of the HEALTHY study on vending machine offerings in middle schools

    Science.gov (United States)

    The purpose of this study is to report the impact of the three-year middle school-based HEALTHY study on intervention school vending machine offerings. There were two goals for the vending machines: serve only dessert/snack foods with 200 kilocalories or less per single serving package, and eliminat...

  19. SU-G-TeP4-09: Development of a Plan Data Aggregator for Time Efficient Physics Second-Checks of Machine Parameters for External Beam Treatment Plans

    Energy Technology Data Exchange (ETDEWEB)

    Belley, M; Schmidt, M; Knutson, N [Rhode Island Hospital, Providence RI (United States); University of Rhode Island, Kingston, RI (United States); Price, M [Rhode Island Hospital, Providence RI (United States); University of Rhode Island, Kingston, RI (United States); Alpert Medical School of Brown University, Providence, RI (United States)

    2016-06-15

    Purpose: Physics second-checks for external beam radiation therapy are performed, in-part, to verify that the machine parameters in the Record-and-Verify (R&V) system that will ultimately be sent to the LINAC exactly match the values initially calculated by the Treatment Planning System (TPS). While performing the second-check, a large portion of the physicists’ time is spent navigating and arranging display windows to locate and compare the relevant numerical values (MLC position, collimator rotation, field size, MU, etc.). Here, we describe the development of a software tool that guides the physicist by aggregating and succinctly displaying machine parameter data relevant to the physics second-check process. Methods: A data retrieval software tool was developed using Python to aggregate data and generate a list of machine parameters that are commonly verified during the physics second-check process. This software tool imported values from (i) the TPS RT Plan DICOM file and (ii) the MOSAIQ (R&V) Structured Query Language (SQL) database. The machine parameters aggregated for this study included: MLC positions, X&Y jaw positions, collimator rotation, gantry rotation, MU, dose rate, wedges and accessories, cumulative dose, energy, machine name, couch angle, and more. Results: A GUI interface was developed to generate a side-by-side display of the aggregated machine parameter values for each field, and presented to the physicist for direct visual comparison. This software tool was tested for 3D conformal, static IMRT, sliding window IMRT, and VMAT treatment plans. Conclusion: This software tool facilitated the data collection process needed in order for the physicist to conduct a second-check, thus yielding an optimized second-check workflow that was both more user friendly and time-efficient. Utilizing this software tool, the physicist was able to spend less time searching through the TPS PDF plan document and the R&V system and focus the second-check efforts on

  20. Parameters for Fabricating Nano-Au Colloids through the Electric Spark Discharge Method with Micro-Electrical Discharge Machining.

    Science.gov (United States)

    Tseng, Kuo-Hsiung; Chung, Meng-Yun; Chang, Chaur-Yang

    2017-06-02

    In this study, the Electric Spark Discharge Method (ESDM) was employed with micro-electrical discharge machining (m-EDM) to create an electric arc that melted two electrodes in deionized water (DW) and fabricated nano-Au colloids through pulse discharges with a controlled on-off duration (T ON -T OFF ) and a total fabrication time of 1 min. A total of six on-off settings were tested under normal experimental conditions and without the addition of any chemical substances. Ultraviolet-visible spectroscopy (UV-Vis), Zetasizer Nano measurements, and scanning electron microscopy-energy dispersive X-ray (SEM-EDX) analyses suggested that the nano-Au colloid fabricated at 10-10 µs (10 µs on, 10 µs off) had higher concentration and suspension stability than products made at other T ON -T OFF settings. The surface plasmon resonance (SPR) of the colloid was 549 nm on the first day of fabrication and stabilized at 532 nm on the third day. As the T ON -T OFF period increased, the absorbance (i.e., concentration) of all nano-Au colloids decreased. Absorbance was highest at 10-10 µs. The SPR peaks stabilized at 532 nm across all T ON -T OFF periods. The Zeta potential at 10-10 µs was -36.6 mV, indicating that no nano-Au agglomeration occurred and that the particles had high suspension stability.

  1. Comparative study of Moore and Mealy machine models adaptation ...

    African Journals Online (AJOL)

    Information and Communications Technology has influenced the need for automated machines that can carry out important production procedures and, automata models are among the computational models used in design and construction of industrial processes. The production process of the popular African Black Soap ...

  2. Machine Shop Practice. Trade and Industrial Education Course of Study.

    Science.gov (United States)

    Emerly, Robert J.; And Others

    Designed for secondary school students who are interested in becoming machinists, this beginning course guide in machine shop practice is organized into the following sections: (1) Introduction, (2) instructional plan, (3) educational philosophy, (4) specific course objectives, (5) course outline, (6) job sheets, and (7) operation sheets. The…

  3. Study of the ion sputter-machining, 1

    International Nuclear Information System (INIS)

    Miyamoto, Iwao; Taniguchi, Norio

    1979-01-01

    A lattice disordering of the surface of single crystal silicon due to ion bombardment of Ar + was investigated by the high energy electron diffraction method, with the incident angle of 1.7 0 and 2.8 0 . By this measuring system, the degree of disorders of the sputter-machined surface layer of Si single crystal in the depth of 50 A and 30 A has been determined, under the working conditions of the ion energy ranging from 0.2 keV to 1.5 keV and the incident angle of ion ranging from 0 0 to 75 0 . Moreover, the recovery of lattice disorder of sputter-machined surface layer of Si single crystal by means of the isochronal thermal annealing has been also confirmed by the same method. From the above experiments, the following conclusions are obtained. (1) The layers of sputter-machined surface of Si single crystal workpiece are highly disordered like amorphous, under the working conditions of ion energy ranging from 0.2 keV to 1.5 keV for the vertical ion incident angle. (2) Under the working conditions of ion incident angle larger than 60 0 , using the ion beam with a lower energy under 300 eV, the surface of the workpiece is not disordered. Therefore, a sputter-machined surface of Si single crystal with highly ordered structure can be obtained under this working condition. (3) The recovery of disorder of sputter-machined surface is completed by the heat-treatment of workpiece under isochronal annealing for 1 hour at 800 0 C. However, it is not clear whether this recovery of lattice point or the dispersion of interstitially located argon atoms from the surface to the outside. (author)

  4. Parametric study of an absorption refrigeration machine using advanced exergy analysis

    International Nuclear Information System (INIS)

    Gong, Sunyoung; Goni Boulama, Kiari

    2014-01-01

    An advanced exergy analysis of a water–lithium bromide absorption refrigeration machine was conducted. For each component of the machine, the proposed analysis quantified the irreversibility that can be avoided and the irreversibility that is unavoidable. It also identified the irreversibility originating from inefficiencies within the component and the irreversibility that does not originate from the operation of the considered component. It was observed that the desorber and absorber concentrated most of the exergy destruction. Furthermore, the exergy destruction at these components was found to be dominantly endogenous and unavoidable. A parametrical study has been presented discussing the sensitivity of the different performance indicators to the temperature at which the heat source is available, the temperature of the refrigerated environment, and the temperature of the cooling medium used at the condenser and absorber. It was observed that the endogenous avoidable exergy destruction at the desorber, i.e. the portion of the desorber irreversibility that could be avoided by improving the design and operation of the desorber, decreased when the heat source or the temperature at which the cooling effect was generated increased, and it decreased when the heat sink temperature increased. The endogenous avoidable exergy destruction at the absorber displayed the same variations, though it was observed to be less affected by the heat source temperature. Contrary to the aforementioned two components, the exergy destruction at the evaporator and condenser were dominantly endogenous and avoidable, with little sensitivity to the cycle operating parameters. - Highlights: • Endogenous, exogenous, avoidable and unavoidable irreversibilities were calculated for a water–LiBr absorption machine. • Overall, desorber and absorber concentrated most of the exergy destruction of the cycle. • The exergy destruction was mainly endogenous and unavoidable for the desorber and

  5. Study of the rheological properties and the finishing behavior of abrasive gels in abrasive flow machining

    Energy Technology Data Exchange (ETDEWEB)

    Wang, A. C.; Liu, C. H.; Liang, K. Z.; Pai, S. H. [Ching Yun University, Taipei (China)

    2007-10-15

    Abrasive flow machining (AFM) is an effective method to finish the smooth surface in the complex holes. Abrasive media are key elements which dominate the polished results in AFM. But it is hard to develop the machining model of these abrasive gels because of its complicated mechanism. In this research, a non-Newtonian flow is used to set up the abrasive mechanism of the abrasive media in AFM. Power law is a main equation of the non-Newtonian flow to describe the motion of the abrasive media. Viscosities vs. shear rates of different abrasive gels are used to establish the power law in CFD-ACE{sup +} software first. And the working parameters of AFM were applied as input to study the properties of the abrasive gels in AFM. Finally, the relationships between the simulations and the experiments were found. And the abrasive mechanism of the abrasive gels was set up in AFM. The simulated results show that the abrasive gel with high viscosity can entirely deform in the complex hole than the abrasive gel with low viscosity. And the abrasive gel with high viscosity generates a larger shear force than the abrasive gel with low viscosity in the same area. Moreover, the strain rate is seriously changed when the abrasive gel cross over the narrow cross-section of the complex hole. It also means that abrasive gel will produce large finish force in that area. And these results indeed consist with the experiments in AFM.

  6. Four Machine Learning Algorithms for Biometrics Fusion: A Comparative Study

    Directory of Open Access Journals (Sweden)

    I. G. Damousis

    2012-01-01

    Full Text Available We examine the efficiency of four machine learning algorithms for the fusion of several biometrics modalities to create a multimodal biometrics security system. The algorithms examined are Gaussian Mixture Models (GMMs, Artificial Neural Networks (ANNs, Fuzzy Expert Systems (FESs, and Support Vector Machines (SVMs. The fusion of biometrics leads to security systems that exhibit higher recognition rates and lower false alarms compared to unimodal biometric security systems. Supervised learning was carried out using a number of patterns from a well-known benchmark biometrics database, and the validation/testing took place with patterns from the same database which were not included in the training dataset. The comparison of the algorithms reveals that the biometrics fusion system is superior to the original unimodal systems and also other fusion schemes found in the literature.

  7. Study of the AC machines winding having fractional q

    Science.gov (United States)

    Bespalov, V. Y.; Sidorov, A. O.

    2018-02-01

    The winding schemes with a fractional numbers of slots per pole and phase q have been known and used for a long time. However, in the literature on the low-noise machines design there are not recommended to use. Nevertheless, fractional q windings have been realized in many applications of special AC electrical machines, allowing to improve their performance, including vibroacoustic one. This paper deals with harmonic analysis of windings having integer and fractional q in permanent magnet synchronous motors, a comparison of their characteristics is performed, frequencies of subharmonics are revealed. Optimal winding pitch design is found giving reduce the amplitudes of subharmonics. Distribution factors for subharmonics, fractional and high-order harmonics are calculated, results analysis is represented, allowing for giving recommendations how to calculate distribution factors for different harmonics when q is fractional.

  8. Studying depression using imaging and machine learning methods

    OpenAIRE

    Patel, Meenal J.; Khalaf, Alexander; Aizenstein, Howard J.

    2015-01-01

    Depression is a complex clinical entity that can pose challenges for clinicians regarding both accurate diagnosis and effective timely treatment. These challenges have prompted the development of multiple machine learning methods to help improve the management of this disease. These methods utilize anatomical and physiological data acquired from neuroimaging to create models that can identify depressed patients vs. non-depressed patients and predict treatment outcomes. This article (1) presen...

  9. An experimental study on a superconducting generator with dual machine shield system

    International Nuclear Information System (INIS)

    Ishigohka, T.; Ninomiya, A.; Okada, T.; Nitta, T.; Shintani, T.; Mukai, E.

    1988-01-01

    The authors have studied the optimal machine shield system through experiments on a 20kVa superconducting generator. The first experiment is carried out on a fully iron-less aluminum-shield machine which has only an aluminum eddy current machine shield in the stator. The second experiment is carried out on a generator with a dual-shield system which has both an aluminum eddy current shield and an iron magnetic shield. From the first one, the authors have got an experimental result that the aluminum-shield machine exhibits so large eddy current loss in the shield that it would be difficult to operate the machine continuously. On the other hand, the second experiment shows that the dual-shield machine exhibits much smaller loss in the shielding system, and that it has higher output power than the aluminum-shield machine. From these experiments, it becomes clear that insertion of a very thin iron shield between the armature winding and the eddy current shield can improve the machine performance eminently without large weight increase even if the iron shield were saturated

  10. Influence of Thermal Parameters, Microstructure, and Morphology of Si on Machinability of an Al–7.0 wt.% Si Alloy Directionally Solidified

    Directory of Open Access Journals (Sweden)

    Cássio A. P. Silva

    2018-01-01

    Full Text Available This study aims to correlate the influence of thermal and microstructural parameters such as growth rate and cooling rate (VL and TR and secondary dendrite spacing (λ2, respectively, in the machining cutting temperature and tool wear on the necking process of the Al–7 wt.% Si alloy solidified in a horizontal directional device using a high-speed steel with a tungsten tool. The dependence of λ2 on VL and TR and dependence of the maximum cutting temperature and maximum flank wear on λ2 were determined by power experimental laws given by λ2 = constant (VL and TRn and TMAX, VBMAX = constant (λ2n, respectively. The maximum cutting temperature increased with increasing of λ2. The opposite occurred with the maximum flank wear. The role of Si alloying element on the aforementioned results has also been analyzed. A morphological change of Si along the solidified ingot length has been observed, that is, the morphology of Si in the eutectic matrix has indicated a transition from particles to fibers along the casting together with an increase of the particle diameters with the position from the metal/mold interface.

  11. Fuel cycle parameters for strategy studies

    International Nuclear Information System (INIS)

    Archinoff, G.H.

    1979-05-01

    This report summarizes seven fuel cycle parameters (efficiency, specific power, burnup, equilibrium net fissile feed, equilibrium net fissile surplus, first charge fissile content, and whether or not fuel reprocessing is required) to be used in long-term strategy analyses of fuel cycles based on natural UO 2 , low enriched uranium, mixed oxides, plutonium topped thorium, uranium topped thorium, and the fast breeder oxide cycle. (LL)

  12. Machinability of nickel based alloys using electrical discharge machining process

    Science.gov (United States)

    Khan, M. Adam; Gokul, A. K.; Bharani Dharan, M. P.; Jeevakarthikeyan, R. V. S.; Uthayakumar, M.; Thirumalai Kumaran, S.; Duraiselvam, M.

    2018-04-01

    The high temperature materials such as nickel based alloys and austenitic steel are frequently used for manufacturing critical aero engine turbine components. Literature on conventional and unconventional machining of steel materials is abundant over the past three decades. However the machining studies on superalloy is still a challenging task due to its inherent property and quality. Thus this material is difficult to be cut in conventional processes. Study on unconventional machining process for nickel alloys is focused in this proposed research. Inconel718 and Monel 400 are the two different candidate materials used for electrical discharge machining (EDM) process. Investigation is to prepare a blind hole using copper electrode of 6mm diameter. Electrical parameters are varied to produce plasma spark for diffusion process and machining time is made constant to calculate the experimental results of both the material. Influence of process parameters on tool wear mechanism and material removal are considered from the proposed experimental design. While machining the tool has prone to discharge more materials due to production of high energy plasma spark and eddy current effect. The surface morphology of the machined surface were observed with high resolution FE SEM. Fused electrode found to be a spherical structure over the machined surface as clumps. Surface roughness were also measured with surface profile using profilometer. It is confirmed that there is no deviation and precise roundness of drilling is maintained.

  13. Monte Carlo simulation based study of a proposed multileaf collimator for a telecobalt machine

    International Nuclear Information System (INIS)

    Sahani, G.; Dash Sharma, P. K.; Hussain, S. A.; Dutt Sharma, Sunil; Sharma, D. N.

    2013-01-01

    Purpose: The objective of the present work was to propose a design of a secondary multileaf collimator (MLC) for a telecobalt machine and optimize its design features through Monte Carlo simulation. Methods: The proposed MLC design consists of 72 leaves (36 leaf pairs) with additional jaws perpendicular to leaf motion having the capability of shaping a maximum square field size of 35 × 35 cm 2 . The projected widths at isocenter of each of the central 34 leaf pairs and 2 peripheral leaf pairs are 10 and 5 mm, respectively. The ends of the leaves and the x-jaws were optimized to obtain acceptable values of dosimetric and leakage parameters. Monte Carlo N-Particle code was used for generating beam profiles and depth dose curves and estimating the leakage radiation through the MLC. A water phantom of dimension 50 × 50 × 40 cm 3 with an array of voxels (4 × 0.3 × 0.6 cm 3 = 0.72 cm 3 ) was used for the study of dosimetric and leakage characteristics of the MLC. Output files generated for beam profiles were exported to the PTW radiation field analyzer software through locally developed software for analysis of beam profiles in order to evaluate radiation field width, beam flatness, symmetry, and beam penumbra. Results: The optimized version of the MLC can define radiation fields of up to 35 × 35 cm 2 within the prescribed tolerance values of 2 mm. The flatness and symmetry were found to be well within the acceptable tolerance value of 3%. The penumbra for a 10 × 10 cm 2 field size is 10.7 mm which is less than the generally acceptable value of 12 mm for a telecobalt machine. The maximum and average radiation leakage through the MLC were found to be 0.74% and 0.41% which are well below the International Electrotechnical Commission recommended tolerance values of 2% and 0.75%, respectively. The maximum leakage through the leaf ends in closed condition was observed to be 8.6% which is less than the values reported for other MLCs designed for medical linear

  14. Main studies results for introduction of EB machine to Vietnam and for its application

    International Nuclear Information System (INIS)

    Tran, Khac An; Nguyen, Quoc Hien; Le, Hai

    2004-01-01

    Upon the national program on utilization of EB machine for research and development purposes and the FNCA project on application of electron accelerator, as a counterpart the Research and Development Center for Radiation Technology (VINAGAMMA) is preparing technical, manpower and financial conditions for introduction of an EB machine for R and D purposes. The paper offers main studied results in the field of Radiation Processing aimed at putting applications of EB technology into Vietnam and studies on selection of EB machine for R and D purposes in Vietnam. (author)

  15. A Fast and On-Machine Measuring System Using the Laser Displacement Sensor for the Contour Parameters of the Drill Pipe Thread

    Directory of Open Access Journals (Sweden)

    Zhixu Dong

    2018-04-01

    Full Text Available The inconvenient loading and unloading of a long and heavy drill pipe gives rise to the difficulty in measuring the contour parameters of its threads at both ends. To solve this problem, in this paper we take the SCK230 drill pipe thread-repairing machine tool as a carrier to design and achieve a fast and on-machine measuring system based on a laser probe. This system drives a laser displacement sensor to acquire the contour data of a certain axial section of the thread by using the servo function of a CNC machine tool. To correct the sensor’s measurement errors caused by the measuring point inclination angle, an inclination error model is built to compensate data in real time. To better suppress random error interference and ensure real contour information, a new wavelet threshold function is proposed to process data through the wavelet threshold denoising. Discrete data after denoising is segmented according to the geometrical characteristics of the drill pipe thread, and the regression model of the contour data in each section is fitted by using the method of weighted total least squares (WTLS. Then, the thread parameters are calculated in real time to judge the processing quality. Inclination error experiments show that the proposed compensation model is accurate and effective, and it can improve the data acquisition accuracy of a sensor. Simulation results indicate that the improved threshold function is of better continuity and self-adaptability, which makes sure that denoising effects are guaranteed, and, meanwhile, the complete elimination of real data distorted in random errors is avoided. Additionally, NC50 thread-testing experiments show that the proposed on-machine measuring system can complete the measurement of a 25 mm thread in 7.8 s, with a measurement accuracy of ±8 μm and repeatability limit ≤ 4 μm (high repeatability, and hence the accuracy and efficiency of measurement are both improved.

  16. A Study of Synchronous Machine Model Implementations in Matlab/Simulink Simulations for New and Renewable Energy Systems

    DEFF Research Database (Denmark)

    Chen, Zhe; Blaabjerg, Frede; Iov, Florin

    2005-01-01

    A direct phase model of synchronous machines implemented in MA TLAB/SIMULINK is presented. The effects of the machine saturation have been included. Simulation studies are performed under various conditions. It has been demonstrated that the MATLAB/SIMULINK is an effective tool to study the compl...... synchronous machine and the implemented model could be used for studies of various applications of synchronous machines including in renewable and DG generation systems....

  17. RAM analysis of earth pressure balance tunnel boring machines: A case study

    Directory of Open Access Journals (Sweden)

    Hasel Amini Khoshalan

    2015-12-01

    Full Text Available Earth pressure balance tunnel boring machines (EPB-TBMs are favorably applied in urban tunneling projects. Despite their numerous advantages, considerable delays and high maintenance cost are the main disadvantages these machines suffer from. Reliability, availability, and maintainability (RAM analysis is a practical technique that uses failure and repair dataset obtained over a reasonable time for dealing with proper machine operation, maintenance scheduling, cost control, and improving the availability and performance of such machines. In the present study, a database of failures and repairs of an EBP-TBM was collected in line 1 of Tabriz subway project over a 26-month interval of machine operation. In order to model the reliability of the TBM, this machine was divided into five distinct subsystems including mechanical, electrical, hydraulic, pneumatic, and water systems in a series configuration. According to trend and serial correlation tests, the renewal processes were applied, for analysis of all subsystems. After calculating the reliability and maintainability functions for all subsystems, it was revealed that the mechanical subsystem with the highest failure frequency has the lowest reliability and maintainability. Similarly, estimating the availability of all subsystems indicated that the mechanical subsystem has a relatively low availability level of 52.6%, while other subsystems have acceptable availability level of 97%. Finally, the overall availability of studied machine was calculated as 48.3%.

  18. The impact of machine learning techniques in the study of bipolar disorder: A systematic review.

    Science.gov (United States)

    Librenza-Garcia, Diego; Kotzian, Bruno Jaskulski; Yang, Jessica; Mwangi, Benson; Cao, Bo; Pereira Lima, Luiza Nunes; Bermudez, Mariane Bagatin; Boeira, Manuela Vianna; Kapczinski, Flávio; Passos, Ives Cavalcante

    2017-09-01

    Machine learning techniques provide new methods to predict diagnosis and clinical outcomes at an individual level. We aim to review the existing literature on the use of machine learning techniques in the assessment of subjects with bipolar disorder. We systematically searched PubMed, Embase and Web of Science for articles published in any language up to January 2017. We found 757 abstracts and included 51 studies in our review. Most of the included studies used multiple levels of biological data to distinguish the diagnosis of bipolar disorder from other psychiatric disorders or healthy controls. We also found studies that assessed the prediction of clinical outcomes and studies using unsupervised machine learning to build more consistent clinical phenotypes of bipolar disorder. We concluded that given the clinical heterogeneity of samples of patients with BD, machine learning techniques may provide clinicians and researchers with important insights in fields such as diagnosis, personalized treatment and prognosis orientation. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. Improving Machining Accuracy of CNC Machines with Innovative Design Methods

    Science.gov (United States)

    Yemelyanov, N. V.; Yemelyanova, I. V.; Zubenko, V. L.

    2018-03-01

    The article considers achieving the machining accuracy of CNC machines by applying innovative methods in modelling and design of machining systems, drives and machine processes. The topological method of analysis involves visualizing the system as matrices of block graphs with a varying degree of detail between the upper and lower hierarchy levels. This approach combines the advantages of graph theory and the efficiency of decomposition methods, it also has visual clarity, which is inherent in both topological models and structural matrices, as well as the resiliency of linear algebra as part of the matrix-based research. The focus of the study is on the design of automated machine workstations, systems, machines and units, which can be broken into interrelated parts and presented as algebraic, topological and set-theoretical models. Every model can be transformed into a model of another type, and, as a result, can be interpreted as a system of linear and non-linear equations which solutions determine the system parameters. This paper analyses the dynamic parameters of the 1716PF4 machine at the stages of design and exploitation. Having researched the impact of the system dynamics on the component quality, the authors have developed a range of practical recommendations which have enabled one to reduce considerably the amplitude of relative motion, exclude some resonance zones within the spindle speed range of 0...6000 min-1 and improve machining accuracy.

  20. An investigative study towards constructing anthropocentric Man-Machine System design evaluation methodology

    International Nuclear Information System (INIS)

    Yoshikawa, H.; Gofuku, A.; Itoh, T.; Sasaki, K.

    1992-01-01

    A methodological investigation has been conducted for evaluating the reliability of man-machine interaction in the total Man-Machine System (MMS) from the view-point of safety maintenance for emergent situations of nuclear power plant. Basic considerations in our study are: (i) what are the MMS design data to be evaluated, (ii) how are those MMS design data should be treated, and (iii) how the introduction effects of various operator support tools can be evaluated. The methods of both qualitative and quantitative MMS design evaluation are summarized in this paper, with the system architecture based on man-machine interaction simulation and the related cognitive human error factor analysis. (author)

  1. Numerical Study of Compact Plate-Fin Heat Exchanger for Rotary-Vane Gas Refrigeration Machine

    Directory of Open Access Journals (Sweden)

    V. V. Trandafilov

    2017-10-01

    Full Text Available Plate-fin heat exchangers are widely used in refrigeration technique. They are popular because of their compactness and excellent heat transfer performance. Here we present a numerical model for the development, research and optimization of a plate-fin heat exchanger for a rotary-vane gas refrigeration machine. The method of analysis by graphic method of plate - fin heat exchanger is proposed. The model describes the effects of secondary parameters such as axial thermal conductivity through a metal matrix of the heat exchanger. The influence of geometric parameters and heat transfer coefficient is studied. Graphs of dependences of length, efficiency of a fin and pressure drop in a heat exchanger on the thickness of the fin and the number of fins per meter are obtained. To analyze the results of numerical simulation, the heat exchanger was designed in the Aspen HYSYS program. The simulation results show that the total deviation from the proposed numerical model is not more than 15%. 

  2. Effectiveness of Hamstring Knee Rehabilitation Exercise Performed in Training Machine vs. Elastic Resistance Electromyography Evaluation Study

    DEFF Research Database (Denmark)

    Jakobsen, M. D.; Sundstrup, E.; Andersen, C. H.

    2014-01-01

    Objective The aim of this study was to evaluate muscle activity during hamstring rehabilitation exercises performed in training machine compared with elastic resistance. Design Six women and 13 men aged 28-67 yrs participated in a crossover study. Electromyographic (EMG) activity was recorded...... inclinometers. Results Training machines and elastic resistance showed similar high levels of muscle activity (biceps femoris and semitendinosus peak normalized EMG >80%). EMG during the concentric phase was higher than during the eccentric phase regardless of exercise and muscle. However, compared with machine.......001) during hamstring curl performed with elastic resistance (7.58 +/- 0.08) compared with hamstring curl performed in a machine (5.92 +/- 0.03). Conclusions Hamstring rehabilitation exercise performed with elastic resistance induces similar peak hamstring muscle activity but slightly lower EMG values at more...

  3. Study and analysis of drift chamber parameters

    International Nuclear Information System (INIS)

    Martinez Laso, L.

    1988-01-01

    The present work deals mainly with drift chambers. In the first chapter a summary of drift chamber properties is presented. The information has been collected from the extensive bibliography available in this field. A very simple calculation procedure of drift chamber parameters has been developed and is presented in detail in the second chapter. Some prototypes have been made following two geometries (multidrift chamber and Z-chambers). Several installations have been used for test and calibration of these prototypes. A complete description of these installations is given in the third chapter. Cosmic rays, beta particles from a Ru106 radiactive source and a test beam in the WA (West Area) of SPS at CERN have been used for experimental purposes. The analysis and the results are described for the different setups. The experimental measurements have been used to produce a complete cell parametrization (position as function of drift time) and to obtain spatial resolution values (in the range of 200-250 um). Experimental results are in good agreement with numerical calculations. (Author)

  4. Study on effect of tool electrodes on surface finish during electrical discharge machining of Nitinol

    Science.gov (United States)

    Sahu, Anshuman Kumar; Chatterjee, Suman; Nayak, Praveen Kumar; Sankar Mahapatra, Siba

    2018-03-01

    Electrical discharge machining (EDM) is a non-traditional machining process which is widely used in machining of difficult-to-machine materials. EDM process can produce complex and intrinsic shaped component made of difficult-to-machine materials, largely applied in aerospace, biomedical, die and mold making industries. To meet the required applications, the EDMed components need to possess high accuracy and excellent surface finish. In this work, EDM process is performed using Nitinol as work piece material and AlSiMg prepared by selective laser sintering (SLS) as tool electrode along with conventional copper and graphite electrodes. The SLS is a rapid prototyping (RP) method to produce complex metallic parts by additive manufacturing (AM) process. Experiments have been carried out varying different process parameters like open circuit voltage (V), discharge current (Ip), duty cycle (τ), pulse-on-time (Ton) and tool material. The surface roughness parameter like average roughness (Ra), maximum height of the profile (Rt) and average height of the profile (Rz) are measured using surface roughness measuring instrument (Talysurf). To reduce the number of experiments, design of experiment (DOE) approach like Taguchi’s L27 orthogonal array has been chosen. The surface properties of the EDM specimen are optimized by desirability function approach and the best parametric setting is reported for the EDM process. Type of tool happens to be the most significant parameter followed by interaction of tool type and duty cycle, duty cycle, discharge current and voltage. Better surface finish of EDMed specimen can be obtained with low value of voltage (V), discharge current (Ip), duty cycle (τ) and pulse on time (Ton) along with the use of AlSiMg RP electrode.

  5. Specimen Machining for the Study of the Effect of Swelling on CGR in PWR Environment.

    Energy Technology Data Exchange (ETDEWEB)

    Teysseyre, Sebastien Paul [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2015-06-01

    This report describes the preparation of ten specimens to be used for the study of the effect of swelling on the propagation of irradiation assisted stress corrosion cracking cracks. Four compact tension specimens, four microscopy plates and two tensile specimens were machined from a AISI 304 material that was irradiated up to 33 dpa. The specimens had been machined such as to represent the behavior of materials with 3.7%swelling and <2% swelling.

  6. Atomic structure of machined semiconducting chips: An x-ray absorption spectroscopy study

    Energy Technology Data Exchange (ETDEWEB)

    Paesler, M.; Sayers, D.

    1988-12-01

    X-ray absorption spectroscopy (XAS) has been used to examine the atomic structure of chips of germanium that were produced by single point diamond machining. It is demonstrated that although the local (nearest neighbor) atomic structure is experimentally quite similar to that of single crystal specimens information from more distant atoms indicates the presence of considerable stress. An outline of the technique is given and the strength of XAS in studying the machining process is demonstrated.

  7. Study of the Effect of Material Machinability on Quality of Surface Created by Abrasive Water Jet

    Czech Academy of Sciences Publication Activity Database

    Klichová, Dagmar; Klich, Jiří

    2016-01-01

    Roč. 149, č. 149 (2016), s. 177-182 E-ISSN 1877-7058. [International Conference on Manufacturing Engineering and Materials, ICMEM 2016. Nový Smokovec, 06.06.2016-10.06.2016] R&D Projects: GA MŠk(CZ) LO1406 Institutional support: RVO:68145535 Keywords : machinability * surface roughness * abrasive water jet * study of quality * aluminium alloy * optical profilometer Subject RIV: JQ - Machines ; Tools http://www.sciencedirect.com/science/article/pii/S1877705816311614

  8. Machine performance assessment and enhancement for a hexapod machine

    Energy Technology Data Exchange (ETDEWEB)

    Mou, J.I. [Arizona State Univ., Tempe, AZ (United States); King, C. [Sandia National Labs., Livermore, CA (United States). Integrated Manufacturing Systems Center

    1998-03-19

    The focus of this study is to develop a sensor fused process modeling and control methodology to model, assess, and then enhance the performance of a hexapod machine for precision product realization. Deterministic modeling technique was used to derive models for machine performance assessment and enhancement. Sensor fusion methodology was adopted to identify the parameters of the derived models. Empirical models and computational algorithms were also derived and implemented to model, assess, and then enhance the machine performance. The developed sensor fusion algorithms can be implemented on a PC-based open architecture controller to receive information from various sensors, assess the status of the process, determine the proper action, and deliver the command to actuators for task execution. This will enhance a hexapod machine`s capability to produce workpieces within the imposed dimensional tolerances.

  9. Studies of the trapped particle and ion temperature gradient instabilities in the Columbia Linear Machine

    International Nuclear Information System (INIS)

    Mathey, O.H.

    1989-01-01

    In the first part of the work, the effects of weak Coulomb and neutral collisions on the collisionless curvature driven trapped particle mode are studied in the Columbia Linear Machine (CLM) [Phys. Rev. Lett. 57, 1729, (1986)]. Low Coulomb collisionality yields a small stabilizing correction to the magnetohydrodynamic (MHD) collisionless mode, which scales as v, using the Krook model, and ν ec 1/2 using a Lorentz pitch angle operator. In higher collisionality regimes, both models tend to yield similar scalings. In view of relative high neutral collisionality in CLM, both types of collisionality are then combined, modeling neutral collisions with the conserving Krook and Coulomb collisions with a Lorentz model. The dispersion relation is then integrated over velocity space. This combination yields results in very good accord with the available experimental data. The Ion Temperature Gradient Instability is then investigated. It is shown that anisotropy in gradient has a substantial effect on the ion temperature gradient driven mode. A gradient in the parallel temperature is needed for an instability to occur, and a gradient in the perpendicular temperature gradient further enhances the instability indirectly as long as the frequency of the mode is near ion resonance. The physical reason for this important role difference is presented. The Columbia Linear Machine is being redesigned to produce and identify the ion temperature gradient driven η i mode. Using the expected parameters, the author has developed detailed predictions of the mode characteristics in the CLM. Strong multi mode instabilities are expected. As the ion parallel and perpendicular ion temperature gradients are expected to differ significantly, we differentiate between η i parallel and ν i perpendicular and explore the physical differences between them, which leads to a scheme for stabilization of the mode

  10. Study on Dynamic Characteristics of Heavy Machine Tool-Composite Pile Foundation-Soil

    Directory of Open Access Journals (Sweden)

    CAI Li-Gang

    2014-09-01

    Full Text Available Heavy duty computer numerical control machine tools have characteristics of large self-weight, load and. The insufficiency of foundation bearing capacity leads to deformation of lathe bed, which effects machining accuracy. A combined-layer foundation model is created to describe the pile group foundation of multi-soil layer in this paper. Considering piles and soil in pile group as transversely isotropic material, equivalent constitutive relationship of composite foundation is constructed. A mathematical model is established by the introduction of boundary conditions, which is based on heavy duty computer numerical control machine tools-composite pile foundation-soil interaction system. And then, the response of different soil and pile depth is studied by a case. The model improves motion accuracy of machine tools.

  11. Feasibility Study for Installing Machine in Production Line to Avoid Particle Contamination Based on CFD Simulation

    Science.gov (United States)

    Khaokom, Adisorn; Thongsri, Jatuporn

    2017-10-01

    Ventilation system inside production line for electronic component production needs to meet the factory standard. Because it can eliminate small particles which may cause of human or machine in production as well as it can distribute the circulating air temperature uniformly. CFD is used in this research in order to study the feasibility and plan for machine layout in production line before actual installation. The simulation shows the airflow in every area inside production line. From simulation with releasing the particles from human and machine is found that this ventilation system generates airflow that makes most particles float out of the machines and no particle downs to the conveyor, it results to contamination. In addition, the simulation also shows the range of 19-26 °C air temperature that meets the factory standard. The results of this research are the parts of the data to renovate the production line to get more efficiency and proper on the production.

  12. A study of wear in refrigerating machines using thin layer activation

    International Nuclear Information System (INIS)

    Hammer, P.; Eichhorn, K.; Eifrig, C.

    1986-01-01

    Wear is studied in a ball-and-socket joint of a newly developed refrigerating machine. Using deuteron activation a 15 μm deep Co-57 layer is generated at the ring-shaped friction area in the steel socket of the joint. The measurement of the Co-57 intensity of the wear particles held back on an oil filter provides information about the wear rate of the socket during machine operation. The measurement of the Co-57 contaminations occuring in the individual parts of the machine at the end of the test gives information about the distribution of the wear particles in the machine and about the material transfer in the ball-and-socket joint. (author)

  13. A Study on the Vibration Measurement and Analysis of Rotating Machine Foundations

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Jong Rim; Jeon, Kyu Sik; Suh, Young Pyo; Cho, Chul Hwan; Kim, Sung Taeg; Lee, Myung Kyu [Korea Electric Power Research Institute, Taejon (Korea, Republic of)

    1996-12-31

    To search for the cause of vibration problem of rotating machine in the power plant, first the rotating machine is classified according to their type and each vibration characteristic is reviewed. The criteria for the evaluation of mechanical vibration effect on the structure and human being during the design of machine foundation is described below. The foundation of rotating machine is classified according to its shape and some factors are described which should be considered during dynamic modeling analysis for its correct result. Also the methods of incorporating foundation vibration into mechanical vibration analysis are reviewed. Type of vibration measurement and analysis which is used to find out the dynamic characteristic of structure is described in accordance with its signal processing and measuring method. Measurement of vibration and its analysis when there occurs real vibration troubles in power plant are compared with the results of numerical modeling as case studies. (author). 16 refs., 23 figs.

  14. The Employment Effects of High-Technology: A Case Study of Machine Vision. Research Report No. 86-19.

    Science.gov (United States)

    Chen, Kan; Stafford, Frank P.

    A case study of machine vision was conducted to identify and analyze the employment effects of high technology in general. (Machine vision is the automatic acquisition and analysis of an image to obtain desired information for use in controlling an industrial activity, such as the visual sensor system that gives eyes to a robot.) Machine vision as…

  15. Comparison of machine-learning algorithms to build a predictive model for detecting undiagnosed diabetes - ELSA-Brasil: accuracy study.

    Science.gov (United States)

    Olivera, André Rodrigues; Roesler, Valter; Iochpe, Cirano; Schmidt, Maria Inês; Vigo, Álvaro; Barreto, Sandhi Maria; Duncan, Bruce Bartholow

    2017-01-01

    Type 2 diabetes is a chronic disease associated with a wide range of serious health complications that have a major impact on overall health. The aims here were to develop and validate predictive models for detecting undiagnosed diabetes using data from the Longitudinal Study of Adult Health (ELSA-Brasil) and to compare the performance of different machine-learning algorithms in this task. Comparison of machine-learning algorithms to develop predictive models using data from ELSA-Brasil. After selecting a subset of 27 candidate variables from the literature, models were built and validated in four sequential steps: (i) parameter tuning with tenfold cross-validation, repeated three times; (ii) automatic variable selection using forward selection, a wrapper strategy with four different machine-learning algorithms and tenfold cross-validation (repeated three times), to evaluate each subset of variables; (iii) error estimation of model parameters with tenfold cross-validation, repeated ten times; and (iv) generalization testing on an independent dataset. The models were created with the following machine-learning algorithms: logistic regression, artificial neural network, naïve Bayes, K-nearest neighbor and random forest. The best models were created using artificial neural networks and logistic regression. -These achieved mean areas under the curve of, respectively, 75.24% and 74.98% in the error estimation step and 74.17% and 74.41% in the generalization testing step. Most of the predictive models produced similar results, and demonstrated the feasibility of identifying individuals with highest probability of having undiagnosed diabetes, through easily-obtained clinical data.

  16. Multi-parameter study of gammas capture

    International Nuclear Information System (INIS)

    Samama, R.; Nifenecker, H.; Carlos, P.; Delaitre, B.

    1966-06-01

    This equipment is intended for analyzing, recording, and reading simultaneous information from several 'gamma' detectors. It allows multiparameter study of γ-γ cascades emitted after thermal neutrons capture. (authors) [fr

  17. Tribological study on machine elements of HTGR components

    International Nuclear Information System (INIS)

    Nemoto, M.; Asanabe, S.; Kawaguchi, K.; Ono, S.; Oyamada, T.

    1980-01-01

    There are some tribological features peculiar to machines used in a high-temperature gas-cooled reactor (HTGR) plant. In this kind of plant, water-lubricated bearing combined with the buffer gas sealing system and/or gas-lubricated bearings are often applied in order to prevent degrading of the purity of coolant helium gas. And, it is essential for the reliability and safety design of the sliding members in the HTGR to obtain fundamental data on their friction and wear in high-temperature helium atmosphere. In this paper, the results of tests on these bearings and sliding members are introduced, which are summarized as follows: (1) Water-lubricated shrouded step thrust bearing and buffer gas sealing system were tested separately under the conditions simulated to those of circulators used in commercial plants. The results showed that each elements satisfies the requirements. (2) A hydrostatically gas-lubricated, pivoted pad journal bearing with a moat-shaped rectangular groove is found to be promising for use as a high-load bearing, which is indispensable for the development of a large-type circulator. (3) Use of ceramic coating and carbon graphite materials is effective for the prevention of adhesive wear which is apt to occur in metal-to-metal combinations. (author)

  18. Tribological study on machine elements of HTGR components

    International Nuclear Information System (INIS)

    Nemoto, Masaaki; Ono, Shigeharu; Asanabe, Sadao; Kawaguchi, Katsuyuki; Oyamada, Tetsuya.

    1981-11-01

    There are some tribological features peculiar to machines used in a high-temperature gas-cooled reactor (HTGR) plant. In this kind of plant, water-lubricated bearing combined with the buffer gas sealing system and/or gas-lubricated bearings are often applied in order to prevent degrading of the purity of coolant helium gas. And, it is essential for the reliability and safety design of the sliding members in the HTGR to obtain fundamental data on their friction and wear in high-temperature helium atmosphere. In this paper, the results of tests on these bearings and sliding members are introduced, which are summarized as follows: (1) Water-lubricated shrouded step thrust bearing and buffer gas sealing system were tested separately under the condition simulated to those of circulators used in commercial plants. The results showed that each elements satisfies the requirements. (2) A hydrostatically gas-lubricated, pivoted pad journal bearing with a moat-shaped rectangular groove is found to be promising for use as a high-load bearing, which is indispensable for the development of a large-type circulator. (3) Use of ceramic coating and carbon graphite materials is effective for the prevention of adhesive wear which is apt to occur in metal-to-metal combinations. (author)

  19. ESTIMATION OF THE SPECIFIC ENERGY OF TUNNEL BORING MACHINE USING POST-FAILURE BEHAVIOUR OF ROCK MASS.CASE STUDY: KARAJ-TEHRAN WATER CONVEYANCE TUNNEL IN IRAN

    Directory of Open Access Journals (Sweden)

    MAJID MIRAHMADI

    2017-09-01

    Full Text Available Performance prediction of tunnel boring machines (TBM is the most important factor for successful tunnel excavation projects. The specific energy (SE of TBM, defined as the amount of energy required to excavate a unit volume of rock, is one of the critical parameters used for performance prediction of these machines. Estimation of SE is very useful to design the drilling project because it is a function of many parameters such as rock mass behaviour, machine properties and project parameters. Several methods are used to estimate this parameter, such as experimental, empirical and numerical. The aim of this study is to estimate the SE considering the postfailure behaviour of rock mass. For this reason, based on the actual data from Karaj-Tehran water conveyance tunnel, a new empirical method is proposed to estimate the SE using the drop-to-deformation modulus ratio (λ. Based on the statistical analysis, the relation between the SE and λ is estimated. It is clear that the amplitude of λ, is high and to increase the correlation between mentioned parameters, the classification of data is performed. All data is classified in three classes as very weak (GSI75. Also a statistical analysis is performed to estimate the SE using the mentioned parameter (λ in any class. The result shows that there is a direct relation between both parameters and the best correlation is achieved. So, the best equations are proposed to estimate SE using λ, considering the post failure behaviour of rock mass.

  20. Selection of Levels of Dressing Process Parameters by Using TOPSIS Technique for Surface Roughness of En-31 Work piece in CNC Cylindrical Grinding Machine

    Science.gov (United States)

    Patil, Sanjay S.; Bhalerao, Yogesh J.

    2017-02-01

    Grinding is metal cutting process used for mainly finishing the automobile components. The grinding wheel performance becomes dull by using it most of times. So it should be reshaping for consistent performance. It is necessary to remove dull grains of grinding wheel which is known as dressing process. The surface finish produced on the work piece is dependent on the dressing parameters in sub-sequent grinding operation. Multi-point diamond dresser has four important parameters such as the dressing cross feed rate, dressing depth of cut, width of the diamond dresser and drag angle of the dresser. The range of cross feed rate level is from 80-100 mm/min, depth of cut varies from 10 - 30 micron, width of diamond dresser is from 0.8 - 1.10mm and drag angle is from 40o - 500, The relative closeness to ideal levels of dressing parameters are found for surface finish produced on the En-31 work piece during sub-sequent grinding operation by using Technique of Order Preference by Similarity to Ideal Solution (TOPSIS).In the present work, closeness to ideal solution i.e. levels of dressing parameters are found for Computer Numerical Control (CNC) cylindrical angular grinding machine. After the TOPSIS technique, it is found that the value of Level I is 0.9738 which gives better surface finish on the En-31 work piece in sub-sequent grinding operation which helps the user to select the correct levels (combinations) of dressing parameters.

  1. Differences in liver stiffness values obtained with new ultrasound elastography machines and Fibroscan: A comparative study.

    Science.gov (United States)

    Piscaglia, Fabio; Salvatore, Veronica; Mulazzani, Lorenzo; Cantisani, Vito; Colecchia, Antonio; Di Donato, Roberto; Felicani, Cristina; Ferrarini, Alessia; Gamal, Nesrine; Grasso, Valentina; Marasco, Giovanni; Mazzotta, Elena; Ravaioli, Federico; Ruggieri, Giacomo; Serio, Ilaria; Sitouok Nkamgho, Joules Fabrice; Serra, Carla; Festi, Davide; Schiavone, Cosima; Bolondi, Luigi

    2017-07-01

    Whether Fibroscan thresholds can be immediately adopted for none, some or all other shear wave elastography techniques has not been tested. The aim of the present study was to test the concordance of the findings obtained from 7 of the most recent ultrasound elastography machines with respect to Fibroscan. Sixteen hepatitis C virus-related patients with fibrosis ≥2 and having reliable results at Fibroscan were investigated in two intercostal spaces using 7 different elastography machines. Coefficients of both precision (an index of data dispersion) and accuracy (an index of bias correction factors expressing different magnitudes of changes in comparison to the reference) were calculated. Median stiffness values differed among the different machines as did coefficients of both precision (range 0.54-0.72) and accuracy (range 0.28-0.87). When the average of the measurements of two intercostal spaces was considered, coefficients of precision significantly increased with all machines (range 0.72-0.90) whereas of accuracy improved more scatteredly and by a smaller degree (range 0.40-0.99). The present results showed only moderate concordance of the majority of elastography machines with the Fibroscan results, preventing the possibility of the immediate universal adoption of Fibroscan thresholds for defining liver fibrosis staging for all new machines. Copyright © 2017 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.

  2. Study of photodissociation parameters of carboxyhemoglobin

    International Nuclear Information System (INIS)

    Kuz'min, V V; Salmin, V V; Provorov, A S; Salmina, A B

    2008-01-01

    The general properties of photodissociation of carboxyhemoglobin (HbCO) in buffer solutions of whole human blood are studied by the flash photolysis method on a setup with intersecting beams. It is shown that the efficiency of photoinduced dissociation of the HbCO complex virtually linearly depends on the photolytic irradiation intensity for the average power density not exceeding 45 mW cm -2 . The general dissociation of the HbCO complex in native conditions occurs in a narrower range of values of the saturation degree than in model experiments with the hemoglobin solution. The dependence of the pulse photolysis efficiency of HbCO on the photolytic radiation wavelength in the range from 550 to 585 nm has a broad bell shape. The efficiency maximum corresponds to the electronic Q transition (porphyrin π-π* absorption) in HbCO at a wavelength of 570 nm. No dissociation of the complex was observed under given experimental conditions upon irradiation of solutions by photolytic radiation at wavelengths above 585 nm. (laser applications and other topics in quantum electronics)

  3. Machine translation

    Energy Technology Data Exchange (ETDEWEB)

    Nagao, M

    1982-04-01

    Each language has its own structure. In translating one language into another one, language attributes and grammatical interpretation must be defined in an unambiguous form. In order to parse a sentence, it is necessary to recognize its structure. A so-called context-free grammar can help in this respect for machine translation and machine-aided translation. Problems to be solved in studying machine translation are taken up in the paper, which discusses subjects for semantics and for syntactic analysis and translation software. 14 references.

  4. The study of multiple PET reconstructed parameter

    International Nuclear Information System (INIS)

    Yin, D. Y.; Tian, J.

    2000-01-01

    PET, compared with SPECT, uses some similar techniques in image reconstruction, on the other hand, there are some difference on the techniques. A phantom experiment was conducted and the result was evaluated objectively through quantitative analysis in order to find ideal filter and cutoff frequency (Fc) for clinical application. The PET phantom have 6 solid inserts (cold) in the upper half and 6 hollow ones (hot) in the lower part. The middle insert is 1cm in diameter, the outer five have diameters of 1 to 3cm respectively. The phantom filled with 111 MBq 18 FDG and studied with segmentation acquisition. 25 set of images were reconstructed using HANN, HAMM, PARZEN, BUTTERWORTH, BUTTERWORTH2 filter and 0.1, 0.2, 0.3, 0.4, 0.5 Fe successively.A ROI of 4*4 pixels was drawn over middle 1 cm, outer 1cm, 3 cm cold column area and background area, the ratio between the ROI of cold column and background was calculated to evaluate the image contrast. A ROI of 15*15 pixels was drawn on the background area to get s.d as a judgement of image noise. A profile curve was drawn on the hollow column of middle 1 cm and outer 1 cm and their FWHM were compared with the real diameter to reflect linearity. With the same Fc, the contrast using HANN and HAMM filter was superior to other filter, The effect of the filter on image noise is listed in high to low order as HAMM, HANN, BUTTERWORTH, PARZEN and BUTTERWORTH2. The higher Fc, the higher image noise. The FWHM will increases as the Fc value decreases. With same Fc, the FWHM of different filter from small to big is HAMM, BUTTERWORTH, HANN, PARZEN, BUTTERWORTH2. The outer FWHM is larger than the middle one. For brain image, we suggest HAMM and HANN with Fc 0.3, 0.4 For image demanding lower resolution, we suggest BUTTERWORTH with Fc 0.4, 0.5, 2. For hot image, we can increase Fc to get high resolution. The FWHM value closed to the real value when HANN, HANN with Fc 0.3 and BUTTERWORTH with Fc 0.2. The 5% difference of FWHM between

  5. Estimation of process capability indices from the results of limit gauge inspection of dimensional parameters in machining industry

    Science.gov (United States)

    Masterenko, Dmitry A.; Metel, Alexander S.

    2018-03-01

    The process capability indices Cp, Cpk are widely used in the modern quality management as statistical measures of the ability of a process to produce output X within specification limits. The customer's requirement to ensure Cp ≥ 1.33 is often applied in contracts. Capability indices estimates may be calculated with the estimates of the mean µ and the variability 6σ, and for it, the quality characteristic in a sample of pieces should be measured. It requires, in turn, using advanced measuring devices and well-qualified staff. From the other hand, quality inspection by attributes, fulfilled with limit gauges (go/no-go) is much simpler and has a higher performance, but it does not give the numerical values of the quality characteristic. The described method allows estimating the mean and the variability of the process on the basis of the results of limit gauge inspection with certain lower limit LCL and upper limit UCL, which separates the pieces into three groups: where X control of the manufacturing process. It is very important for improving quality of articles in machining industry through their tolerance.

  6. Investigation on influence parameters in measurements of the optomechanical hole plate using an optical coordinate measuring machine

    DEFF Research Database (Denmark)

    Morace, Renate Erica; Hansen, Hans Nørgaard; De Chiffre, Leonardo

    2003-01-01

    This paper describes the results of an experimental investigation on influence parameters in optical coordinate measurements of the optomechanical hole plate. Special attention was paid to the background of the object, which strongly influences the measurement result. Furthermore, it is seen that...... influences, the measurements were all performed with no movements of the axes of the CMM....

  7. Researches regarding the reducing of burr size by optimising the cutting parameters on a CNC milling machine

    Directory of Open Access Journals (Sweden)

    Biriş Cristina

    2017-01-01

    Full Text Available This paper presents some experimental researches regarding burrs dimensions reduction that appear after the milling process together with an approach to reduce or eliminate the burrs resulted after this process. In order to reduce burrs dimensions, the milling process was executed with different cutting parameters and strategies then the results were evaluated.

  8. Short-Term Wind Speed Forecasting Using the Data Processing Approach and the Support Vector Machine Model Optimized by the Improved Cuckoo Search Parameter Estimation Algorithm

    Directory of Open Access Journals (Sweden)

    Chen Wang

    2016-01-01

    Full Text Available Power systems could be at risk when the power-grid collapse accident occurs. As a clean and renewable resource, wind energy plays an increasingly vital role in reducing air pollution and wind power generation becomes an important way to produce electrical power. Therefore, accurate wind power and wind speed forecasting are in need. In this research, a novel short-term wind speed forecasting portfolio has been proposed using the following three procedures: (I data preprocessing: apart from the regular normalization preprocessing, the data are preprocessed through empirical model decomposition (EMD, which reduces the effect of noise on the wind speed data; (II artificially intelligent parameter optimization introduction: the unknown parameters in the support vector machine (SVM model are optimized by the cuckoo search (CS algorithm; (III parameter optimization approach modification: an improved parameter optimization approach, called the SDCS model, based on the CS algorithm and the steepest descent (SD method is proposed. The comparison results show that the simple and effective portfolio EMD-SDCS-SVM produces promising predictions and has better performance than the individual forecasting components, with very small root mean squared errors and mean absolute percentage errors.

  9. A Simulation Model for Machine Efficiency Improvement Using Reliability Centered Maintenance: Case Study of Semiconductor Factory

    Directory of Open Access Journals (Sweden)

    Srisawat Supsomboon

    2014-01-01

    Full Text Available The purpose of this study was to increase the quality of product by focusing on the machine efficiency improvement. The principle of the reliability centered maintenance (RCM was applied to increase the machine reliability. The objective was to create preventive maintenance plan under reliability centered maintenance method and to reduce defects. The study target was set to reduce the Lead PPM for a test machine by simulating the proposed preventive maintenance plan. The simulation optimization approach based on evolutionary algorithms was employed for the preventive maintenance technique selection process to select the PM interval that gave the best total cost and Lead PPM values. The research methodology includes procedures such as following the priority of critical components in test machine, analyzing the damage and risk level by using Failure Mode and Effects Analysis (FMEA, calculating the suitable replacement period through reliability estimation, and optimizing the preventive maintenance plan. From the result of the study it is shown that the Lead PPM of test machine can be reduced. The cost of preventive maintenance, cost of good product, and cost of lost product were decreased.

  10. Machine protection systems

    CERN Document Server

    Macpherson, A L

    2010-01-01

    A summary of the Machine Protection System of the LHC is given, with particular attention given to the outstanding issues to be addressed, rather than the successes of the machine protection system from the 2009 run. In particular, the issues of Safe Machine Parameter system, collimation and beam cleaning, the beam dump system and abort gap cleaning, injection and dump protection, and the overall machine protection program for the upcoming run are summarised.

  11. A Comparative Study of Distribution System Parameter Estimation Methods

    Energy Technology Data Exchange (ETDEWEB)

    Sun, Yannan; Williams, Tess L.; Gourisetti, Sri Nikhil Gup

    2016-07-17

    In this paper, we compare two parameter estimation methods for distribution systems: residual sensitivity analysis and state-vector augmentation with a Kalman filter. These two methods were originally proposed for transmission systems, and are still the most commonly used methods for parameter estimation. Distribution systems have much lower measurement redundancy than transmission systems. Therefore, estimating parameters is much more difficult. To increase the robustness of parameter estimation, the two methods are applied with combined measurement snapshots (measurement sets taken at different points in time), so that the redundancy for computing the parameter values is increased. The advantages and disadvantages of both methods are discussed. The results of this paper show that state-vector augmentation is a better approach for parameter estimation in distribution systems. Simulation studies are done on a modified version of IEEE 13-Node Test Feeder with varying levels of measurement noise and non-zero error in the other system model parameters.

  12. Cleaning and outgassing studies of machinable tungsten for beamline safety shutters

    International Nuclear Information System (INIS)

    Liu, C.; Ryding, D.; Nielsen, R.W.; Kruy, T.L.; Kuzay, T.M.

    1996-01-01

    Machinable tungsten blocks are used as safety shutters in the front ends and the beamlines at the Advanced Photon Source (APS). The machinable tungsten used is characterized as a UHV-compatible metal by the vendor and was developed through a joint research effort with the APS. However, because of the inherent porosity in the sintered tungsten metal, it may present a vacuum problem and has to be subjected to strict vacuum testing before it is put on the beamlines. We have chosen specially heat-treated machinable tungsten with a density of 18 g/cm 3 for safety shutters. In-house-developed, environmentally friendly vacuum cleaning procedures were used. In this paper, we present results of thermal outgassing tests for machinable tungsten safety shutter sets. Each set consists of five blocks and has a total area of 4500 cm 2 . A cleaning procedure using alkaline detergent ultrasonic washes, deionized water rinses, and a 500 degree C vacuum furnace baking was used before outgassing measurements. Outgassing rates 10 hours after initial pump down at room temperature reached ∼1.60x10 -10 Torr·l·s -1 ·cm -2 for machinable tungsten and ∼1.56x10 -10 Torr·l·s -1 ·cm -2 for the stainless steel vacuum chamber. The outgassing rate of machinable tungsten 24 hours after an in situ 48 h bake at 160 degree C is also comparable to that of the stainless steel vacuum chamber. The importance of a 500 degree C vacuum furnace baking has been confirmed by outgassing studies for machinable tungsten sets that were not subject to vacuum furnace baking. copyright 1996 American Institute of Physics

  13. Study of Material Densification of In718 in the Higher Throughput Parameter Regime

    Science.gov (United States)

    Cordner, Samuel

    2016-01-01

    Selective Laser Melting (SLM) is a powder bed fusion additive manufacturing process used increasingly in the aerospace industry to reduce the cost, weight, and fabrication time for complex propulsion components. Previous optimization studies for SLM using the Concept Laser M1 and M2 machines at NASA Marshall Space Flight Center have centered on machine default parameters. The objective of this project is to characterize how heat treatment affects density and porosity from a microscopic point of view. This is performs using higher throughput parameters (a previously unexplored region of the manufacturing operating envelope for this application) on material consolidation. Density blocks were analyzed to explore the relationship between build parameters (laser power, scan speed, and hatch spacing) and material consolidation (assessed in terms of density and porosity). The study also considers the impact of post-processing, specifically hot isostatic pressing and heat treatment, as well as deposition pattern on material consolidation in the higher energy parameter regime. Metallurgical evaluation of specimens will also be presented. This work will contribute to creating a knowledge base (understanding material behavior in all ranges of the AM equipment operating envelope) that is critical to transitioning AM from the custom low rate production sphere it currently occupies to the world of mass high rate production, where parts are fabricated at a rapid rate with confidence that they will meet or exceed all stringent functional requirements for spaceflight hardware. These studies will also provide important data on the sensitivity of material consolidation to process parameters that will inform the design and development of future flight articles using SLM.

  14. Study on the Gap Flow Simulation in EDM Small Hole Machining with Ti Alloy

    Directory of Open Access Journals (Sweden)

    Shengfang Zhang

    2017-01-01

    Full Text Available In electrical discharge machining (EDM process, the debris removed from electrode material strongly affects the machining efficiency and accuracy, especially for the deep small hole machining process. In case of Ti alloy, the debris movement and removal process in gap flow between electrodes for small hole EDM process is studied in this paper. Based on the solid-liquid two-phase flow equation, the mathematical model on the gap flow field with flushing and self-adaptive disturbation is developed. In our 3D simulation process, the count of debris increases with number of EDM discharge cycles, and the disturbation generated by the movement of self-adaptive tool in the gap flow is considered. The methods of smoothing and remeshing are also applied in the modeling process to enable a movable tool. Under different depth, flushing velocity, and tool diameter, the distribution of velocity field, pressure field of gap flow, and debris movement are analyzed. The statistical study of debris distribution under different machining conditions is also carried out. Finally, a series of experiments are conducted on a self-made machine to verify the 3D simulation model. The experiment results show the burn mark at hole bottom and the tapered wall, which corresponds well with the simulating conclusion.

  15. Students' perspectives on promoting healthful food choices from campus vending machines: a qualitative interview study.

    Science.gov (United States)

    Ali, Habiba I; Jarrar, Amjad H; Abo-El-Enen, Mostafa; Al Shamsi, Mariam; Al Ashqar, Huda

    2015-05-28

    Increasing the healthfulness of campus food environments is an important step in promoting healthful food choices among college students. This study explored university students' suggestions on promoting healthful food choices from campus vending machines. It also examined factors influencing students' food choices from vending machines. Peer-led semi-structured individual interviews were conducted with 43 undergraduate students (33 females and 10 males) recruited from students enrolled in an introductory nutrition course in a large national university in the United Arab Emirates. Interviews were audiotaped, transcribed, and coded to generate themes using N-Vivo software. Accessibility, peer influence, and busy schedules were the main factors influencing students' food choices from campus vending machines. Participants expressed the need to improve the nutritional quality of the food items sold in the campus vending machines. Recommendations for students' nutrition educational activities included placing nutrition tips on or beside the vending machines and using active learning methods, such as competitions on nutrition knowledge. The results of this study have useful applications in improving the campus food environment and nutrition education opportunities at the university to assist students in making healthful food choices.

  16. Study of the machining of uranium carbide rods obtained by continuous casting under electronic bombardment

    International Nuclear Information System (INIS)

    Rousset, P.; Accary, A.

    1965-01-01

    The authors consider the various methods of machining uranium mono-carbide and compare them critically in the case of their application to uranium carbide obtained by fusion under an electronic bombardment and continuous casting. This study leads them to propose two mechanical machining methods: cylindrical rectification and center-less rectification, preceded by a preliminary roughing out of a cylinder, the latter appearing more suitable. A study of the machining yields as a function of the diameter of the rough bars and of the diameter of the finished rods has shown that an optimum value of the rough bar diameter exists for each value of the finished rod diameter. It is found that the yield increases as the diameter itself increases, this yield rising from 45 per cent to around 70 per cent as the diameter of the rough bars increases from 25-26 mm to 37-38 mm. (authors) [fr

  17. Output-only modal parameter estimator of linear time-varying structural systems based on vector TAR model and least squares support vector machine

    Science.gov (United States)

    Zhou, Si-Da; Ma, Yuan-Chen; Liu, Li; Kang, Jie; Ma, Zhi-Sai; Yu, Lei

    2018-01-01

    Identification of time-varying modal parameters contributes to the structural health monitoring, fault detection, vibration control, etc. of the operational time-varying structural systems. However, it is a challenging task because there is not more information for the identification of the time-varying systems than that of the time-invariant systems. This paper presents a vector time-dependent autoregressive model and least squares support vector machine based modal parameter estimator for linear time-varying structural systems in case of output-only measurements. To reduce the computational cost, a Wendland's compactly supported radial basis function is used to achieve the sparsity of the Gram matrix. A Gamma-test-based non-parametric approach of selecting the regularization factor is adapted for the proposed estimator to replace the time-consuming n-fold cross validation. A series of numerical examples have illustrated the advantages of the proposed modal parameter estimator on the suppression of the overestimate and the short data. A laboratory experiment has further validated the proposed estimator.

  18. Optimization the machining parameters by using VIKOR and Entropy Weight method during EDM process of Al–18% SiCp Metal matrix composit

    Directory of Open Access Journals (Sweden)

    Rajesh Kumar Bhuyan

    2016-06-01

    Full Text Available The objective of this paper is to optimize the process parameters by combined approach of VIKOR and Entropy weight measurement method during Electrical discharge machining (EDM process of Al-18wt.%SiCp metal matrix composite (MMC. The central composite design (CCD method is considered to evaluate the effect of three process parameters; namely pulse on time (Ton, peak current (Ip and flushing pressure (Fp on the responses like material removal rate (MRR, tool wear rate (TWR, Radial over cut (ROC and surface roughness (Ra. The Entropy weight measurement method evaluates the individual weights of each response and, using VIKOR method, the multi-objective responses are optimized to get a single numerical index known as VIKOR Index. Then the Analysis of Variance (ANOVA technique is used to determine the significance of the process parameters on the VIKOR Index. Finally, the result of the VIKOR Indexed is validated by conformation test using the liner mathematical model equation develop by responses surface methodology to identify the effectiveness of the proposed method.

  19. Application of Least-Squares Support Vector Machines for Quantitative Evaluation of Known Contaminant in Water Distribution System Using Online Water Quality Parameters

    Directory of Open Access Journals (Sweden)

    Kexin Wang

    2018-03-01

    Full Text Available In water-quality, early warning systems and qualitative detection of contaminants are always challenging. There are a number of parameters that need to be measured which are not entirely linearly related to pollutant concentrations. Besides the complex correlations between variable water parameters that need to be analyzed also impairs the accuracy of quantitative detection. In aspects of these problems, the application of least-squares support vector machines (LS-SVM is used to evaluate the water contamination and various conventional water quality sensors quantitatively. The various contaminations may cause different correlative responses of sensors, and also the degree of response is related to the concentration of the injected contaminant. Therefore to enhance the reliability and accuracy of water contamination detection a new method is proposed. In this method, a new relative response parameter is introduced to calculate the differences between water quality parameters and their baselines. A variety of regression models has been examined, as result of its high performance, the regression model based on genetic algorithm (GA is combined with LS-SVM. In this paper, the practical application of the proposed method is considered, controlled experiments are designed, and data is collected from the experimental setup. The measured data is applied to analyze the water contamination concentration. The evaluation of results validated that the LS-SVM model can adapt to the local nonlinear variations between water quality parameters and contamination concentration with the excellent generalization ability and accuracy. The validity of the proposed approach in concentration evaluation for potassium ferricyanide is proven to be more than 0.5 mg/L in water distribution systems.

  20. Study of the Induction Machine Unsymmetrical Condition Using In Total Fluxes Equations

    Directory of Open Access Journals (Sweden)

    SIMION, A.

    2010-02-01

    Full Text Available On the basis of the mathematical model, called in total fluxes in a previous paper, and which is proper for the analysis of transient operation of the two-phase induction machine, one obtains the symmetrical steady-state equations, which are valid for three-phase machines, as well. The obtained mathematical expressions are much more simple and easier to use than the consecrated ones, which are generally applied in scientific literature. Moreover, considerations are to be made upon the space-time rotational vectors, emphasizing their importance in understanding the physical phenomena that characterize induction machines. The use of these space vectors is further tested out for the study of unsymmetrical supply, which gives a much faster method in obtaining the electromagnetic torque expression. Finally, the results are compared with the ones that come out from the traditional methods, more exactly, the symmetric component method.

  1. Determination of dosimetric parameters of Asymmetric fields from those of Symmetric fields for equinox 100 Cobalt-60 teletherapy machine

    International Nuclear Information System (INIS)

    Mensah, K.

    2014-07-01

    The Theratron Equinox 100 Cobalt-60 therapy unit is equipped wtih x-ray collimators or jaws that can be moved independently or allow asymmetric fields with field centres positioned away from the true central axis of the beam. Although asymmetric collimation can be performed by beam splitters or secondary blocking on a shadow tray; an independent jaw feature reduces the set-up time and spares the therapist from handling heavy blocks. Clinical sites where asymmetric jaws are typically used include breast, head and neck, craniospinal and prostate. Knowledge of the dose distribution of asymmetric fields is required to help evaluate the dosimetry of this non-standard treatment delivery technique prior to clinical implementation. IBA StarTrack 2-D array was used to acquire beam profiles of symmetric and asymmetric beams of different field sizes and varying depth using the Theratron Equinox 100 Cobalt-60 teletherapy unit. The 2-D water phantom was then used to measure PDDs and output factors of both the symmetric and asymmetric beams at varying depths and field sizes. The off-axis ratio was also determined from the half beam profile of the largest field size of the treatment machine and then the output factor ratios were used to validate it. The treatment planning system was then used to model both the symmetric and asymmetic beams and the PDDs and output factors were also calculated. Beam profiles for asymmetry beams showed good agreement with symmetry beam profiles for smaller field sizes and the deviations among them steadily became more evident with increasing field sizes. This difference in the dose distribution for asymmetric fields compared to the dose distribution for symmetric fields was due to the tilt of the dose profiles towards the beam axis. This tilt in the dose profiles of the asymmetic beams was caused by the oblique incidence of the asymmetric beam at off-axis locations, causing less beam hardening compared to that along the central axis. In treatment

  2. An experimental study on effect of process parameters in deep ...

    African Journals Online (AJOL)

    The effects of various deep drawing process parameters were determined by experimental study with the use of Taguchi fractional factorial design and analysis of variance for AA6111 Aluminum alloy. The optimum process parameters were determined based on their influence on the thickness variation at different regions ...

  3. Study on the Optimization and Process Modeling of the Rotary Ultrasonic Machining of Zerodur Glass-Ceramic

    Science.gov (United States)

    Pitts, James Daniel

    Rotary ultrasonic machining (RUM), a hybrid process combining ultrasonic machining and diamond grinding, was created to increase material removal rates for the fabrication of hard and brittle workpieces. The objective of this research was to experimentally derive empirical equations for the prediction of multiple machined surface roughness parameters for helically pocketed rotary ultrasonic machined Zerodur glass-ceramic workpieces by means of a systematic statistical experimental approach. A Taguchi parametric screening design of experiments was employed to systematically determine the RUM process parameters with the largest effect on mean surface roughness. Next empirically determined equations for the seven common surface quality metrics were developed via Box-Behnken surface response experimental trials. Validation trials were conducted resulting in predicted and experimental surface roughness in varying levels of agreement. The reductions in cutting force and tool wear associated with RUM, reported by previous researchers, was experimentally verified to also extended to helical pocketing of Zerodur glass-ceramic.

  4. Study on Damage Evaluation and Machinability of UD-CFRP for the Orthogonal Cutting Operation Using Scanning Acoustic Microscopy and the Finite Element Method.

    Science.gov (United States)

    Wang, Dongyao; He, Xiaodong; Xu, Zhonghai; Jiao, Weicheng; Yang, Fan; Jiang, Long; Li, Linlin; Liu, Wenbo; Wang, Rongguo

    2017-02-20

    Owing to high specific strength and designability, unidirectional carbon fiber reinforced polymer (UD-CFRP) has been utilized in numerous fields to replace conventional metal materials. Post machining processes are always required for UD-CFRP to achieve dimensional tolerance and assembly specifications. Due to inhomogeneity and anisotropy, UD-CFRP differs greatly from metal materials in machining and failure mechanism. To improve the efficiency and avoid machining-induced damage, this paper undertook to study the correlations between cutting parameters, fiber orientation angle, cutting forces, and cutting-induced damage for UD-CFRP laminate. Scanning acoustic microscopy (SAM) was employed and one-/two-dimensional damage factors were then created to quantitatively characterize the damage of the laminate workpieces. According to the 3D Hashin's criteria a numerical model was further proposed in terms of the finite element method (FEM). A good agreement between simulation and experimental results was validated for the prediction and structural optimization of the UD-CFRP.

  5. Simulation study on effects of machine imperfections in the KEK B-factory

    International Nuclear Information System (INIS)

    Koiso, Haruyo; Funakoshi, Yoshihiro

    1994-01-01

    Effects of machine imperfections in a low beta lattice with noninterleaved sextupoles are studied with computer simulations. Misalignments of quadrupoles and sextupoles significantly degrade the dynamic aperture and the vertical-to-horizontal emittance ratio. However, orbit corrections at sextupoles effectively recover both the dynamic aperture and the emittance ratio. (author)

  6. An Exploratory Study of Problem Gambling on Casino versus Non-Casino Electronic Gaming Machines

    Science.gov (United States)

    Clarke, Dave; Pulford, Justin; Bellringer, Maria; Abbott, Max; Hodgins, David C.

    2012-01-01

    Electronic gaming machines (EGMs) have been frequently associated with problem gambling. Little research has compared the relative contribution of casino EGMs versus non-casino EGMs on current problem gambling, after controlling for demographic factors and gambling behaviour. Our exploratory study obtained data from questionnaires administered to…

  7. Metal matrix composites synthesis, wear characteristics, machinability study of MMC brake drum

    CERN Document Server

    Natarajan, Nanjappan; Davim, J Paulo

    2015-01-01

    This book is dedicated to composite materials, presenting different synthesis processes, composite properties and their machining behaviour. The book describes also the problems on manufacturing of metal matrix composite components. Among others, it provides procedures for manufacturing of metal matrix composites and case studies.

  8. Study of an absorption machine for an ammonia-water system ...

    African Journals Online (AJOL)

    This paper deals with Study of an absorption machine for an ammonia-water system decentralized trigeneration. The effects of evaporator, absorber and boiler temperature on the coefficient of performance of this cycle investigate. Simulation results show that with increasing the evaporator and absorber temperature the ...

  9. Individualized prediction of illness course at the first psychotic episode: a support vector machine MRI study.

    LENUS (Irish Health Repository)

    Mourao-Miranda, J

    2012-05-01

    To date, magnetic resonance imaging (MRI) has made little impact on the diagnosis and monitoring of psychoses in individual patients. In this study, we used a support vector machine (SVM) whole-brain classification approach to predict future illness course at the individual level from MRI data obtained at the first psychotic episode.

  10. Quiescent plasma machine for beam-plasma interaction and wave studies

    International Nuclear Information System (INIS)

    Ferreira, J.L.

    1994-01-01

    A quiescent double plasma machine for beam-plasma interaction wave studies is described. A detailed description of several plasma diagnostics used for plasma and wave excitation detection is given. A beam-plasma wave dispersion relation is used to compare theoretical values with the experimentally measured Langmuir wave frequencies and wavelengths. (author). 14 refs, 10 figs

  11. Study and simulation of a parallel numerical processing machine

    International Nuclear Information System (INIS)

    Bel Hadj, Slaheddine

    1981-12-01

    This study has been carried out in the perspective of the implementation on a minicomputer of the NEPTUNIX package (software for the resolution of very large algebra-differential equation systems). Aiming at increasing the system performance, a previous research work has shown the necessity of reducing the execution time of certain numerical computation tasks, which are of frequent use. It has also demonstrated the feasibility of handling these tasks with efficient algorithms of parallel type. The present work deals with the study and simulation of a parallel architecture processor adapted to the fast execution of these algorithms. A minicomputer fitted with a connection to such a parallel processor, has a greatly extended computing power. Then the architecture of a parallel numerical processor, based on the use of VLSI microprocessors and co-processors, is described. Its design aims at the best cost / performance ratio. The last part deals with the simulation processor with the 'CHAMBOR' program. Results show an increasing factor of 30 in speed, in comparison with the execution on a MITRA 15 minicomputer. Moreover the conflicts importance, mainly at the level of access to a shared resource is evaluated. Although this implementation has been designed having in mind a dedicated application, other uses could be envisaged, particularly for the simulation of nuclear reactors: operator guiding system, the behavioural study under accidental circumstances, etc. (author) [fr

  12. A Comparison Study of Machine Learning Based Algorithms for Fatigue Crack Growth Calculation.

    Science.gov (United States)

    Wang, Hongxun; Zhang, Weifang; Sun, Fuqiang; Zhang, Wei

    2017-05-18

    The relationships between the fatigue crack growth rate ( d a / d N ) and stress intensity factor range ( Δ K ) are not always linear even in the Paris region. The stress ratio effects on fatigue crack growth rate are diverse in different materials. However, most existing fatigue crack growth models cannot handle these nonlinearities appropriately. The machine learning method provides a flexible approach to the modeling of fatigue crack growth because of its excellent nonlinear approximation and multivariable learning ability. In this paper, a fatigue crack growth calculation method is proposed based on three different machine learning algorithms (MLAs): extreme learning machine (ELM), radial basis function network (RBFN) and genetic algorithms optimized back propagation network (GABP). The MLA based method is validated using testing data of different materials. The three MLAs are compared with each other as well as the classical two-parameter model ( K * approach). The results show that the predictions of MLAs are superior to those of K * approach in accuracy and effectiveness, and the ELM based algorithms show overall the best agreement with the experimental data out of the three MLAs, for its global optimization and extrapolation ability.

  13. Study of excitation energy dependence of nuclear level density parameter

    International Nuclear Information System (INIS)

    Mohanto, G.; Nayak, B.K.; Saxena, A.

    2016-01-01

    In the present study, we have populated CN by fusion reaction and excitation energy of the intermediate nuclei is determined after first chance α-emission to investigate excitation energy dependence of the NLD parameter. Evaporated neutron spectra were measured following alpha evaporation for obtaining NLD parameter for the reaction 11 B + 197 Au, populating CN 208 Po. This CN after evaporating an α-particle populates intermediate nucleus 204 Pb. The 204 Pb has magic number of Z=82. Our aim is to study the excitation energy dependence of NLD parameter for closed shell nuclei

  14. Experimental study on bearing preload optimum of machine tool spindle

    International Nuclear Information System (INIS)

    Xu Tao; Xu Guanghua; Zhang Qin; Hua Cheng; Zhang Hu; Jiang Kuosheng

    2012-01-01

    An experimental study is conducted to investigate the possibility and the effect of temperature rise and vibration level of bearing by adjusting axial preloads and radial loads in spindle bearing test rig. The shaft of the test rig is driven by a motorized high speed spindle at the range of 0∼20000 rpm. The axial preloads and radial loads on bearings are controlled by using hydraulic pressure which can be adjusted automatically. Temperature rise and radial vibration of test bearings are measured by thermocouples and Polytec portable laser vibrometer PDV100. Experiment shows that the temperature rise of bearings is nonlinear varying with the increase of radial loads, but temperature rise almost increases linearly with the increase of axial preload and rotating speed. In this paper, an alternate axial preload is used for bearings. When the rotating speed passes through the critical speed of the shaft, axial preload of bearings will have a remarkable effect. The low preload could reduce bearing vibration and temperature rise for bearings as well. At the others speed, the high preload could improve the vibration performance of high speed spindle and the bearing temperature was lower than that of the constant pressure preload spindle.

  15. Asynchronized synchronous machines

    CERN Document Server

    Botvinnik, M M

    1964-01-01

    Asynchronized Synchronous Machines focuses on the theoretical research on asynchronized synchronous (AS) machines, which are "hybrids” of synchronous and induction machines that can operate with slip. Topics covered in this book include the initial equations; vector diagram of an AS machine; regulation in cases of deviation from the law of full compensation; parameters of the excitation system; and schematic diagram of an excitation regulator. The possible applications of AS machines and its calculations in certain cases are also discussed. This publication is beneficial for students and indiv

  16. Molecular beam studies with a time-of-flight machine

    International Nuclear Information System (INIS)

    Beijerinck, H.C.W.

    1975-01-01

    The study concerns the development of the time-of-flight method for the velocity analysis of molecular beams and its application to the measurement of the velocity dependence of the total cross-section of the noble gases. It reviews the elastic scattering theory, both in the framework of classical mechanics and in the quantum mechanical description. Attention is paid to the semiclassical correspondence of classical particle trajectories with the partial waves of the quantum mechanical solution. The total cross-section and the small angle differential cross-section are discussed with special emphasis on their relation. The results of this chapter are used later to derive the correction on the measured total cross-section due to the finite angular resolution of the apparatus. Reviewed also is the available information on the intermolecular potential of the Ar-Ar system. Then a discussion of the measurement of total cross-sections with the molecular beam method and the time-of-flight method is compared to other methods used. It is shown that the single burst time-of-flight method can be developed into a reliable and well-calibrated method for the analysis of the velocity distribution of molecular beams. A comparison of the single burst time-of-flight method with the cross-correlation time-of-flight method shows that the two methods are complementary and that the specific experimental circumstances determine which method is to be preferred. Molecular beam sources are discussed. The peaking factor formalism is introduced and helps to compare the performance of different types of sources. The effusive and the supersonic source are treated and recent experimental results are given. The multichannel source is treated in more detail. For the opaque mode, an experimental investigation of the velocity distribution and the angular distribution of the flow pattern is presented. Comparison of these results with Monte Carlo calculations for free molecular flow in a cylindrical

  17. A data-based technique for monitoring of wound rotor induction machines: A simulation study

    KAUST Repository

    Harrou, Fouzi; Ramahaleomiarantsoa, Jacques F.; Nounou, Mohamed N.; Nounou, Hazem N.

    2016-01-01

    Detecting faults induction machines is crucial for a safe operation of these machines. The aim of this paper is to present a statistical fault detection methodology for the detection of faults in three-phase wound rotor induction machines (WRIM

  18. A study conducted on the impact of effluent waste from machining process on the environment by water analysis

    Energy Technology Data Exchange (ETDEWEB)

    Kovoor, Punnose P.; Idris, Mohd Razif [Kuala Lumpur Univ. (Malaysia). Inst. of Product Design and Manufacturing, IPROM; Hassan, Masjuki Haji [Univ. of Malaya, Kuala Lumpur (Malaysia). Dept. of Mechanical Engineering; Tengku Yahya, Tengku Fazli [Kuala Lumpur Univ., Melaka (Malaysia). Malaysian Inst. of Chemical and Bio Engineering Technology, MICET

    2012-11-01

    Ferrous block metals are used frequently in large quantities in various sectors of industry for making automotive, furniture, electrical and mechanical items, body parts for consumables, and so forth. During the manufacturing stage, the block metals are subjected to some form of material removal process either through turning, grinding, milling, or drilling operations to obtain the final product. Wastes are generated from the machining process in the form of effluent waste, solid waste, atmospheric emission, and energy emission. These wastes, if not recycled or treated properly before disposal, will have a detrimental impact on the environment through air, water, and soil pollution. The purpose of this paper is to determine the impact of the effluent waste from the machining process on the environment through water analysis. A twofold study is carried out to determine the impact of the effluent waste on the water stream. The preliminary study consists of a scenario analysis where five scenarios are drawn out using substances such as spent coolant, tramp oil, solvent, powdered chips, and sludge, which are commonly found in the effluent waste. The wastes are prepared according to the scenarios and are disposed through the Institute of Product Design and Manufacturing (IPROM) storm water drain. Samples of effluent waste are collected at specific locations according to the APHA method and are tested for parameters such as pH, ammoniacal nitrogen, dissolved oxygen, biochemical oxygen demand, chemical oxygen demand, and total suspended solids. A subsequent study is done by collecting 30 samples of the effluent waste from the machining operations from two small- and medium-scale enterprise locations and the IPROM workshop to test the quality of water. The results obtained from the tests showed high values of chemical oxygen demand, ammoniacal nitrogen, and total suspended solids when compared with the Standard B specification for inland water bodies as specified by the

  19. Setup Time Reduction On Solder Paste Printing Machine – A Case Study

    Directory of Open Access Journals (Sweden)

    Rajesh Dhake

    2013-06-01

    Full Text Available Lean manufacturing envisages the reduction of the seven deadly wastes referred to as MUDA. Setup time forms a major component of the equipment downtime. It leads to lower machine utilization and restricts the output and product variety. This necessitates the requirement for quick setups. Single Minute Exchange of Die philosophy (a lean manufacturing tool here after referred as “SMED” is one of the important tool which aims at quick setups driving smaller lot sizes, lower production costs, improve productivity in terms of increased output, increased utilization of machine and labor hours, make additional capacity available (often at bottleneck resources, reduce scrap and rework, and increase flexibility[3]. This paper focuses on the application of Single Minute Exchange of Die[1] and Quick Changeover Philosophy[2] for reducing setup time on Solder Past Printing Machine (bottleneck machine in a electronic speedo-cluster manufacturing company. The four step SMED philosophy was adopted to effect reduction in setup time. The initial step was gathering information about the present setup times and its proportion to the total productive time. A detailed video based time study of setup activities was done to classify them into external and internal setup activities in terms of their need (i.e. preparation, replacement or adjustment, time taken and the way these could be reduced, simplified or eliminated. The improvements effected were of three categories viz., mechanical, procedural and organizational. The paper concludes by comparing the present and proposed (implemented methods of setup procedures.

  20. Impact of corpus domain for sentiment classification: An evaluation study using supervised machine learning techniques

    Science.gov (United States)

    Karsi, Redouane; Zaim, Mounia; El Alami, Jamila

    2017-07-01

    Thanks to the development of the internet, a large community now has the possibility to communicate and express its opinions and preferences through multiple media such as blogs, forums, social networks and e-commerce sites. Today, it becomes clearer that opinions published on the web are a very valuable source for decision-making, so a rapidly growing field of research called “sentiment analysis” is born to address the problem of automatically determining the polarity (Positive, negative, neutral,…) of textual opinions. People expressing themselves in a particular domain often use specific domain language expressions, thus, building a classifier, which performs well in different domains is a challenging problem. The purpose of this paper is to evaluate the impact of domain for sentiment classification when using machine learning techniques. In our study three popular machine learning techniques: Support Vector Machines (SVM), Naive Bayes and K nearest neighbors(KNN) were applied on datasets collected from different domains. Experimental results show that Support Vector Machines outperforms other classifiers in all domains, since it achieved at least 74.75% accuracy with a standard deviation of 4,08.

  1. Astrophysical parameters of ten poorly studied open star clusters

    International Nuclear Information System (INIS)

    Tadross, Ashraf Latif; El-Bendary, Reda; Osman, Anas; Ismail, Nader; Bakry, Abdel Aziz

    2012-01-01

    We present the fundamental parameters of ten open star clusters, nominated from Kronberger et al. who presented some newly discovered stellar groups on the basis of the Two Micron All Sky Survey photometry and Digitized Sky Survey visual images. Star counts and photometric parameters (radius, membership, distance, color excess, age, luminosity function, mass function, total mass, and dynamical relaxation time) have been determined for these ten clusters for the first time. In order to calibrate our procedures, the main parameters (distance, age, and color excess) have been re-estimated for another five clusters, which are also studied by Kronberger et al. (research papers)

  2. Machine learning approaches to the social determinants of health in the health and retirement study.

    Science.gov (United States)

    Seligman, Benjamin; Tuljapurkar, Shripad; Rehkopf, David

    2018-04-01

    Social and economic factors are important predictors of health and of recognized importance for health systems. However, machine learning, used elsewhere in the biomedical literature, has not been extensively applied to study relationships between society and health. We investigate how machine learning may add to our understanding of social determinants of health using data from the Health and Retirement Study. A linear regression of age and gender, and a parsimonious theory-based regression additionally incorporating income, wealth, and education, were used to predict systolic blood pressure, body mass index, waist circumference, and telomere length. Prediction, fit, and interpretability were compared across four machine learning methods: linear regression, penalized regressions, random forests, and neural networks. All models had poor out-of-sample prediction. Most machine learning models performed similarly to the simpler models. However, neural networks greatly outperformed the three other methods. Neural networks also had good fit to the data ( R 2 between 0.4-0.6, versus learning models, nine variables were frequently selected or highly weighted as predictors: dental visits, current smoking, self-rated health, serial-seven subtractions, probability of receiving an inheritance, probability of leaving an inheritance of at least $10,000, number of children ever born, African-American race, and gender. Some of the machine learning methods do not improve prediction or fit beyond simpler models, however, neural networks performed well. The predictors identified across models suggest underlying social factors that are important predictors of biological indicators of chronic disease, and that the non-linear and interactive relationships between variables fundamental to the neural network approach may be important to consider.

  3. Delivery parameters, neonatal parameters and incidence of urinary incontinence six months postpartum: a cohort study.

    Science.gov (United States)

    Wesnes, Stian Langeland; Hannestad, Yngvild; Rortveit, Guri

    2017-10-01

    Contradictory results have been reported regarding most delivery parameters as risk factors for urinary incontinence. We investigated the association between the incidence of urinary incontinence six months postpartum and single obstetric risk factors as well as combinations of risk factors. This study was based on the Norwegian Mother and Child Cohort Study, conducted by the Norwegian Institute of Public Health during 1998-2008. This substudy was based on 7561 primiparous women who were continent before and during pregnancy. Data were obtained from questionnaires answered at weeks 15 and 30 of pregnancy and six months postpartum. Data were linked to the Medical Birth Registry of Norway. Single and combined delivery- and neonatal parameters were analyzed by logistic regression analyses. Birthweight was associated with significantly higher risk of urinary incontinence six months postpartum [3541-4180 g: odds ratio (OR) 1.4, 95% confidence interval (CI) 1.2-1.6; >4180 g: OR 1.6, 95% CI 1.2-2.0]. Fetal presentation, obstetric anal sphincter injuries, episiotomy and epidural analgesia were not significantly associated with increased risk of urinary incontinence. The following combinations of risk factors among women delivering by spontaneous vaginal delivery increased the risk of urinary incontinence six months postpartum; birthweight ≥3540 g and ≥36 cm head circumference; birthweight ≥3540 g and forceps, birthweight ≥3540 g and episiotomy; and ≥36 cm head circumference and episiotomy. Some combinations of delivery parameters and neonatal parameters seem to act together and may increase the risk of incidence of urinary incontinence six months postpartum in a synergetic way. © 2017 Nordic Federation of Societies of Obstetrics and Gynecology.

  4. Spillover effects in epidemiology: parameters, study designs and methodological considerations

    Science.gov (United States)

    Benjamin-Chung, Jade; Arnold, Benjamin F; Berger, David; Luby, Stephen P; Miguel, Edward; Colford Jr, John M; Hubbard, Alan E

    2018-01-01

    Abstract Many public health interventions provide benefits that extend beyond their direct recipients and impact people in close physical or social proximity who did not directly receive the intervention themselves. A classic example of this phenomenon is the herd protection provided by many vaccines. If these ‘spillover effects’ (i.e. ‘herd effects’) are present in the same direction as the effects on the intended recipients, studies that only estimate direct effects on recipients will likely underestimate the full public health benefits of the intervention. Causal inference assumptions for spillover parameters have been articulated in the vaccine literature, but many studies measuring spillovers of other types of public health interventions have not drawn upon that literature. In conjunction with a systematic review we conducted of spillovers of public health interventions delivered in low- and middle-income countries, we classified the most widely used spillover parameters reported in the empirical literature into a standard notation. General classes of spillover parameters include: cluster-level spillovers; spillovers conditional on treatment or outcome density, distance or the number of treated social network links; and vaccine efficacy parameters related to spillovers. We draw on high quality empirical examples to illustrate each of these parameters. We describe study designs to estimate spillovers and assumptions required to make causal inferences about spillovers. We aim to advance and encourage methods for spillover estimation and reporting by standardizing spillover parameter nomenclature and articulating the causal inference assumptions required to estimate spillovers. PMID:29106568

  5. Study of Material Consolidation at Higher Throughput Parameters in Selective Laser Melting of Inconel 718

    Science.gov (United States)

    Prater, Tracie

    2016-01-01

    Selective Laser Melting (SLM) is a powder bed fusion additive manufacturing process used increasingly in the aerospace industry to reduce the cost, weight, and fabrication time for complex propulsion components. SLM stands poised to revolutionize propulsion manufacturing, but there are a number of technical questions that must be addressed in order to achieve rapid, efficient fabrication and ensure adequate performance of parts manufactured using this process in safety-critical flight applications. Previous optimization studies for SLM using the Concept Laser M1 and M2 machines at NASA Marshall Space Flight Center have centered on machine default parameters. The objective of this work is to characterize the impact of higher throughput parameters (a previously unexplored region of the manufacturing operating envelope for this application) on material consolidation. In phase I of this work, density blocks were analyzed to explore the relationship between build parameters (laser power, scan speed, hatch spacing, and layer thickness) and material consolidation (assessed in terms of as-built density and porosity). Phase II additionally considers the impact of post-processing, specifically hot isostatic pressing and heat treatment, as well as deposition pattern on material consolidation in the same higher energy parameter regime considered in the phase I work. Density and microstructure represent the "first-gate" metrics for determining the adequacy of the SLM process in this parameter range and, as a critical initial indicator of material quality, will factor into a follow-on DOE that assesses the impact of these parameters on mechanical properties. This work will contribute to creating a knowledge base (understanding material behavior in all ranges of the AM equipment operating envelope) that is critical to transitioning AM from the custom low rate production sphere it currently occupies to the world of mass high rate production, where parts are fabricated at a rapid

  6. Machinability of IPS Empress 2 framework ceramic.

    Science.gov (United States)

    Schmidt, C; Weigl, P

    2000-01-01

    Using ceramic materials for an automatic production of ceramic dentures by CAD/CAM is a challenge, because many technological, medical, and optical demands must be considered. The IPS Empress 2 framework ceramic meets most of them. This study shows the possibilities for machining this ceramic with economical parameters. The long life-time requirement for ceramic dentures requires a ductile machined surface to avoid the well-known subsurface damages of brittle materials caused by machining. Slow and rapid damage propagation begins at break outs and cracks, and limits life-time significantly. Therefore, ductile machined surfaces are an important demand for machine dental ceramics. The machining tests were performed with various parameters such as tool grain size and feed speed. Denture ceramics were machined by jig grinding on a 5-axis CNC milling machine (Maho HGF 500) with a high-speed spindle up to 120,000 rpm. The results of the wear test indicate low tool wear. With one tool, you can machine eight occlusal surfaces including roughing and finishing. One occlusal surface takes about 60 min machining time. Recommended parameters for roughing are middle diamond grain size (D107), cutting speed v(c) = 4.7 m/s, feed speed v(ft) = 1000 mm/min, depth of cut a(e) = 0.06 mm, width of contact a(p) = 0.8 mm, and for finishing ultra fine diamond grain size (D46), cutting speed v(c) = 4.7 m/s, feed speed v(ft) = 100 mm/min, depth of cut a(e) = 0.02 mm, width of contact a(p) = 0.8 mm. The results of the machining tests give a reference for using IPS Empress(R) 2 framework ceramic in CAD/CAM systems. Copyright 2000 John Wiley & Sons, Inc.

  7. Study on Integration Treatment Technology of Waste Emulsion from Machining Processing

    OpenAIRE

    Xin-dong Li; Wan-fu Huang

    2013-01-01

    The study studied the treatment technology of high concentration emulsion wastewater in metal machining plant. By analyzing the properties of emulsion wastewater, the author used the combination process of membrane technology + Fe-C micro-electrolysis + membrane bioreactor to treat the wastewater. Through the ceramic membrane, the removal rate of CODCr can reach 95%. Fe-C micro-electrolysis treatment can improve the biodegradability of wastewater, lastly through the membrane bioreactor treatm...

  8. Reactor parameters for European economic, safety and environmental studies

    International Nuclear Information System (INIS)

    Hancox, R.; Cooke, P.I.H.; Spears, W.R.

    1990-01-01

    Parameter sets for five 1200 MW e tokamak reactors were developed for the European Study Group on the Environmental, Safety-related and Economic Potential of Fusion Power, showing today's perception of the range of reactors likely to be available as a result of the Commission's fusion programme. On the basis of the cost of generating electricity, relative to a fission reactor, a reference set was chosen and endorsed by the Group for further studies including that on the environmental impact of fusion power. Key physics and technology parameters for the reference reactor are compared with values used in the ITER design, and with those from American studies. (author)

  9. A study on ultra-precision machining technique for Al6061-T6 to fabricate space infrared optics

    Science.gov (United States)

    Ryu, Geun-man; Lee, Gil-jae; Hyun, Sang-won; Sung, Ha-yeong; Chung, Euisik; Kim, Geon-hee

    2014-08-01

    In this paper, analysis of variance on designed experiments with full factorial design was applied to determine the optimized machining parameters for ultra-precision fabrication of the secondary aspheric mirror, which is one of the key elements of the space cryogenic infrared optics. A single point diamond turning machine (SPDTM, Nanotech 4μpL Moore) was adopted to fabricate the material, AL6061-T6, and the three machining parameters of cutting speed, feed rate and depth of cut were selected. With several randomly assigned experimental conditions, surface roughness of each condition was measured by a non-contact optical profiler (NT2000; Vecco). As a result of analysis using Minitab, the optimum cutting condition was determined as following; cutting speed: 122 m/min, feed rate: 3 mm/min and depth of cut: 1 μm. Finally, a 120 mm diameter aspheric secondary mirror was attached to a particularly designed jig by using mixture of paraffin and wax and successfully fabricated under the optimum machining parameters. The profile of machined surface was measured by a high-accuracy 3-D profilometer(UA3P; Panasonic) and we obtained the geometrical errors of 30.6 nm(RMS) and 262.4 nm(PV), which satisfy the requirements of the space cryogenic infrared optics.

  10. Study on the Energetic Parameters in a Photothermic Sensor with ...

    African Journals Online (AJOL)

    Study on the Energetic Parameters in a Photothermic Sensor with Black Polymeric Film. ... The evolution of incidental solar illumination on the horizontal plan of sensor and the temperature distribution are studied. Results showed that the ... Keywords: film, solar energy, greenhouse effect, design, radiation, illumination.

  11. Using machine-coded event data for the micro-level study of political violence

    Directory of Open Access Journals (Sweden)

    Jesse Hammond

    2014-07-01

    Full Text Available Machine-coded datasets likely represent the future of event data analysis. We assess the use of one of these datasets—Global Database of Events, Language and Tone (GDELT—for the micro-level study of political violence by comparing it to two hand-coded conflict event datasets. Our findings indicate that GDELT should be used with caution for geo-spatial analyses at the subnational level: its overall correlation with hand-coded data is mediocre, and at the local level major issues of geographic bias exist in how events are reported. Overall, our findings suggest that due to these issues, researchers studying local conflict processes may want to wait for a more reliable geocoding method before relying too heavily on this set of machine-coded data.

  12. A numerical study of non-linear crack tip parameters

    Directory of Open Access Journals (Sweden)

    F.V. Antunes

    2015-07-01

    Full Text Available Crack closure concept has been widely used to explain different issues of fatigue crack propagation. However, different authors have questioned the relevance of crack closure and have proposed alternative concepts. The main objective here is to check the effectiveness of crack closure concept by linking the contact of crack flanks with non-linear crack tip parameters. Accordingly, 3D-FE numerical models with and without contact were developed for a wide range of loading scenarios and the crack tip parameters usually linked to fatigue crack growth, namely range of cyclic plastic strain, crack tip opening displacement, size of reversed plastic zone and total plastic dissipation per cycle, were investigated. It was demonstrated that: i LEFM concepts are applicable to the problem under study; ii the crack closure phenomenon has a great influence on crack tip parameters decreasing their values; iii the Keff concept is able to explain the variations of crack tip parameters produced by the contact of crack flanks; iv the analysis of remote compliance is the best numerical parameter to quantify the crack opening level; v without contact there is no effect of stress ratio on crack tip parameters. Therefore it is proved that the crack closure concept is valid.

  13. Machinability of advanced materials

    CERN Document Server

    Davim, J Paulo

    2014-01-01

    Machinability of Advanced Materials addresses the level of difficulty involved in machining a material, or multiple materials, with the appropriate tooling and cutting parameters.  A variety of factors determine a material's machinability, including tool life rate, cutting forces and power consumption, surface integrity, limiting rate of metal removal, and chip shape. These topics, among others, and multiple examples comprise this research resource for engineering students, academics, and practitioners.

  14. Job Stress Risk Factors Among Power Generation and Machine Production Employees: A Case Study-2010

    OpenAIRE

    Z. Naghavi; M.R. Hajgholami; Y. Shokoohi; F. Zayeri

    2013-01-01

    Background and Objective: Job stress has been adverse effects on performance, quality of work, absents, unsafe behaviors and occupational accidents and also health problems. Risk factors of job stress can be different in various workplaces. Risk factors determination is the first step of job stress management. Identifying these risk factors among workers of Power production & Machine production industries was the aim of this study. Methods: First parts of Osipow questionnaire was used for ...

  15. Can Machines Learn Respiratory Virus Epidemiology?: A Comparative Study of Likelihood-Free Methods for the Estimation of Epidemiological Dynamics

    Directory of Open Access Journals (Sweden)

    Heidi L. Tessmer

    2018-03-01

    Full Text Available To estimate and predict the transmission dynamics of respiratory viruses, the estimation of the basic reproduction number, R0, is essential. Recently, approximate Bayesian computation methods have been used as likelihood free methods to estimate epidemiological model parameters, particularly R0. In this paper, we explore various machine learning approaches, the multi-layer perceptron, convolutional neural network, and long-short term memory, to learn and estimate the parameters. Further, we compare the accuracy of the estimates and time requirements for machine learning and the approximate Bayesian computation methods on both simulated and real-world epidemiological data from outbreaks of influenza A(H1N1pdm09, mumps, and measles. We find that the machine learning approaches can be verified and tested faster than the approximate Bayesian computation method, but that the approximate Bayesian computation method is more robust across different datasets.

  16. Study of cutting speed on surface roughness and chip formation when machining nickel-based alloy

    International Nuclear Information System (INIS)

    Khidhir, Basim A.; Mohamed, Bashir

    2010-01-01

    Nickel- based alloy is difficult-to-machine because of its low thermal diffusive property and high strength at higher temperature. The machinability of nickel- based Hastelloy C-276 in turning operations has been carried out using different types of inserts under dry conditions on a computer numerical control (CNC) turning machine at different stages of cutting speed. The effects of cutting speed on surface roughness have been investigated. This study explores the types of wear caused by the effect of cutting speed on coated and uncoated carbide inserts. In addition, the effect of burr formation is investigated. The chip burr is found to have different shapes at lower speeds. Triangles and squares have been noticed for both coated and uncoated tips as well. The conclusion from this study is that the transition from thick continuous chip to wider discontinuous chip is caused by different types of inserts. The chip burr has a significant effect on tool damage starting in the line of depth-of-cut. For the coated insert tips, the burr disappears when the speed increases to above 150 m/min with the improvement of surface roughness; increasing the speed above the same limit for uncoated insert tips increases the chip burr size. The results of this study showed that the surface finish of nickel-based alloy is highly affected by the insert type with respect to cutting speed changes and its effect on chip burr formation and tool failure

  17. PRELIMINARY STUDY OF HEMATOLOGICAL PARAMETERS IN HERZEGOVINIAN DONKEY

    Directory of Open Access Journals (Sweden)

    Dunja Rukavina

    2016-02-01

    Full Text Available Herzegovinian donkey is a very important animal resource of Bosnia and Herzegovina. There have been no works attempted at determining the normal values of hematological parameters of Herzegovinian donkey. For this reason, the objective of the present study was to investigate some hematological parameters in Herzegovinian donkey. The research was performed on 30 apparently healthy donkeys (18 female and 12 male of ages from 1 to 20 years. Blood samples (3 ml were obtained by jugular vein puncture (vena jugularis externa in vacuum tubes with EDTA. The mean value of hematocrit was 29.19 %, hemoglobin concentration 10.6 g/dl, mean corpuscular hemoglobin concentration 36.33 g/dl, white blood cells 9.33 x109/L, granulocytes (109/L 5.45 x109/L, granulocytes (% 59.47%, lymphocyte/monocyte (109/L 3.89 x109/L, lymphocyte/monocyte (% 40.53% and platelet cells 148.97 x109/L. Parameters were determined using an automated analyzer IDEXX QBC VET AutoRead. Data were analyzed by SPSS V 15. All hematological parameters (except platelet cells were consistent with the recommended reference ranges for donkeys, and the values found in literature so far. Platelet cells values were much lower than in the literature for the other donkey breeds and the recommended reference ranges for donkeys. The slight differences found between our results and those reported in the previous works confirm the need for further studies to investigate the reference values of hematological parameters of Herzegovinian donkey. This work is a contribution to the study of hematological parameters of Herzegovinian donkey, and we expect these data to be applied to the further studies.

  18. A study on the machining parameters optimization of micro-end ...

    African Journals Online (AJOL)

    user

    industry one of the trends is to manufacture low cost product in short time. MRR which indicates ... electronics, environmental, communications and automotive. ... characterization of surface quality for the micro end milling process. Wang et al.

  19. Geological Hazards analysis in Urban Tunneling by EPB Machine (Case study: Tehran subway line 7 tunnel

    Directory of Open Access Journals (Sweden)

    Hassan Bakhshandeh Amnieh

    2016-06-01

    Full Text Available Technological progress in tunneling has led to modern and efficient tunneling methods in vast underground spaces even under inappropriate geological conditions. Identification and access to appropriate and sufficient geological hazard data are key elements to successful construction of underground structures. Choice of the method, excavation machine, and prediction of suitable solutions to overcome undesirable conditions depend on geological studies and hazard analysis. Identifying and investigating the ground hazards in excavating urban tunnels by an EPB machine could augment the strategy for improving soil conditions during excavation operations. In this paper, challenges such as geological hazards, abrasion of the machine cutting tools, clogging around these tools and inside the chamber, diverse work front, severe water level fluctuations, existence of water, and fine-grained particles in the route were recognized in a study of Tehran subway line 7, for which solutions such as low speed boring, regular cutter head checks, application of soil improving agents, and appropriate grouting were presented and discussed. Due to the presence of fine particles in the route, foam employment was suggested as the optimum strategy where no filler is needed.

  20. Study of Cutting Edge Temperature and Cutting Force of End Mill Tool in High Speed Machining

    Directory of Open Access Journals (Sweden)

    Kiprawi Mohammad Ashaari

    2017-01-01

    Full Text Available A wear of cutting tools during machining process is unavoidable due to the presence of frictional forces during removing process of unwanted material of workpiece. It is unavoidable but can be controlled at slower rate if the cutting speed is fixed at certain point in order to achieve optimum cutting conditions. The wear of cutting tools is closely related with the thermal deformations that occurred between the frictional contact point of cutting edge of cutting tool and workpiece. This research paper is focused on determinations of relationship among cutting temperature, cutting speed, cutting forces and radial depth of cutting parameters. The cutting temperature is determined by using the Indium Arsenide (InAs and Indium Antimonide (InSb photocells to measure infrared radiation that are emitted from cutting tools and cutting forces is determined by using dynamometer. The high speed machining process is done by end milling the outer surface of carbon steel. The signal from the photocell is digitally visualized in the digital oscilloscope. Based on the results, the cutting temperature increased as the radial depth and cutting speed increased. The cutting forces increased when radial depth increased but decreased when cutting speed is increased. The setup for calibration and discussion of the experiment will be explained in this paper.

  1. A Numerical Study of the Spring-Back Phenomenon in Bending with a Rebar Bending Machine

    Directory of Open Access Journals (Sweden)

    Chang Hwan Choi

    2014-10-01

    Full Text Available Recently, the rebar bending methodology started to change from field processing to utilizing rebar bending machines at plant sites prior to transport to the construction locations. Computerized control of rebar plant bending machines provides more accurate and faster bending of rebars than the low quality inefficient field processing alternative. The bending process involves plastic deformation of rebars, where bending stress beyond the yield point of the material is applied. When the bending stress is removed, spring back is caused by the elastic restoring stress. Therefore, an accurate numerical analysis of the spring-back process is required to reduce the bending process errors. The most sensitive factors affecting the spring-back process are the bending radius, the bending angle, the diameter of the rebar, the friction coefficient, and the yielding strength of material. In this paper, we suggest a numerical modeling method using these factors. The finite element modeling of the dynamic mechanical behavior of the material during bending is performed using a commercial dynamic analysis program “DAFUL.” We use the least squares approach to derive the spring-back deflection as a function of the rebar bending parameters.

  2. The normative study of acoustic parameters in normal Egyptian ...

    African Journals Online (AJOL)

    Yehia A. Abo-Ras

    2013-03-21

    Mar 21, 2013 ... all children were subjected to computerized acoustic analysis using Multidimensional voice program ... cal quality is important for social relations to happen effectively. ... lish comparative parameters with the normal values of the acoustic ... from lower age ranges in the normative studies since the child's.

  3. Developing the Parameters of Scholarship in Postgraduate Coursework Studies

    Science.gov (United States)

    McLay, Allan F.

    2013-01-01

    Scholarship parameters, in relation to postgraduate coursework studies, are developed against the expectations of the Boyer classifications of scholarship (Boyer, 1990) with particular emphasis on the role of minor thesis development. An example is presented in which postgraduate coursework students are required to undertake a three semester minor…

  4. Machining of uranium and uranium alloys

    International Nuclear Information System (INIS)

    Morris, T.O.

    1981-01-01

    Uranium and uranium alloys can be readily machined by conventional methods in the standard machine shop when proper safety and operating techniques are used. Material properties that affect machining processes and recommended machining parameters are discussed. Safety procedures and precautions necessary in machining uranium and uranium alloys are also covered. 30 figures

  5. Parameters of importance to determine in geoscientific site studies

    International Nuclear Information System (INIS)

    Andersson, Johan; Almen, K.E.; Ericsson, L.O.; Karlsson, Fred; Stroem, A.; Fredriksson, Anders; Stanfors, R.

    1996-12-01

    This report identifies and describes parameters, that may be determined in a site characterization study, for performing functional and safety analyses of a deep rock repository for radioactive wastes. The report discusses data needs for rock engineering and for description of other environmental aspects. It is intended that the report be used as a basis for formulating the criteria of acceptance in evaluating a candidate site. The report describes how different parameters influence the safety function, and how they are evaluated in practice. The logical order of performing measurements, due to the need of in-data and influence on other measurements is also discussed. 65 refs

  6. Comparitive study of the influence of harmonic voltage distortion on the efficiency of induction machines versus line start permanent magnet machines

    OpenAIRE

    Debruyne, Colin; Derammelaere, Stijn; Desmet, Jan; Vandevelde, Lieven

    2012-01-01

    Induction machines have nearly reached their maximal efficiency. In order to further increase the efficiency the use of permanent magnets in combination with the robust design of the induction machine is being extensively researched. These so-called line start permanent magnet machines have an increased efficiency in sine wave conditions in respect to standard induction machines, however the efficiency of these machines is less researched under distorted voltage conditions. This paper compare...

  7. Study on intelligent processing system of man-machine interactive garment frame model

    Science.gov (United States)

    Chen, Shuwang; Yin, Xiaowei; Chang, Ruijiang; Pan, Peiyun; Wang, Xuedi; Shi, Shuze; Wei, Zhongqian

    2018-05-01

    A man-machine interactive garment frame model intelligent processing system is studied in this paper. The system consists of several sensor device, voice processing module, mechanical parts and data centralized acquisition devices. The sensor device is used to collect information on the environment changes brought by the body near the clothes frame model, the data collection device is used to collect the information of the environment change induced by the sensor device, voice processing module is used for speech recognition of nonspecific person to achieve human-machine interaction, mechanical moving parts are used to make corresponding mechanical responses to the information processed by data collection device.it is connected with data acquisition device by a means of one-way connection. There is a one-way connection between sensor device and data collection device, two-way connection between data acquisition device and voice processing module. The data collection device is one-way connection with mechanical movement parts. The intelligent processing system can judge whether it needs to interact with the customer, realize the man-machine interaction instead of the current rigid frame model.

  8. Application of Machine Learning Algorithms to the Study of Noise Artifacts in Gravitational-Wave Data

    Science.gov (United States)

    Biswas, Rahul; Blackburn, Lindy L.; Cao, Junwei; Essick, Reed; Hodge, Kari Alison; Katsavounidis, Erotokritos; Kim, Kyungmin; Young-Min, Kim; Le Bigot, Eric-Olivier; Lee, Chang-Hwan; hide

    2014-01-01

    The sensitivity of searches for astrophysical transients in data from the Laser Interferometer Gravitationalwave Observatory (LIGO) is generally limited by the presence of transient, non-Gaussian noise artifacts, which occur at a high-enough rate such that accidental coincidence across multiple detectors is non-negligible. Furthermore, non-Gaussian noise artifacts typically dominate over the background contributed from stationary noise. These "glitches" can easily be confused for transient gravitational-wave signals, and their robust identification and removal will help any search for astrophysical gravitational-waves. We apply Machine Learning Algorithms (MLAs) to the problem, using data from auxiliary channels within the LIGO detectors that monitor degrees of freedom unaffected by astrophysical signals. Terrestrial noise sources may manifest characteristic disturbances in these auxiliary channels, inducing non-trivial correlations with glitches in the gravitational-wave data. The number of auxiliary-channel parameters describing these disturbances may also be extremely large; high dimensionality is an area where MLAs are particularly well-suited. We demonstrate the feasibility and applicability of three very different MLAs: Artificial Neural Networks, Support Vector Machines, and Random Forests. These classifiers identify and remove a substantial fraction of the glitches present in two very different data sets: four weeks of LIGO's fourth science run and one week of LIGO's sixth science run. We observe that all three algorithms agree on which events are glitches to within 10% for the sixth science run data, and support this by showing that the different optimization criteria used by each classifier generate the same decision surface, based on a likelihood-ratio statistic. Furthermore, we find that all classifiers obtain similar limiting performance, suggesting that most of the useful information currently contained in the auxiliary channel parameters we extract

  9. Monte Carlo parameter studies and uncertainty analyses with MCNP5

    International Nuclear Information System (INIS)

    Brown, F. B.; Sweezy, J. E.; Hayes, R.

    2004-01-01

    A software tool called mcnp p study has been developed to automate the setup, execution, and collection of results from a series of MCNP5 Monte Carlo calculations. This tool provides a convenient means of performing parameter studies, total uncertainty analyses, parallel job execution on clusters, stochastic geometry modeling, and other types of calculations where a series of MCNP5 jobs must be performed with varying problem input specifications. (authors)

  10. Study of pipe-whip parameters in pipelines

    International Nuclear Information System (INIS)

    Guerreiro, J.N.C.; Loula, A.F.D.; Galeao, A.C.N.R.

    1980-01-01

    The problem of the high energy pipe-whip, assuming an elastic-plastic behavior for the tube material and taking in account the internal pressure, is studied. The constraints are simulated as bilinear springs and viscous dampers. A general research, based on the finite element method was developed to analyse the phenomenon. The influence of the following parameters: gap, damping coefficient, stiffness, constraints positioning and internal pressure of the tube is studied. (Author) [pt

  11. Experimental Studies of the Transport Parameters of Warm Dense Matter

    Energy Technology Data Exchange (ETDEWEB)

    Chouffani, Khalid [Idaho State Univ., Pocatello, ID (United States)

    2014-12-01

    There is a need to establish fundamental properties of matter and energy under extreme physical conditions. Although high energy density physics (HEDP) research spans a wide range of plasma conditions, there is one unifying regime that is of particular importance and complexity: that of warm dense matter, the transitional state between solid state condensed matter and energetic plasmas. Most laboratory experimental conditions, including inertial confinement implosion, fall into this regime. Because all aspects of laboratory-created high-energy-density plasmas transition through the warm dense matter regime, understanding the fundamental properties to determine how matter and energy interact in this regime is an important aspect of major research efforts in HEDP. Improved understanding of warm dense matter would have significant and wide-ranging impact on HEDP science, from helping to explain wire initiation studies on the Sandia Z machine to increasing the predictive power of inertial confinement fusion modeling. The central goal or objective of our proposed research is to experimentally determine the electrical resistivity, temperature, density, and average ionization state of a variety of materials in the warm dense matter regime, without the use of theoretical calculations. Since the lack of an accurate energy of state (EOS) model is primarily due to the lack of experimental data, we propose an experimental study of the transport coefficients of warm dense matter.

  12. Machine Shop Grinding Machines.

    Science.gov (United States)

    Dunn, James

    This curriculum manual is one in a series of machine shop curriculum manuals intended for use in full-time secondary and postsecondary classes, as well as part-time adult classes. The curriculum can also be adapted to open-entry, open-exit programs. Its purpose is to equip students with basic knowledge and skills that will enable them to enter the…

  13. The study of optimization on process parameters of high-accuracy computerized numerical control polishing

    Science.gov (United States)

    Huang, Wei-Ren; Huang, Shih-Pu; Tsai, Tsung-Yueh; Lin, Yi-Jyun; Yu, Zong-Ru; Kuo, Ching-Hsiang; Hsu, Wei-Yao; Young, Hong-Tsu

    2017-09-01

    Spherical lenses lead to forming spherical aberration and reduced optical performance. Consequently, in practice optical system shall apply a combination of spherical lenses for aberration correction. Thus, the volume of the optical system increased. In modern optical systems, aspherical lenses have been widely used because of their high optical performance with less optical components. However, aspherical surfaces cannot be fabricated by traditional full aperture polishing process due to their varying curvature. Sub-aperture computer numerical control (CNC) polishing is adopted for aspherical surface fabrication in recent years. By using CNC polishing process, mid-spatial frequency (MSF) error is normally accompanied during this process. And the MSF surface texture of optics decreases the optical performance for high precision optical system, especially for short-wavelength applications. Based on a bonnet polishing CNC machine, this study focuses on the relationship between MSF surface texture and CNC polishing parameters, which include feed rate, head speed, track spacing and path direction. The power spectral density (PSD) analysis is used to judge the MSF level caused by those polishing parameters. The test results show that controlling the removal depth of single polishing path, through the feed rate, and without same direction polishing path for higher total removal depth can efficiently reduce the MSF error. To verify the optical polishing parameters, we divided a correction polishing process to several polishing runs with different direction polishing paths. Compare to one shot polishing run, multi-direction path polishing plan could produce better surface quality on the optics.

  14. Characterization and modeling of 2D-glass micro-machining by spark-assisted chemical engraving (SACE) with constant velocity

    International Nuclear Information System (INIS)

    Didar, Tohid Fatanat; Dolatabadi, Ali; Wüthrich, Rolf

    2008-01-01

    Spark-assisted chemical engraving (SACE) is an unconventional micro-machining technology based on electrochemical discharge used for micro-machining nonconductive materials. SACE 2D micro-machining with constant speed was used to machine micro-channels in glass. Parameters affecting the quality and geometry of the micro-channels machined by SACE technology with constant velocity were presented and the effect of each of the parameters was assessed. The effect of chemical etching on the geometry of micro-channels under different machining conditions has been studied, and a model is proposed for characterization of the micro-channels as a function of machining voltage and applied speed

  15. Machining of Machine Elements Made of Polymer Composite Materials

    Science.gov (United States)

    Baurova, N. I.; Makarov, K. A.

    2017-12-01

    The machining of the machine elements that are made of polymer composite materials (PCMs) or are repaired using them is considered. Turning, milling, and drilling are shown to be most widely used among all methods of cutting PCMs. Cutting conditions for the machining of PCMs are presented. The factors that most strongly affect the roughness parameters and the accuracy of cutting PCMs are considered.

  16. Parameter studies for a two-component fusion experiment

    International Nuclear Information System (INIS)

    Towner, H.H.

    1975-01-01

    The sensitivity of the energy multiplication of a two-component fusion experiment is examined relative to the following parameters: energy confinement time (tau/sub E/), particle confinement time (tau/sub p/), effective Z of the plasma (Z/sub eff/), injection rate (j/sub I/) and injection energy (E/sub I/). The Energy Research and Development Administration recently approved funding for such a fusion device (the Toroidal Fusion Test Reactor or TFTR) which will be built at the Princeton Plasma Physics Laboratory. Hence, such a parameter study seems both timely and necessary. This work also serves as an independent check on the design values proposed for the TFTR to enable it to achieve energy breakeven (F = 1). Using the nominal TFTR design parameters and a self-consistent ion-electron power balance, the maximum F-value is found to be approximately 1.2 which occurs at an injection energy of approximately 210 KeV. The injector operation, i.e. its current and energy capability are shown to be a very critical factor in the TFTR performance. However, if the injectors meet the design objectives, there appears to be sufficient latitude in the other parameters to offer reasonable assurance that energy breakeven can be achieved. (U.S.)

  17. Shielding study of a fusion machine. Elaboration of a global shielding calculation scheme for the Tokamak tore Supra

    International Nuclear Information System (INIS)

    Diop, C.M'B.

    1984-01-01

    This thesis presents a global shielding calculation scheme for neutron and gamma rays arising from the Tokamak TORE SUPRA fusion device, in which a deuterium plasma is used. To study the shield parameters we have elabored a important chaining of neutron and gamma transport codes, TRIPOLI, ANISN, MERCURE 4, allowing to evaluate the radial and skyshine components of the dose rate behind the concrete shield. The study of thermonuclear neutron activation is fundamental to define a tokamak exploitation strategy. For this, two formalisme have been developed. They are based on a modelization of the activation reaction rates according to TRIPOLI, ANISN, and MERCURE 4 codes capabilities. The first one calculates, in one dimensional geometry, the desactivation gamma dose rate inside the vacuum chamber. The second one is a tridimensional model which determines the spatial variation of the gamma dose rate in the machine room. The problem of the existence of runaway electrons and associated secondaries radiations, bremsstrahlung gamma rays particularly, is approched. The results which are presented have contributed to define the parameters of the concrete shield and a strategy for TORE SUPRA Tokamak exploitation [fr

  18. Nuclear Criticality Technology and Safety Project parameter study database

    International Nuclear Information System (INIS)

    Toffer, H.; Erickson, D.G.; Samuel, T.J.; Pearson, J.S.

    1993-03-01

    A computerized, knowledge-screened, comprehensive database of the nuclear criticality safety documentation has been assembled as part of the Nuclear Criticality Technology and Safety (NCTS) Project. The database is focused on nuclear criticality parameter studies. The database has been computerized using dBASE III Plus and can be used on a personal computer or a workstation. More than 1300 documents have been reviewed by nuclear criticality specialists over the last 5 years to produce over 800 database entries. Nuclear criticality specialists will be able to access the database and retrieve information about topical parameter studies, authors, and chronology. The database places the accumulated knowledge in the nuclear criticality area over the last 50 years at the fingertips of a criticality analyst

  19. Geotechnical parameters for three deep ocean study areas

    International Nuclear Information System (INIS)

    Nicholson, D.P.

    1989-01-01

    This chapter summarizes the results of geotechnical measurements made on cores taken at the three deep ocean sites that have been studied in detail as part of the international programme assessing the feasibility of deep ocean disposal of heat-generating radioactive waste. The capabilities of existing sampling methods and the adequacy of the available data for providing the geotechnical parameters needed to evaluate the technical feasibility of deep ocean disposal are discussed. It is concluded that, while it has not been possible to obtain core samples of sufficient quality and depth to provide all the parameters needed for the assessment, no fundamental differences between the sediments at the study areas and those found on land or in shallow water have been identified. (author)

  20. Identifying product order with restricted Boltzmann machines

    Science.gov (United States)

    Rao, Wen-Jia; Li, Zhenyu; Zhu, Qiong; Luo, Mingxing; Wan, Xin

    2018-03-01

    Unsupervised machine learning via a restricted Boltzmann machine is a useful tool in distinguishing an ordered phase from a disordered phase. Here we study its application on the two-dimensional Ashkin-Teller model, which features a partially ordered product phase. We train the neural network with spin configuration data generated by Monte Carlo simulations and show that distinct features of the product phase can be learned from nonergodic samples resulting from symmetry breaking. Careful analysis of the weight matrices inspires us to define a nontrivial machine-learning motivated quantity of the product form, which resembles the conventional product order parameter.

  1. Economic lifetime of a drilling machine:a case study on mining industry

    OpenAIRE

    Hamodi, Hussan; Lundberg, Jan; Jonsson, Adam

    2013-01-01

    Underground mines use many different types of machinery duringthe drift mining processes of drilling, charging, blasting, loading, scaling andbolting. Drilling machines play a critical role in the mineral extraction processand thus are important economically. However, as the machines age, theirefficiency and effectiveness decrease, negatively affecting productivity andprofitability and increasing total cost. Hence, the economic replacementlifetime of the machine is a key performance indicator...

  2. Study of residual stresses generated in machining of AISI 4340 steel

    International Nuclear Information System (INIS)

    Reis, W.P. dos; Fonseca, M.P. Cindra; Serrao, L.F.; Chuvas, T.C.; Oliveira, L.C.

    2010-01-01

    Among the mechanical construction steels, AISI 4340 has good harden ability, while combining high strength with toughness and good fatigue strength, making it excellent for application in the metalworking industry, where it can work at different levels and types of requests. Residual stresses are generated in almost all processes of mechanical manufacturing. In this study, the residual stresses generated in different machining processes and heat treatment hardening of AISI 4340 were analyzed by X-ray diffraction, by the sen 2 ψ method, using Crκβ radiation and compared. All samples, except for turned and cut by EDM, presented compressive residual stresses in the surface with various magnitudes. (author)

  3. Study of some physiological parameters among mobile phone users

    International Nuclear Information System (INIS)

    Anwar, S.M.; Gabr, S.A.

    2002-01-01

    Forty male mobile users in additional to twenty males as control group similar in age and socio economically matched were chosen for this study. Blood pressure, complete blood picture, five parameters of semen quality and four sex hormones (LH, FSH, prolactin and testosterone)were measured. Elevated significant differences for blood pressure (P<0.01) for the exposed group and some changes in mean values of haematologic parameters, although all values were within the normal range. Minor semen quality and hormonal levels changes between the two groups, including a higher mean follicle-stimulating hormone level; for mobile users (8.10 vs 6.00 mIU/mL), and a slightly higher mean luteinizing hormone level (11.73 vs 10.16 mLU/mL) were noted in the user group

  4. Seismic analysis of steam generator and parameter sensitivity studies

    International Nuclear Information System (INIS)

    Qian Hao; Xu Dinggen; Yang Ren'an; Liang Xingyun

    2013-01-01

    Background: The steam generator (SG) serves as the primary means for removing the heat generated within the reactor core and is part of the reactor coolant system (RCS) pressure boundary. Purpose: Seismic analysis in required for SG, whose seismic category is Cat. I. Methods: The analysis model of SG is created with moisture separator assembly and tube bundle assembly herein. The seismic analysis is performed with RCS pipe and Reactor Pressure Vessel (RPV). Results: The seismic stress results of SG are obtained. In addition, parameter sensitivities of seismic analysis results are studied, such as the effect of another SG, support, anti-vibration bars (AVBs), and so on. Our results show that seismic results are sensitive to support and AVBs setting. Conclusions: The guidance and comments on these parameters are summarized for equipment design and analysis, which should be focused on in future new type NPP SG's research and design. (authors)

  5. The FERMI (at) Elettra Technical Optimization Study: Preliminary Parameter Set and Initial Studies

    International Nuclear Information System (INIS)

    Byrd, John; Corlett, John; Doolittle, Larry; Fawley, William; Lidia, Steven; Penn, Gregory; Ratti, Alex; Staples, John; Wilcox, Russell; Wurtele, Jonathan; Zholents, Alexander

    2005-01-01

    The goal of the FERMI (at) Elettra Technical Optimization Study is to produce a machine design and layout consistent with user needs for radiation in the approximate ranges 100 nm to 40 nm, and 40 nm to 10 nm, using seeded FEL's. The Study will involve collaboration between Italian and US physicists and engineers, and will form the basis for the engineering design and the cost estimation

  6. Statistical Machines for Trauma Hospital Outcomes Research: Application to the PRospective, Observational, Multi-Center Major Trauma Transfusion (PROMMTT Study.

    Directory of Open Access Journals (Sweden)

    Sara E Moore

    Full Text Available Improving the treatment of trauma, a leading cause of death worldwide, is of great clinical and public health interest. This analysis introduces flexible statistical methods for estimating center-level effects on individual outcomes in the context of highly variable patient populations, such as those of the PRospective, Observational, Multi-center Major Trauma Transfusion study. Ten US level I trauma centers enrolled a total of 1,245 trauma patients who survived at least 30 minutes after admission and received at least one unit of red blood cells. Outcomes included death, multiple organ failure, substantial bleeding, and transfusion of blood products. The centers involved were classified as either large or small-volume based on the number of massive transfusion patients enrolled during the study period. We focused on estimation of parameters inspired by causal inference, specifically estimated impacts on patient outcomes related to the volume of the trauma hospital that treated them. We defined this association as the change in mean outcomes of interest that would be observed if, contrary to fact, subjects from large-volume sites were treated at small-volume sites (the effect of treatment among the treated. We estimated this parameter using three different methods, some of which use data-adaptive machine learning tools to derive the outcome models, minimizing residual confounding by reducing model misspecification. Differences between unadjusted and adjusted estimators sometimes differed dramatically, demonstrating the need to account for differences in patient characteristics in clinic comparisons. In addition, the estimators based on robust adjustment methods showed potential impacts of hospital volume. For instance, we estimated a survival benefit for patients who were treated at large-volume sites, which was not apparent in simpler, unadjusted comparisons. By removing arbitrary modeling decisions from the estimation process and concentrating

  7. Machining of Molybdenum by EDM-EP and EDC Processes

    Science.gov (United States)

    Wu, K. L.; Chen, H. J.; Lee, H. M.; Lo, J. S.

    2017-12-01

    Molybdenum metal (Mo) can be machined with conventional tools and equipment, however, its refractory propertytends to chip when being machined. In this study, the nonconventional processes of electrical discharge machining (EDM) and electro-polishing (EP) have been conducted to investigate the machining of Mo metal and fabrication of Mo grid. Satisfactory surface quality was obtained using appropriate EDM parameters of Ip ≦ 3A and Ton EDMed Mo metal. Experimental results proved that the appropriate parameters of Ip = 5A and Ton = 50μs at Toff = 10μs can obtain the deposit with about 60μm thickness. The major phase of deposit on machined Mo surface was SiC ceramic, while the minor phases included MoSi2 and/or SiO2 with the presence of free Si due to improper discharging parameters and the use of silicone oil as the dielectric fluid.

  8. Electronic vending machines for dispensing rapid HIV self-testing kits: a case study.

    Science.gov (United States)

    Young, Sean D; Klausner, Jeffrey; Fynn, Risa; Bolan, Robert

    2014-02-01

    This short report evaluates the feasibility of using electronic vending machines for dispensing oral, fluid, rapid HIV self-testing kits in Los Angeles County. Feasibility criteria that needed to be addressed were defined as: (1) ability to find a manufacturer who would allow dispensing of HIV testing kits and could fit them to the dimensions of a vending machine, (2) ability to identify and address potential initial obstacles, trade-offs in choosing a machine location, and (3) ability to gain community approval for implementing this approach in a community setting. To address these issues, we contracted a vending machine company who could supply a customized, Internet-enabled machine that could dispense HIV kits and partnered with a local health center available to host the machine onsite and provide counseling to participants, if needed. Vending machines appear to be feasible technologies that can be used to distribute HIV testing kits.

  9. Variable geometry Darrieus wind machine

    Science.gov (United States)

    Pytlinski, J. T.; Serrano, D.

    1983-08-01

    A variable geometry Darrieus wind machine is proposed. The lower attachment of the blades to the rotor can move freely up and down the axle allowing the blades of change shape during rotation. Experimental data for a 17 m. diameter Darrieus rotor and a theoretical model for multiple streamtube performance prediction were used to develop a computer simulation program for studying parameters that affect the machine's performance. This new variable geometry concept is described and interrelated with multiple streamtube theory through aerodynamic parameters. The computer simulation study shows that governor behavior of a Darrieus turbine can not be attained by a standard turbine operating within normally occurring rotational velocity limits. A second generation variable geometry Darrieus wind turbine which uses a telescopic blade is proposed as a potential improvement on the studied concept.

  10. Overview of Sustainability Studies of CNC Machining and LAM of Stainless Steel

    Science.gov (United States)

    Nyamekye, Patricia; Leino, Maija; Piili, Heidi; Salminen, Antti

    Laser additive manufacturing (LAM), known also as 3D printing, is a powder bed fusion (PBF) type of additive manufacturing (AM) technology used to fabricate metal parts out of metal powder. The development of the technology from building prototype parts to functional parts has increased remarkably in 2000s. LAM of metals is promising technology that offers new opportunities to manufacturing and to resource efficiency. However, there is only few published articles about its sustainability. Aim in this study was to create supply chain model of LAM and CNC machining and create a methodology to carry out a life cycle inventory (LCI) data collection for these techniques. The methodology of the study was literature review and scenario modeling. The acquisition of raw material, production phase and transportations were used as basis of comparison. The modelled scenarios were fictitious and created for industries, like aviation and healthcare that often require swift delivery as well as customized parts. The results of this study showed that the use of LAM offers a possibility to reduce downtime in supply chains of spare parts and reduce part inventory more effectively than CNC machining. Also the gap between customers and business is possible to be shortened with LAM thus offering a possibility to reduce emissions due to less transportation. The results also indicated weight reduction possibility with LAM due to optimized part geometry which allow lesser amount of metallic powder to be used in making parts.

  11. Radiotracer study of wash load movement in a drum-type fabric washing machine using a gamma camera

    Energy Technology Data Exchange (ETDEWEB)

    Balt, A.P.; Brekel, L.D.M. van den; Vandecasteele, C.; Kolar, Z.

    1987-01-01

    A study was made of the movement of the wash loads in a drum-type washing machine. For this purpose a sup(99m)Tc source was attached to one or two separate textile pieces and the subsequent source positions were determined by means of a gamma-camera. The wash load movement pattern appears to depend on the type of textile material and its amount, as well as on the volume of water present in the washing machine.

  12. Radiotracer study of wash load movement in a drum-type fabric washing machine using a gamma camera

    International Nuclear Information System (INIS)

    Balt, A.P.; Brekel, L.D.M. van den; Vandecasteele, C.; Kolar, Z.

    1987-01-01

    A study was made of the movement of the wash loads in a drum-type washing machine. For this purpose a sup(99m)Tc source was attached to one or two separate textile pieces and the subsequent source positions were determined by means of a gamma-camera. The wash load movement pattern appears to depend on the type of textile material and its amount, as well as on the volume of water present in the washing machine. (author)

  13. POPULATION SYNTHESIS OF HOT SUBDWARFS: A PARAMETER STUDY

    International Nuclear Information System (INIS)

    Clausen, Drew; Wade, Richard A.; Kopparapu, Ravi Kumar; O'Shaughnessy, Richard

    2012-01-01

    Binaries that contain a hot subdwarf (sdB) star and a main-sequence companion may have interacted in the past. This binary population has historically helped determine our understanding of binary stellar evolution. We have computed a grid of binary population synthesis models using different assumptions about the minimum core mass for helium ignition, the envelope binding energy, the common-envelope ejection efficiency, the amount of mass and angular momentum lost during stable mass transfer, and the criteria for stable mass transfer on the red giant branch and in the Hertzsprung gap. These parameters separately and together can significantly change the entire predicted population of sdBs. Nonetheless, several different parameter sets can reproduce the observed subpopulation of sdB + white dwarf and sdB + M dwarf binaries, which has been used to constrain these parameters in previous studies. The period distribution of sdB + early F dwarf binaries offers a better test of different mass transfer scenarios for stars that fill their Roche lobes on the red giant branch.

  14. Study of Temperature Coefficients for Parameters of Photovoltaic Cells

    Directory of Open Access Journals (Sweden)

    Daniel Tudor Cotfas

    2018-01-01

    Full Text Available The temperature is one of the most important factors which affect the performance of the photovoltaic cells and panels along with the irradiance. The current voltage characteristics, I-V, are measured at different temperatures from 25°C to 87°C and at different illumination levels from 400 to 1000 W/m2, because there are locations where the upper limit of the photovoltaic cells working temperature exceeds 80°C. This study reports the influence of the temperature and the irradiance on the important parameters of four commercial photovoltaic cell types: monocrystalline silicon—mSi, polycrystalline silicon—pSi, amorphous silicon—aSi, and multijunction InGaP/InGaAs/Ge (Emcore. The absolute and normalized temperature coefficients are determined and compared with their values from the related literature. The variation of the absolute temperature coefficient function of the irradiance and its significance to accurately determine the important parameters of the photovoltaic cells are also presented. The analysis is made on different types of photovoltaics cells in order to understand the effects of technology on temperature coefficients. The comparison between the open-circuit voltage and short-circuit current was also performed, calculated using the temperature coefficients, determined, and measured, in various conditions. The measurements are realized using the SolarLab system, and the photovoltaic cell parameters are determined and compared using the LabVIEW software created for SolarLab system.

  15. EXPERIMENTAL INVESTIGATION OF THE EFFECT OF MACHINIG PARAMETERS OVER CUTTING FORCE AND SURFACE ROUGHNESS IN THE MACHINABILITY OF AA5052 ALLOY

    Directory of Open Access Journals (Sweden)

    Hasan GÖKKAYA

    2006-03-01

    Full Text Available In this study, the effects of different cutting and feed rates over average surface roughness and main cutting force during the machinability of AA5052 aluminum alloy with uncoated cemented carbide insert were evaluated. In the experiments, stable depth of cut (1.5 mm, four different cutting speeds (200, 300, 400, 500 m/min and five different feed rates (0.10, 0.15, 0.20, 0.25, 0.30 mm/rev were used. Based on cutting and feed rates, the lowest main cutting force was obtained as 113 in 500 m/min cutting speed and 0.10 mm/rev feed rate and the highest cutting force was obtained as 332 N in 200 m/min cutting speed and 0.30 mm/rev feed rate. The lowest average surface roughness was obtained as 0.95 µm in 200 m/min cutting speed and 0.10 mm/rev feed rate and the highest average surface roughness was obtained as 6.65 µm in 300 m/min cutting speed and 0.30 mm/rev feed rate.

  16. Impedance Mismatch study between the Microwave Generator and the PUPR Plasma Machine

    International Nuclear Information System (INIS)

    Gaudier, Jorge R.; Castellanos, Ligeia; Encarnacion, Kabir; Zavala, Natyaliz; Rivera, Ramon; Farahat, Nader; Leal, Edberto

    2006-01-01

    Impedance mismatch inside the connection from the microwave power generator to the plasma machine is studied. A magnetron power generator transmits microwaves of 2.45 GHz and variable power from 50W to 5000W, through a flexible rectangular waveguide to heat plasma inside a Mirror Cusp devise located at the Polytechnic University of Puerto Rico. Before the production of plasma, the residual gas of the devise must be extracted by a vacuum system (5Torr or better), then Argon gas is injected to the machine. The microwaves heat the Argon ions to initiate ionization and plasma is produced. A dielectric wall is used inside the rectangular waveguide to isolate the plasma machine and maintain vacuum. Even though the dielectric will not block the wave propagation, some absorption of microwaves will occur. This absorption will cause reflection, reducing the efficiency of the power transfer. Typically a thin layer of Teflon is used, but measurements using this dielectric show a significant reflection of power back to the generator. Due to the high-power nature of the generator (5KW), this mismatch is not desirable. An electromagnetic field solver based on the Finite Difference Time Domain Method(FDTD) is used to model the rectangular waveguide connection. The characteristic impedance of the simulation is compared with the analytical formula expression and a good agreement is obtain. Furthermore the Teflon-loaded guide is modeled using the above program and the input impedance is computed. The reflection coefficient is calculated based on the transmission line theory with the characteristic and input impedances. Based on the simulation results it is possible to optimize the thickness, shape and dielectric constant of the material, in order to seal the connection with a better match

  17. Study on parameter identification and control of ground temperature

    International Nuclear Information System (INIS)

    Kojima, Keiichi; Suzuki, Seiichi; Kawahara, Mutsuto.

    1995-01-01

    A numerical thermal management system for ground structure is presented. The system consists of two parts, i.e. the identification analysis of the thermal conductivity and the thermal control analysis for the ground. The former is carried out by using the nonlinear least squares method and the latter is based on the optimal control theory. The formulations of these methods are presented and they are applied to an laboratory test. A reasonable thermal conductivity of the ground is identified by parameter estimation method and the ground temperature is actually controled as illustrated by numerical and experimental study. (author)

  18. Studying the noise parameters of thin-film silicon resistors

    International Nuclear Information System (INIS)

    Belogurov, S.V.; Gostilo, V.V.; Yurov, A.S.

    1986-01-01

    The results of studies on spectral density and energy noise equivalent of thin-film resistors on the base of amorphous silicon and KIM and KVM commercial high-ohmic resistors are presented. Dependence of the active part of impedance on frequency is shown to be the main source of redundant noise in resistors. Dependence of spectral density of noise voltage of current noises of silicon resistors on applied voltage is described by the formula S T =B V 2 /f 1.6 with the values B=(1.4-1.7)x10 -12 Hz 0.6 . As to noise parameters the silicon resistor is superior to commercial resistors

  19. Study of nuclear level density parameter and its temperature dependence

    International Nuclear Information System (INIS)

    Nasrabadi, M. N.; Behkami, A. N.

    2000-01-01

    The nuclear level density ρ is the basic ingredient required for theoretical studies of nuclear reaction and structure. It describes the statistical nuclear properties and is expressed as a function of various constants of motion such as number of particles, excitation energy and angular momentum. In this work the energy and spin dependence of nuclear level density will be presented and discussed. In addition the level density parameter α will be extracted from this level density information, and its temperature and mass dependence will be obtained

  20. Characterizing parameters of Jatropha curcas cell cultures for microgravity studies

    Science.gov (United States)

    Vendrame, Wagner A.; Pinares, Ania

    2013-06-01

    Jatropha (Jatropha curcas) is a tropical perennial species identified as a potential biofuel crop. The oil is of excellent quality and it has been successfully tested as biodiesel and in jet fuel mixes. However, studies on breeding and genetic improvement of jatropha are limited. Space offers a unique environment for experiments aiming at the assessment of mutations and differential gene expression of crops and in vitro cultures of plants are convenient for studies of genetic variation as affected by microgravity. However, before microgravity studies can be successfully performed, pre-flight experiments are necessary to characterize plant material and validate flight hardware environmental conditions. Such preliminary studies set the ground for subsequent spaceflight experiments. The objectives of this study were to compare the in vitro growth of cultures from three explant sources (cotyledon, leaf, and stem sections) of three jatropha accessions (Brazil, India, and Tanzania) outside and inside the petriGAP, a modified group activation pack (GAP) flight hardware to fit petri dishes. In vitro jatropha cell cultures were established in petri dishes containing a modified MS medium and maintained in a plant growth chamber at 25 ± 2 °C in the dark. Parameters evaluated were surface area of the explant tissue (A), fresh weight (FW), and dry weight (DW) for a period of 12 weeks. Growth was observed for cultures from all accessions at week 12, including subsequent plantlet regeneration. For all accessions differences in A, FW and DW were observed for inside vs. outside the PetriGAPs. Growth parameters were affected by accession (genotype), explant type, and environment. The type of explant influenced the type of cell growth and subsequent plantlet regeneration capacity. However, overall cell growth showed no abnormalities. The present study demonstrated that jatropha in vitro cell cultures are suitable for growth inside PetriGAPs for a period of 12 weeks. The parameters

  1. Characterizing the Effects of Micro Electrical Discharge Machining Parameters on Material Removal Rate during Micro EDM Drilling of Tungsten Carbide (WC-Co)

    Science.gov (United States)

    Hourmand, Mehdi; Sarhan, Ahmed A. D.; Sayuti, Mohd

    2017-10-01

    Micro-dies, molds and miniaturized products can be manufactured using micro EDM process. In this research, EDM machine and on-machine fabricated CuW micro-electrode were utilized to produce the micro holes in WC-16%Co. The effects of voltage, current, pulse ON time, pulse OFF time, capacitor and rotating speed on Material removal rate (MRR) during micro EDM drilling of WC-16% Co was analyzed using fractional factorial design method. ANOVA analysis shows that increasing current, rotating speed, capacitor and decreasing voltage and pulse ON time lead to the amplify in MRR. It was found that out of all the factors, current and capacitor had the most significant effect on MRR, while the effect of capacitor was more than current. Eventually, it can be concluded that micro holes can be produced using EDM machine.

  2. [A new machinability test machine and the machinability of composite resins for core built-up].

    Science.gov (United States)

    Iwasaki, N

    2001-06-01

    A new machinability test machine especially for dental materials was contrived. The purpose of this study was to evaluate the effects of grinding conditions on machinability of core built-up resins using this machine, and to confirm the relationship between machinability and other properties of composite resins. The experimental machinability test machine consisted of a dental air-turbine handpiece, a control weight unit, a driving unit of the stage fixing the test specimen, and so on. The machinability was evaluated as the change in volume after grinding using a diamond point. Five kinds of core built-up resins and human teeth were used in this study. The machinabilities of these composite resins increased with an increasing load during grinding, and decreased with repeated grinding. There was no obvious correlation between the machinability and Vickers' hardness; however, a negative correlation was observed between machinability and scratch width.

  3. Optimization of pocket machining strategy in HSM

    OpenAIRE

    Msaddek, El Bechir; Bouaziz, Zoubeir; Dessein, Gilles; Baili, Maher

    2012-01-01

    International audience; Our two major concerns, which should be taken into consideration as soon as we start the selecting the machining parameters, are the minimization of the machining time and the maintaining of the high-speed machining machine in good state. The manufacturing strategy is one of the parameters which practically influences the time of the different geometrical forms manufacturing, as well as the machine itself. In this article, we propose an optimization methodology of the ...

  4. Parameter uncertainty in simulations of extreme precipitation and attribution studies.

    Science.gov (United States)

    Timmermans, B.; Collins, W. D.; O'Brien, T. A.; Risser, M. D.

    2017-12-01

    The attribution of extreme weather events, such as heavy rainfall, to anthropogenic influence involves the analysis of their probability in simulations of climate. The climate models used however, such as the Community Atmosphere Model (CAM), employ approximate physics that gives rise to "parameter uncertainty"—uncertainty about the most accurate or optimal values of numerical parameters within the model. In particular, approximate parameterisations for convective processes are well known to be influential in the simulation of precipitation extremes. Towards examining the impact of this source of uncertainty on attribution studies, we investigate the importance of components—through their associated tuning parameters—of parameterisations relating to deep and shallow convection, and cloud and aerosol microphysics in CAM. We hypothesise that as numerical resolution is increased the change in proportion of variance induced by perturbed parameters associated with the respective components is consistent with the decreasing applicability of the underlying hydrostatic assumptions. For example, that the relative influence of deep convection should diminish as resolution approaches that where convection can be resolved numerically ( 10 km). We quantify the relationship between the relative proportion of variance induced and numerical resolution by conducting computer experiments that examine precipitation extremes over the contiguous U.S. In order to mitigate the enormous computational burden of running ensembles of long climate simulations, we use variable-resolution CAM and employ both extreme value theory and surrogate modelling techniques ("emulators"). We discuss the implications of the relationship between parameterised convective processes and resolution both in the context of attribution studies and progression towards models that fully resolve convection.

  5. Theoretical and experimental study of trapped particle echoes in a magnetic mirror machine. Application to diffusion study

    International Nuclear Information System (INIS)

    Chatelier, Michel.

    1976-01-01

    A simple mechanical model is used to investigate the various physical mechanisms originating the echoes. The model is applied to nuclear spins and echoes from particles trapped in a magnetostatic well. The theory of echoes from trapped ions in a magnetic machine is developed. The effects that may be observed when two magnetic perturbations are applied to the plasma are described. Diffusion effects in the velocity space are then taken into account when the diffusion is due either to Coulomb collisions or to a microturbulence at the ion cyclotron frequency. The experimental results obtained with the DECA II B machine are described. Emphasis is put upon the effects observed when magnetic perturbations are applied to the plasma and echoes observation independently of the diffusion study, as it is the first time that trapped particle echoes are observed in a hot plasma [fr

  6. Study of some parameters of the fibrinogen - fibrin transformation reaction

    International Nuclear Information System (INIS)

    Hollard, D.; Suscillon, M.; Marcille, G.; Rambaud, F.; Baloyan, M.

    1966-01-01

    The authors studied the action of some parameters on the reaction of transformation fibrinogen-fibrin. The five parameters studied are: the concentration of substratum: a certain quantity of enzyme determines an optimum quantity of fibrinogen; the concentration of enzyme: a certain quantity of substratum defines an optimum quantity of enzyme, beyond which the excess of enzyme is unable to act, the substratum being saturated by the enzyme; the concentration of Ca ions: between 0,07 and 0,10 mg of Ca by mg of fibrinogen, the reaction appears with a great speed. Between 0,02 and 0,40 mg of Ca by mg of fibrinogen the fibrin stabilisation is possible, the FSF can act only inside the definite bounds; the ph of the solution: the reaction of the transformation appears with its maximum intensity on physiological ph, the polymerisation is not possible on acid ph; the temperature has an effect which could not really be verified owing to the fact that the technical realisation is difficult. (author) [fr

  7. Image Classification, Deep Learning and Convolutional Neural Networks : A Comparative Study of Machine Learning Frameworks

    OpenAIRE

    Airola, Rasmus; Hager, Kristoffer

    2017-01-01

    The use of machine learning and specifically neural networks is a growing trend in software development, and has grown immensely in the last couple of years in the light of an increasing need to handle big data and large information flows. Machine learning has a broad area of application, such as human-computer interaction, predicting stock prices, real-time translation, and self driving vehicles. Large companies such as Microsoft and Google have already implemented machine learning in some o...

  8. THE STUDY OF SELF-BALANCED POTATO SORTING MACHINE WITH LINEAR INDUCTION DRIVE

    OpenAIRE

    Linenko A. V.; Baynazarov V. G.; Kamalov T. I.

    2016-01-01

    In the article we have considered the self-balanced potato sorting machine differing from existing designs of self-balanced potato sorting machines with an oscillatory electric drive. That drive uses a linear induction motor. As the counterbalancing device, the method of the duplicating mechanism is applied. The duplicating mechanism is a specular reflection of the main working body, and also participates in technological process. Its application in the drive of machine allows not only to inc...

  9. Study on Parameters Modeling of Wind Turbines Using SCADA Data

    Directory of Open Access Journals (Sweden)

    Yonglong YAN

    2014-08-01

    Full Text Available Taking the advantage of the current massive monitoring data from Supervisory Control and Data Acquisition (SCADA system of wind farm, it is of important significance for anomaly detection, early warning and fault diagnosis to build the data model of state parameters of wind turbines (WTs. The operational conditions and the relationships between the state parameters of wind turbines are complex. It is difficult to establish the model of state parameter accurately, and the modeling method of state parameters of wind turbines considering parameter selection is proposed. Firstly, by analyzing the characteristic of SCADA data, a reasonable range of data and monitoring parameters are chosen. Secondly, neural network algorithm is adapted, and the selection method of input parameters in the model is presented. Generator bearing temperature and cooling air temperature are regarded as target parameters, and the two models are built and input parameters of the models are selected, respectively. Finally, the parameter selection method in this paper and the method using genetic algorithm-partial least square (GA-PLS are analyzed comparatively, and the results show that the proposed methods are correct and effective. Furthermore, the modeling of two parameters illustrate that the method in this paper can applied to other state parameters of wind turbines.

  10. Study on Gap Flow Field Simulation in Small Hole Machining of Ultrasonic Assisted EDM

    Science.gov (United States)

    Liu, Yu; Chang, Hao; Zhang, Wenchao; Ma, Fujian; Sha, Zhihua; Zhang, Shengfang

    2017-12-01

    When machining a small hole with high aspect ratio in EDM, it is hard for the flushing liquid entering the bottom gap and the debris could hardly be removed, which results in the accumulation of debris and affects the machining efficiency and machining accuracy. The assisted ultrasonic vibration can improve the removal of debris in the gap. Based on dynamics simulation software Fluent, a 3D model of debris movement in the gap flow field of EDM small hole machining assisted with side flushing and ultrasonic vibration is established in this paper. When depth to ratio is 3, the laws of different amplitudes and frequencies on debris distribution and removal are quantitatively analysed. The research results show that periodic ultrasonic vibration can promote the movement of debris, which is beneficial to the removal of debris in the machining gap. Compared to traditional small hole machining in EDM, the debris in the machining gap is greatly reduced, which ensures the stability of machining process and improves the machining efficiency.

  11. A basic experimental study on mental workload for human cognitive work at man-machine interface

    International Nuclear Information System (INIS)

    Yoshikawa, Hidekazu; Shimoda, Hiroshi; Wakamori, Osamu; Nagai, Yoshinori

    1995-01-01

    The nature and measurement methods of mental workload (MWL) for human cognitive activity at man-machine interface (MMI) were firstly discussed from the viewpoint of human information process model. Then, a model VDT experiment which simplifies the actual human-computer-interaction situation at MMI, was conducted for several subjects, where two subjects participated in experiment series and tried to solve the same cognitive task in competition. Adopted experimental parameters were (i)different kinds of cognitive task, and (ii)cycle time of information display, to see the influence on MWL characteristics from psycho-physiological viewpoint. A special processing unit for eye camera was developed and used for measuring subjects' eye movement characteristics. Concerning data analysis, total number of display presentation until problem solving (ie., total information needed for problem solving) was assumed as anchoring objective measure for MWL, and the investigations were conducted from two aspects; (i)global interpretation on MWL characteristics seen in the subjects' behavior from viewpoint of human information process model, and (ii)applicability of MWL by means of biocybernetic method. As regards to applicability of biocybernetic method, the nature of MWL characteristics was first divided into two aspects : (i)efficiency of visual information acquisition, and (ii)difficulty of inner cognitive process to solve problem, both in time pressure situation. Then, the data analysis results for eye movement characteristics were correlated to (i), while for heart rate characteristics, (ii). (author)

  12. Optimization of Multiple Responses of Ultrasonic Machining (USM Process: A Comparative Study

    Directory of Open Access Journals (Sweden)

    Rina Chakravorty

    2013-04-01

    Full Text Available Ultrasonic machining (USM process has multiple performance measures, e.g. material removal rate (MRR, tool wear rate (TWR, surface roughness (SR etc., which are affected by several process parameters. The researchers commonly attempted to optimize USM process with respect to individual responses, separately. In the recent past, several systematic procedures for dealing with the multi-response optimization problems have been proposed in the literature. Although most of these methods use complex mathematics or statistics, there are some simple methods, which can be comprehended and implemented by the engineers to optimize the multiple responses of USM processes. However, the relative optimization performance of these approaches is unknown because the effectiveness of different methods has been demonstrated using different sets of process data. In this paper, the computational requirements for four simple methods are presented, and two sets of past experimental data on USM processes are analysed using these methods. The relative performances of these methods are then compared. The results show that weighted signal-to-noise (WSN ratio method and utility theory (UT method usually give better overall optimisation performance for the USM process than the other approaches.

  13. Performance analysis of single stage libr-water absorption machine operated by waste thermal energy of internal combustion engine: Case study

    Science.gov (United States)

    Sharif, Hafiz Zafar; Leman, A. M.; Muthuraman, S.; Salleh, Mohd Najib Mohd; Zakaria, Supaat

    2017-09-01

    Combined heating, cooling, and power is also known as Tri-generation. Tri-generation system can provide power, hot water, space heating and air -conditioning from single source of energy. The objective of this study is to propose a method to evaluate the characteristic and performance of a single stage lithium bromide-water (LiBr-H2O) absorption machine operated with waste thermal energy of internal combustion engine which is integral part of trigeneration system. Correlations for computer sensitivity analysis are developed in data fit software for (P-T-X), (H-T-X), saturated liquid (water), saturated vapor, saturation pressure and crystallization temperature curve of LiBr-H2O Solution. Number of equations were developed with data fit software and exported into excel work sheet for the evaluation of number of parameter concerned with the performance of vapor absorption machine such as co-efficient of performance, concentration of solution, mass flow rate, size of heat exchangers of the unit in relation to the generator, condenser, absorber and evaporator temperatures. Size of vapor absorption machine within its crystallization limits for cooling and heating by waste energy recovered from exhaust gas, and jacket water of internal combustion engine also presented in this study to save the time and cost for the facilities managers who are interested to utilize the waste thermal energy of their buildings or premises for heating and air conditioning applications.

  14. Pre Design of Beam Parameter Control System for Electron Beam Machine (EBM) 350 keV/10 mA in the Center for Accelerator and Material Process Technology - BATAN Yogyakarta

    International Nuclear Information System (INIS)

    Sutanto

    2009-01-01

    Pre design of beam parameter control system for Electron Beam Machine (EBM) 350 keV/10 mA had an objective to find a control system algorithm for EBM in The Center For Accelerator and Material Process Technology (Pusat Teknologi dan Proses Bahan/PTAPB) - BATAN Yogyakarta. The design was based on the beam parameter model of EBM. The model shown a relationship between the dose parameter setting and the beam energy setting which it was being a problem in setting the beam parameters.The control system algorithm was found by getting compensator equations from the beam parameter model of EBM. The equations would omit the relation between the radiation dose parameter and beam energy parameter, so that the parameters could be adjusted easily. The result of the control system algorithm examine based on simulation shown that the setting of beam parameter value could be done by giving the accelerating voltage value and the filament current value as the operator had determined the value. The value of radiation dose and beam energy would be adjusted as its function of the filament current value and the accelerating voltage value. (author)

  15. Experimental study on practicability of self-created spherical tokamak in coilless STPC-EX machine

    International Nuclear Information System (INIS)

    Sinman, S.

    2002-01-01

    The aim of this study is to recognize the physical basis of the alternative self organization mechanism occurred STPC-EX machine. The conventional diagnostic tools are used in this study and for photographic recording, open shutter integrated post-fogging method is preferred. The annular coaxial two plasma current sheets one within other at the same direction are created and flowed on the surface of floating conductive central rod. Consequently, spherical tokamak configurated by new creation mechanism of Dual Axial Z-Pinch. (DAZP) yields fairly high beta of 0.4-0.6 at self created spherical tokamak plasma. Sustainment time of DAZP is 5.6-6.3 mili second. (author)

  16. Kinetic neutron diffraction and SANS studies of phase formation in bioactive machinable glass ceramics

    International Nuclear Information System (INIS)

    Bentley, P M; Kilcoyne, S H; Bubb, N L; Ritter, C; Dewhurst, C D; Wood, D J

    2007-01-01

    Bioactive fluormica-fluorapatite glass-ceramic materials offer a very encouraging solution to the problem of efficient restoration and reconstruction of hard tissues. To produce material with the desired crystalline phases, a five-stage heat treatment must be performed. This thermal processing has a large impact on the microstructure and ultimately the final mechanical properties of the materials. We have examined the thermal processing of one of our most promising machinable biomaterials, using time-resolved small angle neutron scattering and neutron diffraction to study the nucleation and growth of crystallites. The processing route had already been optimized by studying the properties of quenched samples using x-ray diffraction, mechanical measurements and differential thermal analysis. However these results show that the heat treatment can be further optimized in terms of crystal nucleation, and we show that these techniques are the only methods by which a truly optimized thermal processing route may be obtained

  17. Central magnetic cooling and refrigeration machines (chiller) and their assessment. A feasibility study - Final report

    Energy Technology Data Exchange (ETDEWEB)

    Egolf, P. W.; Gonin, C. [University of Applied Sciences of Western Switzerland, HEIG-VD, Yverdon-les Bains (Switzerland); Kitanovski, A. [University of Ljubljana, Ljubljana (Slovenia)

    2010-03-15

    This final report for the Swiss Federal Office of Energy (SFOE) presents the results of a feasibility study made concerning magnetic cooling and refrigeration machines. This report presents a comprehensive thermodynamic and economic analysis of applications of rotary magnetic chillers. The study deals with magnetic chillers based on permanent magnets and superconducting magnets, respectively. The numerical design of permanent magnet assemblies with different magnetic flux densities is discussed. The authors note that superconducting magnetic chillers are feasible only in large-scale applications with over 1 MW of cooling power. This report describes new ideas for magnetic refrigeration technologies, which go beyond the state of the art. They show potential for a substantial reduction of costs and further improvements in efficiency. Rotary magnetic liquid chillers with 'wavy' structures and using micro tubes are discussed, as are superconducting magnetic chillers and future magneto-caloric technologies.

  18. Studies on some biochemical parameters in viral hepatitis patients

    International Nuclear Information System (INIS)

    El-Sherbiny, E.M.

    2002-01-01

    The present investigation deals with studying liver amino transferases (ALT. AST). Cholesterol and triglycerides. As well as testosterone and protection hormones in blood of Egyptian men infected with hepatitis C virus.hepatitis B virus and mixed B and C viruses. These biochemical parameters were evaluated to be used in diagnosis and prognosis of viral hepatitis. Which considered the most important health problem in Egypt and developing countries. Biochemical analysis were performed using spectrophotometric and radioimmunoassay techniques. All data will be subjected to statistical analysis in order to detect the most suitable biochemical analysis that can be used as specific tests for early diagnosis of viral hepatitis and to detect the parameters that show abnormalities among the different groups of infected patients. The data revealed that AST and ALT levels were increased in all patient groups. Concerning the level of triglycerides, it was increased only in the group of mixed viral hepatitis B and C, while cholesterol showed non-significant changes in all viral hepatitis groups. The sex hormone testosterone was decreased in all infected patients while the prolactin level was increased only in case of patients infected with mixed B and C viruses. However, these abnormal values in such sex hormones play a serious role in male sterility

  19. Sustainable machining

    CERN Document Server

    2017-01-01

    This book provides an overview on current sustainable machining. Its chapters cover the concept in economic, social and environmental dimensions. It provides the reader with proper ways to handle several pollutants produced during the machining process. The book is useful on both undergraduate and postgraduate levels and it is of interest to all those working with manufacturing and machining technology.

  20. Basic study on weldability and machinability of structural materials for ITER toroidal field coils

    International Nuclear Information System (INIS)

    Onozuka, M.; Shimizu, K.; Urata, K.; Kimura, M.; Kadowaki, H.; Okamoto, M.; Nakajima, H.; Hamada, K.; Okuno, K.

    2006-01-01

    The toroidal field (TF) coils for ITER are very large components. The main structural component of the coil is the coil case, which requires a massive complex geometry with high fabrication accuracy to attain the required magnetic performance for plasma operations. To provide high mechanical strength and toughness at cryogenic temperature, the structural components employ high-strength austenite stainless steels that have been specially developed for ITER. However, one of the main drawbacks of using those materials is the difficulty of manufacturing capabilities. A manufacturing study has been conducted to examine welding and machining capabilities for JJ1 and ST-SS316LN, to be employed for TF coil structural components. Both materials include a high nitrogen content up to around 0.2%, which makes welding and machining difficult compared with conventional stainless steels. Electron beam welding conditions were studied for the JJ1 material. The applicable welding condition was found for a bead length of up to about 300 mm in the case of 40 mm thick plates. No optimal condition was found for plates thicker than 40 mm. An additional experimental study was also conducted to explore suitable welding conditions for different welding positions and directions. It was found that the appearance of defects depends on the welding positions and directions. A wider range of welding conditions was found for cases in the vertical upward direction, as opposed to those in the vertical downward and horizontal directions. Based on those results, a verification test up to 900 mm in length was conducted. The test results showed that vertical upward EB welding should be used for the coil case wherever possible. With respect to TIG welding, an average deposition rate as high as 26 g/min (i.e. the filler wire supplying speed of 3,000 mm/min) was achieved. A series of tests have been conducted to examine machinability of JJ1 and ST-SS316LN. Various types of milling tools, including face

  1. Neuromechanism study of insect-machine interface: flight control by neural electrical stimulation.

    Directory of Open Access Journals (Sweden)

    Huixia Zhao

    Full Text Available The insect-machine interface (IMI is a novel approach developed for man-made air vehicles, which directly controls insect flight by either neuromuscular or neural stimulation. In our previous study of IMI, we induced flight initiation and cessation reproducibly in restrained honeybees (Apis mellifera L. via electrical stimulation of the bilateral optic lobes. To explore the neuromechanism underlying IMI, we applied electrical stimulation to seven subregions of the honeybee brain with the aid of a new method for localizing brain regions. Results showed that the success rate for initiating honeybee flight decreased in the order: α-lobe (or β-lobe, ellipsoid body, lobula, medulla and antennal lobe. Based on a comparison with other neurobiological studies in honeybees, we propose that there is a cluster of descending neurons in the honeybee brain that transmits neural excitation from stimulated brain areas to the thoracic ganglia, leading to flight behavior. This neural circuit may involve the higher-order integration center, the primary visual processing center and the suboesophageal ganglion, which is also associated with a possible learning and memory pathway. By pharmacologically manipulating the electrically stimulated honeybee brain, we have shown that octopamine, rather than dopamine, serotonin and acetylcholine, plays a part in the circuit underlying electrically elicited honeybee flight. Our study presents a new brain stimulation protocol for the honeybee-machine interface and has solved one of the questions with regard to understanding which functional divisions of the insect brain participate in flight control. It will support further studies to uncover the involved neurons inside specific brain areas and to test the hypothesized involvement of a visual learning and memory pathway in IMI flight control.

  2. Neuromechanism study of insect-machine interface: flight control by neural electrical stimulation.

    Science.gov (United States)

    Zhao, Huixia; Zheng, Nenggan; Ribi, Willi A; Zheng, Huoqing; Xue, Lei; Gong, Fan; Zheng, Xiaoxiang; Hu, Fuliang

    2014-01-01

    The insect-machine interface (IMI) is a novel approach developed for man-made air vehicles, which directly controls insect flight by either neuromuscular or neural stimulation. In our previous study of IMI, we induced flight initiation and cessation reproducibly in restrained honeybees (Apis mellifera L.) via electrical stimulation of the bilateral optic lobes. To explore the neuromechanism underlying IMI, we applied electrical stimulation to seven subregions of the honeybee brain with the aid of a new method for localizing brain regions. Results showed that the success rate for initiating honeybee flight decreased in the order: α-lobe (or β-lobe), ellipsoid body, lobula, medulla and antennal lobe. Based on a comparison with other neurobiological studies in honeybees, we propose that there is a cluster of descending neurons in the honeybee brain that transmits neural excitation from stimulated brain areas to the thoracic ganglia, leading to flight behavior. This neural circuit may involve the higher-order integration center, the primary visual processing center and the suboesophageal ganglion, which is also associated with a possible learning and memory pathway. By pharmacologically manipulating the electrically stimulated honeybee brain, we have shown that octopamine, rather than dopamine, serotonin and acetylcholine, plays a part in the circuit underlying electrically elicited honeybee flight. Our study presents a new brain stimulation protocol for the honeybee-machine interface and has solved one of the questions with regard to understanding which functional divisions of the insect brain participate in flight control. It will support further studies to uncover the involved neurons inside specific brain areas and to test the hypothesized involvement of a visual learning and memory pathway in IMI flight control.

  3. Neuromechanism Study of Insect–Machine Interface: Flight Control by Neural Electrical Stimulation

    Science.gov (United States)

    Zhao, Huixia; Zheng, Nenggan; Ribi, Willi A.; Zheng, Huoqing; Xue, Lei; Gong, Fan; Zheng, Xiaoxiang; Hu, Fuliang

    2014-01-01

    The insect–machine interface (IMI) is a novel approach developed for man-made air vehicles, which directly controls insect flight by either neuromuscular or neural stimulation. In our previous study of IMI, we induced flight initiation and cessation reproducibly in restrained honeybees (Apis mellifera L.) via electrical stimulation of the bilateral optic lobes. To explore the neuromechanism underlying IMI, we applied electrical stimulation to seven subregions of the honeybee brain with the aid of a new method for localizing brain regions. Results showed that the success rate for initiating honeybee flight decreased in the order: α-lobe (or β-lobe), ellipsoid body, lobula, medulla and antennal lobe. Based on a comparison with other neurobiological studies in honeybees, we propose that there is a cluster of descending neurons in the honeybee brain that transmits neural excitation from stimulated brain areas to the thoracic ganglia, leading to flight behavior. This neural circuit may involve the higher-order integration center, the primary visual processing center and the suboesophageal ganglion, which is also associated with a possible learning and memory pathway. By pharmacologically manipulating the electrically stimulated honeybee brain, we have shown that octopamine, rather than dopamine, serotonin and acetylcholine, plays a part in the circuit underlying electrically elicited honeybee flight. Our study presents a new brain stimulation protocol for the honeybee–machine interface and has solved one of the questions with regard to understanding which functional divisions of the insect brain participate in flight control. It will support further studies to uncover the involved neurons inside specific brain areas and to test the hypothesized involvement of a visual learning and memory pathway in IMI flight control. PMID:25409523

  4. Diagnosis of Dementia by Machine learning methods in Epidemiological studies: a pilot exploratory study from south India.

    Science.gov (United States)

    Bhagyashree, Sheshadri Iyengar Raghavan; Nagaraj, Kiran; Prince, Martin; Fall, Caroline H D; Krishna, Murali

    2018-01-01

    There are limited data on the use of artificial intelligence methods for the diagnosis of dementia in epidemiological studies in low- and middle-income country (LMIC) settings. A culture and education fair battery of cognitive tests was developed and validated for population based studies in low- and middle-income countries including India by the 10/66 Dementia Research Group. We explored the machine learning methods based on the 10/66 battery of cognitive tests for the diagnosis of dementia based in a birth cohort study in South India. The data sets for 466 men and women for this study were obtained from the on-going Mysore Studies of Natal effect of Health and Ageing (MYNAH), in south India. The data sets included: demographics, performance on the 10/66 cognitive function tests, the 10/66 diagnosis of mental disorders and population based normative data for the 10/66 battery of cognitive function tests. Diagnosis of dementia from the rule based approach was compared against the 10/66 diagnosis of dementia. We have applied machine learning techniques to identify minimal number of the 10/66 cognitive function tests required for diagnosing dementia and derived an algorithm to improve the accuracy of dementia diagnosis. Of 466 subjects, 27 had 10/66 diagnosis of dementia, 19 of whom were correctly identified as having dementia by Jrip classification with 100% accuracy. This pilot exploratory study indicates that machine learning methods can help identify community dwelling older adults with 10/66 criterion diagnosis of dementia with good accuracy in a LMIC setting such as India. This should reduce the duration of the diagnostic assessment and make the process easier and quicker for clinicians, patients and will be useful for 'case' ascertainment in population based epidemiological studies.

  5. Support vector machine for breast cancer classification using diffusion-weighted MRI histogram features: Preliminary study.

    Science.gov (United States)

    Vidić, Igor; Egnell, Liv; Jerome, Neil P; Teruel, Jose R; Sjøbakk, Torill E; Østlie, Agnes; Fjøsne, Hans E; Bathen, Tone F; Goa, Pål Erik

    2018-05-01

    Diffusion-weighted MRI (DWI) is currently one of the fastest developing MRI-based techniques in oncology. Histogram properties from model fitting of DWI are useful features for differentiation of lesions, and classification can potentially be improved by machine learning. To evaluate classification of malignant and benign tumors and breast cancer subtypes using support vector machine (SVM). Prospective. Fifty-one patients with benign (n = 23) and malignant (n = 28) breast tumors (26 ER+, whereof six were HER2+). Patients were imaged with DW-MRI (3T) using twice refocused spin-echo echo-planar imaging with echo time / repetition time (TR/TE) = 9000/86 msec, 90 × 90 matrix size, 2 × 2 mm in-plane resolution, 2.5 mm slice thickness, and 13 b-values. Apparent diffusion coefficient (ADC), relative enhanced diffusivity (RED), and the intravoxel incoherent motion (IVIM) parameters diffusivity (D), pseudo-diffusivity (D*), and perfusion fraction (f) were calculated. The histogram properties (median, mean, standard deviation, skewness, kurtosis) were used as features in SVM (10-fold cross-validation) for differentiation of lesions and subtyping. Accuracies of the SVM classifications were calculated to find the combination of features with highest prediction accuracy. Mann-Whitney tests were performed for univariate comparisons. For benign versus malignant tumors, univariate analysis found 11 histogram properties to be significant differentiators. Using SVM, the highest accuracy (0.96) was achieved from a single feature (mean of RED), or from three feature combinations of IVIM or ADC. Combining features from all models gave perfect classification. No single feature predicted HER2 status of ER + tumors (univariate or SVM), although high accuracy (0.90) was achieved with SVM combining several features. Importantly, these features had to include higher-order statistics (kurtosis and skewness), indicating the importance to account for heterogeneity. Our

  6. Application of machine learning algorithms to the study of noise artifacts in gravitational-wave data

    Science.gov (United States)

    Biswas, Rahul; Blackburn, Lindy; Cao, Junwei; Essick, Reed; Hodge, Kari Alison; Katsavounidis, Erotokritos; Kim, Kyungmin; Kim, Young-Min; Le Bigot, Eric-Olivier; Lee, Chang-Hwan; Oh, John J.; Oh, Sang Hoon; Son, Edwin J.; Tao, Ye; Vaulin, Ruslan; Wang, Xiaoge

    2013-09-01

    The sensitivity of searches for astrophysical transients in data from the Laser Interferometer Gravitational-wave Observatory (LIGO) is generally limited by the presence of transient, non-Gaussian noise artifacts, which occur at a high enough rate such that accidental coincidence across multiple detectors is non-negligible. These “glitches” can easily be mistaken for transient gravitational-wave signals, and their robust identification and removal will help any search for astrophysical gravitational waves. We apply machine-learning algorithms (MLAs) to the problem, using data from auxiliary channels within the LIGO detectors that monitor degrees of freedom unaffected by astrophysical signals. Noise sources may produce artifacts in these auxiliary channels as well as the gravitational-wave channel. The number of auxiliary-channel parameters describing these disturbances may also be extremely large; high dimensionality is an area where MLAs are particularly well suited. We demonstrate the feasibility and applicability of three different MLAs: artificial neural networks, support vector machines, and random forests. These classifiers identify and remove a substantial fraction of the glitches present in two different data sets: four weeks of LIGO’s fourth science run and one week of LIGO’s sixth science run. We observe that all three algorithms agree on which events are glitches to within 10% for the sixth-science-run data, and support this by showing that the different optimization criteria used by each classifier generate the same decision surface, based on a likelihood-ratio statistic. Furthermore, we find that all classifiers obtain similar performance to the benchmark algorithm, the ordered veto list, which is optimized to detect pairwise correlations between transients in LIGO auxiliary channels and glitches in the gravitational-wave data. This suggests that most of the useful information currently extracted from the auxiliary channels is already described

  7. Study of Operating Parameters for Accelerated Anode Degradation in SOFCs

    DEFF Research Database (Denmark)

    Ploner, Alexandra; Hagen, Anke; Hauch, Anne

    2017-01-01

    Solid oxide fuel cell (SOFC) applications require lifetimes of several years on the system level. A big challenge is to demonstrate such exceptionally long lifetimes in ongoing R&D projects. Accelerated or compressed testing are alternative methods to obtain this. Activities in this area have been...... carried out without arriving at a generally accepted methodology. This is mainly due to the complexity of degradation mechanisms on the single SOFC components as function of operating parameters. In this study, we present a detailed analysis of approx. 180 durability tests regarding degradation of single...... SOFC components as function of operating conditions. Electrochemical impedance data were collected on the fresh and long-term tested SOFCs and used to de-convolute the individual losses of single SOFC cell components – electrolyte, cathode and anode. The main findings include a time-dependent effect...

  8. Superconducting machines. Chapter 4

    International Nuclear Information System (INIS)

    Appleton, A.D.

    1977-01-01

    A brief account is given of the principles of superconductivity and superconductors. The properties of Nb-Ti superconductors and the method of flux stabilization are described. The basic features of superconducting d.c. machines are illustrated by the use of these machines for ship propulsion, steel-mill drives, industrial drives, aluminium production, and other d.c. power supplies. Superconducting a.c. generators and their design parameters are discussed. (U.K.)

  9. Does Cigarette Smoking Affect Seminal Fluid Parameters? A Comparative Study

    Directory of Open Access Journals (Sweden)

    Zakarya Bani Meri

    2013-01-01

    Full Text Available Objective: To study the effect of cigarette smoking on seminal fluid parameters, namely; volume, sperm concentration, and motility, as well as morphology, leukocyte infiltration, among males complaining of infertility.Methods: Between August 2010 and July 2011, seminal fluid analysis was done for 1438 males who are partners of couples who visited the infertility clinic at Prince Rashid Ben Al Hassan Hospital (PRH for infertility. The men who fit the inclusion criteria (n=960 were classified into two groups: group a (non-smokers; n=564 and group B (smokers; n=396, which represents 41.25% of the study group. Seminal fluid was collected using masturbation after 3-5 days of abstinence then analyzed for volume, sperm count, sperm concentration, motility and morphology. In order to analyze whether the number of cigarettes smoked per day has an effect on the spermatogram; the smoking men were divided into two subgroups: the heavy smokers (n=266 and non-heavy smokers (n=130.Results: A total of 960 adult males were enrolled. Their age ranged between 21 and 76 years, 564 were non-smokers with mean age of 36. 45±6.27 (Mean±SD. Three-hundred-and-ninety-six were smokers with a mean age of 34.35±4.25 (Mean±SD. There was a significant effect of smoking on the motility of sperms and the ratios of abnormality (p<0.005. Concentration appeared not to be affected by smoking. Furthermore, the group of heavy smokers were found to have lower sperm concentrations and a higher percentage of abnormal sperms compared to the non-heavy smokers.Conclusion: Cigarette smoking has a deleterious effect on some of the seminal fluid parameters (motility, morphology and leukocyte count which in turn may result in male subfertility.

  10. Data-driven machine control : a feasibility study on YieldStar

    NARCIS (Netherlands)

    Mehrafrouz, M.

    2014-01-01

    Traditionally machine control software focusses on the control flow; this is also the situation within ASML and YieldStar. With the increased complexity of the machine control software more and more data is needed to accurately control a tool like YieldStar. In other software application areas, like

  11. Comparison of Advanced Machine Learning Tools for Disruption Prediction and Disruption Studies

    Czech Academy of Sciences Publication Activity Database

    Odstrčil, Michal; Murari, A.; Mlynář, Jan

    2013-01-01

    Roč. 41, č. 7 (2013), s. 1751-1759 ISSN 0093-3813 R&D Projects: GA ČR GAP205/10/2055 Institutional support: RVO:61389021 Keywords : Learning Machines * Support Vector Machines * Neural Network * ASDEX Upgrade * JET * Disruption mitigation * Tokamaks * ITER Subject RIV: BL - Plasma and Gas Discharge Physics Impact factor: 0.950, year: 2013

  12. Technical and Symbolic Knowledge in CNC Machining: A Study of Technical Workers of Different Backgrounds.

    Science.gov (United States)

    Martin, Laura M. W.; Beach, King

    Performances of 45 individuals with varying degrees of formal and informal training in machining and programming were compared on tasks designed to tap intellectual changes that may occur with the introduction of computer numerical control (CNC). Participants--30 machinists, 8 machine operators, and 7 engineers--were asked background questions and…

  13. Study on Production Management in Programming of Computer Numerical Control Machines

    Directory of Open Access Journals (Sweden)

    Gheorghe Popovici

    2014-12-01

    Full Text Available The paper presents the results of a study regarding the need for technology in programming for machinetools with computer-aided command. Engineering is the science of making skilled things. That is why, in the "factory of the future", programming engineering will have to realise the part processing on MU-CNCs (Computer Numerical Control Machines in the optimum economic variant. There is no "recipe" when it comes to technologies. In order to select the correct variant from among several technical variants, 10 technological requirements are forwarded for the engineer to take into account in MU-CNC programming. It is the first argued synthesis of the need for technological knowledge in MU-CNC programming.

  14. Case study of a magnetic system for low-energy machines

    Directory of Open Access Journals (Sweden)

    Daniel Schoerling

    2016-08-01

    Full Text Available The extra low-energy antiproton ring (ELENA is a CERN particle decelerator with the purpose to deliver antiprotons at lowest energies aiming to enhance the study of antimatter. The hexagonal shaped ring with a circumference of about 30 m will decelerate antiprotons from momenta of 100 to 13.7  MeV/c. In this paper, the design approach for a magnet system for such a machine is presented. Due to the extra-low beam rigidity, the design of the magnet system is especially challenging because even small fields, arising for example from residual magnetization and hysteresis, have a major impact on beam dynamics. In total, seven prototype magnets of three different magnet types have been built and tested. This paper outlines challenges, describes solutions for the design of the magnet system and discusses the results of the prototypes.

  15. Study on Damage Evaluation and Machinability of UD-CFRP for the Orthogonal Cutting Operation Using Scanning Acoustic Microscopy and the Finite Element Method

    Directory of Open Access Journals (Sweden)

    Dongyao Wang

    2017-02-01

    Full Text Available Owing to high specific strength and designability, unidirectional carbon fiber reinforced polymer (UD-CFRP has been utilized in numerous fields to replace conventional metal materials. Post machining processes are always required for UD-CFRP to achieve dimensional tolerance and assembly specifications. Due to inhomogeneity and anisotropy, UD-CFRP differs greatly from metal materials in machining and failure mechanism. To improve the efficiency and avoid machining-induced damage, this paper undertook to study the correlations between cutting parameters, fiber orientation angle, cutting forces, and cutting-induced damage for UD-CFRP laminate. Scanning acoustic microscopy (SAM was employed and one-/two-dimensional damage factors were then created to quantitatively characterize the damage of the laminate workpieces. According to the 3D Hashin’s criteria a numerical model was further proposed in terms of the finite element method (FEM. A good agreement between simulation and experimental results was validated for the prediction and structural optimization of the UD-CFRP.

  16. Damping parameter study of a perforated plate with bias flow

    Science.gov (United States)

    Mazdeh, Alireza

    role of LES for research studies concerned with damping properties of liners is limited to validation of other empirical or theoretical approaches. This research has shown that LES can go beyond that and can be used for performing parametric studies to characterize the sensitivity of acoustic properties of multi--perforated liners to the changes in the geometry and flow conditions and be used as a tool to design acoustic liners. The conducted research provides an insightful understanding about the contribution of different flow and geometry parameters such as perforated plate thickness, aperture radius, porosity factors and bias flow velocity. While the study agrees with previous observations obtained by analytical or experimental methods, it also quantifies the impact from these parameters on the acoustic impedance of perforated plate, a key parameter to determine the acoustic performance of any system. The conducted study has also explored the limitations and capabilities of commercial tool when are applied for performing simulation studies on damping properties of liners. The overall agreement between LES results and previous studies proves that commercial tools can be effectively used for these applications under certain conditions.

  17. Feasibility study and technical proposal for seismic monitoring of tunnel boring machine in Olkiluoto

    Energy Technology Data Exchange (ETDEWEB)

    Saari, J.; Lakio, A. (AF-Consult Ltd, Vantaa (Finland))

    2009-01-15

    In Olkiluoto, Posiva Oy has operated a local seismic network since February 2002. The purpose of the microearthquake measurements at Olkiluoto is to improve understanding of the structure, behaviour and long term stability of the bedrock. The studies include both tectonic and excavation-induced microearthquakes. An additional task of monitoring is related to safeguarding of the ONKALO. The possibility to excavate an illegal access to the ONKALO, have been concerned when the safeguards are discussed. Therefore all recorded explosions in the Olkiluoto area and in the ONKALO are located. If a concentration of explosions is observed, the origin of that is found out. Also a concept of hidden illegal explosions, detonated at the same time as the real excavation blasts, has been examined. According to the experience gained in Olkiluoto, it can be concluded that, as long the seismic network is in operation and the results are analysed by a skilled person, it is practically impossible to do illegal excavation by blasts. In this report a possibility of seismic monitoring of illegal excavation done by tunnel boring machine (TBM) has been investigated. Characteristics of the seismic signal generated by the raise boring machine are described. According to this study, it can be concluded that the generated seismic signal can be detected and the source of the signal can be located. However, this task calls for different kind of monitoring system than that, which is currently used for monitoring microearthquakes and explosions. The presented technical proposal for seismic monitoring of TBM in Olkiluoto is capable to detect and locate TBM coming outside the ONKALO area about two months before it would reach the ONKALO. (orig.)

  18. Feasibility study and technical proposal for seismic monitoring of tunnel boring machine in Olkiluoto

    International Nuclear Information System (INIS)

    Saari, J.; Lakio, A.

    2009-01-01

    In Olkiluoto, Posiva Oy has operated a local seismic network since February 2002. The purpose of the microearthquake measurements at Olkiluoto is to improve understanding of the structure, behaviour and long term stability of the bedrock. The studies include both tectonic and excavation-induced microearthquakes. An additional task of monitoring is related to safeguarding of the ONKALO. The possibility to excavate an illegal access to the ONKALO, have been concerned when the safeguards are discussed. Therefore all recorded explosions in the Olkiluoto area and in the ONKALO are located. If a concentration of explosions is observed, the origin of that is found out. Also a concept of hidden illegal explosions, detonated at the same time as the real excavation blasts, has been examined. According to the experience gained in Olkiluoto, it can be concluded that, as long the seismic network is in operation and the results are analysed by a skilled person, it is practically impossible to do illegal excavation by blasts. In this report a possibility of seismic monitoring of illegal excavation done by tunnel boring machine (TBM) has been investigated. Characteristics of the seismic signal generated by the raise boring machine are described. According to this study, it can be concluded that the generated seismic signal can be detected and the source of the signal can be located. However, this task calls for different kind of monitoring system than that, which is currently used for monitoring microearthquakes and explosions. The presented technical proposal for seismic monitoring of TBM in Olkiluoto is capable to detect and locate TBM coming outside the ONKALO area about two months before it would reach the ONKALO. (orig.)

  19. Feasibility Study for Electrical Discharge Machining of Large DU-Mo Castings

    International Nuclear Information System (INIS)

    Hill, Mary Ann; Dombrowski, David E.; Clarke, Kester Diederik; Forsyth, Robert Thomas; Aikin, Robert M.; Alexander, David John; Tegtmeier, Eric Lee; Robison, Jeffrey Curt; Beard, Timothy Vance; Edwards, Randall Lynn; Mauro, Michael Ernest; Scott, Jeffrey E.; Strandy, Matthew Thomas

    2016-01-01

    U-10 wt. % Mo (U-10Mo) alloys are being developed as low enrichment monolithic fuel for the CONVERT program. Optimization of processing for the monolithic fuel is being pursued with the use of electrical discharge machining (EDM) under CONVERT HPRR WBS 1.2.4.5 Optimization of Coupon Preparation. The process is applicable to manufacturing experimental fuel plate specimens for the Mini-Plate-1 (MP-1) irradiation campaign. The benefits of EDM are reduced machining costs, ability to achieve higher tolerances, stress-free, burr-free surfaces eliminating the need for milling, and the ability to machine complex shapes. Kerf losses are much smaller with EDM (tenths of mm) compared to conventional machining (mm). Reliable repeatability is achievable with EDM due to its computer-generated machining programs.

  20. Feasibility Study for Electrical Discharge Machining of Large DU-Mo Castings

    Energy Technology Data Exchange (ETDEWEB)

    Hill, Mary Ann [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). SIGMA Division; Dombrowski, David E. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). SIGMA Division; Clarke, Kester Diederik [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). SIGMA Division; Forsyth, Robert Thomas [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). SIGMA Division; Aikin, Robert M. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). SIGMA Division; Alexander, David John [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). SIGMA Division; Tegtmeier, Eric Lee [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). SIGMA Division; Robison, Jeffrey Curt [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). SIGMA Division; Beard, Timothy Vance [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). SIGMA Division; Edwards, Randall Lynn [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). SIGMA Division; Mauro, Michael Ernest [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). SIGMA Division; Scott, Jeffrey E. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). SIGMA Division; Strandy, Matthew Thomas [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). SIGMA Division

    2016-10-31

    U-10 wt. % Mo (U-10Mo) alloys are being developed as low enrichment monolithic fuel for the CONVERT program. Optimization of processing for the monolithic fuel is being pursued with the use of electrical discharge machining (EDM) under CONVERT HPRR WBS 1.2.4.5 Optimization of Coupon Preparation. The process is applicable to manufacturing experimental fuel plate specimens for the Mini-Plate-1 (MP-1) irradiation campaign. The benefits of EDM are reduced machining costs, ability to achieve higher tolerances, stress-free, burr-free surfaces eliminating the need for milling, and the ability to machine complex shapes. Kerf losses are much smaller with EDM (tenths of mm) compared to conventional machining (mm). Reliable repeatability is achievable with EDM due to its computer-generated machining programs.

  1. Machine learning techniques in disease forecasting: a case study on rice blast prediction

    Directory of Open Access Journals (Sweden)

    Kapoor Amar S

    2006-11-01

    Full Text Available Abstract Background Diverse modeling approaches viz. neural networks and multiple regression have been followed to date for disease prediction in plant populations. However, due to their inability to predict value of unknown data points and longer training times, there is need for exploiting new prediction softwares for better understanding of plant-pathogen-environment relationships. Further, there is no online tool available which can help the plant researchers or farmers in timely application of control measures. This paper introduces a new prediction approach based on support vector machines for developing weather-based prediction models of plant diseases. Results Six significant weather variables were selected as predictor variables. Two series of models (cross-location and cross-year were developed and validated using a five-fold cross validation procedure. For cross-year models, the conventional multiple regression (REG approach achieved an average correlation coefficient (r of 0.50, which increased to 0.60 and percent mean absolute error (%MAE decreased from 65.42 to 52.24 when back-propagation neural network (BPNN was used. With generalized regression neural network (GRNN, the r increased to 0.70 and %MAE also improved to 46.30, which further increased to r = 0.77 and %MAE = 36.66 when support vector machine (SVM based method was used. Similarly, cross-location validation achieved r = 0.48, 0.56 and 0.66 using REG, BPNN and GRNN respectively, with their corresponding %MAE as 77.54, 66.11 and 58.26. The SVM-based method outperformed all the three approaches by further increasing r to 0.74 with improvement in %MAE to 44.12. Overall, this SVM-based prediction approach will open new vistas in the area of forecasting plant diseases of various crops. Conclusion Our case study demonstrated that SVM is better than existing machine learning techniques and conventional REG approaches in forecasting plant diseases. In this direction, we have also

  2. Machine Learning for Big Data: A Study to Understand Limits at Scale

    Energy Technology Data Exchange (ETDEWEB)

    Sukumar, Sreenivas R. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Del-Castillo-Negrete, Carlos Emilio [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2015-12-21

    This report aims to empirically understand the limits of machine learning when applied to Big Data. We observe that recent innovations in being able to collect, access, organize, integrate, and query massive amounts of data from a wide variety of data sources have brought statistical data mining and machine learning under more scrutiny, evaluation and application for gleaning insights from the data than ever before. Much is expected from algorithms without understanding their limitations at scale while dealing with massive datasets. In that context, we pose and address the following questions How does a machine learning algorithm perform on measures such as accuracy and execution time with increasing sample size and feature dimensionality? Does training with more samples guarantee better accuracy? How many features to compute for a given problem? Do more features guarantee better accuracy? Do efforts to derive and calculate more features and train on larger samples worth the effort? As problems become more complex and traditional binary classification algorithms are replaced with multi-task, multi-class categorization algorithms do parallel learners perform better? What happens to the accuracy of the learning algorithm when trained to categorize multiple classes within the same feature space? Towards finding answers to these questions, we describe the design of an empirical study and present the results. We conclude with the following observations (i) accuracy of the learning algorithm increases with increasing sample size but saturates at a point, beyond which more samples do not contribute to better accuracy/learning, (ii) the richness of the feature space dictates performance - both accuracy and training time, (iii) increased dimensionality often reflected in better performance (higher accuracy in spite of longer training times) but the improvements are not commensurate the efforts for feature computation and training and (iv) accuracy of the learning algorithms

  3. Machining of Metal Matrix Composites

    CERN Document Server

    2012-01-01

    Machining of Metal Matrix Composites provides the fundamentals and recent advances in the study of machining of metal matrix composites (MMCs). Each chapter is written by an international expert in this important field of research. Machining of Metal Matrix Composites gives the reader information on machining of MMCs with a special emphasis on aluminium matrix composites. Chapter 1 provides the mechanics and modelling of chip formation for traditional machining processes. Chapter 2 is dedicated to surface integrity when machining MMCs. Chapter 3 describes the machinability aspects of MMCs. Chapter 4 contains information on traditional machining processes and Chapter 5 is dedicated to the grinding of MMCs. Chapter 6 describes the dry cutting of MMCs with SiC particulate reinforcement. Finally, Chapter 7 is dedicated to computational methods and optimization in the machining of MMCs. Machining of Metal Matrix Composites can serve as a useful reference for academics, manufacturing and materials researchers, manu...

  4. THE STUDY OF THE MAIN PARAMETERS QUALITY OF BUFFALO MILK

    Directory of Open Access Journals (Sweden)

    AURELIA PECE

    2010-02-01

    Full Text Available Researches were conducted on a biologic material, a buffalo livestock, in different lactating stages and their physico-chemical parameters were determined: fat, protein, lactose, unfat dry substance, density, pH, temperature. Regarding the variation of these components, researches conducted emphasized differences determined by those conditions specific to reference seasons. Individual analysis on the buffalo livestock in the study, emphasized significant differences: fat 8.59-9.36%, protein 5.16-5.31% respective of lactation. Microbiologic determinations mainly envisioned: the number of somatic cells (NSC, number of total germs (NTG Positive Coagulanzo Stafilococii, Listeria, Salmonella, determinations which lay at the basis of the assessment of buffalo milk quality. The positive Coagulanzo stafilococus was absent, excepting sample number 15 (2 germs/ml and sample number 22 (4 germs/ml; Salmonella was absent. Regarding the total number of germs: values between 1.0-1.8 germs/ml were obtained. The detection of this microbiologic parameter in the composition of buffalo milk provides information regarding the hygienic conditions of their production and handling. Correlations between the number of somatic cells, milk production and composition are employed in dairy buffalo farms, in order to assess losses caused by mastitis and the implementing of certain measures for the control of these diseases. On the other hand, correlations between the number of somatic cells and milk composition prove useful in establishing milk processing behaviour, as the practice of setting milk-raw matter prices according to the number of somatic cells in the milk is becoming increasingly more frequent in developed countries.

  5. Investigation of permanent magnet machines for downhole applications: Design, prototype and testing of a flux-switching permanent magnet machine

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Anyuan

    2011-01-15

    downhole applications. Flux-switching PM (FSPM) machines, which have the PMs located on the stator and are therefore more reliable, can theoretically also exhibit high torque density and relatively high efficiency. This thesis has put an emphasis on studying this type of machine. Two FSPM machines have been investigated in detail and compared by analytical method, FEM simulation and prototype measurements. Their operating principle and important design parameters are also presented. A lumped parameter magnetic circuit model for designing a high-torque FSPM machine is newly introduced and the designed machine is verified by FEM simulations. A prototype machine with an outer diameter of 100 mm and an axial length of 200 mm is built in the laboratory and tested at room temperature. Based on that, the machine performance at an ambient temperature of 150 C is also predicted. The results show that the FSPM machine can provide a high torque density with slight compromise of efficiency and power factor. Choosing a proper machine type is significantly dependent on the application specifications. The presented results in this thesis can be used as a reference for selecting the best machine type for a specific downhole case. (Author)

  6. A Study of Applications of Machine Learning Based Classification Methods for Virtual Screening of Lead Molecules.

    Science.gov (United States)

    Vyas, Renu; Bapat, Sanket; Jain, Esha; Tambe, Sanjeev S; Karthikeyan, Muthukumarasamy; Kulkarni, Bhaskar D

    2015-01-01

    The ligand-based virtual screening of combinatorial libraries employs a number of statistical modeling and machine learning methods. A comprehensive analysis of the application of these methods for the diversity oriented virtual screening of biological targets/drug classes is presented here. A number of classification models have been built using three types of inputs namely structure based descriptors, molecular fingerprints and therapeutic category for performing virtual screening. The activity and affinity descriptors of a set of inhibitors of four target classes DHFR, COX, LOX and NMDA have been utilized to train a total of six classifiers viz. Artificial Neural Network (ANN), k nearest neighbor (k-NN), Support Vector Machine (SVM), Naïve Bayes (NB), Decision Tree--(DT) and Random Forest--(RF). Among these classifiers, the ANN was found as the best classifier with an AUC of 0.9 irrespective of the target. New molecular fingerprints based on pharmacophore, toxicophore and chemophore (PTC), were used to build the ANN models for each dataset. A good accuracy of 87.27% was obtained using 296 chemophoric binary fingerprints for the COX-LOX inhibitors compared to pharmacophoric (67.82%) and toxicophoric (70.64%). The methodology was validated on the classical Ames mutagenecity dataset of 4337 molecules. To evaluate it further, selectivity and promiscuity of molecules from five drug classes viz. anti-anginal, anti-convulsant, anti-depressant, anti-arrhythmic and anti-diabetic were studied. The TPC fingerprints computed for each category were able to capture the drug-class specific features using the k-NN classifier. These models can be useful for selecting optimal molecules for drug design.

  7. Developing a dengue forecast model using machine learning: A case study in China.

    Science.gov (United States)

    Guo, Pi; Liu, Tao; Zhang, Qin; Wang, Li; Xiao, Jianpeng; Zhang, Qingying; Luo, Ganfeng; Li, Zhihao; He, Jianfeng; Zhang, Yonghui; Ma, Wenjun

    2017-10-01

    In China, dengue remains an important public health issue with expanded areas and increased incidence recently. Accurate and timely forecasts of dengue incidence in China are still lacking. We aimed to use the state-of-the-art machine learning algorithms to develop an accurate predictive model of dengue. Weekly dengue cases, Baidu search queries and climate factors (mean temperature, relative humidity and rainfall) during 2011-2014 in Guangdong were gathered. A dengue search index was constructed for developing the predictive models in combination with climate factors. The observed year and week were also included in the models to control for the long-term trend and seasonality. Several machine learning algorithms, including the support vector regression (SVR) algorithm, step-down linear regression model, gradient boosted regression tree algorithm (GBM), negative binomial regression model (NBM), least absolute shrinkage and selection operator (LASSO) linear regression model and generalized additive model (GAM), were used as candidate models to predict dengue incidence. Performance and goodness of fit of the models were assessed using the root-mean-square error (RMSE) and R-squared measures. The residuals of the models were examined using the autocorrelation and partial autocorrelation function analyses to check the validity of the models. The models were further validated using dengue surveillance data from five other provinces. The epidemics during the last 12 weeks and the peak of the 2014 large outbreak were accurately forecasted by the SVR model selected by a cross-validation technique. Moreover, the SVR model had the consistently smallest prediction error rates for tracking the dynamics of dengue and forecasting the outbreaks in other areas in China. The proposed SVR model achieved a superior performance in comparison with other forecasting techniques assessed in this study. The findings can help the government and community respond early to dengue epidemics.

  8. studies on the correlation of some aggregate parameters in the ...

    African Journals Online (AJOL)

    BARTH EKWUEME

    simulations for problem solving and forecasting environmental conditions .... METHODS. Parameters: The water quality parameters examined were, Turbidity, Total Dissolved Solids (TDS),. Chemical Oxygen Demand (COD), 5-day Biochemical. Oxygen Demand ..... Vogel's Textbook of Quantitative. Chemical Analysis 6th ed ...

  9. Systematic parameter study of dynamo bifurcations in geodynamo simulations

    Science.gov (United States)

    Petitdemange, Ludovic

    2018-04-01

    We investigate the nature of the dynamo bifurcation in a configuration applicable to the Earth's liquid outer core, i.e. in a rotating spherical shell with thermally driven motions with no-slip boundaries. Unlike in previous studies on dynamo bifurcations, the control parameters have been varied significantly in order to deduce general tendencies. Numerical studies on the stability domain of dipolar magnetic fields found a dichotomy between non-reversing dipole-dominated dynamos and the reversing non-dipole-dominated multipolar solutions. We show that, by considering weak initial fields, the above transition disappears and is replaced by a region of bistability for which dipolar and multipolar dynamos coexist. Such a result was also observed in models with free-slip boundaries in which the geostrophic zonal flow can develop and participate to the dynamo mechanism for non-dipolar fields. We show that a similar process develops in no-slip models when viscous effects are reduced sufficiently. The following three regimes are distinguished: (i) Close to the onset of convection (Rac) with only the most critical convective mode (wave number) being present, dynamos set in supercritically in the Ekman number regime explored here and are dipole-dominated. Larger critical magnetic Reynolds numbers indicate that they are particularly inefficient. (ii) in the range 3 10) , the relative importance of zonal flows increases with Ra in non-magnetic models. The field topology depends on the magnitude of the initial magnetic field. The dipolar branch has a subcritical behavior whereas the multipolar branch has a supercritical behavior. By approaching more realistic parameters, the extension of this bistable regime increases. A hysteretic behavior questions the common interpretation for geomagnetic reversals. Far above the dynamo threshold (by increasing the magnetic Prandtl number), Lorentz forces contribute to the first order force balance, as predicted for planetary dynamos. When

  10. Sensitivity of risk parameters to human errors in reactor safety study for a PWR

    International Nuclear Information System (INIS)

    Samanta, P.K.; Hall, R.E.; Swoboda, A.L.

    1981-01-01

    Sensitivities of the risk parameters, emergency safety system unavailabilities, accident sequence probabilities, release category probabilities and core melt probability were investigated for changes in the human error rates within the general methodological framework of the Reactor Safety Study (RSS) for a Pressurized Water Reactor (PWR). Impact of individual human errors were assessed both in terms of their structural importance to core melt and reliability importance on core melt probability. The Human Error Sensitivity Assessment of a PWR (HESAP) computer code was written for the purpose of this study. The code employed point estimate approach and ignored the smoothing technique applied in RSS. It computed the point estimates for the system unavailabilities from the median values of the component failure rates and proceeded in terms of point values to obtain the point estimates for the accident sequence probabilities, core melt probability, and release category probabilities. The sensitivity measure used was the ratio of the top event probability before and after the perturbation of the constituent events. Core melt probability per reactor year showed significant increase with the increase in the human error rates, but did not show similar decrease with the decrease in the human error rates due to the dominance of the hardware failures. When the Minimum Human Error Rate (M.H.E.R.) used is increased to 10 -3 , the base case human error rates start sensitivity to human errors. This effort now allows the evaluation of new error rate data along with proposed changes in the man machine interface

  11. Study of Parameters that Determine Railway Line Capacity

    Directory of Open Access Journals (Sweden)

    Josip Kukec

    2005-07-01

    Full Text Available In this work the study focuses on:- determining the elements required to determine the locationfor the installation of the main signals,- calculated block lengths, and- calculations of optimal head ways, that have not been studiedin detail although they deserve special attention due totheir impact.Generally speaking, the signals are installed in compliancewith the local circumstances, i. e. according to the technicaland technological characteristics and conditions determinedby the traffic places of work they protect.The distribution and length of the blocks depend on: therailway line and its exploitation characteristics, structure andtype of trains that run on the railway line, traffic organisationand signalisation system, as well as technical and exploitationcharacte1istics of the traction vehicles and the rolling stock.What has to be considered is that the minimum section lengthcannot be shorter than the length of the braking distance, i. e.the length of the longest train which runs on the respective railwayline.The study of these parameters is supplemented by the calculationof the reduction in throughput capacity depending on thelack of uniformity in the operation of trains, which, in order tomaintain the design quality of the transportation se1vice, and inthe activities of establishing and implementing the business policyshouldn't be left out nor bypassed.

  12. Machining of AISI D2 Tool Steel with Multiple Hole Electrodes by EDM Process

    Science.gov (United States)

    Prasad Prathipati, R.; Devuri, Venkateswarlu; Cheepu, Muralimohan; Gudimetla, Kondaiah; Uzwal Kiran, R.

    2018-03-01

    In recent years, with the increasing of technology the demand for machining processes is increasing for the newly developed materials. The conventional machining processes are not adequate to meet the accuracy of the machining of these materials. The non-conventional machining processes of electrical discharge machining is one of the most efficient machining processes is being widely used to machining of high accuracy products of various industries. The optimum selection of process parameters is very important in machining processes as that of an electrical discharge machining as they determine surface quality and dimensional precision of the obtained parts, even though time consumption rate is higher for machining of large dimension features. In this work, D2 high carbon and chromium tool steel has been machined using electrical discharge machining with the multiple hole electrode technique. The D2 steel has several applications such as forming dies, extrusion dies and thread rolling. But the machining of this tool steel is very hard because of it shard alloyed elements of V, Cr and Mo which enhance its strength and wear properties. However, the machining is possible by using electrical discharge machining process and the present study implemented a new technique to reduce the machining time using a multiple hole copper electrode. In this technique, while machining with multiple holes electrode, fin like projections are obtained, which can be removed easily by chipping. Then the finishing is done by using solid electrode. The machining time is reduced to around 50% while using multiple hole electrode technique for electrical discharge machining.

  13. Optimization of the parameter calculation the process of production historic by using Parallel Virtual Machine-PVM; Otimizacao do calculo de parametros no processo de ajuste de historicos de producao usando PVM

    Energy Technology Data Exchange (ETDEWEB)

    Vargas Cuervo, Carlos Hernan

    1997-03-01

    The main objective of this work is to develop a methodology to optimize the simultaneous computation of two parameters in the process of production history matching. This work describes a procedure to minimize an objective function established to find the values of the parameters which are modified in the process. The parameters are chosen after a sensibility analysis. Two optimization methods are tested: a Region Search Method (MBR) and Polytope Method. Both are based in direct search methods which do not require the function derivative. The software PVM (Parallel Virtual Machine) is used to parallelize the simulation runs, allowing the acceleration of the process and the search of multiple solutions. The validation of the methodology is applied to two reservoir models: one homogeneous and other heterogeneous. The advantages of each method and of the parallelization are also present. (author)

  14. The classification problem in machine learning: an overview with study cases in emotion recognition and music-speech differentiation

    OpenAIRE

    Rodríguez Cadavid, Santiago

    2015-01-01

    This work addresses the well-known classification problem in machine learning -- The goal of this study is to approach the reader to the methodological aspects of the feature extraction, feature selection and classifier performance through simple and understandable theoretical aspects and two study cases -- Finally, a very good classification performance was obtained for the emotion recognition from speech

  15. Study on the adjustment capability of the excitation system located inside superconducting machine electromagnetic shield

    Science.gov (United States)

    Xia, D.; Xia, Z.

    2017-12-01

    The ability for the excitation system to adjust quickly plays a very important role in maintaining the normal operation of superconducting machines and power systems. However, the eddy currents in the electromagnetic shield of superconducting machines hinder the exciting magnetic field change and weaken the adjustment capability of the excitation system. To analyze this problem, a finite element calculation model for the transient electromagnetic field with moving parts is established. The effects of three different electromagnetic shields on the exciting magnetic field are analyzed using finite element method. The results show that the electromagnetic shield hinders the field changes significantly, the better its conductivity, the greater the effect on the superconducting machine excitation.

  16. A Qualitative Study of Knowledge Exchange in an Indonesian Machine-Making Company

    Directory of Open Access Journals (Sweden)

    Indria Handoko

    2016-08-01

    Full Text Available In a supply chain, company’s ability to leverage knowledge that resides within the network of contracted and interacting firms is able to improve not only company performance but also the supply chain effectiveness as a whole. However, existing supply chain studies mostly discuss knowledge at company level, and rarely at internal-hierarchical levels. As a result, many things remain concealed, for example, how knowledge exchange between people across levels in a supply chain is influenced by the supply chain government. Moreover, most exsisting studies focus on a rigid hierarchical supply-chain mechanism, and hardly elaborate how interactions in a less-rigid mechanism. This article attempts to address these gaps, discussing how a supplier company that deals with innovation generation activities acquires knowledge that resides in its supply chain network. A qualitative case study about an Indonesian machine-making company has been chosen to represent one of supplier types in the automotive industry that deals with less-rigid mechanism. A social capital perspective is applied to shed light on how interactions between actors in a supply chain network influence knowledge exchange. The study finds out a positive relationship between social capital and knowledge exchange across levels and functions to help generate innovations, allowing the company to manage conflicting effect beliefs more effectively. The study also identifies a tendency of the company to regard intensive knowledge exchange as part of organizational learning process.

  17. An observational study investigating the association of ultrasonographically assessed machine milking-induced changes in teat condition and teat-end shape in dairy cows.

    Science.gov (United States)

    Wieland, M; Virkler, P D; Borkowski, A H; Älveby, N; Wood, P; Nydam, D V

    2018-06-21

    Mechanical forces during machine milking induce changes in teat condition which can be differentiated into short-term and long-term changes. Machine milking-induced short-term changes in teat condition (STC) are defined as tissue responses to a single milking and have been associated with the risk of new intramammary infection. Albeit, their association with teat characteristics, such as teat-end shape, has not been investigated by rigorous methods. The primary objective was to determine the association of STC, as measured by ultrasonography, with teat-end shape. The second objective was to describe possible differences in the recovery time of teat tissue after machine milking among teats with different teat-end shapes. Holstein cows (n=128) were enrolled in an observational study, housed in free-stall pens with sand bedding and milked three times a day. Ultrasonography of the left front and right hind teat was performed after teat preparation before milking (t-1), immediately after milking (t 0) and 1, 3, 5 and 7 h after milking (t 1, t 3, t 5, t 7). The teat tissue parameters measured from ultrasound scans were teat canal length, teat-end diameter, teat-end diameter at the midpoint between the distal and proximal end of the teat canal, teat wall thickness, and teat cistern width. Teat-end shape was assessed visually and classified into three categories: pointed, flat and round. Multivariable linear regression analyses showed differences in the relative change of teat tissue parameters (compared with t-1) at t 0 among teats with different teat-end shapes, with most parameters showing the largest change for round teats. The premilking values were reached (recovery time) after 7 h in teats with a pointed teat-end shape, whereas recovery time was greater than 7 h in teats with flat and round teat-end shapes. Under the same liner and milking machine conditions, teats with a round teat-end shape had the most severe short-term changes. The results of this observational

  18. Simulation Study on the Controllable Dielectrophoresis Parameters of Graphene

    Science.gov (United States)

    Ji, Jian-Long; Liu, Ya-Li; Ge, Yang; Xie, Sheng-Dong; Zhang, Xi; Sang, Sheng-Bo; Jian, Ao-Qun; Duan, Qian-Qian; Zhang, Qiang; Zhang, Wen-Dong

    2017-03-01

    The method of using dielectrophoresis (DEP) to assemble graphene between micro-electrodes has been proven to be simple and efficient. We present an optimization method for the kinetic formula of graphene DEP, and discuss the simulation of the graphene assembly process based on the finite element method. The simulated results illustrate that the accelerated motion of graphene is in agreement with the distribution of the electric field squared gradient. We also conduct research on the controllable parameters of the DEP assembly such as the alternating current (AC) frequency, the shape of micro-electrodes, and the ratio of the gap between electrodes to the characteristic/geometric length of graphene (λ). The simulations based on the Clausius-Mossotti factor reveal that both graphene velocity and direction are influenced by the AC frequency. When graphene is close to the electrodes, the shape of micro-electrodes will exert great influence on the velocity of graphene. Also, λ has a great influence on the velocity of graphene. Generally, the velocity of graphene would be greater when λ is in the range of 0.4-0.6. The study is of a theoretical guiding significance in improving the precision and efficiency of the graphene DEP assembly. Supported by the Basic Research Project of Shanxi Province under Grant No 2015021092, the National Natural Science Foundation of China under Grant Nos 61471255, 61474079, 61501316, 51505324 and 51622507, and the National High-Technology Research and Development Program of China under Grant No 2015AA042601.

  19. Future Circular Collider Study FCC-he Baseline Parameters

    CERN Document Server

    Bruning, Oliver; Klein, Max; Pellegrini, Dario; Schulte, Daniel; Zimmermann, Frank

    2017-01-01

    Initial considerations are presented on the FCC-he, the electron-hadron collider con guration within the Future Circular Collider study. This note considers arguments for the choice of the electron beam energy based on physics, ep scattering kinematics and cost. The default con guration for the electron accelerator, as for the LHeC, is chosen to be a multi-turn energy recovery linac external to the proton beam tunnel. The main accelerator parameters of the FCC-he are discussed, assuming the concurrent operation of ep with the 100TeV cms energy pp collider. These are compared with the LHeC design concept, for increased performance as for a Higgs facility using the HL-LHC, and also the high energy HE-LHC ep collider configuration. Initial estimates are also provided for the luminosity performance of electron-ion colliders for the 60 GeV electron ERL when combined with the LHC, the HE-LHC and the FCC ion beams.

  20. Contribution to the study, modelling and optimisation of a variable reluctance machine excited by permanent magnets; Contribution a l'etude, la modelisation et l'optimisation d'une machine a reluctance variable excitee par des aimants permanents

    Energy Technology Data Exchange (ETDEWEB)

    Haouara, I.

    1998-07-01

    Variable reluctance machines (VRM) with double cogs are interesting solutions for gearing mechanisms requiring a strong torque and a low speed. In the case of wind to electricity power conversion they can represent an improvement with the removal of the speed multiplier. A brief classification of VRMs has been made first and then, a double cogs synchronous structure with an excitation system made of permanent magnets included in the rotor has been chosen for this application. Then, using the dimensioning principles of synchronous machines, an approach is proposed to perform its pre-dimensioning. A finite-elements modeling of the machine and a model of equivalent electrical circuit have been used to evaluate its performances. An analytical approach based on the calculation of the air-gap permeation and of the magnetic scalar potential is proposed to identify the parameters of the equivalent electrical circuit (inductances and electromotive force). After validation, this model has been retained for the study of the performances of the generator-rectifier system in real conditions of operation (converter with a high frequency). Finally the optimization of the geometrical and magnetic parameters of the structure is analyzed in order to maximize its power. A conjugate experiment plans and fields calculation method has been used. It allows to take into consideration the real conditions of operation (saturation and dynamical functioning of magnets) and the interaction between the different parameters. The study of an optimized prototype has shown an improvement for all operation modes. (J.S.)

  1. Parameter studies of sediments in the Storegga Slide region

    Science.gov (United States)

    Yang, S. L.; Kvalstad, T.; Solheim, A.; Forsberg, C. F.

    2006-09-01

    Based on classification tests, oedometer tests, fall-cone tests and triaxial tests, physical and mechanical properties of sediments in the Storegga Slide region were analysed to assess parameter interrelationships. The data show good relationships between a number of physical and mechanical parameters. Goodness of fit between compression index and various physical parameters can be improved by multiple regression analysis. The interclay void ratio and liquidity index correlate well with the undrained shear strength of clay. Sediments with higher water content, liquid limit, activity, interclay void ratio, plasticity index and liquidity index showed higher compression index and/or lower undrained shear strength. Some relationships between parameters were tested by using data from two other sites south of the Storegga Slide. A better understanding of properties of sediments in regions such as that of the Storegga Slide can be obtained through this approach.

  2. Lactate quantification by proton magnetic resonance spectroscopy using a clinical MRI machine: a basic study

    International Nuclear Information System (INIS)

    Isobe, T.; Muraishi, H.; Matsumura, A.; Kawamura, H.; Shibata, Y.; Anno, I.; Minami, M.

    2007-01-01

    The purpose of this study was to establish quantification method of lactate concentration by proton magnetic resonance spectroscopy (MRS) carried out using a conventional 1.5-T MRI machine. We used a lactate phantom with known concentrations (1, 1.5, 3, 6, 12 and 14 mmol/L). As a clinical example, a patient with mitochondrial myopathy, encephalopathy, lactic acidosis and stroke-like episodes (MELAS) was evaluated. Proton MRS was carried out using a clinical 1.5-T super-conducting magnetic resonance whole-body system. Data were acquired by point resolved spectroscopy. A coupling constant of J = 7.35 Hz (2/7 = 272 ms) and two long in-phase echo time of 272 ms and 544 ms were used to calculate the T2 relaxation time. The tissue water signal was used as an internal standard to quantify lactate. The correlation coefficient R between the calculated lactate concentrations and the known concentration of lactate was 0.99 with a constant factor of 0.32 (1/3.14). In patients with MELAS, the lactate concentration measured by MRS was 6.2 mmol/kg wet weight, which is similar to the value obtained in previous studies. In the present study, we have established a reliable method for lactate quantification in a phantom study and have shown a sample of clinical case of MELAS

  3. A comparative machining study of diamond-coated tools made by ...

    Indian Academy of Sciences (India)

    R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

    adherent diamond films on WC–CO tools by all three deposition models and has allowed completion of the ..... cesses with hard turning machining will affect future demand for PCBN (and cBN coated) tools. 6. ... Business Communication Co.

  4. Simple machines

    CERN Document Server

    Graybill, George

    2007-01-01

    Just how simple are simple machines? With our ready-to-use resource, they are simple to teach and easy to learn! Chocked full of information and activities, we begin with a look at force, motion and work, and examples of simple machines in daily life are given. With this background, we move on to different kinds of simple machines including: Levers, Inclined Planes, Wedges, Screws, Pulleys, and Wheels and Axles. An exploration of some compound machines follows, such as the can opener. Our resource is a real time-saver as all the reading passages, student activities are provided. Presented in s

  5. Forecast of hourly global horizontal irradiance based on structured Kernel Support Vector Machine: A case study of Tibet area in China

    International Nuclear Information System (INIS)

    Jiang, He; Dong, Yao

    2017-01-01

    Highlights: • The structured variable selection in Kernel SVM is implemented using two ways. • The two-way interaction model is considered to enforce Heredity Principle. • SVMIC is used to select the kernel parameter in proposed approaches. • Simple and fast computations algorithms are derived. - Abstract: Various applications of forecasting effective global horizontal irradiance play increasingly vital role in grid-connected photovoltaic installations, but suffer from forecasting inaccuracy and prohibitively expensive computational cost. Although Support Vector Machine (SVM) is one of the most powerful forecasting approaches, it does not provide an interpretable model. This motivates penalized variable selection methods to be introduced to SVM to select important variables. However, in some forecasting problems, there are some underlying logic or hierarchical structure such as heredity principle among the variables. Penalized Kernel SVM approaches do not take heredity principles into consideration when enforcing sparsity. This paper investigates structural variable selection in Kernel SVM based approach which pursues heredity principle and sparsity simultaneously. To achieve heredity principle, both optimization and procedure based structural variable selection approaches are studied in the Kernel SVM. Computationally, we derive fast and simple-to-implement algorithms to perform structural variable selection and solar irradiance forecasting. Furthermore, Support Vector Machines Information Criterion is utilized to select the kernel parameters to guarantee the model consistency. Real data experiments directly reveal that our proposed KSVM-SVS based approach following heredity principle delivers superior performances in terms of forecasting accuracy comparing with other competitors.

  6. STUDY OF TRANSIENT AND STATIONARY OPERATION MODES OF SYNCHRONOUS SYSTEM CONSISTING IN TWO MACHINES

    Directory of Open Access Journals (Sweden)

    V. S. Safaryan

    2017-01-01

    Full Text Available The solution of the problem of reliable functioning of an electric power system (EPS in steady-state and transient regimes, prevention of EPS transition into asynchronous regime, maintenance and restoration of stability of post-emergency processes is based on formation and realization of mathematical models of an EPS processes. During the functioning of electric power system in asynchronous regime, besides the main frequencies, the currents and voltages include harmonic components, the frequencies of which are multiple of the difference of main frequencies. At the two-frequency asynchronous regime the electric power system is being made equivalent in a form of a two-machine system, functioning for a generalized load. In the article mathematical models of transient process of a two-machine system in natural form and in d–q coordinate system are presented. The mathematical model of two-machine system is considered in case of two windings of excitement at the rotors. Also, in the article varieties of mathematical models of EPS transient regimes (trivial, simple, complete are presented. Transient process of a synchronous two-machine system is described by the complete model. The quality of transient processes of a synchronous machine depends on the number of rotor excitation windings. When there are two excitation windings on the rotor (dual system of excitation, the mathematical model of electromagnetic transient processes of a synchronous machine is represented in a complex form, i.e. in coordinate system d, q, the current of rotor being represented by a generalized vector. In asynchronous operation of a synchronous two-machine system with two excitation windings on the rotor the current and voltage systems include only harmonics of two frequencies. The mathematical model of synchronous steady-state process of a two-machine system is also provided, and the steady-state regimes with different structures of initial information are considered.

  7. Study on lean thinking among MSMEs in the Machine tool sector in India

    Science.gov (United States)

    Priyaadarshini, R. G.; Sathish Kumar, V. R.; Aishwarya Rajlakshmi, S.

    2018-02-01

    In the era of stiff competition and customer expectations, manufacturing organizations across the world are struggling hard to minimize their costs and maximise their performance. Micro, Small and Medium enterprises (MSMEs), who are dependent on large corporate for business and support have a tall task of keeping pace quality in processes and output. They are in the constant vigil to adopt new systems and practices so that they can minimise their cost and maximize the productivity. This study has been conducted in the machine tool sector of Coimbatore, India; which houses more than 9000 companies and offers employment to over one lakh employees. They have a tremendous pressure to use scientific processes to increase their product quality and productivity. While Lean manufacturing has been the thrust to improve the competitiveness among MSMEs in India, this study has attempted to understand their attitude towards lean management and understand the extent to which companies practice lean tools and practices. It has been found that most of the organizations in the study possess a culture of lean thinking and possess the support of top management and employees also towards the initiative. It is also seen that the organizations that incorporated lean in their daily operations have been able to scale up their productivity.

  8. Computer vision and machine learning for robust phenotyping in genome-wide studies.

    Science.gov (United States)

    Zhang, Jiaoping; Naik, Hsiang Sing; Assefa, Teshale; Sarkar, Soumik; Reddy, R V Chowda; Singh, Arti; Ganapathysubramanian, Baskar; Singh, Asheesh K

    2017-03-08

    Traditional evaluation of crop biotic and abiotic stresses are time-consuming and labor-intensive limiting the ability to dissect the genetic basis of quantitative traits. A machine learning (ML)-enabled image-phenotyping pipeline for the genetic studies of abiotic stress iron deficiency chlorosis (IDC) of soybean is reported. IDC classification and severity for an association panel of 461 diverse plant-introduction accessions was evaluated using an end-to-end phenotyping workflow. The workflow consisted of a multi-stage procedure including: (1) optimized protocols for consistent image capture across plant canopies, (2) canopy identification and registration from cluttered backgrounds, (3) extraction of domain expert informed features from the processed images to accurately represent IDC expression, and (4) supervised ML-based classifiers that linked the automatically extracted features with expert-rating equivalent IDC scores. ML-generated phenotypic data were subsequently utilized for the genome-wide association study and genomic prediction. The results illustrate the reliability and advantage of ML-enabled image-phenotyping pipeline by identifying previously reported locus and a novel locus harboring a gene homolog involved in iron acquisition. This study demonstrates a promising path for integrating the phenotyping pipeline into genomic prediction, and provides a systematic framework enabling robust and quicker phenotyping through ground-based systems.

  9. submitter Studies of CMS data access patterns with machine learning techniques

    CERN Document Server

    De Luca, Silvia

    This thesis presents a study of the Grid data access patterns in distributed analysis in the CMS experiment at the LHC accelerator. This study ranges from the deep analysis of the historical patterns of access to the most relevant data types in CMS, to the exploitation of a supervised Machine Learning classification system to set-up a machinery able to eventually predict future data access patterns - i.e. the so-called dataset “popularity” of the CMS datasets on the Grid - with focus on specific data types. All the CMS workflows run on the Worldwide LHC Computing Grid (WCG) computing centers (Tiers), and in particular the distributed analysis systems sustains hundreds of users and applications submitted every day. These applications (or “jobs”) access different data types hosted on disk storage systems at a large set of WLCG Tiers. The detailed study of how this data is accessed, in terms of data types, hosting Tiers, and different time periods, allows to gain precious insight on storage occupancy ove...

  10. Thermoforming of glass fibre reinforced polypropylene: A study on the influence of different process parameters

    Science.gov (United States)

    Schug, Alexander; Winkelbauer, Jonas; Hinterhölzl, Roland; Drechsler, Klaus

    2017-10-01

    The aim of this study was to analyse the forming behaviour of glass fibre reinforced polypropylene and to identify the influence of several process parameters on the resulting part quality. For this purpose, a complex forming tool was designed, consisting of several areas with single and double curvature. The specimens were produced from unidirectional (UD) tape using the Fiberforge RELAY2000® automated tape laying machine and a subsequent consolidation step. They were then fixed in a support frame, pre-heated in an infrared oven, and formed in the forming tool, which was mounted into a hydraulic heating press. The investigated process parameters were the number and force of the springs in the support frame, the tool temperature and the forming pressure and speed. The layups of the specimens were [0/90/0/90/0¯]s and [0/45/90/-45/0¯]s. After the forming process, the parts were analysed in terms of their quality, with a special focus on wrinkles, undulations, gaps and surface roughness. In addition to optical analysis with a statistical evaluation of the results, 3D scans of the specimens at different steps of the forming process were made to gain an impression of the forming mechanisms and the development of failures. The ATOS system of GOM was used for these 3D scans. The results show that the undulations were influenced by the tool temperature and the spring force. By contrast, the surface quality was most strongly dependent on the forming pressure, which also influenced the size and the number of gaps. The forming speed affected the gaps as well. The tool temperature had the largest influence on the development of wrinkles. As expected, the quasi-isotropic layup showed distinctly more wrinkles and undulations, but it also presented a better surface quality than the orthotropic layup.

  11. Human-machine communication for educational systems design : NATO Advanced Study Institute proceedings, Eindhoven August 16-26, 1993

    NARCIS (Netherlands)

    Janse, M.D.; Harrington, T.L.

    1994-01-01

    This book contains the papers presented at the NATO Advanced Study Institute (ASI) on the Basics of Man-Machine Communication for the Design of Educational Systems, held August 16-26, 1993 in Eindhoven, The Netherlands. The ASI addressed the state of the art in the design of educational systems with

  12. Student Achievement Study, 1970-1974. The IEA Six-Subject Data Bank [machine-readable data file].

    Science.gov (United States)

    International Association for the Evaluation of Educational Achievement, Stockholm (Sweden).

    The "Student Achievement Study" machine-readable data files (MRDF) (also referred to as the "IEA Six-Subject Survey") are the result of an international data collection effort during 1970-1974 by 21 designated National Centers, which had agreed to cooperate. The countries involved were: Australia, Belgium, Chile, England-Wales,…

  13. Effect of changing polarity of graphite tool/ Hadfield steel workpiece couple on machining performances in die sinking EDM

    Directory of Open Access Journals (Sweden)

    Özerkan Haci Bekir

    2017-01-01

    Full Text Available In this study, machining performance ouput parameters such as machined surface roughness (SR, material removal rate (MRR, tool wear rate (TWR, were experimentally examined and analyzed with the diversifying and changing machining parameters in (EDM. The processing parameters (input par. of this research are stated as tool material, peak current (I, pulse duration (ton and pulse interval (toff. The experimental machinings were put into practice by using Hadfield steel workpiece (prismatic and cylindrical graphite electrodes with kerosene dielectric at different machining current, polarity and pulse time settings. The experiments have shown that the type of tool material, polarity (direct polarity forms higher MRR, SR and TWR, current (high current lowers TWR and enhances MRR, TWR and pulse on time (ton=48□s is critical threshold value for MRR and TWR were influential on machining performance in electrical discharge machining.

  14. Study of the transport parameters of cloud lightning plasmas

    International Nuclear Information System (INIS)

    Chang, Z. S.; Yuan, P.; Zhao, N.

    2010-01-01

    Three spectra of cloud lightning have been acquired in Tibet (China) using a slitless grating spectrograph. The electrical conductivity, the electron thermal conductivity, and the electron thermal diffusivity of the cloud lightning, for the first time, are calculated by applying the transport theory of air plasma. In addition, we investigate the change behaviors of parameters (the temperature, the electron density, the electrical conductivity, the electron thermal conductivity, and the electron thermal diffusivity) in one of the cloud lightning channels. The result shows that these parameters decrease slightly along developing direction of the cloud lightning channel. Moreover, they represent similar sudden change behavior in tortuous positions and the branch of the cloud lightning channel.

  15. Machine learning from hard x-ray surveys: applications to magnetic cataclysmic variable studies

    Science.gov (United States)

    Scaringi, Simone

    2009-11-01

    Within this thesis are discussed two main topics of contemporary astrophysics. The first is that of machine learning algorithms for astronomy whilst the second is that of magnetic cataclysmic variables (mCVs). To begin, an overview is given of ISINA: INTEGRAL Scouce Identifiction Network Algorithm. This machine learning algorithm, using random forests, is applied to the IBIS/ISGRI data set in order to ease the production of unbiased future soft gamma-ray source catalogues. The feature extraction process on an initial candidate list is described together with feature merging. Three trainng and testing sets are created in order to deal with the diverse time-scales encountered when dealing with the gamma-ray sky: one dealing with faint persistent source recognition, one dealing with strong persistent sources and a final one dealing with transients. For the latter, a new transient detection technique is introduced and described: the transient matrix. Finally the performance of the network is assessed and discussed using the testing set and some illustrative source examples. ISINA is also compared to the more conventional approach of visual inspection. Next mCVs are discussed, and in particular the properties arising from a hard X-ray selected sample which has proven remarkably efficient in detecting intermediate polars and asynchronous polars, two of the rarest type of cataclysmic variables (CVs). This thesis focuses particularly on the link between hard X-ray properties and spin/orbital periods. To this end, a new sample of these objects is constructed by cross-corelating candidate sources detected in INTEGRAL/IBIS observations against catalogues of known CVs. Also included in the analysis are hard X-ray Observations from Swift/BAT and SUZAKU/HXD in order to make the study more complete. It is found that most hard X-ray detected mCVs have Pspin/Porb<0.1 above the period gap. In this respect, attention is given to the very low number of detected systems in any ban

  16. Face machines

    Energy Technology Data Exchange (ETDEWEB)

    Hindle, D.

    1999-06-01

    The article surveys latest equipment available from the world`s manufacturers of a range of machines for tunnelling. These are grouped under headings: excavators; impact hammers; road headers; and shields and tunnel boring machines. Products of thirty manufacturers are referred to. Addresses and fax numbers of companies are supplied. 5 tabs., 13 photos.

  17. Electric machine

    Science.gov (United States)

    El-Refaie, Ayman Mohamed Fawzi [Niskayuna, NY; Reddy, Patel Bhageerath [Madison, WI

    2012-07-17

    An interior permanent magnet electric machine is disclosed. The interior permanent magnet electric machine comprises a rotor comprising a plurality of radially placed magnets each having a proximal end and a distal end, wherein each magnet comprises a plurality of magnetic segments and at least one magnetic segment towards the distal end comprises a high resistivity magnetic material.

  18. Machine Learning.

    Science.gov (United States)

    Kirrane, Diane E.

    1990-01-01

    As scientists seek to develop machines that can "learn," that is, solve problems by imitating the human brain, a gold mine of information on the processes of human learning is being discovered, expert systems are being improved, and human-machine interactions are being enhanced. (SK)

  19. Nonplanar machines

    International Nuclear Information System (INIS)

    Ritson, D.

    1989-05-01

    This talk examines methods available to minimize, but never entirely eliminate, degradation of machine performance caused by terrain following. Breaking of planar machine symmetry for engineering convenience and/or monetary savings must be balanced against small performance degradation, and can only be decided on a case-by-case basis. 5 refs

  20. Data extraction from machine-translated versus original language randomized trial reports: a comparative study.

    Science.gov (United States)

    Balk, Ethan M; Chung, Mei; Chen, Minghua L; Chang, Lina Kong Win; Trikalinos, Thomas A

    2013-11-07

    Google Translate offers free Web-based translation, but it is unknown whether its translation accuracy is sufficient to use in systematic reviews to mitigate concerns about language bias. We compared data extraction from non-English language studies with extraction from translations by Google Translate of 10 studies in each of five languages (Chinese, French, German, Japanese and Spanish). Fluent speakers double-extracted original-language articles. Researchers who did not speak the given language double-extracted translated articles along with 10 additional English language trials. Using the original language extractions as a gold standard, we estimated the probability and odds ratio of correctly extracting items from translated articles compared with English, adjusting for reviewer and language. Translation required about 30 minutes per article and extraction of translated articles required additional extraction time. The likelihood of correct extractions was greater for study design and intervention domain items than for outcome descriptions and, particularly, study results. Translated Spanish articles yielded the highest percentage of items (93%) that were correctly extracted more than half the time (followed by German and Japanese 89%, French 85%, and Chinese 78%) but Chinese articles yielded the highest percentage of items (41%) that were correctly extracted >98% of the time (followed by Spanish 30%, French 26%, German 22%, and Japanese 19%). In general, extractors' confidence in translations was not associated with their accuracy. Translation by Google Translate generally required few resources. Based on our analysis of translations from five languages, using machine translation has the potential to reduce language bias in systematic reviews; however, pending additional empirical data, reviewers should be cautious about using translated data. There remains a trade-off between completeness of systematic reviews (including all available studies) and risk of

  1. A study on the application of voice interaction in automotive human machine interface experience design

    Science.gov (United States)

    Huang, Zhaohui; Huang, Xiemin

    2018-04-01

    This paper, firstly, introduces the application trend of the integration of multi-channel interactions in automotive HMI ((Human Machine Interface) from complex information models faced by existing automotive HMI and describes various interaction modes. By comparing voice interaction and touch screen, gestures and other interaction modes, the potential and feasibility of voice interaction in automotive HMI experience design are concluded. Then, the related theories of voice interaction, identification technologies, human beings' cognitive models of voices and voice design methods are further explored. And the research priority of this paper is proposed, i.e. how to design voice interaction to create more humane task-oriented dialogue scenarios to enhance interactive experiences of automotive HMI. The specific scenarios in driving behaviors suitable for the use of voice interaction are studied and classified, and the usability principles and key elements for automotive HMI voice design are proposed according to the scenario features. Then, through the user participatory usability testing experiment, the dialogue processes of voice interaction in automotive HMI are defined. The logics and grammars in voice interaction are classified according to the experimental results, and the mental models in the interaction processes are analyzed. At last, the voice interaction design method to create the humane task-oriented dialogue scenarios in the driving environment is proposed.

  2. Modeling the Financial Distress of Microenterprise StartUps Using Support Vector Machines: A Case Study

    Directory of Open Access Journals (Sweden)

    Antonio Blanco-Oliver

    2014-10-01

    Full Text Available Despite the leading role that micro-entrepreneurship plays in economic development, and the high failure rate of microenterprise start-ups in their early years, very few studies have designed financial distress models to detect the financial problems of micro-entrepreneurs. Moreover, due to a lack of research, nothing is known about whether non-financial information and nonparametric statistical techniques improve the predictive capacity of these models. Therefore, this paper provides an innovative financial distress model specifically designed for microenterprise startups via support vector machines (SVMs that employs financial, non-financial, and macroeconomic variables. Based on a sample of almost 5,500 micro- entrepreneurs from a Peruvian Microfinance Institution (MFI, our findings show that the introduction of non-financial information related to the zone in which the entrepreneurs live and situate their business, the duration of the MFI-entrepreneur relationship, the number of loans granted by the MFI in the last year, the loan destination, and the opinion of experts on the probability that microenterprise start-ups may experience financial problems, significantly increases the accuracy performance of our financial distress model. Furthermore, the results reveal that the models that use SVMs outperform those which employ traditional logistic regression (LR analysis.

  3. Study of Body Composition and Metabolic Parameters in HIV-1 Male Patients

    Directory of Open Access Journals (Sweden)

    Gurudath Gundurao Sreekantamurthy

    2014-01-01

    Full Text Available Background. HIV patients on highly active antiretroviral therapy (HAART containing protease inhibitors (PIs had been often associated with lipodystrophy. However, there are only few studies on association of nucleoside and nonnucleoside reverse transcriptase inhibitors (NRTI and NNRTI with lipodystrophy. Study Design. One hundred and one HIV male patients were categorised into ART naïve (n=22, zidovudine (n=22, stavudine (n=18, tenofovir (n=15, and PIs (n=24 based HAART. Their clinicoepidemiological data had been entered in preformed pro forma. The body composition, using TANITA machine and metabolic parameters like lipid profile, blood sugars was analysed. Results. Clinically, lipoatrophy of face was most prevalent in HIV patients on stavudine (15 patients, 83.3% and PIs (20 patients, 83.3% based HAART. The mean BMI among study population was in normal range. Excess visceral fat was most prevalent among patients on PIs, 4 patients (16.7%. The waist-hip ratio was significantly higher in PIs (P=0.01 based HAART. There was no significant difference among different study populations in terms of BMI (P=0.917, body water (P=0.318, body fat (P=0.172, bone mass (P=0.200, and muscle mass (P=0.070. Hypertriglyceridiemia was found in stavudine, tenofovir, and protease inhibitors regimens. Low levels of high density lipoprotein (HDL was found zidovudine, stavudine, and PIs regimens. Fasting and postprandial hyperglycaemia was found PIs and impaired glucose tolerance in stavudine regimen. Conclusion. Patients on PIs were associated with truncal obesity and lipoatrophy of face, along with dyslipidemia and hyperglycaemia. Stavudine based regimen is associated with hypertriglyceridiemia and low HDL along with lipoatrophy of face.

  4. Machinability Study on Milling Kenaf Fiber Reinforced Plastic Composite Materials using Design of Experiments

    Science.gov (United States)

    Azmi, H.; Haron, C. H. C.; Ghani, J. A.; Suhaily, M.; Yuzairi, A. R.

    2018-04-01

    The surface roughness (Ra) and delamination factor (Fd) of a milled kenaf reinforced plastic composite materials are depending on the milling parameters (spindle speed, feed rate and depth of cut). Therefore, a study was carried out to investigate the relationship between the milling parameters and their effects on a kenaf reinforced plastic composite materials. The composite panels were fabricated using vacuum assisted resin transfer moulding (VARTM) method. A full factorial design of experiments was use as an initial step to screen the significance of the parameters on the defects using Analysis of Variance (ANOVA). If the curvature of the collected data shows significant, Response Surface Methodology (RSM) is then applied for obtaining a quadratic modelling equation that has more reliable in expressing the optimization. Thus, the objective of this research is obtaining an optimum setting of milling parameters and modelling equations to minimize the surface roughness (Ra) and delamination factor (Fd) of milled kenaf reinforced plastic composite materials. The spindle speed and feed rate contributed the most in affecting the surface roughness and the delamination factor of the kenaf composite materials.

  5. LHC Report: machine development

    CERN Multimedia

    Rogelio Tomás García for the LHC team

    2015-01-01

    Machine development weeks are carefully planned in the LHC operation schedule to optimise and further study the performance of the machine. The first machine development session of Run 2 ended on Saturday, 25 July. Despite various hiccoughs, it allowed the operators to make great strides towards improving the long-term performance of the LHC.   The main goals of this first machine development (MD) week were to determine the minimum beam-spot size at the interaction points given existing optics and collimation constraints; to test new beam instrumentation; to evaluate the effectiveness of performing part of the beam-squeezing process during the energy ramp; and to explore the limits on the number of protons per bunch arising from the electromagnetic interactions with the accelerator environment and the other beam. Unfortunately, a series of events reduced the machine availability for studies to about 50%. The most critical issue was the recurrent trip of a sextupolar corrector circuit –...

  6. Parameter motivated mutual correlation analysis: Application to the study of currency exchange rates based on intermittency parameter and Hurst exponent

    Science.gov (United States)

    Cristescu, Constantin P.; Stan, Cristina; Scarlat, Eugen I.; Minea, Teofil; Cristescu, Cristina M.

    2012-04-01

    We present a novel method for the parameter oriented analysis of mutual correlation between independent time series or between equivalent structures such as ordered data sets. The proposed method is based on the sliding window technique, defines a new type of correlation measure and can be applied to time series from all domains of science and technology, experimental or simulated. A specific parameter that can characterize the time series is computed for each window and a cross correlation analysis is carried out on the set of values obtained for the time series under investigation. We apply this method to the study of some currency daily exchange rates from the point of view of the Hurst exponent and the intermittency parameter. Interesting correlation relationships are revealed and a tentative crisis prediction is presented.

  7. Machine Learning to Improve Energy Expenditure Estimation in Children With Disabilities: A Pilot Study in Duchenne Muscular Dystrophy.

    Science.gov (United States)

    Pande, Amit; Mohapatra, Prasant; Nicorici, Alina; Han, Jay J

    2016-07-19

    Children with physical impairments are at a greater risk for obesity and decreased physical activity. A better understanding of physical activity pattern and energy expenditure (EE) would lead to a more targeted approach to intervention. This study focuses on studying the use of machine-learning algorithms for EE estimation in children with disabilities. A pilot study was conducted on children with Duchenne muscular dystrophy (DMD) to identify important factors for determining EE and develop a novel algorithm to accurately estimate EE from wearable sensor-collected data. There were 7 boys with DMD, 6 healthy control boys, and 22 control adults recruited. Data were collected using smartphone accelerometer and chest-worn heart rate sensors. The gold standard EE values were obtained from the COSMED K4b2 portable cardiopulmonary metabolic unit worn by boys (aged 6-10 years) with DMD and controls. Data from this sensor setup were collected simultaneously during a series of concurrent activities. Linear regression and nonlinear machine-learning-based approaches were used to analyze the relationship between accelerometer and heart rate readings and COSMED values. Existing calorimetry equations using linear regression and nonlinear machine-learning-based models, developed for healthy adults and young children, give low correlation to actual EE values in children with disabilities (14%-40%). The proposed model for boys with DMD uses ensemble machine learning techniques and gives a 91% correlation with actual measured EE values (root mean square error of 0.017). Our results confirm that the methods developed to determine EE using accelerometer and heart rate sensor values in normal adults are not appropriate for children with disabilities and should not be used. A much more accurate model is obtained using machine-learning-based nonlinear regression specifically developed for this target population. ©Amit Pande, Prasant Mohapatra, Alina Nicorici, Jay J Han. Originally

  8. Study on on-machine defects measuring system on high power laser optical elements

    Science.gov (United States)

    Luo, Chi; Shi, Feng; Lin, Zhifan; Zhang, Tong; Wang, Guilin

    2017-10-01

    The influence of surface defects on high power laser optical elements will cause some harm to the performances of imaging system, including the energy consumption and the damage of film layer. To further increase surface defects on high power laser optical element, on-machine defects measuring system was investigated. Firstly, the selection and design are completed by the working condition analysis of the on-machine defects detection system. By designing on processing algorithms to realize the classification recognition and evaluation of surface defects. The calibration experiment of the scratch was done by using the self-made standard alignment plate. Finally, the detection and evaluation of surface defects of large diameter semi-cylindrical silicon mirror are realized. The calibration results show that the size deviation is less than 4% that meet the precision requirement of the detection of the defects. Through the detection of images the on-machine defects detection system can realize the accurate identification of surface defects.

  9. Permanently split capacitor motor-study of the design parameters

    Science.gov (United States)

    Sarac, Vasilija; Stefanov, Goce

    2017-09-01

    Paper analyzes the influence of various design parameters on torque of permanently split capacitor motor. Motor analytical model is derived and it is used for calculating the performance characteristics of basic motor model. The acquired analytical model is applied in optimization software that uses genetic algorithms (GA) as an optimization method. Optimized motor model with increased torque is derived by varying three motor parameters in GA program: winding turns ratio, average air gap flux density and motor stack length. Increase of torque has been achieved for nominal operation but also at motor starting. Accuracy of the derived models is verified by Simulink. The acquired values of several motor parameters from transient characteristics of Simulink models are compared with the corresponding values obtained from analytical models of both motors, basic and optimized. Numerical analysis, based on finite element method (FEM), is also performed for both motor models. As a result of the FEM analysis, magnetic flux density in motor cross-section is calculated and adequate conclusions are derived in relation to core saturation and air gap flux density in both motor models.

  10. Design study of a plasma-loaded CRM using TPD-II machine

    International Nuclear Information System (INIS)

    Minami, Kazuo

    2007-08-01

    Design study of an experiment for plasma-loaded cyclotron resonance maser (CRM) utilizing TPD-II Machine at NIFS, Japan is described in some detail. The principle of gyrotrons has been believed the CRM instability. However, all the existing linear theories of CRM instability include unphysical modes unstable at infinite values of axial wavenumber that can never be observed experimentally. To overcome the difficulty, we derive and analyze numerically an exact linear dispersion relation of a large orbit electron beam for CRM, and removed the unphysical modes. However, the relation is found to include two principles of cyclotron emission with oscillation frequencies above and below the branch of fast electron cyclotron wave. The former is CRM instability, and the latter is named Chrenkov instability in the azimuthal direction (CIAD). It is noted that the CIAD we found remains only a proposal of a new mechanism for cyclotron emission until the physical existence is verified experimentally. To verify the CIAD, the design study of a plasma-loaded CRM has been carried out. The apparatus consists of two portions installed in the TPD-II: A pair of helical wiggler windings to create a mono-energetic beam with 15 keV and pitch factor V θ /V z ≥1, and microwave circuits including a cylindrical TE 011 mode cavity with resonant frequency 3.45 GHz. For high plasma density n≥1.5x10 11 cm -3 from TPD-II, the CRM instability may be suppressed and the CIAD will take turn. The present experimental study contributes to a deeper understanding and a widened future prospect in gyrotron physics. (author)

  11. Dynamics of polymers in a good solvent - a molecular dynamics study using the Connection Machine

    International Nuclear Information System (INIS)

    Shannon, S.R.; Choy, T.C.

    1996-01-01

    In recent times the use of molecular dynamics simulations has become an important tool in modelling and understanding the dynamics of interacting many-body systems. With recent advances in computing power it is now feasible to perform modelling of systems which contain a large number of interacting particles, and thus to simulate the behaviour of real systems reasonably. Our earlier discoveries of anomalous corrections to scaling behaviour of the Edward's polymer were applied to study the dynamical behaviour of two dimensional polymer systems - either a single chain immersed in a fluid, a pure polymer melt, or with any concentration of polymers in the fluid. By choosing a suitable interaction potential between the fluid particles and the monomers, we are able to study the experimentally observable time dependent structure factor of polymers in a good solvent. Simulations were performed using the Connection Machine CM5 supercomputer at the Australian National University which due to its fast multi- processor nearest neighbour communications facility, enables us to easily model large systems of at least 3000 fluid plus monomer particles. Our study is based on a finite difference solution of Newton's equations of motion i.e. the Verlet algorithm, and the results are used to test current theories of polymer dynamics, which were based primarily on the earlier models proposed by Rouse (1953) and Zimm (1956). In particular dynamical scaling predictions is scrutinised to examine the effects due to the anomalous corrections-to-scaling behaviour found in an earlier work using finite-size scaling analysis of Monte-Carlo data and now understood via a new perturbation concept

  12. Machine learning approaches to evaluate correlation patterns in allosteric signaling: A case study of the PDZ2 domain

    Science.gov (United States)

    Botlani, Mohsen; Siddiqui, Ahnaf; Varma, Sameer

    2018-06-01

    Many proteins are regulated by dynamic allostery wherein regulator-induced changes in structure are comparable with thermal fluctuations. Consequently, understanding their mechanisms requires assessment of relationships between and within conformational ensembles of different states. Here we show how machine learning based approaches can be used to simplify this high-dimensional data mining task and also obtain mechanistic insight. In particular, we use these approaches to investigate two fundamental questions in dynamic allostery. First, how do regulators modify inter-site correlations in conformational fluctuations (Cij)? Second, how are regulator-induced shifts in conformational ensembles at two different sites in a protein related to each other? We address these questions in the context of the human protein tyrosine phosphatase 1E's PDZ2 domain, which is a model protein for studying dynamic allostery. We use molecular dynamics to generate conformational ensembles of the PDZ2 domain in both the regulator-bound and regulator-free states. The employed protocol reproduces methyl deuterium order parameters from NMR. Results from unsupervised clustering of Cij combined with flow analyses of weighted graphs of Cij show that regulator binding significantly alters the global signaling network in the protein; however, not by altering the spatial arrangement of strongly interacting amino acid clusters but by modifying the connectivity between clusters. Additionally, we find that regulator-induced shifts in conformational ensembles, which we evaluate by repartitioning ensembles using supervised learning, are, in fact, correlated. This correlation Δij is less extensive compared to Cij, but in contrast to Cij, Δij depends inversely on the distance from the regulator binding site. Assuming that Δij is an indicator of the transduction of the regulatory signal leads to the conclusion that the regulatory signal weakens with distance from the regulatory site. Overall, this

  13. Three-dimensional, automated, real-time video system for tracking limb motion in brain-machine interface studies.

    Science.gov (United States)

    Peikon, Ian D; Fitzsimmons, Nathan A; Lebedev, Mikhail A; Nicolelis, Miguel A L

    2009-06-15

    Collection and analysis of limb kinematic data are essential components of the study of biological motion, including research into biomechanics, kinesiology, neurophysiology and brain-machine interfaces (BMIs). In particular, BMI research requires advanced, real-time systems capable of sampling limb kinematics with minimal contact to the subject's body. To answer this demand, we have developed an automated video tracking system for real-time tracking of multiple body parts in freely behaving primates. The system employs high-contrast markers painted on the animal's joints to continuously track the three-dimensional positions of their limbs during activity. Two-dimensional coordinates captured by each video camera are combined and converted to three-dimensional coordinates using a quadratic fitting algorithm. Real-time operation of the system is accomplished using direct memory access (DMA). The system tracks the markers at a rate of 52 frames per second (fps) in real-time and up to 100fps if video recordings are captured to be later analyzed off-line. The system has been tested in several BMI primate experiments, in which limb position was sampled simultaneously with chronic recordings of the extracellular activity of hundreds of cortical cells. During these recordings, multiple computational models were employed to extract a series of kinematic parameters from neuronal ensemble activity in real-time. The system operated reliably under these experimental conditions and was able to compensate for marker occlusions that occurred during natural movements. We propose that this system could also be extended to applications that include other classes of biological motion.

  14. Landslide susceptibility mapping based on Support Vector Machine: A case study on natural slopes of Hong Kong, China

    Science.gov (United States)

    Yao, X.; Tham, L. G.; Dai, F. C.

    2008-11-01

    The Support Vector Machine (SVM) is an increasingly popular learning procedure based on statistical learning theory, and involves a training phase in which the model is trained by a training dataset of associated input and target output values. The trained model is then used to evaluate a separate set of testing data. There are two main ideas underlying the SVM for discriminant-type problems. The first is an optimum linear separating hyperplane that separates the data patterns. The second is the use of kernel functions to convert the original non-linear data patterns into the format that is linearly separable in a high-dimensional feature space. In this paper, an overview of the SVM, both one-class and two-class SVM methods, is first presented followed by its use in landslide susceptibility mapping. A study area was selected from the natural terrain of Hong Kong, and slope angle, slope aspect, elevation, profile curvature of slope, lithology, vegetation cover and topographic wetness index (TWI) were used as environmental parameters which influence the occurrence of landslides. One-class and two-class SVM models were trained and then used to map landslide susceptibility respectively. The resulting susceptibility maps obtained by the methods were compared to that obtained by the logistic regression (LR) method. It is concluded that two-class SVM possesses better prediction efficiency than logistic regression and one-class SVM. However, one-class SVM, which only requires failed cases, has an advantage over the other two methods as only "failed" case information is usually available in landslide susceptibility mapping.

  15. Acceptability of using electronic vending machines to deliver oral rapid HIV self-testing kits: a qualitative study.

    Directory of Open Access Journals (Sweden)

    Sean D Young

    Full Text Available Rates of unrecognized HIV infection are significantly higher among Latino and Black men who have sex with men (MSM. Policy makers have proposed that HIV self-testing kits and new methods for delivering self-testing could improve testing uptake among minority MSM. This study sought to conduct qualitative assessments with MSM of color to determine the acceptability of using electronic vending machines to dispense HIV self-testing kits.African American and Latino MSM were recruited using a participant pool from an existing HIV prevention trial on Facebook. If participants expressed interest in using a vending machine to receive an HIV self-testing kit, they were emailed a 4-digit personal identification number (PIN code to retrieve the test from the machine. We followed up with those who had tested to assess their willingness to participate in an interview about their experience.Twelve kits were dispensed and 8 interviews were conducted. In general, participants expressed that the vending machine was an acceptable HIV test delivery method due to its novelty and convenience.Acceptability of this delivery model for HIV testing kits was closely associated with three main factors: credibility, confidentiality, and convenience. Future research is needed to address issues, such as user-induced errors and costs, before scaling up the dispensing method.

  16. Acceptability of using electronic vending machines to deliver oral rapid HIV self-testing kits: a qualitative study.

    Science.gov (United States)

    Young, Sean D; Daniels, Joseph; Chiu, ChingChe J; Bolan, Robert K; Flynn, Risa P; Kwok, Justin; Klausner, Jeffrey D

    2014-01-01

    Rates of unrecognized HIV infection are significantly higher among Latino and Black men who have sex with men (MSM). Policy makers have proposed that HIV self-testing kits and new methods for delivering self-testing could improve testing uptake among minority MSM. This study sought to conduct qualitative assessments with MSM of color to determine the acceptability of using electronic vending machines to dispense HIV self-testing kits. African American and Latino MSM were recruited using a participant pool from an existing HIV prevention trial on Facebook. If participants expressed interest in using a vending machine to receive an HIV self-testing kit, they were emailed a 4-digit personal identification number (PIN) code to retrieve the test from the machine. We followed up with those who had tested to assess their willingness to participate in an interview about their experience. Twelve kits were dispensed and 8 interviews were conducted. In general, participants expressed that the vending machine was an acceptable HIV test delivery method due to its novelty and convenience. Acceptability of this delivery model for HIV testing kits was closely associated with three main factors: credibility, confidentiality, and convenience. Future research is needed to address issues, such as user-induced errors and costs, before scaling up the dispensing method.

  17. Study on Surface Integrity of AISI 1045 Carbon Steel when machined by Carbide Cutting Tool under wet conditions

    Directory of Open Access Journals (Sweden)

    Tamin N. Fauzi

    2017-01-01

    Full Text Available This paper presents the evaluation of surface roughness and roughness profiles when machining carbon steel under wet conditions with low and high cutting speeds. The workpiece materials and cutting tools selected in this research were AISI 1045 carbon steel and canela carbide inserts graded PM25, respectively. The cutting tools undergo machining tests by CNC turning operations and their performances were evaluated by their surface roughness value and observation of the surface roughness profile. The machining tests were held at varied cutting speeds of 35 to 53 m/min, feed rate of 0.15 to 0.50 mm/rev and a constant depth of cut of 1 mm. From the analysis, it was found that surface roughness increased as the feed rate increased. Varian of surface roughness was suspected due to interaction between cutting speeds and feed rates as well as nose radius conditions; whether from tool wear or the formation of a built-up edge. This study helps us understand the effect of cutting speed and feed rate on surface integrity, when machining AISI 1045 carbon steel using carbide cutting tools, under wet cutting conditions.

  18. A comparison study of support vector machines and hidden Markov models in machinery condition monitoring

    International Nuclear Information System (INIS)

    Miao, Qiang; Huang, Hong Zhong; Fan, Xianfeng

    2007-01-01

    Condition classification is an important step in machinery fault detection, which is a problem of pattern recognition. Currently, there are a lot of techniques in this area and the purpose of this paper is to investigate two popular recognition techniques, namely hidden Markov model and support vector machine. At the beginning, we briefly introduced the procedure of feature extraction and the theoretical background of this paper. The comparison experiment was conducted for gearbox fault detection and the analysis results from this work showed that support vector machine has better classification performance in this area

  19. A Supervised Machine Learning Study of Online Discussion Forums about Type-2 Diabetes

    DEFF Research Database (Denmark)

    Reichert, Jonathan-Raphael; Kristensen, Klaus Langholz; Mukkamala, Raghava Rao

    2017-01-01

    supervised machine learning techniques to analyze the online conversations. In order to analyse these online textual conversations, we have chosen four domain specific models (Emotions, Sentiment, Personality Traits and Patient Journey). As part of text classification, we employed the ensemble learning...... method by using 5 different supervised machine learning algorithms to build a set of text classifiers by using the voting method to predict most probable label for a given textual conversation from the online discussion forums. Our findings show that there is a high amount of trust expressed by a subset...

  20. The Machine within the Machine

    CERN Multimedia

    Katarina Anthony

    2014-01-01

    Although Virtual Machines are widespread across CERN, you probably won't have heard of them unless you work for an experiment. Virtual machines - known as VMs - allow you to create a separate machine within your own, allowing you to run Linux on your Mac, or Windows on your Linux - whatever combination you need.   Using a CERN Virtual Machine, a Linux analysis software runs on a Macbook. When it comes to LHC data, one of the primary issues collaborations face is the diversity of computing environments among collaborators spread across the world. What if an institute cannot run the analysis software because they use different operating systems? "That's where the CernVM project comes in," says Gerardo Ganis, PH-SFT staff member and leader of the CernVM project. "We were able to respond to experimentalists' concerns by providing a virtual machine package that could be used to run experiment software. This way, no matter what hardware they have ...

  1. Development of the ultrasonic fatigue testing machine due to study on giga-cycle fatigue at elevated temperature. 2001 annual report. Document on collaborative study

    International Nuclear Information System (INIS)

    Hattori, Shuji; Itoh, Takamoto

    2002-03-01

    An ultrasonic fatigue testing machine was developed to obtain the giga-cycle fatigue life at elevated temperature for safety and reliability of structural components in the faster breeder reactor (FBR). This testing machine consists of an amplifier, booster, horn and the equipments such as a system controller and data acquisition. The test specimen is attached at the end of the horn. The electric power generated in the amplifier is transformed into the mechanical vibration in the converter and is magnified in the booster and horn. The vibration was enough to fatigue the specimen. Since the test frequency is set at a resonant frequency, the shape and dimensions of specimen were designed so as to vibrate itself resonantly. However, the maximum amplitudes of stress and strain in the specimen can be calculated easily by measuring the amplitude of displacement at the end of the specimen. The developed ultrasonic fatigue testing machine enables to carry out the fatigue tests at 20 kHz so that it can perform the giga-cycle fatigue test within a very short time as compared with the regular fatigue testing machines such as a hydraulic fatigue testing machine. By clarifying the material strength characteristics in giga-cycle region, the life evaluation, design and examination of components will be more suitable than ever. This study will contribute to improve the safety and reliability of components in FBR. In this technical report, the specification and characteristics of the testing machine were described along with the several experimental results. (author)

  2. Study and implementation high speed operating of induced magnetization machines; Etude et mise en oeuvre de machines a aimantation induite fonctionnant a haute vitesse

    Energy Technology Data Exchange (ETDEWEB)

    Alhassoun, Y.

    2005-05-15

    Actually, electromechanical machines are characterized by their low cost and reduced maintenance. Therefore, new types of magnetic materials such as soft magnetic composites (SMC), have to be considered not only for multiple applications (small motors for automotive) for cost reduction, but also when considering other special requirements such as high speed drive (aircraft and space applications). Our report of thesis is articulated around four chapters: The first chapter show the various types of magnetic interactions used in the electromagnetic actuators. The second chapter is devoted to the modelling of the induced magnetic machines by analytical resolution of equations of the field in two dimensions. The third chapter presents the four configurations prototypes of switched reluctance machine which mix the exploitation of laminated materials and the soft magnetic powders. The fourth chapter discusses the critical conditions of this machines operating at high speed. We conclude, insisting on the efforts carried out in term of analytical modelling of the induced magnetization machines for their dimensions and exploited in this same structure, the soft magnetic composite materials. The results show the potential of soft magnetic powders when considering in particular the high frequency losses and their ability to favour the heat dissipation in this structure. (author)

  3. Machine learning methods to predict child posttraumatic stress: a proof of concept study.

    Science.gov (United States)

    Saxe, Glenn N; Ma, Sisi; Ren, Jiwen; Aliferis, Constantin

    2017-07-10

    The care of traumatized children would benefit significantly from accurate predictive models for Posttraumatic Stress Disorder (PTSD), using information available around the time of trauma. Machine Learning (ML) computational methods have yielded strong results in recent applications across many diseases and data types, yet they have not been previously applied to childhood PTSD. Since these methods have not been applied to this complex and debilitating disorder, there is a great deal that remains to be learned about their application. The first step is to prove the concept: Can ML methods - as applied in other fields - produce predictive classification models for childhood PTSD? Additionally, we seek to determine if specific variables can be identified - from the aforementioned predictive classification models - with putative causal relations to PTSD. ML predictive classification methods - with causal discovery feature selection - were applied to a data set of 163 children hospitalized with an injury and PTSD was determined three months after hospital discharge. At the time of hospitalization, 105 risk factor variables were collected spanning a range of biopsychosocial domains. Seven percent of subjects had a high level of PTSD symptoms. A predictive classification model was discovered with significant predictive accuracy. A predictive model constructed based on subsets of potentially causally relevant features achieves similar predictivity compared to the best predictive model constructed with all variables. Causal Discovery feature selection methods identified 58 variables of which 10 were identified as most stable. In this first proof-of-concept application of ML methods to predict childhood Posttraumatic Stress we were able to determine both predictive classification models for childhood PTSD and identify several causal variables. This set of techniques has great potential for enhancing the methodological toolkit in the field and future studies should seek to

  4. Predictive models to assess risk of type 2 diabetes, hypertension and comorbidity: machine-learning algorithms and validation using national health data from Kuwait--a cohort study.

    Science.gov (United States)

    Farran, Bassam; Channanath, Arshad Mohamed; Behbehani, Kazem; Thanaraj, Thangavel Alphonse

    2013-05-14

    We build classification models and risk assessment tools for diabetes, hypertension and comorbidity using machine-learning algorithms on data from Kuwait. We model the increased proneness in diabetic patients to develop hypertension and vice versa. We ascertain the importance of ethnicity (and natives vs expatriate migrants) and of using regional data in risk assessment. Retrospective cohort study. Four machine-learning techniques were used: logistic regression, k-nearest neighbours (k-NN), multifactor dimensionality reduction and support vector machines. The study uses fivefold cross validation to obtain generalisation accuracies and errors. Kuwait Health Network (KHN) that integrates data from primary health centres and hospitals in Kuwait. 270 172 hospital visitors (of which, 89 858 are diabetic, 58 745 hypertensive and 30 522 comorbid) comprising Kuwaiti natives, Asian and Arab expatriates. Incident type 2 diabetes, hypertension and comorbidity. Classification accuracies of >85% (for diabetes) and >90% (for hypertension) are achieved using only simple non-laboratory-based parameters. Risk assessment tools based on k-NN classification models are able to assign 'high' risk to 75% of diabetic patients and to 94% of hypertensive patients. Only 5% of diabetic patients are seen assigned 'low' risk. Asian-specific models and assessments perform even better. Pathological conditions of diabetes in the general population or in hypertensive population and those of hypertension are modelled. Two-stage aggregate classification models and risk assessment tools, built combining both the component models on diabetes (or on hypertension), perform better than individual models. Data on diabetes, hypertension and comorbidity from the cosmopolitan State of Kuwait are available for the first time. This enabled us to apply four different case-control models to assess risks. These tools aid in the preliminary non-intrusive assessment of the population. Ethnicity is seen significant

  5. Application of target costing in machining

    Science.gov (United States)

    Gopalakrishnan, Bhaskaran; Kokatnur, Ameet; Gupta, Deepak P.

    2004-11-01

    In today's intensely competitive and highly volatile business environment, consistent development of low cost and high quality products meeting the functionality requirements is a key to a company's survival. Companies continuously strive to reduce the costs while still producing quality products to stay ahead in the competition. Many companies have turned to target costing to achieve this objective. Target costing is a structured approach to determine the cost at which a proposed product, meeting the quality and functionality requirements, must be produced in order to generate the desired profits. It subtracts the desired profit margin from the company's selling price to establish the manufacturing cost of the product. Extensive literature review revealed that companies in automotive, electronic and process industries have reaped the benefits of target costing. However target costing approach has not been applied in the machining industry, but other techniques based on Geometric Programming, Goal Programming, and Lagrange Multiplier have been proposed for application in this industry. These models follow a forward approach, by first selecting a set of machining parameters, and then determining the machining cost. Hence in this study we have developed an algorithm to apply the concepts of target costing, which is a backward approach that selects the machining parameters based on the required machining costs, and is therefore more suitable for practical applications in process improvement and cost reduction. A target costing model was developed for turning operation and was successfully validated using practical data.

  6. Fully automatic CNC machining production system

    Directory of Open Access Journals (Sweden)

    Lee Jeng-Dao

    2017-01-01

    Full Text Available Customized manufacturing is increasing years by years. The consumption habits change has been cause the shorter of product life cycle. Therefore, many countries view industry 4.0 as a target to achieve more efficient and more flexible automated production. To develop an automatic loading and unloading CNC machining system via vision inspection is the first step in industrial upgrading. CNC controller is adopted as the main controller to command to the robot, conveyor, and other equipment in this study. Moreover, machine vision systems are used to detect position of material on the conveyor and the edge of the machining material. In addition, Open CNC and SCADA software will be utilized to make real-time monitor, remote system of control, alarm email notification, and parameters collection. Furthermore, RFID has been added to employee classification and management. The machine handshaking has been successfully proposed to achieve automatic vision detect, edge tracing measurement, machining and system parameters collection for data analysis to accomplish industrial automation system integration with real-time monitor.

  7. The phaco machine: analysing new technology.

    Science.gov (United States)

    Fishkind, William J

    2013-01-01

    The phaco machine is frequently overlooked as the crucial surgical instrument it is. Understanding how to set parameters is initiated by understanding fundamental concepts of machine function. This study analyses the critical concepts of partial occlusion phaco, occlusion phaco and pump technology. In addition, phaco energy categories as well as variations of phaco energy production are explored. Contemporary power modulations and pump controls allow for the enhancement of partial occlusion phacoemulsification. These significant changes in the anterior chamber dynamics produce a balanced environment for phaco; less complications; and improved patient outcomes.

  8. Correction factors for photon spectrometry in nuclear parameters study

    International Nuclear Information System (INIS)

    Patrao, Karla Cristina de Souza

    2004-10-01

    The goal of this work was the determination, using metrologic severity, the factors of correction for coincidences XX, Xγ and γγ and the factors of transference of efficiency for use in gamma spectrometry. On this way, it was carried through by determination of nuclear parameters of a nuclide used in medicine diagnostic ( 201 Tl) and the standardization of two environmental samples, of regular and irregular geometry, proceeding from the residual (ashes and slag) from the nuclear industry. The results shows that this adopted methodology is valid, and it allows its application for many different nuclides, including complex decay schema nuclides, using only photons spectrometry techniques on semiconductor detectors. (author)

  9. Comparative study of radiation shielding parameters for bismuth borate glasses

    International Nuclear Information System (INIS)

    Kaundal, Rajinder Singh

    2016-01-01

    Melt and quench technique was used for the preparation of glassy samples of the composition x Bi 2 O 3- (1-x) B 2 O 3 where x= .05 to .040. XCOM computer program is used for the evaluation of gamma-ray shielding parameters of the prepared glass samples. Further the values of mass attenuation coefficients, effective atomic number and half value layer for the glassy samples have been calculated in the energy range from 1KeV to 100GeV. Rigidity of the glass samples have been analyzed by molar volume of the prepared glass samples. (author)

  10. Comparative study of radiation shielding parameters for bismuth borate glasses

    Energy Technology Data Exchange (ETDEWEB)

    Kaundal, Rajinder Singh, E-mail: rajinder_apd@yahoo.com [Department of Physics, School of Physical Sciences, Lovely Professional University, Phagwara, Punjab (India)

    2016-07-15

    Melt and quench technique was used for the preparation of glassy samples of the composition x Bi{sub 2}O{sub 3-}(1-x) B{sub 2}O{sub 3} where x= .05 to .040. XCOM computer program is used for the evaluation of gamma-ray shielding parameters of the prepared glass samples. Further the values of mass attenuation coefficients, effective atomic number and half value layer for the glassy samples have been calculated in the energy range from 1KeV to 100GeV. Rigidity of the glass samples have been analyzed by molar volume of the prepared glass samples. (author)

  11. Comparative Study of Radiation Shielding Parameters for Bismuth Borate Glasses

    OpenAIRE

    Kaundal, Rajinder Singh

    2016-01-01

    Melt and quench technique was used for the preparation of glassy samples of the composition x Bi2O3-(1-x) B2O3 where x= .05 to .040. XCOM computer program is used for the evaluation of gamma-ray shielding parameters of the prepared glass samples. Further the values of mass attenuation coefficients, effective atomic number and half value layer for the glassy samples have been calculated in the energy range from 1KeV to 100GeV. Rigidity of the glass samples have been analyzed by molar volume of...

  12. Feasibility Study for Using a Linear Transverse Flux Machine as part of the Structure of Point Absorber Wave Energy Converter

    Directory of Open Access Journals (Sweden)

    Ilana Pereira da Costa Cunha

    2017-10-01

    Full Text Available This is a feasibility study for the generation of wave energy by means of a transverse flux machine connected to a device for converting wave energy known as Point Absorber. The article contains literature review on the topic and analysis of data obtained by means of a prototype built in the laboratory. Based on the results, the study concludes that this use is feasible.

  13. Optimization of process parameters of ECM by RSM on AISI 202 steel

    Directory of Open Access Journals (Sweden)

    P. Alex John Britto

    2015-12-01

    Full Text Available The machining of complex shaped designs was difficult earlier, but with the advent of the newer machining processes incorporating in it electrical, chemical & mechanical processes, manufacturing has redefined itself. Especially, the Electrochemical Machining (ECM process is used to machine the hard to cut materials without producing heat and friction. Hence, in this work, the ECM process has been chosen to machine SS AISI 202 steel. This study establishes the effect of process parameters such as voltage, current and concentration of electrolyte on the responses on material removal rate (MRR. In this work, second-order quadratic models were developed for MRR, considering the electrolyte concentration, voltage and current as the machining parameters, using central composite design. The developed models were used for Response Surface Methodology (RSM optimization by desirability function approach to determine the optimum machining parameters.

  14. Vector control of induction machines

    CERN Document Server

    Robyns, Benoit

    2012-01-01

    After a brief introduction to the main law of physics and fundamental concepts inherent in electromechanical conversion, ""Vector Control of Induction Machines"" introduces the standard mathematical models for induction machines - whichever rotor technology is used - as well as several squirrel-cage induction machine vector-control strategies. The use of causal ordering graphs allows systematization of the design stage, as well as standardization of the structure of control devices. ""Vector Control of Induction Machines"" suggests a unique approach aimed at reducing parameter sensitivity for

  15. An Evaluative Study of Machine Translation in the EFL Scenario of Saudi Arabia

    Science.gov (United States)

    Al-Tuwayrish, Raneem Khalid

    2016-01-01

    Artificial Intelligence or AI as it is popularly known and its corollary, Machine Translation (MT) have long engaged scientists, thinkers and linguists alike in the twenty first century. However, the wider question that lies in the relation between technology and translation is, What does technology do to language? This is an important question in…

  16. A comparative study of machine learning classifiers for modeling travel mode choice

    NARCIS (Netherlands)

    Hagenauer, J; Helbich, M

    2017-01-01

    The analysis of travel mode choice is an important task in transportation planning and policy making in order to understand and predict travel demands. While advances in machine learning have led to numerous powerful classifiers, their usefulness for modeling travel mode choice remains largely

  17. Advice taking from humans and machines: an fMRI and effective connectivity study

    Directory of Open Access Journals (Sweden)

    Kimberly Goodyear

    2016-11-01

    Full Text Available With new technological advances, advice can come from different sources such as machines or humans, but how individuals respond to such advice and the neural correlates involved need to be better understood. We combined functional MRI and multivariate Granger causality analysis with an X-ray luggage-screening task to investigate the neural basis and corresponding effective connectivity involved with advice utilization from agents framed as experts. Participants were asked to accept or reject good or bad advice from a human or machine agent with low reliability (high false alarm rate. We showed that unreliable advice decreased performance overall and participants interacting with the human agent had a greater depreciation of advice utilization during bad advice compared to the machine agent. These differences in advice utilization can be perceivably due to reevaluation of expectations arising from association of dispositional credibility for each agent. We demonstrated that differences in advice utilization engaged brain regions that may be associated with evaluation of personal characteristics and traits (precuneus, posterior cingulate cortex, temporoparietal junction and interoception (posterior insula. We found that the right posterior insula and left precuneus were the drivers of the advice utilization network that were reciprocally connected to each other and also projected to all other regions. Our behavioral and neuroimaging results have significant implications for society because of progressions in technology and increased interactions with machines.

  18. The development of mixer machine for organic animal feed production: Proposed study

    Science.gov (United States)

    Leman, A. M.; Wahab, R. Abdul; Zakaria, Supaat; Feriyanto, Dafit; Nor, M. I. F. Che Mohd; Muzarpar, Syafiq

    2017-09-01

    Mixer machine plays a major role in producing homogenous composition of animal feed. Long time production, inhomogeneous and minor agglomeration has been observed by existing mixer. Therefore, this paper proposed continuous mixer to enhance mixing efficiency with shorter time of mixing process in order to abbreviate the whole process in animal feed production. Through calculation of torque, torsion, bending, power and energy consumption will perform in mixer machine process. Proposed mixer machine is designed by two layer buckets with purpose for continuity of mixing process. Mixing process was performed by 4 blades which consists of various arm length such as 50, 100,150 and 225 mm in 60 rpm velocity clockwise rotation. Therefore by using this machine will produce the homogenous composition of animal feed through nutrition analysis and short operation time of mixing process approximately of 5 minutes. Therefore, the production of animal feed will suitable for various animals including poultry and aquatic fish. This mixer will available for various organic material in animal feed production. Therefore, this paper will highlights some areas such as continues animal feed supply chain and bio-based animal feed.

  19. Machine Learning for Social Services: A Study of Prenatal Case Management in Illinois.

    Science.gov (United States)

    Pan, Ian; Nolan, Laura B; Brown, Rashida R; Khan, Romana; van der Boor, Paul; Harris, Daniel G; Ghani, Rayid

    2017-06-01

    To evaluate the positive predictive value of machine learning algorithms for early assessment of adverse birth risk among pregnant women as a means of improving the allocation of social services. We used administrative data for 6457 women collected by the Illinois Department of Human Services from July 2014 to May 2015 to develop a machine learning model for adverse birth prediction and improve upon the existing paper-based risk assessment. We compared different models and determined the strongest predictors of adverse birth outcomes using positive predictive value as the metric for selection. Machine learning algorithms performed similarly, outperforming the current paper-based risk assessment by up to 36%; a refined paper-based assessment outperformed the current assessment by up to 22%. We estimate that these improvements will allow 100 to 170 additional high-risk pregnant women screened for program eligibility each year to receive services that would have otherwise been unobtainable. Our analysis exhibits the potential for machine learning to move government agencies toward a more data-informed approach to evaluating risk and providing social services. Overall, such efforts will improve the efficiency of allocating resource-intensive interventions.

  20. Anarchism & Educational Policy Studies; A Marxist View of Joel Spring's "The Sorting Machine."

    Science.gov (United States)

    Berlowitz, Marvin J.

    A critical analysis and interpretation of "The Sorting Machine" by Joel H. Spring is presented. The book, which uses a historical revisionist approach to trace the development and impact of the corporate-government-foundation network on the ideological orientation of the American educational system, makes its greatest contribution by…