Principle of maximum entropy for reliability analysis in the design of machine components

NASA Astrophysics Data System (ADS)

Zhang, Yimin

2018-03-01

We studied the reliability of machine components with parameters that follow an arbitrary statistical distribution using the principle of maximum entropy (PME). We used PME to select the statistical distribution that best fits the available information. We also established a probability density function (PDF) and a failure probability model for the parameters of mechanical components using the concept of entropy and the PME. We obtained the first four moments of the state function for reliability analysis and design. Furthermore, we attained an estimate of the PDF with the fewest human bias factors using the PME. This function was used to calculate the reliability of the machine components, including a connecting rod, a vehicle half-shaft, a front axle, a rear axle housing, and a leaf spring, which have parameters that typically follow a non-normal distribution. Simulations were conducted for comparison. This study provides a design methodology for the reliability of mechanical components for practical engineering projects.

Voltage THD Improvement for an Outer Rotor Permanent Magnet Synchronous Machine

NASA Astrophysics Data System (ADS)

de la Cruz, Javier; Ramirez, Juan M.; Leyva, Luis

2013-08-01

This article deals with the design of an outer rotor Permanent Magnet Synchronous Machines (PMSM) driven by wind turbines. The Voltage Total Harmonic Distortion (VTHD) is especially addressed, under design parameters' handling, i.e., the geometry of the stator, the polar arc percentage, the air gap, the skew angle in rotor poles, the pole length and the core steel class. Seventy-six cases are simulated and the results provide information useful for designing this kind of machines. The study is conducted on a 5 kW PMSM.

Design of reinforcement welding machine within steel framework for marine engineering

NASA Astrophysics Data System (ADS)

Wang, Gang; Wu, Jin

2017-04-01

In this project, a design scheme that reinforcement welding machine is added within the steel framework is proposed according to the double-side welding technology for box-beam structure in marine engineering. Then the design and development of circuit and transmission mechanism for new welding equipment are completed as well with one sample machine being made. Moreover, the trial running is finished finally. Main technical parameters of the equipment are: the working stroke: ≥1500mm, the welding speed: 8˜15cm/min and the welding sheet thickness: ≥20mm.

Investigation of Machine-ability of Inconel 800 in EDM with Coated Electrode

NASA Astrophysics Data System (ADS)

Karunakaran, K.; Chandrasekaran, M.

2017-03-01

The Inconel 800 is a high temperature application alloy which is classified as a nickel based super alloy. It has wide scope in aerospace engineering, gas Turbine etc. The machine-ability studies were found limited on this material. Hence This research focuses on machine-ability studies on EDM of Inconel 800 with Silver Coated Electrolyte Copper Electrode. The purpose of coating on electrode is to reduce tool wear. The factors pulse on Time, Pulse off Time and Peck Current were considered to observe the responses of surface roughness, material removal rate, tool wear rate. Taguchi Full Factorial Design is employed for Design the experiment. Some specific findings were reported and the percentage of contribution of each parameter was furnished

The design and improvement of radial tire molding machine

NASA Astrophysics Data System (ADS)

Wang, Wenhao; Zhang, Tao

2018-04-01

This paper presented that the high accuracy semisteel meridian tire molding machine structure configurations, combining tyre high precision characteristics, the original structure and parameter optimization, technology improvement innovation design period of opening and closing machine rotary shaping drum institutions. This way out of the shaft from the structure to the push-pull type movable shaping drum of thinking limit, compared with the specifications and shaping drum can smaller contraction, is conducive to forming the tire and reduce the tire deformation.

Design and Development of Maize Dehusker cum Sheller: A Technology for Northern Transition Zone of Karnataka, India

NASA Astrophysics Data System (ADS)

Chilur, Rudragouda; Kumar, Sushilendra

2018-06-01

The Maize ( Zea mays L.) crop is one of the most important cereal in agricultural production systems of Northern Transition Zone (Hyderabad-Karnataka region) in India. These Hyderabad Karnataka farmers (small-medium) are lack of economic technologies with maize dehusking and shelling, which fulfils the two major needs as crops and as livestock in farming. The portable medium size (600 kg/h capacity) electric motor (2.23 kW) operated Maize Dehusker cum Sheller (MDS) was designed to resolve the issue by considering engineering properties of maize. The developed trapezium shaped MDS machine having overall dimensions (length × (top and bottom) × height) of 1200 × (500 and 610) × 810 mm. The selected operational parameters viz, cylinder peripheral speed (7.1 m/s), concave clearance (25 mm) and feed rate (600 kg/h) were studied for machine-performance and seed-quality parameters. The performance of machine under these parameters showed the dehusking efficiency of 99.56%, shelling efficiency of 98.01%, cleaning efficiency of 99.11%, total loss of 3.63% machine capacity of 527.11 kg/kW-h and germination percentage of 98.93%. Overall machine performance was found satisfactory for maize dehusking cum shelling operation as well as to produce the maize grains for seeding purpose.

Design and Development of Maize Dehusker cum Sheller: A Technology for Northern Transition Zone of Karnataka, India

NASA Astrophysics Data System (ADS)

Chilur, Rudragouda; Kumar, Sushilendra

2018-02-01

The Maize (Zea mays L.) crop is one of the most important cereal in agricultural production systems of Northern Transition Zone (Hyderabad-Karnataka region) in India. These Hyderabad Karnataka farmers (small-medium) are lack of economic technologies with maize dehusking and shelling, which fulfils the two major needs as crops and as livestock in farming. The portable medium size (600 kg/h capacity) electric motor (2.23 kW) operated Maize Dehusker cum Sheller (MDS) was designed to resolve the issue by considering engineering properties of maize. The developed trapezium shaped MDS machine having overall dimensions (length × (top and bottom) × height) of 1200 × (500 and 610) × 810 mm. The selected operational parameters viz, cylinder peripheral speed (7.1 m/s), concave clearance (25 mm) and feed rate (600 kg/h) were studied for machine-performance and seed-quality parameters. The performance of machine under these parameters showed the dehusking efficiency of 99.56%, shelling efficiency of 98.01%, cleaning efficiency of 99.11%, total loss of 3.63% machine capacity of 527.11 kg/kW-h and germination percentage of 98.93%. Overall machine performance was found satisfactory for maize dehusking cum shelling operation as well as to produce the maize grains for seeding purpose.

Tuning Parameters in Heuristics by Using Design of Experiments Methods

NASA Technical Reports Server (NTRS)

Arin, Arif; Rabadi, Ghaith; Unal, Resit

2010-01-01

With the growing complexity of today's large scale problems, it has become more difficult to find optimal solutions by using exact mathematical methods. The need to find near-optimal solutions in an acceptable time frame requires heuristic approaches. In many cases, however, most heuristics have several parameters that need to be "tuned" before they can reach good results. The problem then turns into "finding best parameter setting" for the heuristics to solve the problems efficiently and timely. One-Factor-At-a-Time (OFAT) approach for parameter tuning neglects the interactions between parameters. Design of Experiments (DOE) tools can be instead employed to tune the parameters more effectively. In this paper, we seek the best parameter setting for a Genetic Algorithm (GA) to solve the single machine total weighted tardiness problem in which n jobs must be scheduled on a single machine without preemption, and the objective is to minimize the total weighted tardiness. Benchmark instances for the problem are available in the literature. To fine tune the GA parameters in the most efficient way, we compare multiple DOE models including 2-level (2k ) full factorial design, orthogonal array design, central composite design, D-optimal design and signal-to-noise (SIN) ratios. In each DOE method, a mathematical model is created using regression analysis, and solved to obtain the best parameter setting. After verification runs using the tuned parameter setting, the preliminary results for optimal solutions of multiple instances were found efficiently.

Guidelines for reducing dynamic loads in two-bladed teetering-hub downwind wind turbines

NASA Astrophysics Data System (ADS)

Wright, A. D.; Bir, G. S.; Butterfield, C. D.

1995-06-01

A major goal of the federal Wind Energy Program is the rapid development and validation of structural models to determine loads and response for a wide variety of different wind turbine configurations operating under extreme conditions. Such codes are crucial to the successful design of future advanced wind turbines. In previous papers the authors described steps they took to develop a model of a two-bladed teetering-hub downwind wind turbine using ADAMS (Automatic Dynamic Analysis of Mechanical Systems), as well as comparison of model predictions to test data. In this paper they show the use of this analytical model to study the influence of various turbine parameters on predicted system loads. They concentrate their study on turbine response in the frequency range of six to ten times the rotor rotational frequency (6P to 10P). Their goal is to identify the most important parameters which influence the response of this type of machine in this frequency range and give turbine designers some general design guidelines for designing two-bladed teetering-hub machines to be less susceptible to vibration. They study the effects of such parameters as blade edgewise and flapwise stiffness, tower top stiffness, blade tip-brake mass, low-speed shaft stiffness, nacelle mass momenta of inertia, and rotor speed. They show which parameters can be varied in order to make the turbine less responsive to such atmospheric inputs as wind shear and tower shadow. They then give designers a set of design guidelines in order to show how these machines can be designed to be less responsive to these inputs.

Calculation of parameters of technological equipment for deep-sea mining

NASA Astrophysics Data System (ADS)

Yungmeister, D. A.; Ivanov, S. E.; Isaev, A. I.

2018-03-01

The actual problem of extracting minerals from the bottom of the world ocean is considered. On the ocean floor, three types of minerals are of interest: iron-manganese concretions (IMC), cobalt-manganese crusts (CMC) and sulphides. The analysis of known designs of machines and complexes for the extraction of IMC is performed. These machines are based on the principle of excavating the bottom surface; however such methods do not always correspond to “gentle” methods of mining. The ecological purity of such mining methods does not meet the necessary requirements. Such machines require the transmission of high electric power through the water column, which in some cases is a significant challenge. The authors analyzed the options of transportation of the extracted mineral from the bottom. The paper describes the design of machines that collect IMC by the method of vacuum suction. In this method, the gripping plates or drums are provided with cavities in which a vacuum is created and individual IMC are attracted to the devices by a pressure drop. The work of such machines can be called “gentle” processing technology of the bottom areas. Their environmental impact is significantly lower than mechanical devices that carry out the raking of IMC. The parameters of the device for lifting the IMC collected on the bottom are calculated. With the use of Kevlar ropes of serial production up to 0.06 meters in diameter, with a cycle time of up to 2 hours and a lifting speed of up to 3 meters per second, a productivity of about 400,000 tons per year can be realized for IMC. The development of machines based on the calculated parameters and approbation of their designs will create a unique complex for the extraction of minerals at oceanic deposits.

Geometric dimension model of virtual astronaut body for ergonomic analysis of man-machine space system

NASA Astrophysics Data System (ADS)

Qianxiang, Zhou

2012-07-01

It is very important to clarify the geometric characteristic of human body segment and constitute analysis model for ergonomic design and the application of ergonomic virtual human. The typical anthropometric data of 1122 Chinese men aged 20-35 years were collected using three-dimensional laser scanner for human body. According to the correlation between different parameters, curve fitting were made between seven trunk parameters and ten body parameters with the SPSS 16.0 software. It can be concluded that hip circumference and shoulder breadth are the most important parameters in the models and the two parameters have high correlation with the others parameters of human body. By comparison with the conventional regressive curves, the present regression equation with the seven trunk parameters is more accurate to forecast the geometric dimensions of head, neck, height and the four limbs with high precision. Therefore, it is greatly valuable for ergonomic design and analysis of man-machine system.This result will be very useful to astronaut body model analysis and application.

Highly Productive Tools For Turning And Milling

NASA Astrophysics Data System (ADS)

Vasilko, Karol

2015-12-01

Beside cutting speed, shift is another important parameter of machining. Its considerable influence is shown mainly in the workpiece machined surface microgeometry. In practice, mainly its combination with the radius of cutting tool tip rounding is used. Options to further increase machining productivity and machined surface quality are hidden in this approach. The paper presents variations of the design of productive cutting tools for lathe work and milling on the base of the use of the laws of the relationship among the highest reached uneveness of machined surface, tool tip radius and shift.

Theoretical study of cut area of reduction of large surfaces of rotation parts on machines with rotary cutters “Extra”

NASA Astrophysics Data System (ADS)

Bondarenko, J. A.; Fedorenko, M. A.; Pogonin, A. A.

2018-03-01

Large parts can be treated without disassembling machines using “Extra”, having technological and design challenges, which differ from the challenges in the processing of these components on the stationary machine. Extension machines are used to restore large parts up to the condition allowing one to use them in a production environment. To achieve the desired accuracy and surface roughness parameters, the surface after rotary grinding becomes recoverable, which greatly increases complexity. In order to improve production efficiency and productivity of the process, the qualitative rotary processing of the machined surface is applied. The rotary cutting process includes a continuous change of the cutting edge surfaces. The kinematic parameters of a rotary cutting define its main features and patterns, the cutting operation of the rotary cutting instrument.

An algorithm for the design and tuning of RF accelerating structures with variable cell lengths

NASA Astrophysics Data System (ADS)

Lal, Shankar; Pant, K. K.

2018-05-01

An algorithm is proposed for the design of a π mode standing wave buncher structure with variable cell lengths. It employs a two-parameter, multi-step approach for the design of the structure with desired resonant frequency and field flatness. The algorithm, along with analytical scaling laws for the design of the RF power coupling slot, makes it possible to accurately design the structure employing a freely available electromagnetic code like SUPERFISH. To compensate for machining errors, a tuning method has been devised to achieve desired RF parameters for the structure, which has been qualified by the successful tuning of a 7-cell buncher to π mode frequency of 2856 MHz with field flatness <3% and RF coupling coefficient close to unity. The proposed design algorithm and tuning method have demonstrated the feasibility of developing an S-band accelerating structure for desired RF parameters with a relatively relaxed machining tolerance of ∼ 25 μm. This paper discusses the algorithm for the design and tuning of an RF accelerating structure with variable cell lengths.

Design of a cardiac monitor in terms of parameters of QRS complex.

PubMed

Chen, Zhen-cheng; Ni, Li-li; Su, Ke-ping; Wang, Hong-yan; Jiang, Da-zong

2002-08-01

Objective. To design a portable cardiac monitor system based on the available ordinary ECG machine and works on the basis of QRS parameters. Method. The 80196 single chip microcomputer was used as the central microprocessor and real time electrocardiac signal was collected and analyzed [correction of analysized] in the system. Result. Apart from the performance of an ordinary monitor, this machine possesses also the following functions: arrhythmia analysis, HRV analysis, alarm, freeze, and record of automatic papering. Convenient in carrying, the system is powered by AC or DC sources. Stability, low power and low cost are emphasized in the hardware design; and modularization method is applied in software design. Conclusion. Popular in usage and low cost made the portable monitor system suitable for use under simple conditions.

Investigation of a tubular dual-stator flux-switching permanent-magnet linear generator for free-piston energy converter

NASA Astrophysics Data System (ADS)

Sui, Yi; Zheng, Ping; Tong, Chengde; Yu, Bin; Zhu, Shaohong; Zhu, Jianguo

2015-05-01

This paper describes a tubular dual-stator flux-switching permanent-magnet (PM) linear generator for free-piston energy converter. The operating principle, topology, and design considerations of the machine are investigated. Combining the motion characteristic of free-piston Stirling engine, a tubular dual-stator PM linear generator is designed by finite element method. Some major structural parameters, such as the outer and inner radii of the mover, PM thickness, mover tooth width, tooth width of the outer and inner stators, etc., are optimized to improve the machine performances like thrust capability and power density. In comparison with conventional single-stator PM machines like moving-magnet linear machine and flux-switching linear machine, the proposed dual-stator flux-switching PM machine shows advantages in higher mass power density, higher volume power density, and lighter mover.

A hybrid genetic algorithm-extreme learning machine approach for accurate significant wave height reconstruction

NASA Astrophysics Data System (ADS)

Alexandre, E.; Cuadra, L.; Nieto-Borge, J. C.; Candil-García, G.; del Pino, M.; Salcedo-Sanz, S.

2015-08-01

Wave parameters computed from time series measured by buoys (significant wave height Hs, mean wave period, etc.) play a key role in coastal engineering and in the design and operation of wave energy converters. Storms or navigation accidents can make measuring buoys break down, leading to missing data gaps. In this paper we tackle the problem of locally reconstructing Hs at out-of-operation buoys by using wave parameters from nearby buoys, based on the spatial correlation among values at neighboring buoy locations. The novelty of our approach for its potential application to problems in coastal engineering is twofold. On one hand, we propose a genetic algorithm hybridized with an extreme learning machine that selects, among the available wave parameters from the nearby buoys, a subset FnSP with nSP parameters that minimizes the Hs reconstruction error. On the other hand, we evaluate to what extent the selected parameters in subset FnSP are good enough in assisting other machine learning (ML) regressors (extreme learning machines, support vector machines and gaussian process regression) to reconstruct Hs. The results show that all the ML method explored achieve a good Hs reconstruction in the two different locations studied (Caribbean Sea and West Atlantic).

Linear-hall sensor based force detecting unit for lower limb exoskeleton

NASA Astrophysics Data System (ADS)

Li, Hongwu; Zhu, Yanhe; Zhao, Jie; Wang, Tianshuo; Zhang, Zongwei

2018-04-01

This paper describes a knee-joint human-machine interaction force sensor for lower-limb force-assistance exoskeleton. The structure is designed based on hall sensor and series elastic actuator (SEA) structure. The work we have done includes the structure design, the parameter determination and dynamic simulation. By converting the force signal into macro displacement and output voltage, we completed the measurement of man-machine interaction force. And it is proved by experiments that the design is simple, stable and low-cost.

Modelling of teeth of a gear transmission for modern manufacturing technologies

NASA Astrophysics Data System (ADS)

Monica, Z.; Banaś, W.; Ćwikla, G.; Topolska, S.

2017-08-01

The technological process of manufacturing of gear wheels is influenced by many factors. It is designated depending on the type of material from which the gear is to be produced, its heat treatment parameters, the required accuracy, the geometrical form and the modifications of the tooth. Therefor the parameters selection process is not easy and moreover it is unambiguous. Another important stage of the technological process is the selection of appropriate tools to properly machine teeth in the operations of both roughing and finishing. In the presented work the focus is put first of all on modern production methods of gears using technologically advanced instruments in comparison with conventional tools. Conventional processing tools such as gear hobbing cutters or Fellows gear-shaper cutters are used from the beginning of the machines for the production of gear wheels. With the development of technology and the creation of CNC machines designated for machining of gears wheel it was also developed the manufacturing technology as well as the design knowledge concerning the technological tools. Leading manufacturers of cutting tools extended the range of tools designated for machining of gears on the so-called hobbing cutters with inserted cemented carbide tips. The same have be introduced to Fellows gear-shaper cutters. The results of tests show that is advantaged to use hobbing cutters with inserted cemented carbide tips for milling gear wheels with a high number of teeth, where the time gains are very high, in relation to the use of conventional milling cutters.

[The design and experiment of multi-parameter water quality monitoring microsystem based on MOEMS microspectrometer].

PubMed

Wei, Kang-Lin; Wen, Zhi-Yu; Guo, Jian; Chen, Song-Bo

2012-07-01

Aiming at the monitoring and protecting of water resource environment, a multi-parameter water quality monitoring microsystem based on microspectrometer was put forward in the present paper. The microsystem is mainly composed of MOEMS microspectrometer, flow paths system and embedded measuring & controlling system. It has the functions of self-injecting samples and detection regents, automatic constant temperature, self -stirring, self- cleaning and samples' spectrum detection. The principle prototype machine of the microsystem was developed, and its structure principle was introduced in the paper. Through experiment research, it was proved that the principle prototype machine can rapidly detect quite a few water quality parameters and can meet the demands of on-line water quality monitoring, moreover, the principle prototype machine has strong function expansibility.

Effect of hole geometry and Electric-Discharge Machining (EDM) on airflow rates through small diameter holes in turbine blade material

NASA Technical Reports Server (NTRS)

Hippensteele, S. A.; Cochran, R. P.

1980-01-01

The effects of two design parameters, electrode diameter and hole angle, and two machine parameters, electrode current and current-on time, on air flow rates through small-diameter (0.257 to 0.462 mm) electric-discharge-machined holes were measured. The holes were machined individually in rows of 14 each through 1.6 mm thick IN-100 strips. The data showed linear increase in air flow rate with increases in electrode cross sectional area and current-on time and little change with changes in hole angle and electrode current. The average flow-rate deviation (from the mean flow rate for a given row) decreased linearly with electrode diameter and increased with hole angle. Burn time and finished hole diameter were also measured.

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

NASA Astrophysics Data System (ADS)

Khidhir, Basim A.; Mohamed, Bashir

2011-02-01

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.

Design Enhancement and Performance Examination of External Rotor Switched Flux Permanent Magnet Machine for Downhole Application

NASA Astrophysics Data System (ADS)

Kumar, R.; Sulaiman, E.; Soomro, H. A.; Jusoh, L. I.; Bahrim, F. S.; Omar, M. F.

2017-08-01

The recent change in innovation and employments of high-temperature magnets, permanent magnet flux switching machine (PMFSM) has turned out to be one of the suitable contenders for seaward boring, however, less intended for downhole because of high atmospheric temperature. Subsequently, this extensive review manages the design enhancement and performance examination of external rotor PMFSM for the downhole application. Preparatory, the essential design parameters required for machine configuration are computed numerically. At that point, the design enhancement strategy is actualized through deterministic technique. At last, preliminary and refined execution of the machine is contrasted and as a consequence, the yield torque is raised from 16.39Nm to 33.57Nm while depreciating the cogging torque and PM weight up to 1.77Nm and 0.79kg, individually. In this manner, it is inferred that purposed enhanced design of 12slot-22pole with external rotor is convenient for the downhole application.

A general electromagnetic excitation model for electrical machines considering the magnetic saturation and rub impact

NASA Astrophysics Data System (ADS)

Xu, Xueping; Han, Qinkai; Chu, Fulei

2018-03-01

The electromagnetic vibration of electrical machines with an eccentric rotor has been extensively investigated. However, magnetic saturation was often neglected. Moreover, the rub impact between the rotor and stator is inevitable when the amplitude of the rotor vibration exceeds the air-gap. This paper aims to propose a general electromagnetic excitation model for electrical machines. First, a general model which takes the magnetic saturation and rub impact into consideration is proposed and validated by the finite element method and reference. The dynamic equations of a Jeffcott rotor system with electromagnetic excitation and mass imbalance are presented. Then, the effects of pole-pair number and rubbing parameters on vibration amplitude are studied and approaches restraining the amplitude are put forward. Finally, the influences of mass eccentricity, resultant magnetomotive force (MMF), stiffness coefficient, damping coefficient, contact stiffness and friction coefficient on the stability of the rotor system are investigated through the Floquet theory, respectively. The amplitude jumping phenomenon is observed in a synchronous generator for different pole-pair numbers. The changes of design parameters can alter the stability states of the rotor system and the range of parameter values forms the zone of stability, which lays helpful suggestions for the design and application of the electrical machines.

Development of Processing Parameters for Organic Binders Using Selective Laser Sintering

NASA Technical Reports Server (NTRS)

Mobasher, Amir A.

2003-01-01

This document describes rapid prototyping, its relation to Computer Aided Design (CAD), and the application of these techniques to choosing parameters for Selective Laser Sintering (SLS). The document reviews the parameters selected by its author for his project, the SLS machine used, and its software.

Developing Parametric Models for the Assembly of Machine Fixtures for Virtual Multiaxial CNC Machining Centers

NASA Astrophysics Data System (ADS)

Balaykin, A. V.; Bezsonov, K. A.; Nekhoroshev, M. V.; Shulepov, A. P.

2018-01-01

This paper dwells upon a variance parameterization method. Variance or dimensional parameterization is based on sketching, with various parametric links superimposed on the sketch objects and user-imposed constraints in the form of an equation system that determines the parametric dependencies. This method is fully integrated in a top-down design methodology to enable the creation of multi-variant and flexible fixture assembly models, as all the modeling operations are hierarchically linked in the built tree. In this research the authors consider a parameterization method of machine tooling used for manufacturing parts using multiaxial CNC machining centers in the real manufacturing process. The developed method allows to significantly reduce tooling design time when making changes of a part’s geometric parameters. The method can also reduce time for designing and engineering preproduction, in particular, for development of control programs for CNC equipment and control and measuring machines, automate the release of design and engineering documentation. Variance parameterization helps to optimize construction of parts as well as machine tooling using integrated CAE systems. In the framework of this study, the authors demonstrate a comprehensive approach to parametric modeling of machine tooling in the CAD package used in the real manufacturing process of aircraft engines.

Network Modeling and Energy-Efficiency Optimization for Advanced Machine-to-Machine Sensor Networks

PubMed Central

Jung, Sungmo; Kim, Jong Hyun; Kim, Seoksoo

2012-01-01

Wireless machine-to-machine sensor networks with multiple radio interfaces are expected to have several advantages, including high spatial scalability, low event detection latency, and low energy consumption. Here, we propose a network model design method involving network approximation and an optimized multi-tiered clustering algorithm that maximizes node lifespan by minimizing energy consumption in a non-uniformly distributed network. Simulation results show that the cluster scales and network parameters determined with the proposed method facilitate a more efficient performance compared to existing methods. PMID:23202190

PredicT-ML: a tool for automating machine learning model building with big clinical data.

PubMed

Luo, Gang

2016-01-01

Predictive modeling is fundamental to transforming large clinical data sets, or "big clinical data," into actionable knowledge for various healthcare applications. Machine learning is a major predictive modeling approach, but two barriers make its use in healthcare challenging. First, a machine learning tool user must choose an algorithm and assign one or more model parameters called hyper-parameters before model training. The algorithm and hyper-parameter values used typically impact model accuracy by over 40 %, but their selection requires many labor-intensive manual iterations that can be difficult even for computer scientists. Second, many clinical attributes are repeatedly recorded over time, requiring temporal aggregation before predictive modeling can be performed. Many labor-intensive manual iterations are required to identify a good pair of aggregation period and operator for each clinical attribute. Both barriers result in time and human resource bottlenecks, and preclude healthcare administrators and researchers from asking a series of what-if questions when probing opportunities to use predictive models to improve outcomes and reduce costs. This paper describes our design of and vision for PredicT-ML (prediction tool using machine learning), a software system that aims to overcome these barriers and automate machine learning model building with big clinical data. The paper presents the detailed design of PredicT-ML. PredicT-ML will open the use of big clinical data to thousands of healthcare administrators and researchers and increase the ability to advance clinical research and improve healthcare.

Parametric Optimization of Wire Electrical Discharge Machining of Powder Metallurgical Cold Worked Tool Steel using Taguchi Method

NASA Astrophysics Data System (ADS)

Sudhakara, Dara; Prasanthi, Guvvala

2017-04-01

Wire Cut EDM is an unconventional machining process used to build components of complex shape. The current work mainly deals with optimization of surface roughness while machining P/M CW TOOL STEEL by Wire cut EDM using Taguchi method. The process parameters of the Wire Cut EDM is ON, OFF, IP, SV, WT, and WP. L27 OA is used for to design of the experiments for conducting experimentation. In order to find out the effecting parameters on the surface roughness, ANOVA analysis is engaged. The optimum levels for getting minimum surface roughness is ON = 108 µs, OFF = 63 µs, IP = 11 A, SV = 68 V and WT = 8 g.

Machine-learned and codified synthesis parameters of oxide materials

NASA Astrophysics Data System (ADS)

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.

Multiple performance characteristics optimization for Al 7075 on electric discharge drilling by Taguchi grey relational theory

NASA Astrophysics Data System (ADS)

Khanna, Rajesh; Kumar, Anish; Garg, Mohinder Pal; Singh, Ajit; Sharma, Neeraj

2015-12-01

Electric discharge drill machine (EDDM) is a spark erosion process to produce micro-holes in conductive materials. This process is widely used in aerospace, medical, dental and automobile industries. As for the performance evaluation of the electric discharge drilling machine, it is very necessary to study the process parameters of machine tool. In this research paper, a brass rod 2 mm diameter was selected as a tool electrode. The experiments generate output responses such as tool wear rate (TWR). The best parameters such as pulse on-time, pulse off-time and water pressure were studied for best machining characteristics. This investigation presents the use of Taguchi approach for better TWR in drilling of Al-7075. A plan of experiments, based on L27 Taguchi design method, was selected for drilling of material. Analysis of variance (ANOVA) shows the percentage contribution of the control factor in the machining of Al-7075 in EDDM. The optimal combination levels and the significant drilling parameters on TWR were obtained. The optimization results showed that the combination of maximum pulse on-time and minimum pulse off-time gives maximum MRR.

Multivariate Statistical Analysis of Cigarette Design Feature Influence on ISO TNCO Yields.

PubMed

Agnew-Heard, Kimberly A; Lancaster, Vicki A; Bravo, Roberto; Watson, Clifford; Walters, Matthew J; Holman, Matthew R

2016-06-20

The aim of this study is to explore how differences in cigarette physical design parameters influence tar, nicotine, and carbon monoxide (TNCO) yields in mainstream smoke (MSS) using the International Organization of Standardization (ISO) smoking regimen. Standardized smoking methods were used to evaluate 50 U.S. domestic brand cigarettes and a reference cigarette representing a range of TNCO yields in MSS collected from linear smoking machines using a nonintense smoking regimen. Multivariate statistical methods were used to form clusters of cigarettes based on their ISO TNCO yields and then to explore the relationship between the ISO generated TNCO yields and the nine cigarette physical design parameters between and within each cluster simultaneously. The ISO generated TNCO yields in MSS are 1.1-17.0 mg tar/cigarette, 0.1-2.2 mg nicotine/cigarette, and 1.6-17.3 mg CO/cigarette. Cluster analysis divided the 51 cigarettes into five discrete clusters based on their ISO TNCO yields. No one physical parameter dominated across all clusters. Predicting ISO machine generated TNCO yields based on these nine physical design parameters is complex due to the correlation among and between the nine physical design parameters and TNCO yields. From these analyses, it is estimated that approximately 20% of the variability in the ISO generated TNCO yields comes from other parameters (e.g., filter material, filter type, inclusion of expanded or reconstituted tobacco, and tobacco blend composition, along with differences in tobacco leaf origin and stalk positions and added ingredients). A future article will examine the influence of these physical design parameters on TNCO yields under a Canadian Intense (CI) smoking regimen. Together, these papers will provide a more robust picture of the design features that contribute to TNCO exposure across the range of real world smoking patterns.

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

NASA Astrophysics Data System (ADS)

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.

Optimization of process parameters in CNC turning of aluminium alloy using hybrid RSM cum TLBO approach

NASA Astrophysics Data System (ADS)

Rudrapati, R.; Sahoo, P.; Bandyopadhyay, A.

2016-09-01

The main aim of the present work is to analyse the significance of turning parameters on surface roughness in computer numerically controlled (CNC) turning operation while machining of aluminium alloy material. Spindle speed, feed rate and depth of cut have been considered as machining parameters. Experimental runs have been conducted as per Box-Behnken design method. After experimentation, surface roughness is measured by using stylus profile meter. Factor effects have been studied through analysis of variance. Mathematical modelling has been done by response surface methodology, to made relationships between the input parameters and output response. Finally, process optimization has been made by teaching learning based optimization (TLBO) algorithm. Predicted turning condition has been validated through confirmatory experiment.

Decoding the non-stationary neuron spike trains by dual Monte Carlo point process estimation in motor Brain Machine Interfaces.

PubMed

Liao, Yuxi; Li, Hongbao; Zhang, Qiaosheng; Fan, Gong; Wang, Yiwen; Zheng, Xiaoxiang

2014-01-01

Decoding algorithm in motor Brain Machine Interfaces translates the neural signals to movement parameters. They usually assume the connection between the neural firings and movements to be stationary, which is not true according to the recent studies that observe the time-varying neuron tuning property. This property results from the neural plasticity and motor learning etc., which leads to the degeneration of the decoding performance when the model is fixed. To track the non-stationary neuron tuning during decoding, we propose a dual model approach based on Monte Carlo point process filtering method that enables the estimation also on the dynamic tuning parameters. When applied on both simulated neural signal and in vivo BMI data, the proposed adaptive method performs better than the one with static tuning parameters, which raises a promising way to design a long-term-performing model for Brain Machine Interfaces decoder.

A low-cost machine vision system for the recognition and sorting of small parts

NASA Astrophysics Data System (ADS)

Barea, Gustavo; Surgenor, Brian W.; Chauhan, Vedang; Joshi, Keyur D.

2018-04-01

An automated machine vision-based system for the recognition and sorting of small parts was designed, assembled and tested. The system was developed to address a need to expose engineering students to the issues of machine vision and assembly automation technology, with readily available and relatively low-cost hardware and software. This paper outlines the design of the system and presents experimental performance results. Three different styles of plastic gears, together with three different styles of defective gears, were used to test the system. A pattern matching tool was used for part classification. Nine experiments were conducted to demonstrate the effects of changing various hardware and software parameters, including: conveyor speed, gear feed rate, classification, and identification score thresholds. It was found that the system could achieve a maximum system accuracy of 95% at a feed rate of 60 parts/min, for a given set of parameter settings. Future work will be looking at the effect of lighting.

Design, fabrication, and operation of a test rig for high-speed tapered-roller bearings

NASA Technical Reports Server (NTRS)

Signer, H. R.

1974-01-01

A tapered-roller bearing test machine was designed, fabricated and successfully operated at speeds to 20,000 rpm. Infinitely variable radial loads to 26,690 N (6,000 lbs.) and thrust loads to 53,380 N (12,000 lbs.) can be applied to test bearings. The machine instrumentation proved to have the accuracy and reliability required for parametric bearing performance testing and has the capability of monitoring all programmed test parameters at continuous operation during life testing. This system automatically shuts down a test if any important test parameter deviates from the programmed conditions, or if a bearing failure occurs. A lubrication system was developed as an integral part of the machine, capable of lubricating test bearings by external jets and by means of passages feeding through the spindle and bearing rings into the critical internal bearing surfaces. In addition, provisions were made for controlled oil cooling of inner and outer rings to effect the type of bearing thermal management that is required when testing at high speeds.

Application of Box-Behnken Design and Response Surface Methodology for Surface Roughness Prediction Model of CP-Ti Powder Metallurgy Components Through WEDM

NASA Astrophysics Data System (ADS)

Das, Arunangsu; Sarkar, Susenjit; Karanjai, Malobika; Sutradhar, Goutam

2018-04-01

The present work was undertaken to investigate and characterize the machining parameters (such as surface roughness, etc.) of uni-axially pressed commercially pure titanium sintered powder metallurgy components. Powder was uni-axially pressed at designated pressure of 840 MPa to form cylindrical samples and the green compacts were sintered at 0.001 mbar for about 4 h with sintering temperature varying from 1350 to 1450 °C. The influence of the sintering temperature, pulse-on and pulse-off time at wire-EDM on the surface roughness of the preforms has been investigated thoroughly. Experiments were conducted under different machining parameters in a CNC operated wire-cut EDM. The surface roughness of the machined surface was measured and critically analysed. The optimum surface roughness was achieved under the conditions of 6 μs pulse-on time, 9 μs pulse-off time and at sintering temperature of 1450 °C.

Optimal design of earth-moving machine elements with cusp catastrophe theory application

NASA Astrophysics Data System (ADS)

Pitukhin, A. V.; Skobtsov, I. G.

2017-10-01

This paper deals with the optimal design problem solution for the operator of an earth-moving machine with a roll-over protective structure (ROPS) in terms of the catastrophe theory. A brief description of the catastrophe theory is presented, the cusp catastrophe is considered, control parameters are viewed as Gaussian stochastic quantities in the first part of the paper. The statement of optimal design problem is given in the second part of the paper. It includes the choice of the objective function and independent design variables, establishment of system limits. The objective function is determined as mean total cost that includes initial cost and cost of failure according to the cusp catastrophe probability. Algorithm of random search method with an interval reduction subject to side and functional constraints is given in the last part of the paper. The way of optimal design problem solution can be applied to choose rational ROPS parameters, which will increase safety and reduce production and exploitation expenses.

Surface Roughness Optimization of Polyamide-6/Nanoclay Nanocomposites Using Artificial Neural Network: Genetic Algorithm Approach

PubMed Central

Moghri, Mehdi; Omidi, Mostafa; Farahnakian, Masoud

2014-01-01

During the past decade, polymer nanocomposites attracted considerable investment in research and development worldwide. One of the key factors that affect the quality of polymer nanocomposite products in machining is surface roughness. To obtain high quality products and reduce machining costs it is very important to determine the optimal machining conditions so as to achieve enhanced machining performance. The objective of this paper is to develop a predictive model using a combined design of experiments and artificial intelligence approach for optimization of surface roughness in milling of polyamide-6 (PA-6) nanocomposites. A surface roughness predictive model was developed in terms of milling parameters (spindle speed and feed rate) and nanoclay (NC) content using artificial neural network (ANN). As the present study deals with relatively small number of data obtained from full factorial design, application of genetic algorithm (GA) for ANN training is thought to be an appropriate approach for the purpose of developing accurate and robust ANN model. In the optimization phase, a GA is considered in conjunction with the explicit nonlinear function derived from the ANN to determine the optimal milling parameters for minimization of surface roughness for each PA-6 nanocomposite. PMID:24578636

Machinability of nickel based alloys using electrical discharge machining process

NASA Astrophysics Data System (ADS)

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.

Development of the FITS tools package for multiple software environments

NASA Technical Reports Server (NTRS)

Pence, W. D.; Blackburn, J. K.

1992-01-01

The HEASARC is developing a package of general purpose software for analyzing data files in FITS format. This paper describes the design philosophy which makes the software both machine-independent (it runs on VAXs, Suns, and DEC-stations) and software environment-independent. Currently the software can be compiled and linked to produce IRAF tasks, or alternatively, the same source code can be used to generate stand-alone tasks using one of two implementations of a user-parameter interface library. The machine independence of the software is achieved by writing the source code in ANSI standard Fortran or C, using the machine-independent FITSIO subroutine interface for all data file I/O, and using a standard user-parameter subroutine interface for all user I/O. The latter interface is based on the Fortran IRAF Parameter File interface developed at STScI. The IRAF tasks are built by linking to the IRAF implementation of this parameter interface library. Two other implementations of this parameter interface library, which have no IRAF dependencies, are now available which can be used to generate stand-alone executable tasks. These stand-alone tasks can simply be executed from the machine operating system prompt either by supplying all the task parameters on the command line or by entering the task name after which the user will be prompted for any required parameters. A first release of this FTOOLS package is now publicly available. The currently available tasks are described, along with instructions on how to obtain a copy of the software.

Ball-and-Socket-Bearing Wear Test

NASA Technical Reports Server (NTRS)

Graham, W. G.

1984-01-01

Series of experiments to measure wear life of spherical bearing summarized. Report designed to establish clearance, contour, finish, and lubricant parameters for highly-loaded, compact plain spherical bearing. Information useful in design of bearings for helicopter control linkages, business machines, nuclear reactor, and rotor bearings.

Mathematical model of an air-filled alpha stirling refrigerator

NASA Astrophysics Data System (ADS)

McFarlane, Patrick; Semperlotti, Fabio; Sen, Mihir

2013-10-01

This work develops a mathematical model for an alpha Stirling refrigerator with air as the working fluid and will be useful in optimizing the mechanical design of these machines. Two pistons cyclically compress and expand air while moving sinusoidally in separate chambers connected by a regenerator, thus creating a temperature difference across the system. A complete non-linear mathematical model of the machine, including air thermodynamics, and heat transfer from the walls, as well as heat transfer and fluid resistance in the regenerator, is developed. Non-dimensional groups are derived, and the mathematical model is numerically solved. The heat transfer and work are found for both chambers, and the coefficient of performance of each chamber is calculated. Important design parameters are varied and their effect on refrigerator performance determined. This sensitivity analysis, which shows what the significant parameters are, is a useful tool for the design of practical Stirling refrigeration systems.

Lunar Regolith Bagging System

NASA Technical Reports Server (NTRS)

Brown, Sebrina; Lundberg, Kimberly; Mcgarity, Ginger; Silverman, Philip

1990-01-01

A regolith container to be used as a fundamental building block in radiation protection of a habitable lunar base was designed. Parameters for the container are its: size, shape, material, and structural design. Also, a machine was designed to fill the regolith container which is capable of grasping and opening an empty container, filling it, closing it when full, and depositing it on the surface of the Moon. The simple design will bag lunar soil in a relatively short amount of time, with a low equipment weight, and with moving parts distanced from the dirt. The bags are made out of Kevlar 149 with a fabric weight of 6 oz. per square yard. All machine parts are composed of aluminum 6061-T6. Assuming that the vehicle runs at 7 km/hr for 8 hours a day, the machine will bag the necessary 450 cu m of soil in about 12 days. The total mass of the bags and the machine to be shipped to the Moon will be 687 kg. The cost of shipping this weight will be $6.23 million.

Results of Investigative Tests of Gas Turbine Engine Compressor Blades Obtained by Electrochemical Machining

NASA Astrophysics Data System (ADS)

Kozhina, T. D.; Kurochkin, A. V.

2016-04-01

The paper highlights results of the investigative tests of GTE compressor Ti-alloy blades obtained by the method of electrochemical machining with oscillating tool-electrodes, carried out in order to define the optimal parameters of the ECM process providing attainment of specified blade quality parameters given in the design documentation, while providing maximal performance. The new technological methods suggested based on the results of the tests; in particular application of vibrating tool-electrodes and employment of locating elements made of high-strength materials, significantly extend the capabilities of this method.

A strategy for quantum algorithm design assisted by machine learning

NASA Astrophysics Data System (ADS)

Bang, Jeongho; Ryu, Junghee; Yoo, Seokwon; Pawłowski, Marcin; Lee, Jinhyoung

2014-07-01

We propose a method for quantum algorithm design assisted by machine learning. The method uses a quantum-classical hybrid simulator, where a ‘quantum student’ is being taught by a ‘classical teacher’. In other words, in our method, the learning system is supposed to evolve into a quantum algorithm for a given problem, assisted by a classical main-feedback system. Our method is applicable for designing quantum oracle-based algorithms. We chose, as a case study, an oracle decision problem, called a Deutsch-Jozsa problem. We showed by using Monte Carlo simulations that our simulator can faithfully learn a quantum algorithm for solving the problem for a given oracle. Remarkably, the learning time is proportional to the square root of the total number of parameters, rather than showing the exponential dependence found in the classical machine learning-based method.

The design and development of transonic multistage compressors

NASA Technical Reports Server (NTRS)

Ball, C. L.; Steinke, R. J.; Newman, F. A.

1988-01-01

The development of the transonic multistage compressor is reviewed. Changing trends in design and performance parameters are noted. These changes are related to advances in compressor aerodynamics, computational fluid mechanics and other enabling technologies. The parameters normally given to the designer and those that need to be established during the design process are identified. Criteria and procedures used in the selection of these parameters are presented. The selection of tip speed, aerodynamic loading, flowpath geometry, incidence and deviation angles, blade/vane geometry, blade/vane solidity, stage reaction, aerodynamic blockage, inlet flow per unit annulus area, stage/overall velocity ratio, and aerodynamic losses are considered. Trends in these parameters both spanwise and axially through the machine are highlighted. The effects of flow mixing and methods for accounting for the mixing in the design process are discussed.

[Design of Complex Cavity Structure in Air Route System of Automated Peritoneal Dialysis Machine].

PubMed

Quan, Xiaoliang

2017-07-30

This paper introduced problems about Automated Peritoneal Dialysis machine(APD) that the lack of technical issues such as the structural design of the complex cavities. To study the flow characteristics of this special structure, the application of ANSYS CFX software is used with k-ε turbulence model as the theoretical basis of fluid mechanics. The numerical simulation of flow field simulation result in the internal model can be gotten after the complex structure model is imported into ANSYS CFX module. Then, it will present the distribution of complex cavities inside the flow field and the flow characteristics parameter, which will provide an important reference design for APD design.

Chip morphology as a performance predictor during high speed end milling of soda lime glass

NASA Astrophysics Data System (ADS)

Bagum, M. N.; Konneh, M.; Abdullah, K. A.; Ali, M. Y.

2018-01-01

Soda lime glass has application in DNA arrays and lab on chip manufacturing. Although investigation revealed that machining of such brittle material is possible using ductile mode under controlled cutting parameters and tool geometry, it remains a challenging task. Furthermore, ability of ductile machining is usually assed through machined surface texture examination. Soda lime glass is a strain rate and temperature sensitive material. Hence, influence on attainment of ductile surface due to adiabatic heat generated during high speed end milling using uncoated tungsten carbide tool is investigated in this research. Experimental runs were designed using central composite design (CCD), taking spindle speed, feed rate and depth of cut as input variable and tool-chip contact point temperature (Ttc) and the surface roughness (Rt) as responses. Along with machined surface texture, Rt and chip morphology was examined to assess machinability of soda lime glass. The relation between Ttc and chip morphology was examined. Investigation showed that around glass transition temperature (Tg) ductile chip produced and subsequently clean and ductile final machined surface produced.

Drilling High Precision Holes in Ti6Al4V Using Rotary Ultrasonic Machining and Uncertainties Underlying Cutting Force, Tool Wear, and Production Inaccuracies.

PubMed

Chowdhury, M A K; Sharif Ullah, A M M; Anwar, Saqib

2017-09-12

Ti6Al4V alloys are difficult-to-cut materials that have extensive applications in the automotive and aerospace industry. A great deal of effort has been made to develop and improve the machining operations of Ti6Al4V alloys. This paper presents an experimental study that systematically analyzes the effects of the machining conditions (ultrasonic power, feed rate, spindle speed, and tool diameter) on the performance parameters (cutting force, tool wear, overcut error, and cylindricity error), while drilling high precision holes on the workpiece made of Ti6Al4V alloys using rotary ultrasonic machining (RUM). Numerical results were obtained by conducting experiments following the design of an experiment procedure. The effects of the machining conditions on each performance parameter have been determined by constructing a set of possibility distributions (i.e., trapezoidal fuzzy numbers) from the experimental data. A possibility distribution is a probability-distribution-neural representation of uncertainty, and is effective in quantifying the uncertainty underlying physical quantities when there is a limited number of data points which is the case here. Lastly, the optimal machining conditions have been identified using these possibility distributions.

Experimental Research and Mathematical Modeling of Parameters Effecting on Cutting Force and SurfaceRoughness in CNC Turning Process

NASA Astrophysics Data System (ADS)

Zeqiri, F.; Alkan, M.; Kaya, B.; Toros, S.

2018-01-01

In this paper, the effects of cutting parameters on cutting forces and surface roughness based on Taguchi experimental design method are determined. Taguchi L9 orthogonal array is used to investigate the effects of machining parameters. Optimal cutting conditions are determined using the signal/noise (S/N) ratio which is calculated by average surface roughness and cutting force. Using results of analysis, effects of parameters on both average surface roughness and cutting forces are calculated on Minitab 17 using ANOVA method. The material that was investigated is Inconel 625 steel for two cases with heat treatment and without heat treatment. The predicted and calculated values with measurement are very close to each other. Confirmation test of results showed that the Taguchi method was very successful in the optimization of machining parameters for maximum surface roughness and cutting forces in the CNC turning process.

Automated Design of Complex Dynamic Systems

PubMed Central

Hermans, Michiel; Schrauwen, Benjamin; Bienstman, Peter; Dambre, Joni

2014-01-01

Several fields of study are concerned with uniting the concept of computation with that of the design of physical systems. For example, a recent trend in robotics is to design robots in such a way that they require a minimal control effort. Another example is found in the domain of photonics, where recent efforts try to benefit directly from the complex nonlinear dynamics to achieve more efficient signal processing. The underlying goal of these and similar research efforts is to internalize a large part of the necessary computations within the physical system itself by exploiting its inherent non-linear dynamics. This, however, often requires the optimization of large numbers of system parameters, related to both the system's structure as well as its material properties. In addition, many of these parameters are subject to fabrication variability or to variations through time. In this paper we apply a machine learning algorithm to optimize physical dynamic systems. We show that such algorithms, which are normally applied on abstract computational entities, can be extended to the field of differential equations and used to optimize an associated set of parameters which determine their behavior. We show that machine learning training methodologies are highly useful in designing robust systems, and we provide a set of both simple and complex examples using models of physical dynamical systems. Interestingly, the derived optimization method is intimately related to direct collocation a method known in the field of optimal control. Our work suggests that the application domains of both machine learning and optimal control have a largely unexplored overlapping area which envelopes a novel design methodology of smart and highly complex physical systems. PMID:24497969

Precision Parameter Estimation and Machine Learning

NASA Astrophysics Data System (ADS)

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.

Tool geometry and damage mechanisms influencing CNC turning efficiency of Ti6Al4V

NASA Astrophysics Data System (ADS)

Suresh, Sangeeth; Hamid, Darulihsan Abdul; Yazid, M. Z. A.; Nasuha, Nurdiyanah; Ain, Siti Nurul

2017-12-01

Ti6Al4V or Grade 5 titanium alloy is widely used in the aerospace, medical, automotive and fabrication industries, due to its distinctive combination of mechanical and physical properties. Ti6Al4V has always been perverse during its machining, strangely due to the same mix of properties mentioned earlier. Ti6Al4V machining has resulted in shorter cutting tool life which has led to objectionable surface integrity and rapid failure of the parts machined. However, the proven functional relevance of this material has prompted extensive research in the optimization of machine parameters and cutting tool characteristics. Cutting tool geometry plays a vital role in ensuring dimensional and geometric accuracy in machined parts. In this study, an experimental investigation is actualized to optimize the nose radius and relief angles of the cutting tools and their interaction to different levels of machining parameters. Low elastic modulus and thermal conductivity of Ti6Al4V contribute to the rapid tool damage. The impact of these properties over the tool tips damage is studied. An experimental design approach is utilized in the CNC turning process of Ti6Al4V to statistically analyze and propose optimum levels of input parameters to lengthen the tool life and enhance surface characteristics of the machined parts. A greater tool nose radius with a straight flank, combined with low feed rates have resulted in a desirable surface integrity. The presence of relief angle has proven to aggravate tool damage and also dimensional instability in the CNC turning of Ti6Al4V.

A single-phase axially-magnetized permanent-magnet oscillating machine for miniature aerospace power sources

NASA Astrophysics Data System (ADS)

Sui, Yi; Zheng, Ping; Cheng, Luming; Wang, Weinan; Liu, Jiaqi

2017-05-01

A single-phase axially-magnetized permanent-magnet (PM) oscillating machine which can be integrated with a free-piston Stirling engine to generate electric power, is investigated for miniature aerospace power sources. Machine structure, operating principle and detent force characteristic are elaborately studied. With the sinusoidal speed characteristic of the mover considered, the proposed machine is designed by 2D finite-element analysis (FEA), and some main structural parameters such as air gap diameter, dimensions of PMs, pole pitches of both stator and mover, and the pole-pitch combinations, etc., are optimized to improve both the power density and force capability. Compared with the three-phase PM linear machines, the proposed single-phase machine features less PM use, simple control and low controller cost. The power density of the proposed machine is higher than that of the three-phase radially-magnetized PM linear machine, but lower than the three-phase axially-magnetized PM linear machine.

The design and test of collecting device and film purge device joint work of residual film recovery machine based on Solidworks & Adams

NASA Astrophysics Data System (ADS)

Zhai, Haozhou; Jian, Jianming; Hou, Shulin; San, Yunlong; Guo, Wensong; Sun, Yue; Gao, Mingqing

2018-03-01

The twine of residual film is an essential issue in the process of remnant residue recovery of the residual film recovery machine. It is difficult to clean up the residual film in the residual film recovery operation and to influence the subsequent film efficiency. Therefore, in response to this problem a composite tooth pocket residual film recovery device was designed. In this paper, the structure of the film recovery device design, theoretical analysis, simulation experiments, get the most appropriate film recovery device parameters. In addition, the residual film rate of the membrane is dramatically low, reaching about 1.3% only, and the operation of the whole machine is smoother, and the stability of the work is promoted. The operation of the film recovery device is very obvious. Lifting, in addition to the film rate has also been significantly improved to 93.88%

Design and Implementation of a Hypothermic Machine Perfusion Device for Clinical Preservation of Isolated Organs

PubMed Central

Shen, Fei; Yan, Ruqiang

2017-01-01

The imbalance between limited organ supply and huge potential need has hindered the development of organ-graft techniques. In this paper a low-cost hypothermic machine perfusion (HMP) device is designed and implemented to maintain suitable preservation surroundings and extend the survival life of isolated organs. Four necessary elements (the machine perfusion, the physiological parameter monitoring, the thermostatic control and the oxygenation apparatus) involved in this HMP device are introduced. Especially during the thermostatic control process, a modified Bayes estimation, which introduces the concept of improvement factor, is realized to recognize and reduce the possible measurement errors resulting from sensor faults and noise interference. Also, a fuzzy-PID controller contributes to improve the accuracy and reduces the computational load using the DSP. Our experiments indicate that the reliability of the instrument meets the design requirements, thus being appealing for potential clinical preservation applications. PMID:28587173

A tubular hybrid Halbach/axially-magnetized permanent-magnet linear machine

NASA Astrophysics Data System (ADS)

Sui, Yi; Liu, Yong; Cheng, Luming; Liu, Jiaqi; Zheng, Ping

2017-05-01

A single-phase tubular permanent-magnet linear machine (PMLM) with hybrid Halbach/axially-magnetized PM arrays is proposed for free-piston Stirling power generation system. Machine topology and operating principle are elaborately illustrated. With the sinusoidal speed characteristic of the free-piston Stirling engine considered, the proposed machine is designed and calculated by finite-element analysis (FEA). The main structural parameters, such as outer radius of the mover, radial length of both the axially-magnetized PMs and ferromagnetic poles, axial length of both the middle and end radially-magnetized PMs, etc., are optimized to improve both the force capability and power density. Compared with the conventional PMLMs, the proposed machine features high mass and volume power density, and has the advantages of simple control and low converter cost. The proposed machine topology is applicable to tubular PMLMs with any phases.

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

PubMed

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 (P<0.05) in all the studied variables. Milk emission flow variables were similar to those recommended in scientific studies. Milking parameters were adequate in most of the farms, 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 milking machine characteristics were scarce.

Design and Analysis of a Sensor System for Cutting Force Measurement in Machining Processes

PubMed Central

Liang, Qiaokang; Zhang, Dan; Coppola, Gianmarc; Mao, Jianxu; Sun, Wei; Wang, Yaonan; Ge, Yunjian

2016-01-01

Multi-component force sensors have infiltrated a wide variety of automation products since the 1970s. However, one seldom finds full-component sensor systems available in the market for cutting force measurement in machine processes. In this paper, a new six-component sensor system with a compact monolithic elastic element (EE) is designed and developed to detect the tangential cutting forces Fx, Fy and Fz (i.e., forces along x-, y-, and z-axis) as well as the cutting moments Mx, My and Mz (i.e., moments about x-, y-, and z-axis) simultaneously. Optimal structural parameters of the EE are carefully designed via simulation-driven optimization. Moreover, a prototype sensor system is fabricated, which is applied to a 5-axis parallel kinematic machining center. Calibration experimental results demonstrate that the system is capable of measuring cutting forces and moments with good linearity while minimizing coupling error. Both the Finite Element Analysis (FEA) and calibration experimental studies validate the high performance of the proposed sensor system that is expected to be adopted into machining processes. PMID:26751451

Design and Analysis of a Sensor System for Cutting Force Measurement in Machining Processes.

PubMed

Liang, Qiaokang; Zhang, Dan; Coppola, Gianmarc; Mao, Jianxu; Sun, Wei; Wang, Yaonan; Ge, Yunjian

2016-01-07

Multi-component force sensors have infiltrated a wide variety of automation products since the 1970s. However, one seldom finds full-component sensor systems available in the market for cutting force measurement in machine processes. In this paper, a new six-component sensor system with a compact monolithic elastic element (EE) is designed and developed to detect the tangential cutting forces Fx, Fy and Fz (i.e., forces along x-, y-, and z-axis) as well as the cutting moments Mx, My and Mz (i.e., moments about x-, y-, and z-axis) simultaneously. Optimal structural parameters of the EE are carefully designed via simulation-driven optimization. Moreover, a prototype sensor system is fabricated, which is applied to a 5-axis parallel kinematic machining center. Calibration experimental results demonstrate that the system is capable of measuring cutting forces and moments with good linearity while minimizing coupling error. Both the Finite Element Analysis (FEA) and calibration experimental studies validate the high performance of the proposed sensor system that is expected to be adopted into machining processes.

Fundamentals of Digital Engineering: Designing for Reliability

NASA Technical Reports Server (NTRS)

Katz, R.; Day, John H. (Technical Monitor)

2001-01-01

The concept of designing for reliability will be introduced along with a brief overview of reliability, redundancy and traditional methods of fault tolerance is presented, as applied to current logic devices. The fundamentals of advanced circuit design and analysis techniques will be the primary focus. The introduction will cover the definitions of key device parameters and how analysis is used to prove circuit correctness. Basic design techniques such as synchronous vs asynchronous design, metastable state resolution time/arbiter design, and finite state machine structure/implementation will be reviewed. Advanced topics will be explored such as skew-tolerant circuit design, the use of triple-modular redundancy and circuit hazards, device transients and preventative circuit design, lock-up states in finite state machines generated by logic synthesizers, device transient characteristics, radiation mitigation techniques. worst-case analysis, the use of timing analyzer and simulators, and others. Case studies and lessons learned from spaceflight designs will be given as examples

Intelligent printing system with AMPAC: boot program for printing machine with AMPAC

NASA Astrophysics Data System (ADS)

Yuasa, Tomonori; Mishina, Hiromichi

2000-12-01

The database AMPAC proposes the simple and unified format to describe single parameter of whole field of design, production and management. The database described by the format can be used commonly in any field connected by the network production system, since the description accepts any parameter in any fields and is field independent definition.

Application of Taguchi-grey method to optimize drilling of EMS 45 steel using minimum quantity lubrication (MQL) with multiple performance characteristics

NASA Astrophysics Data System (ADS)

Soepangkat, Bobby O. P.; Suhardjono, Pramujati, Bambang

2017-06-01

Machining under minimum quantity lubrication (MQL) has drawn the attention of researchers as an alternative to the traditionally used wet and dry machining conditions with the purpose to minimize the cooling and lubricating cost, as well as to reduce cutting zone temperature, tool wear, and hole surface roughness. Drilling is one of the important operations to assemble machine components. The objective of this study was to optimize drilling parameters such as cutting feed and cutting speed, drill type and drill point angle on the thrust force, torque, hole surface roughness and tool flank wear in drilling EMS 45 tool steel using MQL. In this study, experiments were carried out as per Taguchi design of experiments while an L18 orthogonal array was used to study the influence of various combinations of drilling parameters and tool geometries on the thrust force, torque, hole surface roughness and tool flank wear. The optimum drilling parameters was determined by using grey relational grade obtained from grey relational analysis for multiple-performance characteristics. The drilling experiments were carried out by using twist drill and CNC machining center. This work is useful for optimum values selection of various drilling parameters and tool geometries that would not only minimize the thrust force and torque, but also reduce hole surface roughness and tool flank wear.

Optimization of Maghemite (γ-Fe2O3) Nano-Powder Mixed micro-EDM of CoCrMo with Multiple Responses Using Gray Relational Analysis (GRA)

NASA Astrophysics Data System (ADS)

Mejid Elsiti, Nagwa; Noordin, M. Y.; Idris, Ani; Saed Majeed, Faraj

2017-10-01

This paper presents an optimization of process parameters of Micro-Electrical Discharge Machining (EDM) process with (γ-Fe2O3) nano-powder mixed dielectric using multi-response optimization Grey Relational Analysis (GRA) method instead of single response optimization. These parameters were optimized based on 2-Level factorial design combined with Grey Relational Analysis. The machining parameters such as peak current, gap voltage, and pulse on time were chosen for experimentation. The performance characteristics chosen for this study are material removal rate (MRR), tool wear rate (TWR), Taper and Overcut. Experiments were conducted using electrolyte copper as the tool and CoCrMo as the workpiece. Experimental results have been improved through this approach.

Temperature Measurement and Numerical Prediction in Machining Inconel 718.

PubMed

Díaz-Álvarez, José; Tapetado, Alberto; Vázquez, Carmen; Miguélez, Henar

2017-06-30

Thermal issues are critical when machining Ni-based superalloy components designed for high temperature applications. The low thermal conductivity and extreme strain hardening of this family of materials results in elevated temperatures around the cutting area. This elevated temperature could lead to machining-induced damage such as phase changes and residual stresses, resulting in reduced service life of the component. Measurement of temperature during machining is crucial in order to control the cutting process, avoiding workpiece damage. On the other hand, the development of predictive tools based on numerical models helps in the definition of machining processes and the obtainment of difficult to measure parameters such as the penetration of the heated layer. However, the validation of numerical models strongly depends on the accurate measurement of physical parameters such as temperature, ensuring the calibration of the model. This paper focuses on the measurement and prediction of temperature during the machining of Ni-based superalloys. The temperature sensor was based on a fiber-optic two-color pyrometer developed for localized temperature measurements in turning of Inconel 718. The sensor is capable of measuring temperature in the range of 250 to 1200 °C. Temperature evolution is recorded in a lathe at different feed rates and cutting speeds. Measurements were used to calibrate a simplified numerical model for prediction of temperature fields during turning.

Material Choice for spindle of machine tools

NASA Astrophysics Data System (ADS)

Gouasmi, S.; Merzoug, B.; Abba, G.; Kherredine, L.

2012-02-01

The requirements of contemporary industry and the flashing development of modern sciences impose restrictions on the majority of the elements of machines; the resulting financial constraints can be satisfied by a better output of the production equipment. As for those concerning the design, the resistance and the correct operation of the product, these require the development of increasingly precise parts, therefore the use of increasingly powerful tools [5]. The precision of machining and the output of the machine tools are generally determined by the precision of rotation of the spindle, indeed, more this one is large more the dimensions to obtain are in the zone of tolerance and the defects of shape are minimized. During the development of the machine tool, the spindle which by definition is a rotating shaft receiving and transmitting to the work piece or the cutting tool the rotational movement, must be designed according to certain optimal parameters to be able to ensure the precision required. This study will be devoted to the choice of the material of the spindle fulfilling the imposed requirements of precision.

Shielded cables with optimal braided shields

NASA Astrophysics Data System (ADS)

Homann, E.

1991-01-01

Extensive tests were done in order to determine what factors govern the design of braids with good shielding effectiveness. The results are purely empirical and relate to the geometrical relationships between the braid parameters. The influence of various parameters on the shape of the transfer impedance versus frequency curve were investigated step by step. It was found that the optical coverage had been overestimated in the past. Good shielding effectiveness results not from high optical coverage as such, but from the proper type of coverage, which is a function of the braid angle and the element width. These dependences were measured for the ordinary range of braid angles (20 to 40 degrees). They apply to all plaiting machines and all gages of braid wire. The design rules are largely the same for bright, tinned, silver-plated and even lacquered copper wires. A new type of braid, which has marked advantages over the conventional design, was proposed. With the 'mixed-element' technique, an optimal braid design can be specified on any plaiting machine, for any possible cable diameter, and for any desired angle. This is not possible for the conventional type of braid.

Energy landscapes for a machine-learning prediction of patient discharge

NASA Astrophysics Data System (ADS)

Das, Ritankar; Wales, David J.

2016-06-01

The energy landscapes framework is applied to a configuration space generated by training the parameters of a neural network. In this study the input data consists of time series for a collection of vital signs monitored for hospital patients, and the outcomes are patient discharge or continued hospitalisation. Using machine learning as a predictive diagnostic tool to identify patterns in large quantities of electronic health record data in real time is a very attractive approach for supporting clinical decisions, which have the potential to improve patient outcomes and reduce waiting times for discharge. Here we report some preliminary analysis to show how machine learning might be applied. In particular, we visualize the fitting landscape in terms of locally optimal neural networks and the connections between them in parameter space. We anticipate that these results, and analogues of thermodynamic properties for molecular systems, may help in the future design of improved predictive tools.

Prediction of multi performance characteristics of wire EDM process using grey ANFIS

NASA Astrophysics Data System (ADS)

Kumanan, Somasundaram; Nair, Anish

2017-09-01

Super alloys are used to fabricate components in ultra-supercritical power plants. These hard to machine materials are processed using non-traditional machining methods like Wire cut electrical discharge machining and needs attention. This paper details about multi performance optimization of wire EDM process using Grey ANFIS. Experiments are designed to establish the performance characteristics of wire EDM such as surface roughness, material removal rate, wire wear rate and geometric tolerances. The control parameters are pulse on time, pulse off time, current, voltage, flushing pressure, wire tension, table feed and wire speed. Grey relational analysis is employed to optimise the multi objectives. Analysis of variance of the grey grades is used to identify the critical parameters. A regression model is developed and used to generate datasets for the training of proposed adaptive neuro fuzzy inference system. The developed prediction model is tested for its prediction ability.

Engineering specification and system design for CAD/CAM of custom shoes. Phase 5: UMC involvement (January 1, 1989 - June 30, 1989)

NASA Technical Reports Server (NTRS)

Bao, Han P.

1989-01-01

The CAD/CAM of custom shoes is discussed. The solid object for machining is represented by a wireframe model with its nodes or vertices specified systematically in a grid pattern covering its entire length (point-to-point configuration). Two sets of data from CENCIT and CYBERWARE were used for machining purposes. It was found that the indexing technique (turning the stock by a small angle then moving the tool on a longitudinal path along the foot) yields the best result in terms of ease of programming, savings in wear and tear of the machine and cutting tools, and resolution of fine surface details. The work done using the LASTMOD last design system results in a shoe last specified by a number of congruent surface patches of different sizes. This data format was converted into a form amenable to the machine tool. It involves a series of sorting algorithms and interpolation algorithms to provide the grid pattern that the machine tool needs as was the case in the point to point configuration discussed above. This report also contains an in-depth treatment of the design and production technique of an integrated sole to complement the task of design and manufacture of the shoe last. Clinical data and essential production parameters are discussed. Examples of soles made through this process are given.

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

NASA Astrophysics Data System (ADS)

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.

Parameter optimization of electrochemical machining process using black hole algorithm

NASA Astrophysics Data System (ADS)

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.

Experimental investigation on hard turning of AISI 4340 steel using cemented coated carbide insert

NASA Astrophysics Data System (ADS)

Pradeep Kumar, J.; Kishore, K. P.; Ranjith Kumar, M.; Saran Karthick, K. R.; Vishnu Gowtham, S.

2018-02-01

Hard turning is a developing technology that offers many potential advantages compared to grinding, which remains the standard finishing process for critical hardened surfaces. In this work, an attempt has been made to experimentally investigate hard turning of AISI 4340 steel under wet and dry condition using cemented coated carbide insert. Hardness of the workpiece material is tested using Brinell and Rockwell hardness testers. CNC LATHE and cemented coated carbide inserts of designation CNMG 120408 are used for conducting experimental trials. Significant cutting parameters like cutting speed, feed rate and depth of cut are considered as controllable input parameters and surface roughness (Ra), tool wear are considered as output response parameters. Design of experiments is carried out with the help of Taguchi’s L9 orthogonal array. Results of response parameters like surface roughness and tool wear under wet and dry condition are analysed. It is found that surface roughness and tool wear are higher under dry machining condition when compared to wet machining condition. Feed rate significantly influences the surface roughness followed by cutting speed. Depth of cut significantly influences the tool wear followed by cutting speed.

A Modelling Method of Bolt Joints Based on Basic Characteristic Parameters of Joint Surfaces

NASA Astrophysics Data System (ADS)

Yuansheng, Li; Guangpeng, Zhang; Zhen, Zhang; Ping, Wang

2018-02-01

Bolt joints are common in machine tools and have a direct impact on the overall performance of the tools. Therefore, the understanding of bolt joint characteristics is essential for improving machine design and assembly. Firstly, According to the experimental data obtained from the experiment, the stiffness curve formula was fitted. Secondly, a finite element model of unit bolt joints such as bolt flange joints, bolt head joints, and thread joints was constructed, and lastly the stiffness parameters of joint surfaces were implemented in the model by the secondary development of ABAQUS. The finite element model of the bolt joint established by this method can simulate the contact state very well.

Fuzzy logic controller optimization

DOEpatents

Sepe, Jr., Raymond B; Miller, John Michael

2004-03-23

A method is provided for optimizing a rotating induction machine system fuzzy logic controller. The fuzzy logic controller has at least one input and at least one output. Each input accepts a machine system operating parameter. Each output produces at least one machine system control parameter. The fuzzy logic controller generates each output based on at least one input and on fuzzy logic decision parameters. Optimization begins by obtaining a set of data relating each control parameter to at least one operating parameter for each machine operating region. A model is constructed for each machine operating region based on the machine operating region data obtained. The fuzzy logic controller is simulated with at least one created model in a feedback loop from a fuzzy logic output to a fuzzy logic input. Fuzzy logic decision parameters are optimized based on the simulation.

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

NASA Astrophysics Data System (ADS)

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.

Design and milling manufacture of polyurethane custom contoured cushions for wheelchair users.

PubMed

da Silva, Fabio Pinto; Beretta, Elisa Marangon; Prestes, Rafael Cavalli; Kindlein Junior, Wilson

2011-01-01

The design of custom contoured cushions manufactured in flexible polyurethane foams is an option to improve positioning and comfort for people with disabilities that spend most of the day seated in the same position. These surfaces increase the contact area between the seat and the user. This fact contributes to minimise the local pressures that can generate problems like decubitus ulcers. The present research aims at establishing development routes for custom cushion production to wheelchair users. This study also contributes to the investigation of Computer Numerical Control (CNC) machining of flexible polyurethane foams. The proposed route to obtain the customised seat began with acquiring the user's contour in adequate posture through plaster cast. To collect the surface geometry, the cast was three-dimensionally scanned and manipulated in CAD/CAM software. CNC milling parameters such as tools, spindle speeds and feed rates to machine flexible polyurethane foams were tested. These parameters were analysed regarding the surface quality. The best parameters were then tested in a customised seat. The possible dimensional changes generated during foam cutting were analysed through 3D scanning. Also, the customised seat pressure and temperature distribution was tested. The best parameters found for foams with a density of 50kg/cm(3) were high spindle speeds (24000 rpm) and feed rates between 2400-4000mm/min. Those parameters did not generate significant deformities in the machined cushions. The custom contoured cushion satisfactorily increased the contact area between wheelchair and user, as it distributed pressure and heat evenly. Through this study it was possible to define routes for the development and manufacturing of customised seats using direct CNC milling in flexible polyurethane foams. It also showed that custom contoured cushions efficiently distribute pressure and temperature, which is believed to minimise tissue lesions such as pressure ulcers.

Three-dimensionally printed biological machines powered by skeletal muscle.

PubMed

Cvetkovic, Caroline; Raman, Ritu; Chan, Vincent; Williams, Brian J; Tolish, Madeline; Bajaj, Piyush; Sakar, Mahmut Selman; Asada, H Harry; Saif, M Taher A; Bashir, Rashid

2014-07-15

Combining biological components, such as cells and tissues, with soft robotics can enable the fabrication of biological machines with the ability to sense, process signals, and produce force. An intuitive demonstration of a biological machine is one that can produce motion in response to controllable external signaling. Whereas cardiac cell-driven biological actuators have been demonstrated, the requirements of these machines to respond to stimuli and exhibit controlled movement merit the use of skeletal muscle, the primary generator of actuation in animals, as a contractile power source. Here, we report the development of 3D printed hydrogel "bio-bots" with an asymmetric physical design and powered by the actuation of an engineered mammalian skeletal muscle strip to result in net locomotion of the bio-bot. Geometric design and material properties of the hydrogel bio-bots were optimized using stereolithographic 3D printing, and the effect of collagen I and fibrin extracellular matrix proteins and insulin-like growth factor 1 on the force production of engineered skeletal muscle was characterized. Electrical stimulation triggered contraction of cells in the muscle strip and net locomotion of the bio-bot with a maximum velocity of ∼ 156 μm s(-1), which is over 1.5 body lengths per min. Modeling and simulation were used to understand both the effect of different design parameters on the bio-bot and the mechanism of motion. This demonstration advances the goal of realizing forward-engineered integrated cellular machines and systems, which can have a myriad array of applications in drug screening, programmable tissue engineering, drug delivery, and biomimetic machine design.

Gas flow parameters in laser cutting of wood- nozzle design

Treesearch

Kali Mukherjee; Tom Grendzwell; Parwaiz A.A. Khan; Charles McMillin

1990-01-01

The Automated Lumber Processing System (ALPS) is an ongoing team research effort to optimize the yield of parts in a furniture rough mill. The process is designed to couple aspects of computer vision, computer optimization of yield, and laser cutting. This research is focused on optimizing laser wood cutting. Laser machining of lumber has the advantage over...

A Comprehensive Understanding of Machine and Material Behaviors During Inertia Friction Welding

NASA Astrophysics Data System (ADS)

Tung, Daniel J.

Inertia Friction Welding (IFW), a critical process to many industries, currently relies on trial-and-error experimentation to optimize process parameters. Although this Edisonian approach is very effective, the high time and dollar costs incurred during process development are the driving force for better design approaches. Thermal-stress finite element modeling has been increasingly used to aid in process development in the literature; however, several fundamental questions on machine and material behaviors remain unanswered. The work presented here aims produce an analytical foundation to significantly reduce the costly physical experimentation currently required to design the inertia welding of production parts. Particularly, the work is centered around the following two major areas. First, machine behavior during IFW, which critically determines deformation and heating, had not been well understood to date. In order to properly characterize the IFW machine behavior, a novel method based on torque measurements was invented to measure machine efficiency, i.e. the ratio of the initial kinetic energy of the flywheel to that contributing to workpiece heating and deformation. The measured efficiency was validated by both simple energy balance calculations and more sophisticated finite element modeling. For the first time, the efficiency dependence on both process parameters (flywheel size, initial rotational velocity, axial load, and surface roughness) and materials (1018 steel, Low Solvus High Refractory LSHR and Waspaloy) was quantified using the torque based measurement method. The effect of process parameters on machine efficiency was analyzed to establish simple-to-use yet powerful equations for selection and optimization of IFW process parameters for making welds; however, design criteria such as geometry and material optimization were not addressed. Second, there had been a lack of understanding of the bond formation during IFW. In the present research, an interrupted welding study was developed utilizing purposefully-designed dissimilar metal couples to investigate bond formation for this specific material combination. The inertia welding process was interrupted at various times as the flywheel velocity decreased. The fraction of areas with intermixed metals was quantified to reveal the bond formation during IFW. The results revealed a relationship between the upset and the fraction of bonded material, which, interestingly, was found to be consistent to that established for roll bonding literature. The relationship is critical to studying the bonding mechanism and surface interactions during IFW. Moreover, it is essential to accurately interpret the modeling results to determine the extent of bonding using the computed strains near the workpiece interface. With this method developed, similar data can now be collected for additional similar and dissimilar material combinations. In summary, in the quest to develop, validate, and execute a modeling framework to study the inertia friction weldability of different alloy systems, particularly Fe- and Ni-base alloys, many new discoveries have been made to enhance the body of knowledge surrounding IFW. The data and trends discussed in this dissertation constitute a physics-based framework to understand the machine and material behaviors during IFW. Such a physics-based framework is essential to significantly reduce the costly trial-and-error experimentation currently required to successfully and consistently perform the inertia welding of production parts.

Optimization of Machining Process Parameters for Surface Roughness of Al-Composites

NASA Astrophysics Data System (ADS)

Sharma, S.

2013-10-01

Metal matrix composites (MMCs) have become a leading material among the various types of composite materials for different applications due to their excellent engineering properties. Among the various types of composites materials, aluminum MMCs have received considerable attention in automobile and aerospace applications. These materials are known as the difficult-to-machine materials because of the hardness and abrasive nature of reinforcement element-like silicon carbide particles. In the present investigation Al-SiC composite was produced by stir casting process. The Brinell hardness of the alloy after SiC addition had increased from 74 ± 2 to 95 ± 5 respectively. The composite was machined using CNC turning center under different machining parameters such as cutting speed (S), feed rate (F), depth of cut (D) and nose radius (R). The effect of machining parameters on surface roughness (Ra) was studied using response surface methodology. Face centered composite design with three levels of each factor was used for surface roughness study of the developed composite. A response surface model for surface roughness was developed in terms of main factors (S, F, D and R) and their significant interactions (SD, SR, FD and FR). The developed model was validated by conducting experiments under different conditions. Further the model was optimized for minimum surface roughness. An error of 3-7 % was observed in the modeled and experimental results. Further, it was fond that the surface roughness of Al-alloy at optimum conditions is lower than that of Al-SiC composite.

Extra high speed modified Lundell alternator parameters and open/short-circuit characteristics from global 3D-FE magnetic field solutions

NASA Astrophysics Data System (ADS)

Wang, R.; Demerdash, N. A.

1992-06-01

The combined magnetic vector potential - magnetic scalar potential method of computation of 3D magnetic fields by finite elements, introduced in a companion paper, is used for global 3D field analysis and machine performance computations under open-circuit and short-circuit conditions for an example 14.3 kVA modified Lundell alternator, whose magnetic field is of intrinsic 3D nature. The computed voltages and currents under these machine test conditions were verified and found to be in very good agreement with corresponding test data. Results of use of this modelling and computation method in the study of a design alteration example, in which the stator stack length of the example alternator is stretched in order to increase voltage and volt-ampere rating, are given here. These results demonstrate the inadequacy of conventional 2D-based design concepts and the imperative of use of this type of 3D magnetic field modelling in the design and investigation of such machines.

Extra high speed modified Lundell alternator parameters and open/short-circuit characteristics from global 3D-FE magnetic field solutions

NASA Technical Reports Server (NTRS)

Wang, R.; Demerdash, N. A.

1992-01-01

The combined magnetic vector potential - magnetic scalar potential method of computation of 3D magnetic fields by finite elements, introduced in a companion paper, is used for global 3D field analysis and machine performance computations under open-circuit and short-circuit conditions for an example 14.3 kVA modified Lundell alternator, whose magnetic field is of intrinsic 3D nature. The computed voltages and currents under these machine test conditions were verified and found to be in very good agreement with corresponding test data. Results of use of this modelling and computation method in the study of a design alteration example, in which the stator stack length of the example alternator is stretched in order to increase voltage and volt-ampere rating, are given here. These results demonstrate the inadequacy of conventional 2D-based design concepts and the imperative of use of this type of 3D magnetic field modelling in the design and investigation of such machines.

Optimization of cutting parameters in CNC turning of stainless steel 304 with TiAlN nano coated carbide cutting tool

NASA Astrophysics Data System (ADS)

Durga Prasada Rao, V.; Harsha, N.; Raghu Ram, N. S.; Navya Geethika, V.

2018-02-01

In this work, turning was performed to optimize the surface finish or roughness (Ra) of stainless steel 304 with uncoated and coated carbide tools under dry conditions. The carbide tools were coated with Titanium Aluminium Nitride (TiAlN) nano coating using Physical Vapour Deposition (PVD) method. The machining parameters, viz., cutting speed, depth of cut and feed rate which show major impact on Ra are considered during turning. The experiments are designed as per Taguchi orthogonal array and machining process is done accordingly. Then second-order regression equations have been developed on the basis of experimental results for Ra in terms of machining parameters used. Regarding the effect of machining parameters, an upward trend is observed in Ra with respect to feed rate, and as cutting speed increases the Ra value increased slightly due to chatter and vibrations. The adequacy of response variable (Ra) is tested by conducting additional experiments. The predicted Ra values are found to be a close match of their corresponding experimental values of uncoated and coated tools. The corresponding average % errors are found to be within the acceptable limits. Then the surface roughness equations of uncoated and coated tools are set as the objectives of optimization problem and are solved by using Differential Evolution (DE) algorithm. Also the tool lives of uncoated and coated tools are predicted by using Taylor’s tool life equation.

Optimization of Coolant Technique Conditions for Machining A319 Aluminium Alloy Using Response Surface Method (RSM)

NASA Astrophysics Data System (ADS)

Zainal Ariffin, S.; Razlan, A.; Ali, M. Mohd; Efendee, A. M.; Rahman, M. M.

2018-03-01

Background/Objectives: The paper discusses about the optimum cutting parameters with coolant techniques condition (1.0 mm nozzle orifice, wet and dry) to optimize surface roughness, temperature and tool wear in the machining process based on the selected setting parameters. The selected cutting parameters for this study were the cutting speed, feed rate, depth of cut and coolant techniques condition. Methods/Statistical Analysis Experiments were conducted and investigated based on Design of Experiment (DOE) with Response Surface Method. The research of the aggressive machining process on aluminum alloy (A319) for automotive applications is an effort to understand the machining concept, which widely used in a variety of manufacturing industries especially in the automotive industry. Findings: The results show that the dominant failure mode is the surface roughness, temperature and tool wear when using 1.0 mm nozzle orifice, increases during machining and also can be alternative minimize built up edge of the A319. The exploration for surface roughness, productivity and the optimization of cutting speed in the technical and commercial aspects of the manufacturing processes of A319 are discussed in automotive components industries for further work Applications/Improvements: The research result also beneficial in minimizing the costs incurred and improving productivity of manufacturing firms. According to the mathematical model and equations, generated by CCD based RSM, experiments were performed and cutting coolant condition technique using size nozzle can reduces tool wear, surface roughness and temperature was obtained. Results have been analyzed and optimization has been carried out for selecting cutting parameters, shows that the effectiveness and efficiency of the system can be identified and helps to solve potential problems.

Contributions a la caracterisation et a l'amelioration de l'usinabilite de pieces d'acier elaborees par metallurgie des poudres

NASA Astrophysics Data System (ADS)

Boilard, Patrick

Even though powder metallurgy (P/M) is a near net shape process, a large number of parts still require one or more machining operations during the course of their elaboration and/or their finishing. The main objectives of the work presented in this thesis are centered on the elaboration of blends with enhanced machinability, as well as helping with the definition and in the characterization of the machinability of P/M parts. Enhancing machinability can be done in various ways, through the use of machinability additives and by decreasing the amount of porosity of the parts. These different ways of enhancing machinability have been investigated thoroughly, by systematically planning and preparing series of samples in order to obtain valid and repeatable results leading to meaningful conclusions relevant to the P/M domain. Results obtained during the course of the work are divided into three main chapters: (1) the effect of machining parameters on machinability, (2) the effect of additives on machinability, and (3) the development and the characterization of high density parts obtained by liquid phase sintering. Regarding the effect of machining parameters on machinability, studies were performed on parameters such as rotating speed, feed, tool position and diameter of the tool. Optimal cutting parameters are found for drilling operations performed on a standard FC-0208 blend, for different machinability criteria. Moreover, study of material removal rates shows the sensitivity of the machinability criteria for different machining parameters and indicates that thrust force is more regular than tool wear and slope of the drillability curve in the characterization of machinability. The chapter discussing the effect of various additives on machinability reveals many interesting results. First, work carried out on MoS2 additions reveals the dissociation of this additive and the creation of metallic sulphides (namely CuxS sulphides) when copper is present. Results also show that it is possible to reduce the amount of MoS2 in the blend so as to lower the dimensional change and the cost (blend Mo8A), while enhancing machinability and keeping hardness values within the same range (70 HRB). Second, adding enstatite (MgO·SiO2) permits the observation of the mechanisms occurring with the use of this additive. It is found that the stability of enstatite limits the diffusion of graphite during sintering, leading to the presence of free graphite in the pores, thus enhancing machinability. Furthermore, a lower amount of graphite in the matrix leads to a lower hardness, which is also beneficial to machinability. It is also found that the presence of copper enhances the diffusion of graphite, through the formation of a liquid phase during sintering. With the objective of improving machinability by reaching higher densities, blends were developed for densification through liquid phase sintering. High density samples are obtained (>7.5 g/cm3) for blends prepared with Fe-C-P constituents, namely with 0.5%P and 2.4%C. By systematically studying the effect of different parameters, the importance of the chemical composition (mainly the carbon content) and the importance of the sintering cycle (particularly the cooling rate) are demonstrated. Moreover, various heat treatments studied illustrate the different microstructures achievable for this system, showing various amounts of cementite, pearlite and free graphite. Although the machinability is limited for samples containing large amounts of cementite, it can be greatly improved with very slow cooling, leading to graphitization of the carbon in presence of phosphorus. Adequate control of the sintering cycle on samples made from FGS1625 powder leads to the obtention of high density (≥7.0 g/cm 3) microstructures containing various amounts of pearlite, ferrite and free graphite. Obtaining ferritic microstructures with free graphite designed for very high machinability (tool wear <1.0%) or fine pearlitic microstructures with excellent mechanical properties (transverse rupture strength >1600 MPa) is therefore possible. These results show that improvement of machinability through higher densities is limited by microstructure. Indeed, for the studied samples, microstructure is dominant in the determination of machinability, far more important than density, judging by the influence of cementite or of the volume fraction of free graphite on machinability for example. (Abstract shortened by UMI.)

Temperature Measurement and Numerical Prediction in Machining Inconel 718

PubMed Central

Tapetado, Alberto; Vázquez, Carmen; Miguélez, Henar

2017-01-01

Thermal issues are critical when machining Ni-based superalloy components designed for high temperature applications. The low thermal conductivity and extreme strain hardening of this family of materials results in elevated temperatures around the cutting area. This elevated temperature could lead to machining-induced damage such as phase changes and residual stresses, resulting in reduced service life of the component. Measurement of temperature during machining is crucial in order to control the cutting process, avoiding workpiece damage. On the other hand, the development of predictive tools based on numerical models helps in the definition of machining processes and the obtainment of difficult to measure parameters such as the penetration of the heated layer. However, the validation of numerical models strongly depends on the accurate measurement of physical parameters such as temperature, ensuring the calibration of the model. This paper focuses on the measurement and prediction of temperature during the machining of Ni-based superalloys. The temperature sensor was based on a fiber-optic two-color pyrometer developed for localized temperature measurements in turning of Inconel 718. The sensor is capable of measuring temperature in the range of 250 to 1200 °C. Temperature evolution is recorded in a lathe at different feed rates and cutting speeds. Measurements were used to calibrate a simplified numerical model for prediction of temperature fields during turning. PMID:28665312

Identification of New Potential Scientific and Technology Areas for DoD Application. Summary of Activities

DTIC Science & Technology

1986-07-31

designer will be able to more rapid- ly assemble a total software package from perfected modules that can be easily de - bugged or replaced with more...antinuclear interactions e. gravitational effects of antimatter 2. possible machine parameters and lattice design 3. electron and stochastic cooling needs 4...implementation, reliability requirements; development of design environments and of experimental methodology; technology transfer methods from

A novel single-phase flux-switching permanent magnet linear generator used for free-piston Stirling engine

NASA Astrophysics Data System (ADS)

Zheng, Ping; Sui, Yi; Tong, Chengde; Bai, Jingang; Yu, Bin; Lin, Fei

2014-05-01

This paper investigates a novel single-phase flux-switching permanent-magnet (PM) linear machine used for free-piston Stirling engines. The machine topology and operating principle are studied. A flux-switching PM linear machine is designed based on the quasi-sinusoidal speed characteristic of the resonant piston. Considering the performance of back electromotive force and thrust capability, some leading structural parameters, including the air gap length, the PM thickness, the ratio of the outer radius of mover to that of stator, the mover tooth width, the stator tooth width, etc., are optimized by finite element analysis. Compared with conventional three-phase moving-magnet linear machine, the proposed single-phase flux-switching topology shows advantages in less PM use, lighter mover, and higher volume power density.

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

NASA Astrophysics Data System (ADS)

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.

Performance analysis of a new radial-axial flux machine with SMC cores and ferrite magnets

NASA Astrophysics Data System (ADS)

Liu, Chengcheng; Wang, Youhua; Lei, Gang; Guo, Youguang; Zhu, Jianguo

2017-05-01

Soft magnetic composite (SMC) is a popular material in designing of new 3D flux electrical machines nowadays for it has the merits of isotropic magnetic characteristic, low eddy current loss and high design flexibility over the electric steel. The axial flux machine (AFM) with the extended stator tooth tip both in the radial and circumferential direction is a good example, which has been investigated in the last years. Based on the 3D flux AFM and radial flux machine, this paper proposes a new radial-axial flux machine (RAFM) with SMC cores and ferrite magnets, which has very high torque density though the low cost low magnetic energy ferrite magnet is utilized. Moreover, the cost of RAFM is quite low since the manufacturing cost can be reduced by using the SMC cores and the material cost will be decreased due to the adoption of the ferrite magnets. The 3D finite element method (FEM) is used to calculate the magnetic flux density distribution and electromagnetic parameters. For the core loss calculation, the rotational core loss computation method is used based on the experiment results from previous 3D magnetic tester.

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

NASA Astrophysics Data System (ADS)

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.

Study on Performance of Integration Control by Man and Machine in Stage of Final Approaching for Spaceship Rendezvous and Docking

NASA Astrophysics Data System (ADS)

Zhou, Qianxiang; Liu, Zhongqi

With the development of manned space technology, space rendezvous and docking (RVD) technology will play a more and more important role. The astronauts’ participation in a final close period of man-machine combination control is an important way of RVD technology. Spacecraft RVD control involves control problem of a total of 12 degrees of freedom (location) and attitude which it relative to the inertial space the orbit. Therefore, in order to reduce the astronauts’ operation load and reduce the security requirements to the ground station and achieve an optimal performance of the whole man-machine system, it is need to study how to design the number of control parameters of astronaut or aircraft automatic control system. In this study, with the laboratory conditions on the ground, a method was put forward to develop an experimental system in which the performance evaluation of spaceship RVD integration control by man and machine could be completed. After the RVD precision requirements were determined, 26 male volunteers aged 20-40 took part in the performance evaluation experiments. The RVD integration control success rates and total thruster ignition time were chosen as evaluation indices. Results show that if less than three RVD parameters control tasks were finished by subject and the rest of parameters control task completed by automation, the RVD success rate would be larger than eighty-eight percent and the fuel consumption would be optimized. In addition, there were two subjects who finished the whole six RVD parameters control tasks by enough train. In conclusion, if the astronauts' role should be integrated into the RVD control, it was suitable for them to finish the heading, pitch and roll control in order to assure the man-machine system high performance. If astronauts were needed to finish all parameter control, two points should be taken into consideration, one was enough fuel and another was enough long operation time.

Multi Response Optimization of Laser Micro Marking Process:A Grey- Fuzzy Approach

NASA Astrophysics Data System (ADS)

Shivakoti, I.; Das, P. P.; Kibria, G.; Pradhan, B. B.; Mustafa, Z.; Ghadai, R. K.

2017-07-01

The selection of optimal parametric combination for efficient machining has always become a challenging issue for the manufacturing researcher. The optimal parametric combination always provides a better machining which improves the productivity, product quality and subsequently reduces the production cost and time. The paper presents the hybrid approach of Grey relational analysis and Fuzzy logic to obtain the optimal parametric combination for better laser beam micro marking on the Gallium Nitride (GaN) work material. The response surface methodology has been implemented for design of experiment considering three parameters with their five levels. The parameter such as current, frequency and scanning speed has been considered and the mark width, mark depth and mark intensity has been considered as the process response.

An Analysis of Document Category Prediction Responses to Classifier Model Parameter Treatment Permutations within the Software Design Patterns Subject Domain

ERIC Educational Resources Information Center

Pankau, Brian L.

2009-01-01

This empirical study evaluates the document category prediction effectiveness of Naive Bayes (NB) and K-Nearest Neighbor (KNN) classifier treatments built from different feature selection and machine learning settings and trained and tested against textual corpora of 2300 Gang-Of-Four (GOF) design pattern documents. Analysis of the experiment's…

Performance study of a data flow architecture

NASA Technical Reports Server (NTRS)

Adams, George

1985-01-01

Teams of scientists studied data flow concepts, static data flow machine architecture, and the VAL language. Each team mapped its application onto the machine and coded it in VAL. The principal findings of the study were: (1) Five of the seven applications used the full power of the target machine. The galactic simulation and multigrid fluid flow teams found that a significantly smaller version of the machine (16 processing elements) would suffice. (2) A number of machine design parameters including processing element (PE) function unit numbers, array memory size and bandwidth, and routing network capability were found to be crucial for optimal machine performance. (3) The study participants readily acquired VAL programming skills. (4) Participants learned that application-based performance evaluation is a sound method of evaluating new computer architectures, even those that are not fully specified. During the course of the study, participants developed models for using computers to solve numerical problems and for evaluating new architectures. These models form the bases for future evaluation studies.

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

PubMed

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.

Experimental Investigation – Magnetic Assisted Electro Discharge Machining

NASA Astrophysics Data System (ADS)

Kesava Reddy, Chirra; Manzoor Hussain, M.; Satyanarayana, S.; Krishna, M. V. S. Murali

2018-04-01

Emerging technology needs advanced machined parts with high strength and temperature resistance, high fatigue life at low production cost with good surface quality to fit into various industrial applications. Electro discharge machine is one of the extensively used machines to manufacture advanced machined parts which cannot be machined by other traditional machine with high precision and accuracy. Machining of DIN 17350-1.2080 (High Carbon High Chromium steel), using electro discharge machining has been discussed in this paper. In the present investigation an effort is made to use permanent magnet at various positions near the spark zone to improve surface quality of the machined surface. Taguchi methodology is used to obtain optimal choice for each machining parameter such as peak current, pulse duration, gap voltage and Servo reference voltage etc. Process parameters have significant influence on machining characteristics and surface finish. Improvement in surface finish is observed when process parameters are set at optimum condition under the influence of magnetic field at various positions.

Harmony search optimization in dimensional accuracy of die sinking EDM process using SS316L stainless steel

NASA Astrophysics Data System (ADS)

Deris, A. M.; Zain, A. M.; Sallehuddin, R.; Sharif, S.

2017-09-01

Electric discharge machine (EDM) is one of the widely used nonconventional machining processes for hard and difficult to machine materials. Due to the large number of machining parameters in EDM and its complicated structural, the selection of the optimal solution of machining parameters for obtaining minimum machining performance is remain as a challenging task to the researchers. This paper proposed experimental investigation and optimization of machining parameters for EDM process on stainless steel 316L work piece using Harmony Search (HS) algorithm. The mathematical model was developed based on regression approach with four input parameters which are pulse on time, peak current, servo voltage and servo speed to the output response which is dimensional accuracy (DA). The optimal result of HS approach was compared with regression analysis and it was found HS gave better result y giving the most minimum DA value compared with regression approach.

Design of Clinical Support Systems Using Integrated Genetic Algorithm and Support Vector Machine

NASA Astrophysics Data System (ADS)

Chen, Yung-Fu; Huang, Yung-Fa; Jiang, Xiaoyi; Hsu, Yuan-Nian; Lin, Hsuan-Hung

Clinical decision support system (CDSS) provides knowledge and specific information for clinicians to enhance diagnostic efficiency and improving healthcare quality. An appropriate CDSS can highly elevate patient safety, improve healthcare quality, and increase cost-effectiveness. Support vector machine (SVM) is believed to be superior to traditional statistical and neural network classifiers. However, it is critical to determine suitable combination of SVM parameters regarding classification performance. Genetic algorithm (GA) can find optimal solution within an acceptable time, and is faster than greedy algorithm with exhaustive searching strategy. By taking the advantage of GA in quickly selecting the salient features and adjusting SVM parameters, a method using integrated GA and SVM (IGS), which is different from the traditional method with GA used for feature selection and SVM for classification, was used to design CDSSs for prediction of successful ventilation weaning, diagnosis of patients with severe obstructive sleep apnea, and discrimination of different cell types form Pap smear. The results show that IGS is better than methods using SVM alone or linear discriminator.

CEPC-SPPC accelerator status towards CDR

NASA Astrophysics Data System (ADS)

Gao, J.

2017-12-01

In this paper we will give an introduction to the Circular Electron Positron Collider (CEPC). The scientific background, physics goal, the collider design requirements and the conceptual design principle of the CEPC are described. On the CEPC accelerator, the optimization of parameter designs for the CEPC with different energies, machine lengths, single ring and crab-waist collision partial double ring, advanced partial double ring and fully partial double ring options, etc. have been discussed systematically, and compared. The CEPC accelerator baseline and alternative designs have been proposed based on the luminosity potential in relation with the design goals. The CEPC sub-systems, such as the collider main ring, booster, electron positron injector, etc. have also been introduced. The detector and the MAchine-Detector Interface (MDI) design have been briefly mentioned. Finally, the optimization design of the Super Proton-Proton Collider (SppC), its energy and luminosity potentials, in the same tunnel of the CEPC are also discussed. The CEPC-SppC Progress Report (2015-2016) has been published.

Design of a Smart Ultrasonic Transducer for Interconnecting Machine Applications

PubMed Central

Yan, Tian-Hong; Wang, Wei; Chen, Xue-Dong; Li, Qing; Xu, Chang

2009-01-01

A high-frequency ultrasonic transducer for copper or gold wire bonding has been designed, analyzed, prototyped and tested. Modeling techniques were used in the design phase and a practical design procedure was established and used. The transducer was decomposed into its elementary components. For each component, an initial design was obtained with simulations using a finite elements model (FEM). Simulated ultrasonic modules were built and characterized experimentally through the Laser Doppler Vibrometer (LDV) and electrical resonance spectra. Compared with experimental data, the FEM could be iteratively adjusted and updated. Having achieved a remarkably highly-predictive FEM of the whole transducer, the design parameters could be tuned for the desired applications, then the transducer is fixed on the wire bonder with a complete holder clamping was calculated by the FEM. The approach to mount ultrasonic transducers on wire bonding machines also is of major importance for wire bonding in modern electronic packaging. The presented method can lead to obtaining a nearly complete decoupling clamper design of the transducer to the wire bonder. PMID:22408564

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hussain, A

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 wasmore » 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.« less

Geometric and computer-aided spline hob modeling

NASA Astrophysics Data System (ADS)

Brailov, I. G.; Myasoedova, T. M.; Panchuk, K. L.; Krysova, I. V.; Rogoza, YU A.

2018-03-01

The paper considers acquiring the spline hob geometric model. The objective of the research is the development of a mathematical model of spline hob for spline shaft machining. The structure of the spline hob is described taking into consideration the motion in parameters of the machine tool system of cutting edge positioning and orientation. Computer-aided study is performed with the use of CAD and on the basis of 3D modeling methods. Vector representation of cutting edge geometry is accepted as the principal method of spline hob mathematical model development. The paper defines the correlations described by parametric vector functions representing helical cutting edges designed for spline shaft machining with consideration for helical movement in two dimensions. An application for acquiring the 3D model of spline hob is developed on the basis of AutoLISP for AutoCAD environment. The application presents the opportunity for the use of the acquired model for milling process imitation. An example of evaluation, analytical representation and computer modeling of the proposed geometrical model is reviewed. In the mentioned example, a calculation of key spline hob parameters assuring the capability of hobbing a spline shaft of standard design is performed. The polygonal and solid spline hob 3D models are acquired by the use of imitational computer modeling.

Artificial Neural Networks as an Architectural Design Tool-Generating New Detail Forms Based On the Roman Corinthian Order Capital

NASA Astrophysics Data System (ADS)

Radziszewski, Kacper

2017-10-01

The following paper presents the results of the research in the field of the machine learning, investigating the scope of application of the artificial neural networks algorithms as a tool in architectural design. The computational experiment was held using the backward propagation of errors method of training the artificial neural network, which was trained based on the geometry of the details of the Roman Corinthian order capital. During the experiment, as an input training data set, five local geometry parameters combined has given the best results: Theta, Pi, Rho in spherical coordinate system based on the capital volume centroid, followed by Z value of the Cartesian coordinate system and a distance from vertical planes created based on the capital symmetry. Additionally during the experiment, artificial neural network hidden layers optimal count and structure was found, giving results of the error below 0.2% for the mentioned before input parameters. Once successfully trained artificial network, was able to mimic the details composition on any other geometry type given. Despite of calculating the transformed geometry locally and separately for each of the thousands of surface points, system could create visually attractive and diverse, complex patterns. Designed tool, based on the supervised learning method of machine learning, gives possibility of generating new architectural forms- free of the designer’s imagination bounds. Implementing the infinitely broad computational methods of machine learning, or Artificial Intelligence in general, not only could accelerate and simplify the design process, but give an opportunity to explore never seen before, unpredictable forms or everyday architectural practice solutions.

Grey Relational Analysis Coupled with Principal Component Analysis for Optimization of Stereolithography Process to Enhance Part Quality

NASA Astrophysics Data System (ADS)

Raju, B. S.; Sekhar, U. Chandra; Drakshayani, D. N.

2017-08-01

The paper investigates optimization of stereolithography process for SL5530 epoxy resin material to enhance part quality. The major characteristics indexed for performance selected to evaluate the processes are tensile strength, Flexural strength, Impact strength and Density analysis and corresponding process parameters are Layer thickness, Orientation and Hatch spacing. In this study, the process is intrinsically with multiple parameters tuning so that grey relational analysis which uses grey relational grade as performance index is specially adopted to determine the optimal combination of process parameters. Moreover, the principal component analysis is applied to evaluate the weighting values corresponding to various performance characteristics so that their relative importance can be properly and objectively desired. The results of confirmation experiments reveal that grey relational analysis coupled with principal component analysis can effectively acquire the optimal combination of process parameters. Hence, this confirm that the proposed approach in this study can be an useful tool to improve the process parameters in stereolithography process, which is very useful information for machine designers as well as RP machine users.

Progressive sampling-based Bayesian optimization for efficient and automatic machine learning model selection.

PubMed

Zeng, Xueqiang; Luo, Gang

2017-12-01

Machine learning is broadly used for clinical data analysis. Before training a model, a machine learning algorithm must be selected. Also, the values of one or more model parameters termed hyper-parameters must be set. Selecting algorithms and hyper-parameter values requires advanced machine learning knowledge and many labor-intensive manual iterations. To lower the bar to machine learning, miscellaneous automatic selection methods for algorithms and/or hyper-parameter values have been proposed. Existing automatic selection methods are inefficient on large data sets. This poses a challenge for using machine learning in the clinical big data era. To address the challenge, this paper presents progressive sampling-based Bayesian optimization, an efficient and automatic selection method for both algorithms and hyper-parameter values. We report an implementation of the method. We show that compared to a state of the art automatic selection method, our method can significantly reduce search time, classification error rate, and standard deviation of error rate due to randomization. This is major progress towards enabling fast turnaround in identifying high-quality solutions required by many machine learning-based clinical data analysis tasks.

The Impact Of Surface Shape Of Chip-Breaker On Machined Surface

NASA Astrophysics Data System (ADS)

Šajgalík, Michal; Czán, Andrej; Martinček, Juraj; Varga, Daniel; Hemžský, Pavel; Pitela, David

2015-12-01

Machined surface is one of the most used indicators of workpiece quality. But machined surface is influenced by several factors such as cutting parameters, cutting material, shape of cutting tool or cutting insert, micro-structure of machined material and other known as technological parameters. By improving of these parameters, we can improve machined surface. In the machining, there is important to identify the characteristics of main product of these processes - workpiece, but also the byproduct - the chip. Size and shape of chip has impact on lifetime of cutting tools and its inappropriate form can influence the machine functionality and lifetime, too. This article deals with elimination of long chip created when machining of shaft in automotive industry and with impact of shape of chip-breaker on shape of chip in various cutting conditions based on production requirements.

A Parameter Communication Optimization Strategy for Distributed Machine Learning in Sensors

PubMed Central

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

2017-01-01

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. PMID:28934163

Optimization and Analysis of Laser Beam Machining Parameters for Al7075-TiB2 In-situ Composite

NASA Astrophysics Data System (ADS)

Manjoth, S.; Keshavamurthy, R.; Pradeep Kumar, G. S.

2016-09-01

The paper focuses on laser beam machining (LBM) of In-situ synthesized Al7075-TiB2 metal matrix composite. Optimization and influence of laser machining process parameters on surface roughness, volumetric material removal rate (VMRR) and dimensional accuracy of composites were studied. Al7075-TiB2 metal matrix composite was synthesized by in-situ reaction technique using stir casting process. Taguchi's L9 orthogonal array was used to design experimental trials. Standoff distance (SOD) (0.3 - 0.5mm), Cutting Speed (1000 - 1200 m/hr) and Gas pressure (0.5 - 0.7 bar) were considered as variable input parameters at three different levels, while power and nozzle diameter were maintained constant with air as assisting gas. Optimized process parameters for surface roughness, volumetric material removal rate (VMRR) and dimensional accuracy were calculated by generating the main effects plot for signal noise ratio (S/N ratio) for surface roughness, VMRR and dimensional error using Minitab software (version 16). The Significant of standoff distance (SOD), cutting speed and gas pressure on surface roughness, volumetric material removal rate (VMRR) and dimensional error were calculated using analysis of variance (ANOVA) method. Results indicate that, for surface roughness, cutting speed (56.38%) is most significant parameter followed by standoff distance (41.03%) and gas pressure (2.6%). For volumetric material removal (VMRR), gas pressure (42.32%) is most significant parameter followed by cutting speed (33.60%) and standoff distance (24.06%). For dimensional error, Standoff distance (53.34%) is most significant parameter followed by cutting speed (34.12%) and gas pressure (12.53%). Further, verification experiments were carried out to confirm performance of optimized process parameters.

Design optimization for permanent magnet machine with efficient slot per pole ratio

NASA Astrophysics Data System (ADS)

Potnuru, Upendra Kumar; Rao, P. Mallikarjuna

2018-04-01

This paper presents a methodology for the enhancement of a Brush Less Direct Current motor (BLDC) with 6Poles and 8slots. In particular; it is focused on amulti-objective optimization using a Genetic Algorithmand Grey Wolf Optimization developed in MATLAB. The optimization aims to maximize the maximum output power value and minimize the total losses of a motor. This paper presents an application of the MATLAB optimization algorithms to brushless DC (BLDC) motor design, with 7 design parameters chosen to be free. The optimal design parameters of the motor derived by GA are compared with those obtained by Grey Wolf Optimization technique. A comparative report on the specified enhancement approaches appearsthat Grey Wolf Optimization technique has a better convergence.

Research on tool wearing on milling of TC21 titanium alloy

NASA Astrophysics Data System (ADS)

Guilin, Liu

2017-06-01

Titanium alloys are used in aircraft widely, but the efficiency is a problem for machining titanium alloy. In this paper, the cutting experiment of TC21 titanium alloy was studied. Cutting parameters and test methods for TC21 titanium alloy were designed. The wear behavior of TC21 titanium alloy was studied based on analysis of orthogonal test results. It provides a group of cutting parameters for TC21 titanium alloy processing.

Machining Parameters Optimization using Hybrid Firefly Algorithm and Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

Farahlina Johari, Nur; Zain, Azlan Mohd; Haszlinna Mustaffa, Noorfa; Udin, Amirmudin

2017-09-01

Firefly Algorithm (FA) is a metaheuristic algorithm that is inspired by the flashing behavior of fireflies and the phenomenon of bioluminescent communication and the algorithm is used to optimize the machining parameters (feed rate, depth of cut, and spindle speed) in this research. The algorithm is hybridized with Particle Swarm Optimization (PSO) to discover better solution in exploring the search space. Objective function of previous research is used to optimize the machining parameters in turning operation. The optimal machining cutting parameters estimated by FA that lead to a minimum surface roughness are validated using ANOVA test.

A comparative study on performance of CBN inserts when turning steel under dry and wet conditions

NASA Astrophysics Data System (ADS)

Abdullah Bagaber, Salem; Razlan Yusoff, Ahmad

2017-10-01

Cutting fluids is the most unsustainable components of machining processes, it is negatively impacting on the environmental and additional energy required. Due to its high strength and corrosion resistance, the machinability of stainless steel has attracted considerable interest. This study aims to evaluate performance of cubic boron nitride (CBN) inserts for the machining parameters includes the power consumption and surface roughness. Due to the high single cutting-edge cost of CBN, the performance of significant is importance for hard finish turning. The present work also deals with a comparative study on power consumption and surface roughness under dry and flood conditions. Turning process of the stainless steel 316 was performed. A response surface methodology based box-behnken design (BBD) was utilized for statistical analysis. The optimum process parameters are determined as the overall performance index. The comparison study has been done between dry and wet stainless-steel cut in terms of minimum value of energy and surface roughness. The result shows the stainless still can be machined under dry condition with 18.57% improvement of power consumption and acceptable quality compare to the wet cutting. The CBN tools under dry cutting stainless steel can be used to reduce the environment impacts in terms of no cutting fluid use and less energy required which is effected in machining productivity and profit.

TEA CO2 laser machining of CFRP composite

NASA Astrophysics Data System (ADS)

Salama, A.; Li, L.; Mativenga, P.; Whitehead, D.

2016-05-01

Carbon fibre-reinforced polymer (CFRP) composites have found wide applications in the aerospace, marine, sports and automotive industries owing to their lightweight and acceptable mechanical properties compared to the commonly used metallic materials. Machining of CFRP composites using lasers can be challenging due to inhomogeneity in the material properties and structures, which can lead to thermal damages during laser processing. In the previous studies, Nd:YAG, diode-pumped solid-state, CO2 (continuous wave), disc and fibre lasers were used in cutting CFRP composites and the control of damages such as the size of heat-affected zones (HAZs) remains a challenge. In this paper, a short-pulsed (8 μs) transversely excited atmospheric pressure CO2 laser was used, for the first time, to machine CFRP composites. The laser has high peak powers (up to 250 kW) and excellent absorption by both the carbon fibre and the epoxy binder. Design of experiment and statistical modelling, based on response surface methodology, was used to understand the interactions between the process parameters such as laser fluence, repetition rate and cutting speed and their effects on the cut quality characteristics including size of HAZ, machining depth and material removal rate (MRR). Based on this study, process parameter optimization was carried out to minimize the HAZ and maximize the MRR. A discussion is given on the potential applications and comparisons to other lasers in machining CFRP.

RG-inspired machine learning for lattice field theory

NASA Astrophysics Data System (ADS)

Foreman, Sam; Giedt, Joel; Meurice, Yannick; Unmuth-Yockey, Judah

2018-03-01

Machine learning has been a fast growing field of research in several areas dealing with large datasets. We report recent attempts to use renormalization group (RG) ideas in the context of machine learning. We examine coarse graining procedures for perceptron models designed to identify the digits of the MNIST data. We discuss the correspondence between principal components analysis (PCA) and RG flows across the transition for worm configurations of the 2D Ising model. Preliminary results regarding the logarithmic divergence of the leading PCA eigenvalue were presented at the conference. More generally, we discuss the relationship between PCA and observables in Monte Carlo simulations and the possibility of reducing the number of learning parameters in supervised learning based on RG inspired hierarchical ansatzes.

Intelligent Adaptive Interface: A Design Tool for Enhancing Human-Machine System Performances

DTIC Science & Technology

2009-10-01

and customizable. Thus, an intelligent interface should tailor its parameters to certain prescribed specifications or convert itself and adjust to...Computer Interaction 3(2): 87-122. [51] Schereiber, G., Akkermans, H., Anjewierden, A., de Hoog , R., Shadbolt, N., Van de Velde, W., & Wielinga, W

Influence of grid bar shape on field cleaner performance - Screening tests

USDA-ARS?s Scientific Manuscript database

Extractor type cleaners are used on cotton strippers and in the seed cotton cleaning machinery in the ginning process to remove large foreign material such as burrs and sticks. Previous research on the development of extractor type cleaners focused on machine design and operating parameters that max...

Performance evaluation of the croissant production line with reparable machines

NASA Astrophysics Data System (ADS)

Tsarouhas, Panagiotis H.

2015-03-01

In this study, the analytical probability models for an automated serial production system, bufferless that consists of n-machines in series with common transfer mechanism and control system was developed. Both time to failure and time to repair a failure are assumed to follow exponential distribution. Applying those models, the effect of system parameters on system performance in actual croissant production line was studied. The production line consists of six workstations with different numbers of reparable machines in series. Mathematical models of the croissant production line have been developed using Markov process. The strength of this study is in the classification of the whole system in states, representing failures of different machines. Failure and repair data from the actual production environment have been used to estimate reliability and maintainability for each machine, workstation, and the entire line is based on analytical models. The analysis provides a useful insight into the system's behaviour, helps to find design inherent faults and suggests optimal modifications to upgrade the system and improve its performance.

Optimization of processing parameters of UAV integral structural components based on yield response

NASA Astrophysics Data System (ADS)

Chen, Yunsheng

2018-05-01

In order to improve the overall strength of unmanned aerial vehicle (UAV), it is necessary to optimize the processing parameters of UAV structural components, which is affected by initial residual stress in the process of UAV structural components processing. Because machining errors are easy to occur, an optimization model for machining parameters of UAV integral structural components based on yield response is proposed. The finite element method is used to simulate the machining parameters of UAV integral structural components. The prediction model of workpiece surface machining error is established, and the influence of the path of walking knife on residual stress of UAV integral structure is studied, according to the stress of UAV integral component. The yield response of the time-varying stiffness is analyzed, and the yield response and the stress evolution mechanism of the UAV integral structure are analyzed. The simulation results show that this method is used to optimize the machining parameters of UAV integral structural components and improve the precision of UAV milling processing. The machining error is reduced, and the deformation prediction and error compensation of UAV integral structural parts are realized, thus improving the quality of machining.

Design of a large magnetic-bearing turbomolecular pump for NET

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bernhardt, K.H.; Conrad, A.; Dinner, P.J.

1988-09-01

The feasibility of development of large vacuum components for operation in fusion machines have been investigated in the framework of the European Fusion Technology Programme. The requirements and the results of the feasibility study for the large turbomolecular pump units (TMP) are presented. Design parameters for single flow 50.000 l/s TMP and a double flow 15.000 and a 50.000 l/s TMP have been compared.

Micro-machined resonator oscillator

DOEpatents

Koehler, Dale R.; Sniegowski, Jeffry J.; Bivens, Hugh M.; Wessendorf, Kurt O.

1994-01-01

A micro-miniature resonator-oscillator is disclosed. Due to the miniaturization of the resonator-oscillator, oscillation frequencies of one MHz and higher are utilized. A thickness-mode quartz resonator housed in a micro-machined silicon package and operated as a "telemetered sensor beacon" that is, a digital, self-powered, remote, parameter measuring-transmitter in the FM-band. The resonator design uses trapped energy principles and temperature dependence methodology through crystal orientation control, with operation in the 20-100 MHz range. High volume batch-processing manufacturing is utilized, with package and resonator assembly at the wafer level. Unique design features include squeeze-film damping for robust vibration and shock performance, capacitive coupling through micro-machined diaphragms allowing resonator excitation at the package exterior, circuit integration and extremely small (0.1 in. square) dimensioning. A family of micro-miniature sensor beacons is also disclosed with widespread applications as bio-medical sensors, vehicle status monitors and high-volume animal identification and health sensors. The sensor family allows measurement of temperatures, chemicals, acceleration and pressure. A microphone and clock realization is also available.

Design and Performance Improvement of AC Machines Sharing a Common Stator

NASA Astrophysics Data System (ADS)

Guo, Lusu

With the increasing demand on electric motors in various industrial applications, especially electric powered vehicles (electric cars, more electric aircrafts and future electric ships and submarines), both synchronous reluctance machines (SynRMs) and interior permanent magnet (IPM) machines are recognized as good candidates for high performance variable speed applications. Developing a single stator design which can be used for both SynRM and IPM motors is a good way to reduce manufacturing and maintenance cost. SynRM can be used as a low cost solution for many electric driving applications and IPM machines can be used in power density crucial circumstances or work as generators to meet the increasing demand for electrical power on board. In this research, SynRM and IPM machines are designed sharing a common stator structure. The prototype motors are designed with the aid of finite element analysis (FEA). Machine performances with different stator slot and rotor pole numbers are compared by FEA. An 18-slot, 4-pole structure is selected based on the comparison for this prototype design. Sometimes, torque pulsation is the major drawback of permanent magnet synchronous machines. There are several sources of torque pulsations, such as back-EMF distortion, inductance variation and cogging torque due to presence of permanent magnets. To reduce torque pulsations in permanent magnet machines, all the efforts can be classified into two categories: one is from the design stage, the structure of permanent magnet machines can be optimized with the aid of finite element analysis. The other category of reducing torque pulsation is after the permanent magnet machine has been manufactured or the machine structure cannot be changed because of other reasons. The currents fed into the permanent magnet machine can be controlled to follow a certain profile which will make the machine generate a smoother torque waveform. Torque pulsation reduction methods in both categories will be discussed in this dissertation. In the design stage, an optimization method based on orthogonal experimental design will be introduced. Besides, a universal current profiling technique is proposed to minimize the torque pulsation along with the stator copper losses in modular interior permanent magnet motors. Instead of sinusoidal current waveforms, this algorithm will calculate the proper currents which can minimize the torque pulsation. Finite element analysis and Matlab programing will be used to develop this optimal current profiling algorithm. Permanent magnet machines are becoming more attractive in some modern traction applications, such as traction motors and generators for an electrified vehicle. The operating speed or the load condition in these applications may be changing all the time. Compared to electric machines used to operate at a constant speed and constant load, better control performance is required. In this dissertation, a novel model reference adaptive control (MRAC) used on five-phase interior permanent magnet motor drives is presented. The primary controller is designed based on artificial neural network (ANN) to simulate the nonlinear characteristics of the system without knowledge of accurate motor model or parameters. The proposed motor drive decouples the torque and flux components of five-phase IPM motors by applying a multiple reference frame transformation. Therefore, the motor can be easily driven below the rated speed with the maximum torque per ampere (MTPA) operation or above the rated speed with the flux weakening operation. The ANN based primary controller consists of a radial basis function (RBF) network which is trained on-line to adapt system uncertainties. The complete IPM motor drive is simulated in Matlab/Simulink environment and implemented experimentally utilizing dSPACE DS1104 DSP board on a five-phase prototype IPM motor. The proposed model reference adaptive control method has been applied on the commons stator SynRM and IPM machine as well.

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

NASA Astrophysics Data System (ADS)

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.

Normal contour error measurement on-machine and compensation method for polishing complex surface by MRF

NASA Astrophysics Data System (ADS)

Chen, Hua; Chen, Jihong; Wang, Baorui; Zheng, Yongcheng

2016-10-01

The Magnetorheological finishing (MRF) process, based on the dwell time method with the constant normal spacing for flexible polishing, would bring out the normal contour error in the fine polishing complex surface such as aspheric surface. The normal contour error would change the ribbon's shape and removal characteristics of consistency for MRF. Based on continuously scanning the normal spacing between the workpiece and the finder by the laser range finder, the novel method was put forward to measure the normal contour errors while polishing complex surface on the machining track. The normal contour errors was measured dynamically, by which the workpiece's clamping precision, multi-axis machining NC program and the dynamic performance of the MRF machine were achieved for the verification and security check of the MRF process. The unit for measuring the normal contour errors of complex surface on-machine was designed. Based on the measurement unit's results as feedback to adjust the parameters of the feed forward control and the multi-axis machining, the optimized servo control method was presented to compensate the normal contour errors. The experiment for polishing 180mm × 180mm aspherical workpiece of fused silica by MRF was set up to validate the method. The results show that the normal contour error was controlled in less than 10um. And the PV value of the polished surface accuracy was improved from 0.95λ to 0.09λ under the conditions of the same process parameters. The technology in the paper has been being applied in the PKC600-Q1 MRF machine developed by the China Academe of Engineering Physics for engineering application since 2014. It is being used in the national huge optical engineering for processing the ultra-precision optical parts.

[A prediction model for the activity of insecticidal crystal proteins from Bacillus thuringiensis based on support vector machine].

PubMed

Lin, Yi; Cai, Fu-Ying; Zhang, Guang-Ya

2007-01-01

A quantitative structure-property relationship (QSPR) model in terms of amino acid composition and the activity of Bacillus thuringiensis insecticidal crystal proteins was established. Support vector machine (SVM) is a novel general machine-learning tool based on the structural risk minimization principle that exhibits good generalization when fault samples are few; it is especially suitable for classification, forecasting, and estimation in cases where small amounts of samples are involved such as fault diagnosis; however, some parameters of SVM are selected based on the experience of the operator, which has led to decreased efficiency of SVM in practical application. The uniform design (UD) method was applied to optimize the running parameters of SVM. It was found that the average accuracy rate approached 73% when the penalty factor was 0.01, the epsilon 0.2, the gamma 0.05, and the range 0.5. The results indicated that UD might be used an effective method to optimize the parameters of SVM and SVM and could be used as an alternative powerful modeling tool for QSPR studies of the activity of Bacillus thuringiensis (Bt) insecticidal crystal proteins. Therefore, a novel method for predicting the insecticidal activity of Bt insecticidal crystal proteins was proposed by the authors of this study.

A Genetic Algorithm Based Support Vector Machine Model for Blood-Brain Barrier Penetration Prediction

PubMed Central

Zhang, Daqing; Xiao, Jianfeng; Zhou, Nannan; Luo, Xiaomin; Jiang, Hualiang; Chen, Kaixian

2015-01-01

Blood-brain barrier (BBB) is a highly complex physical barrier determining what substances are allowed to enter the brain. Support vector machine (SVM) is a kernel-based machine learning method that is widely used in QSAR study. For a successful SVM model, the kernel parameters for SVM and feature subset selection are the most important factors affecting prediction accuracy. In most studies, they are treated as two independent problems, but it has been proven that they could affect each other. We designed and implemented genetic algorithm (GA) to optimize kernel parameters and feature subset selection for SVM regression and applied it to the BBB penetration prediction. The results show that our GA/SVM model is more accurate than other currently available log BB models. Therefore, to optimize both SVM parameters and feature subset simultaneously with genetic algorithm is a better approach than other methods that treat the two problems separately. Analysis of our log BB model suggests that carboxylic acid group, polar surface area (PSA)/hydrogen-bonding ability, lipophilicity, and molecular charge play important role in BBB penetration. Among those properties relevant to BBB penetration, lipophilicity could enhance the BBB penetration while all the others are negatively correlated with BBB penetration. PMID:26504797

Additive Manufacturing in Production: A Study Case Applying Technical Requirements

NASA Astrophysics Data System (ADS)

Ituarte, Iñigo Flores; Coatanea, Eric; Salmi, Mika; Tuomi, Jukka; Partanen, Jouni

Additive manufacturing (AM) is expanding the manufacturing capabilities. However, quality of AM produced parts is dependent on a number of machine, geometry and process parameters. The variability of these parameters affects the manufacturing drastically and therefore standardized processes and harmonized methodologies need to be developed to characterize the technology for end use applications and enable the technology for manufacturing. This research proposes a composite methodology integrating Taguchi Design of Experiments, multi-objective optimization and statistical process control, to optimize the manufacturing process and fulfil multiple requirements imposed to an arbitrary geometry. The proposed methodology aims to characterize AM technology depending upon manufacturing process variables as well as to perform a comparative assessment of three AM technologies (Selective Laser Sintering, Laser Stereolithography and Polyjet). Results indicate that only one machine, laser-based Stereolithography, was feasible to fulfil simultaneously macro and micro level geometrical requirements but mechanical properties were not at required level. Future research will study a single AM system at the time to characterize AM machine technical capabilities and stimulate pre-normative initiatives of the technology for end use applications.

Controlling the Adhesion of Superhydrophobic Surfaces Using Electrolyte Jet Machining Techniques

PubMed Central

Yang, Xiaolong; Liu, Xin; Lu, Yao; Zhou, Shining; Gao, Mingqian; Song, Jinlong; Xu, Wenji

2016-01-01

Patterns with controllable adhesion on superhydrophobic areas have various biomedical and chemical applications. Electrolyte jet machining technique (EJM), an electrochemical machining method, was firstly exploited in constructing dimples with various profiles on the superhydrophobic Al alloy surface using different processing parameters. Sliding angles of water droplets on those dimples firstly increased and then stabilized at a certain value with the increase of the processing time or the applied voltages of the EJM, indicating that surfaces with different adhesion force could be obtained by regulating the processing parameters. The contact angle hysteresis and the adhesion force that restricts the droplet from sliding off were investigated through experiments. The results show that the adhesion force could be well described using the classical Furmidge equation. On account of this controllable adhesion force, water droplets could either be firmly pinned to the surface, forming various patterns or slide off at designed tilting angles at specified positions on a superhydrophobic surface. Such dimples on superhydrophopbic surfaces can be applied in water harvesting, biochemical analysis and lab-on-chip devices. PMID:27046771

Investigating the Effect of Approach Angle and Nose Radius on Surface Quality of Inconel 718

NASA Astrophysics Data System (ADS)

Kumar, Sunil; Singh, Dilbag; Kalsi, Nirmal S.

2017-11-01

This experimental work presents a surface quality evaluation of a Nickel-Cr-Fe based Inconel 718 superalloy, which has many applications in the aero engine and turbine components. However, during machining, the early wear of tool leads to decrease in surface quality. The coating on cutting tool plays a significant role in increasing the wear resistance and life of the tool. In this work, the aim is to study the surface quality of Inconel 718 with TiAlN-coated carbide tools. Influence of various geometrical parameters (tool nose radius, approach angle) and machining variables (cutting velocity, feed rate) on the quality of machined surface (surface roughness) was determined by using central composite design (CCD) matrix. The mathematical model of the same was developed. Analysis of variance was used to find the significance of the parameters. Results showed that the tool nose radius and feed were the main active factors. The present experiment accomplished that TiAlN-coated carbide inserts result in better surface quality as compared with uncoated carbide inserts.

Decision based on big data research for non-small cell lung cancer in medical artificial system in developing country.

PubMed

Wu, Jia; Tan, Yanlin; Chen, Zhigang; Zhao, Ming

2018-06-01

Non-small cell lung cancer (NSCLC) is a high risk cancer and is usually scanned by PET-CT for testing, predicting and then give the treatment methods. However, in the actual hospital system, at least 640 images must be generated for each patient through PET-CT scanning. Especially in developing countries, a huge number of patients in NSCLC are attended by doctors. Artificial system can predict and make decision rapidly. According to explore and research artificial medical system, the selection of artificial observations also can result in low work efficiency for doctors. In this study, data information of 2,789,675 patients in three hospitals in China are collected, compiled, and used as the research basis; these data are obtained through image acquisition and diagnostic parameter machine decision-making method on the basis of the machine diagnosis and medical system design model of adjuvant therapy. By combining image and diagnostic parameters, the machine decision diagnosis auxiliary algorithm is established. Experimental result shows that the accuracy has reached 77% in NSCLC. Copyright © 2018 Elsevier B.V. All rights reserved.

Realization of station for testing asynchronous three-phase motors

NASA Astrophysics Data System (ADS)

Wróbel, A.; Surma, W.

2016-08-01

Nowadays, you cannot imagine the construction and operation of machines without the use of electric motors [13-15]. The proposed position is designed to allow testing of asynchronous three-phase motors. The position consists of a tested engine and the engine running as a load, both engines combined with a mechanical clutch [2]. The value of the load is recorded by measuring shaft created with Strain Gauge Bridge. This concept will allow to study the basic parameters of the engines, visualization motor parameters both vector and scalar controlled, during varying load drive system. In addition, registration during the variable physical parameters of the working electric motor, controlled by a frequency converter or controlled by a contactor will be possible. Position is designed as a teaching and research position to characterize the engines. It will be also possible selection of inverter parameters.

Multi-objective optimization model of CNC machining to minimize processing time and environmental impact

NASA Astrophysics Data System (ADS)

Hamada, Aulia; Rosyidi, Cucuk Nur; Jauhari, Wakhid Ahmad

2017-11-01

Minimizing processing time in a production system can increase the efficiency of a manufacturing company. Processing time are influenced by application of modern technology and machining parameter. Application of modern technology can be apply by use of CNC machining, one of the machining process can be done with a CNC machining is turning. However, the machining parameters not only affect the processing time but also affect the environmental impact. Hence, optimization model is needed to optimize the machining parameters to minimize the processing time and environmental impact. This research developed a multi-objective optimization to minimize the processing time and environmental impact in CNC turning process which will result in optimal decision variables of cutting speed and feed rate. Environmental impact is converted from environmental burden through the use of eco-indicator 99. The model were solved by using OptQuest optimization software from Oracle Crystal Ball.

Some aspects of precise laser machining - Part 1: Theory

NASA Astrophysics Data System (ADS)

Wyszynski, Dominik; Grabowski, Marcin; Lipiec, Piotr

2018-05-01

The paper describes the role of laser beam polarization and deflection on quality of laser beam machined parts made of difficult to cut materials (used for cutting tools). Application of efficient and precise cutting tool (laser beam) has significant impact on preparation and finishing operations of cutting tools for aviation part manufacturing. Understanding the phenomena occurring in the polarized light laser cutting gave possibility to design, build and test opto-mechanical instrumentation to control and maintain process parameters and conditions. The research was carried within INNOLOT program funded by Polish National Centre for Research and Development.

Laser beam machining of polycrystalline diamond for cutting tool manufacturing

NASA Astrophysics Data System (ADS)

Wyszyński, Dominik; Ostrowski, Robert; Zwolak, Marek; Bryk, Witold

2017-10-01

The paper concerns application of DPSS Nd: YAG 532nm pulse laser source for machining of polycrystalline WC based diamond inserts (PCD). The goal of the research was to determine optimal laser cutting parameters for cutting tool shaping. Basic criteria to reach the goal was cutting edge quality (minimalization of finishing operations), material removal rate (time and cost efficiency), choice of laser beam characteristics (polarization, power, focused beam diameter). The research was planned and realised and analysed according to design of experiment rules (DOE). The analysis of the cutting edge was prepared with use of Alicona Infinite Focus measurement system.

Quantum cloning disturbed by thermal Davies environment

NASA Astrophysics Data System (ADS)

Dajka, Jerzy; Łuczka, Jerzy

2016-06-01

A network of quantum gates designed to implement universal quantum cloning machine is studied. We analyze how thermal environment coupled to auxiliary qubits, `blank paper' and `toner' required at the preparation stage of copying, modifies an output fidelity of the cloner. Thermal environment is described in terms of the Markovian Davies theory. We show that such a cloning machine is not universal any more but its output is independent of at least a part of parameters of the environment. As a case study, we consider cloning of states in a six-state cryptography's protocol. We also briefly discuss cloning of arbitrary input states.

Energy harvesting using AC machines with high effective pole count

NASA Astrophysics Data System (ADS)

Geiger, Richard Theodore

In this thesis, ways to improve the power conversion of rotating generators at low rotor speeds in energy harvesting applications were investigated. One method is to increase the pole count, which increases the generator back-emf without also increasing the I2R losses, thereby increasing both torque density and conversion efficiency. One machine topology that has a high effective pole count is a hybrid "stepper" machine. However, the large self inductance of these machines decreases their power factor and hence the maximum power that can be delivered to a load. This effect can be cancelled by the addition of capacitors in series with the stepper windings. A circuit was designed and implemented to automatically vary the series capacitance over the entire speed range investigated. The addition of the series capacitors improved the power output of the stepper machine by up to 700%. At low rotor speeds, with the addition of series capacitance, the power output of the hybrid "stepper" was more than 200% that of a similarly sized PMDC brushed motor. Finally, in this thesis a hybrid lumped parameter / finite element model was used to investigate the impact of number, shape and size of the rotor and stator teeth on machine performance. A typical off-the-shelf hybrid stepper machine has significant cogging torque by design. This cogging torque is a major problem in most small energy harvesting applications. In this thesis it was shown that the cogging and ripple torque can be dramatically reduced. These findings confirm that high-pole-count topologies, and specifically the hybrid stepper configuration, are an attractive choice for energy harvesting applications.

Design and construction of an impulse turbine

NASA Astrophysics Data System (ADS)

Hernández, E.

2013-11-01

Impulse turbine has been constructed to be used in the program of Hydraulic Machines, Faculty of Mechanical Engineering at the Universidad Pontificia Bolivariana, sede Bucaramanga. For construction of the impulse turbine (Pelton) detailed plans were drawn up taking into account the design and implementation of the fundamental equations of hydraulic turbomachinery. From the experimental data found maximum mechanical efficiency of 0.6 ± 0.03 for a water flow of 2.1 l/s. The maximum overall efficiency was 0.23 ± 0.02 for a water flow of 0.83 l/s. The design parameter used was a power of 1 kW, as flow regulator built a needle type regulator, which performed well, the model of the bucket or vane is built on a machine type CNC (Computer Numerical Control). For the construction of the impeller and blades was used aluminium because of chemical and physical characteristics and the casing was manufactured in acrylic.

Analysis of static and dynamic characteristic of spindle system and its structure optimization in camshaft grinding machine

NASA Astrophysics Data System (ADS)

Feng, Jianjun; Li, Chengzhe; Wu, Zhi

2017-08-01

As an important part of the valve opening and closing controller in engine, camshaft has high machining accuracy requirement in designing. Taking the high-speed camshaft grinder spindle system as the research object and the spindle system performance as the optimizing target, this paper firstly uses Solidworks to establish the three-dimensional finite element model (FEM) of spindle system, then conducts static analysis and the modal analysis by applying the established FEM in ANSYS Workbench, and finally uses the design optimization function of the ANSYS Workbench to optimize the structure parameter in the spindle system. The study results prove that the design of the spindle system fully meets the production requirements, and the performance of the optimized spindle system is promoted. Besides, this paper provides an analysis and optimization method for other grinder spindle systems.

Aircraft Engine Thrust Estimator Design Based on GSA-LSSVM

NASA Astrophysics Data System (ADS)

Sheng, Hanlin; Zhang, Tianhong

2017-08-01

In view of the necessity of highly precise and reliable thrust estimator to achieve direct thrust control of aircraft engine, based on support vector regression (SVR), as well as least square support vector machine (LSSVM) and a new optimization algorithm - gravitational search algorithm (GSA), by performing integrated modelling and parameter optimization, a GSA-LSSVM-based thrust estimator design solution is proposed. The results show that compared to particle swarm optimization (PSO) algorithm, GSA can find unknown optimization parameter better and enables the model developed with better prediction and generalization ability. The model can better predict aircraft engine thrust and thus fulfills the need of direct thrust control of aircraft engine.

Predictive Modeling and Optimization of Vibration-assisted AFM Tip-based Nanomachining

NASA Astrophysics Data System (ADS)

Kong, Xiangcheng

The tip-based vibration-assisted nanomachining process offers a low-cost, low-effort technique in fabricating nanometer scale 2D/3D structures in sub-100 nm regime. To understand its mechanism, as well as provide the guidelines for process planning and optimization, we have systematically studied this nanomachining technique in this work. To understand the mechanism of this nanomachining technique, we firstly analyzed the interaction between the AFM tip and the workpiece surface during the machining process. A 3D voxel-based numerical algorithm has been developed to calculate the material removal rate as well as the contact area between the AFM tip and the workpiece surface. As a critical factor to understand the mechanism of this nanomachining process, the cutting force has been analyzed and modeled. A semi-empirical model has been proposed by correlating the cutting force with the material removal rate, which was validated using experimental data from different machining conditions. With the understanding of its mechanism, we have developed guidelines for process planning of this nanomachining technique. To provide the guideline for parameter selection, the effect of machining parameters on the feature dimensions (depth and width) has been analyzed. Based on ANOVA test results, the feature width is only controlled by the XY vibration amplitude, while the feature depth is affected by several machining parameters such as setpoint force and feed rate. A semi-empirical model was first proposed to predict the machined feature depth under given machining condition. Then, to reduce the computation intensity, linear and nonlinear regression models were also proposed and validated using experimental data. Given the desired feature dimensions, feasible machining parameters could be provided using these predictive feature dimension models. As the tip wear is unavoidable during the machining process, the machining precision will gradually decrease. To maintain the machining quality, the guideline for when to change the tip should be provided. In this study, we have developed several metrics to detect tip wear, such as tip radius and the pull-off force. The effect of machining parameters on the tip wear rate has been studied using these metrics, and the machining distance before a tip must be changed has been modeled using these machining parameters. Finally, the optimization functions have been built for unit production time and unit production cost subject to realistic constraints, and the optimal machining parameters can be found by solving these functions.

Earth orbital teleoperator visual system evaluation program

NASA Technical Reports Server (NTRS)

Shields, N. L., Jr.; Kirkpatrick, M., III; Frederick, P. N.; Malone, T. B.

1975-01-01

Empirical tests of range estimation accuracy and resolution, via television, under monoptic and steroptic viewing conditions are discussed. Test data are used to derive man machine interface requirements and make design decisions for an orbital remote manipulator system. Remote manipulator system visual tasks are given and the effects of system parameters of these tasks are evaluated.

Summary of the Optics, IR, Injection, Operations, Reliability and Instrumentation Working Group

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wienands, U.; /SLAC; Funakoshi, Y.

2012-04-20

The facilities reported on are all in a fairly mature state of operation, as evidenced by the very detailed studies and correction schemes that all groups are working on. First- and higher-order aberrations are diagnosed and planned to be corrected. Very detailed beam measurements are done to get a global picture of the beam dynamics. More than other facilities the high-luminosity colliders are struggling with experimental background issues, mitigation of which is a permanent challenge. The working group dealt with a very wide rage of practical issues which limit performance of the machines and compared their techniques of operations andmore » their performance. We anticipate this to be a first attempt. In a future workshop in this series, we propose to attempt more fundamental comparisons of each machine, including design parameters. For example, DAPHNE and KEKB employ a finite crossing angle. The minimum value of {beta}*{sub y} attainable at KEKB seems to relate to this scheme. Effectiveness of compensation solenoids and turn-by-turn BPMs etc. should be examined in more detail. In the near future, CESR-C and VEPP-2000 will start their operation. We expect to hear important new experiences from these machines; in particular VEPP-2000 will be the first machine to have adopted round beams. At SLAC and KEK, next generation B Factories are being considered. It will be worthwhile to discuss the design issues of these machines based on the experiences of the existing factory machines.« less

Active chatter suppression with displacement-only measurement in turning process

NASA Astrophysics Data System (ADS)

Ma, Haifeng; Wu, Jianhua; Yang, Liuqing; Xiong, Zhenhua

2017-08-01

Regenerative chatter is a major hindrance for achieving high quality and high production rate in machining processes. Various active controllers have been proposed to mitigate chatter. However, most of existing controllers were developed on the basis of multi-states feedback of the system and state observers were usually needed. Moreover, model parameters of the machining process (mass, damping and stiffness) were required in existing active controllers. In this study, an active sliding mode controller, which employs a dynamic output feedback sliding surface for the unmatched condition and an adaptive law for disturbance estimation, is designed, analyzed, and validated for chatter suppression in turning process. Only displacement measurement is required by this approach. Other sensors and state observers are not needed. Moreover, it facilitates a rapid implementation since the designed controller is established without using model parameters of the turning process. Theoretical analysis, numerical simulations and experiments on a computer numerical control (CNC) lathe are presented. It shows that the chatter can be substantially attenuated and the chatter-free region can be significantly expanded with the presented method.

From design to manufacturing of asymmetric teeth gears using computer application

NASA Astrophysics Data System (ADS)

Suciu, F.; Dascalescu, A.; Ungureanu, M.

2017-05-01

The asymmetric cylindrical gears, with involutes teeth profiles having different base circle diameters, are nonstandard gears, used with the aim to obtain better function parameters for the active profile. We will expect that the manufacturing of these gears became possible only after the design and realization of some specific tools. The paper present how the computer aided design and applications developed in MATLAB, for obtain the geometrical parameters, in the same time for calculation some functional parameters like stress and displacements, transmission error, efficiency of the gears and the 2D models, generated with AUTOLISP applications, are used for computer aided manufacturing of asymmetric gears with standard tools. So the specific tools considered one of the disadvantages of these gears are not necessary and implicitly the expected supplementary costs are reduced. The calculus algorithm established for the asymmetric gear design application use the „direct design“ of the spur gears. This method offers the possibility of determining first the parameters of the gears, followed by the determination of the asymmetric gear rack’s parameters, based on those of the gears. Using original design method and computer applications have been determined the geometrical parameters, the 2D and 3D models of the asymmetric gears and on the base of these models have been manufacturing on CNC machine tool asymmetric gears.

The Study of the Relationship between Probabilistic Design and Axiomatic Design Methodology. Volume 2

NASA Technical Reports Server (NTRS)

Onwubiko, Chin-Yere; Onyebueke, Landon

1996-01-01

The structural design, or the design of machine elements, has been traditionally based on deterministic design methodology. The deterministic method considers all design parameters to be known with certainty. This methodology is, therefore, inadequate to design complex structures that are subjected to a variety of complex, severe loading conditions. A nonlinear behavior that is dependent on stress, stress rate, temperature, number of load cycles, and time is observed on all components subjected to complex conditions. These complex conditions introduce uncertainties; hence, the actual factor of safety margin remains unknown. In the deterministic methodology, the contingency of failure is discounted; hence, there is a use of a high factor of safety. It may be most useful in situations where the design structures are simple. The probabilistic method is concerned with the probability of non-failure performance of structures or machine elements. It is much more useful in situations where the design is characterized by complex geometry, possibility of catastrophic failure, sensitive loads and material properties. Also included: Comparative Study of the use of AGMA Geometry Factors and Probabilistic Design Methodology in the Design of Compact Spur Gear Set.

Investigation of Carbon Fiber Reinforced Plastics Machining Using 355 nm Picosecond Pulsed Laser

NASA Astrophysics Data System (ADS)

Hu, Jun; Zhu, Dezhi

2018-06-01

Carbon fiber reinforced plastics (CFRP) has been widely used in the aircraft industry and automobile industry owing to its superior properties. In this paper, a Nd:YVO4 picosecond pulsed system emitting at 355 nm has been used for CFRP machining experiments to determine optimum milling conditions. Milling parameters including laser power, milling speed and hatch distance were optimized by using box-behnken design of response surface methodology (RSM). Material removal rate was influenced by laser beam overlap ratio which affects mechanical denudation. The results in heat affected zones (HAZ) and milling quality were discussed through the machined surface observed with scanning electron microscope. A re-focusing technique based on the experiment with different focal planes was proposed and milling mechanism was also analyzed in details.

exprso: an R-package for the rapid implementation of machine learning algorithms.

PubMed

Quinn, Thomas; Tylee, Daniel; Glatt, Stephen

2016-01-01

Machine learning plays a major role in many scientific investigations. However, non-expert programmers may struggle to implement the elaborate pipelines necessary to build highly accurate and generalizable models. We introduce exprso , a new R package that is an intuitive machine learning suite designed specifically for non-expert programmers. Built initially for the classification of high-dimensional data, exprso uses an object-oriented framework to encapsulate a number of common analytical methods into a series of interchangeable modules. This includes modules for feature selection, classification, high-throughput parameter grid-searching, elaborate cross-validation schemes (e.g., Monte Carlo and nested cross-validation), ensemble classification, and prediction. In addition, exprso also supports multi-class classification (through the 1-vs-all generalization of binary classifiers) and the prediction of continuous outcomes.

Design of bearings for rotor systems based on stability

NASA Technical Reports Server (NTRS)

Dhar, D.; Barrett, L. E.; Knospe, C. R.

1992-01-01

Design of rotor systems incorporating stable behavior is of great importance to manufacturers of high speed centrifugal machinery since destabilizing mechanisms (from bearings, seals, aerodynamic cross coupling, noncolocation effects from magnetic bearings, etc.) increase with machine efficiency and power density. A new method of designing bearing parameters (stiffness and damping coefficients or coefficients of the controller transfer function) is proposed, based on a numerical search in the parameter space. The feedback control law is based on a decentralized low order controller structure, and the various design requirements are specified as constraints in the specification and parameter spaces. An algorithm is proposed for solving the problem as a sequence of constrained 'minimax' problems, with more and more eigenvalues into an acceptable region in the complex plane. The algorithm uses the method of feasible directions to solve the nonlinear constrained minimization problem at each stage. This methodology emphasizes the designer's interaction with the algorithm to generate acceptable designs by relaxing various constraints and changing initial guesses interactively. A design oriented user interface is proposed to facilitate the interaction.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Imae, T; Haga, A; Saotome, N

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 ofmore » 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.« less

Evaluation of rotor-bearing system dynamic response to unbalance. [air conditioning equipment

NASA Technical Reports Server (NTRS)

Thaller, R. E.; Ozimek, D. W.

1979-01-01

The vibration environment within air conditioner rotating machinery referred to as an air cycle machine (ACM) was investigated to effectively increase ACM reliability. To assist in the selection of design changes which would result in improved ACM performance, various design modifications were incorporated into a baseline ACM configuration. For each design change, testing was conducted with the best balance achieveable (baseline) and with various degrees of unbalance. Relationships between unbalance (within the context of design changes) and the parameters associated with design goals were established. The results of rotor dynamics tests used to establish these relationships are presented.

Machine Learning Approach to Optimizing Combined Stimulation and Medication Therapies for Parkinson's Disease.

PubMed

Shamir, Reuben R; Dolber, Trygve; Noecker, Angela M; Walter, Benjamin L; McIntyre, Cameron C

2015-01-01

Deep brain stimulation (DBS) of the subthalamic region is an established therapy for advanced Parkinson's disease (PD). However, patients often require time-intensive post-operative management to balance their coupled stimulation and medication treatments. Given the large and complex parameter space associated with this task, we propose that clinical decision support systems (CDSS) based on machine learning algorithms could assist in treatment optimization. Develop a proof-of-concept implementation of a CDSS that incorporates patient-specific details on both stimulation and medication. Clinical data from 10 patients, and 89 post-DBS surgery visits, were used to create a prototype CDSS. The system was designed to provide three key functions: (1) information retrieval; (2) visualization of treatment, and; (3) recommendation on expected effective stimulation and drug dosages, based on three machine learning methods that included support vector machines, Naïve Bayes, and random forest. Measures of medication dosages, time factors, and symptom-specific pre-operative response to levodopa were significantly correlated with post-operative outcomes (P < 0.05) and their effect on outcomes was of similar magnitude to that of DBS. Using those results, the combined machine learning algorithms were able to accurately predict 86% (12/14) of the motor improvement scores at one year after surgery. Using patient-specific details, an appropriately parameterized CDSS could help select theoretically optimal DBS parameter settings and medication dosages that have potential to improve the clinical management of PD patients. Copyright © 2015 Elsevier Inc. All rights reserved.

Effects of the sliding rehabilitation machine on balance and gait in chronic stroke patients - a controlled clinical trial.

PubMed

Byun, Seung-Deuk; Jung, Tae-Du; Kim, Chul-Hyun; Lee, Yang-Soo

2011-05-01

To investigate the effects of a sliding rehabilitation machine on balance and gait in chronic stroke patients. A non-randomized crossover design. Inpatient rehabilitation in a general hospital. Thirty patients with chronic stroke who had medium or high falling risk as determined by the Berg Balance Scale. Participants were divided into two groups and underwent four weeks of training. Group A (n = 15) underwent training with the sliding rehabilitation machine for two weeks with concurrent conventional training, followed by conventional training only for another two weeks. Group B (n = 15) underwent the same training in reverse order. The effect of the experimental period was defined as the sum of changes during training with sliding rehabilitation machine in each group, and the effect of the control period was defined as those during the conventional training only in each group. Functional Ambulation Category, Berg Balance Scale, Six-Minute Walk Test, Timed Up and Go Test, Korean Modified Barthel Index, Modified Ashworth Scale and Manual Muscle Test. Statistically significant improvements were observed in all parameters except Modified Ashworth Scale in the experimental period, but only in Six-Minute Walk Test (P < 0.01) in the control period. There were also statistically significant differences in the degree of change in all parameters in the experimental period as compared to the control period. The sliding rehabilitation machine may be a useful tool for the improvement of balance and gait abilities in chronic stroke patients.

Transfer of control system interface solutions from other domains to the thermal power industry.

PubMed

Bligård, L-O; Andersson, J; Osvalder, A-L

2012-01-01

In a thermal power plant the operators' roles are to control and monitor the process to achieve efficient and safe production. To achieve this, the human-machine interfaces have a central part. The interfaces need to be updated and upgraded together with the technical functionality to maintain optimal operation. One way of achieving relevant updates is to study other domains and see how they have solved similar issues in their design solutions. The purpose of this paper is to present how interface design solution ideas can be transferred from domains with operator control to thermal power plants. In the study 15 domains were compared using a model for categorisation of human-machine systems. The result from the domain comparison showed that nuclear power, refinery and ship engine control were most similar to thermal power control. From the findings a basic interface structure and three specific display solutions were proposed for thermal power control: process parameter overview, plant overview, and feed water view. The systematic comparison of the properties of a human-machine system allowed interface designers to find suitable objects, structures and navigation logics in a range of domains that could be transferred to the thermal power domain.

Channel Efficiency with Security Enhancement for Remote Condition Monitoring of Multi Machine System Using Hybrid Huffman Coding

NASA Astrophysics Data System (ADS)

Datta, Jinia; Chowdhuri, Sumana; Bera, Jitendranath

2016-12-01

This paper presents a novel scheme of remote condition monitoring of multi machine system where a secured and coded data of induction machine with different parameters is communicated between a state-of-the-art dedicated hardware Units (DHU) installed at the machine terminal and a centralized PC based machine data management (MDM) software. The DHUs are built for acquisition of different parameters from the respective machines, and hence are placed at their nearby panels in order to acquire different parameters cost effectively during their running condition. The MDM software collects these data through a communication channel where all the DHUs are networked using RS485 protocol. Before transmitting, the parameter's related data is modified with the adoption of differential pulse coded modulation (DPCM) and Huffman coding technique. It is further encrypted with a private key where different keys are used for different DHUs. In this way a data security scheme is adopted during its passage through the communication channel in order to avoid any third party attack into the channel. The hybrid mode of DPCM and Huffman coding is chosen to reduce the data packet length. A MATLAB based simulation and its practical implementation using DHUs at three machine terminals (one healthy three phase, one healthy single phase and one faulty three phase machine) proves its efficacy and usefulness for condition based maintenance of multi machine system. The data at the central control room are decrypted and decoded using MDM software. In this work it is observed that Chanel efficiency with respect to different parameter measurements has been increased very much.

A comparative study of electrochemical machining process parameters by using GA and Taguchi method

NASA Astrophysics Data System (ADS)

Soni, S. K.; Thomas, B.

2017-11-01

In electrochemical machining quality of machined surface strongly depend on the selection of optimal parameter settings. This work deals with the application of Taguchi method and genetic algorithm using MATLAB to maximize the metal removal rate and minimize the surface roughness and overcut. In this paper a comparative study is presented for drilling of LM6 AL/B4C composites by comparing the significant impact of numerous machining process parameters such as, electrolyte concentration (g/l),machining voltage (v),frequency (hz) on the response parameters (surface roughness, material removal rate and over cut). Taguchi L27 orthogonal array was chosen in Minitab 17 software, for the investigation of experimental results and also multiobjective optimization done by genetic algorithm is employed by using MATLAB. After obtaining optimized results from Taguchi method and genetic algorithm, a comparative results are presented.

On the bistable zone of milling processes

PubMed Central

Dombovari, Zoltan; Stepan, Gabor

2015-01-01

A modal-based model of milling machine tools subjected to time-periodic nonlinear cutting forces is introduced. The model describes the phenomenon of bistability for certain cutting parameters. In engineering, these parameter domains are referred to as unsafe zones, where steady-state milling may switch to chatter for certain perturbations. In mathematical terms, these are the parameter domains where the periodic solution of the corresponding nonlinear, time-periodic delay differential equation is linearly stable, but its domain of attraction is limited due to the existence of an unstable quasi-periodic solution emerging from a secondary Hopf bifurcation. A semi-numerical method is presented to identify the borders of these bistable zones by tracking the motion of the milling tool edges as they might leave the surface of the workpiece during the cutting operation. This requires the tracking of unstable quasi-periodic solutions and the checking of their grazing to a time-periodic switching surface in the infinite-dimensional phase space. As the parameters of the linear structural behaviour of the tool/machine tool system can be obtained by means of standard modal testing, the developed numerical algorithm provides efficient support for the design of milling processes with quick estimates of those parameter domains where chatter can still appear in spite of setting the parameters into linearly stable domains. PMID:26303918

Modeling and simulation of five-axis virtual machine based on NX

NASA Astrophysics Data System (ADS)

Li, Xiaoda; Zhan, Xianghui

2018-04-01

Virtual technology in the machinery manufacturing industry has shown the role of growing. In this paper, the Siemens NX software is used to model the virtual CNC machine tool, and the parameters of the virtual machine are defined according to the actual parameters of the machine tool so that the virtual simulation can be carried out without loss of the accuracy of the simulation. How to use the machine builder of the CAM module to define the kinematic chain and machine components of the machine is described. The simulation of virtual machine can provide alarm information of tool collision and over cutting during the process to users, and can evaluate and forecast the rationality of the technological process.

Modeling and Analysis of High Torque Density Transverse Flux Machines for Direct-Drive Applications

NASA Astrophysics Data System (ADS)

Hasan, Iftekhar

Commercially available permanent magnet synchronous machines (PMSM) typically use rare-earth-based permanent magnets (PM). However, volatility and uncertainty associated with the supply and cost of rare-earth magnets have caused a push for increased research into the development of non-rare-earth based PM machines and reluctance machines. Compared to other PMSM topologies, the Transverse Flux Machine (TFM) is a promising candidate to get higher torque densities at low speed for direct-drive applications, using non-rare-earth based PMs. The TFMs can be designed with a very small pole pitch which allows them to attain higher force density than conventional radial flux machines (RFM) and axial flux machines (AFM). This dissertation presents the modeling, electromagnetic design, vibration analysis, and prototype development of a novel non-rare-earth based PM-TFM for a direct-drive wind turbine application. The proposed TFM addresses the issues of low power factor, cogging torque, and torque ripple during the electromagnetic design phase. An improved Magnetic Equivalent Circuit (MEC) based analytical model was developed as an alternative to the time-consuming 3D Finite Element Analysis (FEA) for faster electromagnetic analysis of the TFM. The accuracy and reliability of the MEC model were verified, both with 3D-FEA and experimental results. The improved MEC model was integrated with a Particle Swarm Optimization (PSO) algorithm to further enhance the capability of the analytical tool for performing rigorous optimization of performance-sensitive machine design parameters to extract the highest torque density for rated speed. A novel concept of integrating the rotary transformer within the proposed TFM design was explored to completely eliminate the use of magnets from the TFM. While keeping the same machine envelope, and without changing the stator or rotor cores, the primary and secondary of a rotary transformer were embedded into the double-sided TFM. The proposed structure allowed for improved flux-weakening capabilities of the TFM for wide speed operations. The electromagnetic design feature of stator pole shaping was used to address the issue of cogging torque and torque ripple in 3-phase TFM. The slant-pole tooth-face in the stator showed significant improvements in cogging torque and torque ripple performance during the 3-phase FEA analysis of the TFM. A detailed structural analysis for the proposed TFM was done prior to the prototype development to validate the structural integrity of the TFM design at rated and maximum speed operation. Vibration performance of the TFM was investigated to determine the structural performance of the TFM under resonance. The prototype for the proposed TFM was developed at the Alternative Energy Laboratory of the University of Akron. The working prototype is a testament to the feasibility of developing and implementing the novel TFM design proposed in this research. Experiments were performed to validate the 3D-FEA electromagnetic and vibration performance result.

Optimization of process parameters in drilling of fibre hybrid composite using Taguchi and grey relational analysis

NASA Astrophysics Data System (ADS)

Vijaya Ramnath, B.; Sharavanan, S.; Jeykrishnan, J.

2017-03-01

Nowadays quality plays a vital role in all the products. Hence, the development in manufacturing process focuses on the fabrication of composite with high dimensional accuracy and also incurring low manufacturing cost. In this work, an investigation on machining parameters has been performed on jute-flax hybrid composite. Here, the two important responses characteristics like surface roughness and material removal rate are optimized by employing 3 machining input parameters. The input variables considered are drill bit diameter, spindle speed and feed rate. Machining is done on CNC vertical drilling machine at different levels of drilling parameters. Taguchi’s L16 orthogonal array is used for optimizing individual tool parameters. Analysis Of Variance is used to find the significance of individual parameters. The simultaneous optimization of the process parameters is done by grey relational analysis. The results of this investigation shows that, spindle speed and drill bit diameter have most effect on material removal rate and surface roughness followed by feed rate.

Comparison of effects of overload on parameters and performance of samarium-cobalt and strontium-ferrite radially oriented permanent magnet brushless DC motors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Demerdash, N.A.; Nehl, T.W.; Nyamusa, T.A.

1985-08-01

Effects of high momentary overloads on the samarium-cobalt and strontium-ferrite permanent magnets and the magnetic field in electronically commutated brushless dc machines, as well as their impact on the associated machine parameters were studied. The effect of overload on the machine parameters, and subsequently on the machine system performance was also investigated. This was accomplished through the combined use of finite element analysis of the magnetic field in such machines, perturbation of the magnetic energies to determine machine inductances, and dynamic simulation of the performance of brushless dc machines, when energized from voltage source inverters. These effects were investigated throughmore » application of the above methods to two equivalent 15 hp brushless dc motors, one of which was built with samarium-cobalt magnets, while the other was built with strontium- ferrite magnets. For momentary overloads as high as 4.5 p.u. magnet flux reductions of 29% and 42% of the no load flux were obtained in the samarium-cobalt and strontiumferrite machines, respectively. Corresponding reductions in the line to line armature inductances of 52% and 46% of the no load values were reported for the samarium-cobalt and strontium-ferrite cases, respectively. The overload affected the profiles and magnitudes of armature induced back emfs. Subsequently, the effects of overload on machine parameters were found to have significant impact on the performance of the machine systems, where findings indicate that the samarium-cobalt unit is more suited for higher overload duties than the strontium-ferrite machine.« less

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

NASA Astrophysics Data System (ADS)

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.

Machining of bone: Analysis of cutting force and surface roughness by turning process.

PubMed

Noordin, M Y; Jiawkok, N; Ndaruhadi, P Y M W; Kurniawan, D

2015-11-01

There are millions of orthopedic surgeries and dental implantation procedures performed every year globally. Most of them involve machining of bones and cartilage. However, theoretical and analytical study on bone machining is lagging behind its practice and implementation. This study views bone machining as a machining process with bovine bone as the workpiece material. Turning process which makes the basis of the actually used drilling process was experimented. The focus is on evaluating the effects of three machining parameters, that is, cutting speed, feed, and depth of cut, to machining responses, that is, cutting forces and surface roughness resulted by the turning process. Response surface methodology was used to quantify the relation between the machining parameters and the machining responses. The turning process was done at various cutting speeds (29-156 m/min), depths of cut (0.03 -0.37 mm), and feeds (0.023-0.11 mm/rev). Empirical models of the resulted cutting force and surface roughness as the functions of cutting speed, depth of cut, and feed were developed. Observation using the developed empirical models found that within the range of machining parameters evaluated, the most influential machining parameter to the cutting force is depth of cut, followed by feed and cutting speed. The lowest cutting force was obtained at the lowest cutting speed, lowest depth of cut, and highest feed setting. For surface roughness, feed is the most significant machining condition, followed by cutting speed, and with depth of cut showed no effect. The finest surface finish was obtained at the lowest cutting speed and feed setting. © IMechE 2015.

Testing the quality of images for permanent magnet desktop MRI systems using specially designed phantoms.

PubMed

Qiu, Jianfeng; Wang, Guozhu; Min, Jiao; Wang, Xiaoyan; Wang, Pengcheng

2013-12-21

Our aim was to measure the performance of desktop magnetic resonance imaging (MRI) systems using specially designed phantoms, by testing imaging parameters and analysing the imaging quality. We designed multifunction phantoms with diameters of 18 and 60 mm for desktop MRI scanners in accordance with the American Association of Physicists in Medicine (AAPM) report no. 28. We scanned the phantoms with three permanent magnet 0.5 T desktop MRI systems, measured the MRI image parameters, and analysed imaging quality by comparing the data with the AAPM criteria and Chinese national standards. Image parameters included: resonance frequency, high contrast spatial resolution, low contrast object detectability, slice thickness, geometrical distortion, signal-to-noise ratio (SNR), and image uniformity. The image parameters of three desktop MRI machines could be measured using our specially designed phantoms, and most parameters were in line with MRI quality control criterion, including: resonance frequency, high contrast spatial resolution, low contrast object detectability, slice thickness, geometrical distortion, image uniformity and slice position accuracy. However, SNR was significantly lower than in some references. The imaging test and quality control are necessary for desktop MRI systems, and should be performed with the applicable phantom and corresponding standards.

Large space structures fabrication experiment. [on-orbit fabrication of graphite/thermoplastic beams

NASA Technical Reports Server (NTRS)

1978-01-01

The fabrication machine used for the rolltrusion and on-orbit forming of graphite thermoplastic (CTP) strip material into structural sections is described. The basic process was analytically developed parallel with, and integrated into the conceptual design of, a flight experiment machine for producing a continuous triangular cross section truss. The machine and its associated ancillary equipment are mounted on a Space Lab pallet. Power, thermal control, and instrumentation connections are made during ground installation. Observation, monitoring, caution and warning, and control panels and displays are installed at the payload specialist station in the orbiter. The machine is primed before flight by initiation of beam forming, to include attachment of the first set of cross members and anchoring of the diagonal cords. Control of the experiment will be from the orbiter mission specialist station. Normal operation is by automatic processing control software. Machine operating data are displayed and recorded on the ground. Data is processed and formatted to show progress of the major experiment parameters including stable operation, physical symmetry, joint integrity, and structural properties.

Characterisation of soft magnetic materials by measurement: Evaluation of uncertainties up to 1.8 T and 9 kHz

NASA Astrophysics Data System (ADS)

Elfgen, S.; Franck, D.; Hameyer, K.

2018-04-01

Magnetic measurements are indispensable for the characterization of soft magnetic material used e.g. in electrical machines. Characteristic values are used as quality control during production and for the parametrization of material models. Uncertainties and errors in the measurements are reflected directly in the parameters of the material models. This can result in over-dimensioning and inaccuracies in simulations for the design of electrical machines. Therefore, existing influencing factors in the characterization of soft magnetic materials are named and their resulting uncertainties contributions studied. The analysis of the resulting uncertainty contributions can serve the operator as additional selection criteria for different measuring sensors. The investigation is performed for measurements within and outside the currently prescribed standard, using a Single sheet tester and its impact on the identification of iron loss parameter is studied.

Synthesis and identification of parameters of regenerative device for reversing link with increasing speed

NASA Astrophysics Data System (ADS)

Dubinin, N. N.; Mikhailichenko, S. A.; Goncharov, S. I.

2018-03-01

The article shows the problem of modeling the flow of fibrous suspension in the working bodies of mixing machines. A mathematical model describing the motion of a suspension with fibrous inclusions in a wet-type disintegrator, depending on the design of the accelerating unit and the operating device is obtained.

Intelligent Machine Learning Approaches for Aerospace Applications

NASA Astrophysics Data System (ADS)

Sathyan, Anoop

Machine Learning is a type of artificial intelligence that provides machines or networks the ability to learn from data without the need to explicitly program them. There are different kinds of machine learning techniques. This thesis discusses the applications of two of these approaches: Genetic Fuzzy Logic and Convolutional Neural Networks (CNN). Fuzzy Logic System (FLS) is a powerful tool that can be used for a wide variety of applications. FLS is a universal approximator that reduces the need for complex mathematics and replaces it with expert knowledge of the system to produce an input-output mapping using If-Then rules. The expert knowledge of a system can help in obtaining the parameters for small-scale FLSs, but for larger networks we will need to use sophisticated approaches that can automatically train the network to meet the design requirements. This is where Genetic Algorithms (GA) and EVE come into the picture. Both GA and EVE can tune the FLS parameters to minimize a cost function that is designed to meet the requirements of the specific problem. EVE is an artificial intelligence developed by Psibernetix that is trained to tune large scale FLSs. The parameters of an FLS can include the membership functions and rulebase of the inherent Fuzzy Inference Systems (FISs). The main issue with using the GFS is that the number of parameters in a FIS increase exponentially with the number of inputs thus making it increasingly harder to tune them. To reduce this issue, the FLSs discussed in this thesis consist of 2-input-1-output FISs in cascade (Chapter 4) or as a layer of parallel FISs (Chapter 7). We have obtained extremely good results using GFS for different applications at a reduced computational cost compared to other algorithms that are commonly used to solve the corresponding problems. In this thesis, GFSs have been designed for controlling an inverted double pendulum, a task allocation problem of clustering targets amongst a set of UAVs, a fire detection problem and the aircraft conflict resolution problem. During the last decade, CNNs have become increasingly popular in the domain of image and speech processing. CNNs have a lot more parameters compared to GFSs that are tuned using the back-propagation algorithm. CNNs typically have hundreds of thousands or maybe millions of parameters that are tuned using common cost functions such as integral squared error, softmax loss etc. Chapter 5 discusses a classification problem to classify images as humans or not and Chapter 6 discusses a regression task using CNN for producing an approximate near-optimal route for the Traveling Salesman Problem (TSP) which is regarded as one of the most complicated decision making problem. Both the GFS and CNN are used to develop intelligent systems specific to the application providing them computational efficiency, robustness in the face of uncertainties and scalability.

Machine-Thermal Coupling Stresses Analysis of the Fin-Type Structural Thermoelectric Generator

NASA Astrophysics Data System (ADS)

Zhang, Zheng; Yue, Hao; Chen, Dongbo; Qin, Delei; Chen, Zijian

2017-05-01

The design structure and heat-transfer mechanism of a thermoelectric generator (TEG) determine its body temperature state. Thermal stress and thermal deformation generated by the temperature variation directly affect the stress state of thermoelectric modules (TEMs). Therefore, the rated temperature and pressing force of TEMs are important parameters in TEG design. Here, the relationships between structural of a fin-type TEG (FTEG) and these parameters are studied by modeling and "machine-thermal" coupling simulation. An indirect calculation method is adopted in the coupling simulation. First, numerical heat transfer calculations of a three-dimensional FTEG model are conducted according to an orthogonal simulation table. The influences of structural parameters for heat transfer in the channel and outer fin temperature distribution are analyzed. The optimal structural parameters are obtained and used to simulate temperature field of the outer fins. Second, taking the thermal calculation results as the initial condition, the thermal-solid coupling calculation is adopted. The thermal stresses of outer fin, mechanical force of spring-angle pressing mechanism, and clamping force on a TEM are analyzed. The simulation results show that the heat transfer area of the inner fin and the physical parameters of the metal materials are the keys to determining the FTEG temperature field. The pressing mechanism's mechanical force can be reduced by reducing the outer fin angle. In addition, a corrugated cooling water pipe, which has cooling and spring functionality, is conducive to establishing an adaptable clamping force to avoid the TEMs being crushed by the thermal stresses in the body.

Running accuracy analysis of a 3-RRR parallel kinematic machine considering the deformations of the links

NASA Astrophysics Data System (ADS)

Wang, Liping; Jiang, Yao; Li, Tiemin

2014-09-01

Parallel kinematic machines have drawn considerable attention and have been widely used in some special fields. However, high precision is still one of the challenges when they are used for advanced machine tools. One of the main reasons is that the kinematic chains of parallel kinematic machines are composed of elongated links that can easily suffer deformations, especially at high speeds and under heavy loads. A 3-RRR parallel kinematic machine is taken as a study object for investigating its accuracy with the consideration of the deformations of its links during the motion process. Based on the dynamic model constructed by the Newton-Euler method, all the inertia loads and constraint forces of the links are computed and their deformations are derived. Then the kinematic errors of the machine are derived with the consideration of the deformations of the links. Through further derivation, the accuracy of the machine is given in a simple explicit expression, which will be helpful to increase the calculating speed. The accuracy of this machine when following a selected circle path is simulated. The influences of magnitude of the maximum acceleration and external loads on the running accuracy of the machine are investigated. The results show that the external loads will deteriorate the accuracy of the machine tremendously when their direction coincides with the direction of the worst stiffness of the machine. The proposed method provides a solution for predicting the running accuracy of the parallel kinematic machines and can also be used in their design optimization as well as selection of suitable running parameters.

Optimization of turning process through the analytic flank wear modelling

NASA Astrophysics Data System (ADS)

Del Prete, A.; Franchi, R.; De Lorenzis, D.

2018-05-01

In the present work, the approach used for the optimization of the process capabilities for Oil&Gas components machining will be described. These components are machined by turning of stainless steel castings workpieces. For this purpose, a proper Design Of Experiments (DOE) plan has been designed and executed: as output of the experimentation, data about tool wear have been collected. The DOE has been designed starting from the cutting speed and feed values recommended by the tools manufacturer; the depth of cut parameter has been maintained as a constant. Wear data has been obtained by means the observation of the tool flank wear under an optical microscope: the data acquisition has been carried out at regular intervals of working times. Through a statistical data and regression analysis, analytical models of the flank wear and the tool life have been obtained. The optimization approach used is a multi-objective optimization, which minimizes the production time and the number of cutting tools used, under the constraint on a defined flank wear level. The technique used to solve the optimization problem is a Multi Objective Particle Swarm Optimization (MOPS). The optimization results, validated by the execution of a further experimental campaign, highlighted the reliability of the work and confirmed the usability of the optimized process parameters and the potential benefit for the company.

MRR and TWR evaluation on electrical discharge machining of Ti-6Al-4V using tungsten : copper composite electrode

NASA Astrophysics Data System (ADS)

Prasanna, J.; Rajamanickam, S.; Amith Kumar, O.; Karthick Raj, G.; Sathya Narayanan, P. V. V.

2017-05-01

In this paper Ti-6Al-4V used as workpiece material and it is keenly seen in variety of field including medical, chemical, marine, automotive, aerospace, aviation, electronic industries, nuclear reactor, consumer products etc., The conventional machining of Ti-6Al-4V is very difficult due to its distinctive properties. The Electrical Discharge Machining (EDM) is right choice of machining this material. The tungsten copper composite material is employed as tool material. The gap voltage, peak current, pulse on time and duty factor is considered as the machining parameter to analyze the machining characteristics Material Removal Rate (MRR) and Tool Wear Rate (TWR). The Taguchi method is provided to work for finding the significant parameter of EDM. It is found that for MRR significant parameters rated in the following order Gap Voltage, Pulse On-Time, Peak Current and Duty Factor. On the other hand for TWR significant parameters are listed in line of Gap Voltage, Duty Factor, Peak Current and Pulse On-Time.

Optical Coherence Tomography Machine Learning Classifiers for Glaucoma Detection: A Preliminary Study

PubMed Central

Burgansky-Eliash, Zvia; Wollstein, Gadi; Chu, Tianjiao; Ramsey, Joseph D.; Glymour, Clark; Noecker, Robert J.; Ishikawa, Hiroshi; Schuman, Joel S.

2007-01-01

Purpose Machine-learning classifiers are trained computerized systems with the ability to detect the relationship between multiple input parameters and a diagnosis. The present study investigated whether the use of machine-learning classifiers improves optical coherence tomography (OCT) glaucoma detection. Methods Forty-seven patients with glaucoma (47 eyes) and 42 healthy subjects (42 eyes) were included in this cross-sectional study. Of the glaucoma patients, 27 had early disease (visual field mean deviation [MD] ≥ −6 dB) and 20 had advanced glaucoma (MD < −6 dB). Machine-learning classifiers were trained to discriminate between glaucomatous and healthy eyes using parameters derived from OCT output. The classifiers were trained with all 38 parameters as well as with only 8 parameters that correlated best with the visual field MD. Five classifiers were tested: linear discriminant analysis, support vector machine, recursive partitioning and regression tree, generalized linear model, and generalized additive model. For the last two classifiers, a backward feature selection was used to find the minimal number of parameters that resulted in the best and most simple prediction. The cross-validated receiver operating characteristic (ROC) curve and accuracies were calculated. Results The largest area under the ROC curve (AROC) for glaucoma detection was achieved with the support vector machine using eight parameters (0.981). The sensitivity at 80% and 95% specificity was 97.9% and 92.5%, respectively. This classifier also performed best when judged by cross-validated accuracy (0.966). The best classification between early glaucoma and advanced glaucoma was obtained with the generalized additive model using only three parameters (AROC = 0.854). Conclusions Automated machine classifiers of OCT data might be useful for enhancing the utility of this technology for detecting glaucomatous abnormality. PMID:16249492

Identification of Synchronous Machine Stability - Parameters: AN On-Line Time-Domain Approach.

NASA Astrophysics Data System (ADS)

Le, Loc Xuan

1987-09-01

A time-domain modeling approach is described which enables the stability-study parameters of the synchronous machine to be determined directly from input-output data measured at the terminals of the machine operating under normal conditions. The transient responses due to system perturbations are used to identify the parameters of the equivalent circuit models. The described models are verified by comparing their responses with the machine responses generated from the transient stability models of a small three-generator multi-bus power system and of a single -machine infinite-bus power network. The least-squares method is used for the solution of the model parameters. As a precaution against ill-conditioned problems, the singular value decomposition (SVD) is employed for its inherent numerical stability. In order to identify the equivalent-circuit parameters uniquely, the solution of a linear optimization problem with non-linear constraints is required. Here, the SVD appears to offer a simple solution to this otherwise difficult problem. Furthermore, the SVD yields solutions with small bias and, therefore, physically meaningful parameters even in the presence of noise in the data. The question concerning the need for a more advanced model of the synchronous machine which describes subtransient and even sub-subtransient behavior is dealt with sensibly by the concept of condition number. The concept provides a quantitative measure for determining whether such an advanced model is indeed necessary. Finally, the recursive SVD algorithm is described for real-time parameter identification and tracking of slowly time-variant parameters. The algorithm is applied to identify the dynamic equivalent power system model.

The Effects of Operational Parameters on a Mono-wire Cutting System: Efficiency in Marble Processing

NASA Astrophysics Data System (ADS)

Yilmazkaya, Emre; Ozcelik, Yilmaz

2016-02-01

Mono-wire block cutting machines that cut with a diamond wire can be used for squaring natural stone blocks and the slab-cutting process. The efficient use of these machines reduces operating costs by ensuring less diamond wire wear and longer wire life at high speeds. The high investment costs of these machines will lead to their efficient use and reduce production costs by increasing plant efficiency. Therefore, there is a need to investigate the cutting performance parameters of mono-wire cutting machines in terms of rock properties and operating parameters. This study aims to investigate the effects of the wire rotational speed (peripheral speed) and wire descending speed (cutting speed), which are the operating parameters of a mono-wire cutting machine, on unit wear and unit energy, which are the performance parameters in mono-wire cutting. By using the obtained results, cuttability charts for each natural stone were created on the basis of unit wear and unit energy values, cutting optimizations were performed, and the relationships between some physical and mechanical properties of rocks and the optimum cutting parameters obtained as a result of the optimization were investigated.

Research on intrusion detection based on Kohonen network and support vector machine

NASA Astrophysics Data System (ADS)

Shuai, Chunyan; Yang, Hengcheng; Gong, Zeweiyi

2018-05-01

In view of the problem of low detection accuracy and the long detection time of support vector machine, which directly applied to the network intrusion detection system. Optimization of SVM parameters can greatly improve the detection accuracy, but it can not be applied to high-speed network because of the long detection time. a method based on Kohonen neural network feature selection is proposed to reduce the optimization time of support vector machine parameters. Firstly, this paper is to calculate the weights of the KDD99 network intrusion data by Kohonen network and select feature by weight. Then, after the feature selection is completed, genetic algorithm (GA) and grid search method are used for parameter optimization to find the appropriate parameters and classify them by support vector machines. By comparing experiments, it is concluded that feature selection can reduce the time of parameter optimization, which has little influence on the accuracy of classification. The experiments suggest that the support vector machine can be used in the network intrusion detection system and reduce the missing rate.

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

PubMed

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.

Editorial: Mathematical Methods and Modeling in Machine Fault Diagnosis

DOE PAGES

Yan, Ruqiang; Chen, Xuefeng; Li, Weihua; ...

2014-12-18

Modern mathematics has commonly been utilized as an effective tool to model mechanical equipment so that their dynamic characteristics can be studied analytically. This will help identify potential failures of mechanical equipment by observing change in the equipment’s dynamic parameters. On the other hand, dynamic signals are also important and provide reliable information about the equipment’s working status. Modern mathematics has also provided us with a systematic way to design and implement various signal processing methods, which are used to analyze these dynamic signals, and to enhance intrinsic signal components that are directly related to machine failures. This special issuemore » is aimed at stimulating not only new insights on mathematical methods for modeling but also recently developed signal processing methods, such as sparse decomposition with potential applications in machine fault diagnosis. Finally, the papers included in this special issue provide a glimpse into some of the research and applications in the field of machine fault diagnosis through applications of the modern mathematical methods.« less

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

PubMed Central

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

2017-01-01

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. PMID:28772565

Underground coal mine instrumentation and test

NASA Technical Reports Server (NTRS)

Burchill, R. F.; Waldron, W. D.

1976-01-01

The need to evaluate mechanical performance of mine tools and to obtain test performance data from candidate systems dictate that an engineering data recording system be built. Because of the wide range of test parameters which would be evaluated, a general purpose data gathering system was designed and assembled to permit maximum versatility. A primary objective of this program was to provide a specific operating evaluation of a longwall mining machine vibration response under normal operating conditions. A number of mines were visited and a candidate for test evaluation was selected, based upon management cooperation, machine suitability, and mine conditions. Actual mine testing took place in a West Virginia mine.

Vertical transportation systems embedded on shuffled frog leaping algorithm for manufacturing optimisation problems in industries.

PubMed

Aungkulanon, Pasura; Luangpaiboon, Pongchanun

2016-01-01

Response surface methods via the first or second order models are important in manufacturing processes. This study, however, proposes different structured mechanisms of the vertical transportation systems or VTS embedded on a shuffled frog leaping-based approach. There are three VTS scenarios, a motion reaching a normal operating velocity, and both reaching and not reaching transitional motion. These variants were performed to simultaneously inspect multiple responses affected by machining parameters in multi-pass turning processes. The numerical results of two machining optimisation problems demonstrated the high performance measures of the proposed methods, when compared to other optimisation algorithms for an actual deep cut design.

Comparative Investigation on Tool Wear during End Milling of AISI H13 Steel with Different Tool Path Strategies

NASA Astrophysics Data System (ADS)

Adesta, Erry Yulian T.; Riza, Muhammad; Avicena

2018-03-01

Tool wear prediction plays a significant role in machining industry for proper planning and control machining parameters and optimization of cutting conditions. This paper aims to investigate the effect of tool path strategies that are contour-in and zigzag tool path strategies applied on tool wear during pocket milling process. The experiments were carried out on CNC vertical machining centre by involving PVD coated carbide inserts. Cutting speed, feed rate and depth of cut were set to vary. In an experiment with three factors at three levels, Response Surface Method (RSM) design of experiment with a standard called Central Composite Design (CCD) was employed. Results obtained indicate that tool wear increases significantly at higher range of feed per tooth compared to cutting speed and depth of cut. This result of this experimental work is then proven statistically by developing empirical model. The prediction model for the response variable of tool wear for contour-in strategy developed in this research shows a good agreement with experimental work.

High Temperature Thermoplastic Additive Manufacturing Using Low-Cost, Open-Source Hardware

NASA Technical Reports Server (NTRS)

Gardner, John M.; Stelter, Christopher J.; Yashin, Edward A.; Siochi, Emilie J.

2016-01-01

Additive manufacturing (or 3D printing) via Fused Filament Fabrication (FFF), also known as Fused Deposition Modeling (FDM), is a process where material is placed in specific locations layer-by-layer to create a complete part. Printers designed for FFF build parts by extruding a thermoplastic filament from a nozzle in a predetermined path. Originally developed for commercial printers, 3D printing via FFF has become accessible to a much larger community of users since the introduction of Reprap printers. These low-cost, desktop machines are typically used to print prototype parts or novelty items. As the adoption of desktop sized 3D printers broadens, there is increased demand for these machines to produce functional parts that can withstand harsher conditions such as high temperature and mechanical loads. Materials meeting these requirements tend to possess better mechanical properties and higher glass transition temperatures (Tg), thus requiring printers with high temperature printing capability. This report outlines the problems and solutions, and includes a detailed description of the machine design, printing parameters, and processes specific to high temperature thermoplastic 3D printing.

Micro-machined resonator oscillator

DOEpatents

Koehler, D.R.; Sniegowski, J.J.; Bivens, H.M.; Wessendorf, K.O.

1994-08-16

A micro-miniature resonator-oscillator is disclosed. Due to the miniaturization of the resonator-oscillator, oscillation frequencies of one MHz and higher are utilized. A thickness-mode quartz resonator housed in a micro-machined silicon package and operated as a telemetered sensor beacon'' that is, a digital, self-powered, remote, parameter measuring-transmitter in the FM-band. The resonator design uses trapped energy principles and temperature dependence methodology through crystal orientation control, with operation in the 20--100 MHz range. High volume batch-processing manufacturing is utilized, with package and resonator assembly at the wafer level. Unique design features include squeeze-film damping for robust vibration and shock performance, capacitive coupling through micro-machined diaphragms allowing resonator excitation at the package exterior, circuit integration and extremely small (0.1 in. square) dimensioning. A family of micro-miniature sensor beacons is also disclosed with widespread applications as bio-medical sensors, vehicle status monitors and high-volume animal identification and health sensors. The sensor family allows measurement of temperatures, chemicals, acceleration and pressure. A microphone and clock realization is also available. 21 figs.

Design and analysis of a 3D-flux flux-switching permanent magnet machine with SMC cores and ferrite magnets

NASA Astrophysics Data System (ADS)

Liu, Chengcheng; Wang, Youhua; Lei, Gang; Guo, Youguang; Zhu, Jianguo

2017-05-01

Since permanent magnets (PM) are stacked between the adjacent stator teeth and there are no windings or PMs on the rotor, flux-switching permanent magnet machine (FSPMM) owns the merits of good flux concentrating and robust rotor structure. Compared with the traditional PM machines, FSPMM can provide higher torque density and better thermal dissipation ability. Combined with the soft magnetic composite (SMC) material and ferrite magnets, this paper proposes a new 3D-flux FSPMM (3DFFSPMM). The topology and operation principle are introduced. It can be found that the designed new 3DFFSPMM has many merits over than the traditional FSPMM for it can utilize the advantages of SMC material. Moreover, the PM flux of this new motor can be regulated by using the mechanical method. 3D finite element method (FEM) is used to calculate the magnetic field and parameters of the motor, such as flux density, inductance, PM flux linkage and efficiency map. The demagnetization analysis of the ferrite magnet is also addressed to ensure the safety operation of the proposed motor.

Back analysis of geomechanical parameters in underground engineering using artificial bee colony.

PubMed

Zhu, Changxing; Zhao, Hongbo; Zhao, Ming

2014-01-01

Accurate geomechanical parameters are critical in tunneling excavation, design, and supporting. In this paper, a displacements back analysis based on artificial bee colony (ABC) algorithm is proposed to identify geomechanical parameters from monitored displacements. ABC was used as global optimal algorithm to search the unknown geomechanical parameters for the problem with analytical solution. To the problem without analytical solution, optimal back analysis is time-consuming, and least square support vector machine (LSSVM) was used to build the relationship between unknown geomechanical parameters and displacement and improve the efficiency of back analysis. The proposed method was applied to a tunnel with analytical solution and a tunnel without analytical solution. The results show the proposed method is feasible.

Artificial neural networks for AC losses prediction in superconducting round filaments

NASA Astrophysics Data System (ADS)

Leclerc, J.; Makong Hell, L.; Lorin, C.; Masson, P. J.

2016-06-01

An extensive and fast method to estimate superconducting AC losses within a superconducting round filament carrying an AC current and subjected to an elliptical magnetic field (both rotating and oscillating) is presented. Elliptical fields are present in rotating machine stators and being able to accurately predict AC losses in fully superconducting machines is paramount to generating realistic machine designs. The proposed method relies on an analytical scaling law (ASL) combined with two artificial neural network (ANN) estimators taking 9 input parameters representing the superconductor, external field and transport current characteristics. The ANNs are trained with data generated by finite element (FE) computations with a commercial software (FlexPDE) based on the widely accepted H-formulation. After completion, the model is validated through comparison with additional randomly chosen data points and compared for simple field configurations to other predictive models. The loss estimation discrepancy is about 3% on average compared to the FEA analysis. The main advantages of the model compared to FE simulations is the fast computation time (few milliseconds) which allows it to be used in iterated design processes of fully superconducting machines. In addition, the proposed model provides a higher level of fidelity than the scaling laws existing in literature usually only considering pure AC field.

Finite element analysis of chip formation usingale method

NASA Astrophysics Data System (ADS)

Jayaprakash, V.

2017-05-01

In recent times, many studies made in FEM on plain isotropic metal plate formulation. The stress analysis plays the significant role in the stability of structural safety and system. The stress and distortion estimation is very helpful for designing and manufacturing product well. Usually the residual stress and plastic strain determine the fatigue life of structure, it also plays the significant role in designing and choosing material. When the load magnitude increases the crack starts to form, decreasing the work load and the residual stress reduces the damage of the metal. The manufacturing process is a key parameter in process and forming the part of any system. However, machining operation involves complex thing like hot development, material property and other estimates based on transition of the plastic strain and residual stress. The reduction of residual stress plays the complexity role in the finite element study. This paper deals with the manufacturing process with less residual stress and strain. The results shows that, by applying the ALE method in machining we can reduce the load on the work piece hence the life type of the work piece can be increased. We also investigate the cutting tool wear and there efficiency since it is a essential machine member in fabrication technology. ABAQUS platform used to solve the machining operation

Effect of at-the-source noise reduction on performance and weights of a tilt-rotor aircraft

NASA Technical Reports Server (NTRS)

Gibs, J.; Stepniewski, W. Z.; Spencer, R.

1975-01-01

Reduction of far-field acoustic signature through modification of basic design parameters (tip speed, number of blades, disc loading and rotor blade area) was examined, using a tilt-rotor flight research aircraft as a baseline configuration. Of those design parameters, tip speed appeared as the most important. Next, preliminary design of two aircraft was performed, postulating the following reduction of noise level from that of the baseline machine, at 500 feet from the spot of OGE hover. In one aircraft, the PNL was lowered by 10 PNdB and in the other, OASPL decreased by 10 dB. The resulting weight and performance penalties were examined. Then, PNL and EPNL aspects of terminal operation were compared for the baseline and quieter aircraft.

Analysis of 3D printing parameters of gears for hybrid manufacturing

NASA Astrophysics Data System (ADS)

Budzik, Grzegorz; Przeszlowski, Łukasz; Wieczorowski, Michal; Rzucidlo, Arkadiusz; Gapinski, Bartosz; Krolczyk, Grzegorz

2018-05-01

The paper deals with analysis and selection of parameters of rapid prototyping of gears by selective sintering of metal powders. Presented results show wide spectrum of application of RP systems in manufacturing processes of machine elements, basing on analysis of market in term of application of additive manufacturing technology in different sectors of industry. Considerable growth of these methods over the past years can be observed. The characteristic errors of printed model with respect to ideal one for each technique were pointed out. Special attention was paid to the method of preparation of numerical data CAD/STL/RP. Moreover the analysis of manufacturing processes of gear type elements was presented. The tested gears were modeled with different allowances for final machining and made by DMLS. Metallographic analysis and strength tests on prepared specimens were performed. The above mentioned analysis and tests were used to compare the real properties of material with the nominal ones. To improve the quality of surface after sintering the gears were subjected to final machining. The analysis of geometry of gears after hybrid manufacturing method was performed (fig.1). The manufacturing process was defined in a traditional way as well as with the aid of modern manufacturing techniques. Methodology and obtained results can be used for other machine elements than gears and constitutes the general theory of production processes in rapid prototyping methods as well as in designing and implementation of production.

Study on fibre laser machining quality of plain woven CFRP laminates

NASA Astrophysics Data System (ADS)

Li, Maojun; Li, Shuo; Yang, Xujing; Zhang, Yi; Liang, Zhichao

2018-03-01

Laser cutting is suitable for large-scale and high-efficiency production with relatively high cutting speed, while machining of CFRP composite using lasers is challenging with severe thermal damage due to different material properties and sensitivity to heat. In this paper, surface morphology of cutting plain woven carbon fibre-reinforced plastics (CFRP) by fibre laser and the influence of cutting parameters on machined quality were investigated. A full factorial experimental design was employed involving three variable factors, which included laser pulse frequency at three levels together with laser power and cutting speed at two levels. Heat-affected zone (HAZ), kerf depth and kerf angle were quantified to understand the interactions with cutting parameters. Observations of machined surface were analysed relating to various damages using optical microscope and scanning electron microscopy (SEM), which included HAZ, matrix recession, fibre protruding, striations, fibre-end swelling, collapses, cavities and delamination. Based on ANOVA analysis, it was found that both cutting speed and laser power were significant factors for HAZ and kerf depth, while laser power was the only significant factor for kerf angle. Besides, HAZ and the kerf depth showed similar sensitivity to the pulse energy and energy per unit length, which was opposite for kerf angle. This paper presented the feasibility and experimental results of cutting CFRP laminates using fibre laser, which is possibly the efficient and high-quality process to promote the development of CFRPs.

Evaluation of CFETR as a Fusion Nuclear Science Facility using multiple system codes

NASA Astrophysics Data System (ADS)

Chan, V. S.; Costley, A. E.; Wan, B. N.; Garofalo, A. M.; Leuer, J. A.

2015-02-01

This paper presents the results of a multi-system codes benchmarking study of the recently published China Fusion Engineering Test Reactor (CFETR) pre-conceptual design (Wan et al 2014 IEEE Trans. Plasma Sci. 42 495). Two system codes, General Atomics System Code (GASC) and Tokamak Energy System Code (TESC), using different methodologies to arrive at CFETR performance parameters under the same CFETR constraints show that the correlation between the physics performance and the fusion performance is consistent, and the computed parameters are in good agreement. Optimization of the first wall surface for tritium breeding and the minimization of the machine size are highly compatible. Variations of the plasma currents and profiles lead to changes in the required normalized physics performance, however, they do not significantly affect the optimized size of the machine. GASC and TESC have also been used to explore a lower aspect ratio, larger volume plasma taking advantage of the engineering flexibility in the CFETR design. Assuming the ITER steady-state scenario physics, the larger plasma together with a moderately higher BT and Ip can result in a high gain Qfus ˜ 12, Pfus ˜ 1 GW machine approaching DEMO-like performance. It is concluded that the CFETR baseline mode can meet the minimum goal of the Fusion Nuclear Science Facility (FNSF) mission and advanced physics will enable it to address comprehensively the outstanding critical technology gaps on the path to a demonstration reactor (DEMO). Before proceeding with CFETR construction steady-state operation has to be demonstrated, further development is needed to solve the divertor heat load issue, and blankets have to be designed with tritium breeding ratio (TBR) >1 as a target.

Apparatus and method for fluid analysis

DOEpatents

Wilson, Bary W.; Peters, Timothy J.; Shepard, Chester L.; Reeves, James H.

2004-11-02

The present invention is an apparatus and method for analyzing a fluid used in a machine or in an industrial process line. The apparatus has at least one meter placed proximate the machine or process line and in contact with the machine or process fluid for measuring at least one parameter related to the fluid. The at least one parameter is a standard laboratory analysis parameter. The at least one meter includes but is not limited to viscometer, element meter, optical meter, particulate meter, and combinations thereof.

An analysis of switching and non-switching slot machine player behaviour.

PubMed

Coates, Ewan; Blaszczynski, Alex

2013-12-01

Learning theory predicts that, given the repeated choice to bet between two concurrently available slot machines, gamblers will learn to bet more money on the machine with higher expected return (payback percentage) or higher win probability per spin (volatility). The purpose of this study was to investigate whether this occurs when the two machines vary orthogonally on payback percentage and volatility. The sample comprised 52 first year psychology students (mean age = 20.3 years, 20 females, 32 males) who had played a gaming machine at least once in the previous 12 months. Participants were administered a battery of questionnaires designed to assess level of knowledge on the characteristics and operation of poker machines, frequency of poker machine play in the past 12 months, personality traits of impulsivity and capacity for cognitive reflection, and gambling beliefs. For the experimental task, participants were instructed to play on two PC-simulated electronic gaming machines (EGMs or slot machines) that differed on payback percentage and volatility, with the option of freely switching between EGMs after a practice phase. Results indicated that participants were able to easily discriminate between machines and manifested a preference to play machines offering higher payback or volatility. These findings diverged from previous findings of no preference for play on higher payback/volatility machines, potentially due to of the current study's absence of the option to make multi-line and multi-credit bets. It was concluded that return rate parameters like payback percentage and volatility strongly influenced slot machine preference in the absence of betting options like multi-line bets, though more research is needed to determine the effects of such betting options on player distribution of money between multiple EGMs.

Integrating artificial and human intelligence into tablet production process.

PubMed

Gams, Matjaž; Horvat, Matej; Ožek, Matej; Luštrek, Mitja; Gradišek, Anton

2014-12-01

We developed a new machine learning-based method in order to facilitate the manufacturing processes of pharmaceutical products, such as tablets, in accordance with the Process Analytical Technology (PAT) and Quality by Design (QbD) initiatives. Our approach combines the data, available from prior production runs, with machine learning algorithms that are assisted by a human operator with expert knowledge of the production process. The process parameters encompass those that relate to the attributes of the precursor raw materials and those that relate to the manufacturing process itself. During manufacturing, our method allows production operator to inspect the impacts of various settings of process parameters within their proven acceptable range with the purpose of choosing the most promising values in advance of the actual batch manufacture. The interaction between the human operator and the artificial intelligence system provides improved performance and quality. We successfully implemented the method on data provided by a pharmaceutical company for a particular product, a tablet, under development. We tested the accuracy of the method in comparison with some other machine learning approaches. The method is especially suitable for analyzing manufacturing processes characterized by a limited amount of data.

“Investigations on the machinability of Waspaloy under dry environment”

NASA Astrophysics Data System (ADS)

Deepu, J.; Kuppan, P.; SBalan, A. S.; Oyyaravelu, R.

2016-09-01

Nickel based superalloy, Waspaloy is extensively used in gas turbine, aerospace and automobile industries because of their unique combination of properties like high strength at elevated temperatures, resistance to chemical degradation and excellent wear resistance in many hostile environments. It is considered as one of the difficult to machine superalloy due to excessive tool wear and poor surface finish. The present paper is an attempt for removing cutting fluids from turning process of Waspaloy and to make the processes environmentally safe. For this purpose, the effect of machining parameters such as cutting speed and feed rate on the cutting force, cutting temperature, surface finish and tool wear were investigated barrier. Consequently, the strength and tool wear resistance and tool life increased significantly. Response Surface Methodology (RSM) has been used for developing and analyzing a mathematical model which describes the relationship between machining parameters and output variables. Subsequently ANOVA was used to check the adequacy of the regression model as well as each machining variables. The optimal cutting parameters were determined based on multi-response optimizations by composite desirability approach in order to minimize cutting force, average surface roughness and maximum flank wear. The results obtained from the experiments shown that machining of Waspaloy using coated carbide tool with special ranges of parameters, cutting fluid could be completely removed from machining process

Design of the beryllium window for Brookhaven Linac Isotope Producer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nayak, S.; Mapes, M.; Raparia, D.

2015-11-01

In the Brookhaven Linac Isotope Producer (BLIP) beam line, there were two Beryllium (Be) windows with an air gap to separate the high vacuum upstream side from low vacuum downstream side. There had been frequent window failures in the past which affected the machine productivity and increased the radiation dose received by workers due to unplanned maintenance. To improve the window life, design of Be window is reexamined. Detailed structural and thermal simulations are carried out on Be window for different design parameters and loading conditions to come up with better design to improve the window life. The new designmore » removed the air gap and connect the both beam lines with a Be window in-between. The new design has multiple advantages such as 1) reduces the beam energy loss (because of one window with no air gap), 2) reduces air activation due to nuclear radiation and 3) increased the machine reliability as there is no direct pressure load during operation. For quick replacement of this window, an aluminum bellow coupled with load binder was designed. There hasn’t been a single window failure since the new design was implemented in 2012.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCarthy, J.M.

The theory and methodology of design of general-purpose machines that may be controlled by a computer to perform all the tasks of a set of special-purpose machines is the focus of modern machine design research. These seventeen contributions chronicle recent activity in the analysis and design of robot manipulators that are the prototype of these general-purpose machines. They focus particularly on kinematics, the geometry of rigid-body motion, which is an integral part of machine design theory. The challenges to kinematics researchers presented by general-purpose machines such as the manipulator are leading to new perspectives in the design and control ofmore » simpler machines with two, three, and more degrees of freedom. Researchers are rethinking the uses of gear trains, planar mechanisms, adjustable mechanisms, and computer controlled actuators in the design of modern machines.« less

Multi-Response Optimization of WEDM Process Parameters Using Taguchi Based Desirability Function Analysis

NASA Astrophysics Data System (ADS)

Majumder, Himadri; Maity, Kalipada

2018-03-01

Shape memory alloy has a unique capability to return to its original shape after physical deformation by applying heat or thermo-mechanical or magnetic load. In this experimental investigation, desirability function analysis (DFA), a multi-attribute decision making was utilized to find out the optimum input parameter setting during wire electrical discharge machining (WEDM) of Ni-Ti shape memory alloy. Four critical machining parameters, namely pulse on time (TON), pulse off time (TOFF), wire feed (WF) and wire tension (WT) were taken as machining inputs for the experiments to optimize three interconnected responses like cutting speed, kerf width, and surface roughness. Input parameter combination TON = 120 μs., TOFF = 55 μs., WF = 3 m/min. and WT = 8 kg-F were found to produce the optimum results. The optimum process parameters for each desired response were also attained using Taguchi’s signal-to-noise ratio. Confirmation test has been done to validate the optimum machining parameter combination which affirmed DFA was a competent approach to select optimum input parameters for the ideal response quality for WEDM of Ni-Ti shape memory alloy.

Design and cost drivers in 2-D braiding

NASA Technical Reports Server (NTRS)

Morales, Alberto

1993-01-01

Fundamentally, the braiding process is a highly efficient, low cost method for combining single yarns into circumferential shapes, as evidenced by the number of applications for continuous sleeving. However, this braiding approach cannot fully demonstrate that it can drastically reduce the cost of complex shape structural preforms. Factors such as part geometry, machine design and configuration, materials used, and operating parameters are described as key cost drivers and what is needed to minimize their effect on elevating the cost of structural braided preforms.

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

PubMed

Dong, Zhixu; Sun, Xingwei; Chen, Changzheng; Sun, Mengnan

2018-04-13

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.

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

PubMed Central

Sun, Xingwei; Chen, Changzheng; Sun, Mengnan

2018-01-01

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. PMID:29652836

Parameter optimization and stretch enhancement of AISI 316 sheet using rapid prototyping technique

NASA Astrophysics Data System (ADS)

Moayedfar, M.; Rani, A. M.; Hanaei, H.; Ahmad, A.; Tale, A.

2017-10-01

Incremental sheet forming is a flexible manufacturing process which uses the indenter point-to-point force to shape the sheet metal workpiece into manufactured parts in batch production series. However, the problem sometimes arising from this process is the low plastic point in the stress-strain diagram of the material which leads the low stretching amount before ultra-tensile strain point. Hence, a set of experiments is designed to find the optimum forming parameters in this process for optimum sheet thickness distribution while both sides of the sheet are considered for the surface quality improvement. A five-axis high-speed CNC milling machine is employed to deliver the proper motion based on the programming system while the clamping system for holding the sheet metal was a blank mould. Finally, an electron microscope and roughness machine are utilized to evaluate the surface structure of final parts, illustrate any defect may cause during the forming process and examine the roughness of the final part surface accordingly. The best interaction between parameters is obtained with the optimum values which lead the maximum sheet thickness distribution of 4.211e-01 logarithmic elongation when the depth was 24mm with respect to the design. This study demonstrates that this rapid forming method offers an alternative solution for surface quality improvement of 65% avoiding the low probability of cracks and low probability of crystal structure changes.

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

NASA Astrophysics Data System (ADS)

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.

Anechoic chamber in industrial plants. [construction materials and structural design

NASA Technical Reports Server (NTRS)

Halpert, E.; Juncu, O.; Lorian, R.; Marfievici, D.; Mararu, I.

1974-01-01

A light anechoic chamber for routine acoustical measurements in the machine building industry is reported. The outer housing of the chamber consists of modules cast in glass fiber reinforced polyester resin; the inner housing consists of pyramidal modules cut out of sound absorbing slates. The parameters of this anechoic chamber facilitate acoustical measurements according to ISO and CAEM recommendations.

Design and Mechanical Evaluation of a Capacitive Sensor-Based Indexed Platform for Verification of Portable Coordinate Measuring Instruments

PubMed Central

Avila, Agustín Brau; Mazo, Jorge Santolaria; Martín, Juan José Aguilar

2014-01-01

During the last years, the use of Portable Coordinate Measuring Machines (PCMMs) in industry has increased considerably, mostly due to their flexibility for accomplishing in-line measuring tasks as well as their reduced costs and operational advantages as compared to traditional coordinate measuring machines (CMMs). However, their operation has a significant drawback derived from the techniques applied in the verification and optimization procedures of their kinematic parameters. These techniques are based on the capture of data with the measuring instrument from a calibrated gauge object, fixed successively in various positions so that most of the instrument measuring volume is covered, which results in time-consuming, tedious and expensive verification procedures. In this work the mechanical design of an indexed metrology platform (IMP) is presented. The aim of the IMP is to increase the final accuracy and to radically simplify the calibration, identification and verification of geometrical parameter procedures of PCMMs. The IMP allows us to fix the calibrated gauge object and move the measuring instrument in such a way that it is possible to cover most of the instrument working volume, reducing the time and operator fatigue to carry out these types of procedures. PMID:24451458

Design and mechanical evaluation of a capacitive sensor-based indexed platform for verification of portable coordinate measuring instruments.

PubMed

Avila, Agustín Brau; Mazo, Jorge Santolaria; Martín, Juan José Aguilar

2014-01-02

During the last years, the use of Portable Coordinate Measuring Machines (PCMMs) in industry has increased considerably, mostly due to their flexibility for accomplishing in-line measuring tasks as well as their reduced costs and operational advantages as compared to traditional coordinate measuring machines (CMMs). However, their operation has a significant drawback derived from the techniques applied in the verification and optimization procedures of their kinematic parameters. These techniques are based on the capture of data with the measuring instrument from a calibrated gauge object, fixed successively in various positions so that most of the instrument measuring volume is covered, which results in time-consuming, tedious and expensive verification procedures. In this work the mechanical design of an indexed metrology platform (IMP) is presented. The aim of the IMP is to increase the final accuracy and to radically simplify the calibration, identification and verification of geometrical parameter procedures of PCMMs. The IMP allows us to fix the calibrated gauge object and move the measuring instrument in such a way that it is possible to cover most of the instrument working volume, reducing the time and operator fatigue to carry out these types of procedures.

Analysis of Flatness Deviations for Austenitic Stainless Steel Workpieces after Efficient Surface Machining

NASA Astrophysics Data System (ADS)

Nadolny, K.; Kapłonek, W.

2014-08-01

The following work is an analysis of flatness deviations of a workpiece made of X2CrNiMo17-12-2 austenitic stainless steel. The workpiece surface was shaped using efficient machining techniques (milling, grinding, and smoothing). After the machining was completed, all surfaces underwent stylus measurements in order to obtain surface flatness and roughness parameters. For this purpose the stylus profilometer Hommel-Tester T8000 by Hommelwerke with HommelMap software was used. The research results are presented in the form of 2D surface maps, 3D surface topographies with extracted single profiles, Abbott-Firestone curves, and graphical studies of the Sk parameters. The results of these experimental tests proved the possibility of a correlation between flatness and roughness parameters, as well as enabled an analysis of changes in these parameters from shaping and rough grinding to finished machining. The main novelty of this paper is comprehensive analysis of measurement results obtained during a three-step machining process of austenitic stainless steel. Simultaneous analysis of individual machining steps (milling, grinding, and smoothing) enabled a complementary assessment of the process of shaping the workpiece surface macro- and micro-geometry, giving special consideration to minimize the flatness deviations

Multi-objective component sizing of a power-split plug-in hybrid electric vehicle powertrain using Pareto-based natural optimization machines

NASA Astrophysics Data System (ADS)

Mozaffari, Ahmad; Vajedi, Mahyar; Chehresaz, Maryyeh; Azad, Nasser L.

2016-03-01

The urgent need to meet increasingly tight environmental regulations and new fuel economy requirements has motivated system science researchers and automotive engineers to take advantage of emerging computational techniques to further advance hybrid electric vehicle and plug-in hybrid electric vehicle (PHEV) designs. In particular, research has focused on vehicle powertrain system design optimization, to reduce the fuel consumption and total energy cost while improving the vehicle's driving performance. In this work, two different natural optimization machines, namely the synchronous self-learning Pareto strategy and the elitism non-dominated sorting genetic algorithm, are implemented for component sizing of a specific power-split PHEV platform with a Toyota plug-in Prius as the baseline vehicle. To do this, a high-fidelity model of the Toyota plug-in Prius is employed for the numerical experiments using the Autonomie simulation software. Based on the simulation results, it is demonstrated that Pareto-based algorithms can successfully optimize the design parameters of the vehicle powertrain.

Investigations of Effect of Rotary EDM Electrode on Machining Performance of Al6061 Alloy

NASA Astrophysics Data System (ADS)

Robinson Smart, D. S.; Jenish Smart, Joses; Periasamy, C.; Ratna Kumar, P. S. Samuel

2018-04-01

Electric Discharge Machining is an essential process which is being used for machining desired shape using electrical discharges which creates sparks. There will be electrodes subjected to electric voltage and which are separated by a dielectric liquid. Removing of material will be due to the continuous and rapid current discharges between two electrodes.. The spark is very carefully controlled and localized so that it only affects the surface of the material. Usually in order to prevent the defects which are arising due to the conventional machining, the Electric Discharge Machining (EDM) machining is preferred. Also intricate and complicated shapes can be machined effectively by use of Electric Discharge Machining (EDM). The EDM process usually does not affect the heat treat below the surface. This research work focus on the design and fabrication of rotary EDM tool for machining Al6061alloy and investigation of effect of rotary tool on surface finish, material removal rate and tool wear rate. Also the effect of machining parameters of EDM such as pulse on & off time, current on material Removal Rate (MRR), Surface Roughness (SR) and Electrode wear rate (EWR) have studied. Al6061 alloy can be used for marine and offshore applications by reinforcing some other elements. The investigations have revealed that MRR (material removal rate), surface roughness (Ra) have been improved with the reduction in the tool wear rate (TWR) when the tool is rotating instead of stationary. It was clear that as rotary speed of the tool is increasing the material removal rate is increasing with the reduction of surface finish and tool wear rate.

Effect of Width of Kerf on Machining Accuracy and Subsurface Layer After WEDM

NASA Astrophysics Data System (ADS)

Mouralova, K.; Kovar, J.; Klakurkova, L.; Prokes, T.

2018-02-01

Wire electrical discharge machining is an unconventional machining technology that applies physical principles to material removal. The material is removed by a series of recurring current discharges between the workpiece and the tool electrode, and a `kerf' is created between the wire and the material being machined. The width of the kerf is directly dependent not only on the diameter of the wire used, but also on the machine parameter settings and, in particular, on the set of mechanical and physical properties of the material being machined. To ensure precise machining, it is important to have the width of the kerf as small as possible. The present study deals with the evaluation of the width of the kerf for four different metallic materials (some of which were subsequently heat treated using several methods) with different machine parameter settings. The kerf is investigated on metallographic cross sections using light and electron microscopy.

Machine Learning to Differentiate Between Positive and Negative Emotions Using Pupil Diameter

PubMed Central

Babiker, Areej; Faye, Ibrahima; Prehn, Kristin; Malik, Aamir

2015-01-01

Pupil diameter (PD) has been suggested as a reliable parameter for identifying an individual’s emotional state. In this paper, we introduce a learning machine technique to detect and differentiate between positive and negative emotions. We presented 30 participants with positive and negative sound stimuli and recorded pupillary responses. The results showed a significant increase in pupil dilation during the processing of negative and positive sound stimuli with greater increase for negative stimuli. We also found a more sustained dilation for negative compared to positive stimuli at the end of the trial, which was utilized to differentiate between positive and negative emotions using a machine learning approach which gave an accuracy of 96.5% with sensitivity of 97.93% and specificity of 98%. The obtained results were validated using another dataset designed for a different study and which was recorded while 30 participants processed word pairs with positive and negative emotions. PMID:26733912

Impact of Advance Rate on Entrapment Risk of a Double-Shielded TBM in Squeezing Ground

NASA Astrophysics Data System (ADS)

Hasanpour, Rohola; Rostami, Jamal; Barla, Giovanni

2015-05-01

Shielded tunnel boring machines (TBMs) can get stuck in squeezing ground due to excessive tunnel convergence under high in situ stress. This typically coincides with extended machine stoppages, when the ground has sufficient time to undergo substantial displacements. Excessive convergence of the ground beyond the designated overboring means ground pressure against the shield and high shield frictional resistance that, in some cases, cannot be overcome by the TBM thrust system. This leads to machine entrapment in the ground, which causes significant delays and requires labor-intensive and risky operations of manual excavation to release the machine. To evaluate the impact of the time factor on the possibility of machine entrapment, a comprehensive 3D finite difference simulation of a double-shielded TBM in squeezing ground was performed. The modeling allowed for observation of the impact of the tunnel advance rate on the possibility of machine entrapment in squeezing ground. For this purpose, the model included rock mass properties related to creep in severe squeezing conditions. This paper offers an overview of the modeling results for a given set of rock mass and TBM parameters, as well as lining characteristics, including the magnitude of displacement and contact forces on shields and ground pressure on segmental lining versus time for different advance rates.

Design and analysis of a sub-aperture scanning machine for the transmittance measurements of large-aperture optical system

NASA Astrophysics Data System (ADS)

He, Yingwei; Li, Ping; Feng, Guojin; Cheng, Li; Wang, Yu; Wu, Houping; Liu, Zilong; Zheng, Chundi; Sha, Dingguo

2010-11-01

For measuring large-aperture optical system transmittance, a novel sub-aperture scanning machine with double-rotating arms (SSMDA) was designed to obtain sub-aperture beam spot. Optical system full-aperture transmittance measurements can be achieved by applying sub-aperture beam spot scanning technology. The mathematical model of the SSMDA based on a homogeneous coordinate transformation matrix is established to develop a detailed methodology for analyzing the beam spot scanning errors. The error analysis methodology considers two fundamental sources of scanning errors, namely (1) the length systematic errors and (2) the rotational systematic errors. As the systematic errors of the parameters are given beforehand, computational results of scanning errors are between -0.007~0.028mm while scanning radius is not lager than 400.000mm. The results offer theoretical and data basis to the research on transmission characteristics of large optical system.

Fabrication of cermet bearings for the control system of a high temperature lithium cooled nuclear reactor

NASA Technical Reports Server (NTRS)

Yacobucci, H. G.; Heestand, R. L.; Kizer, D. E.

1973-01-01

The techniques used to fabricate cermet bearings for the fueled control drums of a liquid metal cooled reference-design reactor concept are presented. The bearings were designed for operation in lithium for as long as 5 years at temperatures to 1205 C. Two sets of bearings were fabricated from a hafnium carbide - 8-wt. % molybdenum - 2-wt. % niobium carbide cermet, and two sets were fabricated from a hafnium nitride - 10-wt. % tungsten cermet. Procedures were developed for synthesizing the material in high purity inert-atmosphere glove boxes to minimize oxygen content in order to enhance corrosion resistance. Techniques were developed for pressing cylindrical billets to conserve materials and to reduce machining requirements. Finishing was accomplished by a combination of diamond grinding, electrodischarge machining, and diamond lapping. Samples were characterized in respect to composition, impurity level, lattice parameter, microstructure and density.

A study on the effect of tool electrode thickness on MRR, and TWR in electrical discharge turning process

NASA Astrophysics Data System (ADS)

Gohil, Vikas; Puri, YM

2018-04-01

Turning by electrical discharge machining (EDM) is an emerging area of research. Generally, wire-EDM is used in EDM turning because it is not concerned with electrode tooling cost. In EDM turning wire electrode leaves cusps on the machined surface because of its small diameters and wire breakage which greatly affect the surface finish of the machined part. Moreover, one of the limitations of the process is low machining speed as compared to constituent processes. In this study, conventional EDM was employed for turning purpose in order to generate free-form cylindrical geometries on difficult-to-cut materials. Therefore, a specially designed turning spindle was mounted on a conventional die-sinking EDM machine to rotate the work piece. A conductive preshaped strip of copper as a forming tool is fed (reciprocate) continuously against the rotating work piece; thus, a mirror image of the tool is formed on the circumference of the work piece. In this way, an axisymmetric work piece can be made with small tools. The developed process is termed as the electrical discharge turning (EDT). In the experiments, the effect of machining parameters, such as pulse-on time, peak current, gap voltage and tool thickness on the MRR, and TWR were investigated and practical machining was carried out by turning of SS-304 stainless steel work piece.

Effect of Machining Parameters on Oxidation Behavior of Mild Steel

NASA Astrophysics Data System (ADS)

Majumdar, P.; Shekhar, S.; Mondal, K.

2015-01-01

This study aims to find out a correlation between machining parameters, resultant microstructure, and isothermal oxidation behavior of lathe-machined mild steel in the temperature range of 660-710 °C. The tool rake angles "α" used were +20°, 0°, and -20°, and cutting speeds used were 41, 232, and 541 mm/s. Under isothermal conditions, non-machined and machined mild steel samples follow parabolic oxidation kinetics with activation energy of 181 and ~400 kJ/mol, respectively. Exaggerated grain growth of the machined surface was observed, whereas, the center part of the machined sample showed minimal grain growth during oxidation at higher temperatures. Grain growth on the surface was attributed to the reduction of strain energy at high temperature oxidation, which was accumulated on the sub-region of the machined surface during machining. It was also observed that characteristic surface oxide controlled the oxidation behavior of the machined samples. This study clearly demonstrates the effect of equivalent strain, roughness, and grain size due to machining, and subsequent grain growth on the oxidation behavior of the mild steel.

A Module Experimental Process System Development Unit (MEPSDU)

NASA Technical Reports Server (NTRS)

1981-01-01

The purpose of this program is to demonstrate the technical readiness of a cost effective process sequence that has the potential for the production of flat plate photovoltaic modules which met the price goal in 1986 of $.70 or less per watt peak. Program efforts included: preliminary design review, preliminary cell fabrication using the proposed process sequence, verification of sandblasting back cleanup, study of resist parameters, evaluation of pull strength of the proposed metallization, measurement of contact resistance of Electroless Ni contacts, optimization of process parameter, design of the MEPSDU module, identification and testing of insulator tapes, development of a lamination process sequence, identification, discussions, demonstrations and visits with candidate equipment vendors, evaluation of proposals for tabbing and stringing machine.

Generative Modeling for Machine Learning on the D-Wave

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thulasidasan, Sunil

These are slides on Generative Modeling for Machine Learning on the D-Wave. The following topics are detailed: generative models; Boltzmann machines: a generative model; restricted Boltzmann machines; learning parameters: RBM training; practical ways to train RBM; D-Wave as a Boltzmann sampler; mapping RBM onto the D-Wave; Chimera restricted RBM; mapping binary RBM to Ising model; experiments; data; D-Wave effective temperature, parameters noise, etc.; experiments: contrastive divergence (CD) 1 step; after 50 steps of CD; after 100 steps of CD; D-Wave (experiments 1, 2, 3); D-Wave observations.

Upgrading the fuel-handling machine of the Novovoronezh nuclear power plant unit no. 5

NASA Astrophysics Data System (ADS)

Terekhov, D. V.; Dunaev, V. I.

2014-02-01

The calculation of safety parameters was carried out in the process of upgrading the fuel-handling machine (FHM) of the Novovoronezh nuclear power plant (NPP) unit no. 5 based on the results of quantitative safety analysis of nuclear fuel transfer operations using a dynamic logical-and-probabilistic model of the processing procedure. Specific engineering and design concepts that made it possible to reduce the probability of damaging the fuel assemblies (FAs) when performing various technological operations by an order of magnitude and introduce more flexible algorithms into the modernized FHM control system were developed. The results of pilot operation during two refueling campaigns prove that the total reactor shutdown time is lowered.

A Mechanical Principle for Acquisition of useful Power on a Celestial Body Through Utilisation of its Planetary Precession

NASA Astrophysics Data System (ADS)

Vulkov, K.

In consequence of the phenomenon of planetary precession there emerges a possibility for acquisition of power through utilisation of the rotary motions in the universe. The idea is to acquire useful power on the working shaft of a properly designed machine installed on a celestial body (planet), at the expense of the motional energy of the latter. Strange as it may appear, this is possible if only the regulation of the machine be brought in line with the parameters of the precession. The principle of action of such a planetary engine, including an energy balance, is put forward in the present paper.

A method to identify the main mode of machine tool under operating conditions

NASA Astrophysics Data System (ADS)

Wang, Daming; Pan, Yabing

2017-04-01

The identification of the modal parameters under experimental conditions is the most common procedure when solving the problem of machine tool structure vibration. However, the influence of each mode on the machine tool vibration in real working conditions remains unknown. In fact, the contributions each mode makes to the machine tool vibration during machining process are different. In this article, an active excitation modal analysis is applied to identify the modal parameters in operational condition, and the Operating Deflection Shapes (ODS) in frequencies of high level vibration that affect the quality of machining in real working conditions are obtained. Then, the ODS is decomposed by the mode shapes which are identified in operational conditions. So, the contributions each mode makes to machine tool vibration during machining process are got by decomposition coefficients. From the previous steps, we can find out the main modes which effect the machine tool more significantly in working conditions. This method was also verified to be effective by experiments.

On the decomposition of synchronous state mechines using sequence invariant state machines

NASA Technical Reports Server (NTRS)

Hebbalalu, K.; Whitaker, S.; Cameron, K.

1992-01-01

This paper presents a few techniques for the decomposition of Synchronous State Machines of medium to large sizes into smaller component machines. The methods are based on the nature of the transitions and sequences of states in the machine and on the number and variety of inputs to the machine. The results of the decomposition, and of using the Sequence Invariant State Machine (SISM) Design Technique for generating the component machines, include great ease and quickness in the design and implementation processes. Furthermore, there is increased flexibility in making modifications to the original design leading to negligible re-design time.

Design Control Systems of Human Machine Interface in the NTVS-2894 Seat Grinder Machine to Increase the Productivity

NASA Astrophysics Data System (ADS)

Ardi, S.; Ardyansyah, D.

2018-02-01

In the Manufacturing of automotive spare parts, increased sales of vehicles is resulted in increased demand for production of engine valve of the customer. To meet customer demand, we carry out improvement and overhaul of the NTVS-2894 seat grinder machine on a machining line. NTVS-2894 seat grinder machine has been decreased machine productivity, the amount of trouble, and the amount of downtime. To overcome these problems on overhaul the NTVS-2984 seat grinder machine include mechanical and programs, is to do the design and manufacture of HMI (Human Machine Interface) GP-4501T program. Because of the time prior to the overhaul, NTVS-2894 seat grinder machine does not have a backup HMI (Human Machine Interface) program. The goal of the design and manufacture in this program is to improve the achievement of production, and allows an operator to operate beside it easier to troubleshoot the NTVS-2894 seat grinder machine thereby reducing downtime on the NTVS-2894 seat grinder machine. The results after the design are HMI program successfully made it back, machine productivity increased by 34.8%, the amount of trouble, and downtime decreased 40% decrease from 3,160 minutes to 1,700 minutes. The implication of our design, it could facilitate the operator in operating machine and the technician easer to maintain and do the troubleshooting the machine problems.

A Real-Time Apple Grading System Using Multicolor Space

PubMed Central

2014-01-01

This study was focused on the multicolor space which provides a better specification of the color and size of the apple in an image. In the study, a real-time machine vision system classifying apples into four categories with respect to color and size was designed. In the analysis, different color spaces were used. As a result, 97% identification success for the red fields of the apple was obtained depending on the values of the parameter “a” of CIE L*a*b*color space. Similarly, 94% identification success for the yellow fields was obtained depending on the values of the parameter y of CIE XYZ color space. With the designed system, three kinds of apples (Golden, Starking, and Jonagold) were investigated by classifying them into four groups with respect to two parameters, color and size. Finally, 99% success rate was achieved in the analyses conducted for 595 apples. PMID:24574880

A Novel Extreme Learning Machine Classification Model for e-Nose Application Based on the Multiple Kernel Approach.

PubMed

Jian, Yulin; Huang, Daoyu; Yan, Jia; Lu, Kun; Huang, Ying; Wen, Tailai; Zeng, Tanyue; Zhong, Shijie; Xie, Qilong

2017-06-19

A novel classification model, named the quantum-behaved particle swarm optimization (QPSO)-based weighted multiple kernel extreme learning machine (QWMK-ELM), is proposed in this paper. Experimental validation is carried out with two different electronic nose (e-nose) datasets. Being different from the existing multiple kernel extreme learning machine (MK-ELM) algorithms, the combination coefficients of base kernels are regarded as external parameters of single-hidden layer feedforward neural networks (SLFNs). The combination coefficients of base kernels, the model parameters of each base kernel, and the regularization parameter are optimized by QPSO simultaneously before implementing the kernel extreme learning machine (KELM) with the composite kernel function. Four types of common single kernel functions (Gaussian kernel, polynomial kernel, sigmoid kernel, and wavelet kernel) are utilized to constitute different composite kernel functions. Moreover, the method is also compared with other existing classification methods: extreme learning machine (ELM), kernel extreme learning machine (KELM), k-nearest neighbors (KNN), support vector machine (SVM), multi-layer perceptron (MLP), radical basis function neural network (RBFNN), and probabilistic neural network (PNN). The results have demonstrated that the proposed QWMK-ELM outperforms the aforementioned methods, not only in precision, but also in efficiency for gas classification.

Automatic classification of protein structures using physicochemical parameters.

PubMed

Mohan, Abhilash; Rao, M Divya; Sunderrajan, Shruthi; Pennathur, Gautam

2014-09-01

Protein classification is the first step to functional annotation; SCOP and Pfam databases are currently the most relevant protein classification schemes. However, the disproportion in the number of three dimensional (3D) protein structures generated versus their classification into relevant superfamilies/families emphasizes the need for automated classification schemes. Predicting function of novel proteins based on sequence information alone has proven to be a major challenge. The present study focuses on the use of physicochemical parameters in conjunction with machine learning algorithms (Naive Bayes, Decision Trees, Random Forest and Support Vector Machines) to classify proteins into their respective SCOP superfamily/Pfam family, using sequence derived information. Spectrophores™, a 1D descriptor of the 3D molecular field surrounding a structure was used as a benchmark to compare the performance of the physicochemical parameters. The machine learning algorithms were modified to select features based on information gain for each SCOP superfamily/Pfam family. The effect of combining physicochemical parameters and spectrophores on classification accuracy (CA) was studied. Machine learning algorithms trained with the physicochemical parameters consistently classified SCOP superfamilies and Pfam families with a classification accuracy above 90%, while spectrophores performed with a CA of around 85%. Feature selection improved classification accuracy for both physicochemical parameters and spectrophores based machine learning algorithms. Combining both attributes resulted in a marginal loss of performance. Physicochemical parameters were able to classify proteins from both schemes with classification accuracy ranging from 90-96%. These results suggest the usefulness of this method in classifying proteins from amino acid sequences.

Influence of Cutting Parameters and Tool Wear on the Surface Integrity of Cobalt-Based Stellite 6 Alloy When Machined Under a Dry Cutting Environment

NASA Astrophysics Data System (ADS)

Yingfei, Ge; de Escalona, Patricia Muñoz; Galloway, Alexander

2017-01-01

The efficiency of a machining process can be measured by evaluating the quality of the machined surface and the tool wear rate. The research reported herein is mainly focused on the effect of cutting parameters and tool wear on the machined surface defects, surface roughness, deformation layer and residual stresses when dry milling Stellite 6, deposited by overlay on a carbon steel surface. The results showed that under the selected cutting conditions, abrasion, diffusion, peeling, chipping and breakage were the main tool wear mechanisms presented. Also the feed rate was the primary factor affecting the tool wear with an influence of 83%. With regard to the influence of cutting parameters on the surface roughness, the primary factors were feed rate and cutting speed with 57 and 38%, respectively. In addition, in general, as tool wear increased, the surface roughness increased and the deformation layer was found to be influenced more by the cutting parameters rather than the tool wear. Compressive residual stresses were observed in the un-machined surface, and when machining longer than 5 min, residual stress changed 100% from compression to tension. Finally, results showed that micro-crack initiation was the main mechanism for chip formation.

Effect of cutting parameters on surface finish and machinability of graphite reinforced Al-8011 matrix composite

NASA Astrophysics Data System (ADS)

Anil, K. C.; Vikas, M. G.; Shanmukha Teja, B.; Sreenivas Rao, K. V.

2017-04-01

Many materials such as alloys, composites find their applications on the basis of machinability, cost and availability. In the present work, graphite (Grp) reinforced Aluminium 8011 is synthesized by convention stir casting process and Surface finish & machinability of prepared composite is examined by using lathe tool dynamometer attached with BANKA Lathe by varying the machining parameters like spindle speed, Depth of cut and Feed rate in 3 levels. Also, Roughness Average (Ra) of machined surfaces is measured by using Surface Roughness Tester (Mitutoyo SJ201). From the studies it is cleared that mechanical properties of a composites increases with addition of Grp and The cutting force were decreased with the reinforcement percentage and thus increases the machinability of composites and also results in increased surface finish.

Design, Development and Analysis of Centrifugal Blower

NASA Astrophysics Data System (ADS)

Baloni, Beena Devendra; Channiwala, Salim Abbasbhai; Harsha, Sugnanam Naga Ramannath

2018-06-01

Centrifugal blowers are widely used turbomachines equipment in all kinds of modern and domestic life. Manufacturing of blowers seldom follow an optimum design solution for individual blower. Although centrifugal blowers are developed as highly efficient machines, design is still based on various empirical and semi empirical rules proposed by fan designers. There are different methodologies used to design the impeller and other components of blowers. The objective of present study is to study explicit design methodologies and tracing unified design to get better design point performance. This unified design methodology is based more on fundamental concepts and minimum assumptions. Parametric study is also carried out for the effect of design parameters on pressure ratio and their interdependency in the design. The code is developed based on a unified design using C programming. Numerical analysis is carried out to check the flow parameters inside the blower. Two blowers, one based on the present design and other on industrial design, are developed with a standard OEM blower manufacturing unit. A comparison of both designs is done based on experimental performance analysis as per IS standard. The results suggest better efficiency and more flow rate for the same pressure head in case of the present design compared with industrial one.

Productivity improvement through cycle time analysis

NASA Astrophysics Data System (ADS)

Bonal, Javier; Rios, Luis; Ortega, Carlos; Aparicio, Santiago; Fernandez, Manuel; Rosendo, Maria; Sanchez, Alejandro; Malvar, Sergio

1996-09-01

A cycle time (CT) reduction methodology has been developed in the Lucent Technology facility (former AT&T) in Madrid, Spain. It is based on a comparison of the contribution of each process step in each technology with a target generated by a cycle time model. These targeted cycle times are obtained using capacity data of the machines processing those steps, queuing theory and theory of constrains (TOC) principles (buffers to protect bottleneck and low cycle time/inventory everywhere else). Overall efficiency equipment (OEE) like analysis is done in the machine groups with major differences between their target cycle time and real values. Comparisons between the current value of the parameters that command their capacity (process times, availability, idles, reworks, etc.) and the engineering standards are done to detect the cause of exceeding their contribution to the cycle time. Several friendly and graphical tools have been developed to track and analyze those capacity parameters. Specially important have showed to be two tools: ASAP (analysis of scheduling, arrivals and performance) and performer which analyzes interrelation problems among machines procedures and direct labor. The performer is designed for a detailed and daily analysis of an isolate machine. The extensive use of this tool by the whole labor force has demonstrated impressive results in the elimination of multiple small inefficiencies with a direct positive implications on OEE. As for ASAP, it shows the lot in process/queue for different machines at the same time. ASAP is a powerful tool to analyze the product flow management and the assigned capacity for interdependent operations like the cleaning and the oxidation/diffusion. Additional tools have been developed to track, analyze and improve the process times and the availability.

Preventing chatter vibrations in heavy-duty turning operations in large horizontal lathes

NASA Astrophysics Data System (ADS)

Urbikain, G.; Campa, F.-J.; Zulaika, J.-J.; López de Lacalle, L.-N.; Alonso, M.-A.; Collado, V.

2015-03-01

Productivity and surface finish are typical user manufacturer requirements that are restrained by chatter vibrations sooner or later in every machining operation. Thus, manufacturers are interested in knowing, before building the machine, the dynamic behaviour of each machine structure with respect to another. Stability lobe graphs are the most reliable approach to analyse the dynamic performance. During heavy rough turning operations a model containing (a) several modes, or (b) modes with non-conventional (Cartesian) orientations is necessary. This work proposes two methods which are combined with multimode analysis to predict chatter in big horizontal lathes. First, a traditional single frequency model (SFM) is used. Secondly, the modern collocation method based on the Chebyshev polynomials (CCM) is alternatively studied. The models can be used to identify the machine design features limiting lathe productivity, as well as the threshold values for choosing good cutting parameters. The results have been compared with experimental tests in a horizontal turning centre. Besides the model and approach, this work offers real worthy values for big lathes, difficult to be got from literature.

Design and analysis of drum lathe for manufacturing large-scale optical microstructured surface and load characteristics of aerostatic spindle

NASA Astrophysics Data System (ADS)

Wu, Dongxu; Qiao, Zheng; Wang, Bo; Wang, Huiming; Li, Guo

2014-08-01

In this paper, a four-axis ultra-precision lathe for machining large-scale drum mould with microstructured surface is presented. Firstly, because of the large dimension and weight of drum workpiece, as well as high requirement of machining accuracy, the design guidelines and component parts of this drum lathe is introduced in detail, including control system, moving and driving components, position feedback system and so on. Additionally, the weight of drum workpiece would result in the structural deformation of this lathe, therefore, this paper analyses the effect of structural deformation on machining accuracy by means of ANSYS. The position change is approximately 16.9nm in the X-direction(sensitive direction) which could be negligible. Finally, in order to study the impact of bearing parameters on the load characteristics of aerostatic journal bearing, one of the famous computational fluid dynamics(CFD) software, FLUENT, is adopted, and a series of simulations are carried out. The result shows that the aerostatic spindle has superior performance of carrying capacity and stiffness, it is possible for this lathe to bear the weight of drum workpiece up to 1000kg since there are two aerostatic spindles in the headstock and tailstock.

Prediction of Backbreak in Open-Pit Blasting Operations Using the Machine Learning Method

NASA Astrophysics Data System (ADS)

Khandelwal, Manoj; Monjezi, M.

2013-03-01

Backbreak is an undesirable phenomenon in blasting operations. It can cause instability of mine walls, falling down of machinery, improper fragmentation, reduced efficiency of drilling, etc. The existence of various effective parameters and their unknown relationships are the main reasons for inaccuracy of the empirical models. Presently, the application of new approaches such as artificial intelligence is highly recommended. In this paper, an attempt has been made to predict backbreak in blasting operations of Soungun iron mine, Iran, incorporating rock properties and blast design parameters using the support vector machine (SVM) method. To investigate the suitability of this approach, the predictions by SVM have been compared with multivariate regression analysis (MVRA). The coefficient of determination (CoD) and the mean absolute error (MAE) were taken as performance measures. It was found that the CoD between measured and predicted backbreak was 0.987 and 0.89 by SVM and MVRA, respectively, whereas the MAE was 0.29 and 1.07 by SVM and MVRA, respectively.

Machine learning classifiers for glaucoma diagnosis based on classification of retinal nerve fibre layer thickness parameters measured by Stratus OCT.

PubMed

Bizios, Dimitrios; Heijl, Anders; Hougaard, Jesper Leth; Bengtsson, Boel

2010-02-01

To compare the performance of two machine learning classifiers (MLCs), artificial neural networks (ANNs) and support vector machines (SVMs), with input based on retinal nerve fibre layer thickness (RNFLT) measurements by optical coherence tomography (OCT), on the diagnosis of glaucoma, and to assess the effects of different input parameters. We analysed Stratus OCT data from 90 healthy persons and 62 glaucoma patients. Performance of MLCs was compared using conventional OCT RNFLT parameters plus novel parameters such as minimum RNFLT values, 10th and 90th percentiles of measured RNFLT, and transformations of A-scan measurements. For each input parameter and MLC, the area under the receiver operating characteristic curve (AROC) was calculated. There were no statistically significant differences between ANNs and SVMs. The best AROCs for both ANN (0.982, 95%CI: 0.966-0.999) and SVM (0.989, 95% CI: 0.979-1.0) were based on input of transformed A-scan measurements. Our SVM trained on this input performed better than ANNs or SVMs trained on any of the single RNFLT parameters (p < or = 0.038). The performance of ANNs and SVMs trained on minimum thickness values and the 10th and 90th percentiles were at least as good as ANNs and SVMs with input based on the conventional RNFLT parameters. No differences between ANN and SVM were observed in this study. Both MLCs performed very well, with similar diagnostic performance. Input parameters have a larger impact on diagnostic performance than the type of machine classifier. Our results suggest that parameters based on transformed A-scan thickness measurements of the RNFL processed by machine classifiers can improve OCT-based glaucoma diagnosis.

Machinability of IPS Empress 2 framework ceramic.

PubMed

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.

Machine learnt bond order potential to model metal-organic (Co-C) heterostructures.

PubMed

Narayanan, Badri; Chan, Henry; Kinaci, Alper; Sen, Fatih G; Gray, Stephen K; Chan, Maria K Y; Sankaranarayanan, Subramanian K R S

2017-11-30

A fundamental understanding of the inter-relationships between structure, morphology, atomic scale dynamics, chemistry, and physical properties of mixed metallic-covalent systems is essential to design novel functional materials for applications in flexible nano-electronics, energy storage and catalysis. To achieve such knowledge, it is imperative to develop robust and computationally efficient atomistic models that describe atomic interactions accurately within a single framework. Here, we present a unified Tersoff-Brenner type bond order potential (BOP) for a Co-C system, trained against lattice parameters, cohesive energies, equation of state, and elastic constants of different crystalline phases of cobalt as well as orthorhombic Co 2 C derived from density functional theory (DFT) calculations. The independent BOP parameters are determined using a combination of supervised machine learning (genetic algorithms) and local minimization via the simplex method. Our newly developed BOP accurately describes the structural, thermodynamic, mechanical, and surface properties of both the elemental components as well as the carbide phases, in excellent accordance with DFT calculations and experiments. Using our machine-learnt BOP potential, we performed large-scale molecular dynamics simulations to investigate the effect of metal/carbon concentration on the structure and mechanical properties of porous architectures obtained via self-assembly of cobalt nanoparticles and fullerene molecules. Such porous structures have implications in flexible electronics, where materials with high electrical conductivity and low elastic stiffness are desired. Using unsupervised machine learning (clustering), we identify the pore structure, pore-distribution, and metallic conduction pathways in self-assembled structures at different C/Co ratios. We find that as the C/Co ratio increases, the connectivity between the Co nanoparticles becomes limited, likely resulting in low electrical conductivity; on the other hand, such C-rich hybrid structures are highly flexible (i.e., low stiffness). The BOP model developed in this work is a valuable tool to investigate atomic scale processes, structure-property relationships, and temperature/pressure response of Co-C systems, as well as design organic-inorganic hybrid structures with a desired set of properties.

Computer aided design and manufacturing: analysis and development of research issues

NASA Astrophysics Data System (ADS)

Taylor, K.; Jadeja, J. C.

2005-11-01

The paper focuses on the current issues in the areas of computer aided manufacturing and design. The importance of integrating CAD and CAM is analyzed. The associated issues with the integration and recent advancements in this field have been documented. The development of methods for enhancing productivity is explored. A research experiment was conducted in the laboratories of West Virginia University with an objective to portray effects of various machining parameters on production. Graphical results and their interpretations are supplied to better realize the main purpose of the experimentation.

Design and experimental investigation of an ejector in an air-conditioning and refrigeration system

DOE Office of Scientific and Technical Information (OSTI.GOV)

AL-Khalidy, N.; Zayonia, A.

1995-12-31

This paper discusses the conservation of energy in a refrigerant ejector refrigerating machine using heat driven from the concentrator collectors. The working refrigerant was R-113. The design of an ejector operating in an air-conditioning and refrigerating system with a low thermal source (70 C to 100 C) is presented. The influence of three major parameters--boiler, condenser, and evaporator temperature--on ejector efficiency is discussed. Experimental results show that the condenser temperature is the major influence at a low evaporator temperature. The maximum ejector efficiency was 31%.

Modeling and Analysis of CNC Milling Process Parameters on Al3030 based Composite

NASA Astrophysics Data System (ADS)

Gupta, Anand; Soni, P. K.; Krishna, C. M.

2018-04-01

The machining of Al3030 based composites on Computer Numerical Control (CNC) high speed milling machine have assumed importance because of their wide application in aerospace industries, marine industries and automotive industries etc. Industries mainly focus on surface irregularities; material removal rate (MRR) and tool wear rate (TWR) which usually depends on input process parameters namely cutting speed, feed in mm/min, depth of cut and step over ratio. Many researchers have carried out researches in this area but very few have taken step over ratio or radial depth of cut also as one of the input variables. In this research work, the study of characteristics of Al3030 is carried out at high speed CNC milling machine over the speed range of 3000 to 5000 r.p.m. Step over ratio, depth of cut and feed rate are other input variables taken into consideration in this research work. A total nine experiments are conducted according to Taguchi L9 orthogonal array. The machining is carried out on high speed CNC milling machine using flat end mill of diameter 10mm. Flatness, MRR and TWR are taken as output parameters. Flatness has been measured using portable Coordinate Measuring Machine (CMM). Linear regression models have been developed using Minitab 18 software and result are validated by conducting selected additional set of experiments. Selection of input process parameters in order to get best machining outputs is the key contributions of this research work.

Development of Experimental Setup of Metal Rapid Prototyping Machine using Selective Laser Sintering Technique

NASA Astrophysics Data System (ADS)

Patil, S. N.; Mulay, A. V.; Ahuja, B. B.

2018-04-01

Unlike in the traditional manufacturing processes, additive manufacturing as rapid prototyping, allows designers to produce parts that were previously considered too complex to make economically. The shift is taking place from plastic prototype to fully functional metallic parts by direct deposition of metallic powders as produced parts can be directly used for desired purpose. This work is directed towards the development of experimental setup of metal rapid prototyping machine using selective laser sintering and studies the various parameters, which plays important role in the metal rapid prototyping using SLS technique. The machine structure in mainly divided into three main categories namely, (1) Z-movement of bed and table, (2) X-Y movement arrangement for LASER movements and (3) feeder mechanism. Z-movement of bed is controlled by using lead screw, bevel gear pair and stepper motor, which will maintain the accuracy of layer thickness. X-Y movements are controlled using timing belt and stepper motors for precise movements of LASER source. Feeder mechanism is then developed to control uniformity of layer thickness metal powder. Simultaneously, the study is carried out for selection of material. Various types of metal powders can be used for metal RP as Single metal powder, mixture of two metals powder, and combination of metal and polymer powder. Conclusion leads to use of mixture of two metals powder to minimize the problems such as, balling effect and porosity. Developed System can be validated by conducting various experiments on manufactured part to check mechanical and metallurgical properties. After studying the results of these experiments, various process parameters as LASER properties (as power, speed etc.), and material properties (as grain size and structure etc.) will be optimized. This work is mainly focused on the design and development of cost effective experimental setup of metal rapid prototyping using SLS technique which will gives the feel of metal rapid prototyping process and its important parameters.

On Docking, Scoring and Assessing Protein-DNA Complexes in a Rigid-Body Framework

PubMed Central

Parisien, Marc; Freed, Karl F.; Sosnick, Tobin R.

2012-01-01

We consider the identification of interacting protein-nucleic acid partners using the rigid body docking method FTdock, which is systematic and exhaustive in the exploration of docking conformations. The accuracy of rigid body docking methods is tested using known protein-DNA complexes for which the docked and undocked structures are both available. Additional tests with large decoy sets probe the efficacy of two published statistically derived scoring functions that contain a huge number of parameters. In contrast, we demonstrate that state-of-the-art machine learning techniques can enormously reduce the number of parameters required, thereby identifying the relevant docking features using a miniscule fraction of the number of parameters in the prior works. The present machine learning study considers a 300 dimensional vector (dependent on only 15 parameters), termed the Chemical Context Profile (CCP), where each dimension reflects a specific type of protein amino acid-nucleic acid base interaction. The CCP is designed to capture the chemical complementarities of the interface and is well suited for machine learning techniques. Our objective function is the Chemical Context Discrepancy (CCD), which is defined as the angle between the native system's CCP vector and the decoy's vector and which serves as a substitute for the more commonly used root mean squared deviation (RMSD). We demonstrate that the CCP provides a useful scoring function when certain dimensions are properly weighted. Finally, we explore how the amino acids on a protein's surface can help guide DNA binding, first through long-range interactions, followed by direct contacts, according to specific preferences for either the major or minor grooves of the DNA. PMID:22393431

Performance analysis of cutting graphite-epoxy composite using a 90,000psi abrasive waterjet

NASA Astrophysics Data System (ADS)

Choppali, Aiswarya

Graphite-epoxy composites are being widely used in many aerospace and structural applications because of their properties: which include lighter weight, higher strength to weight ratio and a greater flexibility in design. However, the inherent anisotropy of these composites makes it difficult to machine them using conventional methods. To overcome the major issues that develop with conventional machining such as fiber pull out, delamination, heat generation and high tooling costs, an effort is herein made to study abrasive waterjet machining of composites. An abrasive waterjet is used to cut 1" thick graphite epoxy composites based on baseline data obtained from the cutting of ¼" thick material. The objective of this project is to study the surface roughness of the cut surface with a focus on demonstrating the benefits of using higher pressures for cutting composites. The effects of major cutting parameters: jet pressure, traverse speed, abrasive feed rate and cutting head size are studied at different levels. Statistical analysis of the experimental data provides an understanding of the effect of the process parameters on surface roughness. Additionally, the effect of these parameters on the taper angle of the cut is studied. The data is analyzed to obtain a set of process parameters that optimize the cutting of 1" thick graphite-epoxy composite. The statistical analysis is used to validate the experimental data. Costs involved in the cutting process are investigated in term of abrasive consumed to better understand and illustrate the practical benefits of using higher pressures. It is demonstrated that, as pressure increased, ultra-high pressure waterjets produced a better surface quality at a faster traverse rate with lower costs.

Method and apparatus for monitoring machine performance

DOEpatents

Smith, Stephen F.; Castleberry, Kimberly N.

1996-01-01

Machine operating conditions can be monitored by analyzing, in either the time or frequency domain, the spectral components of the motor current. Changes in the electric background noise, induced by mechanical variations in the machine, are correlated to changes in the operating parameters of the machine.

A study of the applicability/compatibility of inertial energy storage systems to future space missions

NASA Technical Reports Server (NTRS)

Weldon, W. F.

1980-01-01

The applicability/compatibility of inertial energy storage systems like the homopolar generator (HPG) and the compensated pulsed alternator (CPA) to future space missions is explored. Areas of CPA and HPG design requiring development for space applications are identified. The manner in which acceptance parameters of the CPA and HPG scale with operating parameters of the machines are explored and the types of electrical loads which are compatible with the CPA and HPG are examined. Potential applications including the magnetoplasmadynamic (MPD) thruster, pulsed data transmission, laser ranging, welding and electromagnetic space launch are discussed.

Application de la methode de la reponse frequentielle a l'arret "SSFR", sur une machine synchrone a poles saillants de grande puissance

NASA Astrophysics Data System (ADS)

Belqorchi, Abdelghafour

Forty years after Watson and Manchur conducted the Stand-Still Frequency Response (SSFR) test on a large turbogenerator, the applicability of this technic on a powerful salient pole synchronous generator has yet to be confirmed. The scientific literature on the subject is rare and very few have attempted to compare SSFR parameter results with those deduced by classical tests. The validity of SSFR on large salient pole machines has still to be proven. The present work aims in participating to fill this knowledge gap. It can be used to build a database of measurements highly needed to draw the validity of the technic. Also, the author hopes to demonstrate the potential of SSFR model to represent the machine, not only in cases of weak disturbances but also strong ones such as instantaneous three-phase short-circuit faults. The difficulties raised by previous searchers are: The lack of accuracy in very low frequency measurements; The difficulty in rotor positioning, according to d and q axes, in case of salient pole machines; The measurement current level influence on magnetizing inductances, in axes-d and; The rotation impact on damper circuits for some rotors design. Aware of the above difficulties, the author conducted an SSFR test on a large salient pole machine (285 MVA). The generator under test has laminated non isolated rotor and an integral slot number. The damper windings in adjacent poles are connected together, via the polar core and the rotor rim. Finally, the damping circuit is unaffected by rotation. To improve the measurement accuracy, in very low frequencies, the most precise frequency response analyser available on the market was used. Besides, the frequency responses of the signals conditioning modules (i.e., isolation, amplification...) were accounted for to correct the four measured SSFR transfer functions. Immunization against noise and use of instrumentation in their optimum range, were other technics rigorously applied. Magnetizing inductances, being influenced by the measurement current magnitude, the latter was maintained constant in the range 1mHz-20Hz. Other problems such as the rotation impact on damper circuits or the difficulty of rotor positioning are eliminated or attenuated by the intrinsic characteristics of the machine. Regarding the data analysis, the Maximum Likelihood Estimation (MLE) method was used to determine the third and second order equivalent circuit from SSFR measurements. In d-axis, the approaches of adjustment to two and three transfer functions (Ld(s), sG(s) and Lafo(s)) were explored. The second order model, derived from (Ld( s) and G(s)), was used to deduce the machine standard parameters. The latter were compared with the values given by the manufacturer and by conventional on-site tests: Instantaneous three-phase short-circuit, Dalton-Cameron and the d-axis transient time constant at open stator (T'do). The comparison showed the good accuracy of SSFR values. Subsequently, a machine model was built in EMTP-RV based on SSFR standard parameters. The model was able to reproduce stator and rotor currents measured during instantaneous three-phase short-circuit test. Some adjustments, to SSFR parameters, were needed to reproduce stator voltage and rotor current acquired during load rejection d-axis test. It is worthwhile noting that the load rejection d-axis test, recently added to IEEE 115-2009 annex, must be modified to take into account the saturation and excitation impedance impact on deduced parameters. Regarding this issue, some suggestions are proposed by the author. The obtained SSFR results, contribute to raise confidence on SSFR application on large salient pole machines. In addition, it shows the aptitude of the SSFR model to represent the machine in both cases of weak and strong disturbances, at least on machines similar the one studied. Index Terms: Salient pole, frequency response, SSFR, equivalent circuit, operational inductance.

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

NASA Astrophysics Data System (ADS)

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.

Experimental investigation of the tip based micro/nano machining

NASA Astrophysics Data System (ADS)

Guo, Z.; Tian, Y.; Liu, X.; Wang, F.; Zhou, C.; Zhang, D.

2017-12-01

Based on the self-developed three dimensional micro/nano machining system, the effects of machining parameters and sample material on micro/nano machining are investigated. The micro/nano machining system is mainly composed of the probe system and micro/nano positioning stage. The former is applied to control the normal load and the latter is utilized to realize high precision motion in the xy plane. A sample examination method is firstly introduced to estimate whether the sample is placed horizontally. The machining parameters include scratching direction, speed, cycles, normal load and feed. According to the experimental results, the scratching depth is significantly affected by the normal load in all four defined scratching directions but is rarely influenced by the scratching speed. The increase of scratching cycle number can increase the scratching depth as well as smooth the groove wall. In addition, the scratching tests of silicon and copper attest that the harder material is easier to be removed. In the scratching with different feed amount, the machining results indicate that the machined depth increases as the feed reduces. Further, a cubic polynomial is used to fit the experimental results to predict the scratching depth. With the selected machining parameters of scratching direction d3/d4, scratching speed 5 μm/s and feed 0.06 μm, some more micro structures including stair, sinusoidal groove, Chinese character '田', 'TJU' and Chinese panda have been fabricated on the silicon substrate.

Improving the performance of extreme learning machine for hyperspectral image classification

NASA Astrophysics Data System (ADS)

Li, Jiaojiao; Du, Qian; Li, Wei; Li, Yunsong

2015-05-01

Extreme learning machine (ELM) and kernel ELM (KELM) can offer comparable performance as the standard powerful classifier―support vector machine (SVM), but with much lower computational cost due to extremely simple training step. However, their performance may be sensitive to several parameters, such as the number of hidden neurons. An empirical linear relationship between the number of training samples and the number of hidden neurons is proposed. Such a relationship can be easily estimated with two small training sets and extended to large training sets so as to greatly reduce computational cost. Other parameters, such as the steepness parameter in the sigmodal activation function and regularization parameter in the KELM, are also investigated. The experimental results show that classification performance is sensitive to these parameters; fortunately, simple selections will result in suboptimal performance.

Nondimensional parameter for conformal grinding: combining machine and process parameters

NASA Astrophysics Data System (ADS)

Funkenbusch, Paul D.; Takahashi, Toshio; Gracewski, Sheryl M.; Ruckman, Jeffrey L.

1999-11-01

Conformal grinding of optical materials with CNC (Computer Numerical Control) machining equipment can be used to achieve precise control over complex part configurations. However complications can arise due to the need to fabricate complex geometrical shapes at reasonable production rates. For example high machine stiffness is essential, but the need to grind 'inside' small or highly concave surfaces may require use of tooling with less than ideal stiffness characteristics. If grinding generates loads sufficient for significant tool deflection, the programmed removal depth will not be achieved. Moreover since grinding load is a function of the volumetric removal rate the amount of load deflection can vary with location on the part, potentially producing complex figure errors. In addition to machine/tool stiffness and removal rate, load generation is a function of the process parameters. For example by reducing the feed rate of the tool into the part, both the load and resultant deflection/removal error can be decreased. However this must be balanced against the need for part through put. In this paper a simple model which permits combination of machine stiffness and process parameters into a single non-dimensional parameter is adapted for a conformal grinding geometry. Errors in removal can be minimized by maintaining this parameter above a critical value. Moreover, since the value of this parameter depends on the local part geometry, it can be used to optimize process settings during grinding. For example it may be used to guide adjustment of the feed rate as a function of location on the part to eliminate figure errors while minimizing the total grinding time required.

Influence of cutting data on surface quality when machining 17-4 PH stainless steel

NASA Astrophysics Data System (ADS)

Popovici, T. D.; Dijmărescu, M. R.

2017-08-01

The aim of the research presented in this paper is to analyse the cutting data influence upon surface quality for 17-4 PH stainless steel milling machining. The cutting regime parameters considered for the experiments were established using cutting regimes from experimental researches or from industrial conditions as basis, within the recommended ranges. The experimental program structure was determined by taking into account compatibility and orthogonality conditions, minimal use of material and labour. The machined surface roughness was determined by measuring the Ra roughness parameter, followed by surface profile registration in the form of graphics which were saved on a computer with MarSurf PS1Explorer software. Based on Ra roughness parameter, maximum values were extracted from these graphics and the influence charts of the cutting regime parameters upon surface roughness were traced using Microsoft Excel software. After a thorough analysis of the resulting data, relevant conclusions were drawn, presenting the interdependence between the surface roughness of the machined 17-4 PH samples and the cutting data variation.

Determination of initial conditions for heat exchanger placed in furnace by burning pellets

NASA Astrophysics Data System (ADS)

Durčanský, Peter; Jandačka, Jozef; Kapjor, Andrej

2014-08-01

Objective of the experimental facility and subsequent measurements is generally determine whether the expected physical properties of the verification, identification of the real behavior of the proposed system, or part thereof. For the design of heat exchanger for combined energy machine is required to identify and verify a large number of parameters. One of these are the boundary conditions of heat exchanger and pellets burner.

Machining of Molybdenum by EDM-EP and EDC Processes

NASA Astrophysics Data System (ADS)

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 < 80μs at a constant pulse interval of 100μs. The finished Mometal has accomplished by selecting appropriate EP parameters such as electrolyte flow rate of 0.42m/s under EP voltage of 50V and flush time of 20 sec to remove the recast layer and craters on the surface of Mo metal. The surface roughness of machined Mo metal can be improved from Ra of 0.93μm (Rmax = 8.51μm) to 0.23μm (Rmax = 1.48μm). Machined Mo metal surface, when used as grid component in electron gun, needs to be modified by coating materials with high work function, such as silicon carbide (SiC). The main purpose of this study is to explore the electrical discharge coating (EDC) process for coating the SiC layer on 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.

Estimation and Optimization of the Parameters Preserving the Lustre of the Fabrics

NASA Astrophysics Data System (ADS)

Prodanova, Krasimira

2009-11-01

The paper discusses the optimization of the continuance of the Damp-Heating Process of a steaming iron press machine, and the preserving of the lustre of the fabrics. In order to be obtained high qualitative damp-heating processing, it is necessary to monitor parameters such as temperature, damp, and pressure during the process. The purpose of the present paper is a mathematical model to be constructed that adequately describes the technological process using multivariate data analysis. It was established that the full factorial design of type 23 is not adequate. The research has proceeded with central rotatable design of experiment. The obtained model adequately describes the technological process of damp-heating treatment in the defined factor space. The present investigation is helpful to the technological improvement and modernization in sewing companies.

Method of Individual Forecasting of Technical State of Logging Machines

NASA Astrophysics Data System (ADS)

Kozlov, V. G.; Gulevsky, V. A.; Skrypnikov, A. V.; Logoyda, V. S.; Menzhulova, A. S.

2018-03-01

Development of the model that evaluates the possibility of failure requires the knowledge of changes’ regularities of technical condition parameters of the machines in use. To study the regularities, the need to develop stochastic models that take into account physical essence of the processes of destruction of structural elements of the machines, the technology of their production, degradation and the stochastic properties of the parameters of the technical state and the conditions and modes of operation arose.

CAT-PUMA: CME Arrival Time Prediction Using Machine learning Algorithms

NASA Astrophysics Data System (ADS)

Liu, Jiajia; Ye, Yudong; Shen, Chenglong; Wang, Yuming; Erdélyi, Robert

2018-04-01

CAT-PUMA (CME Arrival Time Prediction Using Machine learning Algorithms) quickly and accurately predicts the arrival of Coronal Mass Ejections (CMEs) of CME arrival time. The software was trained via detailed analysis of CME features and solar wind parameters using 182 previously observed geo-effective partial-/full-halo CMEs and uses algorithms of the Support Vector Machine (SVM) to make its predictions, which can be made within minutes of providing the necessary input parameters of a CME.

A Novel Extreme Learning Machine Classification Model for e-Nose Application Based on the Multiple Kernel Approach

PubMed Central

Jian, Yulin; Huang, Daoyu; Yan, Jia; Lu, Kun; Huang, Ying; Wen, Tailai; Zeng, Tanyue; Zhong, Shijie; Xie, Qilong

2017-01-01

A novel classification model, named the quantum-behaved particle swarm optimization (QPSO)-based weighted multiple kernel extreme learning machine (QWMK-ELM), is proposed in this paper. Experimental validation is carried out with two different electronic nose (e-nose) datasets. Being different from the existing multiple kernel extreme learning machine (MK-ELM) algorithms, the combination coefficients of base kernels are regarded as external parameters of single-hidden layer feedforward neural networks (SLFNs). The combination coefficients of base kernels, the model parameters of each base kernel, and the regularization parameter are optimized by QPSO simultaneously before implementing the kernel extreme learning machine (KELM) with the composite kernel function. Four types of common single kernel functions (Gaussian kernel, polynomial kernel, sigmoid kernel, and wavelet kernel) are utilized to constitute different composite kernel functions. Moreover, the method is also compared with other existing classification methods: extreme learning machine (ELM), kernel extreme learning machine (KELM), k-nearest neighbors (KNN), support vector machine (SVM), multi-layer perceptron (MLP), radical basis function neural network (RBFNN), and probabilistic neural network (PNN). The results have demonstrated that the proposed QWMK-ELM outperforms the aforementioned methods, not only in precision, but also in efficiency for gas classification. PMID:28629202

Applying machine learning to identify autistic adults using imitation: An exploratory study.

PubMed

Li, Baihua; Sharma, Arjun; Meng, James; Purushwalkam, Senthil; Gowen, Emma

2017-01-01

Autism spectrum condition (ASC) is primarily diagnosed by behavioural symptoms including social, sensory and motor aspects. Although stereotyped, repetitive motor movements are considered during diagnosis, quantitative measures that identify kinematic characteristics in the movement patterns of autistic individuals are poorly studied, preventing advances in understanding the aetiology of motor impairment, or whether a wider range of motor characteristics could be used for diagnosis. The aim of this study was to investigate whether data-driven machine learning based methods could be used to address some fundamental problems with regard to identifying discriminative test conditions and kinematic parameters to classify between ASC and neurotypical controls. Data was based on a previous task where 16 ASC participants and 14 age, IQ matched controls observed then imitated a series of hand movements. 40 kinematic parameters extracted from eight imitation conditions were analysed using machine learning based methods. Two optimal imitation conditions and nine most significant kinematic parameters were identified and compared with some standard attribute evaluators. To our knowledge, this is the first attempt to apply machine learning to kinematic movement parameters measured during imitation of hand movements to investigate the identification of ASC. Although based on a small sample, the work demonstrates the feasibility of applying machine learning methods to analyse high-dimensional data and suggest the potential of machine learning for identifying kinematic biomarkers that could contribute to the diagnostic classification of autism.

Calculating Synchronous Inductive Reactances of Contactless Machines When Magnetic Circuit is Saturated and of Machines with Superconducting Excitation Windings,

DTIC Science & Technology

The work studies the effect of magnetic circuit saturation on the synchronous inductive reactance of the armature. A practical method is given for...calculating synchronized parameters in saturating synchronized machines with additional clearances and machines with superconducting excitation windings.

Task-oriented display design - Concept and example

NASA Technical Reports Server (NTRS)

Abbott, Terence S.

1989-01-01

The general topic was in the area of display design alternatives for improved man-machine performance. The intent was to define and assess a display design concept oriented toward providing this task-oriented information. The major focus of this concept deals with the processing of data into parameters that are more relevant to the task of the human operator. Closely coupled to this concept of relevant information is the form or manner in which this information is actually presented. Conventional forms of presentation are normally a direct representation of the underlying data. By providing information in a form that is more easily assimilated and understood, a reduction in human error and cognitive workload may be obtained. A description of this proposed concept with a design example is provided. The application for the example was an engine display for a generic, twin-engine civil transport aircraft. The product of this concept was evaluated against a functionally similar, traditional display. The results of this evaluation showed that a task-oriented approach to design is a viable concept with regard to reducing user error and cognitive workload. The goal of this design process, providing task-oriented information to the user, both in content and form, appears to be a feasible mechanism for increasing the overall performance of a man-machine system.

Task-oriented display design: Concept and example

NASA Technical Reports Server (NTRS)

Abbott, Terence S.

1989-01-01

The general topic was in the area of display design alternatives for improved man-machine performance. The intent was to define and assess a display design concept oriented toward providing this task-oriented information. The major focus of this concept deals with the processing of data into parameters that are more relevant to the task of the human operator. Closely coupled to this concept of relevant information is the form or manner in which this information is actually presented. Conventional forms of presentation are normally a direct representation of the underlying data. By providing information in a form that is more easily assimilated and understood, a reduction in human error and cognitive workload may be obtained. A description of this proposed concept with a design example is provided. The application for the example was an engine display for a generic, twin-engine civil transport aircraft. The product of this concept was evaluated against a functionally similar, traditional display. The results of this evaluation showed that a task-oriented approach to design is a viable concept with regard to reducing user error and cognitive workload. The goal of this design process, providing task-oriented information to the user, both in content and form, appears to be a feasible mechanism for increasing the overall performance of a man-machine system.

Warpage analysis in injection moulding process

NASA Astrophysics Data System (ADS)

Hidayah, M. H. N.; Shayfull, Z.; Nasir, S. M.; Fathullah, M.; Hazwan, M. H. M.

2017-09-01

This study was concentrated on the effects of process parameters in plastic injection moulding process towards warpage problem by using Autodesk Moldflow Insight (AMI) software for the simulation. In this study, plastic dispenser of dental floss has been analysed with thermoplastic material of Polypropylene (PP) used as the moulded material and details properties of 80 Tonne Nessei NEX 1000 injection moulding machine also has been used in this study. The variable parameters of the process are packing pressure, packing time, melt temperature and cooling time. Minimization of warpage obtained from the optimization and analysis data from the Design Expert software. Integration of Response Surface Methodology (RSM), Center Composite Design (CCD) with polynomial models that has been obtained from Design of Experiment (DOE) is the method used in this study. The results show that packing pressure is the main factor that will contribute to the formation of warpage in x-axis and y-axis. While in z-axis, the main factor is melt temperature and packing time is the less significant among the four parameters in x, y and z-axes. From optimal processing parameter, the value of warpage in x, y and z-axis have been optimised by 21.60%, 26.45% and 24.53%, respectively.

The backend design of an environmental monitoring system upon real-time prediction of groundwater level fluctuation under the hillslope.

PubMed

Lin, Hsueh-Chun; Hong, Yao-Ming; Kan, Yao-Chiang

2012-01-01

The groundwater level represents a critical factor to evaluate hillside landslides. A monitoring system upon the real-time prediction platform with online analytical functions is important to forecast the groundwater level due to instantaneously monitored data when the heavy precipitation raises the groundwater level under the hillslope and causes instability. This study is to design the backend of an environmental monitoring system with efficient algorithms for machine learning and knowledge bank for the groundwater level fluctuation prediction. A Web-based platform upon the model-view controller-based architecture is established with technology of Web services and engineering data warehouse to support online analytical process and feedback risk assessment parameters for real-time prediction. The proposed system incorporates models of hydrological computation, machine learning, Web services, and online prediction to satisfy varieties of risk assessment requirements and approaches of hazard prevention. The rainfall data monitored from the potential landslide area at Lu-Shan, Nantou and Li-Shan, Taichung, in Taiwan, are applied to examine the system design.

A Boltzmann machine for the organization of intelligent machines

NASA Technical Reports Server (NTRS)

Moed, Michael C.; Saridis, George N.

1989-01-01

In the present technological society, there is a major need to build machines that would execute intelligent tasks operating in uncertain environments with minimum interaction with a human operator. Although some designers have built smart robots, utilizing heuristic ideas, there is no systematic approach to design such machines in an engineering manner. Recently, cross-disciplinary research from the fields of computers, systems AI and information theory has served to set the foundations of the emerging area of the design of intelligent machines. Since 1977 Saridis has been developing an approach, defined as Hierarchical Intelligent Control, designed to organize, coordinate and execute anthropomorphic tasks by a machine with minimum interaction with a human operator. This approach utilizes analytical (probabilistic) models to describe and control the various functions of the intelligent machine structured by the intuitively defined principle of Increasing Precision with Decreasing Intelligence (IPDI) (Saridis 1979). This principle, even though resembles the managerial structure of organizational systems (Levis 1988), has been derived on an analytic basis by Saridis (1988). The purpose is to derive analytically a Boltzmann machine suitable for optimal connection of nodes in a neural net (Fahlman, Hinton, Sejnowski, 1985). Then this machine will serve to search for the optimal design of the organization level of an intelligent machine. In order to accomplish this, some mathematical theory of the intelligent machines will be first outlined. Then some definitions of the variables associated with the principle, like machine intelligence, machine knowledge, and precision will be made (Saridis, Valavanis 1988). Then a procedure to establish the Boltzmann machine on an analytic basis will be presented and illustrated by an example in designing the organization level of an Intelligent Machine. A new search technique, the Modified Genetic Algorithm, is presented and proved to converge to the minimum of a cost function. Finally, simulations will show the effectiveness of a variety of search techniques for the intelligent machine.

Multi-parameter monitoring of electrical machines using integrated fibre Bragg gratings

NASA Astrophysics Data System (ADS)

Fabian, Matthias; Hind, David; Gerada, Chris; Sun, Tong; Grattan, Kenneth T. V.

2017-04-01

In this paper a sensor system for multi-parameter electrical machine condition monitoring is reported. The proposed FBG-based system allows for the simultaneous monitoring of machine vibration, rotor speed and position, torque, spinning direction, temperature distribution along the stator windings and on the rotor surface as well as the stator wave frequency. This all-optical sensing solution reduces the component count of conventional sensor systems, i.e., all 48 sensing elements are contained within the machine operated by a single sensing interrogation unit. In this work, the sensing system has been successfully integrated into and tested on a permanent magnet motor prototype.

Effects of Process Parameters and Cryotreated Electrode on the Radial Overcut of Aisi 304 IN SiC Powder Mixed Edm

NASA Astrophysics Data System (ADS)

Bhaumik, Munmun; Maity, Kalipada

Powder mixed electro discharge machining (PMEDM) is further advancement of conventional electro discharge machining (EDM) where the powder particles are suspended in the dielectric medium to enhance the machining rate as well as surface finish. Cryogenic treatment is introduced in this process for improving the tool life and cutting tool properties. In the present investigation, the characterization of the cryotreated tempered electrode was performed. An attempt has been made to study the effect of cryotreated double tempered electrode on the radial overcut (ROC) when SiC powder is mixed in the kerosene dielectric during electro discharge machining of AISI 304. The process performance has been evaluated by means of ROC when peak current, pulse on time, gap voltage, duty cycle and powder concentration are considered as process parameters and machining is performed by using tungsten carbide electrodes (untreated and double tempered electrodes). A regression analysis was performed to correlate the data between the response and the process parameters. Microstructural analysis was carried out on the machined surfaces. Least radial overcut was observed for conventional EDM as compared to powder mixed EDM. Cryotreated double tempered electrode significantly reduced the radial overcut than untreated electrode.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Skochko, G.W.; Herrmann, T.P.

Axial load cycling fatigue tests of threaded fasteners are useful in determining fastener fatigue failure or design properties. By using appropriate design factors between the failure and design fatigue strengths, such tests are used to establish fatigue failure and design parameters of fasteners for axial and bending cyclic load conditions. This paper reviews the factors which influence the fatigue strength of low Alloy steel threaded fasteners, identifies those most significant to fatigue strength, and provides design guidelines based on the direct evaluation of fatigue tests of threaded fasteners. Influences on fatigue strength of thread manufacturing process (machining and rolling ofmore » threads), effect of fastener membrane and bending stresses, thread root radii, fastener sizes, fastener tensile strength, stress relaxation, mean stress, and test temperature are discussed.« less

Expanded explorations into the optimization of an energy function for protein design

PubMed Central

Huang, Yao-ming; Bystroff, Christopher

2014-01-01

Nature possesses a secret formula for the energy as a function of the structure of a protein. In protein design, approximations are made to both the structural representation of the molecule and to the form of the energy equation, such that the existence of a general energy function for proteins is by no means guaranteed. Here we present new insights towards the application of machine learning to the problem of finding a general energy function for protein design. Machine learning requires the definition of an objective function, which carries with it the implied definition of success in protein design. We explored four functions, consisting of two functional forms, each with two criteria for success. Optimization was carried out by a Monte Carlo search through the space of all variable parameters. Cross-validation of the optimized energy function against a test set gave significantly different results depending on the choice of objective function, pointing to relative correctness of the built-in assumptions. Novel energy cross-terms correct for the observed non-additivity of energy terms and an imbalance in the distribution of predicted amino acids. This paper expands on the work presented at ACM-BCB, Orlando FL , October 2012. PMID:24384706

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

PubMed

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 machining ZnO/Al2O3 ceramic.

Application of Fuzzy TOPSIS for evaluating machining techniques using sustainability metrics

NASA Astrophysics Data System (ADS)

Digalwar, Abhijeet K.

2018-04-01

Sustainable processes and techniques are getting increased attention over the last few decades due to rising concerns over the environment, improved focus on productivity and stringency in environmental as well as occupational health and safety norms. The present work analyzes the research on sustainable machining techniques and identifies techniques and parameters on which sustainability of a process is evaluated. Based on the analysis these parameters are then adopted as criteria’s to evaluate different sustainable machining techniques such as Cryogenic Machining, Dry Machining, Minimum Quantity Lubrication (MQL) and High Pressure Jet Assisted Machining (HPJAM) using a fuzzy TOPSIS framework. In order to facilitate easy arithmetic, the linguistic variables represented by fuzzy numbers are transformed into crisp numbers based on graded mean representation. Cryogenic machining was found to be the best alternative sustainable technique as per the fuzzy TOPSIS framework adopted. The paper provides a method to deal with multi criteria decision making problems in a complex and linguistic environment.

Determining the Effect of Material Hardness During the Hard Turning of AISI4340 Steel

NASA Astrophysics Data System (ADS)

Kambagowni, Venkatasubbaiah; Chitla, Raju; Challa, Suresh

2018-05-01

In the present manufacturing industries hardened steels are most widely used in the applications like tool design and mould design. It enhances the application range of hard turning of hardened steels in manufacturing industries. This study discusses the impact of workpiece hardness, feed and depth of cut on Arithmetic mean roughness (Ra), root mean square roughness (Rq), mean depth of roughness (Rz) and total roughness (Rt) during the hard turning. Experiments have been planned according to the Box-Behnken design and conducted on hardened AISI4340 steel at 45, 50 and 55 HRC with wiper ceramic cutting inserts. Cutting speed is kept constant during this study. The analysis of variance was used to determine the effects of the machining parameters. 3-D response surface plots drawn based on RSM were utilized to set up the input-output relationships. The results indicated that the feed rate has the most significant parameter for Ra, Rq and Rz and hardness has the most critical parameter for the Rt. Further, hardness shows its influence over all the surface roughness characteristics.

Design and implementation of a UNIX based distributed computing system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Love, J.S.; Michael, M.W.

1994-12-31

We have designed, implemented, and are running a corporate-wide distributed processing batch queue on a large number of networked workstations using the UNIX{reg_sign} operating system. Atlas Wireline researchers and scientists have used the system for over a year. The large increase in available computer power has greatly reduced the time required for nuclear and electromagnetic tool modeling. Use of remote distributed computing has simultaneously reduced computation costs and increased usable computer time. The system integrates equipment from different manufacturers, using various CPU architectures, distinct operating system revisions, and even multiple processors per machine. Various differences between the machines have tomore » be accounted for in the master scheduler. These differences include shells, command sets, swap spaces, memory sizes, CPU sizes, and OS revision levels. Remote processing across a network must be performed in a manner that is seamless from the users` perspective. The system currently uses IBM RISC System/6000{reg_sign}, SPARCstation{sup TM}, HP9000s700, HP9000s800, and DEC Alpha AXP{sup TM} machines. Each CPU in the network has its own speed rating, allowed working hours, and workload parameters. The system if designed so that all of the computers in the network can be optimally scheduled without adversely impacting the primary users of the machines. The increase in the total usable computational capacity by means of distributed batch computing can change corporate computing strategy. The integration of disparate computer platforms eliminates the need to buy one type of computer for computations, another for graphics, and yet another for day-to-day operations. It might be possible, for example, to meet all research and engineering computing needs with existing networked computers.« less

Fabrication of micro-lens array on convex surface by meaning of micro-milling

NASA Astrophysics Data System (ADS)

Zhang, Peng; Du, Yunlong; Wang, Bo; Shan, Debin

2014-08-01

In order to develop the application of the micro-milling technology, and to fabricate ultra-precision optical surface with complex microstructure, in this paper, the primary experimental research on micro-milling complex microstructure array is carried out. A complex microstructure array surface with vary parameters is designed, and the mathematic model of the surface is set up and simulated. For the fabrication of the designed microstructure array surface, a micro three-axis ultra-precision milling machine tool is developed, aerostatic guideway drove directly by linear motor is adopted in order to guarantee the enough stiffness of the machine, and novel numerical control strategy with linear encoders of 5nm resolution used as the feedback of the control system is employed to ensure the extremely high motion control accuracy. With the help of CAD/CAM technology, convex micro lens array on convex spherical surface with different scales on material of polyvinyl chloride (PVC) and pure copper is fabricated using micro tungsten carbide ball end milling tool based on the ultra-precision micro-milling machine. Excellent nanometer-level micro-movement performance of the axis is proved by motion control experiment. The fabrication is nearly as the same as the design, the characteristic scale of the microstructure is less than 200μm and the accuracy is better than 1μm. It prove that ultra-precision micro-milling technology based on micro ultra-precision machine tool is a suitable and optional method for micro manufacture of microstructure array surface on different kinds of materials, and with the development of micro milling cutter, ultraprecision micro-milling complex microstructure surface will be achieved in future.

Scale effects and a method for similarity evaluation in micro electrical discharge machining

NASA Astrophysics Data System (ADS)

Liu, Qingyu; Zhang, Qinhe; Wang, Kan; Zhu, Guang; Fu, Xiuzhuo; Zhang, Jianhua

2016-08-01

Electrical discharge machining(EDM) is a promising non-traditional micro machining technology that offers a vast array of applications in the manufacturing industry. However, scale effects occur when machining at the micro-scale, which can make it difficult to predict and optimize the machining performances of micro EDM. A new concept of "scale effects" in micro EDM is proposed, the scale effects can reveal the difference in machining performances between micro EDM and conventional macro EDM. Similarity theory is presented to evaluate the scale effects in micro EDM. Single factor experiments are conducted and the experimental results are analyzed by discussing the similarity difference and similarity precision. The results show that the output results of scale effects in micro EDM do not change linearly with discharge parameters. The values of similarity precision of machining time significantly increase when scaling-down the capacitance or open-circuit voltage. It is indicated that the lower the scale of the discharge parameter, the greater the deviation of non-geometrical similarity degree over geometrical similarity degree, which means that the micro EDM system with lower discharge energy experiences more scale effects. The largest similarity difference is 5.34 while the largest similarity precision can be as high as 114.03. It is suggested that the similarity precision is more effective in reflecting the scale effects and their fluctuation than similarity difference. Consequently, similarity theory is suitable for evaluating the scale effects in micro EDM. This proposed research offers engineering values for optimizing the machining parameters and improving the machining performances of micro EDM.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yan, Ruqiang; Chen, Xuefeng; Li, Weihua

Modern mathematics has commonly been utilized as an effective tool to model mechanical equipment so that their dynamic characteristics can be studied analytically. This will help identify potential failures of mechanical equipment by observing change in the equipment’s dynamic parameters. On the other hand, dynamic signals are also important and provide reliable information about the equipment’s working status. Modern mathematics has also provided us with a systematic way to design and implement various signal processing methods, which are used to analyze these dynamic signals, and to enhance intrinsic signal components that are directly related to machine failures. This special issuemore » is aimed at stimulating not only new insights on mathematical methods for modeling but also recently developed signal processing methods, such as sparse decomposition with potential applications in machine fault diagnosis. Finally, the papers included in this special issue provide a glimpse into some of the research and applications in the field of machine fault diagnosis through applications of the modern mathematical methods.« less

Experimental Investigation and Optimization of Response Variables in WEDM of Inconel - 718

NASA Astrophysics Data System (ADS)

Karidkar, S. S.; Dabade, U. A.

2016-02-01

Effective utilisation of Wire Electrical Discharge Machining (WEDM) technology is challenge for modern manufacturing industries. Day by day new materials with high strengths and capabilities are being developed to fulfil the customers need. Inconel - 718 is similar kind of material which is extensively used in aerospace applications, such as gas turbine, rocket motors, and spacecraft as well as in nuclear reactors and pumps etc. This paper deals with the experimental investigation of optimal machining parameters in WEDM for Surface Roughness, Kerf Width and Dimensional Deviation using DoE such as Taguchi methodology, L9 orthogonal array. By keeping peak current constant at 70 A, the effect of other process parameters on above response variables were analysed. Obtained experimental results were statistically analysed using Minitab-16 software. Analysis of Variance (ANOVA) shows pulse on time as the most influential parameter followed by wire tension whereas spark gap set voltage is observed to be non-influencing parameter. Multi-objective optimization technique, Grey Relational Analysis (GRA), shows optimal machining parameters such as pulse on time 108 Machine unit, spark gap set voltage 50 V and wire tension 12 gm for optimal response variables considered for the experimental analysis.

Layout Design of Human-Machine Interaction Interface of Cabin Based on Cognitive Ergonomics and GA-ACA.

PubMed

Deng, Li; Wang, Guohua; Yu, Suihuai

2016-01-01

In order to consider the psychological cognitive characteristics affecting operating comfort and realize the automatic layout design, cognitive ergonomics and GA-ACA (genetic algorithm and ant colony algorithm) were introduced into the layout design of human-machine interaction interface. First, from the perspective of cognitive psychology, according to the information processing process, the cognitive model of human-machine interaction interface was established. Then, the human cognitive characteristics were analyzed, and the layout principles of human-machine interaction interface were summarized as the constraints in layout design. Again, the expression form of fitness function, pheromone, and heuristic information for the layout optimization of cabin was studied. The layout design model of human-machine interaction interface was established based on GA-ACA. At last, a layout design system was developed based on this model. For validation, the human-machine interaction interface layout design of drilling rig control room was taken as an example, and the optimization result showed the feasibility and effectiveness of the proposed method.

Layout Design of Human-Machine Interaction Interface of Cabin Based on Cognitive Ergonomics and GA-ACA

PubMed Central

Deng, Li; Wang, Guohua; Yu, Suihuai

2016-01-01

In order to consider the psychological cognitive characteristics affecting operating comfort and realize the automatic layout design, cognitive ergonomics and GA-ACA (genetic algorithm and ant colony algorithm) were introduced into the layout design of human-machine interaction interface. First, from the perspective of cognitive psychology, according to the information processing process, the cognitive model of human-machine interaction interface was established. Then, the human cognitive characteristics were analyzed, and the layout principles of human-machine interaction interface were summarized as the constraints in layout design. Again, the expression form of fitness function, pheromone, and heuristic information for the layout optimization of cabin was studied. The layout design model of human-machine interaction interface was established based on GA-ACA. At last, a layout design system was developed based on this model. For validation, the human-machine interaction interface layout design of drilling rig control room was taken as an example, and the optimization result showed the feasibility and effectiveness of the proposed method. PMID:26884745

A superconducting homopolar motor and generator—new approaches

NASA Astrophysics Data System (ADS)

Fuger, Rene; Matsekh, Arkadiy; Kells, John; Sercombe, D. B. T.; Guina, Ante

2016-03-01

Homopolar machines were the first continuously running electromechanical converters ever demonstrated but engineering challenges and the rapid development of AC technology prevented wider commercialisation. Recent developments in superconducting, cryogenic and sliding contact technology together with new areas of application have led to a renewed interest in homopolar machines. Some of the advantages of these machines are ripple free constant torque, pure DC operation, high power-to-weight ratio and that rotating magnets or coils are not required. In this paper we present our unique approach to high power and high torque homopolar electromagnetic turbines using specially designed high field superconducting magnets and liquid metal current collectors. The unique arrangement of the superconducting coils delivers a high static drive field as well as effective shielding for the field critical sliding contacts. The novel use of additional shielding coils reduces weight and stray field of the system. Liquid metal current collectors deliver a low resistance, stable and low maintenance sliding contact by using a thin liquid metal layer that fills a circular channel formed by the moving edge of a rotor and surrounded by a conforming stationary channel of the stator. Both technologies are critical to constructing high performance machines. Homopolar machines are pure DC devices that utilise only DC electric and magnetic fields and have no AC losses in the coils or the supporting structure. Guina Energy Technologies has developed, built and tested different motor and generator concepts over the last few years and has combined its experience to develop a new generation of homopolar electromagnetic turbines. This paper summarises the development process, general design parameters and first test results of our high temperature superconducting test motor.

Machine Shop Lathes.

ERIC Educational Resources Information Center

Dunn, James

This guide, the second in a series of five machine shop curriculum manuals, was designed for use in machine shop courses in Oklahoma. The purpose of the manual is to equip students with basic knowledge and skills that will enable them to enter the machine trade at the machine-operator level. The curriculum is designed so that it can be used in…

National Synchrotron Light Source annual report 1991

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hulbert, S.L.; Lazarz, N.M.

1992-04-01

This report discusses the following research conducted at NSLS: atomic and molecular science; energy dispersive diffraction; lithography, microscopy and tomography; nuclear physics; UV photoemission and surface science; x-ray absorption spectroscopy; x-ray scattering and crystallography; x-ray topography; workshop on surface structure; workshop on electronic and chemical phenomena at surfaces; workshop on imaging; UV FEL machine reviews; VUV machine operations; VUV beamline operations; VUV storage ring parameters; x-ray machine operations; x-ray beamline operations; x-ray storage ring parameters; superconducting x-ray lithography source; SXLS storage ring parameters; the accelerator test facility; proposed UV-FEL user facility at the NSLS; global orbit feedback systems; and NSLSmore » computer system.« less

Lean energy analysis of CNC lathe

NASA Astrophysics Data System (ADS)

Liana, N. A.; Amsyar, N.; Hilmy, I.; Yusof, MD

2018-01-01

The industrial sector in Malaysia is one of the main sectors that have high percentage of energy demand compared to other sector and this problem may lead to the future power shortage and increasing the production cost of a company. Suitable initiatives should be implemented by the industrial sectors to solve the issues such as by improving the machining system. In the past, the majority of the energy consumption in industry focus on lighting, HVAC and office section usage. Future trend, manufacturing process is also considered to be included in the energy analysis. A study on Lean Energy Analysis in a machining process is presented. Improving the energy efficiency in a lathe machine by enhancing the cutting parameters of turning process is discussed. Energy consumption of a lathe machine was analyzed in order to identify the effect of cutting parameters towards energy consumption. It was found that the combination of parameters for third run (spindle speed: 1065 rpm, depth of cut: 1.5 mm, feed rate: 0.3 mm/rev) was the most preferred and ideal to be used during the turning machining process as it consumed less energy usage.

Ontological modelling of knowledge management for human-machine integrated design of ultra-precision grinding machine

NASA Astrophysics Data System (ADS)

Hong, Haibo; Yin, Yuehong; Chen, Xing

2016-11-01

Despite the rapid development of computer science and information technology, an efficient human-machine integrated enterprise information system for designing complex mechatronic products is still not fully accomplished, partly because of the inharmonious communication among collaborators. Therefore, one challenge in human-machine integration is how to establish an appropriate knowledge management (KM) model to support integration and sharing of heterogeneous product knowledge. Aiming at the diversity of design knowledge, this article proposes an ontology-based model to reach an unambiguous and normative representation of knowledge. First, an ontology-based human-machine integrated design framework is described, then corresponding ontologies and sub-ontologies are established according to different purposes and scopes. Second, a similarity calculation-based ontology integration method composed of ontology mapping and ontology merging is introduced. The ontology searching-based knowledge sharing method is then developed. Finally, a case of human-machine integrated design of a large ultra-precision grinding machine is used to demonstrate the effectiveness of the method.

Finite Element Analysis in the Estimation of Air-Gap Torque and Surface Temperature of Induction Machine

NASA Astrophysics Data System (ADS)

Mr., J. Ravi Kumar; Banakara, Basavaraja, Dr.

2017-08-01

This paper presents electromagnetic and thermal behavior of Induction Motor (IM) through the modeling and analysis by applying multiphysics coupled Finite Element Analysis (FEA). Therefore prediction of the magnetic flux, electromagnetic torque, stator and rotor losses and temperature distribution inside an operating electric motor are the most important issues during its design. Prediction and estimation of these parameters allows design engineers to decide capability of the machine for the proposed load, temperature rating and its application for which it is being designed ensuring normal motor operation at rated conditions. In this work, multiphysics coupled electromagnetic - thermal modeling and analysis of induction motor at rated and high frequency has carried out applying Arkkio’s torque method. COMSOL Multiphysics software is used for modeling and finite element analysis of IM. Transient electromagnetic torque, magnetic field distribution, speed-torque characteristics of IM were plotted and studied at different frequencies. This proposed work helps in the design and prediction of accurate performance of induction motor specific to various industrial drive applications. Results obtained are also validated with experimental analysis. The main purpose of this model is to use it as an integral part of the design aiming to system optimization of Variable Speed Drive (VSD) and its components using coupled simulations.

Study on super-long deep-hole drilling of titanium alloy.

PubMed

Liu, Zhanfeng; Liu, Yanshu; Han, Xiaolan; Zheng, Wencui

2018-01-01

In this study, the super-long deep-hole drilling of a titanium alloy was investigated. According to material properties of the titanium alloy, an experimental approach was designed to study three issues discovered during the drilling process: the hole-axis deflection, chip morphology, and tool wear. Based on the results of drilling experiments, crucial parameters for the super-long deep-hole drilling of titanium alloys were obtained, and the influences of these parameters on quality of the alloy's machining were also evaluated. Our results suggest that the developed drilling process is an effective method to overcome the challenge of super-long deep-hole drilling on difficult-to-cut materials.

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

NASA Technical Reports Server (NTRS)

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.

On Intelligent Design and Planning Method of Process Route Based on Gun Breech Machining Process

NASA Astrophysics Data System (ADS)

Hongzhi, Zhao; Jian, Zhang

2018-03-01

The paper states an approach of intelligent design and planning of process route based on gun breech machining process, against several problems, such as complex machining process of gun breech, tedious route design and long period of its traditional unmanageable process route. Based on gun breech machining process, intelligent design and planning system of process route are developed by virtue of DEST and VC++. The system includes two functional modules--process route intelligent design and its planning. The process route intelligent design module, through the analysis of gun breech machining process, summarizes breech process knowledge so as to complete the design of knowledge base and inference engine. And then gun breech process route intelligently output. On the basis of intelligent route design module, the final process route is made, edited and managed in the process route planning module.

Effect of the crown design and interface lute parameters on the stress-state of a machined crown-tooth system: a finite element analysis.

PubMed

Shahrbaf, Shirin; vanNoort, Richard; Mirzakouchaki, Behnam; Ghassemieh, Elaheh; Martin, Nicolas

2013-08-01

The effect of preparation design and the physical properties of the interface lute on the restored machined ceramic crown-tooth complex are poorly understood. The aim of this work was to determine, by means of three-dimensional finite element analysis (3D FEA) the effect of the tooth preparation design and the elastic modulus of the cement on the stress state of the cemented machined ceramic crown-tooth complex. The three-dimensional structure of human premolar teeth, restored with adhesively cemented machined ceramic crowns, was digitized with a micro-CT scanner. An accurate, high resolution, digital replica model of a restored tooth was created. Two preparation designs, with different occlusal morphologies, were modeled with cements of 3 different elastic moduli. Interactive medical image processing software (mimics and professional CAD modeling software) was used to create sophisticated digital models that included the supporting structures; periodontal ligament and alveolar bone. The generated models were imported into an FEA software program (hypermesh version 10.0, Altair Engineering Inc.) with all degrees of freedom constrained at the outer surface of the supporting cortical bone of the crown-tooth complex. Five different elastic moduli values were given to the adhesive cement interface 1.8GPa, 4GPa, 8GPa, 18.3GPa and 40GPa; the four lower values are representative of currently used cementing lutes and 40GPa is set as an extreme high value. The stress distribution under simulated applied loads was determined. The preparation design demonstrated an effect on the stress state of the restored tooth system. The cement elastic modulus affected the stress state in the cement and dentin structures but not in the crown, the pulp, the periodontal ligament or the cancellous and cortical bone. The results of this study suggest that both the choice of the preparation design and the cement elastic modulus can affect the stress state within the restored crown-tooth complex. Copyright © 2013 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

Compact compressive arc and beam switchyard for energy recovery linac-driven ultraviolet free electron lasers

NASA Astrophysics Data System (ADS)

Akkermans, J. A. G.; Di Mitri, S.; Douglas, D.; Setija, I. D.

2017-08-01

High gain free electron lasers (FELs) driven by high repetition rate recirculating accelerators have received considerable attention in the scientific and industrial communities in recent years. Cost-performance optimization of such facilities encourages limiting machine size and complexity, and a compact machine can be realized by combining bending and bunch length compression during the last stage of recirculation, just before lasing. The impact of coherent synchrotron radiation (CSR) on electron beam quality during compression can, however, limit FEL output power. When methods to counteract CSR are implemented, appropriate beam diagnostics become critical to ensure that the target beam parameters are met before lasing, as well as to guarantee reliable, predictable performance and rapid machine setup and recovery. This article describes a beam line for bunch compression and recirculation, and beam switchyard accessing a diagnostic line for EUV lasing at 1 GeV beam energy. The footprint is modest, with 12 m compressive arc diameter and ˜20 m diagnostic line length. The design limits beam quality degradation due to CSR both in the compressor and in the switchyard. Advantages and drawbacks of two switchyard lines providing, respectively, off-line and on-line measurements are discussed. The entire design is scalable to different beam energies and charges.

Effect of processing parameters on surface finish for fused deposition machinable wax patterns

NASA Technical Reports Server (NTRS)

Roberts, F. E., III

1995-01-01

This report presents a study on the effect of material processing parameters used in layer-by-layer material construction on the surface finish of a model to be used as an investment casting pattern. The data presented relate specifically to fused deposition modeling using a machinable wax.

Machine Learning Methods for Analysis of Metabolic Data and Metabolic Pathway Modeling

PubMed Central

Cuperlovic-Culf, Miroslava

2018-01-01

Machine learning uses experimental data to optimize clustering or classification of samples or features, or to develop, augment or verify models that can be used to predict behavior or properties of systems. It is expected that machine learning will help provide actionable knowledge from a variety of big data including metabolomics data, as well as results of metabolism models. A variety of machine learning methods has been applied in bioinformatics and metabolism analyses including self-organizing maps, support vector machines, the kernel machine, Bayesian networks or fuzzy logic. To a lesser extent, machine learning has also been utilized to take advantage of the increasing availability of genomics and metabolomics data for the optimization of metabolic network models and their analysis. In this context, machine learning has aided the development of metabolic networks, the calculation of parameters for stoichiometric and kinetic models, as well as the analysis of major features in the model for the optimal application of bioreactors. Examples of this very interesting, albeit highly complex, application of machine learning for metabolism modeling will be the primary focus of this review presenting several different types of applications for model optimization, parameter determination or system analysis using models, as well as the utilization of several different types of machine learning technologies. PMID:29324649

Machine Learning Methods for Analysis of Metabolic Data and Metabolic Pathway Modeling.

PubMed

Cuperlovic-Culf, Miroslava

2018-01-11

Machine learning uses experimental data to optimize clustering or classification of samples or features, or to develop, augment or verify models that can be used to predict behavior or properties of systems. It is expected that machine learning will help provide actionable knowledge from a variety of big data including metabolomics data, as well as results of metabolism models. A variety of machine learning methods has been applied in bioinformatics and metabolism analyses including self-organizing maps, support vector machines, the kernel machine, Bayesian networks or fuzzy logic. To a lesser extent, machine learning has also been utilized to take advantage of the increasing availability of genomics and metabolomics data for the optimization of metabolic network models and their analysis. In this context, machine learning has aided the development of metabolic networks, the calculation of parameters for stoichiometric and kinetic models, as well as the analysis of major features in the model for the optimal application of bioreactors. Examples of this very interesting, albeit highly complex, application of machine learning for metabolism modeling will be the primary focus of this review presenting several different types of applications for model optimization, parameter determination or system analysis using models, as well as the utilization of several different types of machine learning technologies.

ANN-PSO Integrated Optimization Methodology for Intelligent Control of MMC Machining

NASA Astrophysics Data System (ADS)

Chandrasekaran, Muthumari; Tamang, Santosh

2017-08-01

Metal Matrix Composites (MMC) show improved properties in comparison with non-reinforced alloys and have found increased application in automotive and aerospace industries. The selection of optimum machining parameters to produce components of desired surface roughness is of great concern considering the quality and economy of manufacturing process. In this study, a surface roughness prediction model for turning Al-SiCp MMC is developed using Artificial Neural Network (ANN). Three turning parameters viz., spindle speed ( N), feed rate ( f) and depth of cut ( d) were considered as input neurons and surface roughness was an output neuron. ANN architecture having 3 -5 -1 is found to be optimum and the model predicts with an average percentage error of 7.72 %. Particle Swarm Optimization (PSO) technique is used for optimizing parameters to minimize machining time. The innovative aspect of this work is the development of an integrated ANN-PSO optimization method for intelligent control of MMC machining process applicable to manufacturing industries. The robustness of the method shows its superiority for obtaining optimum cutting parameters satisfying desired surface roughness. The method has better convergent capability with minimum number of iterations.

Machinability Study on Milling Kenaf Fiber Reinforced Plastic Composite Materials using Design of Experiments

NASA Astrophysics Data System (ADS)

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.

Enhanced Learning through Design Problems--Teaching a Components-Based Course through Design

ERIC Educational Resources Information Center

Jensen, Bogi Bech; Hogberg, Stig; Jensen, Frida av Flotum; Mijatovic, Nenad

2012-01-01

This paper describes a teaching method used in an electrical machines course, where the students learn about electrical machines by designing them. The aim of the course is not to teach design, albeit this is a side product, but rather to teach the fundamentals and the function of electrical machines through design. The teaching method is…

Design and experimental validation for direct-drive fault-tolerant permanent-magnet vernier machines.

PubMed

Liu, Guohai; Yang, Junqin; Chen, Ming; Chen, Qian

2014-01-01

A fault-tolerant permanent-magnet vernier (FT-PMV) machine is designed for direct-drive applications, incorporating the merits of high torque density and high reliability. Based on the so-called magnetic gearing effect, PMV machines have the ability of high torque density by introducing the flux-modulation poles (FMPs). This paper investigates the fault-tolerant characteristic of PMV machines and provides a design method, which is able to not only meet the fault-tolerant requirements but also keep the ability of high torque density. The operation principle of the proposed machine has been analyzed. The design process and optimization are presented specifically, such as the combination of slots and poles, the winding distribution, and the dimensions of PMs and teeth. By using the time-stepping finite element method (TS-FEM), the machine performances are evaluated. Finally, the FT-PMV machine is manufactured, and the experimental results are presented to validate the theoretical analysis.

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

NASA Technical Reports Server (NTRS)

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.

Understanding and Writing G & M Code for CNC Machines

ERIC Educational Resources Information Center

Loveland, Thomas

2012-01-01

In modern CAD and CAM manufacturing companies, engineers design parts for machines and consumable goods. Many of these parts are cut on CNC machines. Whether using a CNC lathe, milling machine, or router, the ideas and designs of engineers must be translated into a machine-readable form called G & M Code that can be used to cut parts to precise…

Temperature of Heating and Cooling of Massive, Thin, and Wedge-Shaped Plates from Hard-to-Machine Steels During Their Grinding

NASA Astrophysics Data System (ADS)

Dement‧ev, V. B.; Ivanova, T. N.; Dolginov, A. M.

2017-01-01

Grinding of flat parts occurs by solid abrasive particles due to the physicomechanical process of deformation and to the action of a process liquid at high temperatures in a zone small in volume and difficult for observation. The rate of heating and cooling depends on the change in the intensity of the heat flux and in the velocity and time of action of the heat source. A study has been made of the regularities of the influence of each of these parameters on the depth and character of structural transformations during the grinding of flat parts from hard-to-machine steels. A procedure to calculate temperature in grinding massive, thin, and wedge-shaped parts has been developed with account taken of the geometric and thermophysical parameters of the tool and the treated part, and also of cutting regimes. The procedure can be used as a constituent part in developing a system for automatic design of the technological process of grinding of flat surfaces. A relationship between the temperature in the grinding zone and the regimes of treatment has been established which makes it possible to control the quality of the surface layer of massive, thin, and wedge-shaped plates from hard-to-machine steels. The rational boundaries of shift of cutting regimes have been determined.

DOE-RCT-0003641 Final Technical Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wagner, Edward; Lesster, Ted

2014-07-30

This program studied novel concepts for an Axial Flux Reluctance Machine to capture energy from marine hydrokinetic sources and compared their attributes to a Radial Flux Reluctance Machine which was designed under a prior Department of Energy program for the same application. Detailed electromagnetic and mechanical analyses were performed to determine the validity of the concept and to provide a direct comparison with the existing conventional Radial Flux Switched Reluctance Machine designed during the Advanced Wave Energy Conversion Project, DE-EE0003641. The alternate design changed the machine topology so that the flux that is switched flows axially rather than radially andmore » the poles themselves are long radially, as opposed to the radial flux machine that has pole pieces that are long axially. It appeared possible to build an axial flux machine that should be considerably more compact than the radial machine. In an “apples to apples” comparison, the same rules with regard to generating magnetic force and the fundamental limitations of flux density hold, so that at the heart of the machine the same torque equations hold. The differences are in the mechanical configuration that limits or enhances the change of permeance with rotor position, in the amount of permeable iron required to channel the flux via the pole pieces to the air-gaps, and in the sizing and complexity of the electrical winding. Accordingly it was anticipated that the magnetic component weight would be similar but that better use of space would result in a shorter machine with accompanying reduction in housing and support structure. For the comparison the pole count was kept the same at 28 though it was also expected that the radial tapering of the slots between pole pieces would permit a higher pole count machine, enabling the generation of greater power at a given speed in some future design. The baseline Radial Flux Machine design was established during the previous DOE program. Its characteristics were tabulated for use in comparing to the Axial Flux Machine. Three basic conceptual designs for the Axial Flux Machine were considered: (1) a machine with a single coil at the inner diameter of the machine, (2) a machine with a single coil at the outside diameter of the machine, and (3) a machine with a coil around each tooth. Slight variations of these basic configurations were considered during the study. Analysis was performed on these configurations to determine the best candidate design to advance to preliminary design, based on size, weight, performance, cost and manufacturability. The configuration selected as the most promising was the multi-pole machine with a coil around each tooth. This configuration provided the least complexity with respect to the mechanical configuration and manufacturing, which would yield the highest reliability and lowest cost machine of the three options. A preliminary design was performed on this selected configuration. For this first ever axial design of the multi rotor configuration the 'apples to apples' comparison was based on using the same length of rotor pole as the axial length of rotor pole in the radial machine and making the mean radius of the rotor in the axial machine the same as the air gap radius in the radial machine. The tooth to slot ratio at the mean radius of the axial machine was the same as the tooth to slot ratio of the radial machine. The comparison between the original radial flux machine and the new axial flux machine indicates that for the same torque, the axial flux machine diameter will be 27% greater, but it will have 30% of the length, and 76% of the weight. Based on these results, it is concluded that an axial flux reluctance machine presents a viable option for large generators to be used for the capture of wave energy. In the analysis of Task 4, below, it is pointed out that our selection of dimensional similarity for the 'apples to apples' comparison did not produce an optimum axial flux design. There is torque capability to spare, implying we could reduce the magnetic structure, but the winding area, constrained by the pole separation at the inner pole radius has a higher resistance than desirable, implying we need more room for copper. The recommendation is to proceed via one cycle of optimization and review to correct this unbalance and then proceed to a detailed design phase to produce manufacturing drawings, followed by the construction of a prototype to test the performance of the machine against predicted results.« less

Machinability of Al 6061 Deposited with Cold Spray Additive Manufacturing

NASA Astrophysics Data System (ADS)

Aldwell, Barry; Kelly, Elaine; Wall, Ronan; Amaldi, Andrea; O'Donnell, Garret E.; Lupoi, Rocco

2017-10-01

Additive manufacturing techniques such as cold spray are translating from research laboratories into more mainstream high-end production systems. Similar to many additive processes, finishing still depends on removal processes. This research presents the results from investigations into aspects of the machinability of aluminum 6061 tubes manufactured with cold spray. Through the analysis of cutting forces and observations on chip formation and surface morphology, the effect of cutting speed, feed rate, and heat treatment was quantified, for both cold-sprayed and bulk aluminum 6061. High-speed video of chip formation shows changes in chip form for varying material and heat treatment, which is supported by the force data and quantitative imaging of the machined surface. The results shown in this paper demonstrate that parameters involved in cold spray directly impact on machinability and therefore have implications for machining parameters and strategy.

Neural networks with fuzzy Petri nets for modeling a machining process

NASA Astrophysics Data System (ADS)

Hanna, Moheb M.

1998-03-01

The paper presents an intelligent architecture based a feedforward neural network with fuzzy Petri nets for modeling product quality in a CNC machining center. It discusses how the proposed architecture can be used for modeling, monitoring and control a product quality specification such as surface roughness. The surface roughness represents the output quality specification manufactured by a CNC machining center as a result of a milling process. The neural network approach employed the selected input parameters which defined by the machine operator via the CNC code. The fuzzy Petri nets approach utilized the exact input milling parameters, such as spindle speed, feed rate, tool diameter and coolant (off/on), which can be obtained via the machine or sensors system. An aim of the proposed architecture is to model the demanded quality of surface roughness as high, medium or low.

Design study of an ultra-compact superconducting cyclotron for isotope production

NASA Astrophysics Data System (ADS)

Smirnov, V.; Vorozhtsov, S.; Vincent, J.

2014-11-01

A 12.5 MeV, 25 μA, proton compact superconducting cyclotron for medical isotope production has been designed and is currently in fabrication. The machine is initially aimed at producing 13N ammonia for Positron Emission Tomography (PET) cardiology applications. With an ultra-compact size and cost-effective price point, this system will offer clinicians unprecedented access to the preferred radiopharmaceutical isotope for cardiac PET imaging. A systems approach that carefully balanced the subsystem requirements coupled to precise beam dynamics calculations was followed. The system is designed to irradiate a liquid target internal to the cyclotron and to minimize the need for radiation shielding. The main parameters of the cyclotron, its design, and principal steps of the development work are presented here.

Hybrid Metaheuristics for Solving a Fuzzy Single Batch-Processing Machine Scheduling Problem

PubMed Central

Molla-Alizadeh-Zavardehi, S.; Tavakkoli-Moghaddam, R.; Lotfi, F. Hosseinzadeh

2014-01-01

This paper deals with a problem of minimizing total weighted tardiness of jobs in a real-world single batch-processing machine (SBPM) scheduling in the presence of fuzzy due date. In this paper, first a fuzzy mixed integer linear programming model is developed. Then, due to the complexity of the problem, which is NP-hard, we design two hybrid metaheuristics called GA-VNS and VNS-SA applying the advantages of genetic algorithm (GA), variable neighborhood search (VNS), and simulated annealing (SA) frameworks. Besides, we propose three fuzzy earliest due date heuristics to solve the given problem. Through computational experiments with several random test problems, a robust calibration is applied on the parameters. Finally, computational results on different-scale test problems are presented to compare the proposed algorithms. PMID:24883359

Space Radiation Effects Laboratory

NASA Technical Reports Server (NTRS)

1969-01-01

The SREL User's Handbook is designed to provide information needed by those who plan experiments involving the accelerators at this laboratory. Thus the Handbook will contain information on the properties of the machines, the beam parameters, the facilities and services provided for experimenters, etc. This information will be brought up to date as new equipment is added and modifications accomplished. This Handbook is influenced by the many excellent models prepared at other accelerator laboratories. In particular, the CERN Synchrocyclotron User's Handbook (November 1967) is closely followed in some sections, since the SREL Synchrocyclotron is a duplicate of the CERN machine. We wish to thank Dr. E. G. Michaelis for permission to draw so heavily on his work, particularly in Section II of this Handbook. We hope that the Handbook will prove useful, and will welcome suggestions and criticism.

Using a Virtual Tablet Machine to Improve Student Understanding of the Complex Processes Involved in Tablet Manufacturing.

PubMed

Mattsson, Sofia; Sjöström, Hans-Erik; Englund, Claire

2016-06-25

Objective. To develop and implement a virtual tablet machine simulation to aid distance students' understanding of the processes involved in tablet production. Design. A tablet simulation was created enabling students to study the effects different parameters have on the properties of the tablet. Once results were generated, students interpreted and explained them on the basis of current theory. Assessment. The simulation was evaluated using written questionnaires and focus group interviews. Students appreciated the exercise and considered it to be motivational. Students commented that they found the simulation, together with the online seminar and the writing of the report, was beneficial for their learning process. Conclusion. According to students' perceptions, the use of the tablet simulation contributed to their understanding of the compaction process.

Using a Virtual Tablet Machine to Improve Student Understanding of the Complex Processes Involved in Tablet Manufacturing

PubMed Central

Sjöström, Hans-Erik; Englund, Claire

2016-01-01

Objective. To develop and implement a virtual tablet machine simulation to aid distance students’ understanding of the processes involved in tablet production. Design. A tablet simulation was created enabling students to study the effects different parameters have on the properties of the tablet. Once results were generated, students interpreted and explained them on the basis of current theory. Assessment. The simulation was evaluated using written questionnaires and focus group interviews. Students appreciated the exercise and considered it to be motivational. Students commented that they found the simulation, together with the online seminar and the writing of the report, was beneficial for their learning process. Conclusion. According to students’ perceptions, the use of the tablet simulation contributed to their understanding of the compaction process. PMID:27402990

Performance Monitoring Of A Computer Numerically Controlled (CNC) Lathe Using Pattern Recognition Techniques

NASA Astrophysics Data System (ADS)

Daneshmend, L. K.; Pak, H. A.

1984-02-01

On-line monitoring of the cutting process in CNC lathe is desirable to ensure unattended fault-free operation in an automated environment. The state of the cutting tool is one of the most important parameters which characterises the cutting process. Direct monitoring of the cutting tool or workpiece is not feasible during machining. However several variables related to the state of the tool can be measured on-line. A novel monitoring technique is presented which uses cutting torque as the variable for on-line monitoring. A classifier is designed on the basis of the empirical relationship between cutting torque and flank wear. The empirical model required by the on-line classifier is established during an automated training cycle using machine vision for off-line direct inspection of the tool.

Sugeno-Fuzzy Expert System Modeling for Quality Prediction of Non-Contact Machining Process

NASA Astrophysics Data System (ADS)

Sivaraos; Khalim, A. Z.; Salleh, M. S.; Sivakumar, D.; Kadirgama, K.

2018-03-01

Modeling can be categorised into four main domains: prediction, optimisation, estimation and calibration. In this paper, the Takagi-Sugeno-Kang (TSK) fuzzy logic method is examined as a prediction modelling method to investigate the taper quality of laser lathing, which seeks to replace traditional lathe machines with 3D laser lathing in order to achieve the desired cylindrical shape of stock materials. Three design parameters were selected: feed rate, cutting speed and depth of cut. A total of twenty-four experiments were conducted with eight sequential runs and replicated three times. The results were found to be 99% of accuracy rate of the TSK fuzzy predictive model, which suggests that the model is a suitable and practical method for non-linear laser lathing process.

30 CFR 18.54 - High-voltage continuous mining machines.

Code of Federal Regulations, 2010 CFR

2010-07-01

... and Design Requirements § 18.54 High-voltage continuous mining machines. (a) Separation of high... removed. (c) Circuit-interrupting devices. Circuit-interrupting devices must be designed and installed to... ground. (e) Onboard ungrounded, three-phase power circuit. A continuous mining machine designed with an...

30 CFR 18.54 - High-voltage continuous mining machines.

Code of Federal Regulations, 2013 CFR

2013-07-01

... and Design Requirements § 18.54 High-voltage continuous mining machines. (a) Separation of high... removed. (c) Circuit-interrupting devices. Circuit-interrupting devices must be designed and installed to... ground. (e) Onboard ungrounded, three-phase power circuit. A continuous mining machine designed with an...

30 CFR 18.54 - High-voltage continuous mining machines.

Code of Federal Regulations, 2014 CFR

2014-07-01

... and Design Requirements § 18.54 High-voltage continuous mining machines. (a) Separation of high... removed. (c) Circuit-interrupting devices. Circuit-interrupting devices must be designed and installed to... ground. (e) Onboard ungrounded, three-phase power circuit. A continuous mining machine designed with an...

30 CFR 18.54 - High-voltage continuous mining machines.

Code of Federal Regulations, 2012 CFR

2012-07-01

... and Design Requirements § 18.54 High-voltage continuous mining machines. (a) Separation of high... removed. (c) Circuit-interrupting devices. Circuit-interrupting devices must be designed and installed to... ground. (e) Onboard ungrounded, three-phase power circuit. A continuous mining machine designed with an...

30 CFR 18.54 - High-voltage continuous mining machines.

Code of Federal Regulations, 2011 CFR

2011-07-01

... and Design Requirements § 18.54 High-voltage continuous mining machines. (a) Separation of high... removed. (c) Circuit-interrupting devices. Circuit-interrupting devices must be designed and installed to... ground. (e) Onboard ungrounded, three-phase power circuit. A continuous mining machine designed with an...

Un formalisme de systemes a sauts pour la recirculation optimale des casses dans une machine a papier

NASA Astrophysics Data System (ADS)

Khanbaghi, Maryam

Increasing closure of white water circuits is making mill productivity and quality of paper produced increasingly affected by the occurrence of paper breaks. In this thesis the main objective is the development of white water and broke recirculation policies. The thesis consists of three main parts, respectively corresponding to the synthesis of a statistical model of paper breaks in a paper mill, the basic mathematical setup for the formulation of white water and broke recirculation policies in the mill as a jump linear quadratic regulation problem, and finally the tuning of the control law based on first passage-time theory, and its extension to the case of control sensitive paper break rates. More specifically, in the first part a statistical model of paper machine breaks is developed. We start from the hypothesis that the breaks process is a Markov chain with three states: the first state is the operational one, while the two others are associated with the general types of paper-breaks that can take place in the mill (wet breaks and dry breaks). The Markovian hypothesis is empirically validated. We also establish how paper-break rates are correlated with machine speed and broke recirculation ratio. Subsequently, we show how the obtained Markov chain model of paper-breaks can be used to formulate a machine operating speed parameter optimization problem. In the second part, upon recognizing that paper breaks can be modelled as a Markov chain type of process which, when interacting with the continuous mill dynamics, yields a jump Markov model, jump linear theory is proposed as a means of constructing white water and broke recirculation strategies which minimize process variability. Reduced process variability comes at the expense of relatively large swings in white water and broke tanks level. Since the linear design does not specifically account for constraints on the state-space, under the resulting law, damaging events of tank overflow or emptiness can occur. A heuristic simulation-based approach is proposed to choose the performance measure design parameters to keep the mean time between incidents of fluid in broke and white water tanks either overflowing, or reaching dangerously low levels, sufficiently long. In the third part, a methodology, mainly founded on the first passage-time theory of stochastic processes, is proposed to choose the performance measure design parameters to limit process variability while accounting for the possibility of undesirable tank overflows or tank emptiness. The heart of the approach is an approximation technique for evaluating mean first passage-times of the controlled tanks levels. This technique appears to have an applicability which largely exceeds the problem area it was designed for. Furthermore, the introduction of control sensitive break rates and the analysis of the ensuing control problem are presented. This is to account for the experimentally observed increase in breaks concomitant with flow rate variability.

Comparison of surface roughness and chip characteristics obtained under different modes of lubrication during hard turning of AISI H13 tool work steel.

NASA Astrophysics Data System (ADS)

Raj, Anil; Wins, K. Leo Dev; Varadarajan, A. S.

2016-09-01

Surface roughness is one of the important parameters, which not only affects the service life of a component but also serves as a good index of machinability. Near Dry Machining, methods (NDM) are considered as sustainable alternative for workshops trying to bring down their dependence on cutting fluids and the hazards associated with their indiscriminate usage. The present work presents a comparison of the surface roughness and chip characteristics during hard turning of AISI H13 tool work steel using hard metal inserts under two popular NDM techniques namely the minimal fluid application and the Minimum Quantity Lubrication technique(MQL) using an experiment designed based on Taguchi's techniques. The statistical method of analysis of variance (ANOVA) was used to determine the relative significance of input parameters consisting of cutting speed, feed and depth of cut on the attainable surface finish and the chip characteristics. It was observed that the performance during minimal fluid application was better than that during MQL application.

Application of high speed machining technology in aviation

NASA Astrophysics Data System (ADS)

Bałon, Paweł; Szostak, Janusz; Kiełbasa, Bartłomiej; Rejman, Edward; Smusz, Robert

2018-05-01

Aircraft structures are exposed to many loads during their working lifespan. Every particular action made during a flight is composed of a series of air movements which generate various aircraft loads. The most rigorous requirement which modern aircraft structures must fulfill is to maintain their high durability and reliability. This requirement involves taking many restrictions into account during the aircraft design process. The most important factor is the structure's overall mass, which has a crucial impact on both utility properties and cost-effectiveness. This makes aircraft one of the most complex results of modern technology. Additionally, there is currently an increasing utilization of high strength aluminum alloys, which requires the implementation of new manufacturing processes. High Speed Machining technology (HSM) is currently one of the most important machining technologies used in the aviation industry, especially in the machining of aluminium alloys. The primary difference between HSM and other milling techniques is the ability to select cutting parameters - depth of the cut layer, feed rate, and cutting speed in order to simultaneously ensure high quality, precision of the machined surface, and high machining efficiency, all of which shorten the manufacturing process of the integral components. In this paper, the authors explain the implementation of the HSM method in integral aircraft constructions. It presents the method of the airframe manufacturing method, and the final results. The HSM method is compared to the previous method where all subcomponents were manufactured by bending and forming processes, and then, they were joined by riveting.

Status of the Future Circular Collider Study

NASA Astrophysics Data System (ADS)

Benedikt, Michael

2016-03-01

Following the 2013 update of the European Strategy for Particle Physics, the international Future Circular Collider (FCC) Study has been launched by CERN as host institute, to design an energy frontier hadron collider (FCC-hh) in a new 80-100 km tunnel with a centre-of-mass energy of about 100 TeV, an order of magnitude beyond the LHC's, as a long-term goal. The FCC study also includes the design of a 90-350 GeV high-luminosity lepton collider (FCC-ee) installed in the same tunnel, serving as Higgs, top and Z factory, as a potential intermediate step, as well as an electron-proton collider option (FCC-he). The physics cases for such machines will be assessed and concepts for experiments will be developed in time for the next update of the European Strategy for Particle Physics by the end of 2018. The presentation will summarize the status of machine designs and parameters and discuss the essential technical components to be developed in the frame of the FCC study. Key elements are superconducting accelerator-dipole magnets with a field of 16 T for the hadron collider and high-power, high-efficiency RF systems for the lepton collider. In addition the unprecedented beam power presents special challenges for the hadron collider for all aspects of beam handling and machine protection. First conclusions of geological investigations and implementation studies will be presented. The status of the FCC collaboration and the further planning for the study will be outlined.

Using Active Learning for Speeding up Calibration in Simulation Models.

PubMed

Cevik, Mucahit; Ergun, Mehmet Ali; Stout, Natasha K; Trentham-Dietz, Amy; Craven, Mark; Alagoz, Oguzhan

2016-07-01

Most cancer simulation models include unobservable parameters that determine disease onset and tumor growth. These parameters play an important role in matching key outcomes such as cancer incidence and mortality, and their values are typically estimated via a lengthy calibration procedure, which involves evaluating a large number of combinations of parameter values via simulation. The objective of this study is to demonstrate how machine learning approaches can be used to accelerate the calibration process by reducing the number of parameter combinations that are actually evaluated. Active learning is a popular machine learning method that enables a learning algorithm such as artificial neural networks to interactively choose which parameter combinations to evaluate. We developed an active learning algorithm to expedite the calibration process. Our algorithm determines the parameter combinations that are more likely to produce desired outputs and therefore reduces the number of simulation runs performed during calibration. We demonstrate our method using the previously developed University of Wisconsin breast cancer simulation model (UWBCS). In a recent study, calibration of the UWBCS required the evaluation of 378 000 input parameter combinations to build a race-specific model, and only 69 of these combinations produced results that closely matched observed data. By using the active learning algorithm in conjunction with standard calibration methods, we identify all 69 parameter combinations by evaluating only 5620 of the 378 000 combinations. Machine learning methods hold potential in guiding model developers in the selection of more promising parameter combinations and hence speeding up the calibration process. Applying our machine learning algorithm to one model shows that evaluating only 1.49% of all parameter combinations would be sufficient for the calibration. © The Author(s) 2015.

Using Active Learning for Speeding up Calibration in Simulation Models

PubMed Central

Cevik, Mucahit; Ali Ergun, Mehmet; Stout, Natasha K.; Trentham-Dietz, Amy; Craven, Mark; Alagoz, Oguzhan

2015-01-01

Background Most cancer simulation models include unobservable parameters that determine the disease onset and tumor growth. These parameters play an important role in matching key outcomes such as cancer incidence and mortality and their values are typically estimated via lengthy calibration procedure, which involves evaluating large number of combinations of parameter values via simulation. The objective of this study is to demonstrate how machine learning approaches can be used to accelerate the calibration process by reducing the number of parameter combinations that are actually evaluated. Methods Active learning is a popular machine learning method that enables a learning algorithm such as artificial neural networks to interactively choose which parameter combinations to evaluate. We develop an active learning algorithm to expedite the calibration process. Our algorithm determines the parameter combinations that are more likely to produce desired outputs, therefore reduces the number of simulation runs performed during calibration. We demonstrate our method using previously developed University of Wisconsin Breast Cancer Simulation Model (UWBCS). Results In a recent study, calibration of the UWBCS required the evaluation of 378,000 input parameter combinations to build a race-specific model and only 69 of these combinations produced results that closely matched observed data. By using the active learning algorithm in conjunction with standard calibration methods, we identify all 69 parameter combinations by evaluating only 5620 of the 378,000 combinations. Conclusion Machine learning methods hold potential in guiding model developers in the selection of more promising parameter combinations and hence speeding up the calibration process. Applying our machine learning algorithm to one model shows that evaluating only 1.49% of all parameter combinations would be sufficient for the calibration. PMID:26471190

Surface roughness analysis after laser assisted machining of hard to cut materials

NASA Astrophysics Data System (ADS)

Przestacki, D.; Jankowiak, M.

2014-03-01

Metal matrix composites and Si3N4 ceramics are very attractive materials for various industry applications due to extremely high hardness and abrasive wear resistance. However because of these features they are problematic for the conventional turning process. The machining on a classic lathe still requires special polycrystalline diamond (PCD) or cubic boron nitride (CBN) cutting inserts which are very expensive. In the paper an experimental surface roughness analysis of laser assisted machining (LAM) for two tapes of hard-to-cut materials was presented. In LAM, the surface of work piece is heated directly by a laser beam in order to facilitate, the decohesion of material. Surface analysis concentrates on the influence of laser assisted machining on the surface quality of the silicon nitride ceramic Si3N4 and metal matrix composite (MMC). The effect of the laser assisted machining was compared to the conventional machining. The machining parameters influence on surface roughness parameters was also investigated. The 3D surface topographies were measured using optical surface profiler. The analysis of power spectrum density (PSD) roughness profile were analyzed.

Cutting Zone Temperature Identification During Machining of Nickel Alloy Inconel 718

NASA Astrophysics Data System (ADS)

Czán, Andrej; Daniš, Igor; Holubják, Jozef; Zaušková, Lucia; Czánová, Tatiana; Mikloš, Matej; Martikáň, Pavol

2017-12-01

Quality of machined surface is affected by quality of cutting process. There are many parameters, which influence on the quality of the cutting process. The cutting temperature is one of most important parameters that influence the tool life and the quality of machined surfaces. Its identification and determination is key objective in specialized machining processes such as dry machining of hard-to-machine materials. It is well known that maximum temperature is obtained in the tool rake face at the vicinity of the cutting edge. A moderate level of cutting edge temperature and a low thermal shock reduce the tool wear phenomena, and a low temperature gradient in the machined sublayer reduces the risk of high tensile residual stresses. The thermocouple method was used to measure the temperature directly in the cutting zone. An original thermocouple was specially developed for measuring of temperature in the cutting zone, surface and subsurface layers of machined surface. This paper deals with identification of temperature and temperature gradient during dry peripheral milling of Inconel 718. The measurements were used to identification the temperature gradients and to reconstruct the thermal distribution in cutting zone with various cutting conditions.

National Synchrotron Light Source annual report 1991. Volume 1, October 1, 1990--September 30, 1991

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hulbert, S.L.; Lazarz, N.M.

1992-04-01

This report discusses the following research conducted at NSLS: atomic and molecular science; energy dispersive diffraction; lithography, microscopy and tomography; nuclear physics; UV photoemission and surface science; x-ray absorption spectroscopy; x-ray scattering and crystallography; x-ray topography; workshop on surface structure; workshop on electronic and chemical phenomena at surfaces; workshop on imaging; UV FEL machine reviews; VUV machine operations; VUV beamline operations; VUV storage ring parameters; x-ray machine operations; x-ray beamline operations; x-ray storage ring parameters; superconducting x-ray lithography source; SXLS storage ring parameters; the accelerator test facility; proposed UV-FEL user facility at the NSLS; global orbit feedback systems; and NSLSmore » computer system.« less

Large-Scale Linear Optimization through Machine Learning: From Theory to Practical System Design and Implementation

DTIC Science & Technology

2016-08-10

AFRL-AFOSR-JP-TR-2016-0073 Large-scale Linear Optimization through Machine Learning: From Theory to Practical System Design and Implementation ...2016 4.  TITLE AND SUBTITLE Large-scale Linear Optimization through Machine Learning: From Theory to Practical System Design and Implementation 5a...performances on various machine learning tasks and it naturally lends itself to fast parallel implementations . Despite this, very little work has been

An improved method of early diagnosis of smoking-induced respiratory changes using machine learning algorithms.

PubMed

Amaral, Jorge L M; Lopes, Agnaldo J; Jansen, José M; Faria, Alvaro C D; Melo, Pedro L

2013-12-01

The purpose of this study was to develop an automatic classifier to increase the accuracy of the forced oscillation technique (FOT) for diagnosing early respiratory abnormalities in smoking patients. The data consisted of FOT parameters obtained from 56 volunteers, 28 healthy and 28 smokers with low tobacco consumption. Many supervised learning techniques were investigated, including logistic linear classifiers, k nearest neighbor (KNN), neural networks and support vector machines (SVM). To evaluate performance, the ROC curve of the most accurate parameter was established as baseline. To determine the best input features and classifier parameters, we used genetic algorithms and a 10-fold cross-validation using the average area under the ROC curve (AUC). In the first experiment, the original FOT parameters were used as input. We observed a significant improvement in accuracy (KNN=0.89 and SVM=0.87) compared with the baseline (0.77). The second experiment performed a feature selection on the original FOT parameters. This selection did not cause any significant improvement in accuracy, but it was useful in identifying more adequate FOT parameters. In the third experiment, we performed a feature selection on the cross products of the FOT parameters. This selection resulted in a further increase in AUC (KNN=SVM=0.91), which allows for high diagnostic accuracy. In conclusion, machine learning classifiers can help identify early smoking-induced respiratory alterations. The use of FOT cross products and the search for the best features and classifier parameters can markedly improve the performance of machine learning classifiers. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

RANS computations for identification of 1-D cavitation model parameters: application to full load cavitation vortex rope

NASA Astrophysics Data System (ADS)

Alligné, S.; Decaix, J.; Müller, A.; Nicolet, C.; Avellan, F.; Münch, C.

2017-04-01

Due to the massive penetration of alternative renewable energies, hydropower is a key energy conversion technology for stabilizing the electrical power network by using hydraulic machines at off design operating conditions. At full load, the axisymmetric cavitation vortex rope developing in Francis turbines acts as an internal source of energy, leading to an instability commonly referred to as self-excited surge. 1-D models are developed to predict this phenomenon and to define the range of safe operating points for a hydropower plant. These models require a calibration of several parameters. The present work aims at identifying these parameters by using CFD results as objective functions for an optimization process. A 2-D Venturi and 3-D Francis turbine are considered.

Design of a multiple kernel learning algorithm for LS-SVM by convex programming.

PubMed

Jian, Ling; Xia, Zhonghang; Liang, Xijun; Gao, Chuanhou

2011-06-01

As a kernel based method, the performance of least squares support vector machine (LS-SVM) depends on the selection of the kernel as well as the regularization parameter (Duan, Keerthi, & Poo, 2003). Cross-validation is efficient in selecting a single kernel and the regularization parameter; however, it suffers from heavy computational cost and is not flexible to deal with multiple kernels. In this paper, we address the issue of multiple kernel learning for LS-SVM by formulating it as semidefinite programming (SDP). Furthermore, we show that the regularization parameter can be optimized in a unified framework with the kernel, which leads to an automatic process for model selection. Extensive experimental validations are performed and analyzed. Copyright © 2011 Elsevier Ltd. All rights reserved.

A low-cost contact system to assess load displacement velocity in a resistance training machine.

PubMed

Buscà, Bernat; Font, Anna

2011-01-01

This study sought to determine the validity of a new system for assessing the displacement and average velocity within machine-based resistance training exercise using the Chronojump System. The new design is based on a contact bar and a simple, low-cost mechanism that detects the conductivity of electrical potentials with a precision chronograph. This system allows coaches to assess velocity to control the strength training process. A validation study was performed by assessing the concentric phase parameters of a leg press exercise. Output time data from the Chronojump System in combination with the pre-established range of movement was compared with data from a position sensor connected to a Biopac System. A subset of 87 actions from 11 professional tennis players was recorded and, using the two methods, average velocity and displacement variables in the same action were compared. A t-test for dependent samples and a correlation analysis were undertaken. The r value derived from the correlation between the Biopac System and the contact Chronojump System was >0.94 for all measures of displacement and velocity on all loads (p < 0.01). The Effect Size (ES) was 0.18 in displacement and 0.14 in velocity and ranged from 0.09 to 0.31 and from 0.07 to 0.34, respectively. The magnitude of the difference between the two methods in all parameters and the correlation values provided certain evidence of validity of the Chronojump System to assess the average displacement velocity of loads in a resistance training machine. Key pointsThe assessment of speed in resistance machines is a valuable source of information for strength training.Many commercial systems used to assess velocity, power and force are expensive thereby preventing widespread use by coaches and athletes.The system is intended to be a low-cost device for assessing and controlling the velocity exerted on each repetition in any resistance training machine.The system could be easily adapted in any vertical displacement barbell exercise.

Optimizing a machine learning based glioma grading system using multi-parametric MRI histogram and texture features

PubMed Central

Hu, Yu-Chuan; Li, Gang; Yang, Yang; Han, Yu; Sun, Ying-Zhi; Liu, Zhi-Cheng; Tian, Qiang; Han, Zi-Yang; Liu, Le-De; Hu, Bin-Quan; Qiu, Zi-Yu; Wang, Wen; Cui, Guang-Bin

2017-01-01

Current machine learning techniques provide the opportunity to develop noninvasive and automated glioma grading tools, by utilizing quantitative parameters derived from multi-modal magnetic resonance imaging (MRI) data. However, the efficacies of different machine learning methods in glioma grading have not been investigated.A comprehensive comparison of varied machine learning methods in differentiating low-grade gliomas (LGGs) and high-grade gliomas (HGGs) as well as WHO grade II, III and IV gliomas based on multi-parametric MRI images was proposed in the current study. The parametric histogram and image texture attributes of 120 glioma patients were extracted from the perfusion, diffusion and permeability parametric maps of preoperative MRI. Then, 25 commonly used machine learning classifiers combined with 8 independent attribute selection methods were applied and evaluated using leave-one-out cross validation (LOOCV) strategy. Besides, the influences of parameter selection on the classifying performances were investigated. We found that support vector machine (SVM) exhibited superior performance to other classifiers. By combining all tumor attributes with synthetic minority over-sampling technique (SMOTE), the highest classifying accuracy of 0.945 or 0.961 for LGG and HGG or grade II, III and IV gliomas was achieved. Application of Recursive Feature Elimination (RFE) attribute selection strategy further improved the classifying accuracies. Besides, the performances of LibSVM, SMO, IBk classifiers were influenced by some key parameters such as kernel type, c, gama, K, etc. SVM is a promising tool in developing automated preoperative glioma grading system, especially when being combined with RFE strategy. Model parameters should be considered in glioma grading model optimization. PMID:28599282

Optimizing a machine learning based glioma grading system using multi-parametric MRI histogram and texture features.

PubMed

Zhang, Xin; Yan, Lin-Feng; Hu, Yu-Chuan; Li, Gang; Yang, Yang; Han, Yu; Sun, Ying-Zhi; Liu, Zhi-Cheng; Tian, Qiang; Han, Zi-Yang; Liu, Le-De; Hu, Bin-Quan; Qiu, Zi-Yu; Wang, Wen; Cui, Guang-Bin

2017-07-18

Current machine learning techniques provide the opportunity to develop noninvasive and automated glioma grading tools, by utilizing quantitative parameters derived from multi-modal magnetic resonance imaging (MRI) data. However, the efficacies of different machine learning methods in glioma grading have not been investigated.A comprehensive comparison of varied machine learning methods in differentiating low-grade gliomas (LGGs) and high-grade gliomas (HGGs) as well as WHO grade II, III and IV gliomas based on multi-parametric MRI images was proposed in the current study. The parametric histogram and image texture attributes of 120 glioma patients were extracted from the perfusion, diffusion and permeability parametric maps of preoperative MRI. Then, 25 commonly used machine learning classifiers combined with 8 independent attribute selection methods were applied and evaluated using leave-one-out cross validation (LOOCV) strategy. Besides, the influences of parameter selection on the classifying performances were investigated. We found that support vector machine (SVM) exhibited superior performance to other classifiers. By combining all tumor attributes with synthetic minority over-sampling technique (SMOTE), the highest classifying accuracy of 0.945 or 0.961 for LGG and HGG or grade II, III and IV gliomas was achieved. Application of Recursive Feature Elimination (RFE) attribute selection strategy further improved the classifying accuracies. Besides, the performances of LibSVM, SMO, IBk classifiers were influenced by some key parameters such as kernel type, c, gama, K, etc. SVM is a promising tool in developing automated preoperative glioma grading system, especially when being combined with RFE strategy. Model parameters should be considered in glioma grading model optimization.

Study of the Effect of Lubricant Emulsion Percentage and Tool Material on Surface Roughness in Machining of EN-AC 48000 Alloy

NASA Astrophysics Data System (ADS)

Soltani, E.; Shahali, H.; Zarepour, H.

2011-01-01

In this paper, the effect of machining parameters, namely, lubricant emulsion percentage and tool material on surface roughness has been studied in machining process of EN-AC 48000 aluminum alloy. EN-AC 48000 aluminum alloy is an important alloy in industries. Machining of this alloy is of vital importance due to built-up edge and tool wear. A L9 Taguchi standard orthogonal array has been applied as experimental design to investigate the effect of the factors and their interaction. Nine machining tests have been carried out with three random replications resulting in 27 experiments. Three type of cutting tools including coated carbide (CD1810), uncoated carbide (H10), and polycrystalline diamond (CD10) have been used in this research. Emulsion percentage of lubricant is selected at three levels including 3%, 5% and 10%. Statistical analysis has been employed to study the effect of factors and their interactions using ANOVA method. Moreover, the optimal factors level has been achieved through signal to noise ratio (S/N) analysis. Also, a regression model has been provided to predict the surface roughness. Finally, the results of the confirmation tests have been presented to verify the adequacy of the predictive model. In this research, surface quality was improved by 9% using lubricant and statistical optimization method.

Grinding, Machining Morphological Studies on C/SiC Composites

NASA Astrophysics Data System (ADS)

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.

Influence of Electrical Resistivity and Machining Parameters on Electrical Discharge Machining Performance of Engineering Ceramics

PubMed Central

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 machining ZnO/Al2O3 ceramic. PMID:25364912

Product modular design incorporating preventive maintenance issues

NASA Astrophysics Data System (ADS)

Gao, Yicong; Feng, Yixiong; Tan, Jianrong

2016-03-01

Traditional modular design methods lead to product maintenance problems, because the module form of a system is created according to either the function requirements or the manufacturing considerations. For solving these problems, a new modular design method is proposed with the considerations of not only the traditional function related attributes, but also the maintenance related ones. First, modularity parameters and modularity scenarios for product modularity are defined. Then the reliability and economic assessment models of product modularity strategies are formulated with the introduction of the effective working age of modules. A mathematical model used to evaluate the difference among the modules of the product so that the optimal module of the product can be established. After that, a multi-objective optimization problem based on metrics for preventive maintenance interval different degrees and preventive maintenance economics is formulated for modular optimization. Multi-objective GA is utilized to rapidly approximate the Pareto set of optimal modularity strategy trade-offs between preventive maintenance cost and preventive maintenance interval difference degree. Finally, a coordinate CNC boring machine is adopted to depict the process of product modularity. In addition, two factorial design experiments based on the modularity parameters are constructed and analyzed. These experiments investigate the impacts of these parameters on the optimal modularity strategies and the structure of module. The research proposes a new modular design method, which may help to improve the maintainability of product in modular design.

Swept Mechanism of Micro-Milling Tool Geometry Effect on Machined Oxygen Free High Conductivity Copper (OFHC) Surface Roughness

PubMed Central

Shi, Zhenyu; Liu, Zhanqiang; Li, Yuchao; Qiao, Yang

2017-01-01

Cutting tool geometry should be very much considered in micro-cutting because it has a significant effect on the topography and accuracy of the machined surface, particularly considering the uncut chip thickness is comparable to the cutting edge radius. The objective of this paper was to clarify the influence of the mechanism of the cutting tool geometry on the surface topography in the micro-milling process. Four different cutting tools including two two-fluted end milling tools with different helix angles of 15° and 30° cutting tools, as well as two three-fluted end milling tools with different helix angles of 15° and 30° were investigated by combining theoretical modeling analysis with experimental research. The tool geometry was mathematically modeled through coordinate translation and transformation to make all three cutting edges at the cutting tool tip into the same coordinate system. Swept mechanisms, minimum uncut chip thickness, and cutting tool run-out were considered on modeling surface roughness parameters (the height of surface roughness Rz and average surface roughness Ra) based on the established mathematical model. A set of cutting experiments was carried out using four different shaped cutting tools. It was found that the sweeping volume of the cutting tool increases with the decrease of both the cutting tool helix angle and the flute number. Great coarse machined surface roughness and more non-uniform surface topography are generated when the sweeping volume increases. The outcome of this research should bring about new methodologies for micro-end milling tool design and manufacturing. The machined surface roughness can be improved by appropriately selecting the tool geometrical parameters. PMID:28772479

Pushing the MAX IV 3 GeV storage ring brightness and coherence towards the limit of its magnetic lattice

NASA Astrophysics Data System (ADS)

Leemann, S. C.; Wurtz, W. A.

2018-03-01

The MAX IV 3 GeV storage ring is presently being commissioned and crucial parameters such as machine functions, emittance, and stored current have either already been reached or are approaching their design specifications. Once the baseline performance has been achieved, a campaign will be launched to further improve the brightness and coherence of this storage ring for typical X-ray users. During recent years, several such improvements have been designed. Common to these approaches is that they attempt to improve the storage ring performance using existing hardware provided for the baseline design. Such improvements therefore present more short-term upgrades. In this paper, however, we investigate medium-term improvements assuming power supplies can be exchanged in an attempt to push the brightness and coherence of the storage ring to the limit of what can be achieved without exchanging the magnetic lattice itself. We outline optics requirements, the optics optimization process, and summarize achievable parameters and expected performance.

High speed operation of permanent magnet machines

NASA Astrophysics Data System (ADS)

El-Refaie, Ayman M.

This work proposes methods to extend the high-speed operating capabilities of both the interior PM (IPM) and surface PM (SPM) machines. For interior PM machines, this research has developed and presented the first thorough analysis of how a new bi-state magnetic material can be usefully applied to the design of IPM machines. Key elements of this contribution include identifying how the unique properties of the bi-state magnetic material can be applied most effectively in the rotor design of an IPM machine by "unmagnetizing" the magnet cavity center posts rather than the outer bridges. The importance of elevated rotor speed in making the best use of the bi-state magnetic material while recognizing its limitations has been identified. For surface PM machines, this research has provided, for the first time, a clear explanation of how fractional-slot concentrated windings can be applied to SPM machines in order to achieve the necessary conditions for optimal flux weakening. A closed-form analytical procedure for analyzing SPM machines designed with concentrated windings has been developed. Guidelines for designing SPM machines using concentrated windings in order to achieve optimum flux weakening are provided. Analytical and numerical finite element analysis (FEA) results have provided promising evidence of the scalability of the concentrated winding technique with respect to the number of poles, machine aspect ratio, and output power rating. Useful comparisons between the predicted performance characteristics of SPM machines equipped with concentrated windings and both SPM and IPM machines designed with distributed windings are included. Analytical techniques have been used to evaluate the impact of the high pole number on various converter performance metrics. Both analytical techniques and FEA have been used for evaluating the eddy-current losses in the surface magnets due to the stator winding subharmonics. Techniques for reducing these losses have been investigated. A 6kW, 36slot/30pole prototype SPM machine has been designed and built. Experimental measurements have been used to verify the analytical and FEA results. These test results have demonstrated that wide constant-power speed range can be achieved. Other important machine features such as the near-sinusoidal back-emf, high efficiency, and low cogging torque have also been demonstrated.

Design and Experimental Validation for Direct-Drive Fault-Tolerant Permanent-Magnet Vernier Machines

PubMed Central

Liu, Guohai; Yang, Junqin; Chen, Ming; Chen, Qian

2014-01-01

A fault-tolerant permanent-magnet vernier (FT-PMV) machine is designed for direct-drive applications, incorporating the merits of high torque density and high reliability. Based on the so-called magnetic gearing effect, PMV machines have the ability of high torque density by introducing the flux-modulation poles (FMPs). This paper investigates the fault-tolerant characteristic of PMV machines and provides a design method, which is able to not only meet the fault-tolerant requirements but also keep the ability of high torque density. The operation principle of the proposed machine has been analyzed. The design process and optimization are presented specifically, such as the combination of slots and poles, the winding distribution, and the dimensions of PMs and teeth. By using the time-stepping finite element method (TS-FEM), the machine performances are evaluated. Finally, the FT-PMV machine is manufactured, and the experimental results are presented to validate the theoretical analysis. PMID:25045729

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

NASA Astrophysics Data System (ADS)

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.

Improved transistor-controlled and commutated brushless DC motors for electric vehicle propulsion

NASA Technical Reports Server (NTRS)

Demerdash, N. A.; Miller, R. H.; Nehl, T. W.; Nyamusa, T. A.

1983-01-01

The development, design, construction, and testing processes of two electronically (transistor) controlled and commutated permanent magnet brushless dc machine systems, for propulsion of electric vehicles are detailed. One machine system was designed and constructed using samarium cobalt for permanent magnets, which supply the rotor (field) excitation. Meanwhile, the other machine system was designed and constructed with strontium ferrite permanent magnets as the source of rotor (field) excitation. These machine systems were designed for continuous rated power output of 15 hp (11.2 kw), and a peak one minute rated power output of 35 hp (26.1 kw). Both power ratings are for a rated voltage of 115 volts dc, assuming a voltage drop in the source (battery) of about 5 volts. That is, an internal source voltage of 120 volts dc. Machine-power conditioner system computer-aided simulations were used extensively in the design process. These simulations relied heavily on the magnetic field analysis in these machines using the method of finite elements, as well as methods of modeling of the machine power conditioner system dynamic interaction. These simulation processes are detailed. Testing revealed that typical machine system efficiencies at 15 hp (11.2 kw) were about 88% and 84% for the samarium cobalt and strontium ferrite based machine systems, respectively. Both systems met the peak one minute rating of 35 hp.

Sensitivity and specificity of machine learning classifiers for glaucoma diagnosis using Spectral Domain OCT and standard automated perimetry.

PubMed

Silva, Fabrício R; Vidotti, Vanessa G; Cremasco, Fernanda; Dias, Marcelo; Gomi, Edson S; Costa, Vital P

2013-01-01

To evaluate the sensitivity and specificity of machine learning classifiers (MLCs) for glaucoma diagnosis using Spectral Domain OCT (SD-OCT) and standard automated perimetry (SAP). Observational cross-sectional study. Sixty two glaucoma patients and 48 healthy individuals were included. All patients underwent a complete ophthalmologic examination, achromatic standard automated perimetry (SAP) and retinal nerve fiber layer (RNFL) imaging with SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec Inc., Dublin, California). Receiver operating characteristic (ROC) curves were obtained for all SD-OCT parameters and global indices of SAP. Subsequently, the following MLCs were tested using parameters from the SD-OCT and SAP: Bagging (BAG), Naive-Bayes (NB), Multilayer Perceptron (MLP), Radial Basis Function (RBF), Random Forest (RAN), Ensemble Selection (ENS), Classification Tree (CTREE), Ada Boost M1(ADA),Support Vector Machine Linear (SVML) and Support Vector Machine Gaussian (SVMG). Areas under the receiver operating characteristic curves (aROC) obtained for isolated SAP and OCT parameters were compared with MLCs using OCT+SAP data. Combining OCT and SAP data, MLCs' aROCs varied from 0.777(CTREE) to 0.946 (RAN).The best OCT+SAP aROC obtained with RAN (0.946) was significantly larger the best single OCT parameter (p<0.05), but was not significantly different from the aROC obtained with the best single SAP parameter (p=0.19). Machine learning classifiers trained on OCT and SAP data can successfully discriminate between healthy and glaucomatous eyes. The combination of OCT and SAP measurements improved the diagnostic accuracy compared with OCT data alone.

Modelling of tunnelling processes and rock cutting tool wear with the particle finite element method

NASA Astrophysics Data System (ADS)

Carbonell, Josep Maria; Oñate, Eugenio; Suárez, Benjamín

2013-09-01

Underground construction involves all sort of challenges in analysis, design, project and execution phases. The dimension of tunnels and their structural requirements are growing, and so safety and security demands do. New engineering tools are needed to perform a safer planning and design. This work presents the advances in the particle finite element method (PFEM) for the modelling and the analysis of tunneling processes including the wear of the cutting tools. The PFEM has its foundation on the Lagrangian description of the motion of a continuum built from a set of particles with known physical properties. The method uses a remeshing process combined with the alpha-shape technique to detect the contacting surfaces and a finite element method for the mechanical computations. A contact procedure has been developed for the PFEM which is combined with a constitutive model for predicting the excavation front and the wear of cutting tools. The material parameters govern the coupling of frictional contact and wear between the interacting domains at the excavation front. The PFEM allows predicting several parameters which are relevant for estimating the performance of a tunnelling boring machine such as wear in the cutting tools, the pressure distribution on the face of the boring machine and the vibrations produced in the machinery and the adjacent soil/rock. The final aim is to help in the design of the excavating tools and in the planning of the tunnelling operations. The applications presented show that the PFEM is a promising technique for the analysis of tunnelling problems.

A novel electromagnetic design and a new manufacturing process for the cavity BPM (Beam Position Monitor)

NASA Astrophysics Data System (ADS)

Dal Forno, Massimo; Craievich, Paolo; Baruzzo, Roberto; De Monte, Raffaele; Ferianis, Mario; Lamanna, Giuseppe; Vescovo, Roberto

2012-01-01

The Cavity Beam Position Monitor (BPM) is a beam diagnostic instrument which, in a seeded Free Electron Laser (FEL), allows the measurement of the electron beam position in a non-destructive way and with sub-micron resolution. It is composed by two resonant cavities called reference and position cavity, respectively. The measurement exploits the dipole mode that arises when the electron bunch passes off axis. In this paper we describe the Cavity BPM that has been designed and realized in the context of the FERMI@Elettra project [1]. New strategies have been adopted for the microwave design, for both the reference and the position cavities. Both cavities have been simulated by means of Ansoft HFSS [2] and CST Particle Studio [3], and have been realized using high precision lathe and wire-EDM (Electro-Discharge) machine, with a new technique that avoids the use of the sinker-EDM machine. Tuners have been used to accurately adjust the working frequencies for both cavities. The RF parameters have been estimated, and the modifications of the resonant frequencies produced by brazing and tuning have been evaluated. Finally, the Cavity BPM has been installed and tested in the presence of the electron beam.

Parameter estimation using meta-heuristics in systems biology: a comprehensive review.

PubMed

Sun, Jianyong; Garibaldi, Jonathan M; Hodgman, Charlie

2012-01-01

This paper gives a comprehensive review of the application of meta-heuristics to optimization problems in systems biology, mainly focussing on the parameter estimation problem (also called the inverse problem or model calibration). It is intended for either the system biologist who wishes to learn more about the various optimization techniques available and/or the meta-heuristic optimizer who is interested in applying such techniques to problems in systems biology. First, the parameter estimation problems emerging from different areas of systems biology are described from the point of view of machine learning. Brief descriptions of various meta-heuristics developed for these problems follow, along with outlines of their advantages and disadvantages. Several important issues in applying meta-heuristics to the systems biology modelling problem are addressed, including the reliability and identifiability of model parameters, optimal design of experiments, and so on. Finally, we highlight some possible future research directions in this field.

An experimental analysis of process parameters to manufacture micro-channels in AISI H13 tempered steel by laser micro-milling

NASA Astrophysics Data System (ADS)

Teixidor, D.; Ferrer, I.; Ciurana, J.

2012-04-01

This paper reports the characterization of laser machining (milling) process to manufacture micro-channels in order to understand the incidence of process parameters on the final features. Selection of process operational parameters is highly critical for successful laser micromachining. A set of designed experiments is carried out in a pulsed Nd:YAG laser system using AISI H13 hardened tool steel as work material. Several micro-channels have been manufactured as micro-mold cavities varying parameters such as scanning speed (SS), pulse intensity (PI) and pulse frequency (PF). Results are obtained by evaluating the dimensions and the surface finish of the micro-channel. The dimensions and shape of the micro-channels produced with laser-micro-milling process exhibit variations. In general the use of low scanning speeds increases the quality of the feature in both surface finishing and dimensional.

Robust Online Hamiltonian Learning

NASA Astrophysics Data System (ADS)

Granade, Christopher; Ferrie, Christopher; Wiebe, Nathan; Cory, David

2013-05-01

In this talk, we introduce a machine-learning algorithm for the problem of inferring the dynamical parameters of a quantum system, and discuss this algorithm in the example of estimating the precession frequency of a single qubit in a static field. Our algorithm is designed with practicality in mind by including parameters that control trade-offs between the requirements on computational and experimental resources. The algorithm can be implemented online, during experimental data collection, or can be used as a tool for post-processing. Most importantly, our algorithm is capable of learning Hamiltonian parameters even when the parameters change from experiment-to-experiment, and also when additional noise processes are present and unknown. Finally, we discuss the performance of the our algorithm by appeal to the Cramer-Rao bound. This work was financially supported by the Canadian government through NSERC and CERC and by the United States government through DARPA. NW would like to acknowledge funding from USARO-DTO.

Technological and economical analysis of salient pole and permanent magnet synchronous machines designed for wind turbines

NASA Astrophysics Data System (ADS)

Gündoğdu, Tayfun; Kömürgöz, Güven

2012-08-01

Chinese export restrictions already reduced the planning reliability for investments in permanent magnet wind turbines. Today the production of permanent magnets consumes the largest proportion of rare earth elements, with 40% of the rare earth-based magnets used for generators and other electrical machines. The cost and availability of NdFeB magnets will likely determine the production rate of permanent magnet generators. The high volatility of rare earth metals makes it very difficult to quote a price. Prices may also vary from supplier to supplier to an extent of up to 50% for the same size, shape and quantity with a minor difference in quality. The paper presents the analysis and the comparison of salient pole with field winding and of peripheral winding synchronous electrical machines, presenting important advantages. A neodymium alloy magnet rotor structure has been considered and compared to the salient rotor case. The Salient Pole Synchronous Machine and the Permanent Magnet Synchronous Machine were designed so that the plate values remain constant. The Eddy current effect on the windings is taken into account during the design, and the efficiency, output power and the air-gap flux density obtained after the simulation were compared. The analysis results clearly indicate that Salient Pole Synchronous Machine designs would be attractive to wind power companies. Furthermore, the importance of the design of electrical machines and the determination of criteria are emphasized. This paper will be a helpful resource in terms of examination and comparison of the basic structure and magnetic features of the Salient Pole Synchronous Machine and Permanent Magnet Synchronous Machine. Furthermore, an economic analysis of the designed machines was conducted.

A Brief Description of My Projects

NASA Technical Reports Server (NTRS)

Barnes, Tobin

2016-01-01

My internship was in the IDC which consist of a machine shop and an array of design space. During my tour I worked on a wide variety of projects some of which included design, research, machining and fabrication. I gained further knowledge on some machines that I have had prior experience on such as the lathe and Hurco CNC machines. The first thing we did was complete our checkout in the machine shop which went pretty well, since I was already familiar with most of the machines. I also did a couple of practice parts on some of the machines, I made a name block on the CNC machine and I also used the vertical milling machine to complete this project. One of the other projects that I did was machine a hammer with my initials with the use of the lathe and CNC machine, this project took much longer since I had to set up a cylindrical piece on the CNC machine. The first project that I began work on was the Systems Engineering & Management Advancement Program (SEPMAP) Hexacopter project and helped them to assemble and modify one of their particle capture doors on their boxes. After a while we ended up helping them make a hinge and holes to reduce the weight of their design. We helped the NASA Extreme Environment Mission Operations (NEEMO) team a bit with some of their name tags and assembly of some of their underwater parts. One of the more challenging projects was a rail that came in with a rather weirdly drawn part. The biggest project that I worked on was the solar array project. Which consisted of a variety of machining and 3D printing and it took me about 3 different times of re-designing to come up with a final prototype. Along with this project I also had to complete a project in which I had to modify a thermos. This was rather simple since I just had to draw up a part and print it out on the 3D printer. I also learned how to use Pro E/Creo parametric to design a square block and print it on the 3D Printer. All of these projects increased my experience on all of the machines and equipment that I used. I also got to tweak my design skills and better understand how to modify my designs and how to improve those specific designs.

Automated Design Space Exploration with Aspen

DOE Office of Scientific and Technical Information (OSTI.GOV)

Spafford, Kyle L.; Vetter, Jeffrey S.

Architects and applications scientists often use performance models to explore a multidimensional design space of architectural characteristics, algorithm designs, and application parameters. With traditional performance modeling tools, these explorations forced users to first develop a performance model and then repeatedly evaluate and analyze the model manually. These manual investigations proved laborious and error prone. More importantly, the complexity of this traditional process often forced users to simplify their investigations. To address this challenge of design space exploration, we extend our Aspen (Abstract Scalable Performance Engineering Notation) language with three new language constructs: user-defined resources, parameter ranges, and a collection ofmore » costs in the abstract machine model. Then, we use these constructs to enable automated design space exploration via a nonlinear optimization solver. We show how four interesting classes of design space exploration scenarios can be derived from Aspen models and formulated as pure nonlinear programs. The analysis tools are demonstrated using examples based on Aspen models for a three-dimensional Fast Fourier Transform, the CoMD molecular dynamics proxy application, and the DARPA Streaming Sensor Challenge Problem. Our results show that this approach can compose and solve arbitrary performance modeling questions quickly and rigorously when compared to the traditional manual approach.« less

Automated Design Space Exploration with Aspen

DOE PAGES

Spafford, Kyle L.; Vetter, Jeffrey S.

2015-01-01

Architects and applications scientists often use performance models to explore a multidimensional design space of architectural characteristics, algorithm designs, and application parameters. With traditional performance modeling tools, these explorations forced users to first develop a performance model and then repeatedly evaluate and analyze the model manually. These manual investigations proved laborious and error prone. More importantly, the complexity of this traditional process often forced users to simplify their investigations. To address this challenge of design space exploration, we extend our Aspen (Abstract Scalable Performance Engineering Notation) language with three new language constructs: user-defined resources, parameter ranges, and a collection ofmore » costs in the abstract machine model. Then, we use these constructs to enable automated design space exploration via a nonlinear optimization solver. We show how four interesting classes of design space exploration scenarios can be derived from Aspen models and formulated as pure nonlinear programs. The analysis tools are demonstrated using examples based on Aspen models for a three-dimensional Fast Fourier Transform, the CoMD molecular dynamics proxy application, and the DARPA Streaming Sensor Challenge Problem. Our results show that this approach can compose and solve arbitrary performance modeling questions quickly and rigorously when compared to the traditional manual approach.« less

Comparisons between designs for single-sided linear electric motors: Homopolar synchronous and induction

NASA Astrophysics Data System (ADS)

Nondahl, T. A.; Richter, E.

1980-09-01

A design study of two types of single sided (with a passive rail) linear electric machine designs, namely homopolar linear synchronous machines (LSM's) and linear induction machines (LIM's), is described. It is assumed the machines provide tractive effort for several types of light rail vehicles and locomotives. These vehicles are wheel supported and require tractive powers ranging from 200 kW to 3735 kW and top speeds ranging from 112 km/hr to 400 km/hr. All designs are made according to specified magnetic and thermal criteria. The LSM advantages are a higher power factor, much greater restoring forces for track misalignments, and less track heating. The LIM advantages are no need to synchronize the excitation frequency precisely to vehicle speed, simpler machine construction, and a more easily anchored track structure. The relative weights of the two machine types vary with excitation frequency and speed; low frequencies and low speeds favor the LSM.

Quantification of uncertainty in machining operations for on-machine acceptance.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Claudet, Andre A.; Tran, Hy D.; Su, Jiann-Chemg

2008-09-01

Manufactured parts are designed with acceptance tolerances, i.e. deviations from ideal design conditions, due to unavoidable errors in the manufacturing process. It is necessary to measure and evaluate the manufactured part, compared to the nominal design, to determine whether the part meets design specifications. The scope of this research project is dimensional acceptance of machined parts; specifically, parts machined using numerically controlled (NC, or also CNC for Computer Numerically Controlled) machines. In the design/build/accept cycle, the designer will specify both a nominal value, and an acceptable tolerance. As part of the typical design/build/accept business practice, it is required to verifymore » that the part did meet acceptable values prior to acceptance. Manufacturing cost must include not only raw materials and added labor, but also the cost of ensuring conformance to specifications. Ensuring conformance is a substantial portion of the cost of manufacturing. In this project, the costs of measurements were approximately 50% of the cost of the machined part. In production, cost of measurement would be smaller, but still a substantial proportion of manufacturing cost. The results of this research project will point to a science-based approach to reducing the cost of ensuring conformance to specifications. The approach that we take is to determine, a priori, how well a CNC machine can manufacture a particular geometry from stock. Based on the knowledge of the manufacturing process, we are then able to decide features which need further measurements from features which can be accepted 'as is' from the CNC. By calibration of the machine tool, and establishing a machining accuracy ratio, we can validate the ability of CNC to fabricate to a particular level of tolerance. This will eliminate the costs of checking for conformance for relatively large tolerances.« less

Analytical Model-Based Design Optimization of a Transverse Flux Machine

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hasan, Iftekhar; Husain, Tausif; Sozer, Yilmaz

This paper proposes an analytical machine design tool using magnetic equivalent circuit (MEC)-based particle swarm optimization (PSO) for a double-sided, flux-concentrating transverse flux machine (TFM). The magnetic equivalent circuit method is applied to analytically establish the relationship between the design objective and the input variables of prospective TFM designs. This is computationally less intensive and more time efficient than finite element solvers. A PSO algorithm is then used to design a machine with the highest torque density within the specified power range along with some geometric design constraints. The stator pole length, magnet length, and rotor thickness are the variablesmore » that define the optimization search space. Finite element analysis (FEA) was carried out to verify the performance of the MEC-PSO optimized machine. The proposed analytical design tool helps save computation time by at least 50% when compared to commercial FEA-based optimization programs, with results found to be in agreement with less than 5% error.« less

The laser micro-machining system for diamond anvil cell experiments and general precision machining applications at the High Pressure Collaborative Access Team

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hrubiak, Rostislav; Sinogeikin, Stanislav; Rod, Eric

We have designed and constructed a new system for micro-machining parts and sample assemblies used for diamond anvil cells and general user operations at the High Pressure Collaborative Access Team, sector 16 of the Advanced Photon Source. The new micro-machining system uses a pulsed laser of 400 ps pulse duration, ablating various materials without thermal melting, thus leaving a clean edge. With optics designed for a tight focus, the system can machine holes any size larger than 3 μm in diameter. Unlike a standard electrical discharge machining drill, the new laser system allows micro-machining of non-conductive materials such as: amorphousmore » boron and silicon carbide gaskets, diamond, oxides, and other materials including organic materials such as polyimide films (i.e., Kapton). An important feature of the new system is the use of gas-tight or gas-flow environmental chambers which allow the laser micro-machining to be done in a controlled (e.g., inert gas) atmosphere to prevent oxidation and other chemical reactions in air sensitive materials. The gas-tight workpiece enclosure is also useful for machining materials with known health risks (e.g., beryllium). Specialized control software with a graphical interface enables micro-machining of custom 2D and 3D shapes. The laser-machining system was designed in a Class 1 laser enclosure, i.e., it includes laser safety interlocks and computer controls and allows for routine operation. Though initially designed mainly for machining of the diamond anvil cell gaskets, the laser-machining system has since found many other micro-machining applications, several of which are presented here.« less

Effect of cutting parameters on strain hardening of nickel–titanium shape memory alloy

NASA Astrophysics Data System (ADS)

Wang, Guijie; Liu, Zhanqiang; Ai, Xing; Huang, Weimin; Niu, Jintao

2018-07-01

Nickel–titanium shape memory alloy (SMA) has been widely used as implant materials due to its good biocompatibility, shape memory property and super-elasticity. However, the severe strain hardening is a main challenge due to cutting force and temperature caused by machining. An orthogonal experiment of nickel–titanium SMA with different milling parameters conditions was conducted in this paper. On the one hand, the effect of cutting parameters on work hardening is obtained. It is found that the cutting speed has the most important effect on work hardening. The depth of machining induced layer and the degree of hardening become smaller with the increase of cutting speed when the cutting speed is less than 200 m min‑1 and then get larger with further increase of cutting speed. The relative intensity of diffraction peak increases as the cutting speed increase. In addition, all of the depth of machining induced layer, the degree of hardening and the relative intensity of diffraction peak increase when the feed rate increases. On the other hand, it is found that the depth of machining induced layer is closely related with the degree of hardening and phase transition. The higher the content of austenite in the machined surface is, the higher the degree of hardening will be. The depth of the machining induced layer increases with the degree of hardening increasing.

Prediction of surface roughness and cutting force under MQL turning of AISI 4340 with nano fluid by using response surface methodology

NASA Astrophysics Data System (ADS)

Patole, Pralhad B.; Kulkarni, Vivek V.

2018-06-01

This paper presents an investigation into the minimum quantity lubrication mode with nano fluid during turning of alloy steel AISI 4340 work piece material with the objective of experimental model in order to predict surface roughness and cutting force and analyze effect of process parameters on machinability. Full factorial design matrix was used for experimental plan. According to design of experiment surface roughness and cutting force were measured. The relationship between the response variables and the process parameters is determined through the response surface methodology, using a quadratic regression model. Results show how much surface roughness is mainly influenced by feed rate and cutting speed. The depth of cut exhibits maximum influence on cutting force components as compared to the feed rate and cutting speed. The values predicted from the model and experimental values are very close to each other.

Numerical Simulation of Earth Pressure on Head Chamber of Shield Machine with FEM

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li Shouju; Kang Chengang; Sun, Wei

2010-05-21

Model parameters of conditioned soils in head chamber of shield machine are determined based on tree-axial compression tests in laboratory. The loads acting on tunneling face are estimated according to static earth pressure principle. Based on Duncan-Chang nonlinear elastic constitutive model, the earth pressures on head chamber of shield machine are simulated in different aperture ratio cases for rotating cutterhead of shield machine. Relationship between pressure transportation factor and aperture ratio of shield machine is proposed by using aggression analysis.

Mars vertical axis wind machines. The design of a Darreus and a Giromill for use on Mars

NASA Astrophysics Data System (ADS)

Brach, David; Dube, John; Kelly, Jon; Peterson, Joanna; Bollig, John; Gohr, Lisa; Mahoney, Kamin; Polidori, Dave

1992-05-01

This report contains the design of both a Darrieus and a Giromill for use on Mars. The report has been organized so that the interested reader may read only about one machine without having to read the entire report. Where components for the two machines differ greatly, separate sections have been allotted for each machine. Each section is complete; therefore, no relevant information is missed by reading only the section for the machine of interest. Also, when components for both machines are similar, both machines have been combined into one section. This is done so that the reader interested in both machines need not read the same information twice.

Mars vertical axis wind machines. The design of a Darreus and a Giromill for use on Mars

NASA Technical Reports Server (NTRS)

Brach, David; Dube, John; Kelly, Jon; Peterson, Joanna; Bollig, John; Gohr, Lisa; Mahoney, Kamin; Polidori, Dave

1992-01-01

This report contains the design of both a Darrieus and a Giromill for use on Mars. The report has been organized so that the interested reader may read only about one machine without having to read the entire report. Where components for the two machines differ greatly, separate sections have been allotted for each machine. Each section is complete; therefore, no relevant information is missed by reading only the section for the machine of interest. Also, when components for both machines are similar, both machines have been combined into one section. This is done so that the reader interested in both machines need not read the same information twice.

The strength study of the rotating device driver indexing spatial mechanism

NASA Astrophysics Data System (ADS)

Zakharenkov, N. V.; Kvasov, I. N.

2018-04-01

The indexing spatial mechanisms are widely used in automatic machines. The mechanisms maximum load-bearing capacity measurement is possible based on both the physical and numerical models tests results. The paper deals with the driven disk indexing spatial cam mechanism numerical model at the constant angular cam velocity. The presented mechanism kinematics and geometry parameters and finite element model are analyzed in the SolidWorks design environment. The calculation initial data and missing parameters having been found from the structure analysis were identified. The structure and kinematics analysis revealed the mechanism failures possible reasons. The numerical calculations results showing the structure performance at the contact and bending stresses are represented.

Machine Learning and Inverse Problem in Geodynamics

NASA Astrophysics Data System (ADS)

Shahnas, M. H.; Yuen, D. A.; Pysklywec, R.

2017-12-01

During the past few decades numerical modeling and traditional HPC have been widely deployed in many diverse fields for problem solutions. However, in recent years the rapid emergence of machine learning (ML), a subfield of the artificial intelligence (AI), in many fields of sciences, engineering, and finance seems to mark a turning point in the replacement of traditional modeling procedures with artificial intelligence-based techniques. The study of the circulation in the interior of Earth relies on the study of high pressure mineral physics, geochemistry, and petrology where the number of the mantle parameters is large and the thermoelastic parameters are highly pressure- and temperature-dependent. More complexity arises from the fact that many of these parameters that are incorporated in the numerical models as input parameters are not yet well established. In such complex systems the application of machine learning algorithms can play a valuable role. Our focus in this study is the application of supervised machine learning (SML) algorithms in predicting mantle properties with the emphasis on SML techniques in solving the inverse problem. As a sample problem we focus on the spin transition in ferropericlase and perovskite that may cause slab and plume stagnation at mid-mantle depths. The degree of the stagnation depends on the degree of negative density anomaly at the spin transition zone. The training and testing samples for the machine learning models are produced by the numerical convection models with known magnitudes of density anomaly (as the class labels of the samples). The volume fractions of the stagnated slabs and plumes which can be considered as measures for the degree of stagnation are assigned as sample features. The machine learning models can determine the magnitude of the spin transition-induced density anomalies that can cause flow stagnation at mid-mantle depths. Employing support vector machine (SVM) algorithms we show that SML techniques can successfully predict the magnitude of the mantle density anomalies and can also be used in characterizing mantle flow patterns. The technique can be extended to more complex problems in mantle dynamics by employing deep learning algorithms for estimation of mantle properties such as viscosity, elastic parameters, and thermal and chemical anomalies.

A feasibility study of automatic lung nodule detection in chest digital tomosynthesis with machine learning based on support vector machine

NASA Astrophysics Data System (ADS)

Lee, Donghoon; Kim, Ye-seul; Choi, Sunghoon; Lee, Haenghwa; Jo, Byungdu; Choi, Seungyeon; Shin, Jungwook; Kim, Hee-Joung

2017-03-01

The chest digital tomosynthesis(CDT) is recently developed medical device that has several advantage for diagnosing lung disease. For example, CDT provides depth information with relatively low radiation dose compared to computed tomography (CT). However, a major problem with CDT is the image artifacts associated with data incompleteness resulting from limited angle data acquisition in CDT geometry. For this reason, the sensitivity of lung disease was not clear compared to CT. In this study, to improve sensitivity of lung disease detection in CDT, we developed computer aided diagnosis (CAD) systems based on machine learning. For design CAD systems, we used 100 cases of lung nodules cropped images and 100 cases of normal lesion cropped images acquired by lung man phantoms and proto type CDT. We used machine learning techniques based on support vector machine and Gabor filter. The Gabor filter was used for extracting characteristics of lung nodules and we compared performance of feature extraction of Gabor filter with various scale and orientation parameters. We used 3, 4, 5 scales and 4, 6, 8 orientations. After extracting features, support vector machine (SVM) was used for classifying feature of lesions. The linear, polynomial and Gaussian kernels of SVM were compared to decide the best SVM conditions for CDT reconstruction images. The results of CAD system with machine learning showed the capability of automatically lung lesion detection. Furthermore detection performance was the best when Gabor filter with 5 scale and 8 orientation and SVM with Gaussian kernel were used. In conclusion, our suggested CAD system showed improving sensitivity of lung lesion detection in CDT and decide Gabor filter and SVM conditions to achieve higher detection performance of our developed CAD system for CDT.

Machine characterization based on an abstract high-level language machine

NASA Technical Reports Server (NTRS)

Saavedra-Barrera, Rafael H.; Smith, Alan Jay; Miya, Eugene

1989-01-01

Measurements are presented for a large number of machines ranging from small workstations to supercomputers. The authors combine these measurements into groups of parameters which relate to specific aspects of the machine implementation, and use these groups to provide overall machine characterizations. The authors also define the concept of pershapes, which represent the level of performance of a machine for different types of computation. A metric based on pershapes is introduced that provides a quantitative way of measuring how similar two machines are in terms of their performance distributions. The metric is related to the extent to which pairs of machines have varying relative performance levels depending on which benchmark is used.

The Bi-Directional Prediction of Carbon Fiber Production Using a Combination of Improved Particle Swarm Optimization and Support Vector Machine.

PubMed

Xiao, Chuncai; Hao, Kuangrong; Ding, Yongsheng

2014-12-30

This paper creates a bi-directional prediction model to predict the performance of carbon fiber and the productive parameters based on a support vector machine (SVM) and improved particle swarm optimization (IPSO) algorithm (SVM-IPSO). In the SVM, it is crucial to select the parameters that have an important impact on the performance of prediction. The IPSO is proposed to optimize them, and then the SVM-IPSO model is applied to the bi-directional prediction of carbon fiber production. The predictive accuracy of SVM is mainly dependent on its parameters, and IPSO is thus exploited to seek the optimal parameters for SVM in order to improve its prediction capability. Inspired by a cell communication mechanism, we propose IPSO by incorporating information of the global best solution into the search strategy to improve exploitation, and we employ IPSO to establish the bi-directional prediction model: in the direction of the forward prediction, we consider productive parameters as input and property indexes as output; in the direction of the backward prediction, we consider property indexes as input and productive parameters as output, and in this case, the model becomes a scheme design for novel style carbon fibers. The results from a set of the experimental data show that the proposed model can outperform the radial basis function neural network (RNN), the basic particle swarm optimization (PSO) method and the hybrid approach of genetic algorithm and improved particle swarm optimization (GA-IPSO) method in most of the experiments. In other words, simulation results demonstrate the effectiveness and advantages of the SVM-IPSO model in dealing with the problem of forecasting.

A sustainable solid state recycling of pure aluminum by means of friction stir extrusion process (FSE)

NASA Astrophysics Data System (ADS)

Mehtedi, Mohamad El; Forcellese, Archimede; Simoncini, Michela; Spigarelli, Stefano

2018-05-01

In this research, the feasibility of solid-state recycling of pure aluminum AA1099 machining chips using FSE process is investigated. In the early stage, a FE simulation was conducted in order to optimize the die design and the process parameters in terms of plunge rotational speed and extrusion rate. The AA1099 aluminum chips were produced by turning of an as-received bar without lubrication. The chips were compacted on a MTS machine up to 150KN of load. The extruded samples were analyzed by optical and electron microscope in order to see the material flow and to characterize the microstructure. Finally, micro-hardness Vickers profiles were carried out, in both longitudinal and transversal direction of the obtained profiles, in order to investigate the homogeneity of the mechanical properties of the extrudate.

Development of High vacuum facility for baking and cool down experiments for SST-1 Tokamak components

NASA Astrophysics Data System (ADS)

Khan, Ziauddin; Pathan, Firozkhan S.; Yuvakiran, Paravastu; George, Siju; Manthena, Himabindu; Raval, Dilip C.; Thankey, Prashant L.; Dhanani, Kalpesh R.; Gupta, Manoj Kumar; Pradhan, Subrata

2012-11-01

SST-1 Tokamak, a steady state super-conducting device, is under refurbishment to demonstrate the plasma discharge for the duration of 1000 second. The major fabricated components of SST-1 like vacuum vessel, thermal shields, superconducting magnets etc have to be tested for their functional parameters. During machine operation, vacuum vessel will be baked at 150 °C, thermal shields will be operated at 85 K and magnet system will be operated at 4.5 K. All these components must have helium leak tightness under these conditions so far as the machine operation is concerned. In order to validate the helium leak tightness of these components, in-house high vacuum chamber is fabricated. This paper describes the analysis, design and fabrication of high vacuum chamber to demonstrate these functionalities. Also some results will be presented.

A study on stimulation of DC high voltage power of LCC series parallel resonant in projectile velocity measurement system

NASA Astrophysics Data System (ADS)

Lu, Dong-dong; Gu, Jin-liang; Luo, Hong-e.; Xia, Yan

2017-10-01

According to specific requirements of the X-ray machine system for measuring velocity of outfield projectile, a DC high voltage power supply system is designed for the high voltage or the smaller current. The system comprises: a series resonant circuit is selected as a full-bridge inverter circuit; a high-frequency zero-current soft switching of a high-voltage power supply is realized by PWM output by STM32; a nanocrystalline alloy transformer is chosen as a high-frequency booster transformer; and the related parameters of an LCC series-parallel resonant are determined according to the preset parameters of the transformer. The concrete method includes: a LCC series parallel resonant circuit and a voltage doubling circuit are stimulated by using MULTISM and MATLAB; selecting an optimal solution and an optimal parameter of all parts after stimulation analysis; and finally verifying the correctness of the parameter by stimulation of the whole system. Through stimulation analysis, the output voltage of the series-parallel resonant circuit gets to 10KV in 28s: then passing through the voltage doubling circuit, the output voltage gets to 120KV in one hour. According to the system, the wave range of the output voltage is so small as to provide the stable X-ray supply for the X-ray machine for measuring velocity of outfield projectile. It is fast in charging and high in efficiency.

Kernel machines for epilepsy diagnosis via EEG signal classification: a comparative study.

PubMed

Lima, Clodoaldo A M; Coelho, André L V

2011-10-01

We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely, Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). Copyright © 2011 Elsevier B.V. All rights reserved.

Control and performance of the AGS and AGS Booster Main Magnet Power Supplies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reece, R.K.; Casella, R.; Culwick, B.

1993-06-01

Techniques for precision control of the main magnet power supplies for the AGS and AGS Booster synchrotron will be discussed. Both synchrotrons are designed to operate in a Pulse-to-Pulse Modulation (PPM) environment with a Supercycle Generator defining and distributing global timing events for the AGS Facility. Details of modelling, real-time feedback and feedforward systems, generation and distribution of real time field data, operational parameters and an overview of performance for both machines are included.

Control and performance of the AGS and AGS Booster Main Magnet Power Supplies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reece, R.K.; Casella, R.; Culwick, B.

1993-01-01

Techniques for precision control of the main magnet power supplies for the AGS and AGS Booster synchrotron will be discussed. Both synchrotrons are designed to operate in a Pulse-to-Pulse Modulation (PPM) environment with a Supercycle Generator defining and distributing global timing events for the AGS Facility. Details of modelling, real-time feedback and feedforward systems, generation and distribution of real time field data, operational parameters and an overview of performance for both machines are included.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Belley, M; Schmidt, M; Knutson, N

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 themore » 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 assessing the patient-specific plan-quality.« less

SU-E-T-473: A Patient-Specific QC Paradigm Based On Trajectory Log Files and DICOM Plan Files

DOE Office of Scientific and Technical Information (OSTI.GOV)

DeMarco, J; McCloskey, S; Low, D

Purpose: To evaluate a remote QC tool for monitoring treatment machine parameters and treatment workflow. Methods: The Varian TrueBeamTM linear accelerator is a digital machine that records machine axis parameters and MLC leaf positions as a function of delivered monitor unit or control point. This information is saved to a binary trajectory log file for every treatment or imaging field in the patient treatment session. A MATLAB analysis routine was developed to parse the trajectory log files for a given patient, compare the expected versus actual machine and MLC positions as well as perform a cross-comparison with the DICOM-RT planmore » file exported from the treatment planning system. The parsing routine sorts the trajectory log files based on the time and date stamp and generates a sequential report file listing treatment parameters and provides a match relative to the DICOM-RT plan file. Results: The trajectory log parsing-routine was compared against a standard record and verify listing for patients undergoing initial IMRT dosimetry verification and weekly and final chart QC. The complete treatment course was independently verified for 10 patients of varying treatment site and a total of 1267 treatment fields were evaluated including pre-treatment imaging fields where applicable. In the context of IMRT plan verification, eight prostate SBRT plans with 4-arcs per plan were evaluated based on expected versus actual machine axis parameters. The average value for the maximum RMS MLC error was 0.067±0.001mm and 0.066±0.002mm for leaf bank A and B respectively. Conclusion: A real-time QC analysis program was tested using trajectory log files and DICOM-RT plan files. The parsing routine is efficient and able to evaluate all relevant machine axis parameters during a patient treatment course including MLC leaf positions and table positions at time of image acquisition and during treatment.« less

Using Pipelined XNOR Logic to Reduce SEU Risks in State Machines

NASA Technical Reports Server (NTRS)

Le, Martin; Zheng, Xin; Katanyoutant, Sunant

2008-01-01

Single-event upsets (SEUs) pose great threats to avionic systems state machine control logic, which are frequently used to control sequence of events and to qualify protocols. The risks of SEUs manifest in two ways: (a) the state machine s state information is changed, causing the state machine to unexpectedly transition to another state; (b) due to the asynchronous nature of SEU, the state machine's state registers become metastable, consequently causing any combinational logic associated with the metastable registers to malfunction temporarily. Effect (a) can be mitigated with methods such as triplemodular redundancy (TMR). However, effect (b) cannot be eliminated and can degrade the effectiveness of any mitigation method of effect (a). Although there is no way to completely eliminate the risk of SEU-induced errors, the risk can be made very small by use of a combination of very fast state-machine logic and error-detection logic. Therefore, one goal of two main elements of the present method is to design the fastest state-machine logic circuitry by basing it on the fastest generic state-machine design, which is that of a one-hot state machine. The other of the two main design elements is to design fast error-detection logic circuitry and to optimize it for implementation in a field-programmable gate array (FPGA) architecture: In the resulting design, the one-hot state machine is fitted with a multiple-input XNOR gate for detection of illegal states. The XNOR gate is implemented with lookup tables and with pipelines for high speed. In this method, the task of designing all the logic must be performed manually because no currently available logic synthesis software tool can produce optimal solutions of design problems of this type. However, some assistance is provided by a script, written for this purpose in the Python language (an object-oriented interpretive computer language) to automatically generate hardware description language (HDL) code from state-transition rules.

Probabilistic Design Methodology and its Application to the Design of an Umbilical Retract Mechanism

NASA Technical Reports Server (NTRS)

Onyebueke, Landon; Ameye, Olusesan

2002-01-01

A lot has been learned from past experience with structural and machine element failures. The understanding of failure modes and the application of an appropriate design analysis method can lead to improved structural and machine element safety as well as serviceability. To apply Probabilistic Design Methodology (PDM), all uncertainties are modeled as random variables with selected distribution types, means, and standard deviations. It is quite difficult to achieve a robust design without considering the randomness of the design parameters which is the case in the use of the Deterministic Design Approach. The US Navy has a fleet of submarine-launched ballistic missiles. An umbilical plug joins the missile to the submarine in order to provide electrical and cooling water connections. As the missile leaves the submarine, an umbilical retract mechanism retracts the umbilical plug clear of the advancing missile after disengagement during launch and retrains the plug in the retracted position. The design of the current retract mechanism in use was based on the deterministic approach which puts emphasis on factor of safety. A new umbilical retract mechanism that is simpler in design, lighter in weight, more reliable, easier to adjust, and more cost effective has become desirable since this will increase the performance and efficiency of the system. This paper reports on a recent project performed at Tennessee State University for the US Navy that involved the application of PDM to the design of an umbilical retract mechanism. This paper demonstrates how the use of PDM lead to the minimization of weight and cost, and the maximization of reliability and performance.

Parameter monitoring compensation system and method

DOEpatents

Barkman, William E.; Babelay, Edwin F.; DeMint, Paul D.; Hebble, Thomas L.; Igou, Richard E.; Williams, Richard R.; Klages, Edward J.; Rasnick, William H.

1995-01-01

A compensation system for a computer-controlled machining apparatus having a controller and including a cutting tool and a workpiece holder which are movable relative to one another along preprogrammed path during a machining operation utilizes sensors for gathering information at a preselected stage of a machining operation relating to an actual condition. The controller compares the actual condition to a condition which the program presumes to exist at the preselected stage and alters the program in accordance with detected variations between the actual condition and the assumed condition. Such conditions may be related to process parameters, such as a position, dimension or shape of the cutting tool or workpiece or an environmental temperature associated with the machining operation, and such sensors may be a contact or a non-contact type of sensor or a temperature transducer.

Reducing the uncertainty in robotic machining by modal analysis

NASA Astrophysics Data System (ADS)

Alberdi, Iñigo; Pelegay, Jose Angel; Arrazola, Pedro Jose; Ørskov, Klaus Bonde

2017-10-01

The use of industrial robots for machining could lead to high cost and energy savings for the manufacturing industry. Machining robots offer several advantages respect to CNC machines such as flexibility, wide working space, adaptability and relatively low cost. However, there are some drawbacks that are preventing a widespread adoption of robotic solutions namely lower stiffness, vibration/chatter problems and lower accuracy and repeatability. Normally due to these issues conservative cutting parameters are chosen, resulting in a low material removal rate (MRR). In this article, an example of a modal analysis of a robot is presented. For that purpose the Tap-testing technology is introduced, which aims at maximizing productivity, reducing the uncertainty in the selection of cutting parameters and offering a stable process free from chatter vibrations.

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

NASA Astrophysics Data System (ADS)

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.

Effect of magnetic polarity on surface roughness during magnetic field assisted EDM of tool steel

NASA Astrophysics Data System (ADS)

Efendee, A. M.; Saifuldin, M.; Gebremariam, MA; Azhari, A.

2018-04-01

Electrical discharge machining (EDM) is one of the non-traditional machining techniques where the process offers wide range of parameters manipulation and machining applications. However, surface roughness, material removal rate, electrode wear and operation costs were among the topmost issue within this technique. Alteration of magnetic device around machining area offers exciting output to be investigated and the effects of magnetic polarity on EDM remain unacquainted. The aim of this research is to investigate the effect of magnetic polarity on surface roughness during magnetic field assisted electrical discharge machining (MFAEDM) on tool steel material (AISI 420 mod.) using graphite electrode. A Magnet with a force of 18 Tesla was applied to the EDM process at selected parameters. The sparks under magnetic field assisted EDM produced better surface finish than the normal conventional EDM process. At the presence of high magnetic field, the spark produced was squeezed and discharge craters generated on the machined surface was tiny and shallow. Correct magnetic polarity combination of MFAEDM process is highly useful to attain a high efficiency machining and improved quality of surface finish to meet the demand of modern industrial applications.

3D FE simulation of semi-finishing machining of Ti6Al4V additively manufactured by direct metal laser sintering

NASA Astrophysics Data System (ADS)

Imbrogno, Stano; Rinaldi, Sergio; Raso, Antonio; Bordin, Alberto; Bruschi, Stefania; Umbrello, Domenico

2018-05-01

The Additive Manufacturing techniques are gaining more and more interest in various industrial fields due to the possibility of drastically reduce the material waste during the production processes, revolutionizing the standard scheme and strategies of the manufacturing processes. However, the metal parts shape produced, frequently do not satisfy the tolerances as well as the surface quality requirements. During the design phase, the finite element simulation results a fundamental tool to help the engineers in the correct decision of the most suitable process parameters, especially in manufacturing processes, in order to produce products of high quality. The aim of this work is to develop a 3D finite element model of semi-finishing turning operation of Ti6Al4V, produced via Direct Metal Laser Sintering (DMLS). A customized user sub-routine was built-up in order to model the mechanical behavior of the material under machining operations to predict the main fundamental variables as cutting forces and temperature. Moreover, the machining induced alterations are also studied by the finite element model developed.

Calibrating Building Energy Models Using Supercomputer Trained Machine Learning Agents

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sanyal, Jibonananda; New, Joshua Ryan; Edwards, Richard

2014-01-01

Building Energy Modeling (BEM) is an approach to model the energy usage in buildings for design and retrofit purposes. EnergyPlus is the flagship Department of Energy software that performs BEM for different types of buildings. The input to EnergyPlus can often extend in the order of a few thousand parameters which have to be calibrated manually by an expert for realistic energy modeling. This makes it challenging and expensive thereby making building energy modeling unfeasible for smaller projects. In this paper, we describe the Autotune research which employs machine learning algorithms to generate agents for the different kinds of standardmore » reference buildings in the U.S. building stock. The parametric space and the variety of building locations and types make this a challenging computational problem necessitating the use of supercomputers. Millions of EnergyPlus simulations are run on supercomputers which are subsequently used to train machine learning algorithms to generate agents. These agents, once created, can then run in a fraction of the time thereby allowing cost-effective calibration of building models.« less

Performance characteristics and typical industrial applications of Selfshield® electron accelerators (< 300 kV)

NASA Astrophysics Data System (ADS)

Aaronson, Judith N.; Nablo, Sam V.

1985-05-01

Selfshielded electron accelerators have been successfully used in industry for more than ten years. One of the important advantages of these machines is their compactness for easy adaptation to conventional coating and product finishing machinery. It is equally important that these machines qualify for use under "unrestricted" conditions as specified by OSHA. The shielding and product handling configurations which make this unrestricted designation possible for operating voltages under 300 kV are discussed. Thin film dosimetry techniques used for the determination of the machine performance parameters are discussed along with the rotary scanner techniques employed for the dose rate studies which are important in the application of these processors. Paper and wood coatings, which are important industrial applications involving electron initiated polymerization, are reviewed. The sterilization and disinfestation applications are also discussed. The increasing concern of these industries for the more efficient use of energy and for compliance with more stringent pollution regulations, coupled with the novel processes this energy source makes possible, assure a bright future for this developing technology.

Design and experiment on 2KF-15 type disc cutter and shallow fertilization machine in rubber plantation

NASA Astrophysics Data System (ADS)

Deng, Yiguo; Zhang, Yuan; Wang, Yeqin

2017-12-01

At present, the trenching and fertilization machine has a serious weed plug problem when trenching and fertilization operation in rubber plantation. So a disc cutter and shallow fertilization machine in rubber plantation named 2KF-15 was designed, the design scheme used the front disc cutter cutting the grass, while using the rear of the disc furrow to trenching, the prototype of a disc anti-plugging trenching and shallow fertilization machine was completed. Afterwards, a series of trenching and fertilization field experiments were carried out, and the results showed that the ditching depth of this machine could achieve from 131 to 176 mm, and the average depth could reach 156 mm, the ditching depth stability coefficient could achieve 90.3%; The fertilizer amount of this machine could achieve from 113.2 to 156.4 kg/hm2, the average fertilizer amount reach 134.2kg/hm2, the fertilizer amount stability coefficient could achieve 89.6%, the fertilizer broken rate was 0%, the fertilizer coverage rate of 98.4%;The situation of fertilizer accumulation occurred less by using this machine, and the fertilization performance was relatively stable. This new designed machine for trenching, fertilization and covering the soil were carried out at the same time. So the number of operations could be effectively reduced. This new designed machine does not only meet the agronomic requirements of rubber plantation fertilization, but also provides a reference for the trenching and fertilization operation in other.

Micro- to Macroroughness of Additively Manufactured Titanium Implants in Terms of Coagulation and Contact Activation.

PubMed

Klingvall Ek, Rebecca; Hong, Jaan; Thor, Andreas; Bäckström, Mikael; Rännar, Lars-Erik

This study aimed to evaluate how as-built electron beam melting (EBM) surface properties affect the onset of blood coagulation. The properties of EBM-manufactured implant surfaces for placement have, until now, remained largely unexplored in literature. Implants with conventional designs and custom-made implants have been manufactured using EBM technology and later placed into the human body. Many of the conventional implants used today, such as dental implants, display modified surfaces to optimize bone ingrowth, whereas custom-made implants, by and large, have machined surfaces. However, titanium in itself demonstrates good material properties for the purpose of bone ingrowth. Specimens manufactured using EBM were selected according to their surface roughness and process parameters. EBM-produced specimens, conventional machined titanium surfaces, as well as PVC surfaces for control were evaluated using the slide chamber model. A significant increase in activation was found, in all factors evaluated, between the machined samples and EBM-manufactured samples. The results show that EBM-manufactured implants with as-built surfaces augment the thrombogenic properties. EBM that uses Ti6Al4V powder appears to be a good manufacturing solution for load-bearing implants with bone anchorage. The as-built surfaces can be used "as is" for direct bone contact, although any surface treatment available for conventional implants can be performed on EBM-manufactured implants with a conventional design.

Manufacturing conditioned roughness and wear of biomedical oxide ceramics for all-ceramic knee implants

PubMed Central

2013-01-01

Background Ceramic materials are used in a growing proportion of hip joint prostheses due to their wear resistance and biocompatibility properties. However, ceramics have not been applied successfully in total knee joint endoprostheses to date. One reason for this is that with strict surface quality requirements, there are significant challenges with regard to machining. High-toughness bioceramics can only be machined by grinding and polishing processes. The aim of this study was to develop an automated process chain for the manufacturing of an all-ceramic knee implant. Methods A five-axis machining process was developed for all-ceramic implant components. These components were used in an investigation of the influence of surface conformity on wear behavior under simplified knee joint motion. Results The implant components showed considerably reduced wear compared to conventional material combinations. Contact area resulting from a variety of component surface shapes, with a variety of levels of surface conformity, greatly influenced wear rate. Conclusions It is possible to realize an all-ceramic knee endoprosthesis device, with a precise and affordable manufacturing process. The shape accuracy of the component surfaces, as specified by the design and achieved during the manufacturing process, has a substantial influence on the wear behavior of the prosthesis. This result, if corroborated by results with a greater sample size, is likely to influence the design parameters of such devices. PMID:23988155

Manufacturing conditioned roughness and wear of biomedical oxide ceramics for all-ceramic knee implants.

PubMed

Turger, Anke; Köhler, Jens; Denkena, Berend; Correa, Tomas A; Becher, Christoph; Hurschler, Christof

2013-08-29

Ceramic materials are used in a growing proportion of hip joint prostheses due to their wear resistance and biocompatibility properties. However, ceramics have not been applied successfully in total knee joint endoprostheses to date. One reason for this is that with strict surface quality requirements, there are significant challenges with regard to machining. High-toughness bioceramics can only be machined by grinding and polishing processes. The aim of this study was to develop an automated process chain for the manufacturing of an all-ceramic knee implant. A five-axis machining process was developed for all-ceramic implant components. These components were used in an investigation of the influence of surface conformity on wear behavior under simplified knee joint motion. The implant components showed considerably reduced wear compared to conventional material combinations. Contact area resulting from a variety of component surface shapes, with a variety of levels of surface conformity, greatly influenced wear rate. It is possible to realize an all-ceramic knee endoprosthesis device, with a precise and affordable manufacturing process. The shape accuracy of the component surfaces, as specified by the design and achieved during the manufacturing process, has a substantial influence on the wear behavior of the prosthesis. This result, if corroborated by results with a greater sample size, is likely to influence the design parameters of such devices.

Differentially Private Empirical Risk Minimization

PubMed Central

Chaudhuri, Kamalika; Monteleoni, Claire; Sarwate, Anand D.

2011-01-01

Privacy-preserving machine learning algorithms are crucial for the increasingly common setting in which personal data, such as medical or financial records, are analyzed. We provide general techniques to produce privacy-preserving approximations of classifiers learned via (regularized) empirical risk minimization (ERM). These algorithms are private under the ε-differential privacy definition due to Dwork et al. (2006). First we apply the output perturbation ideas of Dwork et al. (2006), to ERM classification. Then we propose a new method, objective perturbation, for privacy-preserving machine learning algorithm design. This method entails perturbing the objective function before optimizing over classifiers. If the loss and regularizer satisfy certain convexity and differentiability criteria, we prove theoretical results showing that our algorithms preserve privacy, and provide generalization bounds for linear and nonlinear kernels. We further present a privacy-preserving technique for tuning the parameters in general machine learning algorithms, thereby providing end-to-end privacy guarantees for the training process. We apply these results to produce privacy-preserving analogues of regularized logistic regression and support vector machines. We obtain encouraging results from evaluating their performance on real demographic and benchmark data sets. Our results show that both theoretically and empirically, objective perturbation is superior to the previous state-of-the-art, output perturbation, in managing the inherent tradeoff between privacy and learning performance. PMID:21892342

Using machine learning to identify factors that govern amorphization of irradiated pyrochlores

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pilania, Ghanshyam; Whittle, Karl R.; Jiang, Chao

Structure–property relationships are a key materials science concept that enables the design of new materials. In the case of materials for application in radiation environments, correlating radiation tolerance with fundamental structural features of a material enables materials discovery. Here, we use a machine learning model to examine the factors that govern amorphization resistance in the complex oxide pyrochlore (A 2B 2O 7) in a regime in which amorphization occurs as a consequence of defect accumulation. We examine the fidelity of predictions based on cation radii and electronegativities, the oxygen positional parameter, and the energetics of disordering and amorphizing the material.more » No one factor alone adequately predicts amorphization resistance. We find that when multiple families of pyrochlores (with different B cations) are considered, radii and electronegativities provide the best prediction, but when the machine learning model is restricted to only the B = Ti pyrochlores, the energetics of disordering and amorphization are critical factors. We discuss how these static quantities provide insight into an inherently kinetic property such as amorphization resistance at finite temperature. Lastly, this work provides new insight into the factors that govern the amorphization susceptibility and highlights the ability of machine learning approaches to generate that insight.« less

High-Temperature Creep Behaviour and Positive Effect on Straightening Deformation of Q345c Continuous Casting Slab

NASA Astrophysics Data System (ADS)

Guo, Long; Zhang, Xingzhong

2018-03-01

Mechanical and creep properties of Q345c continuous casting slab subjected to uniaxial tensile tests at high temperature were considered in this paper. The minimum creep strain rate and creep rupture life equations whose parameters are calculated by inverse-estimation using the regression analysis were derived based on experimental data. The minimum creep strain rate under constant stress increases with the increase of the temperature from 1000 °C to 1200 °C. A new casting machine curve with the aim of fully using high-temperature creep behaviour is proposed in this paper. The basic arc segment is cancelled in the new curve so that length of the straightening area can be extended and time of creep behaviour can be increased significantly. For the new casting machine curve, the maximum straightening strain rate at the slab surface is less than the minimum creep strain rate. So slab straightening deformation based on the steel creep behaviour at high temperature can be carried out in the process of Q345c steel continuous casting. The effect of creep property at high temperature on slab straightening deformation is positive. It is helpful for the design of new casting machine and improvement of old casting machine.

Using machine learning to identify factors that govern amorphization of irradiated pyrochlores

DOE PAGES

Pilania, Ghanshyam; Whittle, Karl R.; Jiang, Chao; ...

2017-02-10

Structure–property relationships are a key materials science concept that enables the design of new materials. In the case of materials for application in radiation environments, correlating radiation tolerance with fundamental structural features of a material enables materials discovery. Here, we use a machine learning model to examine the factors that govern amorphization resistance in the complex oxide pyrochlore (A 2B 2O 7) in a regime in which amorphization occurs as a consequence of defect accumulation. We examine the fidelity of predictions based on cation radii and electronegativities, the oxygen positional parameter, and the energetics of disordering and amorphizing the material.more » No one factor alone adequately predicts amorphization resistance. We find that when multiple families of pyrochlores (with different B cations) are considered, radii and electronegativities provide the best prediction, but when the machine learning model is restricted to only the B = Ti pyrochlores, the energetics of disordering and amorphization are critical factors. We discuss how these static quantities provide insight into an inherently kinetic property such as amorphization resistance at finite temperature. Lastly, this work provides new insight into the factors that govern the amorphization susceptibility and highlights the ability of machine learning approaches to generate that insight.« less

Design of static synchronous series compensator based damping controller employing invasive weed optimization algorithm.

PubMed

Ahmed, Ashik; Al-Amin, Rasheduzzaman; Amin, Ruhul

2014-01-01

This paper proposes designing of Static Synchronous Series Compensator (SSSC) based damping controller to enhance the stability of a Single Machine Infinite Bus (SMIB) system by means of Invasive Weed Optimization (IWO) technique. Conventional PI controller is used as the SSSC damping controller which takes rotor speed deviation as the input. The damping controller parameters are tuned based on time integral of absolute error based cost function using IWO. Performance of IWO based controller is compared to that of Particle Swarm Optimization (PSO) based controller. Time domain based simulation results are presented and performance of the controllers under different loading conditions and fault scenarios is studied in order to illustrate the effectiveness of the IWO based design approach.

Data analysis on physical and mechanical properties of cassava pellets.

PubMed

Oguntunde, Pelumi E; Adejumo, Oluyemisi A; Odetunmibi, Oluwole A; Okagbue, Hilary I; Adejumo, Adebowale O

2018-02-01

In this data article, laboratory experimental investigation results carried out at National Centre for Agricultural Mechanization (NCAM) on moisture content, machine speed, die diameter of the rig, and the outputs (hardness, durability, bulk density, and unit density of the pellets) at different levels of cassava pellets were observed. Analysis of variance using randomized complete block design with factorial was used to perform analysis for each of the outputs: hardness, durability, bulk density, and unit density of the pellets. A clear description on each of these outputs was considered separately using tables and figures. It was observed that for all the output with the exception of unit density, their main factor effects as well as two and three ways interactions is significant at 5% level. This means that the hardness, bulk density and durability of cassava pellets respectively depend on the moisture content of the cassava dough, the machine speed, the die diameter of the extrusion rig and the combinations of these factors in pairs as well as the three altogether. Higher machine speeds produced more quality pellets at lower die diameters while lower machine speed is recommended for higher die diameter. Also the unit density depends on die diameter and the three-way interaction only. Unit density of cassava pellets is neither affected by machine parameters nor moisture content of the cassava dough. Moisture content of cassava dough, speed of the machine and die diameter of the extrusion rig are significant factors to be considered in pelletizing cassava to produce pellets. Increase in moisture content of cassava dough increase the quality of cassava pellets.

Supervised Learning of Two-Layer Perceptron under the Existence of External Noise — Learning Curve of Boolean Functions of Two Variables in Tree-Like Architecture —

NASA Astrophysics Data System (ADS)

Uezu, Tatsuya; Kiyokawa, Shuji

2016-06-01

We investigate the supervised batch learning of Boolean functions expressed by a two-layer perceptron with a tree-like structure. We adopt continuous weights (spherical model) and the Gibbs algorithm. We study the Parity and And machines and two types of noise, input and output noise, together with the noiseless case. We assume that only the teacher suffers from noise. By using the replica method, we derive the saddle point equations for order parameters under the replica symmetric (RS) ansatz. We study the critical value αC of the loading rate α above which the learning phase exists for cases with and without noise. We find that αC is nonzero for the Parity machine, while it is zero for the And machine. We derive the exponents barβ of order parameters expressed as (α - α C)bar{β} when α is near to αC. Furthermore, in the Parity machine, when noise exists, we find a spin glass solution, in which the overlap between the teacher and student vectors is zero but that between student vectors is nonzero. We perform Markov chain Monte Carlo simulations by simulated annealing and also by exchange Monte Carlo simulations in both machines. In the Parity machine, we study the de Almeida-Thouless stability, and by comparing theoretical and numerical results, we find that there exist parameter regions where the RS solution is unstable, and that the spin glass solution is metastable or unstable. We also study asymptotic learning behavior for large α and derive the exponents hat{β } of order parameters expressed as α - hat{β } when α is large in both machines. By simulated annealing simulations, we confirm these results and conclude that learning takes place for the input noise case with any noise amplitude and for the output noise case when the probability that the teacher's output is reversed is less than one-half.

The research on construction and application of machining process knowledge base

NASA Astrophysics Data System (ADS)

Zhao, Tan; Qiao, Lihong; Qie, Yifan; Guo, Kai

2018-03-01

In order to realize the application of knowledge in machining process design, from the perspective of knowledge in the application of computer aided process planning(CAPP), a hierarchical structure of knowledge classification is established according to the characteristics of mechanical engineering field. The expression of machining process knowledge is structured by means of production rules and the object-oriented methods. Three kinds of knowledge base models are constructed according to the representation of machining process knowledge. In this paper, the definition and classification of machining process knowledge, knowledge model, and the application flow of the process design based on the knowledge base are given, and the main steps of the design decision of the machine tool are carried out as an application by using the knowledge base.

Development of elastomeric isolators to reduce roof bolting machine drilling noise

PubMed Central

Michael, Robert; Yantek, David; Johnson, David; Ferro, Ernie; Swope, Chad

2015-01-01

Among underground coal miners, hearing loss remains one of the most common occupational illnesses. In response to this problem, the National Institute for Occupational Safety and Health (NIOSH) Office of Mine Safety and Health Research (OMSHR) conducts research to reduce the noise emission of underground coal-mining equipment, an example of which is a roof bolting machine. Field studies show that, on average, drilling noise is the most significant contributor to a roof bolting machine operator’s noise exposure. NIOSH OMSHR has determined that the drill steel and chuck are the dominant sources of drilling noise. NIOSH OMSHR, Corry Rubber Corporation, and Kennametal, Inc. have developed a bit isolator that breaks the steel-to-steel link between the drill bit and drill steel and a chuck isolator that breaks the mechanical connection between the drill steel and the chuck, thus reducing the noise radiated by the drill steel and chuck, and the noise exposure of the roof bolter operator. This paper documents the evolution of the bit isolator and chuck isolator including various alternative designs which may enhance performance. Laboratory testing confirms that production bit and chuck isolators reduce the A-weighted sound level generated during drilling by 3.7 to 6.6 dB. Finally, this paper summarizes results of a finite element analysis used to explore the key parameters of the drill bit isolator and chuck isolator to understand the impact these parameters have on noise. PMID:26568650

Application of TRIZ approach to machine vibration condition monitoring problems

NASA Astrophysics Data System (ADS)

Cempel, Czesław

2013-12-01

Up to now machine condition monitoring has not been seriously approached by TRIZ1TRIZ= Russian acronym for Inventive Problem Solving System, created by G. Altshuller ca 50 years ago. users, and the knowledge of TRIZ methodology has not been applied there intensively. However, there are some introductory papers of present author posted on Diagnostic Congress in Cracow (Cempel, in press [11]), and Diagnostyka Journal as well. But it seems to be further need to make such approach from different sides in order to see, if some new knowledge and technology will emerge. In doing this we need at first to define the ideal final result (IFR) of our innovation problem. As a next we need a set of parameters to describe the problems of system condition monitoring (CM) in terms of TRIZ language and set of inventive principles possible to apply, on the way to IFR. This means we should present the machine CM problem by means of contradiction and contradiction matrix. When specifying the problem parameters and inventive principles, one should use analogy and metaphorical thinking, which by definition is not exact but fuzzy, and leads sometimes to unexpected results and outcomes. The paper undertakes this important problem again and brings some new insight into system and machine CM problems. This may mean for example the minimal dimensionality of TRIZ engineering parameter set for the description of machine CM problems, and the set of most useful inventive principles applied to given engineering parameter and contradictions of TRIZ.

Designing Contestability: Interaction Design, Machine Learning, and Mental Health

PubMed Central

Hirsch, Tad; Merced, Kritzia; Narayanan, Shrikanth; Imel, Zac E.; Atkins, David C.

2017-01-01

We describe the design of an automated assessment and training tool for psychotherapists to illustrate challenges with creating interactive machine learning (ML) systems, particularly in contexts where human life, livelihood, and wellbeing are at stake. We explore how existing theories of interaction design and machine learning apply to the psychotherapy context, and identify “contestability” as a new principle for designing systems that evaluate human behavior. Finally, we offer several strategies for making ML systems more accountable to human actors. PMID:28890949

Application of dragonfly algorithm for optimal performance analysis of process parameters in turn-mill operations- A case study

NASA Astrophysics Data System (ADS)

Vikram, K. Arun; Ratnam, Ch; Lakshmi, VVK; Kumar, A. Sunny; Ramakanth, RT

2018-02-01

Meta-heuristic multi-response optimization methods are widely in use to solve multi-objective problems to obtain Pareto optimal solutions during optimization. This work focuses on optimal multi-response evaluation of process parameters in generating responses like surface roughness (Ra), surface hardness (H) and tool vibration displacement amplitude (Vib) while performing operations like tangential and orthogonal turn-mill processes on A-axis Computer Numerical Control vertical milling center. Process parameters like tool speed, feed rate and depth of cut are considered as process parameters machined over brass material under dry condition with high speed steel end milling cutters using Taguchi design of experiments (DOE). Meta-heuristic like Dragonfly algorithm is used to optimize the multi-objectives like ‘Ra’, ‘H’ and ‘Vib’ to identify the optimal multi-response process parameters combination. Later, the results thus obtained from multi-objective dragonfly algorithm (MODA) are compared with another multi-response optimization technique Viz. Grey relational analysis (GRA).

Terminator Detection by Support Vector Machine Utilizing aStochastic Context-Free Grammar

DOE Office of Scientific and Technical Information (OSTI.GOV)

Francis-Lyon, Patricia; Cristianini, Nello; Holbrook, Stephen

2006-12-30

A 2-stage detector was designed to find rho-independent transcription terminators in the Escherichia coli genome. The detector includes a Stochastic Context Free Grammar (SCFG) component and a Support Vector Machine (SVM) component. To find terminators, the SCFG searches the intergenic regions of nucleotide sequence for local matches to a terminator grammar that was designed and trained utilizing examples of known terminators. The grammar selects sequences that are the best candidates for terminators and assigns them a prefix, stem-loop, suffix structure using the Cocke-Younger-Kasaami (CYK) algorithm, modified to incorporate energy affects of base pairing. The parameters from this inferred structure aremore » passed to the SVM classifier, which distinguishes terminators from non-terminators that score high according to the terminator grammar. The SVM was trained with negative examples drawn from intergenic sequences that include both featureless and RNA gene regions (which were assigned prefix, stem-loop, suffix structure by the SCFG), so that it successfully distinguishes terminators from either of these. The classifier was found to be 96.4% successful during testing.« less

Design study and performance analysis of 12S-14P field excitation flux switching motor for hybrid electric vehicle

NASA Astrophysics Data System (ADS)

Husin, Zhafir Aizat; Sulaiman, Erwan; Khan, Faisal; Mazlan, Mohamed Mubin Aizat; Othman, Syed Muhammad Naufal Syed

2015-05-01

This paper presents a new structure of 12slot-14pole field excitation flux switching motor (FEFSM) as an alternative candidate of non-Permanent Magnet (PM) machine for HEV drives. Design study, performance analysis and optimization of field excitation flux switching machine with non-rare-earth magnet for hybrid electric vehicle drive applications is done. The stator of projected machine consists of iron core made of electromagnetic steels, armature coils and field excitation coils as the only field mmf source. The rotor is consisted of only stack of iron and hence, it is reliable and appropriate for high speed operation. The design target is a machine with the maximum torque, power and power density, more than 210Nm, 123kW and 3.5kW/kg, respectively, which competes with interior permanent magnet synchronous machine used in existing hybrid electric vehicle. Some design feasibility studies on FEFSM based on 2D-FEA and deterministic optimization method will be applied to design the proposed machine.

Rapid performance modeling and parameter regression of geodynamic models

NASA Astrophysics Data System (ADS)

Brown, J.; Duplyakin, D.

2016-12-01

Geodynamic models run in a parallel environment have many parameters with complicated effects on performance and scientifically-relevant functionals. Manually choosing an efficient machine configuration and mapping out the parameter space requires a great deal of expert knowledge and time-consuming experiments. We propose an active learning technique based on Gaussion Process Regression to automatically select experiments to map out the performance landscape with respect to scientific and machine parameters. The resulting performance model is then used to select optimal experiments for improving the accuracy of a reduced order model per unit of computational cost. We present the framework and evaluate its quality and capability using popular lithospheric dynamics models.

Extreme Learning Machine and Particle Swarm Optimization in optimizing CNC turning operation

NASA Astrophysics Data System (ADS)

Janahiraman, Tiagrajah V.; Ahmad, Nooraziah; Hani Nordin, Farah

2018-04-01

The CNC machine is controlled by manipulating cutting parameters that could directly influence the process performance. Many optimization methods has been applied to obtain the optimal cutting parameters for the desired performance function. Nonetheless, the industry still uses the traditional technique to obtain those values. Lack of knowledge on optimization techniques is the main reason for this issue to be prolonged. Therefore, the simple yet easy to implement, Optimal Cutting Parameters Selection System is introduced to help the manufacturer to easily understand and determine the best optimal parameters for their turning operation. This new system consists of two stages which are modelling and optimization. In modelling of input-output and in-process parameters, the hybrid of Extreme Learning Machine and Particle Swarm Optimization is applied. This modelling technique tend to converge faster than other artificial intelligent technique and give accurate result. For the optimization stage, again the Particle Swarm Optimization is used to get the optimal cutting parameters based on the performance function preferred by the manufacturer. Overall, the system can reduce the gap between academic world and the industry by introducing a simple yet easy to implement optimization technique. This novel optimization technique can give accurate result besides being the fastest technique.

Design concept of K-DEMO for near-term implementation

NASA Astrophysics Data System (ADS)

Kim, K.; Im, K.; Kim, H. C.; Oh, S.; Park, J. S.; Kwon, S.; Lee, Y. S.; Yeom, J. H.; Lee, C.; Lee, G.-S.; Neilson, G.; Kessel, C.; Brown, T.; Titus, P.; Mikkelsen, D.; Zhai, Y.

2015-05-01

A Korean fusion energy development promotion law (FEDPL) was enacted in 2007. As a following step, a conceptual design study for a steady-state Korean fusion demonstration reactor (K-DEMO) was initiated in 2012. After the thorough 0D system analysis, the parameters of the main machine characterized by the major and minor radii of 6.8 and 2.1 m, respectively, were chosen for further study. The analyses of heating and current drives were performed for the development of the plasma operation scenarios. Preliminary results on lower hybrid and neutral beam current drive are included herein. A high performance Nb3Sn-based superconducting conductor is adopted, providing a peak magnetic field approaching 16 T with the magnetic field at the plasma centre above 7 T. Pressurized water is the prominent choice for the main coolant of K-DEMO when the balance of plant development details is considered. The blanket system adopts a ceramic pebble type breeder. Considering plasma performance, a double-null divertor is the reference configuration choice of K-DEMO. For a high availability operation, K-DEMO incorporates a design with vertical maintenance. A design concept for K-DEMO is presented together with the preliminary design parameters.

CNC Machining Of The Complex Copper Electrodes

NASA Astrophysics Data System (ADS)

Popan, Ioan Alexandru; Balc, Nicolae; Popan, Alina

2015-07-01

This paper presents the machining process of the complex copper electrodes. Machining of the complex shapes in copper is difficult because this material is soft and sticky. This research presents the main steps for processing those copper electrodes at a high dimensional accuracy and a good surface quality. Special tooling solutions are required for this machining process and optimal process parameters have been found for the accurate CNC equipment, using smart CAD/CAM software.

Progress Toward Fabrication of Machined Metal Shells for the First Double-Shell Implosions at the National Ignition Facility

DOE PAGES

Cardenas, Tana; Schmidt, Derek W.; Loomis, Eric N.; ...

2018-01-25

The double-shell platform fielded at the National Ignition Facility requires developments in new machining techniques and robotic assembly stations to meet the experimental specifications. Current double-shell target designs use a dense high-Z inner shell, a foam cushion, and a low-Z outer shell. The design requires that the inner shell be gas filled using a fill tube. This tube impacts the entire machining and assembly design. Other intermediate physics designs have to be fielded to answer physics questions and advance the technology to be able to fabricate the full point design in the near future. One of these intermediate designs ismore » a mid-Z imaging design. The methods of designing, fabricating, and characterizing each of the major components of an imaging double shell are discussed with an emphasis on the fabrication of the machined outer metal shell.« less

Progress Toward Fabrication of Machined Metal Shells for the First Double-Shell Implosions at the National Ignition Facility

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cardenas, Tana; Schmidt, Derek W.; Loomis, Eric N.

The double-shell platform fielded at the National Ignition Facility requires developments in new machining techniques and robotic assembly stations to meet the experimental specifications. Current double-shell target designs use a dense high-Z inner shell, a foam cushion, and a low-Z outer shell. The design requires that the inner shell be gas filled using a fill tube. This tube impacts the entire machining and assembly design. Other intermediate physics designs have to be fielded to answer physics questions and advance the technology to be able to fabricate the full point design in the near future. One of these intermediate designs ismore » a mid-Z imaging design. The methods of designing, fabricating, and characterizing each of the major components of an imaging double shell are discussed with an emphasis on the fabrication of the machined outer metal shell.« less

Fractional watt Vuillemier cryogenic refrigerator program engineering notebook. Volume 1: Thermal analysis

NASA Technical Reports Server (NTRS)

Miller, W. S.

1974-01-01

The cryogenic refrigerator thermal design calculations establish design approach and basic sizing of the machine's elements. After the basic design is defined, effort concentrates on matching the thermodynamic design with that of the heat transfer devices (heat exchangers and regenerators). Typically, the heat transfer device configurations and volumes are adjusted to improve their heat transfer and pressure drop characteristics. These adjustments imply that changes be made to the active displaced volumes, compensating for the influence of the heat transfer devices on the thermodynamic processes of the working fluid. Then, once the active volumes are changed, the heat transfer devices require adjustment to account for the variations in flows, pressure levels, and heat loads. This iterative process is continued until the thermodynamic cycle parameters match the design of the heat transfer devices. By examing several matched designs, a near-optimum refrigerator is selected.

The Simpsons program 6-D phase space tracking with acceleration

NASA Astrophysics Data System (ADS)

Machida, S.

1993-12-01

A particle tracking code, Simpsons, in 6-D phase space including energy ramping has been developed to model proton synchrotrons and storage rings. We take time as the independent variable to change machine parameters and diagnose beam quality in a quite similar way as real machines, unlike existing tracking codes for synchrotrons which advance a particle element by element. Arbitrary energy ramping and rf voltage curves as a function of time are read as an input file for defining a machine cycle. The code is used to study beam dynamics with time dependent parameters. Some of the examples from simulations of the Superconducting Super Collider (SSC) boosters are shown.

A low cost implementation of multi-parameter patient monitor using intersection kernel support vector machine classifier

NASA Astrophysics Data System (ADS)

Mohan, Dhanya; Kumar, C. Santhosh

2016-03-01

Predicting the physiological condition (normal/abnormal) of a patient is highly desirable to enhance the quality of health care. Multi-parameter patient monitors (MPMs) using heart rate, arterial blood pressure, respiration rate and oxygen saturation (S pO2) as input parameters were developed to monitor the condition of patients, with minimum human resource utilization. The Support vector machine (SVM), an advanced machine learning approach popularly used for classification and regression is used for the realization of MPMs. For making MPMs cost effective, we experiment on the hardware implementation of the MPM using support vector machine classifier. The training of the system is done using the matlab environment and the detection of the alarm/noalarm condition is implemented in hardware. We used different kernels for SVM classification and note that the best performance was obtained using intersection kernel SVM (IKSVM). The intersection kernel support vector machine classifier MPM has outperformed the best known MPM using radial basis function kernel by an absoute improvement of 2.74% in accuracy, 1.86% in sensitivity and 3.01% in specificity. The hardware model was developed based on the improved performance system using Verilog Hardware Description Language and was implemented on Altera cyclone-II development board.

The Influence of Injection Molding Parameter on Properties of Thermally Conductive Plastic

NASA Astrophysics Data System (ADS)

Hafizah Azis, N.; Zulafif Rahim, M.; Sa'ude, Nasuha; Rafai, N.; Yusof, M. S.; Tobi, ALM; Sharif, ZM; Rasidi Ibrahim, M.; Ismail, A. E.

2017-05-01

Thermally conductive plastic is the composite between metal-plastic material that is becoming popular because if it special characteristic. Injection moulding was regarded as the best process for mass manufacturing of the plastic composite due to its low production cost. The objective of this research is to find the best combination of the injection parameter setting and to find the most significant factor that effect the strength and thermal conductivity of the composite. Several parameter such as the volume percentage of copper powder, nozzle temperature and injection pressure of injection moulding machine were investigated. The analysis was done using Design Expert Software by implementing design of experiment method. From the analysis, the significant effects were determined and mathematical models of only significant effect were established. In order to ensure the validity of the model, confirmation run was done and percentage errors were calculated. It was found that the best combination parameter setting to maximize the value of tensile strength is volume percentage of copper powder of 3.00%, the nozzle temperature of 195°C and the injection pressure of 65%, and the best combination parameter settings to maximize the value of thermal conductivity is volume percentage of copper powder of 7.00%, the nozzle temperature of 195°C and the injection pressure of 65% as recommended..

Design Comparison of Inner and Outer Rotor of Permanent Magnet Flux Switching Machine for Electric Bicycle Application

NASA Astrophysics Data System (ADS)

Jusoh, L. I.; Sulaiman, E.; Bahrim, F. S.; Kumar, R.

2017-08-01

Recent advancements have led to the development of flux switching machines (FSMs) with flux sources within the stators. The advantage of being a single-piece machine with a robust rotor structure makes FSM an excellent choice for speed applications. There are three categories of FSM, namely, the permanent magnet (PM) FSM, the field excitation (FE) FSM, and the hybrid excitation (HE) FSM. The PMFSM and the FEFSM have their respective PM and field excitation coil (FEC) as their key flux sources. Meanwhile, as the name suggests, the HEFSM has a combination of PM and FECs as the flux sources. The PMFSM is a simple and cheap machine, and it has the ability to control variable flux, which would be suitable for an electric bicycle. Thus, this paper will present a design comparison between an inner rotor and an outer rotor for a single-phase permanent magnet flux switching machine with 8S-10P, designed specifically for an electric bicycle. The performance of this machine was validated using the 2D- FEA. As conclusion, the outer-rotor has much higher torque approximately at 54.2% of an innerrotor PMFSM. From the comprehensive analysis of both designs it can be conclude that output performance is lower than the SRM and IPMSM design machine. But, it shows that the possibility to increase the design performance by using “deterministic optimization method”.

Design and Fabrication of Automatic Glass Cutting Machine

NASA Astrophysics Data System (ADS)

Veena, T. R.; Kadadevaramath, R. S.; Nagaraj, P. M.; Madhusudhan, S. V.

2016-09-01

This paper deals with the design and fabrication of the automatic glass or mirror cutting machine. In order to increase the accuracy of cut and production rate; and decrease the production time and accidents caused due to manual cutting of mirror or glass, this project aims at development of an automatic machine which uses a programmable logic controller (PLC) for controlling the movement of the conveyer and also to control the pneumatic circuit. In this machine, the work of the operator is to load and unload the mirror. The cutter used in this machine is carbide wheel with its cutting edge ground to a V-shaped profile. The PLC controls the pneumatic cylinder and intern actuates the cutter along the glass, a fracture layer is formed causing a mark to be formed below the fracture layer and a crack to be formed below the rib mark. The machine elements are designed using CATIA V5R20 and pneumatic circuit are designed using FESTO FLUID SIM software.

Machine learning and data science in soft materials engineering

NASA Astrophysics Data System (ADS)

Ferguson, Andrew L.

2018-01-01

In many branches of materials science it is now routine to generate data sets of such large size and dimensionality that conventional methods of analysis fail. Paradigms and tools from data science and machine learning can provide scalable approaches to identify and extract trends and patterns within voluminous data sets, perform guided traversals of high-dimensional phase spaces, and furnish data-driven strategies for inverse materials design. This topical review provides an accessible introduction to machine learning tools in the context of soft and biological materials by ‘de-jargonizing’ data science terminology, presenting a taxonomy of machine learning techniques, and surveying the mathematical underpinnings and software implementations of popular tools, including principal component analysis, independent component analysis, diffusion maps, support vector machines, and relative entropy. We present illustrative examples of machine learning applications in soft matter, including inverse design of self-assembling materials, nonlinear learning of protein folding landscapes, high-throughput antimicrobial peptide design, and data-driven materials design engines. We close with an outlook on the challenges and opportunities for the field.

Machine learning and data science in soft materials engineering.

PubMed

Ferguson, Andrew L

2018-01-31

In many branches of materials science it is now routine to generate data sets of such large size and dimensionality that conventional methods of analysis fail. Paradigms and tools from data science and machine learning can provide scalable approaches to identify and extract trends and patterns within voluminous data sets, perform guided traversals of high-dimensional phase spaces, and furnish data-driven strategies for inverse materials design. This topical review provides an accessible introduction to machine learning tools in the context of soft and biological materials by 'de-jargonizing' data science terminology, presenting a taxonomy of machine learning techniques, and surveying the mathematical underpinnings and software implementations of popular tools, including principal component analysis, independent component analysis, diffusion maps, support vector machines, and relative entropy. We present illustrative examples of machine learning applications in soft matter, including inverse design of self-assembling materials, nonlinear learning of protein folding landscapes, high-throughput antimicrobial peptide design, and data-driven materials design engines. We close with an outlook on the challenges and opportunities for the field.

Gesture-controlled interfaces for self-service machines and other applications

NASA Technical Reports Server (NTRS)

Cohen, Charles J. (Inventor); Jacobus, Charles J. (Inventor); Paul, George (Inventor); Beach, Glenn (Inventor); Foulk, Gene (Inventor); Obermark, Jay (Inventor); Cavell, Brook (Inventor)

2004-01-01

A gesture recognition interface for use in controlling self-service machines and other devices is disclosed. A gesture is defined as motions and kinematic poses generated by humans, animals, or machines. Specific body features are tracked, and static and motion gestures are interpreted. Motion gestures are defined as a family of parametrically delimited oscillatory motions, modeled as a linear-in-parameters dynamic system with added geometric constraints to allow for real-time recognition using a small amount of memory and processing time. A linear least squares method is preferably used to determine the parameters which represent each gesture. Feature position measure is used in conjunction with a bank of predictor bins seeded with the gesture parameters, and the system determines which bin best fits the observed motion. Recognizing static pose gestures is preferably performed by localizing the body/object from the rest of the image, describing that object, and identifying that description. The disclosure details methods for gesture recognition, as well as the overall architecture for using gesture recognition to control of devices, including self-service machines.

Developing Lathing Parameters for PBX 9501

DOE Office of Scientific and Technical Information (OSTI.GOV)

Woodrum, Randall Brock

This thesis presents the work performed on lathing PBX 9501 to gather and analyze cutting force and temperature data during the machining process. This data will be used to decrease federal-regulation-constrained machining time of the high explosive PBX 9501. The effects of machining parameters depth of cut, surface feet per minute, and inches per revolution on cutting force and cutting interface were evaluated. Cutting tools of tip radius 0.005 -inches and 0.05 -inches were tested to determine what effect the tool shape had on the machining process as well. A consistently repeatable relationship of temperature to changing depth of cutmore » and surface feet per minute is found, while only a weak dependence was found to changing inches per revolution. Results also show the relation of cutting force to depth of cut and inches per revolution, while weak dependence on SFM is found. Conclusions suggest rapid, shallow cuts optimize machining time for a billet of PBX 9501, while minimizing temperature increase and cutting force.« less

From "Gut Feeling" to Objectivity: Machine Preservation of the Liver as a Tool to Assess Organ Viability.

PubMed

Watson, Christopher J E; Jochmans, Ina

2018-01-01

The purpose of this review was to summarise how machine perfusion could contribute to viability assessment of donor livers. In both hypothermic and normothermic machine perfusion, perfusate transaminase measurement has allowed pretransplant assessment of hepatocellular damage. Hypothermic perfusion permits transplantation of marginal grafts but as yet has not permitted formal viability assessment. Livers undergoing normothermic perfusion have been investigated using parameters similar to those used to evaluate the liver in vivo. Lactate clearance, glucose evolution and pH regulation during normothermic perfusion seem promising measures of viability. In addition, bile chemistry might inform on cholangiocyte viability and the likelihood of post-transplant cholangiopathy. While the use of machine perfusion technology has the potential to reduce and even remove uncertainty regarding liver graft viability, analysis of large datasets, such as those derived from large multicenter trials of machine perfusion, are needed to provide sufficient information to enable viability parameters to be defined and validated .

Machinability of Green Powder Metallurgy Components: Part I. Characterization of the Influence of Tool Wear

NASA Astrophysics Data System (ADS)

Robert-Perron, Etienne; Blais, Carl; Pelletier, Sylvain; Thomas, Yannig

2007-06-01

The green machining process is an interesting approach for solving the mediocre machining behavior of high-performance powder metallurgy (PM) steels. This process appears as a promising method for extending tool life and reducing machining costs. Recent improvements in binder/lubricant technologies have led to high green strength systems that enable green machining. So far, tool wear has been considered negligible when characterizing the machinability of green PM specimens. This inaccurate assumption may lead to the selection of suboptimum cutting conditions. The first part of this study involves the optimization of the machining parameters to minimize the effects of tool wear on the machinability in turning of green PM components. The second part of our work compares the sintered mechanical properties of components machined in green state with other machined after sintering.

X-Ray Backscatter Machine Support Frame

NASA Technical Reports Server (NTRS)

Cannon, Brooke

2010-01-01

This summer at Kennedy Space Center, I spent 10 weeks as an intern working at the Prototype Development Lab. During this time I learned about the design and machining done here at NASA. I became familiar with the process from where a design begins in Pro/Engineer and finishes at the hands of the machinists. As an intern I was given various small jobs to do and then one project of my own. My personal project was a job for the Applied Physics Lab; in their work they use an X-Ray Backscatter machine. Previously it was resting atop a temporary frame that limited the use of the machine. My job was to design a frame for the machine to rest upon that would allow a full range of sample sizes. The frame was required to support the machine and provide a strain relief for the cords attached to the machine as it moved in the x and y directions. Calculations also had to be done to be sure the design would be able to withstand any loads or outside sources of stress. After the calculations proved the design to be ready to withstand the requirements, the parts were ordered or fabricated, as required. This helped me understand the full process of jobs sent to the Prototype Development Lab.

Electron paramagnetic resonance field-modulation eddy-current analysis of silver-plated graphite resonators

NASA Astrophysics Data System (ADS)

Mett, Richard R.; Anderson, James R.; Sidabras, Jason W.; Hyde, James S.

2005-09-01

Magnetic field modulation is often introduced into a cylindrical TE011 electron paramagnetic resonance (EPR) cavity through silver plating over a nonconductive substrate. The plating thickness must be many times the skin depth of the rf and smaller than the skin depth of the modulation. We derive a parameter that quantifies the modulation field penetration and find that it also depends on resonator dimensions. Design criteria based on this parameter are presented graphically. This parameter is then used to predict the behavior of eddy currents in substrates of moderate conductivity, such as graphite. The conductivity of the graphite permits improved plating uniformity and permits use of electric discharge machining (EDM) techniques to make the resonator. EDM offers precision tolerances of 0.005 mm and is suitable for small, complicated shapes that are difficult to machine by other methods. Analytic predictions of the modulation penetration are compared with the results of finite-element simulations. Simulated magnetic field modulation uniformity and penetration are shown for several elemental coils and structures including the plated graphite TE011 cavity. Fabrication and experimental testing of the structure are discussed. Spatial inhomogeneity of the modulation phase is also investigated by computer simulation. We find that the modulation phase is uniform to within 1% over the TE011 cavity. Structures of lower symmetry have increased phase nonuniformity.

Parameter monitoring compensation system and method

DOEpatents

Barkman, W.E.; Babelay, E.F.; DeMint, P.D.; Hebble, T.L.; Igou, R.E.; Williams, R.R.; Klages, E.J.; Rasnick, W.H.

1995-02-07

A compensation system is described for a computer-controlled machining apparatus having a controller and including a cutting tool and a workpiece holder which are movable relative to one another along a preprogrammed path during a machining operation. It utilizes sensors for gathering information at a preselected stage of a machining operation relating to an actual condition. The controller compares the actual condition to a condition which the program presumes to exist at the preselected stage and alters the program in accordance with detected variations between the actual condition and the assumed condition. Such conditions may be related to process parameters, such as a position, dimension or shape of the cutting tool or workpiece or an environmental temperature associated with the machining operation, and such sensors may be a contact or a non-contact type of sensor or a temperature transducer. 7 figs.

Experimental investigation of various surface integrity aspects in hard turning of AISI 4340 alloy steel with coated and uncoated cermet

NASA Astrophysics Data System (ADS)

Das, Anshuman; Patel, S. K.; Sateesh Kumar, Ch.; Biswal, B. B.

2018-03-01

The newer technological developments are exerting immense pressure on domain of production. These fabrication industries are busy finding solutions to reduce the costs of cutting materials, enhance the machined parts quality and testing different materials, which can be made versatile for cutting materials, which are difficult for machining. High-speed machining has been the domain of paramount importance for mechanical engineering. In this study, the variation of surface integrity parameters of hardened AISI 4340 alloy steel was analyzed. The surface integrity parameters like surface roughness, micro hardness, machined surface morphology and white layer of hardened AISI 4340 alloy steel were compared using coated and uncoated cermet inserts under dry cutting condition. From the results, it was deduced that coated insert outperformed uncoated one in terms of different surface integrity characteristics.

Biomachining - A new approach for micromachining of metals

NASA Astrophysics Data System (ADS)

Vigneshwaran, S. C. Sakthi; Ramakrishnan, R.; Arun Prakash, C.; Sashank, C.

2018-04-01

Machining is the process of removal of material from workpiece. Machining can be done by physical, chemical or biological methods. Though physical and chemical methods have been widely used in machining process, they have their own disadvantages such as development of heat affected zone and usage of hazardous chemicals. Biomachining is the machining process in which bacteria is used to remove material from the metal parts. Chemolithotrophic bacteria such as Acidothiobacillus ferroxidans has been used in biomachining of metals like copper, iron etc. These bacteria are used because of their property of catalyzing the oxidation of inorganic substances. Biomachining is a suitable process for micromachining of metals. This paper reviews the biomachining process and various mechanisms involved in biomachining. This paper also briefs about various parameters/factors to be considered in biomachining and also the effect of those parameters on metal removal rate.

Cogging Torque Minimization in Transverse Flux Machines

DOE Office of Scientific and Technical Information (OSTI.GOV)

Husain, Tausif; Hasan, Iftekhar; Sozer, Yilmaz

2017-02-16

This paper presents the design considerations in cogging torque minimization in two types of transverse flux machines. The machines have a double stator-single rotor configuration with flux concentrating ferrite magnets. One of the machines has pole windings across each leg of an E-Core stator. Another machine has quasi-U-shaped stator cores and a ring winding. The flux in the stator back iron is transverse in both machines. Different methods of cogging torque minimization are investigated. Key methods of cogging torque minimization are identified and used as design variables for optimization using a design of experiments (DOE) based on the Taguchi method.more » A three-level DOE is performed to reach an optimum solution with minimum simulations. Finite element analysis is used to study the different effects. Two prototypes are being fabricated for experimental verification.« less

Mapping groundwater contamination risk of multiple aquifers using multi-model ensemble of machine learning algorithms.

PubMed

Barzegar, Rahim; Moghaddam, Asghar Asghari; Deo, Ravinesh; Fijani, Elham; Tziritis, Evangelos

2018-04-15

Constructing accurate and reliable groundwater risk maps provide scientifically prudent and strategic measures for the protection and management of groundwater. The objectives of this paper are to design and validate machine learning based-risk maps using ensemble-based modelling with an integrative approach. We employ the extreme learning machines (ELM), multivariate regression splines (MARS), M5 Tree and support vector regression (SVR) applied in multiple aquifer systems (e.g. unconfined, semi-confined and confined) in the Marand plain, North West Iran, to encapsulate the merits of individual learning algorithms in a final committee-based ANN model. The DRASTIC Vulnerability Index (VI) ranged from 56.7 to 128.1, categorized with no risk, low and moderate vulnerability thresholds. The correlation coefficient (r) and Willmott's Index (d) between NO 3 concentrations and VI were 0.64 and 0.314, respectively. To introduce improvements in the original DRASTIC method, the vulnerability indices were adjusted by NO 3 concentrations, termed as the groundwater contamination risk (GCR). Seven DRASTIC parameters utilized as the model inputs and GCR values utilized as the outputs of individual machine learning models were served in the fully optimized committee-based ANN-predictive model. The correlation indicators demonstrated that the ELM and SVR models outperformed the MARS and M5 Tree models, by virtue of a larger d and r value. Subsequently, the r and d metrics for the ANN-committee based multi-model in the testing phase were 0.8889 and 0.7913, respectively; revealing the superiority of the integrated (or ensemble) machine learning models when compared with the original DRASTIC approach. The newly designed multi-model ensemble-based approach can be considered as a pragmatic step for mapping groundwater contamination risks of multiple aquifer systems with multi-model techniques, yielding the high accuracy of the ANN committee-based model. Copyright © 2017 Elsevier B.V. All rights reserved.

Unsupervised learning of structure in spectroscopic cubes

NASA Astrophysics Data System (ADS)

Araya, M.; Mendoza, M.; Solar, M.; Mardones, D.; Bayo, A.

2018-07-01

We consider the problem of analyzing the structure of spectroscopic cubes using unsupervised machine learning techniques. We propose representing the target's signal as a homogeneous set of volumes through an iterative algorithm that separates the structured emission from the background while not overestimating the flux. Besides verifying some basic theoretical properties, the algorithm is designed to be tuned by domain experts, because its parameters have meaningful values in the astronomical context. Nevertheless, we propose a heuristic to automatically estimate the signal-to-noise ratio parameter of the algorithm directly from data. The resulting light-weighted set of samples (≤ 1% compared to the original data) offer several advantages. For instance, it is statistically correct and computationally inexpensive to apply well-established techniques of the pattern recognition and machine learning domains; such as clustering and dimensionality reduction algorithms. We use ALMA science verification data to validate our method, and present examples of the operations that can be performed by using the proposed representation. Even though this approach is focused on providing faster and better analysis tools for the end-user astronomer, it also opens the possibility of content-aware data discovery by applying our algorithm to big data.

High speed machining of space shuttle external tank liquid hydrogen barrel panel

NASA Technical Reports Server (NTRS)

Hankins, J. D.

1983-01-01

Actual and projected optimum High Speed Machining data for producing shuttle external tank liquid hydrogen barrel panels of aluminum alloy 2219-T87 are reported. The data included various machining parameters; e.g., spindle speeds, cutting speed, table feed, chip load, metal removal rate, horsepower, cutting efficiency, cutter wear (lack of) and chip removal methods.

High speed machining of space shuttle external tank liquid hydrogen barrel panel

NASA Astrophysics Data System (ADS)

Hankins, J. D.

1983-11-01

Actual and projected optimum High Speed Machining data for producing shuttle external tank liquid hydrogen barrel panels of aluminum alloy 2219-T87 are reported. The data included various machining parameters; e.g., spindle speeds, cutting speed, table feed, chip load, metal removal rate, horsepower, cutting efficiency, cutter wear (lack of) and chip removal methods.

Design Methodology for Automated Construction Machines

DTIC Science & Technology

1987-12-11

along with the design of a pair of machines which automate framework installation.-,, 20. DISTRIBUTION IAVAILABILITY OF ABSTRACT 21. ABSTRACT SECURITY... Development Assistant Professor of Civil Engineering and Laura A . Demsetz, David H. Levy, Bruce Schena Graduate Research Assistants December 11, 1987 U.S...are discussed along with the design of a pair of machines which automate framework installation. Preliminary analysis and testing indicate that these

Agreement Between Institutional Measurements and Treatment Planning System Calculations for Basic Dosimetric Parameters as Measured by the Imaging and Radiation Oncology Core-Houston

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kerns, James R.; Followill, David S.; Imaging and Radiation Oncology Core-Houston, The University of Texas Health Science Center-Houston, Houston, Texas

Purpose: To compare radiation machine measurement data collected by the Imaging and Radiation Oncology Core at Houston (IROC-H) with institutional treatment planning system (TPS) values, to identify parameters with large differences in agreement; the findings will help institutions focus their efforts to improve the accuracy of their TPS models. Methods and Materials: Between 2000 and 2014, IROC-H visited more than 250 institutions and conducted independent measurements of machine dosimetric data points, including percentage depth dose, output factors, off-axis factors, multileaf collimator small fields, and wedge data. We compared these data with the institutional TPS values for the same points bymore » energy, class, and parameter to identify differences and similarities using criteria involving both the medians and standard deviations for Varian linear accelerators. Distributions of differences between machine measurements and institutional TPS values were generated for basic dosimetric parameters. Results: On average, intensity modulated radiation therapy–style and stereotactic body radiation therapy–style output factors and upper physical wedge output factors were the most problematic. Percentage depth dose, jaw output factors, and enhanced dynamic wedge output factors agreed best between the IROC-H measurements and the TPS values. Although small differences were shown between 2 common TPS systems, neither was superior to the other. Parameter agreement was constant over time from 2000 to 2014. Conclusions: Differences in basic dosimetric parameters between machine measurements and TPS values vary widely depending on the parameter, although agreement does not seem to vary by TPS and has not changed over time. Intensity modulated radiation therapy–style output factors, stereotactic body radiation therapy–style output factors, and upper physical wedge output factors had the largest disagreement and should be carefully modeled to ensure accuracy.« less

Using machine learning tools to model complex toxic interactions with limited sampling regimes.

PubMed

Bertin, Matthew J; Moeller, Peter; Guillette, Louis J; Chapman, Robert W

2013-03-19

A major impediment to understanding the impact of environmental stress, including toxins and other pollutants, on organisms, is that organisms are rarely challenged by one or a few stressors in natural systems. Thus, linking laboratory experiments that are limited by practical considerations to a few stressors and a few levels of these stressors to real world conditions is constrained. In addition, while the existence of complex interactions among stressors can be identified by current statistical methods, these methods do not provide a means to construct mathematical models of these interactions. In this paper, we offer a two-step process by which complex interactions of stressors on biological systems can be modeled in an experimental design that is within the limits of practicality. We begin with the notion that environment conditions circumscribe an n-dimensional hyperspace within which biological processes or end points are embedded. We then randomly sample this hyperspace to establish experimental conditions that span the range of the relevant parameters and conduct the experiment(s) based upon these selected conditions. Models of the complex interactions of the parameters are then extracted using machine learning tools, specifically artificial neural networks. This approach can rapidly generate highly accurate models of biological responses to complex interactions among environmentally relevant toxins, identify critical subspaces where nonlinear responses exist, and provide an expedient means of designing traditional experiments to test the impact of complex mixtures on biological responses. Further, this can be accomplished with an astonishingly small sample size.

Analysis of machining accuracy during free form surface milling simulation for different milling strategies

NASA Astrophysics Data System (ADS)

Matras, A.; Kowalczyk, R.

2014-11-01

The analysis results of machining accuracy after the free form surface milling simulations (based on machining EN AW- 7075 alloys) for different machining strategies (Level Z, Radial, Square, Circular) are presented in the work. Particular milling simulations were performed using CAD/CAM Esprit software. The accuracy of obtained allowance is defined as a difference between the theoretical surface of work piece element (the surface designed in CAD software) and the machined surface after a milling simulation. The difference between two surfaces describes a value of roughness, which is as the result of tool shape mapping on the machined surface. Accuracy of the left allowance notifies in direct way a surface quality after the finish machining. Described methodology of usage CAD/CAM software can to let improve a time design of machining process for a free form surface milling by a 5-axis CNC milling machine with omitting to perform the item on a milling machine in order to measure the machining accuracy for the selected strategies and cutting data.

Investigation of fault modes in permanent magnet synchronous machines for traction applications

NASA Astrophysics Data System (ADS)

Choi, Gilsu

Over the past few decades, electric motor drives have been more widely adopted to power the transportation sector to reduce our dependence on foreign oil and carbon emissions. Permanent magnet synchronous machines (PMSMs) are popular in many applications in the aerospace and automotive industries that require high power density and high efficiency. However, the presence of magnets that cannot be turned off in the event of a fault has always been an issue that hinders adoption of PMSMs in these demanding applications. This work investigates the design and analysis of PMSMs for automotive traction applications with particular emphasis on fault-mode operation caused by faults appearing at the terminals of the machine. New models and analytical techniques are introduced for evaluating the steady-state and dynamic response of PMSM drives to various fault conditions. Attention is focused on modeling the PMSM drive including nonlinear magnetic behavior under several different fault conditions, evaluating the risks of irreversible demagnetization caused by the large fault currents, as well as developing fault mitigation techniques in terms of both the fault currents and demagnetization risks. Of the major classes of machine terminal faults that can occur in PMSMs, short-circuit (SC) faults produce much more dangerous fault currents than open-circuit faults. The impact of different PMSM topologies and parameters on their responses to symmetrical and asymmetrical short-circuit (SSC & ASC) faults has been investigated. A detailed investigation on both the SSC and ASC faults is presented including both closed-form and numerical analysis. The demagnetization characteristics caused by high fault-mode stator currents (i.e., armature reaction) for different types of PMSMs are investigated. A thorough analysis and comparison of the relative demagnetization vulnerability for different types of PMSMs is presented. This analysis includes design guidelines and recommendations for minimizing the demagnetization risks while examining corresponding trade-offs. Two PM machines have been tested to validate the predicted fault currents and braking torque as well as demagnetization risks in PMSM drives. The generality and scalability of key results have also been demonstrated by analyzing several PM machines with a variety of stator, rotor, and winding configurations for various power ratings.

Crabbing System for an Electron-Ion Collider

NASA Astrophysics Data System (ADS)

Castilla, Alejandro

As high energy and nuclear physicists continue to push further the boundaries of knowledge using colliders, there is an imperative need, not only to increase the colliding beams' energies, but also to improve the accuracy of the experiments, and to collect a large quantity of events with good statistical sensitivity. To achieve the latter, it is necessary to collect more data by increasing the rate at which these pro- cesses are being produced and detected in the machine. This rate of events depends directly on the machine's luminosity. The luminosity itself is proportional to the frequency at which the beams are being delivered, the number of particles in each beam, and inversely proportional to the cross-sectional size of the colliding beams. There are several approaches that can be considered to increase the events statistics in a collider other than increasing the luminosity, such as running the experiments for a longer time. However, this also elevates the operation expenses, while increas- ing the frequency at which the beams are delivered implies strong physical changes along the accelerator and the detectors. Therefore, it is preferred to increase the beam intensities and reduce the beams cross-sectional areas to achieve these higher luminosities. In the case where the goal is to push the limits, sometimes even beyond the machines design parameters, one must develop a detailed High Luminosity Scheme. Any high luminosity scheme on a modern collider considers--in one of their versions--the use of crab cavities to correct the geometrical reduction of the luminosity due to the beams crossing angle. In this dissertation, we present the design and testing of a proof-of-principle compact superconducting crab cavity, at 750 MHz, for the future electron-ion collider, currently under design at Jefferson Lab. In addition to the design and validation of the cavity prototype, we present the analysis of the first order beam dynamics and the integration of the crabbing systems to the interaction region. Following this, we propose the concept of twin crabs to allow machines with variable beam transverse coupling in the interaction region to have full crabbing in only the desired plane. Finally, we present recommendations to extend this work to other frequencies.

AC Loss Analysis of MgB2-Based Fully Superconducting Machines

NASA Astrophysics Data System (ADS)

Feddersen, M.; Haran, K. S.; Berg, F.

2017-12-01

Superconducting electric machines have shown potential for significant increase in power density, making them attractive for size and weight sensitive applications such as offshore wind generation, marine propulsion, and hybrid-electric aircraft propulsion. Superconductors exhibit no loss under dc conditions, though ac current and field produce considerable losses due to hysteresis, eddy currents, and coupling mechanisms. For this reason, many present machines are designed to be partially superconducting, meaning that the dc field components are superconducting while the ac armature coils are conventional conductors. Fully superconducting designs can provide increases in power density with significantly higher armature current; however, a good estimate of ac losses is required to determine the feasibility under the machines intended operating conditions. This paper aims to characterize the expected losses in a fully superconducting machine targeted towards aircraft, based on an actively-shielded, partially superconducting machine from prior work. Various factors are examined such as magnet strength, operating frequency, and machine load to produce a model for the loss in the superconducting components of the machine. This model is then used to optimize the design of the machine for minimal ac loss while maximizing power density. Important observations from the study are discussed.

Machinist (AFSC 42750).

ERIC Educational Resources Information Center

Air Univ., Gunter AFS, Ala. Extension Course Inst.

This four-volume student text is designed for use by Air Force personnel enrolled in a self-study extension course for machinists. Covered in the individual volumes are machine shop fundamentals, metallurgy and advanced machine work, advanced machine work, and tool design and shop management. Each volume in the set contains a series of lessons,…

Heidelberg Retina Tomograph 3 machine learning classifiers for glaucoma detection

PubMed Central

Townsend, K A; Wollstein, G; Danks, D; Sung, K R; Ishikawa, H; Kagemann, L; Gabriele, M L; Schuman, J S

2010-01-01

Aims To assess performance of classifiers trained on Heidelberg Retina Tomograph 3 (HRT3) parameters for discriminating between healthy and glaucomatous eyes. Methods Classifiers were trained using HRT3 parameters from 60 healthy subjects and 140 glaucomatous subjects. The classifiers were trained on all 95 variables and smaller sets created with backward elimination. Seven types of classifiers, including Support Vector Machines with radial basis (SVM-radial), and Recursive Partitioning and Regression Trees (RPART), were trained on the parameters. The area under the ROC curve (AUC) was calculated for classifiers, individual parameters and HRT3 glaucoma probability scores (GPS). Classifier AUCs and leave-one-out accuracy were compared with the highest individual parameter and GPS AUCs and accuracies. Results The highest AUC and accuracy for an individual parameter were 0.848 and 0.79, for vertical cup/disc ratio (vC/D). For GPS, global GPS performed best with AUC 0.829 and accuracy 0.78. SVM-radial with all parameters showed significant improvement over global GPS and vC/ D with AUC 0.916 and accuracy 0.85. RPART with all parameters provided significant improvement over global GPS with AUC 0.899 and significant improvement over global GPS and vC/D with accuracy 0.875. Conclusions Machine learning classifiers of HRT3 data provide significant enhancement over current methods for detection of glaucoma. PMID:18523087

A subthreshold aVLSI implementation of the Izhikevich simple neuron model.

PubMed

Rangan, Venkat; Ghosh, Abhishek; Aparin, Vladimir; Cauwenberghs, Gert

2010-01-01

We present a circuit architecture for compact analog VLSI implementation of the Izhikevich neuron model, which efficiently describes a wide variety of neuron spiking and bursting dynamics using two state variables and four adjustable parameters. Log-domain circuit design utilizing MOS transistors in subthreshold results in high energy efficiency, with less than 1pJ of energy consumed per spike. We also discuss the effects of parameter variations on the dynamics of the equations, and present simulation results that replicate several types of neural dynamics. The low power operation and compact analog VLSI realization make the architecture suitable for human-machine interface applications in neural prostheses and implantable bioelectronics, as well as large-scale neural emulation tools for computational neuroscience.

Comparison of metal versus absorbable implants in tension-band wiring: a preliminary study.

PubMed

Morgan, W J; Slowman, L A; Wotton, H M; Nairus, J

2001-04-01

The strength of tension-band wiring using bioabsorbable materials versus metal implants was assessed with a rabbit knee fusion model. Ten rabbit knees were osteotomized and rigidly fixed using a tension-band technique: five with metal implants (2 pins and 24-gauge wire) and five with absorbable implants (2-mm pins [Bionx, Blue Bell, Pa] and 1 Maxon [Davis and Geck, Danbury, Conn]). Biomechanical testing of the fixation strength was completed using a servohydraulic mechanical testing machine and a specifically designed four-point bending jig. The parameters assessed were maximal load, relative stiffness, displacement, and bending moment of the constructs. Results of the biomechanical testing showed no statistical difference between the constructs on any of the parameters assessed.

Considerations on the construction of a Powder Bed Fusion platform for Additive Manufacturing

NASA Astrophysics Data System (ADS)

Andersen, Sebastian Aagaard; Nielsen, Karl-Emil; Pedersen, David Bue; Nielsen, Jakob Skov

As the demand for moulds and other tools becomes increasingly specific and complex, an additive manufacturing approach to production is making its way to the industry through laser based consolidation of metal powder particles by a method known as powder bed fusion. This paper concerns a variety of design choices facilitating the development of an experimental powder bed fusion machine tool, capable of manufacturing metal parts with strength matching that of conventional manufactured parts and a complexity surpassing that of subtractive processes. To understand the different mechanisms acting within such an experimental machine tool, a fully open and customizable rig is constructed. Emphasizing modularity in the rig, allows alternation of lasers, scanner systems, optical elements, powder deposition, layer height, temperature, atmosphere, and powder type. Through a custom-made software platform, control of the process is achieved, which extends into a graphical user interface, easing adjustment of process parameters and the job file generation.

Human-machine interface hardware: The next decade

NASA Technical Reports Server (NTRS)

Marcus, Elizabeth A.

1991-01-01

In order to understand where human-machine interface hardware is headed, it is important to understand where we are today, how we got there, and what our goals for the future are. As computers become more capable, faster, and programs become more sophisticated, it becomes apparent that the interface hardware is the key to an exciting future in computing. How can a user interact and control a seemingly limitless array of parameters effectively? Today, the answer is most often a limitless array of controls. The link between these controls and human sensory motor capabilities does not utilize existing human capabilities to their full extent. Interface hardware for teleoperation and virtual environments is now facing a crossroad in design. Therefore, we as developers need to explore how the combination of interface hardware, human capabilities, and user experience can be blended to get the best performance today and in the future.

Predictive optimized adaptive PSS in a single machine infinite bus.

PubMed

Milla, Freddy; Duarte-Mermoud, Manuel A

2016-07-01

Power System Stabilizer (PSS) devices are responsible for providing a damping torque component to generators for reducing fluctuations in the system caused by small perturbations. A Predictive Optimized Adaptive PSS (POA-PSS) to improve the oscillations in a Single Machine Infinite Bus (SMIB) power system is discussed in this paper. POA-PSS provides the optimal design parameters for the classic PSS using an optimization predictive algorithm, which adapts to changes in the inputs of the system. This approach is part of small signal stability analysis, which uses equations in an incremental form around an operating point. Simulation studies on the SMIB power system illustrate that the proposed POA-PSS approach has better performance than the classical PSS. In addition, the effort in the control action of the POA-PSS is much less than that of other approaches considered for comparison. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Fuzzy wavelet plus a quantum neural network as a design base for power system stability enhancement.

PubMed

Ganjefar, Soheil; Tofighi, Morteza; Karami, Hamidreza

2015-11-01

In this study, we introduce an indirect adaptive fuzzy wavelet neural controller (IAFWNC) as a power system stabilizer to damp inter-area modes of oscillations in a multi-machine power system. Quantum computing is an efficient method for improving the computational efficiency of neural networks, so we developed an identifier based on a quantum neural network (QNN) to train the IAFWNC in the proposed scheme. All of the controller parameters are tuned online based on the Lyapunov stability theory to guarantee the closed-loop stability. A two-machine, two-area power system equipped with a static synchronous series compensator as a series flexible ac transmission system was used to demonstrate the effectiveness of the proposed controller. The simulation and experimental results demonstrated that the proposed IAFWNC scheme can achieve favorable control performance. Copyright © 2015 Elsevier Ltd. All rights reserved.

Computation of the Distribution of the Fiber-Matrix Interface Cracks in the Edge Trimming of CFRP

NASA Astrophysics Data System (ADS)

Wang, Fu-ji; Zhang, Bo-yu; Ma, Jian-wei; Bi, Guang-jian; Hu, Hai-bo

2018-04-01

Edge trimming is commonly used to bring the CFRP components to right dimension and shape in aerospace industries. However, various forms of undesirable machining damage occur frequently which will significantly decrease the material performance of CFRP. The damage is difficult to predict and control due to the complicated changing laws, causing unsatisfactory machining quality of CFRP components. Since the most of damage has the same essence: the fiber-matrix interface cracks, this study aims to calculate the distribution of them in edge trimming of CFRP, thereby to obtain the effects of the machining parameters, which could be helpful to guide the optimal selection of the machining parameters in engineering. Through the orthogonal cutting experiments, the quantitative relation between the fiber-matrix interface crack depth and the fiber cutting angle, cutting depth as well as cutting speed is established. According to the analysis on material removal process on any location of the workpiece in edge trimming, the instantaneous cutting parameters are calculated, and the formation process of the fiber-matrix interface crack is revealed. Finally, the computational method for the fiber-matrix interface cracks in edge trimming of CFRP is proposed. Upon the computational results, it is found that the fiber orientations of CFRP workpieces is the most significant factor on the fiber-matrix interface cracks, which can not only change the depth of them from micrometers to millimeters, but control the distribution image of them. Other machining parameters, only influence the fiber-matrix interface cracks depth but have little effect on the distribution image.

IN718 Additive Manufacturing Properties and Influences

NASA Technical Reports Server (NTRS)

Lambert, Dennis M.

2015-01-01

The results of tensile, fracture, and fatigue testing of IN718 coupons produced using the selective laser melting (SLM) additive manufacturing technique are presented. The data have been "sanitized" to remove the numerical values, although certain references to material standards are provided. This document provides some knowledge of the effect of variation of controlled build parameters used in the SLM process, a snapshot of the capabilities of SLM in industry at present, and shares some of the lessons learned along the way. For the build parameter characterization, the parameters were varied over a range that was centered about the machine manufacturer's recommended value, and in each case they were varied individually, although some co-variance of those parameters would be expected. Tensile, fracture, and high-cycle fatigue properties equivalent to wrought IN718 are achievable with SLM-produced IN718. Build and post-build processes need to be determined and then controlled to established limits to accomplish this. It is recommended that a multi-variable evaluation, e.g., design-of experiment (DOE), of the build parameters be performed to better evaluate the co-variance of the parameters.

IN718 Additive Manufacturing Properties and Influences

NASA Technical Reports Server (NTRS)

Lambert, Dennis M.

2015-01-01

The results of tensile, fracture, and fatigue testing of IN718 coupons produced using the selective laser melting (SLM) additive manufacturing technique are presented. The data has been "generalized" to remove the numerical values, although certain references to material standards are provided. This document provides some knowledge of the effect of variation of controlled build parameters used in the SLM process, a snapshot of the capabilities of SLM in industry at present, and shares some of the lessons learned along the way. For the build parameter characterization, the parameters were varied over a range about the machine manufacturer's recommended value, and in each case they were varied individually, although some co-variance of those parameters would be expected. SLM-produced IN718, tensile, fracture, and high-cycle fatigue properties equivalent to wrought IN718 are achievable. Build and post-build processes need to be determined and then controlled to established limits to accomplish this. It is recommended that a multi-variable evaluation, e.g., design-of-experiment (DOE), of the build parameters be performed to better evaluate the co-variance of the parameters.

Temperature based Restricted Boltzmann Machines

NASA Astrophysics Data System (ADS)

Li, Guoqi; Deng, Lei; Xu, Yi; Wen, Changyun; Wang, Wei; Pei, Jing; Shi, Luping

2016-01-01

Restricted Boltzmann machines (RBMs), which apply graphical models to learning probability distribution over a set of inputs, have attracted much attention recently since being proposed as building blocks of multi-layer learning systems called deep belief networks (DBNs). Note that temperature is a key factor of the Boltzmann distribution that RBMs originate from. However, none of existing schemes have considered the impact of temperature in the graphical model of DBNs. In this work, we propose temperature based restricted Boltzmann machines (TRBMs) which reveals that temperature is an essential parameter controlling the selectivity of the firing neurons in the hidden layers. We theoretically prove that the effect of temperature can be adjusted by setting the parameter of the sharpness of the logistic function in the proposed TRBMs. The performance of RBMs can be improved by adjusting the temperature parameter of TRBMs. This work provides a comprehensive insights into the deep belief networks and deep learning architectures from a physical point of view.

Dual stator winding variable speed asynchronous generator: optimal design and experiments

NASA Astrophysics Data System (ADS)

Tutelea, L. N.; Deaconu, S. I.; Popa, G. N.

2015-06-01

In the present paper is carried out a theoretical and experimental study of dual stator winding squirrel cage asynchronous generator (DSWA) behavior in the presence of saturation regime (non-sinusoidal) due to the variable speed operation. The main aims are the determination of the relations of calculating the equivalent parameters of the machine windings to optimal design using a Matlab code. Issue is limited to three phase range of double stator winding cage-induction generator of small sized powers, the most currently used in the small adjustable speed wind or hydro power plants. The tests were carried out using three-phase asynchronous generator having rated power of 6 [kVA].

Measurement of the Thermal Expansion Coefficient for Ultra-High Temperatures up to 3000 K

NASA Astrophysics Data System (ADS)

Kompan, T. A.; Kondratiev, S. V.; Korenev, A. S.; Puhov, N. F.; Inochkin, F. M.; Kruglov, S. K.; Bronshtein, I. G.

2018-03-01

The paper is devoted to a new high-temperature dilatometer, a part of the State Primary Standard of the thermal expansion coefficient (TEC) unit. The dilatometer is designed for investigation and certification of materials for TEC standards in the range of extremely high temperatures. The critical review of existing methods of TEC measurements is given. Also, the design, principles of operation and metrological parameters of the new device are described. The main attention is paid to the system of machine vision that allows accurate measurement of elongation at high temperatures. The results of TEC measurements for graphite GIP-4, single crystal Al2O3, and some other materials are also presented.

Heat engine generator control system

DOEpatents

Rajashekara, K.; Gorti, B.V.; McMullen, S.R.; Raibert, R.J.

1998-05-12

An electrical power generation system includes a heat engine having an output member operatively coupled to the rotor of a dynamoelectric machine. System output power is controlled by varying an electrical parameter of the dynamoelectric machine. A power request signal is related to an engine speed and the electrical parameter is varied in accordance with a speed control loop. Initially, the sense of change in the electrical parameter in response to a change in the power request signal is opposite that required to effectuate a steady state output power consistent with the power request signal. Thereafter, the electrical parameter is varied to converge the output member speed to the speed known to be associated with the desired electrical output power. 8 figs.

Heat engine generator control system

DOEpatents

Rajashekara, Kaushik; Gorti, Bhanuprasad Venkata; McMullen, Steven Robert; Raibert, Robert Joseph

1998-01-01

An electrical power generation system includes a heat engine having an output member operatively coupled to the rotor of a dynamoelectric machine. System output power is controlled by varying an electrical parameter of the dynamoelectric machine. A power request signal is related to an engine speed and the electrical parameter is varied in accordance with a speed control loop. Initially, the sense of change in the electrical parameter in response to a change in the power request signal is opposite that required to effectuate a steady state output power consistent with the power request signal. Thereafter, the electrical parameter is varied to converge the output member speed to the speed known to be associated with the desired electrical output power.

Development of sacrificial support fixture using deflection analysis

NASA Astrophysics Data System (ADS)

Ramteke, Ashwini M.; Ashtankar, Kishor M.

2018-04-01

Sacrificial support fixtures are the structures used to hold the part during machining while rotating the part about the fourth axis of CNC machining. In Four axis CNC machining part is held in a indexer which is rotated about the fourth axis of rotation. So using traditional fixturing devices to hold the part during machining such as jigs, v blocks and clamping plates needs a several set ups, manufacturing time which increase the cost associated with it. Since the part is rotated about the axis of rotation in four axis CNC machining so using traditional fixturing devices to hold the part while machining we need to reorient the fixture each time for particular orientation of part about the axis of rotation. So our proposed methodology of fixture design eliminates the cost associate with the complicated fixture design for customized parts which in turn reduces the time of manufacturing of the fixtures. But while designing the layout of the fixtures it is found out that the machining the part using four axis CNC machining the accurate machining of the part is directly proportional to the deflection produced in a part. So to machine an accurate part the deflection produced in a part should be minimum. We assume that the deflection produced in a part is a result of the deflection produced in a sacrificial support fixture while machining. So this paper provides the study of the deflection checking in a part machined using sacrificial support fixture by using FEA analysis.

Application of grey-fuzzy approach in parametric optimization of EDM process in machining of MDN 300 steel

NASA Astrophysics Data System (ADS)

Protim Das, Partha; Gupta, P.; Das, S.; Pradhan, B. B.; Chakraborty, S.

2018-01-01

Maraging steel (MDN 300) find its application in many industries as it exhibits high hardness which are very difficult to machine material. Electro discharge machining (EDM) is an extensively popular machining process which can be used in machining of such materials. Optimization of response parameters are essential for effective machining of these materials. Past researchers have already used Taguchi for obtaining the optimal responses of EDM process for this material with responses such as material removal rate (MRR), tool wear rate (TWR), relative wear ratio (RWR), and surface roughness (SR) considering discharge current, pulse on time, pulse off time, arc gap, and duty cycle as process parameters. In this paper, grey relation analysis (GRA) with fuzzy logic is applied to this multi objective optimization problem to check the responses by an implementation of the derived parametric setting. It was found that the parametric setting derived by the proposed method results in better a response than those reported by the past researchers. Obtained results are also verified using the technique for order of preference by similarity to ideal solution (TOPSIS). The predicted result also shows that there is a significant improvement in comparison to the results of past researchers.

Machine processing of ERTS and ground truth data

NASA Technical Reports Server (NTRS)

Rogers, R. H. (Principal Investigator); Peacock, K.

1973-01-01

The author has identified the following significant results. Results achieved by ERTS-Atmospheric Experiment PR303, whose objective is to establish a radiometric calibration technique, are reported. This technique, which determines and removes solar and atmospheric parameters that degrade the radiometric fidelity of ERTS-1 data, transforms the ERTS-1 sensor radiance measurements to absolute target reflectance signatures. A radiant power measuring instrument and its use in determining atmospheric parameters needed for ground truth are discussed. The procedures used and results achieved in machine processing ERTS-1 computer -compatible tapes and atmospheric parameters to obtain target reflectance are reviewed.

Optimal shutdown management

NASA Astrophysics Data System (ADS)

Bottasso, C. L.; Croce, A.; Riboldi, C. E. D.

2014-06-01

The paper presents a novel approach for the synthesis of the open-loop pitch profile during emergency shutdowns. The problem is of interest in the design of wind turbines, as such maneuvers often generate design driving loads on some of the machine components. The pitch profile synthesis is formulated as a constrained optimal control problem, solved numerically using a direct single shooting approach. A cost function expressing a compromise between load reduction and rotor overspeed is minimized with respect to the unknown blade pitch profile. Constraints may include a load reduction not-to-exceed the next dominating loads, a not-to-be-exceeded maximum rotor speed, and a maximum achievable blade pitch rate. Cost function and constraints are computed over a possibly large number of operating conditions, defined so as to cover as well as possible the operating situations encountered in the lifetime of the machine. All such conditions are simulated by using a high-fidelity aeroservoelastic model of the wind turbine, ensuring the accuracy of the evaluation of all relevant parameters. The paper demonstrates the capabilities of the novel proposed formulation, by optimizing the pitch profile of a multi-MW wind turbine. Results show that the procedure can reliably identify optimal pitch profiles that reduce design-driving loads, in a fully automated way.

A survey of anthropometry of rural agricultural workers in Enugu State, south-eastern Nigeria.

PubMed

Obi, Okey Francis; Ugwuishiwu, Boniface O; Adeboye, Busayo S

2015-01-01

In developed countries, large amount of anthropometric data are available for reference purposes; however, anthropometric data of Nigerian populace are lacking. As a result, most agricultural machines and equipment used are designed using anthropometric data from other populations of the world. A total of 377 rural agricultural workers within the age limit of 18-45 years, who are involved in different agricultural activities, were selected from six rural agriculture-based communities in Enugu state. Thirty-six anthropometric body dimensions were measured including age and body weight. A comparison between the male and female data indicated that data obtained from male agricultural workers were higher than that obtained from their female counterparts in all body dimensions except chest (bust) depth, abdominal breadth and hip breadth (sitting). In terms of design parameters, it was observed that the data from Nigerian agricultural workers were different from that obtained from agricultural workers in north-eastern India. Practitioner Summary. Anthropometric data of Nigeria populace are lacking. As a result, most agricultural machines and equipment used are designed using anthropometric data from other populations of the world. It was observed that the data from Nigerian agricultural workers were different from that obtained from agricultural workers in north-eastern India.

An Analysis of the Effects of Chip-groove Geometry on Machining Performance Using Finite Element Methods

NASA Astrophysics Data System (ADS)

Ee, K. C.; Dillon, O. W.; Jawahir, I. S.

2004-06-01

This paper discusses the influence of major chip-groove parameters of a cutting tool on the chip formation process in orthogonal machining using finite element (FE) methods. In the FE formulation, a thermal elastic-viscoplastic material model is used together with a modified Johnson-Cook material law for the flow stress. The chip back-flow angle and the chip up-curl radius are calculated for a range of cutting conditions by varying the chip-groove parameters. The analysis provides greater understanding of the effectiveness of chip-groove configurations and points a way to correlate cutting conditions with tool-wear when machining with a grooved cutting tool.

Supervised Machine Learning for Regionalization of Environmental Data: Distribution of Uranium in Groundwater in Ukraine

NASA Astrophysics Data System (ADS)

Govorov, Michael; Gienko, Gennady; Putrenko, Viktor

2018-05-01

In this paper, several supervised machine learning algorithms were explored to define homogeneous regions of con-centration of uranium in surface waters in Ukraine using multiple environmental parameters. The previous study was focused on finding the primary environmental parameters related to uranium in ground waters using several methods of spatial statistics and unsupervised classification. At this step, we refined the regionalization using Artifi-cial Neural Networks (ANN) techniques including Multilayer Perceptron (MLP), Radial Basis Function (RBF), and Convolutional Neural Network (CNN). The study is focused on building local ANN models which may significantly improve the prediction results of machine learning algorithms by taking into considerations non-stationarity and autocorrelation in spatial data.

Prototype Development of Remote Operated Hot Uniaxial Press (ROHUP) to Fabricate Advanced Tc-99 Bearing Ceramic Waste Forms - 13381

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alaniz, Ariana J.; Delgado, Luc R.; Werbick, Brett M.

The objective of this senior student project is to design and build a prototype construction of a machine that simultaneously provides the proper pressure and temperature parameters to sinter ceramic powders in-situ to create pellets of rather high densities of above 90% (theoretical). This ROHUP (Remote Operated Hot Uniaxial Press) device is designed specifically to fabricate advanced ceramic Tc-99 bearing waste forms and therefore radiological barriers have been included in the system. The HUP features electronic control and feedback systems to set and monitor pressure, load, and temperature parameters. This device operates wirelessly via portable computer using Bluetooth{sup R} technology.more » The HUP device is designed to fit in a standard atmosphere controlled glove box to further allow sintering under inert conditions (e.g. under Ar, He, N{sub 2}). This will further allow utilizing this HUP for other potential applications, including radioactive samples, novel ceramic waste forms, advanced oxide fuels, air-sensitive samples, metallic systems, advanced powder metallurgy, diffusion experiments and more. (authors)« less

Technology development plan: Geotechnical survey systems for OTEC (Ocean Thermal Energy Conversion) cold water pipes

NASA Astrophysics Data System (ADS)

Valent, Philip J.; Riggins, Michael

1989-04-01

An overview is given of current and developing technologies and techniques for performing geotechnical investigations for siting and designing Cold Water Pipes (CWP) for shelf-resting Ocean Thermal Energy Conversion (OTEC) power plants. The geotechnical in situ tools used to measure the required parameters and the equipment/systems used to deploy these tools are identified. The capabilities of these geotechnical tools and deployment systems are compared to the data requirements for the CWP foundation/anchor design, and shortfalls are identified. For the last phase of geotechnical data gathering for design, a drillship will be required to perform soil boring work, to obtain required high quality sediment samples for laboratory dynamic testing, and to perform deep penetration in situ tests. To remedy shortfalls and to reduce the future OTEC CWP geotechnical survey costs, it is recommended that a seafloor resting machine be developed to advance the friction cone penetrometer, and also probably a pressuremeter, to provide geotechnical parameters to shallow subseafloor penetrations on slopes of 35 deg and in water depths to 1300 m.

The use of modern measurement techniques for designing pro ecological constructions

NASA Astrophysics Data System (ADS)

Wieczorowski, Michał; Gapiński, Bartosz; Szymański, Maciej; Rękas, Artur

2017-10-01

In the paper some possibilities of application modern length and angle metrology techniques to design constructions that support ecology were presented. The paper is based on a project where a lighter bus and train car seat was developed. Different options were presented including static and dynamic photogrammetry, computed tomography and thermography. Research related with dynamic behaviour of designed structures gave input to determine deformation of a seat and passengers sitting on it during communication accidents. Works connected to strength of construction elements made it possible to optimize its dimensions maintaining proper durability. Metrological actions taken in relation to production machines and equipment enabled to better recognize phenomena that take place during manufacturing process and to correct its parameters, what in turns also contributed to slim down the construction.

Banknotes and unattended cash transactions

NASA Astrophysics Data System (ADS)

Bernardini, Ronald R.

2000-04-01

There is a 64 billion dollar annual unattended cash transaction business in the US with 10 to 20 million daily transactions. Even small problems with the machine readability of banknotes can quickly become a major problem to the machine manufacturer and consumer. Traditional note designs incorporate overt security features for visual validation by the public. Many of these features such as fine line engraving, microprinting and watermarks are unsuitable as machine readable features in low cost note acceptors. Current machine readable features, mostly covert, were designed and implemented with the central banks in mind. These features are only usable by the banks large, high speed currency sorting and validation equipment. New note designs should consider and provide for low cost not acceptors, implementing features developed for inexpensive sensing technologies. Machine readable features are only as good as their consistency. Quality of security features as well as that of the overall printing process must be maintained to ensure reliable and secure operation of note readers. Variations in printing and of the components used to make the note are one of the major causes of poor performance in low cost note acceptors. The involvement of machine manufacturers in new currency designs will aid note producers in the design of a note that is machine friendly, helping to secure the acceptance of the note by the public as well as acting asa deterrent to fraud.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hasan, Iftekhar; Husain, Tausif; Sozer, Yilmaz

This paper proposes an analytical machine design tool using magnetic equivalent circuit (MEC)-based particle swarm optimization (PSO) for a double-sided, flux-concentrating transverse flux machine (TFM). The magnetic equivalent circuit method is applied to analytically establish the relationship between the design objective and the input variables of prospective TFM designs. This is computationally less intensive and more time efficient than finite element solvers. A PSO algorithm is then used to design a machine with the highest torque density within the specified power range along with some geometric design constraints. The stator pole length, magnet length, and rotor thickness are the variablesmore » that define the optimization search space. Finite element analysis (FEA) was carried out to verify the performance of the MEC-PSO optimized machine. The proposed analytical design tool helps save computation time by at least 50% when compared to commercial FEA-based optimization programs, with results found to be in agreement with less than 5% error.« less

34 CFR 395.17 - Suspension of designation as State licensing agency.

Code of Federal Regulations, 2013 CFR

2013-07-01

... lapse of a reasonable time, the Secretary is of the opinion that such failure to comply still continues... protection of Federal property on which vending machines subject to the requirements of § 395.32 are located in the State. Upon the suspension of such designation, vending machine income from vending machines...

34 CFR 395.17 - Suspension of designation as State licensing agency.

Code of Federal Regulations, 2012 CFR

2012-07-01

... lapse of a reasonable time, the Secretary is of the opinion that such failure to comply still continues... protection of Federal property on which vending machines subject to the requirements of § 395.32 are located in the State. Upon the suspension of such designation, vending machine income from vending machines...

34 CFR 395.17 - Suspension of designation as State licensing agency.

Code of Federal Regulations, 2014 CFR

2014-07-01

... lapse of a reasonable time, the Secretary is of the opinion that such failure to comply still continues... protection of Federal property on which vending machines subject to the requirements of § 395.32 are located in the State. Upon the suspension of such designation, vending machine income from vending machines...

34 CFR 395.17 - Suspension of designation as State licensing agency.

Code of Federal Regulations, 2010 CFR

2010-07-01

... lapse of a reasonable time, the Secretary is of the opinion that such failure to comply still continues... protection of Federal property on which vending machines subject to the requirements of § 395.32 are located in the State. Upon the suspension of such designation, vending machine income from vending machines...

34 CFR 395.17 - Suspension of designation as State licensing agency.

Code of Federal Regulations, 2011 CFR

2011-07-01

... lapse of a reasonable time, the Secretary is of the opinion that such failure to comply still continues... protection of Federal property on which vending machines subject to the requirements of § 395.32 are located in the State. Upon the suspension of such designation, vending machine income from vending machines...

Mechanical design of walking machines.

PubMed

Arikawa, Keisuke; Hirose, Shigeo

2007-01-15

The performance of existing actuators, such as electric motors, is very limited, be it power-weight ratio or energy efficiency. In this paper, we discuss the method to design a practical walking machine under this severe constraint with focus on two concepts, the gravitationally decoupled actuation (GDA) and the coupled drive. The GDA decouples the driving system against the gravitational field to suppress generation of negative power and improve energy efficiency. On the other hand, the coupled drive couples the driving system to distribute the output power equally among actuators and maximize the utilization of installed actuator power. First, we depict the GDA and coupled drive in detail. Then, we present actual machines, TITAN-III and VIII, quadruped walking machines designed on the basis of the GDA, and NINJA-I and II, quadruped wall walking machines designed on the basis of the coupled drive. Finally, we discuss walking machines that travel on three-dimensional terrain (3D terrain), which includes the ground, walls and ceiling. Then, we demonstrate with computer simulation that we can selectively leverage GDA and coupled drive by walking posture control.

Optimisation of warpage on thin shell plastic part using response surface methodology (RSM) and glowworm swarm optimisation (GSO)

NASA Astrophysics Data System (ADS)

Asyirah, B. N.; Shayfull, Z.; Nasir, S. M.; Fathullah, M.; Hazwan, M. H. M.

2017-09-01

In manufacturing a variety of parts, plastic injection moulding is widely use. The injection moulding process parameters have played important role that affects the product's quality and productivity. There are many approaches in minimising the warpage ans shrinkage such as artificial neural network, genetic algorithm, glowworm swarm optimisation and hybrid approaches are addressed. In this paper, a systematic methodology for determining a warpage and shrinkage in injection moulding process especially in thin shell plastic parts are presented. To identify the effects of the machining parameters on the warpage and shrinkage value, response surface methodology is applied. In thos study, a part of electronic night lamp are chosen as the model. Firstly, experimental design were used to determine the injection parameters on warpage for different thickness value. The software used to analyse the warpage is Autodesk Moldflow Insight (AMI) 2012.

Optimal nonlinear information processing capacity in delay-based reservoir computers

NASA Astrophysics Data System (ADS)

Grigoryeva, Lyudmila; Henriques, Julie; Larger, Laurent; Ortega, Juan-Pablo

2015-09-01

Reservoir computing is a recently introduced brain-inspired machine learning paradigm capable of excellent performances in the processing of empirical data. We focus in a particular kind of time-delay based reservoir computers that have been physically implemented using optical and electronic systems and have shown unprecedented data processing rates. Reservoir computing is well-known for the ease of the associated training scheme but also for the problematic sensitivity of its performance to architecture parameters. This article addresses the reservoir design problem, which remains the biggest challenge in the applicability of this information processing scheme. More specifically, we use the information available regarding the optimal reservoir working regimes to construct a functional link between the reservoir parameters and its performance. This function is used to explore various properties of the device and to choose the optimal reservoir architecture, thus replacing the tedious and time consuming parameter scannings used so far in the literature.

Optimal nonlinear information processing capacity in delay-based reservoir computers.

PubMed

Grigoryeva, Lyudmila; Henriques, Julie; Larger, Laurent; Ortega, Juan-Pablo

2015-09-11

Reservoir computing is a recently introduced brain-inspired machine learning paradigm capable of excellent performances in the processing of empirical data. We focus in a particular kind of time-delay based reservoir computers that have been physically implemented using optical and electronic systems and have shown unprecedented data processing rates. Reservoir computing is well-known for the ease of the associated training scheme but also for the problematic sensitivity of its performance to architecture parameters. This article addresses the reservoir design problem, which remains the biggest challenge in the applicability of this information processing scheme. More specifically, we use the information available regarding the optimal reservoir working regimes to construct a functional link between the reservoir parameters and its performance. This function is used to explore various properties of the device and to choose the optimal reservoir architecture, thus replacing the tedious and time consuming parameter scannings used so far in the literature.

Model reference adaptive control (MRAC)-based parameter identification applied to surface-mounted permanent magnet synchronous motor

NASA Astrophysics Data System (ADS)

Zhong, Chongquan; Lin, Yaoyao

2017-11-01

In this work, a model reference adaptive control-based estimated algorithm is proposed for online multi-parameter identification of surface-mounted permanent magnet synchronous machines. By taking the dq-axis equations of a practical motor as the reference model and the dq-axis estimation equations as the adjustable model, a standard model-reference-adaptive-system-based estimator was established. Additionally, the Popov hyperstability principle was used in the design of the adaptive law to guarantee accurate convergence. In order to reduce the oscillation of identification result, this work introduces a first-order low-pass digital filter to improve precision regarding the parameter estimation. The proposed scheme was then applied to an SPM synchronous motor control system without any additional circuits and implemented using a DSP TMS320LF2812. For analysis, the experimental results reveal the effectiveness of the proposed method.

Thermo-Mechanical Calculations of Hybrid Rotary Friction Welding at Equal Diameter Copper Bars and Effects of Essential Parameters on Dependent Special Variables

NASA Astrophysics Data System (ADS)

Parsa, M. H.; Davari, H.; Hadian, A. M.; Ahmadabadi, M. Nili

2007-05-01

Hybrid Rotary Friction Welding is a modified type of common rotary friction welding processes. In this welding method parameters such as pressure, angular velocity and time of welding control temperature, stress, strain and their variations. These dependent factors play an important rule in defining optimum process parameters combinations in order to improve the design and manufacturing of welding machines and quality of welded parts. Thermo-mechanical simulation of friction welding has been carried out and it has been shown that, simulation is an important tool for prediction of generated heat and strain at the weld interface and can be used for prediction of microstructure and evaluation of quality of welds. For simulation of Hybrid Rotary Friction Welding, a commercial finite element program has been used and the effects of pressure and rotary velocity of rotary part on temperature and strain variations have been investigated.

Optimal nonlinear information processing capacity in delay-based reservoir computers

PubMed Central

Grigoryeva, Lyudmila; Henriques, Julie; Larger, Laurent; Ortega, Juan-Pablo

2015-01-01

Reservoir computing is a recently introduced brain-inspired machine learning paradigm capable of excellent performances in the processing of empirical data. We focus in a particular kind of time-delay based reservoir computers that have been physically implemented using optical and electronic systems and have shown unprecedented data processing rates. Reservoir computing is well-known for the ease of the associated training scheme but also for the problematic sensitivity of its performance to architecture parameters. This article addresses the reservoir design problem, which remains the biggest challenge in the applicability of this information processing scheme. More specifically, we use the information available regarding the optimal reservoir working regimes to construct a functional link between the reservoir parameters and its performance. This function is used to explore various properties of the device and to choose the optimal reservoir architecture, thus replacing the tedious and time consuming parameter scannings used so far in the literature. PMID:26358528

Application of Taguchi method to optimization of surface roughness during precise turning of NiTi shape memory alloy

NASA Astrophysics Data System (ADS)

Kowalczyk, M.

2017-08-01

This paper describes the research results of surface quality research after the NiTi shape memory alloy (Nitinol) precise turning by the tools with edges made of polycrystalline diamonds (PCD). Nitinol, a nearly equiatomic nickel-titanium shape memory alloy, has wide applications in the arms industry, military, medicine and aerospace industry, and industrial robots. Due to their specific properties NiTi alloys are known to be difficult-to-machine materials particularly by using conventional techniques. The research trials were conducted for three independent parameters (vc, f, ap) affecting the surface roughness were analyzed. The choice of parameter configurations were performed by factorial design methods using orthogonal plan type L9, with three control factors, changing on three levels, developed by G. Taguchi. S/N ratio and ANOVA analyses were performed to identify the best of cutting parameters influencing surface roughness.

Optimisation Of Cutting Parameters Of Composite Material Laser Cutting Process By Taguchi Method

NASA Astrophysics Data System (ADS)

Lokesh, S.; Niresh, J.; Neelakrishnan, S.; Rahul, S. P. Deepak

2018-03-01

The aim of this work is to develop a laser cutting process model that can predict the relationship between the process input parameters and resultant surface roughness, kerf width characteristics. The research conduct is based on the Design of Experiment (DOE) analysis. Response Surface Methodology (RSM) is used in this work. It is one of the most practical and most effective techniques to develop a process model. Even though RSM has been used for the optimization of the laser process, this research investigates laser cutting of materials like Composite wood (veneer)to be best circumstances of laser cutting using RSM process. The input parameters evaluated are focal length, power supply and cutting speed, the output responses being kerf width, surface roughness, temperature. To efficiently optimize and customize the kerf width and surface roughness characteristics, a machine laser cutting process model using Taguchi L9 orthogonal methodology was proposed.

Study on Temperature and Synthetic Compensation of Piezo-Resistive Differential Pressure Sensors by Coupled Simulated Annealing and Simplex Optimized Kernel Extreme Learning Machine

PubMed Central

Li, Ji; Hu, Guoqing; Zhou, Yonghong; Zou, Chong; Peng, Wei; Alam SM, Jahangir

2017-01-01

As a high performance-cost ratio solution for differential pressure measurement, piezo-resistive differential pressure sensors are widely used in engineering processes. However, their performance is severely affected by the environmental temperature and the static pressure applied to them. In order to modify the non-linear measuring characteristics of the piezo-resistive differential pressure sensor, compensation actions should synthetically consider these two aspects. Advantages such as nonlinear approximation capability, highly desirable generalization ability and computational efficiency make the kernel extreme learning machine (KELM) a practical approach for this critical task. Since the KELM model is intrinsically sensitive to the regularization parameter and the kernel parameter, a searching scheme combining the coupled simulated annealing (CSA) algorithm and the Nelder-Mead simplex algorithm is adopted to find an optimal KLEM parameter set. A calibration experiment at different working pressure levels was conducted within the temperature range to assess the proposed method. In comparison with other compensation models such as the back-propagation neural network (BP), radius basis neural network (RBF), particle swarm optimization optimized support vector machine (PSO-SVM), particle swarm optimization optimized least squares support vector machine (PSO-LSSVM) and extreme learning machine (ELM), the compensation results show that the presented compensation algorithm exhibits a more satisfactory performance with respect to temperature compensation and synthetic compensation problems. PMID:28422080

Study on Temperature and Synthetic Compensation of Piezo-Resistive Differential Pressure Sensors by Coupled Simulated Annealing and Simplex Optimized Kernel Extreme Learning Machine.

PubMed

Li, Ji; Hu, Guoqing; Zhou, Yonghong; Zou, Chong; Peng, Wei; Alam Sm, Jahangir

2017-04-19

As a high performance-cost ratio solution for differential pressure measurement, piezo-resistive differential pressure sensors are widely used in engineering processes. However, their performance is severely affected by the environmental temperature and the static pressure applied to them. In order to modify the non-linear measuring characteristics of the piezo-resistive differential pressure sensor, compensation actions should synthetically consider these two aspects. Advantages such as nonlinear approximation capability, highly desirable generalization ability and computational efficiency make the kernel extreme learning machine (KELM) a practical approach for this critical task. Since the KELM model is intrinsically sensitive to the regularization parameter and the kernel parameter, a searching scheme combining the coupled simulated annealing (CSA) algorithm and the Nelder-Mead simplex algorithm is adopted to find an optimal KLEM parameter set. A calibration experiment at different working pressure levels was conducted within the temperature range to assess the proposed method. In comparison with other compensation models such as the back-propagation neural network (BP), radius basis neural network (RBF), particle swarm optimization optimized support vector machine (PSO-SVM), particle swarm optimization optimized least squares support vector machine (PSO-LSSVM) and extreme learning machine (ELM), the compensation results show that the presented compensation algorithm exhibits a more satisfactory performance with respect to temperature compensation and synthetic compensation problems.