NASA Astrophysics Data System (ADS)
Kumano, Teruhisa
As known well, two of the fundamental processes which give rise to voltage collapse in power systems are the on load tap changers of transformers and dynamic characteristics of loads such as induction machines. It has been well established that, comparing among these two, the former makes slower collapse while the latter makes faster. However, in realistic situations, the load level of each induction machine is not uniform and it is well expected that only a part of loads collapses first, followed by collapse process of each load which did not go into instability during the preceding collapses. In such situations the over all equivalent collapse behavior viewed from bulk transmission level becomes somewhat different from the simple collapse driven by one aggregated induction machine. This paper studies the process of cascaded voltage collapse among many induction machines by time simulation, where load distribution on a feeder line is modeled by several hundreds of induction machines and static impedance loads. It is shown that in some cases voltage collapse really cascades among induction machines, where the macroscopic load dynamics viewed from upper voltage level makes slower collapse than expected by the aggregated load model. Also shown is the effects of machine protection of induction machines, which also makes slower collapse.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Reusch, Joshua A.; Bodner, Grant M.; Bongard, Michael W.
This public data set contains openly-documented, machine readable digital research data corresponding to figures published in J.A. Reusch et al., 'Non-inductively Driven Tokamak Plasmas at Near-Unity βt in the Pegasus Toroidal Experiment,' Phys. Plasmas 25, 056101 (2018).
Energy saving concepts relating to induction generators
NASA Technical Reports Server (NTRS)
Nola, F. J.
1980-01-01
Energy saving concepts relating to induction generators are presented. The first describes a regenerative scheme using an induction generator as a variable load for prime movers under test is described. A method for reducing losses in induction machines used specifically as wind driven generators is also described.
Miniature Gas-Circulating Machine
NASA Technical Reports Server (NTRS)
Swift, Walter L.; Valenzuela, Javier A.; Sixsmith, Herbert; Nutt, William E.
1993-01-01
Proposed gas-circulating machine consists essentially of centrifugal pump driven by induction motor. Noncontact bearings suppress wear and contamination. Used to circulate helium (or possibly hydrogen or another gas) in regeneration sorption-compressor refrigeration system aboard spacecraft. Also proves useful in terrestrial applications in which long life, reliability, and low contamination essential.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Schlossberg, David J.; Bodner, Grant M.; Bongard, Michael W.
This public data set contains openly-documented, machine readable digital research data corresponding to figures published in D.J. Schlossberg et al., 'Non-Inductively Driven Tokamak Plasmas at Near-Unity Toroidal Beta,' Phys. Rev. Lett. 119, 035001 (2017).
A solid-state controller for a wind-driven slip-ring induction generator
NASA Astrophysics Data System (ADS)
Velayudhan, C.; Bundell, J. H.; Leary, B. G.
1984-08-01
The three-phase induction generator appears to become the preferred choice for wind-powered systems operated in parallel with existing power systems. A problem arises in connection with the useful operating speed range of the squirrel-cage machine, which is relatively narrow, as, for instance, in the range from 1 to 1.15. Efficient extraction of energy from a wind turbine, on the other hand, requires a speed range, perhaps as large as 1 to 3. One approach for 'matching' the generator to the turbine for the extraction of maximum power at any usable wind speed involves the use of a slip-ring induction machine. The power demand of the slip-ring machine can be matched to the available output from the wind turbine by modifying the speed-torque characteristics of the generator. A description is presented of a simple electronic rotor resistance controller which can optimize the power taken from a wind turbine over the full speed range.
Design and performance tests of a distributed power-driven wheel loader
NASA Astrophysics Data System (ADS)
Jin, Xiaolin; Shi, Laide; Bian, Yongming
2010-03-01
An improved ZLM15B distributed power-driven wheel loader was designed, whose travel and brake system was accomplished by two permanent magnet synchronous motorized-wheels instead of traditional mechanical components, and whose hydraulic systems such as the working device system and steering system were both actuated by an induction motor. All above systems were flexibly coupled with 3-phase 380VAC electric power with which the diesel engine power is replaced. On the level cement road, traveling, braking, traction and steering tests were carried out separately under non-load and heavy-load conditions. Data show that machine speed is 5 km/h around and travel efficiency of motorized-wheels is above 95%; that machine braking deceleration is between 0.5 and 0.64 m/s2 but efficiency of motorized-wheels is less than 10%; that maximum machine traction is above 2t while efficiency of motorized-wheels is more than 90% and that adaptive differential steering can be smoothly achieved by motorized-wheels.
Design and performance tests of a distributed power-driven wheel loader
NASA Astrophysics Data System (ADS)
Jin, Xiaolin; Shi, Laide; Bian, Yongming
2009-12-01
An improved ZLM15B distributed power-driven wheel loader was designed, whose travel and brake system was accomplished by two permanent magnet synchronous motorized-wheels instead of traditional mechanical components, and whose hydraulic systems such as the working device system and steering system were both actuated by an induction motor. All above systems were flexibly coupled with 3-phase 380VAC electric power with which the diesel engine power is replaced. On the level cement road, traveling, braking, traction and steering tests were carried out separately under non-load and heavy-load conditions. Data show that machine speed is 5 km/h around and travel efficiency of motorized-wheels is above 95%; that machine braking deceleration is between 0.5 and 0.64 m/s2 but efficiency of motorized-wheels is less than 10%; that maximum machine traction is above 2t while efficiency of motorized-wheels is more than 90% and that adaptive differential steering can be smoothly achieved by motorized-wheels.
Chung, Tien-Kan; Yeh, Po-Chen; Lee, Hao; Lin, Cheng-Mao; Tseng, Chia-Yung; Lo, Wen-Tuan; Wang, Chieh-Min; Wang, Wen-Chin; Tu, Chi-Jen; Tasi, Pei-Yuan; Chang, Jui-Wen
2016-02-23
An attachable electromagnetic-energy-harvester driven wireless vibration-sensing system for monitoring milling-processes and cutter-wear/breakage-conditions is demonstrated. The system includes an electromagnetic energy harvester, three single-axis Micro Electro-Mechanical Systems (MEMS) accelerometers, a wireless chip module, and corresponding circuits. The harvester consisting of magnets with a coil uses electromagnetic induction to harness mechanical energy produced by the rotating spindle in milling processes and consequently convert the harnessed energy to electrical output. The electrical output is rectified by the rectification circuit to power the accelerometers and wireless chip module. The harvester, circuits, accelerometer, and wireless chip are integrated as an energy-harvester driven wireless vibration-sensing system. Therefore, this completes a self-powered wireless vibration sensing system. For system testing, a numerical-controlled machining tool with various milling processes is used. According to the test results, the system is fully self-powered and able to successfully sense vibration in the milling processes. Furthermore, by analyzing the vibration signals (i.e., through analyzing the electrical outputs of the accelerometers), criteria are successfully established for the system for real-time accurate simulations of the milling-processes and cutter-conditions (such as cutter-wear conditions and cutter-breaking occurrence). Due to these results, our approach can be applied to most milling and other machining machines in factories to realize more smart machining technologies.
Chung, Tien-Kan; Yeh, Po-Chen; Lee, Hao; Lin, Cheng-Mao; Tseng, Chia-Yung; Lo, Wen-Tuan; Wang, Chieh-Min; Wang, Wen-Chin; Tu, Chi-Jen; Tasi, Pei-Yuan; Chang, Jui-Wen
2016-01-01
An attachable electromagnetic-energy-harvester driven wireless vibration-sensing system for monitoring milling-processes and cutter-wear/breakage-conditions is demonstrated. The system includes an electromagnetic energy harvester, three single-axis Micro Electro-Mechanical Systems (MEMS) accelerometers, a wireless chip module, and corresponding circuits. The harvester consisting of magnets with a coil uses electromagnetic induction to harness mechanical energy produced by the rotating spindle in milling processes and consequently convert the harnessed energy to electrical output. The electrical output is rectified by the rectification circuit to power the accelerometers and wireless chip module. The harvester, circuits, accelerometer, and wireless chip are integrated as an energy-harvester driven wireless vibration-sensing system. Therefore, this completes a self-powered wireless vibration sensing system. For system testing, a numerical-controlled machining tool with various milling processes is used. According to the test results, the system is fully self-powered and able to successfully sense vibration in the milling processes. Furthermore, by analyzing the vibration signals (i.e., through analyzing the electrical outputs of the accelerometers), criteria are successfully established for the system for real-time accurate simulations of the milling-processes and cutter-conditions (such as cutter-wear conditions and cutter-breaking occurrence). Due to these results, our approach can be applied to most milling and other machining machines in factories to realize more smart machining technologies. PMID:26907297
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lawler, J.S.
2001-10-29
Previous theoretical work has shown that when all loss mechanisms are neglected the constant power speed range (CPSR) of a brushless dc motor (BDCM) is infinite when the motor is driven by the dual-mode inverter control (DMIC) [1,2]. In a physical drive, losses, particularly speed-sensitive losses, will limit the CPSR to a finite value. In this paper we report the results of laboratory testing of a low-inductance, 7.5-hp BDCM driven by the DMIC. The speed rating of the test motor rotor limited the upper speed of the testing, and the results show that the CPSR of the test machine ismore » greater than 6:1 when driven by the DMIC. Current wave shape, peak, and rms values remained controlled and within rating over the entire speed range. The laboratory measurements allowed the speed-sensitive losses to be quantified and incorporated into computer simulation models, which then accurately reproduce the results of lab testing. The simulator shows that the limiting CPSR of the test motor is 8:1. These results confirm that the DMIC is capable of driving low-inductance BDCMs over the wide CPSR that would be required in electric vehicle applications.« less
Evaluation and selection of refrigeration systems for lunar surface and space applications
NASA Technical Reports Server (NTRS)
Copeland, R. J.; Blount, T. D.; Williams, J. L.
1971-01-01
Evaluated are the various refrigeration machines which could be used to provide heat rejection in environmental control systems for lunar surface and spacecraft applications, in order to select the best refrigeration machine for satisfying each individual application and the best refrigeration machine for satisfying all of the applications. The refrigeration machine considered include: (1) vapor comparison cycle (work-driven); (2) vapor adsorption cycle (heat-driven); (3) vapor absorption cycle (heat-driven); (4) thermoelectric (electrically-driven); (5) gas cycle (work driven); (6) steam-jet (heat-driven).
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.
Applications of Machine Learning and Rule Induction,
1995-02-15
An important area of application for machine learning is in automating the acquisition of knowledge bases required for expert systems. In this paper...we review the major paradigms for machine learning , including neural networks, instance-based methods, genetic learning, rule induction, and analytic
Skeist, S. Merrill; Baker, Richard H.
2005-10-11
An electro-mechanical energy conversion system coupled between an energy source and an energy load including an energy converter device having a doubly fed induction machine coupled between the energy source and the energy load to convert the energy from the energy source and to transfer the converted energy to the energy load and an energy transfer multiplexer coupled to the energy converter device to control the flow of power or energy through the doubly fed induction machine.
Equivalence Between Squirrel Cage and Sheet Rotor Induction Motor
NASA Astrophysics Data System (ADS)
Dwivedi, Ankita; Singh, S. K.; Srivastava, R. K.
2016-06-01
Due to topological changes in dual stator induction motor and high cost of its fabrication, it is convenient to replace the squirrel cage rotor with a composite sheet rotor. For an experimental machine, the inner and outer stator stampings are normally available whereas the procurement of rotor stampings is quite cumbersome and is not always cost effective. In this paper, the equivalence between sheet/solid rotor induction motor and squirrel cage induction motor has been investigated using layer theory of electrical machines, so as to enable one to utilize sheet/solid rotor in dual port experimental machines.
Energy Harvesting with a Liquid-Metal Microfluidic Influence Machine
NASA Astrophysics Data System (ADS)
Conner, Christopher; de Visser, Tim; Loessberg, Joshua; Sherman, Sam; Smith, Andrew; Ma, Shuo; Napoli, Maria Teresa; Pennathur, Sumita; Weld, David
2018-04-01
We describe and demonstrate an alternative energy-harvesting technology based on a microfluidic realization of a Wimshurst influence machine. The prototype device converts the mechanical energy of a pressure-driven flow into electrical energy, using a multiphase system composed of droplets of liquid mercury surrounded by insulating oil. Electrostatic induction between adjacent metal droplets drives charge through external electrode paths, resulting in continuous charge amplification and collection. We demonstrate a power output of 4 nW from the initial prototype and present calculations suggesting that straightforward device optimization could increase the power output by more than 3 orders of magnitude. At that level, the power efficiency of this energy-harvesting mechanism, limited by viscous dissipation, could exceed 90%. The microfluidic context enables straightforward scaling and parallelization, as well as hydraulic matching to a variety of ambient mechanical energy sources, such as human locomotion.
Induced electric fields in workers near low-frequency induction heating machines.
Kos, Bor; Valič, Blaž; Kotnik, Tadej; Gajšek, Peter
2014-04-01
Published data on occupational exposure to induction heating equipment are scarce, particularly in terms of induced quantities in the human body. This article provides some additional information by investigating exposure to two such machines-an induction furnace and an induction hardening machine. Additionally, a spatial averaging algorithm for measured fields we developed in a previous publication is tested on new data. The human model was positioned at distances where measured values of magnetic flux density were above the reference levels. All human exposure was below the basic restriction-the lower bound of the 0.1 top percentile induced electric field in the body of a worker was 0.193 V/m at 30 cm from the induction furnace. © 2013 Wiley Periodicals, Inc.
Hybrid-secondary uncluttered induction machine
Hsu, John S.
2001-01-01
An uncluttered secondary induction machine (100) includes an uncluttered rotating transformer (66) which is mounted on the same shaft as the rotor (73) of the induction machine. Current in the rotor (73) is electrically connected to current in the rotor winding (67) of the transformer, which is not electrically connected to, but is magnetically coupled to, a stator secondary winding (40). The stator secondary winding (40) is alternately connected to an effective resistance (41), an AC source inverter (42) or a magnetic switch (43) to provide a cost effective slip-energy-controlled, adjustable speed, induction motor that operates over a wide speed range from below synchronous speed to above synchronous speed based on the AC line frequency fed to the stator.
NASA Astrophysics Data System (ADS)
Laithwaite, E. R.; Kuznetsov, S. B.
1980-09-01
A new technique of continuously generating reactive power from the stator of a brushless induction machine is conceived and tested on a 10-kw linear machine and on 35 and 150 rotary cage motors. An auxiliary magnetic wave traveling at rotor speed is artificially created by the space-transient attributable to the asymmetrical stator winding. At least two distinct windings of different pole-pitch must be incorporated. This rotor wave drifts in and out of phase repeatedly with the stator MMF wave proper and the resulting modulation of the airgap flux is used to generate reactive VA apart from that required for magnetization or leakage flux. The VAR generation effect increases with machine size, and leading power factor operation of the entire machine is viable for large industrial motors and power system induction generators.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Fukami, Tadashi; Imamura, Michinori; Kaburaki, Yuichi
1995-12-31
A new single-phase capacitor self-excited induction generator with self-regulating feature is presented. The new generator consists of a squirrel cage three-phase induction machine and three capacitors connected in series and parallel with a single phase load. The voltage regulation of this generator is very small due to the effect of the three capacitors. Moreover, since a Y-connected stator winding is employed, the waveform of the output voltage becomes sinusoidal. In this paper the system configuration and the operating principle of the new generator are explained, and the basic characteristics are also investigated by means of a simple analysis and experimentsmore » with a laboratory machine.« less
Code of Federal Regulations, 2011 CFR
2011-07-01
... woodworking machines (Order 5). 570.55 Section 570.55 Labor Regulations Relating to Labor (Continued) WAGE AND... woodworking machines (Order 5). (a) Finding and declaration of fact. The following occupations involved in the operation of power-driven wood-working machines are particularly hazardous for minors between 16 and 18...
Method and device for determining bond separation strength using induction heating
NASA Technical Reports Server (NTRS)
Coultrip, Robert H. (Inventor); Johnson, Samuel D. (Inventor); Copeland, Carl E. (Inventor); Phillips, W. Morris (Inventor); Fox, Robert L. (Inventor)
1994-01-01
An induction heating device includes an induction heating gun which includes a housing, a U-shaped pole piece having two spaced apart opposite ends defining a gap there between, the U-shaped pole piece being mounted in one end of the housing, and a tank circuit including an induction coil wrapped around the pole piece and a capacitor connected to the induction coil. A power source is connected to the tank circuit. A pull test machine is provided having a stationary chuck and a movable chuck, the two chucks holding two test pieces bonded together at a bond region. The heating gun is mounted on the pull test machine in close proximity to the bond region of the two test pieces, whereby when the tank circuit is energized, the two test pieces are heated by induction heating while a tension load is applied to the two test pieces by the pull test machine to determine separation strength of the bond region.
Code of Federal Regulations, 2010 CFR
2010-07-01
... woodworking machines (Order 5). 570.55 Section 570.55 Labor Regulations Relating to Labor (Continued) WAGE AND... woodworking machines (Order 5). Link to an amendment published at 75 FR 28455, May 20, 2010. (a) Finding and declaration of fact. The following occupations involved in the operation of power-driven wood-working machines...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jayadev, T.S.
1976-02-01
The application of induction generators in Wind Energy Conversion Systems (WECS) is described. The conventional induction generator, which is an induction machine with a squirrel cage rotor, had been used in large wind power plants in Europe, but has not caught much attention until now by designers of large systems in this country. The induction generator with a squirrel cage rotor is described and useful design techniques to build induction generators for wind energy application are outlined. The Double Output Induction Generator (DOIG) - so called because power is fed into the grid from the stator, as well as themore » rotor is described. It is a wound rotor induction machine with power electronics to convert rotor slip frequency power to that of line frequency.« less
Analysis and design of asymmetrical reluctance machine
NASA Astrophysics Data System (ADS)
Harianto, Cahya A.
Over the past few decades the induction machine has been chosen for many applications due to its structural simplicity and low manufacturing cost. However, modest torque density and control challenges have motivated researchers to find alternative machines. The permanent magnet synchronous machine has been viewed as one of the alternatives because it features higher torque density for a given loss than the induction machine. However, the assembly and permanent magnet material cost, along with safety under fault conditions, have been concerns for this class of machine. An alternative machine type, namely the asymmetrical reluctance machine, is proposed in this work. Since the proposed machine is of the reluctance machine type, it possesses desirable feature, such as near absence of rotor losses, low assembly cost, low no-load rotational losses, modest torque ripple, and rather benign fault conditions. Through theoretical analysis performed herein, it is shown that this machine has a higher torque density for a given loss than typical reluctance machines, although not as high as the permanent magnet machines. Thus, the asymmetrical reluctance machine is a viable and advantageous machine alternative where the use of permanent magnet machines are undesirable.
Wind-energy recovery by a static Scherbius induction generator
NASA Astrophysics Data System (ADS)
Smith, G. A.; Nigim, K. A.
1981-11-01
The paper describes a technique for controlling a doubly fed induction generator driven by a windmill, or other form of variable-speed prime mover, to provide power generation into the national grid system. The secondary circuit of the generator is supplied at a variable frequency from a current source inverter which for test purposes is rated to allow energy recovery, from a simulated windmill, from maximum speed to standstill. To overcome the stability problems normally associated with doubly fed machines a novel signal generator, which is locked in phase with the rotor EMF, controls the secondary power to provide operation over a wide range of subsynchronous and supersynchronous speeds. Consideration of power flow enables the VA rating of the secondary power source to be determined as a function of the gear ratio and online operating range of the system. A simple current source model is used to predict performance which is compared with experimental results. The results indicate a viable system, and suggestions for further work are proposed.
A Double-Sided Linear Primary Permanent Magnet Vernier Machine
2015-01-01
The purpose of this paper is to present a new double-sided linear primary permanent magnet (PM) vernier (DSLPPMV) machine, which can offer high thrust force, low detent force, and improved power factor. Both PMs and windings of the proposed machine are on the short translator, while the long stator is designed as a double-sided simple iron core with salient teeth so that it is very robust to transmit high thrust force. The key of this new machine is the introduction of double stator and the elimination of translator yoke, so that the inductance and the volume of the machine can be reduced. Hence, the proposed machine offers improved power factor and thrust force density. The electromagnetic performances of the proposed machine are analyzed including flux, no-load EMF, thrust force density, and inductance. Based on using the finite element analysis, the characteristics and performances of the proposed machine are assessed. PMID:25874250
A double-sided linear primary permanent magnet vernier machine.
Du, Yi; Zou, Chunhua; Liu, Xianxing
2015-01-01
The purpose of this paper is to present a new double-sided linear primary permanent magnet (PM) vernier (DSLPPMV) machine, which can offer high thrust force, low detent force, and improved power factor. Both PMs and windings of the proposed machine are on the short translator, while the long stator is designed as a double-sided simple iron core with salient teeth so that it is very robust to transmit high thrust force. The key of this new machine is the introduction of double stator and the elimination of translator yoke, so that the inductance and the volume of the machine can be reduced. Hence, the proposed machine offers improved power factor and thrust force density. The electromagnetic performances of the proposed machine are analyzed including flux, no-load EMF, thrust force density, and inductance. Based on using the finite element analysis, the characteristics and performances of the proposed machine are assessed.
NASA Astrophysics Data System (ADS)
Petrovic, Goran; Kilic, Tomislav; Terzic, Bozo
2009-04-01
In this paper a sensorless speed detection method of induction squirrel-cage machines is presented. This method is based on frequency determination of the stator neutral point voltage primary slot harmonic, which is dependent on rotor speed. In order to prove method in steady state and dynamic conditions the simulation and experimental study was carried out. For theoretical investigation the mathematical model of squirrel cage induction machines, which takes into consideration actual geometry and windings layout, is used. Speed-related harmonics that arise from rotor slotting are analyzed using digital signal processing and DFT algorithm with Hanning window. The performance of the method is demonstrated over a wide range of load conditions.
Amey, David L.; Degner, Michael W.
2002-01-01
A method for reducing the starting time and reducing the peak phase currents for an internal combustion engine that is started using an induction machine starter/alternator. The starting time is reduced by pre-fluxing the induction machine and the peak phase currents are reduced by reducing the flux current command after a predetermined period of time has elapsed and concurrent to the application of the torque current command. The method of the present invention also provides a strategy for anticipating the start command for an internal combustion engine and determines a start strategy based on the start command and the operating state of the internal combustion engine.
Skeist, S. Merrill; Baker, Richard H.
2006-01-10
An electro-mechanical energy conversion system coupled between an energy source and an energy load comprising an energy converter device including a permanent magnet induction machine coupled between the energy source and the energy load to convert the energy from the energy source and to transfer the converted energy to the energy load and an energy transfer multiplexer to control the flow of power or energy through the permanent magnetic induction machine.
NASA Astrophysics Data System (ADS)
Rimbawati; Azis Hutasuhut, Abdul; Irsan Pasaribu, Faisal; Cholish; Muharnif
2017-09-01
There is an electric machine that can operate as a generator either single-phase or three-phase in almost every household and industry today. This electric engine cannot be labeled as a generator but can be functioned as a generator. The machine that is mentioned is “squirrel cage motors” or it is well-known as induction motor that can be found in water pumps, washing machines, fans, blowers and other industrial machines. The induction motor can be functioned as a generator when the rotational speed of the rotor is made larger than the speed of the rotary field. In this regard, this study aims to modify the remains of 3-phase induction motor to be a permanent generator. Data of research based conducted on the river flow of Rumah Sumbul Village, STM Hulu district of Deli Serdang. The method of this research is by changing rotor and stator winding on a 3 phase induction motor, so it can produce a generator with rotation speed of 500 rpm. Based on the research, it can be concluded that the output voltage generator has occurred a voltage drop 10% between before and after loading for Star circuit and 2% for Delta circuit.
NASA Technical Reports Server (NTRS)
Kuznetsov, Stephen; Marriott, Darin
2008-01-01
Advances in ultra high speed linear induction electromagnetic launchers over the past decade have focused on magnetic compensation of the exit and entry-edge transient flux wave to produce efficient and compact linear electric machinery. The paper discusses two approaches to edge compensation in long-stator induction catapults with typical end speeds of 150 to 1,500 m/s. In classical linear induction machines, the exit-edge effect is manifest as two auxiliary traveling waves that produce a magnetic drag on the projectile and a loss of magnetic flux over the main surface of the machine. In the new design for the Stator Compensated Induction Machine (SCIM) high velocity launcher, the exit-edge effect is nulled by a dual wavelength machine or alternately the airgap flux is peaked at a location prior to the exit edge. A four (4) stage LIM catapult is presently being constructed for 180 m/s end speed operation using double-sided longitudinal flux machines. Advanced exit and entry edge compensation is being used to maximize system efficiency, and minimize stray heating of the reaction armature. Each stage will output approximately 60 kN of force and produce over 500 G s of acceleration on the armature. The advantage of this design is there is no ablation to the projectile and no sliding contacts, allowing repeated firing of the launcher without maintenance of any sort. The paper shows results of a parametric study for 500 m/s and 1,500 m/s linear induction launchers incorporating two of the latest compensation techniques for an air-core stator primary and an iron-core primary winding. Typical thrust densities for these machines are in the range of 150 kN/sq.m. to 225 kN/sq.m. and these compete favorably with permanent magnet linear synchronous machines. The operational advantages of the high speed SCIM launcher are shown by eliminating the need for pole-angle position sensors as would be required by synchronous systems. The stator power factor is also improved.
NASA Astrophysics Data System (ADS)
Toporkov, D. M.; Vialcev, G. B.
2017-10-01
The implementation of parallel branches is a commonly used manufacturing method of the realizing of fractional slot concentrated windings in electrical machines. If the rotor eccentricity is enabled in a machine with parallel branches, the equalizing currents can arise. The simulation approach of the equalizing currents in parallel branches of an electrical machine winding based on magnetic field calculation by using Finite Elements Method is discussed in the paper. The high accuracy of the model is provided by the dynamic improvement of the inductances in the differential equation system describing a machine. The pre-computed table flux linkage functions are used for that. The functions are the dependences of the flux linkage of parallel branches on the branches currents and rotor position angle. The functions permit to calculate self-inductances and mutual inductances by partial derivative. The calculated results obtained for the electric machine specimen are presented. The results received show that the adverse combination of design solutions and the rotor eccentricity leads to a high value of the equalizing currents and windings heating. Additional torque ripples also arise. The additional ripples harmonic content is not similar to the cogging torque or ripples caused by the rotor eccentricity.
Optimal Control of Induction Machines to Minimize Transient Energy Losses
NASA Astrophysics Data System (ADS)
Plathottam, Siby Jose
Induction machines are electromechanical energy conversion devices comprised of a stator and a rotor. Torque is generated due to the interaction between the rotating magnetic field from the stator, and the current induced in the rotor conductors. Their speed and torque output can be precisely controlled by manipulating the magnitude, frequency, and phase of the three input sinusoidal voltage waveforms. Their ruggedness, low cost, and high efficiency have made them ubiquitous component of nearly every industrial application. Thus, even a small improvement in their energy efficient tend to give a large amount of electrical energy savings over the lifetime of the machine. Hence, increasing energy efficiency (reducing energy losses) in induction machines is a constrained optimization problem that has attracted attention from researchers. The energy conversion efficiency of induction machines depends on both the speed-torque operating point, as well as the input voltage waveform. It also depends on whether the machine is in the transient or steady state. Maximizing energy efficiency during steady state is a Static Optimization problem, that has been extensively studied, with commercial solutions available. On the other hand, improving energy efficiency during transients is a Dynamic Optimization problem that is sparsely studied. This dissertation exclusively focuses on improving energy efficiency during transients. This dissertation treats the transient energy loss minimization problem as an optimal control problem which consists of a dynamic model of the machine, and a cost functional. The rotor field oriented current fed model of the induction machine is selected as the dynamic model. The rotor speed and rotor d-axis flux are the state variables in the dynamic model. The stator currents referred to as d-and q-axis currents are the control inputs. A cost functional is proposed that assigns a cost to both the energy losses in the induction machine, as well as the deviations from desired speed-torque-magnetic flux setpoints. Using Pontryagin's minimum principle, a set of necessary conditions that must be satisfied by the optimal control trajectories are derived. The conditions are in the form a two-point boundary value problem, that can be solved numerically. The conjugate gradient method that was modified using the Hestenes-Stiefel formula was used to obtain the numerical solution of both the control and state trajectories. Using the distinctive shape of the numerical trajectories as inspiration, analytical expressions were derived for the state, and control trajectories. It was shown that the trajectory could be fully described by finding the solution of a one-dimensional optimization problem. The sensitivity of both the optimal trajectory and the optimal energy efficiency to different induction machine parameters were analyzed. A non-iterative solution that can use feedback for generating optimal control trajectories in real time was explored. It was found that an artificial neural network could be trained using the numerical solutions and made to emulate the optimal control trajectories with a high degree of accuracy. Hence a neural network along with a supervisory logic was implemented and used in a real-time simulation to control the Finite Element Method model of the induction machine. The results were compared with three other control regimes and the optimal control system was found to have the highest energy efficiency for the same drive cycle.
The Role of Guided Induction in Paper-Based Data-Driven Learning
ERIC Educational Resources Information Center
Smart, Jonathan
2014-01-01
This study examines the role of guided induction as an instructional approach in paper-based data-driven learning (DDL) in the context of an ESL grammar course during an intensive English program at an American public university. Specifically, it examines whether corpus-informed grammar instruction is more effective through inductive, data-driven…
Application of vibratory-percussion crusher for disintegration of supertough materials
NASA Astrophysics Data System (ADS)
Shishkin, E. V.; Kazakov, S. V.
2017-10-01
This article describes the results of theoretical and experimental studies of a vibratory-percussion crusher, which is driven from a pair of self-synchronizing vibration exciters, attached to the shell symmetrically about its vertical axis. In addition to that, crusher’s dynamic model is symmetrical and balanced. Forced oscillation laws for crusher working members and their amplitude-frequency characteristics have been inducted. Domains of existence of synchronous opposite-phase oscillations of crusher working members (crusher’s operating mode) and crusher capabilities have been identified. The results of mechanical and technological tests of a pilot crusher presented in the article show that this crusher may be viewed as an advanced machine for disintegration of supertough materials with minimum regrinding of finished products.
Jungnickel, Luise; Kruse, Casper; Vaeth, Michael; Kirkevang, Lise-Lotte
2018-04-01
To evaluate factors associated with treatment quality of ex vivo root canal treatments performed by undergraduate dental students using different endodontic treatment systems. Four students performed root canal treatment on 80 extracted human teeth using four endodontic treatment systems in designated treatment order following a Latin square design. Lateral seal and length of root canal fillings was radiographically assessed; for lateral seal, a graded visual scale was used. Treatment time was measured separately for access preparation, biomechanical root canal preparation, obturation and for the total procedure. Mishaps were registered. An ANOVA mirroring the Latin square design was performed. Use of machine-driven nickel-titanium systems resulted in overall better quality scores for lateral seal than use of the manual stainless-steel system. Among systems with machine-driven files, scores did not significantly differ. Use of machine-driven instruments resulted in shorter treatment time than manual instrumentation. Machine-driven systems with few files achieved shorter treatment times. With increasing number of treatments, root canal-filling quality increased, treatment time decreased; a learning curve was plotted. No root canal shaping file separated. The use of endodontic treatment systems with machine-driven files led to higher quality lateral seal compared to the manual system. The three contemporary machine-driven systems delivered comparable results regarding quality of root canal fillings; they were safe to use and provided a more efficient workflow than the manual technique. Increasing experience had a positive impact on the quality of root canal fillings while treatment time decreased.
Yang, Kamie K; Lewis, Ian H
2014-06-15
Various equipment malfunctions of anesthesia gas delivery systems have been previously reported. Our profession increasingly uses technology as a means to prevent these errors. We report a case of a near-total anesthesia circuit obstruction that went undetected before the induction of anesthesia despite the use of automated machine check technology. This case highlights that automated machine check modules can fail to detect severe equipment failure and demonstrates how, even in this era of expanding technology, manual checks still remain essential components of safe care.
NASA Astrophysics Data System (ADS)
Corne, Bram; Vervisch, Bram; Derammelaere, Stijn; Knockaert, Jos; Desmet, Jan
2018-07-01
Stator current analysis has the potential of becoming the most cost-effective condition monitoring technology regarding electric rotating machinery. Since both electrical and mechanical faults are detected by inexpensive and robust current-sensors, measuring current is advantageous on other techniques such as vibration, acoustic or temperature analysis. However, this technology is struggling to breach into the market of condition monitoring as the electrical interpretation of mechanical machine-problems is highly complicated. Recently, the authors built a test-rig which facilitates the emulation of several representative mechanical faults on an 11 kW induction machine with high accuracy and reproducibility. Operating this test-rig, the stator current of the induction machine under test can be analyzed while mechanical faults are emulated. Furthermore, while emulating, the fault-severity can be manipulated adaptively under controllable environmental conditions. This creates the opportunity of examining the relation between the magnitude of the well-known current fault components and the corresponding fault-severity. This paper presents the emulation of evolving bearing faults and their reflection in the Extended Park Vector Approach for the 11 kW induction machine under test. The results confirm the strong relation between the bearing faults and the stator current fault components in both identification and fault-severity. Conclusively, stator current analysis increases reliability in the application as a complete, robust, on-line condition monitoring technology.
Astumian, R. Dean
2015-01-01
A simple model for a chemically driven molecular walker shows that the elastic energy stored by the molecule and released during the conformational change known as the power-stroke (i.e., the free-energy difference between the pre- and post-power-stroke states) is irrelevant for determining the directionality, stopping force, and efficiency of the motor. Further, the apportionment of the dependence on the externally applied force between the forward and reverse rate constants of the power-stroke (or indeed among all rate constants) is irrelevant for determining the directionality, stopping force, and efficiency of the motor. Arguments based on the principle of microscopic reversibility demonstrate that this result is general for all chemically driven molecular machines, and even more broadly that the relative energies of the states of the motor have no role in determining the directionality, stopping force, or optimal efficiency of the machine. Instead, the directionality, stopping force, and optimal efficiency are determined solely by the relative heights of the energy barriers between the states. Molecular recognition—the ability of a molecular machine to discriminate between substrate and product depending on the state of the machine—is far more important for determining the intrinsic directionality and thermodynamics of chemo-mechanical coupling than are the details of the internal mechanical conformational motions of the machine. In contrast to the conclusions for chemical driving, a power-stroke is very important for the directionality and efficiency of light-driven molecular machines and for molecular machines driven by external modulation of thermodynamic parameters. PMID:25606678
Harmonic reduction of Direct Torque Control of six-phase induction motor.
Taheri, A
2016-07-01
In this paper, a new switching method in Direct Torque Control (DTC) of a six-phase induction machine for reduction of current harmonics is introduced. Selecting a suitable vector in each sampling period is an ordinal method in the ST-DTC drive of a six-phase induction machine. The six-phase induction machine has 64 voltage vectors and divided further into four groups. In the proposed DTC method, the suitable voltage vectors are selected from two vector groups. By a suitable selection of two vectors in each sampling period, the harmonic amplitude is decreased more, in and various comparison to that of the ST-DTC drive. The harmonics loss is greater reduced, while the electromechanical energy is decreased with switching loss showing a little increase. Spectrum analysis of the phase current in the standard and new switching table DTC of the six-phase induction machine and determination for the amplitude of each harmonics is proposed in this paper. The proposed method has a less sampling time in comparison to the ordinary method. The Harmonic analyses of the current in the low and high speed shows the performance of the presented method. The simplicity of the proposed method and its implementation without any extra hardware is other advantages of the proposed method. The simulation and experimental results show the preference of the proposed method. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
User-driven sampling strategies in image exploitation
NASA Astrophysics Data System (ADS)
Harvey, Neal; Porter, Reid
2013-12-01
Visual analytics and interactive machine learning both try to leverage the complementary strengths of humans and machines to solve complex data exploitation tasks. These fields overlap most significantly when training is involved: the visualization or machine learning tool improves over time by exploiting observations of the human-computer interaction. This paper focuses on one aspect of the human-computer interaction that we call user-driven sampling strategies. Unlike relevance feedback and active learning sampling strategies, where the computer selects which data to label at each iteration, we investigate situations where the user selects which data is to be labeled at each iteration. User-driven sampling strategies can emerge in many visual analytics applications but they have not been fully developed in machine learning. User-driven sampling strategies suggest new theoretical and practical research questions for both visualization science and machine learning. In this paper we identify and quantify the potential benefits of these strategies in a practical image analysis application. We find user-driven sampling strategies can sometimes provide significant performance gains by steering tools towards local minima that have lower error than tools trained with all of the data. In preliminary experiments we find these performance gains are particularly pronounced when the user is experienced with the tool and application domain.
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.
Contributions a l'etude et a l'application industrielle de la machine asynchrone
NASA Astrophysics Data System (ADS)
Ouhrouche, Mohand-Ameziane
The work presented in this thesis, done in the Electrical Drives Laboratory of Electrical and Computer Engineering Department, deals with the industrial applications of a three-phase induction machine (electrical drives and electricity generation). This thesis, characterized by its multidisciplinary content, has two major parts. The first one deals with the on-line and off-line parametric identification of the induction machine model necessary to achieve accurate vector control strategy. The second part, which is a resume of a research work sponsored by Hydro-Quebec, deals with the application of an induction machine in Asynchronous Non Utility Generators units (ANUG). As it is shown in the following, major scientific contributions are made in both two parts. In the first part of our research work, we propose a new speed sensorless vector control strategy for an induction machine, which is adaptive to the rotor resistance variations. The proposed control strategy is based on the Extended Kalman Filter approach and a decoupling controller which takes into account the rotor resistance variations. The consideration of coupled electrical and mechanical modes leads to a fifth order nonlinear model of the induction machine. The load torque is taken as a function of the rotor angular speed. The Extended Kalman Filter, based on the process's nonlinear (bilinear) model, estimate simultaneously the rotor resistance, angular speed and the flux vector from the startup to the steady state equilibrium point. The machine-converter-control system is implemented in MATLAB/SIMULINK environment and the obtained results confirm the robustness of the proposed scheme. As in the electrical drives erea, the induction machine is now widely used by small to medium power Non Utility Generator units (NUG) to produce electricity. In Quebec, these NUGs units are integrated into the Hydro-Quebec 25 kV distribution system via transformer which exhibit nonlinear characteristics. We have shown by using the ElectroMagnetic Program (EMTP) that, in some islanding scenarios, i.e. that the NUG unit is disconnected from the power grid, in addition to frequency variations, appearence of high an abnormal overvoltages, ferroresonance should occur. As a consequence, normal protective devices could fail to securely operate, which could cause serious damages to the equipment and the maintenance staff. This result, established for the first time , can be useful to improve the reliability of the NUGs units and is considered important by the power engineering community. This has led to a publication in the John Wiley & Sons Encyclopedia of Electrical and Electronics Engineering which will be available in February 1999 ( http://www.engr.wisc.edu/ ece/ece).
Detection of inter-turn short-circuit at start-up of induction machine based on torque analysis
NASA Astrophysics Data System (ADS)
Pietrowski, Wojciech; Górny, Konrad
2017-12-01
Recently, interest in new diagnostics methods in a field of induction machines was observed. Research presented in the paper shows the diagnostics of induction machine based on torque pulsation, under inter-turn short-circuit, during start-up of a machine. In the paper three numerical techniques were used: finite element analysis, signal analysis and artificial neural networks (ANN). The elaborated numerical model of faulty machine consists of field, circuit and motion equations. Voltage excited supply allowed to determine the torque waveform during start-up. The inter-turn short-circuit was treated as a galvanic connection between two points of the stator winding. The waveforms were calculated for different amounts of shorted-turns from 0 to 55. Due to the non-stationary waveforms a wavelet packet decomposition was used to perform an analysis of the torque. The obtained results of analysis were used as input vector for ANN. The response of the neural network was the number of shorted-turns in the stator winding. Special attention was paid to compare response of general regression neural network (GRNN) and multi-layer perceptron neural network (MLP). Based on the results of the research, the efficiency of the developed algorithm can be inferred.
Owen, Whitney H.
1980-01-01
A polyphase rotary induction machine for use as a motor or generator utilizing a single rotor assembly having two series connected sets of rotor windings, a first stator winding disposed around the first rotor winding and means for controlling the current induced in one set of the rotor windings compared to the current induced in the other set of the rotor windings. The rotor windings may be wound rotor windings or squirrel cage windings.
Direct Torque Control of a Three-Phase Voltage Source Inverter-Fed Induction Machine
2013-12-01
factors, FOC acquires all advantages of DC machine control and frees itself from the mechanical commutation drawbacks. Furthermore, FOC leads to high...of three-phase induction motor using microcontroller,” S.R.M Engineering College, Tamil Nadu, India , June/July 2006. [5] Texas Instruments Europe...loop. Direct flux control is possible through the constant magnetic field orientation achieved through commutator action. These two primary factors
Non-equilibrium quantum heat machines
NASA Astrophysics Data System (ADS)
Alicki, Robert; Gelbwaser-Klimovsky, David
2015-11-01
Standard heat machines (engine, heat pump, refrigerator) are composed of a system (working fluid) coupled to at least two equilibrium baths at different temperatures and periodically driven by an external device (piston or rotor) sometimes called the work reservoir. The aim of this paper is to go beyond this scheme by considering environments which are stationary but cannot be decomposed into a few baths at thermal equilibrium. Such situations are important, for example in solar cells, chemical machines in biology, various realizations of laser cooling or nanoscopic machines driven by laser radiation. We classify non-equilibrium baths depending on their thermodynamic behavior and show that the efficiency of heat machines powered by them is limited by the generalized Carnot bound.
Performance testing of a high frequency link converter for Space Station power distribution system
NASA Technical Reports Server (NTRS)
Sul, S. K.; Alan, I.; Lipo, T. A.
1989-01-01
The testing of a brassboard version of a 20-kHz high-frequency ac voltage link prototype converter dynamics for Space Station application is presented. The converter is based on a three-phase six-pulse bridge concept. The testing includes details of the operation of the converter when it is driving an induction machine source/load. By adapting a field orientation controller (FOC) to the converter, four-quadrant operation of the induction machine from the converter has been achieved. Circuit modifications carried out to improve the performance of the converter are described. The performance of two 400-Hz induction machines powered by the converter with simple V/f regulation mode is reported. The testing and performance results for the converter utilizing the FOC, which provides the capability for rapid torque changes, speed reversal, and four-quadrant operation, are reported.
NASA Astrophysics Data System (ADS)
Permiakov, V.; Pulnikov, A.; Dupré, L.; De Wulf, M.; Melkebeek, J.
2003-05-01
In this article, the magnetic properties of nonoriented electrical steel under sinusoidal and distorted excitations are investigated for the whole range of unidirectional mechanical stresses. The distorted flux obtained from the tooth tip of 3 kW induction machine at no-load test was put into the measurement system. The total losses increase for compressive stress both under sinusoidal and distorted excitations. For tensile elastic stresses, the total losses first decrease and then increase in a very similar way for both excitations. In contrast, the difference between total losses under sinusoidal and distorted magnetic fluxes becomes smaller with increase of the plastic strain. This work is a serious step toward complete characterization of the magnetic properties of electrical steel in the teeth area of induction machines. A deeper insight of that problem can improve the design of induction machines and other electromagnetic devices.
Burriel-Valencia, Jordi; Martinez-Roman, Javier; Sapena-Bano, Angel
2018-01-01
The aim of this paper is to introduce a new methodology for the fault diagnosis of induction machines working in the transient regime, when time-frequency analysis tools are used. The proposed method relies on the use of the optimized Slepian window for performing the short time Fourier transform (STFT) of the stator current signal. It is shown that for a given sequence length of finite duration, the Slepian window has the maximum concentration of energy, greater than can be reached with a gated Gaussian window, which is usually used as the analysis window. In this paper, the use and optimization of the Slepian window for fault diagnosis of induction machines is theoretically introduced and experimentally validated through the test of a 3.15-MW induction motor with broken bars during the start-up transient. The theoretical analysis and the experimental results show that the use of the Slepian window can highlight the fault components in the current’s spectrogram with a significant reduction of the required computational resources. PMID:29316650
Burriel-Valencia, Jordi; Puche-Panadero, Ruben; Martinez-Roman, Javier; Sapena-Bano, Angel; Pineda-Sanchez, Manuel
2018-01-06
The aim of this paper is to introduce a new methodology for the fault diagnosis of induction machines working in the transient regime, when time-frequency analysis tools are used. The proposed method relies on the use of the optimized Slepian window for performing the short time Fourier transform (STFT) of the stator current signal. It is shown that for a given sequence length of finite duration, the Slepian window has the maximum concentration of energy, greater than can be reached with a gated Gaussian window, which is usually used as the analysis window. In this paper, the use and optimization of the Slepian window for fault diagnosis of induction machines is theoretically introduced and experimentally validated through the test of a 3.15-MW induction motor with broken bars during the start-up transient. The theoretical analysis and the experimental results show that the use of the Slepian window can highlight the fault components in the current's spectrogram with a significant reduction of the required computational resources.
Chang, Cheng; Yang, Xin; Fahmi, Odette A; Riccardi, Keith A; Di, Li; Obach, R Scott
2017-08-01
1. Induction is an important mechanism contributing to drug-drug interactions. It is most commonly evaluated in the human hepatocyte assay over 48-h or 72-h incubation period. However, whether the overall exposure (i.e. Area Under the Curve (AUC) or C ave ) or maximum exposure (i.e. C max ) of the inducer is responsible for the magnitude of subsequent induction has not been thoroughly investigated. Additionally, in vitro induction assays are typically treated as static systems, which could lead to inaccurate induction potency estimation. Hence, European Medicines Agency (EMA) guidance now specifies quantitation of drug levels in the incubation. 2. This work treated the typical in vitro evaluation of rifampin induction as an in vivo system by generating various target engagement profiles, measuring free rifampin concentration over 3 d of incubation and evaluating the impact of these factors on final induction response. 3. This rifampin-based analysis demonstrates that the induction process is driven by time-averaged target engagement (i.e. AUC-driven). Additionally, depletion of rifampin in the incubation medium over 3 d as well as non-specific/specific binding were observed. 4. These findings should help aid the discovery of clinical candidates with minimal induction liability and further expand our knowledge in the quantitative translatability of in vitro induction assays.
Acoustic sensor for real-time control for the inductive heating process
Kelley, John Bruce; Lu, Wei-Yang; Zutavern, Fred J.
2003-09-30
Disclosed is a system and method for providing closed-loop control of the heating of a workpiece by an induction heating machine, including generating an acoustic wave in the workpiece with a pulsed laser; optically measuring displacements of the surface of the workpiece in response to the acoustic wave; calculating a sub-surface material property by analyzing the measured surface displacements; creating an error signal by comparing an attribute of the calculated sub-surface material properties with a desired attribute; and reducing the error signal below an acceptable limit by adjusting, in real-time, as often as necessary, the operation of the inductive heating machine.
NASA Astrophysics Data System (ADS)
Yang, Xiaojun; Lu, Dun; Liu, Hui; Zhao, Wanhua
2018-06-01
The complicated electromechanical coupling phenomena due to different kinds of causes have significant influences on the dynamic precision of the direct driven feed system in machine tools. In this paper, a novel integrated modeling and analysis method of the multiple electromechanical couplings for the direct driven feed system in machine tools is presented. At first, four different kinds of electromechanical coupling phenomena in the direct driven feed system are analyzed systematically. Then a novel integrated modeling and analysis method of the electromechanical coupling which is influenced by multiple factors is put forward. In addition, the effects of multiple electromechanical couplings on the dynamic precision of the feed system and their main influencing factors are compared and discussed, respectively. Finally, the results of modeling and analysis are verified by the experiments. It finds out that multiple electromechanical coupling loops, which are overlapped and influenced by each other, are the main reasons of the displacement fluctuations in the direct driven feed system.
On the Stability of Jump-Linear Systems Driven by Finite-State Machines with Markovian Inputs
NASA Technical Reports Server (NTRS)
Patilkulkarni, Sudarshan; Herencia-Zapana, Heber; Gray, W. Steven; Gonzalez, Oscar R.
2004-01-01
This paper presents two mean-square stability tests for a jump-linear system driven by a finite-state machine with a first-order Markovian input process. The first test is based on conventional Markov jump-linear theory and avoids the use of any higher-order statistics. The second test is developed directly using the higher-order statistics of the machine s output process. The two approaches are illustrated with a simple model for a recoverable computer control system.
User-Driven Sampling Strategies in Image Exploitation
Harvey, Neal R.; Porter, Reid B.
2013-12-23
Visual analytics and interactive machine learning both try to leverage the complementary strengths of humans and machines to solve complex data exploitation tasks. These fields overlap most significantly when training is involved: the visualization or machine learning tool improves over time by exploiting observations of the human-computer interaction. This paper focuses on one aspect of the human-computer interaction that we call user-driven sampling strategies. Unlike relevance feedback and active learning sampling strategies, where the computer selects which data to label at each iteration, we investigate situations where the user selects which data is to be labeled at each iteration. User-drivenmore » sampling strategies can emerge in many visual analytics applications but they have not been fully developed in machine learning. We discovered that in user-driven sampling strategies suggest new theoretical and practical research questions for both visualization science and machine learning. In this paper we identify and quantify the potential benefits of these strategies in a practical image analysis application. We find user-driven sampling strategies can sometimes provide significant performance gains by steering tools towards local minima that have lower error than tools trained with all of the data. Furthermore, in preliminary experiments we find these performance gains are particularly pronounced when the user is experienced with the tool and application domain.« less
Elbouchikhi, Elhoussin; Choqueuse, Vincent; Benbouzid, Mohamed
2016-07-01
Condition monitoring of electric drives is of paramount importance since it contributes to enhance the system reliability and availability. Moreover, the knowledge about the fault mode behavior is extremely important in order to improve system protection and fault-tolerant control. Fault detection and diagnosis in squirrel cage induction machines based on motor current signature analysis (MCSA) has been widely investigated. Several high resolution spectral estimation techniques have been developed and used to detect induction machine abnormal operating conditions. This paper focuses on the application of MCSA for the detection of abnormal mechanical conditions that may lead to induction machines failure. In fact, this paper is devoted to the detection of single-point defects in bearings based on parametric spectral estimation. A multi-dimensional MUSIC (MD MUSIC) algorithm has been developed for bearing faults detection based on bearing faults characteristic frequencies. This method has been used to estimate the fundamental frequency and the fault related frequency. Then, an amplitude estimator of the fault characteristic frequencies has been proposed and fault indicator has been derived for fault severity measurement. The proposed bearing faults detection approach is assessed using simulated stator currents data, issued from a coupled electromagnetic circuits approach for air-gap eccentricity emulating bearing faults. Then, experimental data are used for validation purposes. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
The Physics and Physical Chemistry of Molecular Machines.
Astumian, R Dean; Mukherjee, Shayantani; Warshel, Arieh
2016-06-17
The concept of a "power stroke"-a free-energy releasing conformational change-appears in almost every textbook that deals with the molecular details of muscle, the flagellar rotor, and many other biomolecular machines. Here, it is shown by using the constraints of microscopic reversibility that the power stroke model is incorrect as an explanation of how chemical energy is used by a molecular machine to do mechanical work. Instead, chemically driven molecular machines operating under thermodynamic constraints imposed by the reactant and product concentrations in the bulk function as information ratchets in which the directionality and stopping torque or stopping force are controlled entirely by the gating of the chemical reaction that provides the fuel for the machine. The gating of the chemical free energy occurs through chemical state dependent conformational changes of the molecular machine that, in turn, are capable of generating directional mechanical motions. In strong contrast to this general conclusion for molecular machines driven by catalysis of a chemical reaction, a power stroke may be (and often is) an essential component for a molecular machine driven by external modulation of pH or redox potential or by light. This difference between optical and chemical driving properties arises from the fundamental symmetry difference between the physics of optical processes, governed by the Bose-Einstein relations, and the constraints of microscopic reversibility for thermally activated processes. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Machine finishes balls to high degree of roundness
NASA Technical Reports Server (NTRS)
Angele, W.; Hill, J. P., Jr.
1972-01-01
Machine was developed to finish ball to roundness within 12.5 nm (half a microinch) from any types of hard material. Grinding and polishing to this tolerance is accomplished by lapping elements on four to six motor-driven spindles. Spindles are adjustably spring-loaded to ensure constant contact pressure on ball and are driven by variable speed electric motors.
NASA Technical Reports Server (NTRS)
Bose, Bimal K.; Kim, Min-Huei
1995-01-01
The report essentially summarizes the work performed in order to satisfy the above project objective. In the beginning, different energy storage devices, such as battery, flywheel and ultra capacitor are reviewed and compared, establishing the superiority of the battery. Then, the possible power sources, such as IC engine, diesel engine, gas turbine and fuel cell are reviewed and compared, and the superiority of IC engine has been established. Different types of machines for drive motor/engine generator, such as induction machine, PM synchronous machine and switched reluctance machine are compared, and the induction machine is established as the superior candidate. Similar discussion was made for power converters and devices. The Insulated Gate Bipolar Transistor (IGBT) appears to be the most superior device although Mercury Cadmium Telluride (MCT) shows future promise. Different types of candidate distribution systems with the possible combinations of power and energy sources have been discussed and the most viable system consisting of battery, IC engine and induction machine has been identified. Then, HFAC system has been compared with the DC system establishing the superiority of the former. The detailed component sizing calculations of HFAC and DC systems reinforce the superiority of the former. A preliminary control strategy has been developed for the candidate HFAC system. Finally, modeling and simulation study have been made to validate the system performance. The study in the report demonstrates the superiority of HFAC distribution system for next generation electric/hybrid vehicle.
Providing QoS through machine-learning-driven adaptive multimedia applications.
Ruiz, Pedro M; Botía, Juan A; Gómez-Skarmeta, Antonio
2004-06-01
We investigate the optimization of the quality of service (QoS) offered by real-time multimedia adaptive applications through machine learning algorithms. These applications are able to adapt in real time their internal settings (i.e., video sizes, audio and video codecs, among others) to the unpredictably changing capacity of the network. Traditional adaptive applications just select a set of settings to consume less than the available bandwidth. We propose a novel approach in which the selected set of settings is the one which offers a better user-perceived QoS among all those combinations which satisfy the bandwidth restrictions. We use a genetic algorithm to decide when to trigger the adaptation process depending on the network conditions (i.e., loss-rate, jitter, etc.). Additionally, the selection of the new set of settings is done according to a set of rules which model the user-perceived QoS. These rules are learned using the SLIPPER rule induction algorithm over a set of examples extracted from scores provided by real users. We will demonstrate that the proposed approach guarantees a good user-perceived QoS even when the network conditions are constantly changing.
A defect-driven diagnostic method for machine tool spindles
Vogl, Gregory W.; Donmez, M. Alkan
2016-01-01
Simple vibration-based metrics are, in many cases, insufficient to diagnose machine tool spindle condition. These metrics couple defect-based motion with spindle dynamics; diagnostics should be defect-driven. A new method and spindle condition estimation device (SCED) were developed to acquire data and to separate system dynamics from defect geometry. Based on this method, a spindle condition metric relying only on defect geometry is proposed. Application of the SCED on various milling and turning spindles shows that the new approach is robust for diagnosing the machine tool spindle condition. PMID:28065985
Construction and Initial Tests of MAIZE: 1 MA LTD-Driven Z-Pinch *
NASA Astrophysics Data System (ADS)
Gilgenbach, R. M.; Gomez, M. R.; Zier, J. C.; Tang, W.; French, D. M.; Lau, Y. Y.; Mazarakis, M. G.; Cuneo, M. E.; Johnston, M. D.; Oliver, B. V.; Mehlhorn, T. A.; Kim, A. A.; Sinebryukhov, V. A.
2008-11-01
We report construction and initial testing of a 1-MA Linear Transformer Driver (LTD), The Michigan Accelerator for Inductive Z-pinch Experiments, (MAIZE). This machine, the first of its type to reach the USA, is based on the joint HCEI, Sandia Laboratories, and UM development effort. The compact LTD uses 80 capacitors and 40 spark gap switches, in 40 ``bricks'', to deliver 1 MA, 100 kV pulses with 70 ns risetime into a matched resistive load. Test results will be presented for a single brick and the full LTD. Design and construction will be presented of a low-inductance MITL. Experimental research programs under design and construction at UM include: a) Studies of Magneto-Raleigh-Taylor Instability of planar foils, and b) Vacuum convolute studies including cathode and anode plasma. Theory and simulation results will be presented for these planned experiments. Initial experimental designs and moderate-current feasibility experiments will be discussed. *Research supported by U. S. DoE through Sandia National Laboratories award document numbers 240985, 768225, 790791 and 805234 to the UM. MRG supported by NNSA Fellowship and JCZ supported by NPSC Fellowship / Sandia National Labs.
Torque shudder protection device and method
King, Robert D.; De Doncker, Rik W. A. A.; Szczesny, Paul M.
1997-01-01
A torque shudder protection device for an induction machine includes a flux command generator for supplying a steady state flux command and a torque shudder detector for supplying a status including a negative status to indicate a lack of torque shudder and a positive status to indicate a presence of torque shudder. A flux adapter uses the steady state flux command and the status to supply a present flux command identical to the steady state flux command for a negative status and different from the steady state flux command for a positive status. A limiter can receive the present flux command, prevent the present flux command from exceeding a predetermined maximum flux command magnitude, and supply the present flux command to a field oriented controller. After determining a critical electrical excitation frequency at which a torque shudder occurs for the induction machine, a flux adjuster can monitor the electrical excitation frequency of the induction machine and adjust a flux command to prevent the monitored electrical excitation frequency from reaching the critical electrical excitation frequency.
Torque shudder protection device and method
King, R.D.; Doncker, R.W.A.A. De.; Szczesny, P.M.
1997-03-11
A torque shudder protection device for an induction machine includes a flux command generator for supplying a steady state flux command and a torque shudder detector for supplying a status including a negative status to indicate a lack of torque shudder and a positive status to indicate a presence of torque shudder. A flux adapter uses the steady state flux command and the status to supply a present flux command identical to the steady state flux command for a negative status and different from the steady state flux command for a positive status. A limiter can receive the present flux command, prevent the present flux command from exceeding a predetermined maximum flux command magnitude, and supply the present flux command to a field oriented controller. After determining a critical electrical excitation frequency at which a torque shudder occurs for the induction machine, a flux adjuster can monitor the electrical excitation frequency of the induction machine and adjust a flux command to prevent the monitored electrical excitation frequency from reaching the critical electrical excitation frequency. 5 figs.
Proceedings of the Workshop on Change of Representation and Problem Reformulation
NASA Technical Reports Server (NTRS)
Lowry, Michael R.
1992-01-01
The proceedings of the third Workshop on Change of representation and Problem Reformulation is presented. In contrast to the first two workshops, this workshop was focused on analytic or knowledge-based approaches, as opposed to statistical or empirical approaches called 'constructive induction'. The organizing committee believes that there is a potential for combining analytic and inductive approaches at a future date. However, it became apparent at the previous two workshops that the communities pursuing these different approaches are currently interested in largely non-overlapping issues. The constructive induction community has been holding its own workshops, principally in conjunction with the machine learning conference. While this workshop is more focused on analytic approaches, the organizing committee has made an effort to include more application domains. We have greatly expanded from the origins in the machine learning community. Participants in this workshop come from the full spectrum of AI application domains including planning, qualitative physics, software engineering, knowledge representation, and machine learning.
Pole-phase modulated toroidal winding for an induction machine
Miller, John Michael; Ostovic, Vlado
1999-11-02
A stator (10) for an induction machine for a vehicle has a cylindrical core (12) with inner and outer slots (26, 28) extending longitudinally along the inner and outer peripheries between the end faces (22, 24). Each outer slot is associated with several adjacent inner slots. A plurality of toroidal coils (14) are wound about the core and laid in the inner and outer slots. Each coil occupies a single inner slot and is laid in the associated outer slot thereby minimizing the distance the coil extends from the end faces and minimizing the length of the induction machine. The toroidal coils are configured for an arbitrary pole phase modulation wherein the coils are configured with variable numbers of phases and poles for providing maximum torque for cranking and switchable to a another phase and pole configuration for alternator operation. An adaptor ring (36) circumferentially positioned about the stator improves mechanical strength, and provides a coolant channel manifold (34) for removing heat produced in stator windings during operation.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chikkagoudar, Satish; Chatterjee, Samrat; Thomas, Dennis G.
The absence of a robust and unified theory of cyber dynamics presents challenges and opportunities for using machine learning based data-driven approaches to further the understanding of the behavior of such complex systems. Analysts can also use machine learning approaches to gain operational insights. In order to be operationally beneficial, cybersecurity machine learning based models need to have the ability to: (1) represent a real-world system, (2) infer system properties, and (3) learn and adapt based on expert knowledge and observations. Probabilistic models and Probabilistic graphical models provide these necessary properties and are further explored in this chapter. Bayesian Networksmore » and Hidden Markov Models are introduced as an example of a widely used data driven classification/modeling strategy.« less
Data-Driven Learning of Speech Acts Based on Corpora of DVD Subtitles
ERIC Educational Resources Information Center
Kitao, S. Kathleen; Kitao, Kenji
2013-01-01
Data-driven learning (DDL) is an inductive approach to language learning in which students study examples of authentic language and use them to find patterns of language use. This inductive approach to learning has the advantages of being learner-centered, encouraging hypothesis testing and learner autonomy, and helping develop learning skills.…
Beam-return current systems in solar flares
NASA Technical Reports Server (NTRS)
Spicer, D. S.; Sudan, R. N.
1984-01-01
It is demonstrated that the common assumption made in solar flare beam transport theory that the beam-accompanied return current is purely electrostatically driven is incorrect, and that the return current is both electrostatically and inductively driven, in accordance with Lenz's law, with the inductive effects dominating for times greater than a few plasma periods. In addition, it is shown that a beam can only exist in a solar plasma for a finite time which is much smaller than the inductive return current dissipation time. The importance of accounting for the role of the acceleration mechanism in forming the beam is discussed. In addition, the role of return current driven anomalous resistivity and its subsequent anomalous Joule heating during the flare process is elucidated.
Intrusion Detection Systems with Live Knowledge System
2016-05-31
Ripple -down Rule (RDR) to maintain the knowledge from human experts with knowledge base generated by the Induct RDR, which is a machine-learning based RDR...propose novel approach that uses Ripple -down Rule (RDR) to maintain the knowledge from human experts with knowledge base generated by the Induct RDR...detection model by applying Induct RDR approach. The proposed induct RDR ( Ripple Down Rules) approach allows to acquire the phishing detection
Code of Federal Regulations, 2011 CFR
2011-07-01
... machines. (3) All occupations involved in tankage or rendering of dead animals, animal offal, animal fats..., and hashing machines; and presses (except belly-rolling machines). Except, the provisions of this.... Rendering plants means establishments engaged in the conversion of dead animals, animal offal, animal fats...
Towards a generalized energy prediction model for machine tools
Bhinge, Raunak; Park, Jinkyoo; Law, Kincho H.; Dornfeld, David A.; Helu, Moneer; Rachuri, Sudarsan
2017-01-01
Energy prediction of machine tools can deliver many advantages to a manufacturing enterprise, ranging from energy-efficient process planning to machine tool monitoring. Physics-based, energy prediction models have been proposed in the past to understand the energy usage pattern of a machine tool. However, uncertainties in both the machine and the operating environment make it difficult to predict the energy consumption of the target machine reliably. Taking advantage of the opportunity to collect extensive, contextual, energy-consumption data, we discuss a data-driven approach to develop an energy prediction model of a machine tool in this paper. First, we present a methodology that can efficiently and effectively collect and process data extracted from a machine tool and its sensors. We then present a data-driven model that can be used to predict the energy consumption of the machine tool for machining a generic part. Specifically, we use Gaussian Process (GP) Regression, a non-parametric machine-learning technique, to develop the prediction model. The energy prediction model is then generalized over multiple process parameters and operations. Finally, we apply this generalized model with a method to assess uncertainty intervals to predict the energy consumed to machine any part using a Mori Seiki NVD1500 machine tool. Furthermore, the same model can be used during process planning to optimize the energy-efficiency of a machining process. PMID:28652687
Towards a generalized energy prediction model for machine tools.
Bhinge, Raunak; Park, Jinkyoo; Law, Kincho H; Dornfeld, David A; Helu, Moneer; Rachuri, Sudarsan
2017-04-01
Energy prediction of machine tools can deliver many advantages to a manufacturing enterprise, ranging from energy-efficient process planning to machine tool monitoring. Physics-based, energy prediction models have been proposed in the past to understand the energy usage pattern of a machine tool. However, uncertainties in both the machine and the operating environment make it difficult to predict the energy consumption of the target machine reliably. Taking advantage of the opportunity to collect extensive, contextual, energy-consumption data, we discuss a data-driven approach to develop an energy prediction model of a machine tool in this paper. First, we present a methodology that can efficiently and effectively collect and process data extracted from a machine tool and its sensors. We then present a data-driven model that can be used to predict the energy consumption of the machine tool for machining a generic part. Specifically, we use Gaussian Process (GP) Regression, a non-parametric machine-learning technique, to develop the prediction model. The energy prediction model is then generalized over multiple process parameters and operations. Finally, we apply this generalized model with a method to assess uncertainty intervals to predict the energy consumed to machine any part using a Mori Seiki NVD1500 machine tool. Furthermore, the same model can be used during process planning to optimize the energy-efficiency of a machining process.
Numerical analysis method for linear induction machines.
NASA Technical Reports Server (NTRS)
Elliott, D. G.
1972-01-01
A numerical analysis method has been developed for linear induction machines such as liquid metal MHD pumps and generators and linear motors. Arbitrary phase currents or voltages can be specified and the moving conductor can have arbitrary velocity and conductivity variations from point to point. The moving conductor is divided into a mesh and coefficients are calculated for the voltage induced at each mesh point by unit current at every other mesh point. Combining the coefficients with the mesh resistances yields a set of simultaneous equations which are solved for the unknown currents.
29 CFR 570.34 - Occupations that may be performed by minors 14 and 15 years of age.
Code of Federal Regulations, 2011 CFR
2011-07-01
... comparative shopping. (e) Price marking and tagging by hand or machine, assembling orders, packing, and... machines shall mean all fixed or portable machines or tools driven by power and used or designed for...
29 CFR 570.34 - Occupations that may be performed by minors 14 and 15 years of age.
Code of Federal Regulations, 2012 CFR
2012-07-01
... comparative shopping. (e) Price marking and tagging by hand or machine, assembling orders, packing, and... machines shall mean all fixed or portable machines or tools driven by power and used or designed for...
29 CFR 570.34 - Occupations that may be performed by minors 14 and 15 years of age.
Code of Federal Regulations, 2013 CFR
2013-07-01
... comparative shopping. (e) Price marking and tagging by hand or machine, assembling orders, packing, and... machines shall mean all fixed or portable machines or tools driven by power and used or designed for...
29 CFR 570.34 - Occupations that may be performed by minors 14 and 15 years of age.
Code of Federal Regulations, 2014 CFR
2014-07-01
... comparative shopping. (e) Price marking and tagging by hand or machine, assembling orders, packing, and... machines shall mean all fixed or portable machines or tools driven by power and used or designed for...
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
Overview of the Helicity Injected Torus (HIT) Program
NASA Astrophysics Data System (ADS)
Redd, A. J.; Jarboe, T. R.; Hamp, W. T.; Nelson, B. A.; O'Neill, R. G.; Sieck, P. E.; Smith, R. J.; Sutphin, G. L.; Wrobel, J. S.
2007-06-01
The Helicity Injected Torus with Steady Inductive Helicity Injection (HIT-SI) consists of a "bowtie"-shaped axisymmetric confinement region, with two half-torus helicity injectors mounted on each side of the axisymmetric flux conserver [Sieck et al, IEEE Trans. Plasma Sci., v.33, p.723 (2005); Jarboe, Fusion Technology, v.36, p.85 (1999)]. Current and flux are driven sinusoidally with time in each injector, with the goal of generating and sustaining an axisymmetric spheromak in the main confinement region. Improvements in machine conditioning have enabled systematic study of HIT-SI discharges with significant toroidal current ITOR, including cases in which this current ITOR switches sign one or more times during the discharge. Statistical studies of all HIT-SI discharges to date demonstrate a minimum injected power to form significant ITOR, and that the maximum ITOR scales approximately linearly with the total injected power.
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.
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.
Yamaura, Hiroshi; Matsushita, Kojiro; Kato, Ryu; Yokoi, Hiroshi
2009-01-01
We have developed a hand rehabilitation system for patients suffering from paralysis or contracture. It consists of two components: a hand rehabilitation machine, which moves human finger joints with motors, and a data glove, which provides control of the movement of finger joints attached to the rehabilitation machine. The machine is based on the arm structure type of hand rehabilitation machine; a motor indirectly moves a finger joint via a closed four-link mechanism. We employ a wire-driven mechanism and develop a compact design that can control all three joints (i.e., PIP, DIP and MP ) of a finger and that offers a wider range of joint motion than conventional systems. Furthermore, we demonstrate the hand rehabilitation process, finger joints of the left hand attached to the machine are controlled by the finger joints of the right hand wearing the data glove.
[Cyclic fatigue of Vita mark II machinable ceramics under Hertzian's contact].
Liu, Wei-Cai; Zhang, Zhi-Shen; Huang, Cheng-Min; Chao, Yong-Lie; Wan, Qian-Bing
2006-08-01
To investigate the cyclic fatigue modes of Vita mark II machinable ceramics under Hertzian's contact. Hertzian's contact technique (WC spheres r = 3.18 mm) was used to investigate the cyclic fatigue of Vita mark II machinable ceramic. All specimens were fatigued by cyclic loading in moist environment, furthermore, surviving strength was examined by three point test and morphology damage observation. In homogeneous Vita mark II machinable ceramics, two fatigue damage modes existed after cyclic loading with spheres under moist environment, including conventional tensile-driven cone cracking (brittle mode) and shear-driven microdamage accumulation (quasi-plastic mode). The latter generated radial cracks and deeply penetrating secondary cone crack. Initial strength degradation were caused by the cone cracks, subsequent and much more deleterious loss was caused by radial cracks. Cyclic fatigue modes of Vita mark II machinable ceramics includes brittle and quasi-plastic mode.
Study on magnetic force of electromagnetic levitation circular knitting machine
NASA Astrophysics Data System (ADS)
Wu, X. G.; Zhang, C.; Xu, X. S.; Zhang, J. G.; Yan, N.; Zhang, G. Z.
2018-06-01
The structure of the driving coil and the electromagnetic force of the test prototype of electromagnetic-levitation (EL) circular knitting machine are studied. In this paper, the driving coil’s structure and working principle of the EL circular knitting machine are firstly introduced, then the mathematical modelling analysis of the driving electromagnetic force is carried out, and through the Ansoft Maxwell finite element simulation software the coil’s magnetic induction intensity and the needle’s electromagnetic force is simulated, finally an experimental platform is built to measure the coil’s magnetic induction intensity and the needle’s electromagnetic force. The results show that the theoretical analysis, the simulation analysis and the results of the test are very close, which proves the correctness of the proposed model.
NASA Technical Reports Server (NTRS)
Hansen, Irving G.
1990-01-01
Electromechanical actuators developed to date have commonly utilized permanent magnet (PM) synchronous motors. More recently switched reluctance (SR) motors have been advocated due to their robust characteristics. Implications of work which utilizes induction motors and advanced control techniques are discussed. When induction motors are operated from an energy source capable of controlling voltages and frequencies independently, drive characteristics are obtained which are superior to either PM or SR motors. By synthesizing the machine frequency from a high frequency carrier (nominally 20 kHz), high efficiencies, low distortion, and rapid torque response are available. At this time multiple horsepower machine drives were demonstrated, and work is on-going to develop a 20 hp average, 40 hp peak class of aerospace actuators. This effort is based upon high frequency power distribution and management techniques developed by NASA for Space Station Freedom.
NASA Technical Reports Server (NTRS)
Hansen, Irving G.
1990-01-01
Electromechanical actuators developed to date have commonly ultilized permanent magnet (PM) synchronous motors. More recently switched reluctance (SR) motors have been advocated due to their robust characteristics. Implications of work which utilized induction motors and advanced control techniques are discussed. When induction motors are operated from an energy source capable of controlling voltages and frequencies independently, drive characteristics are obtained which are superior to either PM or SR motors. By synthesizing the machine frequency from a high-frequency carrier (nominally 20 kHz), high efficiencies, low distortion, and rapid torque response are available. At this time multiple horsepower machine drives were demonstrated, and work is on-going to develop a 20 hp average, 40 hp peak class of aerospace actuators. This effort is based upon high-frequency power distribution and management techniques developed by NASA for Space Station Freedom.
Four quadrant control of induction motors
NASA Technical Reports Server (NTRS)
Hansen, Irving G.
1991-01-01
Induction motors are the nation's workhorse, being the motor of choice in most applications due to their simple rugged construction. It has been estimated that 14 to 27 percent of the country's total electricity use could be saved with adjustable speed drives. Until now, induction motors have not been suited well for variable speed or servo-drives, due to the inherent complexity, size, and inefficiency of their variable speed controls. Work at NASA Lewis Research Center on field oriented control of induction motors using pulse population modulation method holds the promise for the desired drive electronics. The system allows for a variable voltage to frequency ratio which enables the user to operate the motor at maximum efficiency, while having independent control of both the speed and torque of an induction motor in all four quadrants of the speed torque map. Multiple horsepower machine drives were demonstrated, and work is on-going to develop a 20 hp average, 40 hp peak class of machine. The pulse population technique, results to date, and projections for implementation of this existing new motor control technology are discussed.
30 CFR 18.96 - Preparation of machines for inspection; requirements.
Code of Federal Regulations, 2010 CFR
2010-07-01
... TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Field Approval of Electrically Operated Mining Equipment § 18.96 Preparation of machines for inspection... place at which a field approval investigation will be conducted with respect to any machine, the...
30 CFR 18.96 - Preparation of machines for inspection; requirements.
Code of Federal Regulations, 2011 CFR
2011-07-01
... TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Field Approval of Electrically Operated Mining Equipment § 18.96 Preparation of machines for inspection... place at which a field approval investigation will be conducted with respect to any machine, the...
DIRECT SIMULATION OF A-C MACHINERY.
show the application of the simulation to both induction and synchronous machines. The fundamental space harmonic only, the fundamental and third ... space harmonic only, or all the space harmonics are considered. The report concludes that: (1) Successful direct simulation of the 2-phase induction
NASA Astrophysics Data System (ADS)
Nelson, Kevin; Corbin, George; Blowers, Misty
2014-05-01
Machine learning is continuing to gain popularity due to its ability to solve problems that are difficult to model using conventional computer programming logic. Much of the current and past work has focused on algorithm development, data processing, and optimization. Lately, a subset of research has emerged which explores issues related to security. This research is gaining traction as systems employing these methods are being applied to both secure and adversarial environments. One of machine learning's biggest benefits, its data-driven versus logic-driven approach, is also a weakness if the data on which the models rely are corrupted. Adversaries could maliciously influence systems which address drift and data distribution changes using re-training and online learning. Our work is focused on exploring the resilience of various machine learning algorithms to these data-driven attacks. In this paper, we present our initial findings using Monte Carlo simulations, and statistical analysis, to explore the maximal achievable shift to a classification model, as well as the required amount of control over the data.
NASA Technical Reports Server (NTRS)
Hamilton, H. B.; Strangas, E.
1980-01-01
The time dependent solution of the magnetic field is introduced as a method for accounting for the variation, in time, of the machine parameters in predicting and analyzing the performance of the electrical machines. The method of time dependent finite element was used in combination with an also time dependent construction of a grid for the air gap region. The Maxwell stress tensor was used to calculate the airgap torque from the magnetic vector potential distribution. Incremental inductances were defined and calculated as functions of time, depending on eddy currents and saturation. The currents in all the machine circuits were calculated in the time domain based on these inductances, which were continuously updated. The method was applied to a chopper controlled DC series motor used for electric vehicle drive, and to a salient pole sychronous motor with damper bars. Simulation results were compared to experimentally obtained ones.
Pinch current limitation effect in plasma focus
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lee, S.; Saw, S. H.; INTI International University College, 71800 Nilai
The Lee model couples the electrical circuit with plasma focus dynamics, thermodynamics, and radiation. It is used to design and simulate experiments. A beam-target mechanism is incorporated, resulting in realistic neutron yield scaling with pinch current and increasing its versatility for investigating all Mather-type machines. Recent runs indicate a previously unsuspected 'pinch current limitation' effect. The pinch current does not increase beyond a certain value however low the static inductance is reduced to. The results indicate that decreasing the present static inductance of the PF1000 machine will neither increase the pinch current nor the neutron yield, contrary to expectations.
research focuses on optimization and machine learning applied to complex energy systems and turbulent flows techniques to improve wind plant design and controls and developed a new data-driven machine learning closure
Asynchronous machine rotor speed estimation using a tabulated numerical approach
NASA Astrophysics Data System (ADS)
Nguyen, Huu Phuc; De Miras, Jérôme; Charara, Ali; Eltabach, Mario; Bonnet, Stéphane
2017-12-01
This paper proposes a new method to estimate the rotor speed of the asynchronous machine by looking at the estimation problem as a nonlinear optimal control problem. The behavior of the nonlinear plant model is approximated off-line as a prediction map using a numerical one-step time discretization obtained from simulations. At each time-step, the speed of the induction machine is selected satisfying the dynamic fitting problem between the plant output and the predicted output, leading the system to adopt its dynamical behavior. Thanks to the limitation of the prediction horizon to a single time-step, the execution time of the algorithm can be completely bounded. It can thus easily be implemented and embedded into a real-time system to observe the speed of the real induction motor. Simulation results show the performance and robustness of the proposed estimator.
Naderi, Peyman
2016-09-01
The inter-turn short fault for the Cage-Rotor-Induction-Machine (CRIM) is studied in this paper and its local saturation is taken into account. However, in order to observe the exact behavior of machine, the Magnetic-Equivalent-Circuit (MEC) and nonlinear B-H curve are proposed to provide an insight into the machine model and saturation effect respectively. The electrical machines are generally operated near to their saturation zone due to some design necessities. Hence, when the machine is exposed to a fault such as short circuit or eccentricities, it is operated within its saturation zone and thus, time and space harmonics are integrated and as a result, current and torque harmonics are generated which the phenomenon cannot be explored when saturation is dismissed. Nonetheless, inter-turn short circuit may lead to local saturation and this occurrence is studied in this paper using MEC model. In order to achieve the mentioned objectives, two and also four-pole machines are modeled as two samples and the machines performances are analyzed in healthy and faulty cases with and without saturation effect. A novel strategy is proposed to precisely detect inter-turn short circuit fault according to the stator׳s lines current signatures and the accuracy of the proposed method is verified by experimental results. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Li, Hao; Liu, Jianshe; Zhang, Yingshan; Cai, Han; Li, Gang; Liu, Qichun; Han, Siyuan; Chen, Wei
2017-03-01
A negative-inductance superconducting quantum interference device (nSQUID) is an adiabatic superconducting logic device with high energy efficiency, and therefore a promising building block for large-scale low-power superconducting computing. However, the principle of the nSQUID is not that straightforward and an nSQUID driven by voltage is vulnerable to common mode noise. We investigate a single nSQUID driven by current instead of voltage, and clarify the principle of the adiabatic transition of the current-driven nSQUID between different states. The basic logic operations of the current-driven nSQUID with proper parameters are simulated by WRspice. The corresponding circuit is fabricated with a 100 A cm-2 Nb-based lift-off process, and the experimental results at low temperature confirm the basic logic operations as a gated buffer.
Lokriti, Abdesslam; Salhi, Issam; Doubabi, Said; Zidani, Youssef
2013-05-01
An IP-self-tuning controller tuned by a fuzzy adjustor, is proposed to improve induction machine speed control. The interest of such controller is the possibility to adjust only one gain, instead of two gains for the case of the PI-self-tuning controllers commonly used in the literature. This paper presents simulation and experimental results. These latter were obtained by practical implementation on a DSPace 1104 board of three different speed controllers (the classical IP, the fuzzy-like-PI and the IP-self-tuning), for a 1.5KW induction machine. The paper presents different tests used to compare the performances of the proposed controller to the two others in terms of computation time, tracking performances and disturbances rejection. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.
Data-driven advice for applying machine learning to bioinformatics problems
Olson, Randal S.; La Cava, William; Mustahsan, Zairah; Varik, Akshay; Moore, Jason H.
2017-01-01
As the bioinformatics field grows, it must keep pace not only with new data but with new algorithms. Here we contribute a thorough analysis of 13 state-of-the-art, commonly used machine learning algorithms on a set of 165 publicly available classification problems in order to provide data-driven algorithm recommendations to current researchers. We present a number of statistical and visual comparisons of algorithm performance and quantify the effect of model selection and algorithm tuning for each algorithm and dataset. The analysis culminates in the recommendation of five algorithms with hyperparameters that maximize classifier performance across the tested problems, as well as general guidelines for applying machine learning to supervised classification problems. PMID:29218881
Mass sensitivity studies for an inductively driven railgun
NASA Astrophysics Data System (ADS)
Scanlon, J. J., III; Young, A. F.
1991-01-01
Those areas which result in substantial system mass reductions for an HPG (homopolar generator) driven EML (electromagnetic launcher) are identified. Sensitivity studies are performed by varying launch mass, peak acceleration, launcher efficiency, inductance gradient, injection velocity, barrel mass per unit length, fuel tankage and pump estimates, and component energy and power densities. Two major contributors to the system mass are the allowed number of shots per barrel versus the number required for the mission, and the barrel length. The effects of component performance parameters, such as friction coefficient, injection velocity, ablation coefficient, rail resistivity, armature voltage, peak acceleration, and inductance gradient on these two areas, are addressed.
Performance Analysis of Saturated Induction Motors by Virtual Tests
ERIC Educational Resources Information Center
Ojaghi, M.; Faiz, J.; Kazemi, M.; Rezaei, M.
2012-01-01
Many undergraduate-level electrical machines textbooks give detailed treatments of the performance of induction motors. Students can deepen this understanding of motor performance by performing the appropriate practical work in laboratories or in simulation using proper software packages. This paper considers various common and less-common tests…
A nanojet: propulsion of a molecular machine by an asymmetric distribution of reaction--products
NASA Astrophysics Data System (ADS)
Liverpool, Tanniemola; Golestanian, Ramin; Ajdari, Armand
2006-03-01
A simple model for the reaction-driven propulsion of a small device is proposed as a model for (part of) a molecular machine in aqueous media. Motion of the device is driven by an asymmetric distribution of reaction products. We calculate the propulsive velocity of the device as well as the scale of the velocity fluctuations. We also consider the effects of hydrodynamic flow as well as a number of different scenarios for the kinetics of the reaction.
Propulsion of a Molecular Machine by Asymmetric Distribution of Reaction Products
NASA Astrophysics Data System (ADS)
Golestanian, Ramin; Liverpool, Tanniemola B.; Ajdari, Armand
2005-06-01
A simple model for the reaction-driven propulsion of a small device is proposed as a model for (part of) a molecular machine in aqueous media. The motion of the device is driven by an asymmetric distribution of reaction products. The propulsive velocity of the device is calculated as well as the scale of the velocity fluctuations. The effects of hydrodynamic flow as well as a number of different scenarios for the kinetics of the reaction are addressed.
Propulsion of a molecular machine by asymmetric distribution of reaction products.
Golestanian, Ramin; Liverpool, Tanniemola B; Ajdari, Armand
2005-06-10
A simple model for the reaction-driven propulsion of a small device is proposed as a model for (part of) a molecular machine in aqueous media. The motion of the device is driven by an asymmetric distribution of reaction products. The propulsive velocity of the device is calculated as well as the scale of the velocity fluctuations. The effects of hydrodynamic flow as well as a number of different scenarios for the kinetics of the reaction are addressed.
Steels with controlled hardenability for induction hardening
NASA Astrophysics Data System (ADS)
Shepelyakovskii, K. Z.
1980-07-01
Steels of the CH and LH type developed in the Soviet Union permit the use of a new method of induction hardening — bulk-surface hardening — and efficient utilization of the high-strength conditions (σb = 230-250 kgf/mm2). These steels make it possible to improve the structural strength, operating characteristics, service life, and reliability of critical heavily loaded machine parts. At the same time, CH steels make it possible to reduce by a factor of 2-3 the quantity of alloying elements, reduce the electrical energy for heat treatment, and completely exclude the cost of quenching oil for heat treatment in automatic equipment with high labor productivity, while retaining good working conditions. All this leads to substantial savings in production and operation. For example, when transmission gears (cylindrical and conical) are manufactured from LH steels the annual savings amount to more than 700,000 rubles at two automobile plants. Machine parts of CH steels — half axles and bearings in railway cars —have saved respectively six and four million rubles annually. The introduction of controlled-hardenability steels for induction hardening is a necessary condition for technological progress in machine construction and metallurgy.
Structural Design Optimization of Doubly-Fed Induction Generators Using GeneratorSE
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sethuraman, Latha; Fingersh, Lee J; Dykes, Katherine L
2017-11-13
A wind turbine with a larger rotor swept area can generate more electricity, however, this increases costs disproportionately for manufacturing, transportation, and installation. This poster presents analytical models for optimizing doubly-fed induction generators (DFIGs), with the objective of reducing the costs and mass of wind turbine drivetrains. The structural design for the induction machine includes models for the casing, stator, rotor, and high-speed shaft developed within the DFIG module in the National Renewable Energy Laboratory's wind turbine sizing tool, GeneratorSE. The mechanical integrity of the machine is verified by examining stresses, structural deflections, and modal properties. The optimization results aremore » then validated using finite element analysis (FEA). The results suggest that our analytical model correlates with the FEA in some areas, such as radial deflection, differing by less than 20 percent. But the analytical model requires further development for axial deflections, torsional deflections, and stress calculations.« less
A video, text, and speech-driven realistic 3-d virtual head for human-machine interface.
Yu, Jun; Wang, Zeng-Fu
2015-05-01
A multiple inputs-driven realistic facial animation system based on 3-D virtual head for human-machine interface is proposed. The system can be driven independently by video, text, and speech, thus can interact with humans through diverse interfaces. The combination of parameterized model and muscular model is used to obtain a tradeoff between computational efficiency and high realism of 3-D facial animation. The online appearance model is used to track 3-D facial motion from video in the framework of particle filtering, and multiple measurements, i.e., pixel color value of input image and Gabor wavelet coefficient of illumination ratio image, are infused to reduce the influence of lighting and person dependence for the construction of online appearance model. The tri-phone model is used to reduce the computational consumption of visual co-articulation in speech synchronized viseme synthesis without sacrificing any performance. The objective and subjective experiments show that the system is suitable for human-machine interaction.
Investigation of Combined Motor/Magnetic Bearings for Flywheel Energy Storage Systems
NASA Technical Reports Server (NTRS)
Hofmann, Heath
2003-01-01
Dr. Hofmann's work in the summer of 2003 consisted of two separate projects. In the first part of the summer, Dr. Hofmann prepared and collected information regarding rotor losses in synchronous machines; in particular, machines with low rotor losses operating in vacuum and supported by magnetic bearings, such as the motor/generator for flywheel energy storage systems. This work culminated in a presentation at NASA Glenn Research Center on this topic. In the second part, Dr. Hofmann investigated an approach to flywheel energy storage where the phases of the flywheel motor/generator are connected in parallel with the phases of an induction machine driving a mechanical actuator. With this approach, additional power electronics for driving the flywheel unit are not required. Simulations of the connection of a flywheel energy storage system to a model of an electromechanical actuator testbed at NASA Glenn were performed that validated the proposed approach. A proof-of-concept experiment using the D1 flywheel unit at NASA Glenn and a Sundstrand induction machine connected to a dynamometer was successfully conducted.
Inductive tuners for microwave driven discharge lamps
Simpson, James E.
1999-01-01
An RF powered electrodeless lamp utilizing an inductive tuner in the waveguide which couples the RF power to the lamp cavity, for reducing reflected RF power and causing the lamp to operate efficiently.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Schwarz, Jens; Savage, Mark E.; Lucero, Diego Jose
Future pulsed power systems may rely on linear transformer driver (LTD) technology. The LTD's will be the building blocks for a driver that can deliver higher current than the Z-Machine. The LTD's would require tens of thousands of low inductance ( %3C 85nH), high voltage (200 kV DC) switches with high reliability and long lifetime ( 10 4 shots). Sandia's Z-Machine employs 36 megavolt class switches that are laser triggered by a single channel discharge. This is feasible for tens of switches but the high inductance and short switch life- time associated with the single channel discharge are undesirable formore » future machines. Thus the fundamental problem is how to lower inductance and losses while increasing switch life- time and reliability. These goals can be achieved by increasing the number of current-carrying channels. The rail gap switch is ideal for this purpose. Although those switches have been extensively studied during the past decades, each effort has only characterized a particular switch. There is no comprehensive understanding of the underlying physics that would allow predictive capability for arbitrary switch geometry. We have studied rail gap switches via an extensive suite of advanced diagnostics in synergy with theoretical physics and advanced modeling capability. Design and topology of multichannel switches as they relate to discharge dynamics are investigated. This involves electrically and optically triggered rail gaps, as well as discrete multi-site switch concepts.« less
ERIC Educational Resources Information Center
Alsford, Sally; Rose, Christine
2014-01-01
This case study gives an analytical account of institutional development in induction provision. Driven by student experience concerns, a London post-1992 University set up an "enhanced induction project" to provide a more integrated, personalised approach through more coordinated processes. In a large, diverse context, university-wide…
Foam-Mixing-And-Dispensing Machine
NASA Technical Reports Server (NTRS)
Chong, Keith Y.; Toombs, Gordon R.; Jackson, Richard J.
1996-01-01
Time-and-money-saving machine produces consistent, homogeneously mixed foam, enhancing production efficiency. Automatically mixes and dispenses polyurethane foam in quantities specified by weight. Consists of cart-mounted, air-driven proportioning unit; air-activated mechanical mixing gun; programmable timer/counter, and controller.
NASA Astrophysics Data System (ADS)
Ma, Zhichao; Hu, Leilei; Zhao, Hongwei; Wu, Boda; Peng, Zhenxing; Zhou, Xiaoqin; Zhang, Hongguo; Zhu, Shuai; Xing, Lifeng; Hu, Huang
2010-08-01
The theories and techniques for improving machining accuracy via position control of diamond tool's tip and raising resolution of cutting depth on precise CNC lathes have been extremely focused on. A new piezo-driven ultra-precision machine tool servo system is designed and tested to improve manufacturing accuracy of workpiece. The mathematical model of machine tool servo system is established and the finite element analysis is carried out on parallel plate flexure hinges. The output position of diamond tool's tip driven by the machine tool servo system is tested via a contact capacitive displacement sensor. Proportional, integral, derivative (PID) feedback is also implemented to accommodate and compensate dynamical change owing cutting forces as well as the inherent non-linearity factors of the piezoelectric stack during cutting process. By closed loop feedback controlling strategy, the tracking error is limited to 0.8 μm. Experimental results have shown the proposed machine tool servo system could provide a tool positioning resolution of 12 nm, which is much accurate than the inherent CNC resolution magnitude. The stepped shaft of aluminum specimen with a step increment of cutting depth of 1 μm is tested, and the obtained contour illustrates the displacement command output from controller is accurately and real-time reflected on the machined part.
Method of fabricating a micro machine
Stalford, Harold L
2014-11-11
A micro machine may be in or less than the micrometer domain. The micro machine may include a micro actuator and a micro shaft coupled to the micro actuator. The micro shaft is operable to be driven by the micro actuator. A tool is coupled to the micro shaft and is operable to perform work in response to at least motion of the micro shaft.
Methods and systems for micro machines
Stalford, Harold L.
2018-03-06
A micro machine may be in or less than the micrometer domain. The micro machine may include a micro actuator and a micro shaft coupled to the micro actuator. The micro shaft is operable to be driven by the micro actuator. A tool is coupled to the micro shaft and is operable to perform work in response to at least motion of the micro shaft.
Methods and systems for micro machines
DOE Office of Scientific and Technical Information (OSTI.GOV)
Stalford, Harold L.
2017-04-11
A micro machine may be in or less than the micrometer domain. The micro machine may include a micro actuator and a micro shaft coupled to the micro actuator. The micro shaft is operable to be driven by the micro actuator. A tool is coupled to the micro shaft and is operable to perform work in response to at least motion of the micro shaft.
Methods and systems for micro machines
DOE Office of Scientific and Technical Information (OSTI.GOV)
Stalford, Harold L.
A micro machine may be in or less than the micrometer domain. The micro machine may include a micro actuator and a micro shaft coupled to the micro actuator. The micro shaft is operable to be driven by the micro actuator. A tool is coupled to the micro shaft and is operable to perform work in response to at least motion of the micro shaft.
Integrated Inverter For Driving Multiple Electric Machines
Su, Gui-Jia [Knoxville, TN; Hsu, John S [Oak Ridge, TN
2006-04-04
An electric machine drive (50) has a plurality of inverters (50a, 50b) for controlling respective electric machines (57, 62), which may include a three-phase main traction machine (57) and two-phase accessory machines (62) in a hybrid or electric vehicle. The drive (50) has a common control section (53, 54) for controlling the plurality of inverters (50a, 50b) with only one microelectronic processor (54) for controlling the plurality of inverters (50a, 50b), only one gate driver circuit (53) for controlling conduction of semiconductor switches (S1-S10) in the plurality of inverters (50a, 50b), and also includes a common dc bus (70), a common dc bus filtering capacitor (C1) and a common dc bus voltage sensor (67). The electric machines (57, 62) may be synchronous machines, induction machines, or PM machines and may be operated in a motoring mode or a generating mode.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lee, Seong T; Burress, Timothy A; Tolbert, Leon M
2009-01-01
This paper introduces a new method for calculating the power factor and output torque by considering the cross saturation between direct-axis (d-axis) and quadrature-axis (q-axis) of an interior permanent magnet synchronous motor (IPMSM). The conventional two-axis IPMSM model is modified to include the cross saturation effect by adding the cross-coupled inductance terms. This paper also contains the new method of calculating the cross-coupled inductance values as well as self-inductance values in d- and q-axes. The analyzed motor is a high-speed brushless field excitation machine that offers high torque per ampere per core length at low speed and weakened flux atmore » high speed, which was developed for the traction motor of a hybrid electric vehicle. The conventional two-axis IPMSM model was modified to include the cross-saturation effect by adding the cross-coupled inductance terms Ldq and Lqd. By the advantage of the excited structure of the experimental IPMSM, the analyzing works were performed under two conditions, the highest and lowest excited conditions. Therefore, it is possible to investigate the cross-saturation effect when a machine has higher magnetic flux from its rotor. The following is a summary of conclusions that may be drawn from this work: (1) Considering cross saturation of an IPMSM offers more accurate expected values of motor parameters in output torque calculation, especially when negative d-axis current is high; (2) A less saturated synchronous machine could be more affected by the cross-coupled saturation effect; (3) Both cross-coupled inductances, L{sub qd} and L{sub dq}, are mainly governed by d-axis current rather than q-axis current; (4) The modified torque equation, can be used for the dynamic model of an IPMSM for developing a better control model or control strategy; and (5) It is possible that the brushless field excitation structure has a common magnetic flux path on both d- and q-axis, and as a result, the reluctance torque of the machine could be reduced.« less
Block-Module Electric Machines of Alternating Current
NASA Astrophysics Data System (ADS)
Zabora, I.
2018-03-01
The paper deals with electric machines having active zone based on uniform elements. It presents data on disk-type asynchronous electric motors with short-circuited rotors, where active elements are made by integrated technique that forms modular elements. Photolithography, spraying, stamping of windings, pressing of core and combined methods are utilized as the basic technological approaches of production. The constructions and features of operation for new electric machine - compatible electric machines-transformers are considered. Induction motors are intended for operation in hermetic plants with extreme conditions surrounding gas, steam-to-gas and liquid environment at a high temperature (to several hundred of degrees).
Model-Driven Engineering of Machine Executable Code
NASA Astrophysics Data System (ADS)
Eichberg, Michael; Monperrus, Martin; Kloppenburg, Sven; Mezini, Mira
Implementing static analyses of machine-level executable code is labor intensive and complex. We show how to leverage model-driven engineering to facilitate the design and implementation of programs doing static analyses. Further, we report on important lessons learned on the benefits and drawbacks while using the following technologies: using the Scala programming language as target of code generation, using XML-Schema to express a metamodel, and using XSLT to implement (a) transformations and (b) a lint like tool. Finally, we report on the use of Prolog for writing model transformations.
Free electron lasers driven by linear induction accelerators: High power radiation sources
NASA Technical Reports Server (NTRS)
Orzechowski, T. J.
1989-01-01
The technology of Free Electron Lasers (FELs) and linear induction accelerators (LIAs) is addressed by outlining the following topics: fundamentals of FELs; basic concepts of linear induction accelerators; the Electron Laser Facility (a microwave FEL); PALADIN (an infrared FEL); magnetic switching; IMP; and future directions (relativistic klystrons). This presentation is represented by viewgraphs only.
Linear motor drive system for continuous-path closed-loop position control of an object
Barkman, William E.
1980-01-01
A precision numerical controlled servo-positioning system is provided for continuous closed-loop position control of a machine slide or platform driven by a linear-induction motor. The system utilizes filtered velocity feedback to provide system stability required to operate with a system gain of 100 inches/minute/0.001 inch of following error. The filtered velocity feedback signal is derived from the position output signals of a laser interferometer utilized to monitor the movement of the slide. Air-bearing slides mounted to a stable support are utilized to minimize friction and small irregularities in the slideway which would tend to introduce positioning errors. A microprocessor is programmed to read command and feedback information and converts this information into the system following error signal. This error signal is summed with the negative filtered velocity feedback signal at the input of a servo amplifier whose output serves as the drive power signal to the linear motor position control coil.
A Deep Learning Approach for Fault Diagnosis of Induction Motors in Manufacturing
NASA Astrophysics Data System (ADS)
Shao, Si-Yu; Sun, Wen-Jun; Yan, Ru-Qiang; Wang, Peng; Gao, Robert X.
2017-11-01
Extracting features from original signals is a key procedure for traditional fault diagnosis of induction motors, as it directly influences the performance of fault recognition. However, high quality features need expert knowledge and human intervention. In this paper, a deep learning approach based on deep belief networks (DBN) is developed to learn features from frequency distribution of vibration signals with the purpose of characterizing working status of induction motors. It combines feature extraction procedure with classification task together to achieve automated and intelligent fault diagnosis. The DBN model is built by stacking multiple-units of restricted Boltzmann machine (RBM), and is trained using layer-by-layer pre-training algorithm. Compared with traditional diagnostic approaches where feature extraction is needed, the presented approach has the ability of learning hierarchical representations, which are suitable for fault classification, directly from frequency distribution of the measurement data. The structure of the DBN model is investigated as the scale and depth of the DBN architecture directly affect its classification performance. Experimental study conducted on a machine fault simulator verifies the effectiveness of the deep learning approach for fault diagnosis of induction motors. This research proposes an intelligent diagnosis method for induction motor which utilizes deep learning model to automatically learn features from sensor data and realize working status recognition.
Using a PC and External Media to Quantitatively Investigate Electromagnetic Induction
ERIC Educational Resources Information Center
Bonanno, A.; Bozzo, G.; Camarca, M.; Sapia, P.
2011-01-01
In this article we describe an experimental learning path about electromagnetic induction which uses an Atwood machine where one of the two hanging bodies is a cylindrical magnet falling through a plexiglass guide, surrounded either by a coil or by a copper pipe. The first configuration (magnet falling across a coil) allows students to…
Offline detection of broken rotor bars in AC induction motors
NASA Astrophysics Data System (ADS)
Powers, Craig Stephen
ABSTRACT. OFFLINE DETECTION OF BROKEN ROTOR BARS IN AC INDUCTION MOTORS. The detection of the broken rotor bar defect in medium- and large-sized AC induction machines is currently one of the most difficult tasks for the motor condition and monitoring industry. If a broken rotor bar defect goes undetected, it can cause a catastrophic failure of an expensive machine. If a broken rotor bar defect is falsely determined, it wastes time and money to physically tear down and inspect the machine only to find an incorrect diagnosis. Previous work in 2009 at Baker/SKF-USA in collaboration with the Korea University has developed a prototype instrument that has been highly successful in correctly detecting the broken rotor bar defect in ACIMs where other methods have failed. Dr. Sang Bin and his students at the Korea University have been using this prototype instrument to help the industry save money in the successful detection of the BRB defect. A review of the current state of motor conditioning and monitoring technology for detecting the broken rotor bar defect in ACIMs shows improved detection of this fault is still relevant. An analysis of previous work in the creation of this prototype instrument leads into the refactoring of the software and hardware into something more deployable, cost effective and commercially viable.
Code of Federal Regulations, 2010 CFR
2010-07-01
..., or bending rolls; and hot or cold rolling mills. (ii) All pressing or punching machines, such as... presses; and plate punches. (iii) All bending machines, such as apron brakes and press brakes. (iv) All...
Embedded control system for computerized franking machine
NASA Astrophysics Data System (ADS)
Shi, W. M.; Zhang, L. B.; Xu, F.; Zhan, H. W.
2007-12-01
This paper presents a novel control system for franking machine. A methodology for operating a franking machine using the functional controls consisting of connection, configuration and franking electromechanical drive is studied. A set of enabling technologies to synthesize postage management software architectures driven microprocessor-based embedded systems is proposed. The cryptographic algorithm that calculates mail items is analyzed to enhance the postal indicia accountability and security. The study indicated that the franking machine is reliability, performance and flexibility in printing mail items.
Reactive Power Compensating System.
Williams, Timothy J.; El-Sharkawi, Mohamed A.; Venkata, Subrahmanyam S.
1985-01-04
The circuit was designed for the specific application of wind-driven induction generators. It has great potential for application in any situation where a varying reactive power load is present, such as with induction motors or generators, or for transmission network compensation.
Safety Features in Anaesthesia Machine
Subrahmanyam, M; Mohan, S
2013-01-01
Anaesthesia is one of the few sub-specialties of medicine, which has quickly adapted technology to improve patient safety. This application of technology can be seen in patient monitoring, advances in anaesthesia machines, intubating devices, ultrasound for visualisation of nerves and vessels, etc., Anaesthesia machines have come a long way in the last 100 years, the improvements being driven both by patient safety as well as functionality and economy of use. Incorporation of safety features in anaesthesia machines and ensuring that a proper check of the machine is done before use on a patient ensures patient safety. This review will trace all the present safety features in the machine and their evolution. PMID:24249880
30 CFR 18.97 - Inspection of machines; minimum requirements.
Code of Federal Regulations, 2010 CFR
2010-07-01
... TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Field Approval of Electrically Operated Mining Equipment § 18.97 Inspection of machines; minimum... shall be conducted by an electrical representative and such inspection shall include: (1) Examination of...
30 CFR 18.97 - Inspection of machines; minimum requirements.
Code of Federal Regulations, 2011 CFR
2011-07-01
... TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Field Approval of Electrically Operated Mining Equipment § 18.97 Inspection of machines; minimum... shall be conducted by an electrical representative and such inspection shall include: (1) Examination of...
Autonomous Soil Assessment System: A Data-Driven Approach to Planetary Mobility Hazard Detection
NASA Astrophysics Data System (ADS)
Raimalwala, K.; Faragalli, M.; Reid, E.
2018-04-01
The Autonomous Soil Assessment System predicts mobility hazards for rovers. Its development and performance are presented, with focus on its data-driven models, machine learning algorithms, and real-time sensor data fusion for predictive analytics.
Control Demonstration of Multiple Doubly-Fed Induction Motors for Hybrid Electric Propulsion
NASA Technical Reports Server (NTRS)
Sadey, David J.; Bodson, Marc; Csank, Jeffrey T.; Hunker, Keith R.; Theman, Casey J.; Taylor, Linda M.
2017-01-01
The Convergent Aeronautics Solutions (CAS) High Voltage-Hybrid Electric Propulsion (HVHEP) task was formulated to support the move into future hybrid-electric aircraft. The goal of this project is to develop a new AC power architecture to support the needs of higher efficiency and lower emissions. This proposed architecture will adopt the use of the doubly-fed induction machine (DFIM) for propulsor drive motor application.The Convergent Aeronautics Solutions (CAS) High Voltage-Hybrid Electric Propulsion (HVHEP) task was formulated to support the move into future hybrid-electric aircraft. The goal of this project is to develop a new AC power architecture to support the needs of higher efficiency and lower emissions. This proposed architecture will adopt the use of the doubly-fed induction machine (DFIM) for propulsor drive motor application. DFIMs are attractive for several reasons, including but not limited to the ability to self-start, ability to operate sub- and super-synchronously, and requiring only fractionally rated power converters on a per-unit basis depending on the required range of operation. The focus of this paper is based specifically on the presentation and analysis of a novel strategy which allows for independent operation of each of the aforementioned doubly-fed induction motors. This strategy includes synchronization, soft-start, and closed loop speed control of each motor as a means of controlling output thrust; be it concurrently or differentially. The demonstration of this strategy has recently been proven out on a low power test bed using fractional horsepower machines. Simulation and hardware test results are presented in the paper.
Optimized Generator Designs for the DTU 10-MW Offshore Wind Turbine using GeneratorSE
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sethuraman, Latha; Maness, Michael; Dykes, Katherine
Compared to land-based applications, offshore wind imposes challenges for the development of next generation wind turbine generator technology. Direct-drive generators are believed to offer high availability, efficiency, and reduced operation and maintenance requirements; however, previous research suggests difficulties in scaling to several megawatts or more in size. The resulting designs are excessively large and/or massive, which are major impediments to transportation logistics, especially for offshore applications. At the same time, geared wind turbines continue to sustain offshore market growth through relatively cheaper and lightweight generators. However, reliability issues associated with mechanical components in a geared system create significant operation andmore » maintenance costs, and these costs make up a large portion of overall system costs offshore. Thus, direct-drive turbines are likely to outnumber their gear-driven counterparts for this market, and there is a need to review the costs or opportunities of building machines with different types of generators and examining their competitiveness at the sizes necessary for the next generation of offshore wind turbines. In this paper, we use GeneratorSE, the National Renewable Energy Laboratory's newly developed systems engineering generator sizing tool to estimate mass, efficiency, and the costs of different generator technologies satisfying the electromagnetic, structural, and basic thermal design requirements for application in a very large-scale offshore wind turbine such as the Technical University of Denmark's (DTU) 10-MW reference wind turbine. For the DTU reference wind turbine, we use the previously mentioned criteria to optimize a direct-drive, radial flux, permanent-magnet synchronous generator; a direct-drive electrically excited synchronous generator; a medium-speed permanent-magnet generator; and a high-speed, doubly-fed induction generator. Preliminary analysis of leveled costs of energy indicate that for large turbines, the cost of permanent magnets and reliability issues associated with brushes in electrically excited machines are the biggest deterrents for building direct-drive systems. The advantage of medium-speed permanent-magnet machines over doubly-fed induction generators is evident, yet, variability in magnet prices and solutions to address reliability issues associated with gearing and brushes can change this outlook. This suggests the need to potentially pursue fundamentally new innovations in generator designs that help avoid high capital costs but still have significant reliability related to performance.« less
Optimized Generator Designs for the DTU 10-MW Offshore Wind Turbine using GeneratorSE: Preprint
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sethuraman, Latha; Maness, Michael; Dykes, Katherine
Compared to land-based applications, offshore wind imposes challenges for the development of next generation wind turbine generator technology. Direct-drive generators are believed to offer high availability, efficiency, and reduced operation and maintenance requirements; however, previous research suggests difficulties in scaling to several megawatts or more in size. The resulting designs are excessively large and/or massive, which are major impediments to transportation logistics, especially for offshore applications. At the same time, geared wind turbines continue to sustain offshore market growth through relatively cheaper and lightweight generators. However, reliability issues associated with mechanical components in a geared system create significant operation andmore » maintenance costs, and these costs make up a large portion of overall system costs offshore. Thus, direct-drive turbines are likely to outnumber their gear-driven counterparts for this market, and there is a need to review the costs or opportunities of building machines with different types of generators and examining their competitiveness at the sizes necessary for the next generation of offshore wind turbines. In this paper, we use GeneratorSE, the National Renewable Energy Laboratory's newly developed systems engineering generator sizing tool to estimate mass, efficiency, and the costs of different generator technologies satisfying the electromagnetic, structural, and basic thermal design requirements for application in a very large-scale offshore wind turbine such as the Technical University of Denmark's (DTU) 10-MW reference wind turbine. For the DTU reference wind turbine, we use the previously mentioned criteria to optimize a direct-drive, radial flux, permanent-magnet synchronous generator; a direct-drive electrically excited synchronous generator; a medium-speed permanent-magnet generator; and a high-speed, doubly-fed induction generator. Preliminary analysis of leveled costs of energy indicate that for large turbines, the cost of permanent magnets and reliability issues associated with brushes in electrically excited machines are the biggest deterrents for building direct-drive systems. The advantage of medium-speed permanent-magnet machines over doubly-fed induction generators is evident, yet, variability in magnet prices and solutions to address reliability issues associated with gearing and brushes can change this outlook. This suggests the need to potentially pursue fundamentally new innovations in generator designs that help avoid high capital costs but still have significant reliability related to performance.« less
A machine learning approach to computer-aided molecular design
NASA Astrophysics Data System (ADS)
Bolis, Giorgio; Di Pace, Luigi; Fabrocini, Filippo
1991-12-01
Preliminary results of a machine learning application concerning computer-aided molecular design applied to drug discovery are presented. The artificial intelligence techniques of machine learning use a sample of active and inactive compounds, which is viewed as a set of positive and negative examples, to allow the induction of a molecular model characterizing the interaction between the compounds and a target molecule. The algorithm is based on a twofold phase. In the first one — the specialization step — the program identifies a number of active/inactive pairs of compounds which appear to be the most useful in order to make the learning process as effective as possible and generates a dictionary of molecular fragments, deemed to be responsible for the activity of the compounds. In the second phase — the generalization step — the fragments thus generated are combined and generalized in order to select the most plausible hypothesis with respect to the sample of compounds. A knowledge base concerning physical and chemical properties is utilized during the inductive process.
Induced sadness increases persistence in a simulated slot machine task among recreational gamblers.
Devos, Gaëtan; Clark, Luke; Maurage, Pierre; Billieux, Joël
2018-05-01
Gambling may constitute a strategy for coping with depressive mood, but a direct influence of depressive mood on gambling behaviors has never been tested via realistic experimental designs in gamblers. The current study tested whether experimentally induced sadness increases persistence on a simulated slot machine task using real monetary reinforcement in recreational gamblers. Sixty participants were randomly assigned to an experimental (sadness induction) or control (no emotional induction) condition, and then performed a slot machine task consisting of a mandatory phase followed by a persistence phase. Potential confounding variables (problem gambling symptoms, impulsivity traits, gambling cognitions) were measured to ensure that the experimental and control groups were comparable. The study showed that participants in the sadness condition displayed greater gambling persistence than control participants (p = .011). These data support the causal role of negative affect in decisions to gamble and persistence, which bears important theoretical and clinical implications. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
Investigation of self-excited induction generators for wind turbine applications
DOE Office of Scientific and Technical Information (OSTI.GOV)
Muljadi, E.; Butterfield, C.P.; Sallan, J.
2000-02-28
The use of squirrel-cage induction machines in wind generation is widely accepted as a generator of choice. The squirrel-cage induction machine is simple, reliable, cheap, lightweight, and requires very little maintenance. Generally, the induction generator is connected to the utility at constant frequency. With a constant frequency operation, the induction generator operates at practically constant speed (small range of slip). The wind turbine operates in optimum efficiency only within a small range of wind speed variation. The variable-speed operation allows an increase in energy captured and reduces both the torque peaks in the drive train and the power fluctuations sentmore » to the utility. In variable-speed operation, an induction generator needs an interface to convert the variable frequency output of the generator to the fixed frequency at the utility. This interface can be simplified by using a self-excited generator because a simple diode bridge is required to perform the ac/dc conversion. The subsequent dc/ac conversion can be performed using different techniques. The use of a thyristor bridge is readily available for large power conversion and has a lower cost and higher reliability. The firing angle of the inverter bridge can be controlled to track the optimum power curve of the wind turbine. With only diodes and thyristors used in power conversion, the system can be scaled up to a very high voltage and high power applications. This paper analyzes the operation of such a system applied to a 1/3-hp self-excited induction generator. It includes the simulations and tests performed for the different excitation configurations.« less
A Novelty Design Of Minimization Of Electrical Losses In A Vector Controlled Induction Machine Drive
NASA Astrophysics Data System (ADS)
Aryza, Solly; Irwanto, M.; Lubis, Zulkarnain; Putera Utama Siahaan, Andysah; Rahim, Robbi; Furqan, Mhd.
2018-01-01
The induction motor has in the industry . More attention has been a focus to develop and design of induction motor drive. With the method of vector control novelty prove the efficiency of induction motor over their entire speed range. In this paper desirable to design a loss minimization controller which can improve the efficiency. Also, this research described Modeling of an induction motor with core loss included. Realization of methods vector control for an induction motor drive with loss element included. The case of the loss minimization condition. The procedure was successful to calculate the gains of a PI controller. Though the problem of obtaining a robust and sensorless induction motor drive is by no means completely solved, the results obtained as part of this work point in a promising direction.
Real time automatic detection of bearing fault in induction machine using kurtogram analysis.
Tafinine, Farid; Mokrani, Karim
2012-11-01
A proposed signal processing technique for incipient real time bearing fault detection based on kurtogram analysis is presented in this paper. The kurtogram is a fourth-order spectral analysis tool introduced for detecting and characterizing non-stationarities in a signal. This technique starts from investigating the resonance signatures over selected frequency bands to extract the representative features. The traditional spectral analysis is not appropriate for non-stationary vibration signal and for real time diagnosis. The performance of the proposed technique is examined by a series of experimental tests corresponding to different bearing conditions. Test results show that this signal processing technique is an effective bearing fault automatic detection method and gives a good basis for an integrated induction machine condition monitor.
Relational machine learning for electronic health record-driven phenotyping.
Peissig, Peggy L; Santos Costa, Vitor; Caldwell, Michael D; Rottscheit, Carla; Berg, Richard L; Mendonca, Eneida A; Page, David
2014-12-01
Electronic health records (EHR) offer medical and pharmacogenomics research unprecedented opportunities to identify and classify patients at risk. EHRs are collections of highly inter-dependent records that include biological, anatomical, physiological, and behavioral observations. They comprise a patient's clinical phenome, where each patient has thousands of date-stamped records distributed across many relational tables. Development of EHR computer-based phenotyping algorithms require time and medical insight from clinical experts, who most often can only review a small patient subset representative of the total EHR records, to identify phenotype features. In this research we evaluate whether relational machine learning (ML) using inductive logic programming (ILP) can contribute to addressing these issues as a viable approach for EHR-based phenotyping. Two relational learning ILP approaches and three well-known WEKA (Waikato Environment for Knowledge Analysis) implementations of non-relational approaches (PART, J48, and JRIP) were used to develop models for nine phenotypes. International Classification of Diseases, Ninth Revision (ICD-9) coded EHR data were used to select training cohorts for the development of each phenotypic model. Accuracy, precision, recall, F-Measure, and Area Under the Receiver Operating Characteristic (AUROC) curve statistics were measured for each phenotypic model based on independent manually verified test cohorts. A two-sided binomial distribution test (sign test) compared the five ML approaches across phenotypes for statistical significance. We developed an approach to automatically label training examples using ICD-9 diagnosis codes for the ML approaches being evaluated. Nine phenotypic models for each ML approach were evaluated, resulting in better overall model performance in AUROC using ILP when compared to PART (p=0.039), J48 (p=0.003) and JRIP (p=0.003). ILP has the potential to improve phenotyping by independently delivering clinically expert interpretable rules for phenotype definitions, or intuitive phenotypes to assist experts. Relational learning using ILP offers a viable approach to EHR-driven phenotyping. Copyright © 2014 Elsevier Inc. All rights reserved.
French wind generator systems. [as auxiliary power sources for electrical networks
NASA Technical Reports Server (NTRS)
Noel, J. M.
1973-01-01
The experimental design of a wind driven generator with a rated power of 800 kilovolt amperes and capable of being connected to the main electrical network is reported. The rotor is a three bladed propeller; each blade is twisted but the fixed pitch is adjustable. The asynchronous 800-kilovolt ampere generator is driven by the propeller through a gearbox. A dissipating resistor regulates the machine under no-load conditions. The first propeller on the machine lasted 18 months; replacement of the rigid propeller with a flexible structure resulted in breakdown due to flutter effects.
30 CFR 18.49 - Connection boxes on machines.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Connection boxes on machines. 18.49 Section 18.49 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Construction and...
30 CFR 18.61 - Final inspection of complete machine.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Final inspection of complete machine. 18.61 Section 18.61 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Inspections...
Varying execution discipline to increase performance
DOE Office of Scientific and Technical Information (OSTI.GOV)
Campbell, P.L.; Maccabe, A.B.
1993-12-22
This research investigates the relationship between execution discipline and performance. The hypothesis has two parts: 1. Different execution disciplines exhibit different performance for different computations, and 2. These differences can be effectively predicted by heuristics. A machine model is developed that can vary its execution discipline. That is, the model can execute a given program using either the control-driven, data-driven or demand-driven execution discipline. This model is referred to as a ``variable-execution-discipline`` machine. The instruction set for the model is the Program Dependence Web (PDW). The first part of the hypothesis will be tested by simulating the execution of themore » machine model on a suite of computations, based on the Livermore Fortran Kernel (LFK) Test (a.k.a. the Livermore Loops), using all three execution disciplines. Heuristics are developed to predict relative performance. These heuristics predict (a) the execution time under each discipline for one iteration of each loop and (b) the number of iterations taken by that loop; then the heuristics use those predictions to develop a prediction for the execution of the entire loop. Similar calculations are performed for branch statements. The second part of the hypothesis will be tested by comparing the results of the simulated execution with the predictions produced by the heuristics. If the hypothesis is supported, then the door is open for the development of machines that can vary execution discipline to increase performance.« less
Informatics and machine learning to define the phenotype.
Basile, Anna Okula; Ritchie, Marylyn DeRiggi
2018-03-01
For the past decade, the focus of complex disease research has been the genotype. From technological advancements to the development of analysis methods, great progress has been made. However, advances in our definition of the phenotype have remained stagnant. Phenotype characterization has recently emerged as an exciting area of informatics and machine learning. The copious amounts of diverse biomedical data that have been collected may be leveraged with data-driven approaches to elucidate trait-related features and patterns. Areas covered: In this review, the authors discuss the phenotype in traditional genetic associations and the challenges this has imposed.Approaches for phenotype refinement that can aid in more accurate characterization of traits are also discussed. Further, the authors highlight promising machine learning approaches for establishing a phenotype and the challenges of electronic health record (EHR)-derived data. Expert commentary: The authors hypothesize that through unsupervised machine learning, data-driven approaches can be used to define phenotypes rather than relying on expert clinician knowledge. Through the use of machine learning and an unbiased set of features extracted from clinical repositories, researchers will have the potential to further understand complex traits and identify patient subgroups. This knowledge may lead to more preventative and precise clinical care.
30 CFR 18.21 - Machines equipped with powered dust collectors.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Machines equipped with powered dust collectors. 18.21 Section 18.21 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES...
Water-assisted femtosecond laser machining of electrospray nozzles on glass microfluidic devices.
An, Ran; Hoffman, Michelle D; Donoghue, Margaret A; Hunt, Alan J; Jacobson, Stephen C
2008-09-15
Using water-assisted femtosecond laser machining, we fabricated electrospray nozzles on glass coverslips and on assembled microfluidic devices. Machining the nozzles after device assembly facilitated alignment of the nozzles over the microchannels. The basic nozzle design is a through-hole in the coverslip to pass liquids and a trough machined around the through-hole to confine the electrospray and prevent liquid from wicking across the glass surface. Electrospray from the nozzles was stable with and without pressure-driven flow applied and was evaluated using mass spectra of the peptide bradykinin.
Data-Driven Approaches to Empirical Discovery
1988-10-31
if nece ry and identify by block number) empirical discovery history of science data-driven heuristics numeric laws theoretical terms scope of laws...to the normative side. Machine Discovery and the History of Science The history of science studies the actual path followed by scientists over the
Machine learning of fault characteristics from rocket engine simulation data
NASA Technical Reports Server (NTRS)
Ke, Min; Ali, Moonis
1990-01-01
Transformation of data into knowledge through conceptual induction has been the focus of our research described in this paper. We have developed a Machine Learning System (MLS) to analyze the rocket engine simulation data. MLS can provide to its users fault analysis, characteristics, and conceptual descriptions of faults, and the relationships of attributes and sensors. All the results are critically important in identifying faults.
Fuzzy logic controller optimization
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.
New Technique of High-Performance Torque Control Developed for Induction Machines
NASA Technical Reports Server (NTRS)
Kenny, Barbara H.
2003-01-01
Two forms of high-performance torque control for motor drives have been described in the literature: field orientation control and direct torque control. Field orientation control has been the method of choice for previous NASA electromechanical actuator research efforts with induction motors. Direct torque control has the potential to offer some advantages over field orientation, including ease of implementation and faster response. However, the most common form of direct torque control is not suitable for the highspeed, low-stator-flux linkage induction machines designed for electromechanical actuators with the presently available sample rates of digital control systems (higher sample rates are required). In addition, this form of direct torque control is not suitable for the addition of a high-frequency carrier signal necessary for the "self-sensing" (sensorless) position estimation technique. This technique enables low- and zero-speed position sensorless operation of the machine. Sensorless operation is desirable to reduce the number of necessary feedback signals and transducers, thus improving the reliability and reducing the mass and volume of the system. This research was directed at developing an alternative form of direct torque control known as a "deadbeat," or inverse model, solution. This form uses pulse-width modulation of the voltage applied to the machine, thus reducing the necessary sample and switching frequency for the high-speed NASA motor. In addition, the structure of the deadbeat form allows the addition of the high-frequency carrier signal so that low- and zero-speed sensorless operation is possible. The new deadbeat solution is based on using the stator and rotor flux as state variables. This choice of state variables leads to a simple graphical representation of the solution as the intersection of a constant torque line with a constant stator flux circle. Previous solutions have been expressed only in complex mathematical terms without a method to clearly visualize the solution. The graphical technique allows a more insightful understanding of the operation of the machine under various conditions.
FSW of Aluminum Tailor Welded Blanks across Machine Platforms
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hovanski, Yuri; Upadhyay, Piyush; Carlson, Blair
2015-02-16
Development and characterization of friction stir welded aluminum tailor welded blanks was successfully carried out on three separate machine platforms. Each was a commercially available, gantry style, multi-axis machine designed specifically for friction stir welding. Weld parameters were developed to support high volume production of dissimilar thickness aluminum tailor welded blanks at speeds of 3 m/min and greater. Parameters originally developed on an ultra-high stiffness servo driven machine where first transferred to a high stiffness servo-hydraulic friction stir welding machine, and subsequently transferred to a purpose built machine designed to accommodate thin sheet aluminum welding. The inherent beam stiffness, bearingmore » compliance, and control system for each machine were distinctly unique, which posed specific challenges in transferring welding parameters across machine platforms. This work documents the challenges imposed by successfully transferring weld parameters from machine to machine, produced from different manufacturers and with unique control systems and interfaces.« less
XRF inductive bead fusion and PLC based control system
NASA Astrophysics Data System (ADS)
Zhu, Jin-hong; Wang, Ying-jie; Shi, Hong-xin; Chen, Qing-ling; Chen, Yu-xi
2009-03-01
In order to ensure high-quality X-ray fluorescence spectrometry (XRF) analysis, an inductive bead fusion machine was developed. The prototype consists of super-audio IGBT induction heating power supply, rotation and swing mechanisms, and programmable logic controller (PLC). The system can realize sequence control, mechanical movement control, output current and temperature control. Experimental results show that the power supply can operate at an ideal quasi-resonant state, in which the expected power output and the required temperature can be achieved for rapid heating and the uniform formation of glass beads respectively.
Comprehension-Driven Program Analysis (CPA) for Malware Detection in Android Phones
2015-07-01
COMPREHENSION-DRIVEN PROGRAM ANALYSIS (CPA) FOR MALWARE DETECTION IN ANDROID PHONES IOWA STATE UNIVERSITY JULY 2015 FINAL...DRIVEN PROGRAM ANALYSIS (CPA) FOR MALWARE DETECTION IN ANDROID PHONES Sb. GRANT NUMBER N/A Sc. PROGRAM ELEMENT NUMBER 6 1101E 6. AUTHOR(S) Sd...machine analysis system to detect novel, sophisticated Android malware. (c) An innovative library summarization technique and its incorporation in
NASA Astrophysics Data System (ADS)
Birx, Daniel
1992-03-01
Among the family of particle accelerators, the Induction Linear Accelerator is the best suited for the acceleration of high current electron beams. Because the electromagnetic radiation used to accelerate the electron beam is not stored in the cavities but is supplied by transmission lines during the beam pulse it is possible to utilize very low Q (typically<10) structures and very large beam pipes. This combination increases the beam breakup limited maximum currents to of order kiloamperes. The micropulse lengths of these machines are measured in 10's of nanoseconds and duty factors as high as 10-4 have been achieved. Until recently the major problem with these machines has been associated with the pulse power drive. Beam currents of kiloamperes and accelerating potentials of megavolts require peak power drives of gigawatts since no energy is stored in the structure. The marriage of liner accelerator technology and nonlinear magnetic compressors has produced some unique capabilities. It now appears possible to produce electron beams with average currents measured in amperes, peak currents in kiloamperes and gradients exceeding 1 MeV/meter, with power efficiencies approaching 50%. The nonlinear magnetic compression technology has replaced the spark gap drivers used on earlier accelerators with state-of-the-art all-solid-state SCR commutated compression chains. The reliability of these machines is now approaching 1010 shot MTBF. In the following paper we will briefly review the historical development of induction linear accelerators and then discuss the design considerations.
NASA Astrophysics Data System (ADS)
Takayama, Ken; Briggs*, Richard J.
The motivation for the initial development of linear induction accelerators starting in the early 1960s came mainly from applications requiring intense electron pulses with beam currents and a charge per pulse above the range accessible to RF accelerators, and with particle energies beyond the capabilities of single stage pulsed-power diodes. The linear induction accelerators developed to meet these needs utilize a series of induction cells containing magnetic cores (torroidal geometry) driven directly by pulse modulators (pulsed power sources). This multistage "one-to-one transformer" configuration with non-resonant, low impedance induction cells accelerates kilo-Ampere-scale electron beam current pulses in induction linacs.
High-explosive driven crowbar switch
Dike, Robert S.; Kewish, Jr., Ralph W.
1976-01-13
The disclosure relates to a compact explosive driven switch for use as a low resistance, low inductance crowbar switch. A high-explosive charge extrudes a deformable conductive metallic plate through a polyethylene insulating layer to achieve a hard current contact with a supportive annular conductor.
Energy partitioning in an inductively driven rail gun
NASA Technical Reports Server (NTRS)
Sen, K. K.; Ray, P. K.
1984-01-01
The equations describing the performance of an inductively driven rail are analyzed numerically. Friction between the projectile and rails is included through an empirical formulation. The equations are applied to the experiment of Rashleigh and Marshall to obtain an estimate of energy distribution in rail guns as a function of time. It is found that only 15 percent of energy delivered by the inductor to the gun is transformed into the kinetic energy of the projectile. This study provides an insight into the nature of nonlinear coupling involved in the electromechanical interactions in a rail gun.
Comparative investigation of diagnosis media for induction machine mechanical unbalance fault.
Salah, Mohamed; Bacha, Khmais; Chaari, Abdelkader
2013-11-01
For an induction machine, we suggest a theoretical development of the mechanical unbalance effect on the analytical expressions of radial vibration and stator current. Related spectra are described and characteristic defect frequencies are determined. Moreover, the stray flux expressions are developed for both axial and radial sensor coil positions and a substitute diagnosis technique is proposed. In addition, the load torque effect on the detection efficiency of these diagnosis media is discussed and a comparative investigation is performed. The decisive factor of comparison is the fault sensitivity. Experimental results show that spectral analysis of the axial stray flux can be an alternative solution to cover effectiveness limitation of the traditional stator current technique and to substitute the classical vibration practice. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.
Astumian, R. D.
2017-01-01
The Nobel prize in Chemistry for 2016 was awarded to Jean Pierre Sauvage, Sir James Fraser Stoddart, and Bernard (Ben) Feringa for their contributions to the design and synthesis of molecular machines. While this field is still in its infancy, and at present there are no commercial applications, many observers have stressed the tremendous potential of molecular machines to revolutionize technology. However, perhaps the most important result so far accruing from the synthesis of molecular machines is the insight provided into the fundamental mechanisms by which molecular motors, including biological motors such as kinesin, myosin, FoF1 ATPase, and the flagellar motor, function. The ability to “tinker” with separate components of molecular motors allows asking, and answering, specific questions about mechanism, particularly with regard to light driven vs. chemistry driven molecular motors. PMID:28572896
Source localization in an ocean waveguide using supervised machine learning.
Niu, Haiqiang; Reeves, Emma; Gerstoft, Peter
2017-09-01
Source localization in ocean acoustics is posed as a machine learning problem in which data-driven methods learn source ranges directly from observed acoustic data. The pressure received by a vertical linear array is preprocessed by constructing a normalized sample covariance matrix and used as the input for three machine learning methods: feed-forward neural networks (FNN), support vector machines (SVM), and random forests (RF). The range estimation problem is solved both as a classification problem and as a regression problem by these three machine learning algorithms. The results of range estimation for the Noise09 experiment are compared for FNN, SVM, RF, and conventional matched-field processing and demonstrate the potential of machine learning for underwater source localization.
A Model-Driven Approach to e-Course Management
ERIC Educational Resources Information Center
Savic, Goran; Segedinac, Milan; Milenkovic, Dušica; Hrin, Tamara; Segedinac, Mirjana
2018-01-01
This paper presents research on using a model-driven approach to the development and management of electronic courses. We propose a course management system which stores a course model represented as distinct machine-readable components containing domain knowledge of different course aspects. Based on this formally defined platform-independent…
Moreno-Duarte, Ingrid; Montenegro, Julio; Balonov, Konstantin; Schumann, Roman
2017-04-15
Most modern anesthesia workstations provide automated checkout, which indicates the readiness of the anesthesia machine. In this case report, an anesthesia machine passed the automated machine checkout. Minutes after the induction of general anesthesia, we observed a mismatch between the selected and delivered tidal volumes in the volume auto flow mode with increased inspiratory resistance during manual ventilation. Endotracheal tube kinking, circuit obstruction, leaks, and patient-related factors were ruled out. Further investigation revealed a broken internal insert within the CO2 absorbent canister that allowed absorbent granules to cause a partial obstruction to inspiratory and expiratory flow triggering contradictory alarms. We concluded that even when the automated machine checkout indicates machine readiness, unforeseen equipment failure due to unexpected events can occur and require providers to remain vigilant.
Scarf-related injuries at a major trauma center in northern India.
Singh, Pritish; Kumar, Ashok; Shekhawat, Vishal
2017-04-01
Scarf is a long loose piece of cloth worn around the neck and shoulder. Despite cultural association of this apparel, it is part of numerous injury episodes of varying enormity. Entanglement of loose scarf in spoke wheels of bike, tricycle, belt driven machines like sugarcane juice machine, thresher, grinding machines, etc is observed both in social and industrial milieu. This study aims to investigate the scarf-related injuries at a major trauma center in northern India. From June 2013 to May 2015, a hospital-based prospective observational study was done in patients who presented to a level 1 trauma center in northern India with the mode of injury involving scarf around the neck. Demographic profile, mode of trauma, contributing factors, injury pattern, and the early management as well as early complications were recorded. There were 76 injuries directly related from scarf with the mean age of patients being 32.4 years. The most common primary factor involved was rotating wheel of motorbike/tricycle (46.1%), followed by belt driven machines (28.9%). The spectrum of injuries was diverse, including minor abrasions or lacerations (53.9%), large lacerations (15.8%), fractures and spine trauma (18.4%), mangled extremity and amputations (7.9%) and death (3.9%). More severe injury patterns were noted with belt driven machines. Scarf-related injuries constitute a sizable proportion of trauma, with varying degrees of severity. Devastating consequences in significant proportion of cases dictate the call for a prevention plan comprising both educational and legislative measures. Urgent preventive measures targeting scarf-related injuries will help reduce mortality and morbidity. Copyright © 2017 Daping Hospital and the Research Institute of Surgery of the Third Military Medical University. Production and hosting by Elsevier B.V. All rights reserved.
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.
Computer-aided design studies of the homopolar linear synchronous motor
NASA Astrophysics Data System (ADS)
Dawson, G. E.; Eastham, A. R.; Ong, R.
1984-09-01
The linear induction motor (LIM), as an urban transit drive, can provide good grade-climbing capabilities and propulsion/braking performance that is independent of steel wheel-rail adhesion. In view of its 10-12 mm airgap, the LIM is characterized by a low power factor-efficiency product of order 0.4. A synchronous machine offers high efficiency and controllable power factor. An assessment of the linear homopolar configuration of this machine is presented as an alternative to the LIM. Computer-aided design studies using the finite element technique have been conducted to identify a suitable machine design for urban transit propulsion.
Semi-supervised prediction of gene regulatory networks using machine learning algorithms.
Patel, Nihir; Wang, Jason T L
2015-10-01
Use of computational methods to predict gene regulatory networks (GRNs) from gene expression data is a challenging task. Many studies have been conducted using unsupervised methods to fulfill the task; however, such methods usually yield low prediction accuracies due to the lack of training data. In this article, we propose semi-supervised methods for GRN prediction by utilizing two machine learning algorithms, namely, support vector machines (SVM) and random forests (RF). The semi-supervised methods make use of unlabelled data for training. We investigated inductive and transductive learning approaches, both of which adopt an iterative procedure to obtain reliable negative training data from the unlabelled data. We then applied our semi-supervised methods to gene expression data of Escherichia coli and Saccharomyces cerevisiae, and evaluated the performance of our methods using the expression data. Our analysis indicated that the transductive learning approach outperformed the inductive learning approach for both organisms. However, there was no conclusive difference identified in the performance of SVM and RF. Experimental results also showed that the proposed semi-supervised methods performed better than existing supervised methods for both organisms.
Design and application of electromechanical actuators for deep space missions
NASA Technical Reports Server (NTRS)
Haskew, Tim A.; Wander, John
1993-01-01
The annual report Design and Application of Electromechanical Actuators for Deep Space Missions is presented. The reporting period is 16 Aug. 1992 to 15 Aug. 1993. However, the primary focus will be work performed since submission of our semi-annual progress report in Feb. 1993. Substantial progress was made. We currently feel confident in providing guidelines for motor and control strategy selection in electromechanical actuators to be used in thrust vector control (TVC) applications. A small portion was presented in the semi-annual report. At this point, we have implemented highly detailed simulations of various motor/drive systems. The primary motor candidates were the brushless dc machine, permanent magnet synchronous machine, and the induction machine. The primary control implementations were pulse width modulation and hysteresis current control. Each of the two control strategies were applied to each of the three motor choices. With either pulse width modulation or hysteresis current control, the induction machine was always vector controlled. A standard test position command sequence for system performance evaluation is defined. Currently, we are gathering all of the necessary data for formal presentation of the results. Briefly stated for TVC application, we feel that the brushless dc machine operating under PWM current control is the best option. Substantial details on the topic, with supporting simulation results, will be provided later, in the form of a technical paper prepared for submission and also in the next progress report with more detail than allowed for paper publication.
Active machine learning-driven experimentation to determine compound effects on protein patterns.
Naik, Armaghan W; Kangas, Joshua D; Sullivan, Devin P; Murphy, Robert F
2016-02-03
High throughput screening determines the effects of many conditions on a given biological target. Currently, to estimate the effects of those conditions on other targets requires either strong modeling assumptions (e.g. similarities among targets) or separate screens. Ideally, data-driven experimentation could be used to learn accurate models for many conditions and targets without doing all possible experiments. We have previously described an active machine learning algorithm that can iteratively choose small sets of experiments to learn models of multiple effects. We now show that, with no prior knowledge and with liquid handling robotics and automated microscopy under its control, this learner accurately learned the effects of 48 chemical compounds on the subcellular localization of 48 proteins while performing only 29% of all possible experiments. The results represent the first practical demonstration of the utility of active learning-driven biological experimentation in which the set of possible phenotypes is unknown in advance.
Challenges in Soft Computing: Case Study with Louisville MSD CSO Modeling
NASA Astrophysics Data System (ADS)
Ormsbee, L.; Tufail, M.
2005-12-01
The principal constituents of soft computing include fuzzy logic, neural computing, evolutionary computation, machine learning, and probabilistic reasoning. There are numerous applications of these constituents (both individually and combination of two or more) in the area of water resources and environmental systems. These range from development of data driven models to optimal control strategies to assist in more informed and intelligent decision making process. Availability of data is critical to such applications and having scarce data may lead to models that do not represent the response function over the entire domain. At the same time, too much data has a tendency to lead to over-constraining of the problem. This paper will describe the application of a subset of these soft computing techniques (neural computing and genetic algorithms) to the Beargrass Creek watershed in Louisville, Kentucky. The application include development of inductive models as substitutes for more complex process-based models to predict water quality of key constituents (such as dissolved oxygen) and use them in an optimization framework for optimal load reductions. Such a process will facilitate the development of total maximum daily loads for the impaired water bodies in the watershed. Some of the challenges faced in this application include 1) uncertainty in data sets, 2) model application, and 3) development of cause-and-effect relationships between water quality constituents and watershed parameters through use of inductive models. The paper will discuss these challenges and how they affect the desired goals of the project.
A data-driven multi-model methodology with deep feature selection for short-term wind forecasting
DOE Office of Scientific and Technical Information (OSTI.GOV)
Feng, Cong; Cui, Mingjian; Hodge, Bri-Mathias
With the growing wind penetration into the power system worldwide, improving wind power forecasting accuracy is becoming increasingly important to ensure continued economic and reliable power system operations. In this paper, a data-driven multi-model wind forecasting methodology is developed with a two-layer ensemble machine learning technique. The first layer is composed of multiple machine learning models that generate individual forecasts. A deep feature selection framework is developed to determine the most suitable inputs to the first layer machine learning models. Then, a blending algorithm is applied in the second layer to create an ensemble of the forecasts produced by firstmore » layer models and generate both deterministic and probabilistic forecasts. This two-layer model seeks to utilize the statistically different characteristics of each machine learning algorithm. A number of machine learning algorithms are selected and compared in both layers. This developed multi-model wind forecasting methodology is compared to several benchmarks. The effectiveness of the proposed methodology is evaluated to provide 1-hour-ahead wind speed forecasting at seven locations of the Surface Radiation network. Numerical results show that comparing to the single-algorithm models, the developed multi-model framework with deep feature selection procedure has improved the forecasting accuracy by up to 30%.« less
Design of a line-VISAR interferometer system for the Sandia Z Machine
NASA Astrophysics Data System (ADS)
Galbraith, J.; Austin, K.; Baker, J.; Bettencourt, R.; Bliss, E.; Celeste, J.; Clancy, T.; Cohen, S.; Crosley, M.; Datte, P.; Fratanduono, D.; Frieders, G.; Hammer, J.; Jackson, J.; Johnson, D.; Jones, M.; Koen, D.; Lusk, J.; Martinez, A.; Massey, W.; McCarville, T.; McLean, H.; Raman, K.; Rodriguez, S.; Spencer, D.; Springer, P.; Wong, J.
2017-08-01
A joint team comprised of Lawrence Livermore National Laboratory (LLNL) and Sandia National Laboratory (SNL) personnel is designing a line-VISAR (Velocity Interferometer System for Any Reflector) for the Sandia Z Machine, Z Line-VISAR. The diagnostic utilizes interferometry to assess current delivery as a function of radius during a magnetically-driven implosion. The Z Line-VISAR system is comprised of the following: a two-leg line-VISAR interferometer, an eight-channel Gated Optical Imager (GOI), and a fifty-meter transport beampath to/from the target of interest. The Z Machine presents unique optomechanical design challenges. The machine utilizes magnetically driven pulsed power to drive a target to elevated temperatures and pressures useful for high energy density science. Shock accelerations exceeding 30g and a strong electromagnetic pulse (EMP) are generated during the shot event as the machine discharges currents of over 25 million amps. Sensitive optical components must be protected from shock loading, and electrical equipment must be adequately shielded from the EMP. The optical design must accommodate temperature and humidity fluctuations in the facility as well as airborne hydrocarbons from the pulsed power components. We will describe the engineering design and concept of operations of the Z Line-VISAR system. Focus will be on optomechanical design.
Soft Computing Application in Fault Detection of Induction Motor
DOE Office of Scientific and Technical Information (OSTI.GOV)
Konar, P.; Puhan, P. S.; Chattopadhyay, P. Dr.
2010-10-26
The paper investigates the effectiveness of different patter classifier like Feed Forward Back Propagation (FFBPN), Radial Basis Function (RBF) and Support Vector Machine (SVM) for detection of bearing faults in Induction Motor. The steady state motor current with Park's Transformation has been used for discrimination of inner race and outer race bearing defects. The RBF neural network shows very encouraging results for multi-class classification problems and is hoped to set up a base for incipient fault detection of induction motor. SVM is also found to be a very good fault classifier which is highly competitive with RBF.
6. Photograph of a photograph in possession of Rock Island ...
6. Photograph of a photograph in possession of Rock Island Arsenal Historical Office. FIRST FLOOR, EAST WING, SHOWING BELT-DRIVEN EQUIPMENT (LATHES, DRILLS, SCREW MACHINES) USED IN MACHINING COMPONENTS FOR ARTILLERY GUN CARRIAGES. DATED MAY 12, 1904. - Rock Island Arsenal, Building No. 108, Rodman Avenue between Third & Fourth Streets, Rock Island, Rock Island County, IL
21. INTERIOR VIEW, UNDER THE MAIN FLOOR SHOWING THE LINESHAFT ...
21. INTERIOR VIEW, UNDER THE MAIN FLOOR SHOWING THE LINESHAFT SYSTEM ONCE POWERED BY A STEAM ENGINE AND LATER BY TWO LARGE ELECTRICAL MILL MOTORS (NOTICE LARGE GEAR IN FOREGROUND) THAT OPERATED EACH NAIL MACHINE; PRESENTLY THE NAIL MACHINES ARE DRIVEN BY INDIVIDUAL ELECTRICAL MOTORS - LaBelle Iron Works, Thirtieth & Wood Streets, Wheeling, Ohio County, WV
Functional language and data flow architectures
NASA Technical Reports Server (NTRS)
Ercegovac, M. D.; Patel, D. R.; Lang, T.
1983-01-01
This is a tutorial article about language and architecture approaches for highly concurrent computer systems based on the functional style of programming. The discussion concentrates on the basic aspects of functional languages, and sequencing models such as data-flow, demand-driven and reduction which are essential at the machine organization level. Several examples of highly concurrent machines are described.
NASA Astrophysics Data System (ADS)
Federici, Stefania; Oliviero, Giulio; Hamad-Schifferli, Kimberly; Bergese, Paolo
2010-12-01
We report the first example of microcantilever beams that are reversibly driven by protein thin film machines fuelled by cycling the salt concentration of the surrounding solution. We also show that upon the same salinity stimulus the drive can be completely reversed in its direction by introducing a surface coating ligand. Experimental results are throughout discussed within a general yet simple thermodynamic model.
Opportunistic Constructive Induction: Using Fragments of Domain Knowledge to Guide Construction
1991-01-01
contribute to its success in ways which they are often unaware of and, unfortunately, which go by unacknowledged. At the risk of omitting some people I am...ference on Machine Learning, pages 322 -329, Austin, TX, June 1990. [Blumer e_1 al... 19871 Anselm Blurner, Andrzej Ehrenfeucht, David Haussler, and...and Ryszard S. Michalki. A Comparative Review of Selected Methods fur Learning from Examples. In- Machine Learning: An A rtificialIntelligence
Superconductivity for Electromagnetic Guns
1984-03-01
greater than that for a pulsed homopolar machine when the time constant is less than 0.1 sec (ref 32) (See fig. 18). Since the energy density in a...transferred from the capacitor to the induct- or. If the capacitor is replaced by a homopolar machine, then, as is well-known, the kinetic energy of the...rotor plays the role of an "electrical" capacitance and the two arrangements (capacitance and homopolar ) are functionally equivalent. Group 3. In
Electric field prediction for a human body-electric machine system.
Ioannides, Maria G; Papadopoulos, Peter J; Dimitropoulou, Eugenia
2004-01-01
A system consisting of an electric machine and a human body is studied and the resulting electric field is predicted. A 3-phase induction machine operating at full load is modeled considering its geometry, windings, and materials. A human model is also constructed approximating its geometry and the electric properties of tissues. Using the finite element technique the electric field distribution in the human body is determined for a distance of 1 and 5 m from the machine and its effects are studied. Particularly, electric field potential variations are determined at specific points inside the human body and for these points the electric field intensity is computed and compared to the limit values for exposure according to international standards.
NASA Technical Reports Server (NTRS)
Demerdash, N. A.; Wang, R.; Secunde, R.
1992-01-01
A 3D finite element (FE) approach was developed and implemented for computation of global magnetic fields in a 14.3 kVA modified Lundell alternator. The essence of the new method is the combined use of magnetic vector and scalar potential formulations in 3D FEs. This approach makes it practical, using state of the art supercomputer resources, to globally analyze magnetic fields and operating performances of rotating machines which have truly 3D magnetic flux patterns. The 3D FE-computed fields and machine inductances as well as various machine performance simulations of the 14.3 kVA machine are presented in this paper and its two companion papers.
Active Vibration Control of Hydrodynamic Journal Bearings
NASA Astrophysics Data System (ADS)
Tůma, J.; Šimek, J.; Škuta, J.; Los, J.; Zavadil, J.
Rotor instability is one of the most serious problems of high-speed rotors supported by sliding bearings. With constantly increasing parameters, new machines problems with rotor instability are encountered more and more often. Even though there are many solutions based on passive improvement of the bearing geometry to enlarge the operational speed range of the journal bearing, the paper deals with a working prototype of a system for the active vibration control of journal bearings with the use of piezoactuators. The actively controlled journal bearing consists of a movable bushing, which is actuated by two piezoactuators. It is assumed that the journal vibration is measured by a pair of proximity probes. Force produced by piezoactuators and acting at the bushing is controlled according to error signals derived from the proximity probe output signals. The active vibration control was tested with the use of a test rig, which consists of a rotor supported by two controllable journal bearings and driven by an inductive motor up to 23,000 rpm. As it was proved by experiments the active vibration control extends considerably the range of the rotor operational speed.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Friedman, A.; Barnard, J. J.; Cohen, R. H.
The Heavy Ion Fusion Science Virtual National Laboratory(a collaboration of LBNL, LLNL, and PPPL) is using intense ion beams to heat thin foils to the"warm dense matter" regime at<~;; 1 eV, and is developing capabilities for studying target physics relevant to ion-driven inertial fusion energy. The need for rapid target heating led to the development of plasma-neutralized pulse compression, with current amplification factors exceeding 50 now routine on the Neutralized Drift Compression Experiment (NDCX). Construction of an improved platform, NDCX-II, has begun at LBNL with planned completion in 2012. Using refurbished induction cells from the Advanced Test Accelerator at LLNL,more » NDCX-II will compress a ~;;500 ns pulse of Li+ ions to ~;;1 ns while accelerating it to 3-4 MeV over ~;;15 m. Strong space charge forces are incorporated into the machine design at a fundamental level. We are using analysis, an interactive 1D PIC code (ASP) with optimizing capabilities and centroid tracking, and multi-dimensional Warpcode PIC simulations, to develop the NDCX-II accelerator. This paper describes the computational models employed, and the resulting physics design for the accelerator.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Friedman, A; Barnard, J J; Cohen, R H
The Heavy Ion Fusion Science Virtual National Laboratory (a collaboration of LBNL, LLNL, and PPPL) is using intense ion beams to heat thin foils to the 'warm dense matter' regime at {approx}< 1 eV, and is developing capabilities for studying target physics relevant to ion-driven inertial fusion energy. The need for rapid target heating led to the development of plasma-neutralized pulse compression, with current amplification factors exceeding 50 now routine on the Neutralized Drift Compression Experiment (NDCX). Construction of an improved platform, NDCX-II, has begun at LBNL with planned completion in 2012. Using refurbished induction cells from the Advanced Testmore » Accelerator at LLNL, NDCX-II will compress a {approx}500 ns pulse of Li{sup +} ions to {approx} 1 ns while accelerating it to 3-4 MeV over {approx} 15 m. Strong space charge forces are incorporated into the machine design at a fundamental level. We are using analysis, an interactive 1D PIC code (ASP) with optimizing capabilities and centroid tracking, and multi-dimensional Warpcode PIC simulations, to develop the NDCX-II accelerator. This paper describes the computational models employed, and the resulting physics design for the accelerator.« less
Wireless Monitoring of Induction Machine Rotor Physical Variables
Doolan Fernandes, Jefferson; Carvalho Souza, Francisco Elvis; de Paiva, José Alvaro
2017-01-01
With the widespread use of electric machines, there is a growing need to extract information from the machines to improve their control systems and maintenance management. The present work shows the development of an embedded system to perform the monitoring of the rotor physical variables of a squirrel cage induction motor. The system is comprised of: a circuit to acquire desirable rotor variable(s) and value(s) that send it to the computer; a rectifier and power storage circuit that converts an alternating current in a continuous current but also stores energy for a certain amount of time to wait for the motor’s shutdown; and a magnetic generator that harvests energy from the rotating field to power the circuits mentioned above. The embedded system is set on the rotor of a 5 HP squirrel cage induction motor, making it difficult to power the system because it is rotating. This problem can be solved with the construction of a magnetic generator device to avoid the need of using batteries or collector rings and will send data to the computer using a wireless NRF24L01 module. For the proposed system, initial validation tests were made using a temperature sensor (DS18b20), as this variable is known as the most important when identifying the need for maintenance and control systems. Few tests have shown promising results that, with further improvements, can prove the feasibility of using sensors in the rotor. PMID:29156564
Wireless Monitoring of Induction Machine Rotor Physical Variables.
Doolan Fernandes, Jefferson; Carvalho Souza, Francisco Elvis; Cipriano Maniçoba, Glauco George; Salazar, Andrés Ortiz; de Paiva, José Alvaro
2017-11-18
With the widespread use of electric machines, there is a growing need to extract information from the machines to improve their control systems and maintenance management. The present work shows the development of an embedded system to perform the monitoring of the rotor physical variables of a squirrel cage induction motor. The system is comprised of: a circuit to acquire desirable rotor variable(s) and value(s) that send it to the computer; a rectifier and power storage circuit that converts an alternating current in a continuous current but also stores energy for a certain amount of time to wait for the motor's shutdown; and a magnetic generator that harvests energy from the rotating field to power the circuits mentioned above. The embedded system is set on the rotor of a 5 HP squirrel cage induction motor, making it difficult to power the system because it is rotating. This problem can be solved with the construction of a magnetic generator device to avoid the need of using batteries or collector rings and will send data to the computer using a wireless NRF24L01 module. For the proposed system, initial validation tests were made using a temperature sensor (DS18b20), as this variable is known as the most important when identifying the need for maintenance and control systems. Few tests have shown promising results that, with further improvements, can prove the feasibility of using sensors in the rotor.
Punching influence on magnetic properties of the stator teeth of an induction motor
NASA Astrophysics Data System (ADS)
Kedous-Lebouc, A.; Cornut, B.; Perrier, J. C.; Manfé, Ph.; Chevalier, Th.
2003-01-01
In order to study the effects of punching of electrical steel sheets, a suitable geometrical structure able to characterize the stator teeth behavior of an induction motor is proposed and validated. The influence of the punching on a fully processed M330-65A is then characterized. A spectacular degradation of loss and B( H) curves is observed. This leads to a perceptible increase of the no-load machine current.
Schormans, Matthew; Valente, Virgilio; Demosthenous, Andreas
2015-01-01
Inductive powering for implanted medical devices is a commonly employed technique, that allows for implants to avoid more dangerous methods such as the use of transcutaneous wires or implanted batteries. However, wireless powering in this way also comes with a number of difficulties and conflicting requirements, which are often met by using designs based on compromise. In particular, one aspect common to most inductive power links is that they are driven with a fixed frequency, which may not be optimal depending on factors such as coupling and load. In this paper, a method is proposed in which an inductive power link is driven by a frequency that is maintained at an optimum value f(opt), to ensure that the link is in resonance. In order to maintain this resonance, a phase tracking technique is employed at the primary side of the link; this allows for compensation of changes in coil separation and load. The technique is shown to provide significant improvements in maintained secondary voltage and efficiency for a range of loads when the link is overcoupled.
NASA Astrophysics Data System (ADS)
Hua, Wei; Qi, Ji; Jia, Meng
2017-05-01
Switched reluctance machines (SRMs) have attracted extensive attentions due to the inherent advantages, including simple and robust structure, low cost, excellent fault-tolerance and wide speed range, etc. However, one of the bottlenecks limiting the SRMs for further applications is its unfavorable torque ripple, and consequently noise and vibration due to the unique doubly-salient structure and pulse-current-based power supply method. In this paper, an inductance Fourier decomposition-based current-hysteresis-control (IFD-CHC) strategy is proposed to reduce torque ripple of SRMs. After obtaining a nonlinear inductance-current-position model based Fourier decomposition, reference currents can be calculated by reference torque and the derived inductance model. Both the simulations and experimental results confirm the effectiveness of the proposed strategy.
Machine Learning and Deep Learning Models to Predict Runoff Water Quantity and Quality
NASA Astrophysics Data System (ADS)
Bradford, S. A.; Liang, J.; Li, W.; Murata, T.; Simunek, J.
2017-12-01
Contaminants can be rapidly transported at the soil surface by runoff to surface water bodies. Physically-based models, which are based on the mathematical description of main hydrological processes, are key tools for predicting surface water impairment. Along with physically-based models, data-driven models are becoming increasingly popular for describing the behavior of hydrological and water resources systems since these models can be used to complement or even replace physically based-models. In this presentation we propose a new data-driven model as an alternative to a physically-based overland flow and transport model. First, we have developed a physically-based numerical model to simulate overland flow and contaminant transport (the HYDRUS-1D overland flow module). A large number of numerical simulations were carried out to develop a database containing information about the impact of various input parameters (weather patterns, surface topography, vegetation, soil conditions, contaminants, and best management practices) on runoff water quantity and quality outputs. This database was used to train data-driven models. Three different methods (Neural Networks, Support Vector Machines, and Recurrence Neural Networks) were explored to prepare input- output functional relations. Results demonstrate the ability and limitations of machine learning and deep learning models to predict runoff water quantity and quality.
Aerospace induction motor actuators driven from a 20-kHz power link
NASA Technical Reports Server (NTRS)
Hansen, Irving G.
1990-01-01
Aerospace electromechanical actuators utilizing induction motors are under development in sizes up to 40 kW. While these actuators have immediate application to the Advanced Launch System (ALS) program, several potential applications are currently under study including the Advanced Aircraft Program. Several recent advances developed for the Space Station Freedom have allowed induction motors to be selected as a first choice for such applications. Among these technologies are bi-directional electronics and high frequency power distribution techniques. Each of these technologies are discussed with emphasis on their impact upon induction motor operation.
A system framework of inter-enterprise machining quality control based on fractal theory
NASA Astrophysics Data System (ADS)
Zhao, Liping; Qin, Yongtao; Yao, Yiyong; Yan, Peng
2014-03-01
In order to meet the quality control requirement of dynamic and complicated product machining processes among enterprises, a system framework of inter-enterprise machining quality control based on fractal was proposed. In this system framework, the fractal-specific characteristic of inter-enterprise machining quality control function was analysed, and the model of inter-enterprise machining quality control was constructed by the nature of fractal structures. Furthermore, the goal-driven strategy of inter-enterprise quality control and the dynamic organisation strategy of inter-enterprise quality improvement were constructed by the characteristic analysis on this model. In addition, the architecture of inter-enterprise machining quality control based on fractal was established by means of Web service. Finally, a case study for application was presented. The result showed that the proposed method was available, and could provide guidance for quality control and support for product reliability in inter-enterprise machining processes.
NASA Astrophysics Data System (ADS)
Tabekina, N. A.; Chepchurov, M. S.; Evtushenko, E. I.; Dmitrievsky, B. S.
2018-05-01
The work solves the problem of automation of machining process namely turning to produce parts having the planes parallel to an axis of rotation of part without using special tools. According to the results, the availability of the equipment of a high speed electromechanical drive to control the operative movements of lathe machine will enable one to get the planes parallel to the part axis. The method of getting planes parallel to the part axis is based on the mathematical model, which is presented as functional dependency between the conveying velocity of the driven element and the time. It describes the operative movements of lathe machine all over the tool path. Using the model of movement of the tool, it has been found that the conveying velocity varies from the maximum to zero value. It will allow one to carry out the reverse of the drive. The scheme of tool placement regarding the workpiece has been proposed for unidirectional movement of the driven element at high conveying velocity. The control method of CNC machines can be used for getting geometrically complex parts on the lathe without using special milling tools.
Suzuki, Hajime; Sakabe, Takahiro; Hirose, Yuu; Eki, Toshihiko
2017-01-01
We aimed to develop the bioassays for genotixicity and/or oxidative damage using the recombinant yeast. A genotoxicity assay was developed using recombinant Saccharomyces cerevisiae strain BY4741 with a green fluorescent protein (GFP) reporter plasmid, driven by the DNA damage-responsive RNR3 promoter. Enhanced fluorescence induction was observed in DNA repair-deficient strains treated with methyl methanesulfonate, but not with hydrogen peroxide. A GFP reporter yeast strain driven by the oxidative stress-responsive TRX2 promoter was newly developed to assess oxidative damage, but fluorescence was poorly induced by oxidants. In place of GFP, yeast strains with luciferase gene reporter plasmids (luc2 and luc2CP, encoding stable and unstable luciferase, respectively) were prepared. Transient induction of luciferase activity was clearly detected only in a TRX2 promoter-driven luc2CP reporter strain within 90 min of oxidant exposure. However, luciferase was strongly induced by hydroxyurea in the RNR3 promoter-driven luc2 and GFP reporter strains over 8 h after the exposure, suggesting that the RNR3 promoter is continuously upregulated by DNA damage, whereas the TRX2 promoter is transiently activated by oxidative agents. Luciferase activity levels were also increased in a TRX2-promoter-driven luc2CP reporter strain treated with tert-butyl hydroperoxide and menadione and weakly induced with diamide and diethyl maleate. Weakly enhanced luciferase activity induction was detected in the sod1Δ, sod2Δ, and rad27Δ strains treated with hydrogen peroxide compared with that in the wild-type strain. In conclusion, tests using GFP and stable luciferase reporters are useful for genotoxicity, and oxidative damage can be clearly detected by assay with an unstable luciferase reporter.
Unlearning Overgenerated "Be" through Data-Driven Learning in the Secondary EFL Classroom
ERIC Educational Resources Information Center
Moon, Soyeon; Oh, Sun-Young
2018-01-01
This paper reports on the cognitive and affective benefits of data-driven learning (DDL), in which Korean EFL learners at the secondary level notice and unlearn their "overgenerated 'be'" by comparing native English-speaker and learner corpora with guided induction. To select the target language item and compile learner-corpus-based…
Using a PC and external media to quantitatively investigate electromagnetic induction
NASA Astrophysics Data System (ADS)
Bonanno, A.; Bozzo, G.; Camarca, M.; Sapia, P.
2011-07-01
In this article we describe an experimental learning path about electromagnetic induction which uses an Atwood machine where one of the two hanging bodies is a cylindrical magnet falling through a plexiglass guide, surrounded either by a coil or by a copper pipe. The first configuration (magnet falling across a coil) allows students to quantitatively study the Faraday-Neumann-Lenz law, while the second configuration (falling through a copper pipe) permits learners to investigate the complex phenomena of induction by quantifying the amount of electric power dissipated through the pipe as a result of Foucault eddy currents, when the magnet travels through the pipe. The magnet's fall acceleration can be set by adjusting the counterweight of the Atwood machine so that both the kinematic quantities associated with it and the electromotive force induced within the coil are continuously and quantitatively monitored (respectively, by a common personal computer (PC) equipped with a webcam and by freely available software that makes it possible to use the audio card to convert the PC into an oscilloscope). Measurements carried out when the various experimental parameters are changed provide a useful framework for a thorough understanding and clarification of the conceptual nodes related to electromagnetic induction. The proposed learning path is under evaluation in various high schools participating in the project 'Lauree Scientifiche' promoted by the Italian Department of Education.
Cooperating reduction machines
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kluge, W.E.
1983-11-01
This paper presents a concept and a system architecture for the concurrent execution of program expressions of a concrete reduction language based on lamda-expressions. If formulated appropriately, these expressions are well-suited for concurrent execution, following a demand-driven model of computation. In particular, recursive program expressions with nonlinear expansion may, at run time, recursively be partitioned into a hierarchy of independent subexpressions which can be reduced by a corresponding hierarchy of virtual reduction machines. This hierarchy unfolds and collapses dynamically, with virtual machines recursively assuming the role of masters that create and eventually terminate, or synchronize with, slaves. The paper alsomore » proposes a nonhierarchically organized system of reduction machines, each featuring a stack architecture, that effectively supports the allocation of virtual machines to the real machines of the system in compliance with their hierarchical order of creation and termination. 25 references.« less
Energy efficient quantum machines
NASA Astrophysics Data System (ADS)
Abah, Obinna; Lutz, Eric
2017-05-01
We investigate the performance of a quantum thermal machine operating in finite time based on shortcut-to-adiabaticity techniques. We compute efficiency and power for a paradigmatic harmonic quantum Otto engine by taking the energetic cost of the shortcut driving explicitly into account. We demonstrate that shortcut-to-adiabaticity machines outperform conventional ones for fast cycles. We further derive generic upper bounds on both quantities, valid for any heat engine cycle, using the notion of quantum speed limit for driven systems. We establish that these quantum bounds are tighter than those stemming from the second law of thermodynamics.
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.
Fernandez, Michael; Abreu, Jose I; Shi, Hongqing; Barnard, Amanda S
2016-11-14
The possibility of band gap engineering in graphene opens countless new opportunities for application in nanoelectronics. In this work, the energy gaps of 622 computationally optimized graphene nanoflakes were mapped to topological autocorrelation vectors using machine learning techniques. Machine learning modeling revealed that the most relevant correlations appear at topological distances in the range of 1 to 42 with prediction accuracy higher than 80%. The data-driven model can statistically discriminate between graphene nanoflakes with different energy gaps on the basis of their molecular topology.
Table-driven software architecture for a stitching system
NASA Technical Reports Server (NTRS)
Thrash, Patrick J. (Inventor); Miller, Jeffrey L. (Inventor); Pallas, Ken (Inventor); Trank, Robert C. (Inventor); Fox, Rhoda (Inventor); Korte, Mike (Inventor); Codos, Richard (Inventor); Korolev, Alexandre (Inventor); Collan, William (Inventor)
2001-01-01
Native code for a CNC stitching machine is generated by generating a geometry model of a preform; generating tool paths from the geometry model, the tool paths including stitching instructions for making stitches; and generating additional instructions indicating thickness values. The thickness values are obtained from a lookup table. When the stitching machine runs the native code, it accesses a lookup table to determine a thread tension value corresponding to the thickness value. The stitching machine accesses another lookup table to determine a thread path geometry value corresponding to the thickness value.
Method and system for controlling a permanent magnet machine during fault conditions
Krefta, Ronald John; Walters, James E.; Gunawan, Fani S.
2004-05-25
Method and system for controlling a permanent magnet machine driven by an inverter is provided. The method allows for monitoring a signal indicative of a fault condition. The method further allows for generating during the fault condition a respective signal configured to maintain a field weakening current even though electrical power from an energy source is absent during said fault condition. The level of the maintained field-weakening current enables the machine to operate in a safe mode so that the inverter is protected from excess voltage.
SABRE, a 10-MV linear induction accelerator
DOE Office of Scientific and Technical Information (OSTI.GOV)
Corely, J.P.; Alexander, J.A.; Pankuch, P.J.
SABRE (Sandia Accelerator and Beam Research Experiment) is a 10-MV, 250-kA, 40-ns linear induction accelerator. It was designed to be used in positive polarity output. Positive polarity accelerators are important for application to Sandia's ICF (Inertial Confinement Fusion) and LMF (Laboratory Microfusion Facility) program efforts. SABRE was built to allow a more detailed study of pulsed power issues associated with positive polarity output machines. MITL (Magnetically Insulated Transmission Line) voltage adder efficiency, extraction ion diode development, and ion beam transport and focusing. The SABRE design allows the system to operate in either positive polarity output for ion extraction applications ormore » negative polarity output for more conventional electron beam loads. Details of the design of SABRE and the results of initial machine performance in negative polarity operation are presented in this paper. 13 refs., 12 figs., 1 tab.« less
Signal injection as a fault detection technique.
Cusidó, Jordi; Romeral, Luis; Ortega, Juan Antonio; Garcia, Antoni; Riba, Jordi
2011-01-01
Double frequency tests are used for evaluating stator windings and analyzing the temperature. Likewise, signal injection on induction machines is used on sensorless motor control fields to find out the rotor position. Motor Current Signature Analysis (MCSA), which focuses on the spectral analysis of stator current, is the most widely used method for identifying faults in induction motors. Motor faults such as broken rotor bars, bearing damage and eccentricity of the rotor axis can be detected. However, the method presents some problems at low speed and low torque, mainly due to the proximity between the frequencies to be detected and the small amplitude of the resulting harmonics. This paper proposes the injection of an additional voltage into the machine being tested at a frequency different from the fundamental one, and then studying the resulting harmonics around the new frequencies appearing due to the composition between injected and main frequencies.
Ben Salem, Samira; Bacha, Khmais; Chaari, Abdelkader
2012-09-01
In this work we suggest an original fault signature based on an improved combination of Hilbert and Park transforms. Starting from this combination we can create two fault signatures: Hilbert modulus current space vector (HMCSV) and Hilbert phase current space vector (HPCSV). These two fault signatures are subsequently analysed using the classical fast Fourier transform (FFT). The effects of mechanical faults on the HMCSV and HPCSV spectrums are described, and the related frequencies are determined. The magnitudes of spectral components, relative to the studied faults (air-gap eccentricity and outer raceway ball bearing defect), are extracted in order to develop the input vector necessary for learning and testing the support vector machine with an aim of classifying automatically the various states of the induction motor. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.
Grid-connected in-stream hydroelectric generation based on the doubly fed induction machine
NASA Astrophysics Data System (ADS)
Lenberg, Timothy J.
Within the United States, there is a growing demand for new environmentally friendly power generation. This has led to a surge in wind turbine development. Unfortunately, wind is not a stable prime mover, but water is. Why not apply the advances made for wind to in-stream hydroelectric generation? One important advancement is the creation of the Doubly Fed Induction Machine (DFIM). This thesis covers the application of a gearless DFIM topology for hydrokinetic generation. After providing background, this thesis presents many of the options available for the mechanical portion of the design. A mechanical turbine is then specified. Next, a method is presented for designing a DFIM including the actual design for this application. In Chapter 4, a simulation model of the system is presented, complete with a control system that maximizes power generation based on water speed. This section then goes on to present simulation results demonstrating proper operation.
Signal Injection as a Fault Detection Technique
Cusidó, Jordi; Romeral, Luis; Ortega, Juan Antonio; Garcia, Antoni; Riba, Jordi
2011-01-01
Double frequency tests are used for evaluating stator windings and analyzing the temperature. Likewise, signal injection on induction machines is used on sensorless motor control fields to find out the rotor position. Motor Current Signature Analysis (MCSA), which focuses on the spectral analysis of stator current, is the most widely used method for identifying faults in induction motors. Motor faults such as broken rotor bars, bearing damage and eccentricity of the rotor axis can be detected. However, the method presents some problems at low speed and low torque, mainly due to the proximity between the frequencies to be detected and the small amplitude of the resulting harmonics. This paper proposes the injection of an additional voltage into the machine being tested at a frequency different from the fundamental one, and then studying the resulting harmonics around the new frequencies appearing due to the composition between injected and main frequencies. PMID:22163801
Non-inductive current driven by Alfvén waves in solar coronal loops
NASA Astrophysics Data System (ADS)
Elfimov, A. G.; de Azevedo, C. A.; de Assis, A. S.
1996-08-01
It has been shown that Alfvén waves can drive non-inductive current in solar coronal loops via collisional or collisionless damping. Assuming that all the coronal-loop density of dissipated wave power (W= 10-3 erg cm-3 s-1), which is necessary to keep the plasma hot, is due to Alfvén wave electron heating, we have estimated the axial current density driven by Alfvén waves to be
Gutierrez-Villalobos, Jose M.; Rodriguez-Resendiz, Juvenal; Rivas-Araiza, Edgar A.; Martínez-Hernández, Moisés A.
2015-01-01
Three-phase induction motor drive requires high accuracy in high performance processes in industrial applications. Field oriented control, which is one of the most employed control schemes for induction motors, bases its function on the electrical parameter estimation coming from the motor. These parameters make an electrical machine driver work improperly, since these electrical parameter values change at low speeds, temperature changes, and especially with load and duty changes. The focus of this paper is the real-time and on-line electrical parameters with a CMAC-ADALINE block added in the standard FOC scheme to improve the IM driver performance and endure the driver and the induction motor lifetime. Two kinds of neural network structures are used; one to estimate rotor speed and the other one to estimate rotor resistance of an induction motor. PMID:26131677
Gutierrez-Villalobos, Jose M; Rodriguez-Resendiz, Juvenal; Rivas-Araiza, Edgar A; Martínez-Hernández, Moisés A
2015-06-29
Three-phase induction motor drive requires high accuracy in high performance processes in industrial applications. Field oriented control, which is one of the most employed control schemes for induction motors, bases its function on the electrical parameter estimation coming from the motor. These parameters make an electrical machine driver work improperly, since these electrical parameter values change at low speeds, temperature changes, and especially with load and duty changes. The focus of this paper is the real-time and on-line electrical parameters with a CMAC-ADALINE block added in the standard FOC scheme to improve the IM driver performance and endure the driver and the induction motor lifetime. Two kinds of neural network structures are used; one to estimate rotor speed and the other one to estimate rotor resistance of an induction motor.
Intelligent fuzzy controller for event-driven real time systems
NASA Technical Reports Server (NTRS)
Grantner, Janos; Patyra, Marek; Stachowicz, Marian S.
1992-01-01
Most of the known linguistic models are essentially static, that is, time is not a parameter in describing the behavior of the object's model. In this paper we show a model for synchronous finite state machines based on fuzzy logic. Such finite state machines can be used to build both event-driven, time-varying, rule-based systems and the control unit section of a fuzzy logic computer. The architecture of a pipelined intelligent fuzzy controller is presented, and the linguistic model is represented by an overall fuzzy relation stored in a single rule memory. A VLSI integrated circuit implementation of the fuzzy controller is suggested. At a clock rate of 30 MHz, the controller can perform 3 MFLIPS on multi-dimensional fuzzy data.
Spectral and spatial characterisation of laser-driven positron beams
Sarri, G.; Warwick, J.; Schumaker, W.; ...
2016-10-18
The generation of high-quality relativistic positron beams is a central area of research in experimental physics, due to their potential relevance in a wide range of scientific and engineering areas, ranging from fundamental science to practical applications. There is now growing interest in developing hybrid machines that will combine plasma-based acceleration techniques with more conventional radio-frequency accelerators, in order to minimise the size and cost of these machines. Here we report on recent experiments on laser-driven generation of high-quality positron beams using a relatively low energy and potentially table-top laser system. Lastly, the results obtained indicate that current technology allowsmore » to create, in a compact setup, positron beams suitable for injection in radio-frequency accelerators.« less
Gómez-Cogolludo, Pablo; Castillo-Oyagüe, Raquel; Lynch, Christopher D; Suárez-García, María-Jesús
2013-09-01
The aim of this study was to identify the most appropriate alloy composition and melting technique by evaluating the marginal accuracy of cast metal-ceramic crowns. Seventy standardised stainless-steel abutments were prepared to receive metal-ceramic crowns and were randomly divided into four alloy groups: Group 1: palladium-gold (Pd-Au), Group 2: nickel-chromium-titanium (Ni-Cr-Ti), Group 3: nickel-chromium (Ni-Cr) and Group 4: titanium (Ti). Groups 1, 2 and 3 were in turn subdivided to be melted and cast using: (a) gas oxygen torch and centrifugal casting machine (TC) or (b) induction and centrifugal casting machine (IC). Group 4 was melted and cast using electric arc and vacuum/pressure machine (EV). All of the metal-ceramic crowns were luted with glass-ionomer cement. The marginal fit was measured under an optical microscope before and after cementation using image analysis software. All data was subjected to two-way analysis of variance (ANOVA). Duncan's multiple range test was run for post-hoc comparisons. The Student's t-test was used to investigate the influence of cementation (α=0.05). Uncemented Pd-Au/TC samples achieved the best marginal adaptation, while the worst fit corresponded to the luted Ti/EV crowns. Pd-Au/TC, Ni-Cr and Ti restorations demonstrated significantly increased misfit after cementation. The Ni-Cr-Ti alloy was the most predictable in terms of differences in misfit when either torch or induction was applied before or after cementation. Cemented titanium crowns exceeded the clinically acceptable limit of 120μm. The combination of alloy composition, melting technique, casting method and luting process influences the vertical seal of cast metal-ceramic crowns. An accurate use of the gas oxygen torch may overcome the results attained with the induction system concerning the marginal adaptation of fixed dental prostheses. Copyright © 2013 Elsevier Ltd. All rights reserved.
On-line diagnosis of defaults on squirrel cage motors using FEM
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bentounsi, A.; Nicolas, A.
1998-09-01
In industry, the predictive maintenance has become a strategic concept. Economic interest of on-line diagnosis of faults in electric machines gave rise to various researches in that field. This paper proposes a local approach to tackle the problem of breaking bars and end-rings of squirrel cage in induction machines based mainly on the signature of the local variables, such as the normal flux density. This allows a finer analysis, by use of a finite element based simulation.
Active machine learning-driven experimentation to determine compound effects on protein patterns
Naik, Armaghan W; Kangas, Joshua D; Sullivan, Devin P; Murphy, Robert F
2016-01-01
High throughput screening determines the effects of many conditions on a given biological target. Currently, to estimate the effects of those conditions on other targets requires either strong modeling assumptions (e.g. similarities among targets) or separate screens. Ideally, data-driven experimentation could be used to learn accurate models for many conditions and targets without doing all possible experiments. We have previously described an active machine learning algorithm that can iteratively choose small sets of experiments to learn models of multiple effects. We now show that, with no prior knowledge and with liquid handling robotics and automated microscopy under its control, this learner accurately learned the effects of 48 chemical compounds on the subcellular localization of 48 proteins while performing only 29% of all possible experiments. The results represent the first practical demonstration of the utility of active learning-driven biological experimentation in which the set of possible phenotypes is unknown in advance. DOI: http://dx.doi.org/10.7554/eLife.10047.001 PMID:26840049
NASA Astrophysics Data System (ADS)
Otero
2017-10-01
Here we review the persisting conceptual discrepancies between different research groups working on artificial muscles based on conducting polymers and other electroactive material. The basic question is if they can be treated as traditional electro-mechanical (physical) actuators driven by electric fields and described by some adaptation of their physical models or if, replicating natural muscles, they are electro-chemo-mechanical actuators driven by electrochemical reaction of the constitutive molecular machines: the polymeric chains. In that case the charge consumed by the reaction will control the volume variation of the muscular material and the motor displacement, following the basic and single Faraday's laws: the charge consumed by the reaction determines the number of exchanged ions and solvent, the film volume variation to lodge/expel them and the amplitude of the movement. Deviations from the linear relationships are due to the osmotic exchange of solvent and to the presence of parallel reactions from the electrolyte, which originate creeping effects. Challenges and limitations are underlined.
Data-Driven Property Estimation for Protective Clothing
2014-09-01
reliable predictions falls under the rubric “machine learning”. Inspired by the applications of machine learning in pharmaceutical drug design and...using genetic algorithms, for instance— descriptor selection can be automated as well. A well-known structured learning technique—Artificial Neural...descriptors automatically, by iteration, e.g., using a genetic algorithm [49]. 4.2.4 Avoiding Overfitting A peril of all regression—least squares as
The Fusion Gain Analysis of the Inductively Driven Liner Compression Based Fusion
NASA Astrophysics Data System (ADS)
Shimazu, Akihisa; Slough, John
2016-10-01
An analytical analysis of the fusion gain expected in the inductively driven liner compression (IDLC) based fusion is conducted to identify the fusion gain scaling at various operating conditions. The fusion based on the IDLC is a magneto-inertial fusion concept, where a Field-Reversed Configuration (FRC) plasmoid is compressed via the inductively-driven metal liner to drive the FRC to fusion conditions. In the past, an approximate scaling law for the expected fusion gain for the IDLC based fusion was obtained under the key assumptions of (1) D-T fuel at 5-40 keV, (2) adiabatic scaling laws for the FRC dynamics, (3) FRC energy dominated by the pressure balance with the edge magnetic field at the peak compression, and (4) the liner dwell time being liner final diameter divided by the peak liner velocity. In this study, various assumptions made in the previous derivation is relaxed to study the change in the fusion gain scaling from the previous result of G ml1 / 2 El11 / 8 , where ml is the liner mass and El is the peak liner kinetic energy. The implication from the modified fusion gain scaling on the performance of the IDLC fusion reactor system is also explored.
PV Array Driven Adjustable Speed Drive for a Lunar Base Heat Pump
NASA Technical Reports Server (NTRS)
Domijan, Alexander, Jr.; Buchh, Tariq Aslam
1995-01-01
A study of various aspects of Adjustable Speed Drives (ASD) is presented. A summary of the relative merits of different ASD systems presently in vogue is discussed. The advantages of using microcomputer based ASDs is now widely understood and accepted. Of the three most popular drive systems, namely the Induction Motor Drive, Switched Reluctance Motor Drive and Brushless DC Motor Drive, any one may be chosen. The choice would depend on the nature of the application and its requirements. The suitability of the above mentioned drive systems for a photovoltaic array driven ASD for an aerospace application are discussed. The discussion is based on the experience of the authors, various researchers and industry. In chapter 2 a PV array power supply scheme has been proposed, this scheme will have an enhanced reliability in addition to the other known advantages of the case where a stand alone PV array is feeding the heat pump. In chapter 3 the results of computer simulation of PV array driven induction motor drive system have been included. A discussion on these preliminary simulation results have also been included in this chapter. Chapter 4 includes a brief discussion on various control techniques for three phase induction motors. A discussion on different power devices and their various performance characteristics is given in Chapter 5.
NASA Astrophysics Data System (ADS)
Osgerby, S.; Loveday, M. S.
1992-06-01
A manual for the NPL Creep Laboratory, a collective name given to two testing laboratories, the Uniaxial Creep Laboratory and the Advanced High Temperature Mechanical Testing Laboratory, is presented. The first laboratory is devoted to uniaxial creep testing and houses approximately 50 high sensitivity creep machines including 10 constant stress cam lever machines. The second laboratory houses a low cycle fatigue testing machine of 100 kN capacity driven by a servo-electric actuator, five machines for uniaxial tensile creep testing of engineering ceramics at temperatures up to 1600C, and an electronic creep machine. Details of the operational procedures for carrying out uniaxial creep testing are given. Calibration procedures to be followed in order to comply with the specifications laid down by British standards, and to provide traceability back to the primary standards are described.
Axial magnetic field injection in magnetized liner inertial fusion
NASA Astrophysics Data System (ADS)
Gourdain, P.-A.; Adams, M. B.; Davies, J. R.; Seyler, C. E.
2017-10-01
MagLIF is a fusion concept using a Z-pinch implosion to reach thermonuclear fusion. In current experiments, the implosion is driven by the Z-machine using 19 MA of electrical current with a rise time of 100 ns. MagLIF requires an initial axial magnetic field of 30 T to reduce heat losses to the liner wall during compression and to confine alpha particles during fusion burn. This field is generated well before the current ramp starts and needs to penetrate the transmission lines of the pulsed-power generator, as well as the liner itself. Consequently, the axial field rise time must exceed hundreds of microseconds. Any coil capable of being submitted to such a field for that length of time is inevitably bulky. The space required to fit the coil near the liner, increases the inductance of the load. In turn, the total current delivered to the load decreases since the voltage is limited by driver design. Yet, the large amount of current provided by the Z-machine can be used to produce the required 30 T field by tilting the return current posts surrounding the liner, eliminating the need for a separate coil. However, the problem now is the field penetration time, across the liner wall. This paper discusses why skin effect arguments do not hold in the presence of resistivity gradients. Numerical simulations show that fields larger than 30 T can diffuse across the liner wall in less than 60 ns, demonstrating that external coils can be replaced by return current posts with optimal helicity.
Light-operated machines based on threaded molecular structures.
Credi, Alberto; Silvi, Serena; Venturi, Margherita
2014-01-01
Rotaxanes and related species represent the most common implementation of the concept of artificial molecular machines, because the supramolecular nature of the interactions between the components and their interlocked architecture allow a precise control on the position and movement of the molecular units. The use of light to power artificial molecular machines is particularly valuable because it can play the dual role of "writing" and "reading" the system. Moreover, light-driven machines can operate without accumulation of waste products, and photons are the ideal inputs to enable autonomous operation mechanisms. In appropriately designed molecular machines, light can be used to control not only the stability of the system, which affects the relative position of the molecular components but also the kinetics of the mechanical processes, thereby enabling control on the direction of the movements. This step forward is necessary in order to make a leap from molecular machines to molecular motors.
Designs and Plans for MAIZE: a 1 MA LTD-Driven Z-Pinch
NASA Astrophysics Data System (ADS)
Gilgenbach, R. M.; Gomez, M. R.; Zier, J.; Tang, W.; French, D. M.; Hoff, B. W.; Jordan, N.; Cruz, E.; Lau, Y. Y.; Fowler-Guzzardo, T.; Meisel, J.; Mazarakis, M. G.; Cuneo, M. E.; Johnston, M. D.; Mehlhorn, T. A.; Kim, A. A.; Sinebryukhov, V. A.
2007-11-01
We present designs and experimental plans of the first 1 MA z-pinch in the USA to be driven by a Linear Transformer Driver (LTD). The Michigan Accelerator for Inductive Z-pinch Experiments, (MAIZE), is based on the LTD developed at the Institute for High Current Electronics, utilizing 80 capacitors and 40 spark gap switches to deliver a 1 MA, 100 kV pulse with <100 ns risetime. Designs will be presented of a low-inductance MITL terminated in a wire-array z-pinch. Initial, planned experiments will evaluate the LTD driving time-changing inductance of imploding 4-16 wire-array z-pinches. Wire ablation dynamics, axial-correlations and instability development will be explored. *This work was supported by U. S. DoE through Sandia National Laboratories award number 240985 to the University of Michigan. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy's National Nuclear Security Administration under Contract DE-AC04-94AL85000.
Shchelokova, Alena V; van den Berg, Cornelis A T; Dobrykh, Dmitry A; Glybovski, Stanislav B; Zubkov, Mikhail A; Brui, Ekaterina A; Dmitriev, Dmitry S; Kozachenko, Alexander V; Efimtcev, Alexander Y; Sokolov, Andrey V; Fokin, Vladimir A; Melchakova, Irina V; Belov, Pavel A
2018-02-09
Design and characterization of a new inductively driven wireless coil (WLC) for wrist imaging at 1.5 T with high homogeneity operating due to focusing the B 1 field of a birdcage body coil. The WLC design has been proposed based on a volumetric self-resonant periodic structure of inductively coupled split-loop resonators with structural capacitance. The WLC was optimized and studied regarding radiofrequency fields and interaction to the birdcage coil (BC) by electromagnetic simulations. The manufactured WLC was characterized by on-bench measurements and in vivo and phantom study in comparison to a standard cable-connected receive-only coil. The WLC placed into BC gave the measured B1+ increase of the latter by 8.6 times for the same accepted power. The phantom and in vivo wrist imaging showed that the BC in receiving with the WLC inside reached equal or higher signal-to-noise ratio than the conventional clinical setup comprising the transmit-only BC and a commercial receive-only flex-coil and created no artifacts. Simulations and on-bench measurements proved safety in terms of specific absorption rate and reflected transmit power. The results showed that the proposed WLC could be an alternative to standard cable-connected receive coils in clinical magnetic resonance imaging. As an example, with no cable connection, the WLC allowed wrist imaging on a 1.5 T clinical machine using a full-body BC for transmitting and receive with the desired signal-to-noise ratio, image quality, and safety. © 2018 International Society for Magnetic Resonance in Medicine.
Quantum dynamics of light-driven chiral molecular motors.
Yamaki, Masahiro; Nakayama, Shin-ichiro; Hoki, Kunihito; Kono, Hirohiko; Fujimura, Yuichi
2009-03-21
The results of theoretical studies on quantum dynamics of light-driven molecular motors with internal rotation are presented. Characteristic features of chiral motors driven by a non-helical, linearly polarized electric field of light are explained on the basis of symmetry argument. The rotational potential of the chiral motor is characterized by a ratchet form. The asymmetric potential determines the directional motion: the rotational direction is toward the gentle slope of the asymmetric potential. This direction is called the intuitive direction. To confirm the unidirectional rotational motion, results of quantum dynamical calculations of randomly-oriented molecular motors are presented. A theoretical design of the smallest light-driven molecular machine is presented. The smallest chiral molecular machine has an optically driven engine and a running propeller on its body. The mechanisms of transmission of driving forces from the engine to the propeller are elucidated by using a quantum dynamical treatment. The results provide a principle for control of optically-driven molecular bevel gears. Temperature effects are discussed using the density operator formalism. An effective method for ultrafast control of rotational motions in any desired direction is presented with the help of a quantum control theory. In this method, visible or UV light pulses are applied to drive the motor via an electronic excited state. A method for driving a large molecular motor consisting of an aromatic hydrocarbon is presented. The molecular motor is operated by interactions between the induced dipole of the molecular motor and the electric field of light pulses.
As above, so below? Towards understanding inverse models in BCI
NASA Astrophysics Data System (ADS)
Lindgren, Jussi T.
2018-02-01
Objective. In brain-computer interfaces (BCI), measurements of the user’s brain activity are classified into commands for the computer. With EEG-based BCIs, the origins of the classified phenomena are often considered to be spatially localized in the cortical volume and mixed in the EEG. We investigate if more accurate BCIs can be obtained by reconstructing the source activities in the volume. Approach. We contrast the physiology-driven source reconstruction with data-driven representations obtained by statistical machine learning. We explain these approaches in a common linear dictionary framework and review the different ways to obtain the dictionary parameters. We consider the effect of source reconstruction on some major difficulties in BCI classification, namely information loss, feature selection and nonstationarity of the EEG. Main results. Our analysis suggests that the approaches differ mainly in their parameter estimation. Physiological source reconstruction may thus be expected to improve BCI accuracy if machine learning is not used or where it produces less optimal parameters. We argue that the considered difficulties of surface EEG classification can remain in the reconstructed volume and that data-driven techniques are still necessary. Finally, we provide some suggestions for comparing approaches. Significance. The present work illustrates the relationships between source reconstruction and machine learning-based approaches for EEG data representation. The provided analysis and discussion should help in understanding, applying, comparing and improving such techniques in the future.
Performance Analysis of Three-Phase Induction Motor with AC Direct and VFD
NASA Astrophysics Data System (ADS)
Kumar, Dinesh
2018-03-01
The electrical machine analysis and performance calculation is a very important aspect of efficient drive system design. The development of power electronics devices and power converters provide smooth speed control of Induction Motors by changing the frequency of input supply. These converters, on one hand are providing a more flexible speed control that also leads to problems of harmonics and their associated ailments like pulsating torque, distorted current and voltage waveforms, increasing losses etc. This paper includes the performance analysis of three phase induction motor with three-phase AC direct and variable frequency drives (VFD). The comparison has been concluded with respect to various parameters. MATLAB-SIMULINKTM is used for the analysis.
Two models for identification and predicting behaviour of an induction motor system
NASA Astrophysics Data System (ADS)
Kuo, Chien-Hsun
2018-01-01
System identification or modelling is the process of building mathematical models of dynamical systems based on the available input and output data from the systems. This paper introduces system identification by using ARX (Auto Regressive with eXogeneous input) and ARMAX (Auto Regressive Moving Average with eXogeneous input) models. Through the identified system model, the predicted output could be compared with the measured one to help prevent the motor faults from developing into a catastrophic machine failure and avoid unnecessary costs and delays caused by the need to carry out unscheduled repairs. The induction motor system is illustrated as an example. Numerical and experimental results are shown for the identified induction motor system.
Compact Superconducting Power Systems for Airborne Applications (Postprint)
2009-01-01
rotating machin- ery such as motors and alternators, is to maximize the magnet- ic flux density. This can be achieved by using a higher current...future systems could be driven to much higher power ratios, since the initial machine configuration was a homopolar inductor alternator‡ (HIA). A... Homopolar inductor alternator is an electrically symmetrical synchro- nous generator with a field winding that has a fixed magnetic position in relation to
Mujtaba, Ghulam; Shuib, Liyana; Raj, Ram Gopal; Rajandram, Retnagowri; Shaikh, Khairunisa; Al-Garadi, Mohammed Ali
2017-01-01
Widespread implementation of electronic databases has improved the accessibility of plaintext clinical information for supplementary use. Numerous machine learning techniques, such as supervised machine learning approaches or ontology-based approaches, have been employed to obtain useful information from plaintext clinical data. This study proposes an automatic multi-class classification system to predict accident-related causes of death from plaintext autopsy reports through expert-driven feature selection with supervised automatic text classification decision models. Accident-related autopsy reports were obtained from one of the largest hospital in Kuala Lumpur. These reports belong to nine different accident-related causes of death. Master feature vector was prepared by extracting features from the collected autopsy reports by using unigram with lexical categorization. This master feature vector was used to detect cause of death [according to internal classification of disease version 10 (ICD-10) classification system] through five automated feature selection schemes, proposed expert-driven approach, five subset sizes of features, and five machine learning classifiers. Model performance was evaluated using precisionM, recallM, F-measureM, accuracy, and area under ROC curve. Four baselines were used to compare the results with the proposed system. Random forest and J48 decision models parameterized using expert-driven feature selection yielded the highest evaluation measure approaching (85% to 90%) for most metrics by using a feature subset size of 30. The proposed system also showed approximately 14% to 16% improvement in the overall accuracy compared with the existing techniques and four baselines. The proposed system is feasible and practical to use for automatic classification of ICD-10-related cause of death from autopsy reports. The proposed system assists pathologists to accurately and rapidly determine underlying cause of death based on autopsy findings. Furthermore, the proposed expert-driven feature selection approach and the findings are generally applicable to other kinds of plaintext clinical reports.
Mujtaba, Ghulam; Shuib, Liyana; Raj, Ram Gopal; Rajandram, Retnagowri; Shaikh, Khairunisa; Al-Garadi, Mohammed Ali
2017-01-01
Objectives Widespread implementation of electronic databases has improved the accessibility of plaintext clinical information for supplementary use. Numerous machine learning techniques, such as supervised machine learning approaches or ontology-based approaches, have been employed to obtain useful information from plaintext clinical data. This study proposes an automatic multi-class classification system to predict accident-related causes of death from plaintext autopsy reports through expert-driven feature selection with supervised automatic text classification decision models. Methods Accident-related autopsy reports were obtained from one of the largest hospital in Kuala Lumpur. These reports belong to nine different accident-related causes of death. Master feature vector was prepared by extracting features from the collected autopsy reports by using unigram with lexical categorization. This master feature vector was used to detect cause of death [according to internal classification of disease version 10 (ICD-10) classification system] through five automated feature selection schemes, proposed expert-driven approach, five subset sizes of features, and five machine learning classifiers. Model performance was evaluated using precisionM, recallM, F-measureM, accuracy, and area under ROC curve. Four baselines were used to compare the results with the proposed system. Results Random forest and J48 decision models parameterized using expert-driven feature selection yielded the highest evaluation measure approaching (85% to 90%) for most metrics by using a feature subset size of 30. The proposed system also showed approximately 14% to 16% improvement in the overall accuracy compared with the existing techniques and four baselines. Conclusion The proposed system is feasible and practical to use for automatic classification of ICD-10-related cause of death from autopsy reports. The proposed system assists pathologists to accurately and rapidly determine underlying cause of death based on autopsy findings. Furthermore, the proposed expert-driven feature selection approach and the findings are generally applicable to other kinds of plaintext clinical reports. PMID:28166263
No Evidence That Gratitude Enhances Neural Performance Monitoring or Conflict-Driven Control
Saunders, Blair; He, Frank F. H.; Inzlicht, Michael
2015-01-01
It has recently been suggested that gratitude can benefit self-regulation by reducing impulsivity during economic decision making. We tested if comparable benefits of gratitude are observed for neural performance monitoring and conflict-driven self-control. In a pre-post design, 61 participants were randomly assigned to either a gratitude or happiness condition, and then performed a pre-induction flanker task. Subsequently, participants recalled an autobiographical event where they had felt grateful or happy, followed by a post-induction flanker task. Despite closely following existing protocols, participants in the gratitude condition did not report elevated gratefulness compared to the happy group. In regard to self-control, we found no association between gratitude—operationalized by experimental condition or as a continuous predictor—and any control metric, including flanker interference, post-error adjustments, or neural monitoring (the error-related negativity, ERN). Thus, while gratitude might increase economic patience, such benefits may not generalize to conflict-driven control processes. PMID:26633830
No Evidence That Gratitude Enhances Neural Performance Monitoring or Conflict-Driven Control.
Saunders, Blair; He, Frank F H; Inzlicht, Michael
2015-01-01
It has recently been suggested that gratitude can benefit self-regulation by reducing impulsivity during economic decision making. We tested if comparable benefits of gratitude are observed for neural performance monitoring and conflict-driven self-control. In a pre-post design, 61 participants were randomly assigned to either a gratitude or happiness condition, and then performed a pre-induction flanker task. Subsequently, participants recalled an autobiographical event where they had felt grateful or happy, followed by a post-induction flanker task. Despite closely following existing protocols, participants in the gratitude condition did not report elevated gratefulness compared to the happy group. In regard to self-control, we found no association between gratitude--operationalized by experimental condition or as a continuous predictor--and any control metric, including flanker interference, post-error adjustments, or neural monitoring (the error-related negativity, ERN). Thus, while gratitude might increase economic patience, such benefits may not generalize to conflict-driven control processes.
Design of control system for optical fiber drawing machine driven by double motor
NASA Astrophysics Data System (ADS)
Yu, Yue Chen; Bo, Yu Ming; Wang, Jun
2018-01-01
Micro channel Plate (MCP) is a kind of large-area array electron multiplier with high two-dimensional spatial resolution, used as high-performance night vision intensifier. The high precision control of the fiber is the key technology of the micro channel plate manufacturing process, and it was achieved by the control of optical fiber drawing machine driven by dual-motor in this paper. First of all, utilizing STM32 chip, the servo motor drive and control circuit was designed to realize the dual motor synchronization. Secondly, neural network PID control algorithm was designed for controlling the fiber diameter fabricated in high precision; Finally, the hexagonal fiber was manufactured by this system and it shows that multifilament diameter accuracy of the fiber is +/- 1.5μm.
Extreme learning machine for reduced order modeling of turbulent geophysical flows.
San, Omer; Maulik, Romit
2018-04-01
We investigate the application of artificial neural networks to stabilize proper orthogonal decomposition-based reduced order models for quasistationary geophysical turbulent flows. An extreme learning machine concept is introduced for computing an eddy-viscosity closure dynamically to incorporate the effects of the truncated modes. We consider a four-gyre wind-driven ocean circulation problem as our prototype setting to assess the performance of the proposed data-driven approach. Our framework provides a significant reduction in computational time and effectively retains the dynamics of the full-order model during the forward simulation period beyond the training data set. Furthermore, we show that the method is robust for larger choices of time steps and can be used as an efficient and reliable tool for long time integration of general circulation models.
Luebke, N H; Brantley, W A; Sabri, Z I; Luebke, F L; Lausten, L L
1995-05-01
A laboratory study was performed on machine-driven Canal Master drills to determine their physical dimensions, torsional performance, bending properties, and metallurgical characteristics in fracture. Physical dimensions were determined for each of the available sizes (#50 to #100) of Canal Master drills from the manufacturer that distributes these instruments in the United States. Samples were also tested in clockwise torsion using a Maillefer memocouple. Bending properties of cantilever specimens were measured with a Tinius Olsen stiffness tester. Bending fatigue testing was performed on a unique laboratory apparatus. Scanning electron microscope examination confirmed visual observations that the stainless steel Canal Master drills exhibited ductile torsional fracture. This study is part of a continuing investigation to establish standards for all machine-driven rotary endodontic instruments.
Machine learning based cloud mask algorithm driven by radiative transfer modeling
NASA Astrophysics Data System (ADS)
Chen, N.; Li, W.; Tanikawa, T.; Hori, M.; Shimada, R.; Stamnes, K. H.
2017-12-01
Cloud detection is a critically important first step required to derive many satellite data products. Traditional threshold based cloud mask algorithms require a complicated design process and fine tuning for each sensor, and have difficulty over snow/ice covered areas. With the advance of computational power and machine learning techniques, we have developed a new algorithm based on a neural network classifier driven by extensive radiative transfer modeling. Statistical validation results obtained by using collocated CALIOP and MODIS data show that its performance is consistent over different ecosystems and significantly better than the MODIS Cloud Mask (MOD35 C6) during the winter seasons over mid-latitude snow covered areas. Simulations using a reduced number of satellite channels also show satisfactory results, indicating its flexibility to be configured for different sensors.
Data-Driven Learning of Total and Local Energies in Elemental Boron
NASA Astrophysics Data System (ADS)
Deringer, Volker L.; Pickard, Chris J.; Csányi, Gábor
2018-04-01
The allotropes of boron continue to challenge structural elucidation and solid-state theory. Here we use machine learning combined with random structure searching (RSS) algorithms to systematically construct an interatomic potential for boron. Starting from ensembles of randomized atomic configurations, we use alternating single-point quantum-mechanical energy and force computations, Gaussian approximation potential (GAP) fitting, and GAP-driven RSS to iteratively generate a representation of the element's potential-energy surface. Beyond the total energies of the very different boron allotropes, our model readily provides atom-resolved, local energies and thus deepened insight into the frustrated β -rhombohedral boron structure. Our results open the door for the efficient and automated generation of GAPs, and other machine-learning-based interatomic potentials, and suggest their usefulness as a tool for materials discovery.
Extreme learning machine for reduced order modeling of turbulent geophysical flows
NASA Astrophysics Data System (ADS)
San, Omer; Maulik, Romit
2018-04-01
We investigate the application of artificial neural networks to stabilize proper orthogonal decomposition-based reduced order models for quasistationary geophysical turbulent flows. An extreme learning machine concept is introduced for computing an eddy-viscosity closure dynamically to incorporate the effects of the truncated modes. We consider a four-gyre wind-driven ocean circulation problem as our prototype setting to assess the performance of the proposed data-driven approach. Our framework provides a significant reduction in computational time and effectively retains the dynamics of the full-order model during the forward simulation period beyond the training data set. Furthermore, we show that the method is robust for larger choices of time steps and can be used as an efficient and reliable tool for long time integration of general circulation models.
Data-Driven Learning of Total and Local Energies in Elemental Boron.
Deringer, Volker L; Pickard, Chris J; Csányi, Gábor
2018-04-13
The allotropes of boron continue to challenge structural elucidation and solid-state theory. Here we use machine learning combined with random structure searching (RSS) algorithms to systematically construct an interatomic potential for boron. Starting from ensembles of randomized atomic configurations, we use alternating single-point quantum-mechanical energy and force computations, Gaussian approximation potential (GAP) fitting, and GAP-driven RSS to iteratively generate a representation of the element's potential-energy surface. Beyond the total energies of the very different boron allotropes, our model readily provides atom-resolved, local energies and thus deepened insight into the frustrated β-rhombohedral boron structure. Our results open the door for the efficient and automated generation of GAPs, and other machine-learning-based interatomic potentials, and suggest their usefulness as a tool for materials discovery.
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.
Field-circuit analysis and measurements of a single-phase self-excited induction generator
NASA Astrophysics Data System (ADS)
Makowski, Krzysztof; Leicht, Aleksander
2017-12-01
The paper deals with a single-phase induction machine operating as a stand-alone self-excited single-phase induction generator for generation of electrical energy from renewable energy sources. By changing number of turns and size of wires in the auxiliary stator winding, an improvement of performance characteristics of the generator were obtained as regards no-load and load voltage of the stator windings as well as stator winding currents of the generator. Field-circuit simulation models of the generator were developed using Flux2D software package for the generator with shunt capacitor in the main stator winding. The obtained results have been validated experimentally at the laboratory setup using the single-phase capacitor induction motor of 1.1 kW rated power and 230 V voltage as a base model of the generator.
ERIC Educational Resources Information Center
Grotzer, Tina A.; Tutwiler, M. Shane
2014-01-01
This article considers a set of well-researched default assumptions that people make in reasoning about complex causality and argues that, in part, they result from the forms of causal induction that we engage in and the type of information available in complex environments. It considers how information often falls outside our attentional frame…
Modeling Stochastic Kinetics of Molecular Machines at Multiple Levels: From Molecules to Modules
Chowdhury, Debashish
2013-01-01
A molecular machine is either a single macromolecule or a macromolecular complex. In spite of the striking superficial similarities between these natural nanomachines and their man-made macroscopic counterparts, there are crucial differences. Molecular machines in a living cell operate stochastically in an isothermal environment far from thermodynamic equilibrium. In this mini-review we present a catalog of the molecular machines and an inventory of the essential toolbox for theoretically modeling these machines. The tool kits include 1), nonequilibrium statistical-physics techniques for modeling machines and machine-driven processes; and 2), statistical-inference methods for reverse engineering a functional machine from the empirical data. The cell is often likened to a microfactory in which the machineries are organized in modular fashion; each module consists of strongly coupled multiple machines, but different modules interact weakly with each other. This microfactory has its own automated supply chain and delivery system. Buoyed by the success achieved in modeling individual molecular machines, we advocate integration of these models in the near future to develop models of functional modules. A system-level description of the cell from the perspective of molecular machinery (the mechanome) is likely to emerge from further integrations that we envisage here. PMID:23746505
Digital Suicide Prevention: Can Technology Become a Game-changer?
Vahabzadeh, Arshya; Sahin, Ned; Kalali, Amir
2016-01-01
Suicide continues to be a leading cause of death and has been recognized as a significant public health issue. Rapid advances in data science can provide us with useful tools for suicide prevention, and help to dynamically assess suicide risk in quantitative data-driven ways. In this article, the authors highlight the most current international research in digital suicide prevention, including the use of machine learning, smartphone applications, and wearable sensor driven systems. The authors also discuss future opportunities for digital suicide prevention, and propose a novel Sensor-driven Mental State Assessment System.
A computer architecture for intelligent machines
NASA Technical Reports Server (NTRS)
Lefebvre, D. R.; Saridis, G. N.
1992-01-01
The theory of intelligent machines proposes a hierarchical organization for the functions of an autonomous robot based on the principle of increasing precision with decreasing intelligence. An analytic formulation of this theory using information-theoretic measures of uncertainty for each level of the intelligent machine has been developed. The authors present a computer architecture that implements the lower two levels of the intelligent machine. The architecture supports an event-driven programming paradigm that is independent of the underlying computer architecture and operating system. Execution-level controllers for motion and vision systems are briefly addressed, as well as the Petri net transducer software used to implement coordination-level functions. A case study illustrates how this computer architecture integrates real-time and higher-level control of manipulator and vision systems.
Machine learning: Trends, perspectives, and prospects.
Jordan, M I; Mitchell, T M
2015-07-17
Machine learning addresses the question of how to build computers that improve automatically through experience. It is one of today's most rapidly growing technical fields, lying at the intersection of computer science and statistics, and at the core of artificial intelligence and data science. Recent progress in machine learning has been driven both by the development of new learning algorithms and theory and by the ongoing explosion in the availability of online data and low-cost computation. The adoption of data-intensive machine-learning methods can be found throughout science, technology and commerce, leading to more evidence-based decision-making across many walks of life, including health care, manufacturing, education, financial modeling, policing, and marketing. Copyright © 2015, American Association for the Advancement of Science.
Toward Usable Interactive Analytics: Coupling Cognition and Computation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Endert, Alexander; North, Chris; Chang, Remco
Interactive analytics provide users a myriad of computational means to aid in extracting meaningful information from large and complex datasets. Much prior work focuses either on advancing the capabilities of machine-centric approaches by the data mining and machine learning communities, or human-driven methods by the visualization and CHI communities. However, these methods do not yet support a true human-machine symbiotic relationship where users and machines work together collaboratively and adapt to each other to advance an interactive analytic process. In this paper we discuss some of the inherent issues, outlining what we believe are the steps toward usable interactive analyticsmore » that will ultimately increase the effectiveness for both humans and computers to produce insights.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tolbert, Leon M; Lee, Seong T
2010-01-01
This paper shows how to maximize the effect of the slanted air-gap structure of an interior permanent magnet synchronous motor with brushless field excitation (BFE) for application in a hybrid electric vehicle. The BFE structure offers high torque density at low speed and weakened flux at high speed. The unique slanted air-gap is intended to increase the output torque of the machine as well as to maximize the ratio of the back-emf of a machine that is controllable by BFE. This irregularly shaped air-gap makes a flux barrier along the d-axis flux path and decreases the d-axis inductance; as amore » result, the reluctance torque of the machine is much higher than a uniform air-gap machine, and so is the output torque. Also, the machine achieves a higher ratio of the magnitude of controllable back-emf. The determination of the slanted shape was performed by using magnetic equivalent circuit analysis and finite element analysis (FEA).« less
Comparison of Solid State Inverters for AC Induction Motor Traction Propulsion Systems
DOT National Transportation Integrated Search
1980-12-01
This report is one of a series concerned with the application of ac machines as traction motors for railroad motive power. It presents results of a laboratory evaluation and computer analysis of different inverter systems. Three inverter systems, sin...
NASA Astrophysics Data System (ADS)
Haram, M.; Wang, T.; Gu, F.; Ball, A. D.
2012-05-01
Motor current signal analysis has been an effective way for many years of monitoring electrical machines themselves. However, little work has been carried out in using this technique for monitoring their downstream equipment because of difficulties in extracting small fault components in the measured current signals. This paper investigates the characteristics of electrical current signals for monitoring the faults from a downstream gearbox using a modulation signal bispectrum (MSB), including phase effects in extracting small modulating components in a noisy measurement. An analytical study is firstly performed to understand amplitude, frequency and phase characteristics of current signals due to faults. It then explores the performance of MSB analysis in detecting weak modulating components in current signals. Experimental study based on a 10kw two stage gearbox, driven by a three phase induction motor, shows that MSB peaks at different rotational frequencies can be based to quantify the severity of gear tooth breakage and the degrees of shaft misalignment. In addition, the type and location of a fault can be recognized based on the frequency at which the change of MSB peak is the highest among different frequencies.
Active vibrations control of journal bearings with the use of piezoactuators
NASA Astrophysics Data System (ADS)
Tůma, Jiří; Šimek, Jiří; Škuta, Jaromír; Los, Jaroslav
2013-04-01
Rotor instability is one of the most serious problems of high-speed rotors supported by sliding bearings. With constantly increasing parameters, new machines problems with rotor instability are encountered more and more often. Even though there are many solutions based on passive improvement of the bearing geometry to enlarge the operational speed range of the journal bearing, the paper deals with a working prototype of a system for the active vibration control of journal bearings with the use of piezoactuators. The controllable journal bearing is a part of a test rig, which consists of a rotor driven by an inductive motor up to 23,000 rpm. The actively controlled journal bearing consists of a movable bushing, which is actuated by two piezoactuators. The journal vibration is measured by a pair of proximity probes. The control system enables run-up, coast-down and steady-state rotation. A real-time simulator dSpace encloses the control loop. Force produced by piezoactuators and acting at the bushing is controlled according to error signals derived from the proximity probe output signals. As it was proved by experiments the active vibration control extends considerably the range of the operational speed.
Comparaison de méthodes d'identification des paramètres d'une machine asynchrone
NASA Astrophysics Data System (ADS)
Bellaaj-Mrabet, N.; Jelassi, K.
1998-07-01
Interests, in Genetic Algorithms (G.A.) expands rapidly. This paper consists initially to apply G.A. for identifying induction motor parameters. Next, we compare the performances with classical methods like Maximum Likelihood and classical electrotechnical methods. These methods are applied on three induction motors of different powers to compare results following a set of criteria. Les algorithmes génétiques sont des méthodes adaptatives de plus en plus utilisée pour la résolution de certains problèmes d'optimisation. Le présent travail consiste d'une part, à mettre en œuvre un A.G sur des problèmes d'identification des machines électriques, et d'autre part à comparer ses performances avec les méthodes classiques tels que la méthode du maximum de vraisemblance et la méthode électrotechnique basée sur des essais à vides et en court-circuit. Ces méthodes sont appliquées sur des machines asynchrones de différentes puissances. Les résultats obtenus sont comparés selon certains critères, permettant de conclure sur la validité et la performance de chaque méthode.
1987-11-23
it have been possible, through reliance on millet plus rifles, to achieve victory over the better-armed Japanese militarists? Today, as we build...an exam- ple. If most products are made from spinning machines and only a few are produced by hand-driven spinning machines, the former is made...twisting. The way she referred to "madam" when reporting to Sister Feng caused much confusion to You, a married woman . However, it happened that
Faraday's first dynamo: A retrospective
NASA Astrophysics Data System (ADS)
Smith, Glenn S.
2013-12-01
In the early 1830s, Michael Faraday performed his seminal experimental research on electromagnetic induction, in which he created the first electric dynamo—a machine for continuously converting rotational mechanical energy into electrical energy. His machine was a conducting disc, rotating between the poles of a permanent magnet, with the voltage/current obtained from brushes contacting the disc. In his first dynamo, the magnetic field was asymmetric with respect to the axis of the disc. This is to be contrasted with some of his later symmetric designs, which are the ones almost invariably discussed in textbooks on electromagnetism. In this paper, a theoretical analysis is developed for Faraday's first dynamo. From this analysis, the eddy currents in the disc and the open-circuit voltage for arbitrary positioning of the brushes are determined. The approximate analysis is verified by comparing theoretical results with measurements made on an experimental recreation of the dynamo. Quantitative results from the analysis are used to elucidate Faraday's qualitative observations, from which he learned so much about electromagnetic induction. For the asymmetric design, the eddy currents in the disc dissipate energy that makes the dynamo inefficient, prohibiting its use as a practical generator of electric power. Faraday's experiments with his first dynamo provided valuable insight into electromagnetic induction, and this insight was quickly used by others to design practical generators.
Superconducting-electromagnetic hybrid bearing using YBCO bulk blocks for passive axial levitation
NASA Astrophysics Data System (ADS)
Nicolsky, R.; de Andrade, R., Jr.; Ripper, A.; David, D. F. B.; Santisteban, J. A.; Stephan, R. M.; Gawalek, W.; Habisreuther, T.; Strasser, T.
2000-06-01
A superconducting/electromagnetic hybrid bearing has been designed using active radial electromagnetic positioning and a superconducting passive axial levitator. This bearing has been tested for an induction machine with a vertical shaft. The prototype was conceived as a four-pole, two-phase induction machine using specially designed stator windings for delivering torque and radial positioning simultaneously. The radial bearing uses four eddy-current sensors, displaced 90° from each other, for measuring the shaft position and a PID control system for feeding back the currents. The stator windings have been adapted from the ones of a standard induction motor. The superconducting axial bearing has been assembled with commercial NdFeB permanent magnets and a set of seven top-seeded-melt-textured YBCO large-grain cylindrical blocks. The bearing set-up was previously simulated by a finite element method for different permanent magnet-superconductor block configurations. The stiffness of the superconducting axial bearing has been investigated by measuring by a dynamic method the vertical and transversal elastic constants for different field cooling processes. The resulting elastic constants show a linear dependence on the air gap, i.e. the clearance between the permanent magnet assembly and the set of superconducting large-grain blocks, which is dependent on cooling distance.
State reference design and saturated control of doubly-fed induction generators under voltage dips
NASA Astrophysics Data System (ADS)
Tilli, Andrea; Conficoni, Christian; Hashemi, Ahmad
2017-04-01
In this paper, the stator/rotor currents control problem of doubly-fed induction generator under faulty line voltage is carried out. Common grid faults cause a steep decline in the line voltage profile, commonly denoted as voltage dip. This point is critical for such kind of machines, having their stator windings directly connected to the grid. In this respect, solid methodological nonlinear control theory arguments are exploited and applied to design a novel controller, whose main goal is to improve the system behaviour during voltage dips, endowing it with low voltage ride through capability, a fundamental feature required by modern Grid Codes. The proposed solution exploits both feedforward and feedback actions. The feedforward part relies on suitable reference trajectories for the system internal dynamics, which are designed to prevent large oscillations in the rotor currents and command voltages, excited by line perturbations. The feedback part uses state measurements and is designed according to Linear Matrix Inequalities (LMI) based saturated control techniques to further reduce oscillations, while explicitly accounting for the system constraints. Numerical simulations verify the benefits of the internal dynamics trajectory planning, and the saturated state feedback action, in crucially improving the Doubly-Fed Induction Machine response under severe grid faults.
Correlation of Noise Signature to Pulsed Power Events at the HERMES III Accelerator.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lewis, Barbara; Joseph, Nathan Ryan; Salazar, Juan Diego
2016-11-01
The HERMES III accelerator, which is located at Sandia National Laboratories' Tech Area IV, is the largest pulsed gamma X-ray source in the world. The accelerator is made up of 20 inductive cavities that are charged to 1 MV each by complex pulsed power circuitry. The firing time of the machine components ranges between the microsecond and nanosecond timescales. This results in a variety of electromagnetic frequencies when the accelerator fires. Testing was done to identify the HERMES electromagnetic noise signal and to map it to the various accelerator trigger events. This report will show the measurement methods used tomore » capture the noise spectrum produced from the machine and correlate this noise signature with machine events.« less
PWM Inverter control and the application thereof within electric vehicles
Geppert, Steven
1982-01-01
An inverter (34) which provides power to an A.C. machine (28) is controlled by a circuit (36) employing PWM control strategy whereby A.C. power is supplied to the machine at a preselectable frequency and preselectable voltage. This is accomplished by the technique of waveform notching in which the shapes of the notches are varied to determine the average energy content of the overall waveform. Through this arrangement, the operational efficiency of the A.C. machine is optimized. The control circuit includes a micro-computer and memory element which receive various parametric inputs and calculate optimized machine control data signals therefrom. The control data is asynchronously loaded into the inverter through an intermediate buffer (38). In its preferred embodiment, the present invention is incorporated within an electric vehicle (10) employing a 144 VDC battery pack (32) and a three-phase induction motor (18).
EV drivetrain inverter with V/HZ optimization
Gritter, David J.; O'Neil, Walter K.
1986-01-01
An inverter (34) which provides power to an A.C. machine (28) is controlled by a circuit (36) employing PWM control strategy whereby A.C. power is supplied to the machine at a preselectable frequency and preselectable voltage. This is accomplished by the technique of waveform notching in which the shapes of the notches are varied to determine the average energy content of the overall waveform. Through this arrangement, the operational efficiency of the A.C. machine is optimized. The control circuit includes a micro-computer which calculates optimized machine control data signals from various parametric inputs and during steady state load conditions, seeks a best V/HZ ratio to minimize battery current drawn (system losses) from a D.C. power source (32). In the preferred embodiment, the present invention is incorporated within an electric vehicle (10) employing a 144 VDC battery pack and a three-phase induction motor (18).
NASA Astrophysics Data System (ADS)
Ramachandran, R.; Nair, U. S.; Word, A.
2014-12-01
Threshold concepts in any discipline are the core concepts an individual must understand in order to master a discipline. By their very nature, these concepts are troublesome, irreversible, integrative, bounded, discursive, and reconstitutive. Although grasping threshold concepts can be extremely challenging for each learner as s/he moves through stages of cognitive development relative to a given discipline, the learner's grasp of these concepts determines the extent to which s/he is prepared to work competently and creatively within the field itself. The movement of individuals from a state of ignorance of these core concepts to one of mastery occurs not along a linear path but in iterative cycles of knowledge creation and adjustment in liminal spaces - conceptual spaces through which learners move from the vaguest awareness of concepts to mastery, accompanied by understanding of their relevance, connectivity, and usefulness relative to questions and constructs in a given discipline. With the explosive growth of data available in atmospheric science, driven largely by satellite Earth observations and high-resolution numerical simulations, paradigms such as that of data-intensive science have emerged. These paradigm shifts are based on the growing realization that current infrastructure, tools and processes will not allow us to analyze and fully utilize the complex and voluminous data that is being gathered. In this emerging paradigm, the scientific discovery process is driven by knowledge extracted from large volumes of data. In this presentation, we contend that this paradigm naturally lends to inquiry-driven pedagogy where knowledge is discovered through inductive engagement with large volumes of data rather than reached through traditional, deductive, hypothesis-driven analyses. In particular, data-intensive techniques married with an inductive methodology allow for exploration on a scale that is not possible in the traditional classroom with its typical problem sets and static, limited data samples. In addition, we identify existing gaps and possible solutions for addressing the infrastructure and tools as well as a pedagogical framework through which to implement this inductive approach.
30 CFR 18.8 - Date for conducting investigation and tests.
Code of Federal Regulations, 2010 CFR
2010-07-01
..., EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES General... determine the order of precedence for investigation and testing. If an electrical machine component or...
NASA Astrophysics Data System (ADS)
Bernardet, Ulysses; Bermúdez I Badia, Sergi; Duff, Armin; Inderbitzin, Martin; Le Groux, Sylvain; Manzolli, Jônatas; Mathews, Zenon; Mura, Anna; Väljamäe, Aleksander; Verschure, Paul F. M. J.
The eXperience Induction Machine (XIM) is one of the most advanced mixed-reality spaces available today. XIM is an immersive space that consists of physical sensors and effectors and which is conceptualized as a general-purpose infrastructure for research in the field of psychology and human-artifact interaction. In this chapter, we set out the epistemological rational behind XIM by putting the installation in the context of psychological research. The design and implementation of XIM are based on principles and technologies of neuromorphic control. We give a detailed description of the hardware infrastructure and software architecture, including the logic of the overall behavioral control. To illustrate the approach toward psychological experimentation, we discuss a number of practical applications of XIM. These include the so-called, persistent virtual community, the application in the research of the relationship between human experience and multi-modal stimulation, and an investigation of a mixed-reality social interaction paradigm.
NASA Astrophysics Data System (ADS)
Yamamoto, Shu; Ara, Takahiro
Recently, induction motors (IMs) and permanent-magnet synchronous motors (PMSMs) have been used in various industrial drive systems. The features of the hardware device used for controlling the adjustable-speed drive in these motors are almost identical. Despite this, different techniques are generally used for parameter measurement and speed-sensorless control of these motors. If the same technique can be used for parameter measurement and sensorless control, a highly versatile adjustable-speed-drive system can be realized. In this paper, the authors describe a new universal sensorless control technique for both IMs and PMSMs (including salient pole and nonsalient pole machines). A mathematical model applicable for IMs and PMSMs is discussed. Using this model, the authors derive the proposed universal sensorless vector control algorithm on the basis of estimation of the stator flux linkage vector. All the electrical motor parameters are determined by a unified test procedure. The proposed method is implemented on three test machines. The actual driving test results demonstrate the validity of the proposed method.
Predicting the dissolution kinetics of silicate glasses using machine learning
NASA Astrophysics Data System (ADS)
Anoop Krishnan, N. M.; Mangalathu, Sujith; Smedskjaer, Morten M.; Tandia, Adama; Burton, Henry; Bauchy, Mathieu
2018-05-01
Predicting the dissolution rates of silicate glasses in aqueous conditions is a complex task as the underlying mechanism(s) remain poorly understood and the dissolution kinetics can depend on a large number of intrinsic and extrinsic factors. Here, we assess the potential of data-driven models based on machine learning to predict the dissolution rates of various aluminosilicate glasses exposed to a wide range of solution pH values, from acidic to caustic conditions. Four classes of machine learning methods are investigated, namely, linear regression, support vector machine regression, random forest, and artificial neural network. We observe that, although linear methods all fail to describe the dissolution kinetics, the artificial neural network approach offers excellent predictions, thanks to its inherent ability to handle non-linear data. Overall, we suggest that a more extensive use of machine learning approaches could significantly accelerate the design of novel glasses with tailored properties.
Analysis of laser-induction hybrid cladding processing conditions
NASA Astrophysics Data System (ADS)
Huang, Yongjun; Zeng, Xiaoyan; Hu, Qianwu
2007-12-01
A new cladding approach based on laser-induction hybrid technique on flat sheets is presented in this paper. Coating is produced by means of 5kw cw CO II laser equipped with 100kw high frequent inductor, and the experiments set-up, involving a special machining-head, which can provide laser-induction hybrid heat resources simultaneously. The formation of thick NiCrSiB coating on a steel substrate by off-axial powder feeding is studied from an experimental point of view. A substrate melting energy model is developed to describe the energy relationship between laser-induction hybrid cladding and laser cladding alone quantitatively. By comparing the experimental results with the calculational ones, it is shown that the tendency of fusion zone height of theoretical calculation is in agreement with that of tests in laser-induction hybrid cladding. Via analyses and tests, the conclusions can be lead to that the fusion zone height can be increased easily and the good bond of cladding track can be achieved within wide cladding processing window in laser-induction hybrid processing. It shows that the induction heating has an obvious effect on substrate melting and metallurgical bond.
Bending Distortion Analysis of a Steel Shaft Manufacturing Chain from Cold Drawing to Grinding
NASA Astrophysics Data System (ADS)
Dias, Vinicius Waechter; da Silva Rocha, Alexandre; Zottis, Juliana; Dong, Juan; Epp, Jérémy; Zoch, Hans Werner
2017-04-01
Shafts are usually manufactured from bars that are cold drawn, cut machined, induction hardened, straightened, and finally ground. The main distortion is characterized by bending that appears after induction hardening and is corrected by straightening and/or grinding. In this work, the consequence of the variation of manufacturing parameters on the distortion was analyzed for a complete manufacturing route for production of induction hardened shafts made of Grade 1045 steel. A DoE plan was implemented varying the drawing angle, cutting method, induction hardening layer depth, and grinding penetration depth. The distortion was determined by calculating curvature vectors from dimensional analysis by 3D coordinate measurements. Optical microscopy, microhardness testing, residual stress analysis, and FEM process simulation were used to evaluate and understand effects of the main carriers of distortion potential. The drawing process was identified as the most significant influence on the final distortion of the shafts.
Code of Federal Regulations, 2010 CFR
2010-07-01
... as butcher shops, grocery stores, restaurants/fast-food establishments, hotels, delicatessens, and... stores, restaurants and quick service food establishments, hotels, delicatessens, and meat locker...
30 CFR 18.10 - Notice of approval or disapproval.
Code of Federal Regulations, 2010 CFR
2010-07-01
..., EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES General... assembly of an electrical machine or accessory, MSHA will issue to the applicant either a written notice of...
Applications of Support Vector Machines In Chemo And Bioinformatics
NASA Astrophysics Data System (ADS)
Jayaraman, V. K.; Sundararajan, V.
2010-10-01
Conventional linear & nonlinear tools for classification, regression & data driven modeling are being replaced on a rapid scale by newer techniques & tools based on artificial intelligence and machine learning. While the linear techniques are not applicable for inherently nonlinear problems, newer methods serve as attractive alternatives for solving real life problems. Support Vector Machine (SVM) classifiers are a set of universal feed-forward network based classification algorithms that have been formulated from statistical learning theory and structural risk minimization principle. SVM regression closely follows the classification methodology. In this work recent applications of SVM in Chemo & Bioinformatics will be described with suitable illustrative examples.
Fabric circuits and method of manufacturing fabric circuits
NASA Technical Reports Server (NTRS)
Chu, Andrew W. (Inventor); Dobbins, Justin A. (Inventor); Scully, Robert C. (Inventor); Trevino, Robert C. (Inventor); Lin, Greg Y. (Inventor); Fink, Patrick W. (Inventor)
2011-01-01
A flexible, fabric-based circuit comprises a non-conductive flexible layer of fabric and a conductive flexible layer of fabric adjacent thereto. A non-conductive thread, an adhesive, and/or other means may be used for attaching the conductive layer to the non-conductive layer. In some embodiments, the layers are attached by a computer-driven embroidery machine at pre-determined portions or locations in accordance with a pre-determined attachment layout before automated cutting. In some other embodiments, an automated milling machine or a computer-driven laser using a pre-designed circuit trace as a template cuts the conductive layer so as to separate an undesired portion of the conductive layer from a desired portion of the conductive layer. Additional layers of conductive fabric may be attached in some embodiments to form a multi-layer construct.
ERIC Educational Resources Information Center
Griffiths, Thomas L.; Tenenbaum, Joshua B.
2009-01-01
Inducing causal relationships from observations is a classic problem in scientific inference, statistics, and machine learning. It is also a central part of human learning, and a task that people perform remarkably well given its notorious difficulties. People can learn causal structure in various settings, from diverse forms of data: observations…
Probabilistic and machine learning-based retrieval approaches for biomedical dataset retrieval
Karisani, Payam; Qin, Zhaohui S; Agichtein, Eugene
2018-01-01
Abstract The bioCADDIE dataset retrieval challenge brought together different approaches to retrieval of biomedical datasets relevant to a user’s query, expressed as a text description of a needed dataset. We describe experiments in applying a data-driven, machine learning-based approach to biomedical dataset retrieval as part of this challenge. We report on a series of experiments carried out to evaluate the performance of both probabilistic and machine learning-driven techniques from information retrieval, as applied to this challenge. Our experiments with probabilistic information retrieval methods, such as query term weight optimization, automatic query expansion and simulated user relevance feedback, demonstrate that automatically boosting the weights of important keywords in a verbose query is more effective than other methods. We also show that although there is a rich space of potential representations and features available in this domain, machine learning-based re-ranking models are not able to improve on probabilistic information retrieval techniques with the currently available training data. The models and algorithms presented in this paper can serve as a viable implementation of a search engine to provide access to biomedical datasets. The retrieval performance is expected to be further improved by using additional training data that is created by expert annotation, or gathered through usage logs, clicks and other processes during natural operation of the system. Database URL: https://github.com/emory-irlab/biocaddie PMID:29688379
On the Conditioning of Machine-Learning-Assisted Turbulence Modeling
NASA Astrophysics Data System (ADS)
Wu, Jinlong; Sun, Rui; Wang, Qiqi; Xiao, Heng
2017-11-01
Recently, several researchers have demonstrated that machine learning techniques can be used to improve the RANS modeled Reynolds stress by training on available database of high fidelity simulations. However, obtaining improved mean velocity field remains an unsolved challenge, restricting the predictive capability of current machine-learning-assisted turbulence modeling approaches. In this work we define a condition number to evaluate the model conditioning of data-driven turbulence modeling approaches, and propose a stability-oriented machine learning framework to model Reynolds stress. Two canonical flows, the flow in a square duct and the flow over periodic hills, are investigated to demonstrate the predictive capability of the proposed framework. The satisfactory prediction performance of mean velocity field for both flows demonstrates the predictive capability of the proposed framework for machine-learning-assisted turbulence modeling. With showing the capability of improving the prediction of mean flow field, the proposed stability-oriented machine learning framework bridges the gap between the existing machine-learning-assisted turbulence modeling approaches and the demand of predictive capability of turbulence models in real applications.
NASA Astrophysics Data System (ADS)
Mølgaard, Lasse L.; Buus, Ole T.; Larsen, Jan; Babamoradi, Hamid; Thygesen, Ida L.; Laustsen, Milan; Munk, Jens Kristian; Dossi, Eleftheria; O'Keeffe, Caroline; Lässig, Lina; Tatlow, Sol; Sandström, Lars; Jakobsen, Mogens H.
2017-05-01
We present a data-driven machine learning approach to detect drug- and explosives-precursors using colorimetric sensor technology for air-sampling. The sensing technology has been developed in the context of the CRIM-TRACK project. At present a fully- integrated portable prototype for air sampling with disposable sensing chips and automated data acquisition has been developed. The prototype allows for fast, user-friendly sampling, which has made it possible to produce large datasets of colorimetric data for different target analytes in laboratory and simulated real-world application scenarios. To make use of the highly multi-variate data produced from the colorimetric chip a number of machine learning techniques are employed to provide reliable classification of target analytes from confounders found in the air streams. We demonstrate that a data-driven machine learning method using dimensionality reduction in combination with a probabilistic classifier makes it possible to produce informative features and a high detection rate of analytes. Furthermore, the probabilistic machine learning approach provides a means of automatically identifying unreliable measurements that could produce false predictions. The robustness of the colorimetric sensor has been evaluated in a series of experiments focusing on the amphetamine pre-cursor phenylacetone as well as the improvised explosives pre-cursor hydrogen peroxide. The analysis demonstrates that the system is able to detect analytes in clean air and mixed with substances that occur naturally in real-world sampling scenarios. The technology under development in CRIM-TRACK has the potential as an effective tool to control trafficking of illegal drugs, explosive detection, or in other law enforcement applications.
Modeling stochastic kinetics of molecular machines at multiple levels: from molecules to modules.
Chowdhury, Debashish
2013-06-04
A molecular machine is either a single macromolecule or a macromolecular complex. In spite of the striking superficial similarities between these natural nanomachines and their man-made macroscopic counterparts, there are crucial differences. Molecular machines in a living cell operate stochastically in an isothermal environment far from thermodynamic equilibrium. In this mini-review we present a catalog of the molecular machines and an inventory of the essential toolbox for theoretically modeling these machines. The tool kits include 1), nonequilibrium statistical-physics techniques for modeling machines and machine-driven processes; and 2), statistical-inference methods for reverse engineering a functional machine from the empirical data. The cell is often likened to a microfactory in which the machineries are organized in modular fashion; each module consists of strongly coupled multiple machines, but different modules interact weakly with each other. This microfactory has its own automated supply chain and delivery system. Buoyed by the success achieved in modeling individual molecular machines, we advocate integration of these models in the near future to develop models of functional modules. A system-level description of the cell from the perspective of molecular machinery (the mechanome) is likely to emerge from further integrations that we envisage here. Copyright © 2013 Biophysical Society. Published by Elsevier Inc. All rights reserved.
Digital Suicide Prevention: Can Technology Become a Game-changer?
Sahin, Ned; Kalali, Amir
2016-01-01
Suicide continues to be a leading cause of death and has been recognized as a significant public health issue. Rapid advances in data science can provide us with useful tools for suicide prevention, and help to dynamically assess suicide risk in quantitative data-driven ways. In this article, the authors highlight the most current international research in digital suicide prevention, including the use of machine learning, smartphone applications, and wearable sensor driven systems. The authors also discuss future opportunities for digital suicide prevention, and propose a novel Sensor-driven Mental State Assessment System. PMID:27800282
Characterizing the plasma of the Rotating Wall Machine
NASA Astrophysics Data System (ADS)
Hannum, David A.
The Rotating Wall Machine (RoWM) is a line-tied linear screw pinch built to study current-driven external kink modes. The plasma column is formed by an array of seven electrostatic washer guns which can also be biased to drive plasma current. The array allows independent control over the electron density ne and current density Jz profiles of the column. Internal measurements of the plasma have been made with singletip Langmuir and magnetic induction ("B-dot") probes for a range of bias currents (Ib = 0, 300, 500 A/gun). Streams from the individual guns are seen to merge at a distance of z ≈ 36 cm from the guns; the exact distance depends on the value of Ib. The density of the column is directly proportional to the Ohmic dissipation power, but the temperature stays at a low, uniform value (Te ≈ 3.5 eV) for each bias level. Electron densities are on the order of ne ˜10 20 m-3. The electron density expands radially (across the Bz guide field) as the plasma moves along the column, though the current density Jz mainly stays parallel to the field lines. The singletip Langmuir probe diagnostic is difficult to analyze for Ib = 500 A/gun plasmas and fails as Ib is raised beyond this level. Spectrographic analysis of the Halpha line indicates that the hydrogen plasmas are nearly fully ionized at each bias level. Azimuthal E x B rotation is axially and radially sheared; rotation slows as the plasma reaches the anode. Perpendicular diffusivity is consistent with the classical value, D⊥ ≈ 5 m2/sec, while parallel resistivity is seen to be twice the classical Spitzer value, 2 x 10-4 O m.
In-duct identification of fluid-borne source with high spatial resolution
NASA Astrophysics Data System (ADS)
Heo, Yong-Ho; Ih, Jeong-Guon; Bodén, Hans
2014-11-01
Source identification of acoustic characteristics of in-duct fluid machinery is required for coping with the fluid-borne noise. By knowing the acoustic pressure and particle velocity field at the source plane in detail, the sound generation mechanism of a fluid machine can be understood. The identified spatial distribution of the strength of major radiators would be useful for the low noise design. Conventional methods for measuring the source in a wide duct have not been very helpful in investigating the source properties in detail because their spatial resolution is improper for the design purpose. In this work, an inverse method to estimate the source parameters with a high spatial resolution is studied. The theoretical formulation including the evanescent modes and near-field measurement data is given for a wide duct. After validating the proposed method to a duct excited by an acoustic driver, an experiment on a duct system driven by an air blower is conducted in the presence of flow. A convergence test for the evanescent modes is performed to find the necessary number of modes to regenerate the measured pressure field precisely. By using the converged modal amplitudes, very-close near-field pressure to the source is regenerated and compared with the measured pressure, and the maximum error was -16.3 dB. The source parameters are restored from the converged modal amplitudes. Then, the distribution of source parameters on the driver and the blower is clearly revealed with a high spatial resolution for kR<1.84 in which range only plane waves can propagate to far field in a duct. Measurement using a flush mounted sensor array is discussed, and the removal of pure radial modes in the modeling is suggested.
Composite synchronization of three eccentric rotors driven by induction motors in a vibrating system
NASA Astrophysics Data System (ADS)
Kong, Xiangxi; Chen, Changzheng; Wen, Bangchun
2018-03-01
This paper addresses the problem of composite synchronization of three eccentric rotors (ERs) driven by induction motors in a vibrating system. The composite synchronous motion of three ERs is composed of the controlled synchronous motion of two ERs and the self-synchronous motion of the third ER. Combining an adaptive sliding mode control (ASMC) algorithm with a modified master-slave control structure, the controllers are designed to implement controlled synchronous motion of two ERs with zero phase difference. Based on Lyapunov stability theorem and Barbalat's lemma, the stability of the designed controllers is verified. On basis of controlled synchronization of two ERs, self-synchronization of the third ER is introduced to implement composite synchronous motion of three ERs. The feasibility of the proposed composite synchronization method is analyzed by numerical method. The effects of motor and structure parameters on composite synchronous motion are discussed. Experiments on a vibrating test bench driven by three ERs are operated to validate the effectiveness of the proposed composite synchronization method, including a comparison with self-synchronization method.
Diagnosis of the three-phase induction motor using thermal imaging
NASA Astrophysics Data System (ADS)
Glowacz, Adam; Glowacz, Zygfryd
2017-03-01
Three-phase induction motors are used in the industry commonly for example woodworking machines, blowers, pumps, conveyors, elevators, compressors, mining industry, automotive industry, chemical industry and railway applications. Diagnosis of faults is essential for proper maintenance. Faults may damage a motor and damaged motors generate economic losses caused by breakdowns in production lines. In this paper the authors develop fault diagnostic techniques of the three-phase induction motor. The described techniques are based on the analysis of thermal images of three-phase induction motor. The authors analyse thermal images of 3 states of the three-phase induction motor: healthy three-phase induction motor, three-phase induction motor with 2 broken bars, three-phase induction motor with faulty ring of squirrel-cage. In this paper the authors develop an original method of the feature extraction of thermal images MoASoID (Method of Areas Selection of Image Differences). This method compares many training sets together and it selects the areas with the biggest changes for the recognition process. Feature vectors are obtained with the use of mentioned MoASoID and image histogram. Next 3 methods of classification are used: NN (the Nearest Neighbour classifier), K-means, BNN (the back-propagation neural network). The described fault diagnostic techniques are useful for protection of three-phase induction motor and other types of rotating electrical motors such as: DC motors, generators, synchronous motors.
FUZZY LOGIC BASED INTELLIGENT CONTROL OF A VARIABLE SPEED CAGE MACHINE WIND GENERATION SYSTEM
The paper describes a variable-speed wind generation system where fuzzy logic principles are used to optimize efficiency and enhance performance control. A squirrel cage induction generator feeds the power to a double-sided pulse width modulated converter system which either pump...
FUZZY LOGIC BASED INTELLIGENT CONTROL OF A VARIABLE SPEED CAGE MACHINE WIND GENERATION SYSTEM
The report gives results of a demonstration of the successful application of fuzzy logic to enhance the performance and control of a variable-speed wind generation system. A squirrel cage induction generator feeds the power to either a double-sided pulse-width modulation converte...
Incremental Inductive Learning in a Constructivist Agent
NASA Astrophysics Data System (ADS)
Perotto, Filipo Studzinski; Älvares, Luís Otávio
The constructivist paradigm in Artificial Intelligence has been definitively inaugurated in the earlier 1990's by Drescher's pioneer work [10]. He faces the challenge of design an alternative model for machine learning, founded in the human cognitive developmental process described by Piaget [x]. His effort has inspired many other researchers.
Methods of Cost Reduction for United States Coast Guard Telephone Systems.
1981-03-01
System (’FTS) for a single low utilization command is questionable. Small FAX machines such as EXXON’s QWIP /FAX can be purchased at approxi- mately...unsatisfactory operating condi- tion. Electrical faults, such as leakage or poor insulation, noise induction, crosstalk, or poor transmission
2009-04-22
bandwidth and response times. Forrester Research uses the analogy of a consumer using an automated teller machine to explain how technical SLAs should...be crafted. “It’s not enough that you put your card and Personal Identification Number (PIN) [in the machine ] and request to withdraw cash...IRR) Net Present Value (NPV) Other Relevant Metrics Payback Period Cost/Benefit Ratio Cost, Economic, and/or Financial Analysis Yes Yes Yes
Experiments in Schema-Driven Interpretation of a Natural Scene
1980-04-01
Intilliaence, "rbilisi, USSR; 1975, pp. 483-490. EFEL743 JzA. Feldman and Y. Yakimovsky, "Deciesion Theorg and Artificiel Int lligence:, I. A Semantics-Based...lTra. ttern i a Machine Intelligence , Vol. PAMI-., Janua’ry 1980 p’p. 16-27. CRIS743 E.M. Riseman and A.R. Hanson, "I)eign o’f a Semanticall...Machine Intelligence , School of Artificial Intelligence , University of Edinburgh, 1974. tUHR723 L. Uhr, "Layered ’Recognition Cone’ Networks That
The effect of sample size and disease prevalence on supervised machine learning of narrative data.
McKnight, Lawrence K.; Wilcox, Adam; Hripcsak, George
2002-01-01
This paper examines the independent effects of outcome prevalence and training sample sizes on inductive learning performance. We trained 3 inductive learning algorithms (MC4, IB, and Naïve-Bayes) on 60 simulated datasets of parsed radiology text reports labeled with 6 disease states. Data sets were constructed to define positive outcome states at 4 prevalence rates (1, 5, 10, 25, and 50%) in training set sizes of 200 and 2,000 cases. We found that the effect of outcome prevalence is significant when outcome classes drop below 10% of cases. The effect appeared independent of sample size, induction algorithm used, or class label. Work is needed to identify methods of improving classifier performance when output classes are rare. PMID:12463878
Automatic inference of multicellular regulatory networks using informative priors.
Sun, Xiaoyun; Hong, Pengyu
2009-01-01
To fully understand the mechanisms governing animal development, computational models and algorithms are needed to enable quantitative studies of the underlying regulatory networks. We developed a mathematical model based on dynamic Bayesian networks to model multicellular regulatory networks that govern cell differentiation processes. A machine-learning method was developed to automatically infer such a model from heterogeneous data. We show that the model inference procedure can be greatly improved by incorporating interaction data across species. The proposed approach was applied to C. elegans vulval induction to reconstruct a model capable of simulating C. elegans vulval induction under 73 different genetic conditions.
Electric motor-transformer aggregate in hermetic objects of transport vehicles
NASA Astrophysics Data System (ADS)
Zabora, Igor
2017-10-01
The construction and features of operation for new electrical unit - electric motor-transformer aggregate (DTA) are considered. Induction motors are intended for operation in hermetic plants with extreme conditions surrounding gas, steam-to-gas and liquid environment at a high temperature (to several hundred of degrees). Main objective of spent researches is the substantiation of possibility reliable and effective electric power transform with electric machine means directly in hermetic objects with extreme conditions environment by means of new DTA. The principle and job analysis of new disk induction motors of block-module type are observed.
Jang, Seung-Ho; Ih, Jeong-Guon
2003-02-01
It is known that the direct method yields different results from the indirect (or load) method in measuring the in-duct acoustic source parameters of fluid machines. The load method usually comes up with a negative source resistance, although a fairly accurate prediction of radiated noise can be obtained from any method. This study is focused on the effect of the time-varying nature of fluid machines on the output results of two typical measurement methods. For this purpose, a simplified fluid machine consisting of a reservoir, a valve, and an exhaust pipe is considered as representing a typical periodic, time-varying system and the measurement situations are simulated by using the method of characteristics. The equivalent circuits for such simulations are also analyzed by considering the system as having a linear time-varying source. It is found that the results from the load method are quite sensitive to the change of cylinder pressure or valve profile, in contrast to those from the direct method. In the load method, the source admittance turns out to be predominantly dependent on the valve admittance at the calculation frequency as well as the valve and load admittances at other frequencies. In the direct method, however, the source resistance is always positive and the source admittance depends mainly upon the zeroth order of valve admittance.
NASA Astrophysics Data System (ADS)
Abellán-Nebot, J. V.; Liu, J.; Romero, F.
2009-11-01
The State Space modelling approach has been recently proposed as an engineering-driven technique for part quality prediction in Multistage Machining Processes (MMP). Current State Space models incorporate fixture and datum variations in the multi-stage variation propagation, without explicitly considering common operation variations such as machine-tool thermal distortions, cutting-tool wear, cutting-tool deflections, etc. This paper shows the limitations of the current State Space model through an experimental case study where the effect of the spindle thermal expansion, cutting-tool flank wear and locator errors are introduced. The paper also discusses the extension of the current State Space model to include operation variations and its potential benefits.
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.
NASA Astrophysics Data System (ADS)
Nebot, Àngela; Mugica, Francisco
2012-10-01
Fuzzy inductive reasoning (FIR) is a modelling and simulation methodology derived from the General Systems Problem Solver. It compares favourably with other soft computing methodologies, such as neural networks, genetic or neuro-fuzzy systems, and with hard computing methodologies, such as AR, ARIMA, or NARMAX, when it is used to predict future behaviour of different kinds of systems. This paper contains an overview of the FIR methodology, its historical background, and its evolution.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ahn, S. K.; Chang, H. Y.
To elucidate plasma nonuniformity in high frequency capacitive discharges, Langmuir probe and B-dot probe measurements were carried out in the radial direction in a cylindrical capacitive discharge driven at 90 MHz with argon pressures of 50 and 400 mTorr. Through the measurements, a significant inductive electric field (i.e., time-varying magnetic field) was observed at the radial edge, and it was found that the inductive electric field creates strong plasma nonuniformity at high pressure operation. The plasma nonuniformity at high pressure operation is physically similar to the E-H mode transition typically observed in inductive discharges. This result agrees well with themore » theories of electromagnetic effects in large area and/or high frequency capacitive discharges.« less
Modernization of gas-turbine engines with high-frequency induction motors
NASA Astrophysics Data System (ADS)
Abramovich, B. N.; Sychev, Yu A.; Kuznetsov, P. A.
2018-03-01
Main tendencies of growth of electric energy consumption in general and mining industries were analyzed in the paper. A key role of electric drive in this process was designated. A review about advantages and disadvantages of unregulated gearboxes with mechanical units that are commonly used in domestically produced gas-turbine engines was made. This review allows one to propose different gas-turbine engines modernization schemes with the help of PWM-driven high-frequency induction motors. Induction motors with the double rotor winding were examined. A simulation of high-frequency induction motors with double rotor windings in Matlab-Simulink software was carried out based on equivalent circuit parameters. Obtained characteristics of new motors were compared with serially produced analogues. After the simulation, results were implemented in the real prototype.
Impact of wind generator infed on dynamic performance of a power system
NASA Astrophysics Data System (ADS)
Alam, Md. Ahsanul
Wind energy is one of the most prominent sources of electrical energy in the years to come. A tendency to increase the amount of electricity generation from wind turbine can be observed in many countries. One of the major concerns related to the high penetration level of the wind energy into the existing power grid is its influence on power system dynamic performance. In this thesis, the impact of wind generation system on power system dynamic performance is investigated through detailed dynamic modeling of the entire wind generator system considering all the relevant components. Nonlinear and linear models of a single machine as well as multimachine wind-AC system have been derived. For the dynamic model of integrated wind-AC system, a general transformation matrix is determined for the transformation of machine and network quantities to a common reference frame. Both time-domain and frequency domain analyses on single machine and multimachine systems have been carried out. The considered multimachine systems are---A 4 machine 12 bus system, and 10 machine 39 bus New England system. Through eigenvalue analysis, impact of asynchronous wind system on overall network damping has been quantified and modes responsible for the instability have been identified. Over with a number of simulation studies it is observed that for a induction generator based wind generation system, the fixed capacitor located at the generator terminal cannot normally cater for the reactive power demand during the transient disturbances like wind gust and fault on the system. For weak network connection, system instability may be initiated because of induction generator terminal voltage collapse under certain disturbance conditions. Incorporation of dynamic reactive power compensation scheme through either variable susceptance control or static compensator (STATCOM) is found to improve the dynamic performance significantly. Further improvement in transient profile has been brought in by supporting STATCOM with bulk energy storage devices. Two types of energy storage system (ESS) have been considered---battery energy storage system, and supercapacitor based energy storage system. A decoupled P -- Q control strategy has been implemented on STATCOM/ESS. It is observed that wind generators when supported by STATCOM/ESS can achieve significant withstand capability in the presence of grid fault of reasonable duration. It experiences almost negligible rotor speed variation, maintains constant terminal voltage, and resumes delivery of smoothed (almost transient free) power to the grid immediately after the fault is cleared. Keywords: Wind energy, induction generator, dynamic performance of wind generators, energy storage system, decoupled P -- Q control, multimachine system.
How similar are recognition memory and inductive reasoning?
Hayes, Brett K; Heit, Evan
2013-07-01
Conventionally, memory and reasoning are seen as different types of cognitive activities driven by different processes. In two experiments, we challenged this view by examining the relationship between recognition memory and inductive reasoning involving multiple forms of similarity. A common study set (members of a conjunctive category) was followed by a test set containing old and new category members, as well as items that matched the study set on only one dimension. The study and test sets were presented under recognition or induction instructions. In Experiments 1 and 2, the inductive property being generalized was varied in order to direct attention to different dimensions of similarity. When there was no time pressure on decisions, patterns of positive responding were strongly affected by property type, indicating that different types of similarity were driving recognition and induction. By comparison, speeded judgments showed weaker property effects and could be explained by generalization based on overall similarity. An exemplar model, GEN-EX (GENeralization from EXamples), could account for both the induction and recognition data. These findings show that induction and recognition share core component processes, even when the tasks involve flexible forms of similarity.
Disruption prediction investigations using Machine Learning tools on DIII-D and Alcator C-Mod
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rea, C.; Granetz, R. S.; Montes, K.
Using data-driven methodology, we exploit the time series of relevant plasma parameters for a large set of disrupted and non-disrupted discharges to develop a classification algorithm for detecting disruptive phases in shots that eventually disrupt. Comparing the same methodology on different devices is crucial in order to have information on the portability of the developed algorithm and the possible extrapolation to ITER. Therefore, we use data from two very different tokamaks, DIII-D and Alcator C-Mod. We then focus on a subset of disruption predictors, most of which are dimensionless and/or machine-independent parameters, coming from both plasma diagnostics and equilibrium reconstructions,more » such as the normalized plasma internal inductance ℓ and the n = 1 mode amplitude normalized to the toroidal magnetic field. Using such dimensionless indicators facilitates a more direct comparison between DIII-D and C-Mod. We then choose a shallow Machine Learning technique, called Random Forests, to explore the databases available for the two devices. We show results from the classification task, where we introduce a time dependency through the definition of class labels on the basis of the elapsed time before the disruption (i.e. ‘far from a disruption’ and ‘close to a disruption’). The performances of the different Random Forest classifiers are discussed in terms of several metrics, by showing the number of successfully detected samples, as well as the misclassifications. The overall model accuracies are above 97% when identifying a ‘far from disruption’ and a ‘disruptive’ phase for disrupted discharges. Nevertheless, the Forests are intrinsically different in their capability of predicting a disruptive behavior, with C-Mod predictions comparable to random guesses. Indeed, we show that C-Mod recall index, i.e. the sensitivity to a disruptive behavior, is as low as 0.47, while DIII-D recall is ~0.72. The portability of the developed algorithm is also tested across the two devices, by using DIII-D data for training the forests and C-Mod for testing and vice versa.« less
Disruption prediction investigations using Machine Learning tools on DIII-D and Alcator C-Mod
Rea, C.; Granetz, R. S.; Montes, K.; ...
2018-06-18
Using data-driven methodology, we exploit the time series of relevant plasma parameters for a large set of disrupted and non-disrupted discharges to develop a classification algorithm for detecting disruptive phases in shots that eventually disrupt. Comparing the same methodology on different devices is crucial in order to have information on the portability of the developed algorithm and the possible extrapolation to ITER. Therefore, we use data from two very different tokamaks, DIII-D and Alcator C-Mod. We then focus on a subset of disruption predictors, most of which are dimensionless and/or machine-independent parameters, coming from both plasma diagnostics and equilibrium reconstructions,more » such as the normalized plasma internal inductance ℓ and the n = 1 mode amplitude normalized to the toroidal magnetic field. Using such dimensionless indicators facilitates a more direct comparison between DIII-D and C-Mod. We then choose a shallow Machine Learning technique, called Random Forests, to explore the databases available for the two devices. We show results from the classification task, where we introduce a time dependency through the definition of class labels on the basis of the elapsed time before the disruption (i.e. ‘far from a disruption’ and ‘close to a disruption’). The performances of the different Random Forest classifiers are discussed in terms of several metrics, by showing the number of successfully detected samples, as well as the misclassifications. The overall model accuracies are above 97% when identifying a ‘far from disruption’ and a ‘disruptive’ phase for disrupted discharges. Nevertheless, the Forests are intrinsically different in their capability of predicting a disruptive behavior, with C-Mod predictions comparable to random guesses. Indeed, we show that C-Mod recall index, i.e. the sensitivity to a disruptive behavior, is as low as 0.47, while DIII-D recall is ~0.72. The portability of the developed algorithm is also tested across the two devices, by using DIII-D data for training the forests and C-Mod for testing and vice versa.« less
NASA Astrophysics Data System (ADS)
Forkel, Matthias; Dorigo, Wouter; Lasslop, Gitta; Teubner, Irene; Chuvieco, Emilio; Thonicke, Kirsten
2017-12-01
Vegetation fires affect human infrastructures, ecosystems, global vegetation distribution, and atmospheric composition. However, the climatic, environmental, and socioeconomic factors that control global fire activity in vegetation are only poorly understood, and in various complexities and formulations are represented in global process-oriented vegetation-fire models. Data-driven model approaches such as machine learning algorithms have successfully been used to identify and better understand controlling factors for fire activity. However, such machine learning models cannot be easily adapted or even implemented within process-oriented global vegetation-fire models. To overcome this gap between machine learning-based approaches and process-oriented global fire models, we introduce a new flexible data-driven fire modelling approach here (Satellite Observations to predict FIre Activity, SOFIA approach version 1). SOFIA models can use several predictor variables and functional relationships to estimate burned area that can be easily adapted with more complex process-oriented vegetation-fire models. We created an ensemble of SOFIA models to test the importance of several predictor variables. SOFIA models result in the highest performance in predicting burned area if they account for a direct restriction of fire activity under wet conditions and if they include a land cover-dependent restriction or allowance of fire activity by vegetation density and biomass. The use of vegetation optical depth data from microwave satellite observations, a proxy for vegetation biomass and water content, reaches higher model performance than commonly used vegetation variables from optical sensors. We further analyse spatial patterns of the sensitivity between anthropogenic, climate, and vegetation predictor variables and burned area. We finally discuss how multiple observational datasets on climate, hydrological, vegetation, and socioeconomic variables together with data-driven modelling and model-data integration approaches can guide the future development of global process-oriented vegetation-fire models.
Carnahan, Brian; Meyer, Gérard; Kuntz, Lois-Ann
2003-01-01
Multivariate classification models play an increasingly important role in human factors research. In the past, these models have been based primarily on discriminant analysis and logistic regression. Models developed from machine learning research offer the human factors professional a viable alternative to these traditional statistical classification methods. To illustrate this point, two machine learning approaches--genetic programming and decision tree induction--were used to construct classification models designed to predict whether or not a student truck driver would pass his or her commercial driver license (CDL) examination. The models were developed and validated using the curriculum scores and CDL exam performances of 37 student truck drivers who had completed a 320-hr driver training course. Results indicated that the machine learning classification models were superior to discriminant analysis and logistic regression in terms of predictive accuracy. Actual or potential applications of this research include the creation of models that more accurately predict human performance outcomes.
Base drive and overlap protection circuit
Gritter, David J.
1983-01-01
An inverter (34) which provides power to an A. C. machine (28) is controlled by a circuit (36) employing PWM control strategy whereby A. C. power is supplied to the machine at a preselectable frequency and preselectable voltage. This is accomplished by the technique of waveform notching in which the shapes of the notches are varied to determine the average energy content of the overall waveform. Through this arrangement, the operational efficiency of the A. C. machine is optimized. The control circuit includes a microcomputer and memory element which receive various parametric inputs and calculate optimized machine control data signals therefrom. The control data is asynchronously loaded into the inverter through an intermediate buffer (38). A base drive and overlap protection circuit is included to insure that both transistors of a complimentary pair are not conducting at the same time. In its preferred embodiment, the present invention is incorporated within an electric vehicle (10) employing a 144 VDC battery pack (32) and a three-phase induction motor (18).
Experimental Studies of Instability Development in Magnetically Driven Systems
Awe, Thomas James
2015-03-01
The author highlights results from a variety of experiments on the Z Machine, for which he served as the lead experimentalist. All experiments on Z take dedicated effort from a large collaboration of scientists, engineers, and technicians.
Chaotic behaviour of Zeeman machines at introductory course of mechanics
NASA Astrophysics Data System (ADS)
Nagy, Péter; Tasnádi, Péter
2016-05-01
Investigation of chaotic motions and cooperative systems offers a magnificent opportunity to involve modern physics into the basic course of mechanics taught to engineering students. In the present paper it will be demonstrated that Zeeman Machine can be a versatile and motivating tool for students to get introductory knowledge about chaotic motion via interactive simulations. It works in a relatively simple way and its properties can be understood very easily. Since the machine can be built easily and the simulation of its movement is also simple the experimental investigation and the theoretical description can be connected intuitively. Although Zeeman Machine is known mainly for its quasi-static and catastrophic behaviour, its dynamic properties are also of interest with its typical chaotic features. By means of a periodically driven Zeeman Machine a wide range of chaotic properties of the simple systems can be demonstrated such as bifurcation diagrams, chaotic attractors, transient chaos and so on. The main goal of this paper is the presentation of an interactive learning material for teaching the basic features of the chaotic systems through the investigation of the Zeeman Machine.
Microcompartments and Protein Machines in Prokaryotes
Saier, Milton H.
2013-01-01
The prokaryotic cell was once thought of as a “bag of enzymes” with little or no intracellular compartmentalization. In this view, most reactions essential for life occurred as a consequence of random molecular collisions involving substrates, cofactors and cytoplasmic enzymes. Our current conception of a prokaryote is far from this view. We now consider a bacterium or an archaeon as a highly structured, non-random collection of functional membrane-embedded and proteinaceous molecular machines, each of which serves a specialized function. In this article we shall present an overview of such microcompartments including (i) the bacterial cytoskeleton and the apparati allowing DNA segregation during cells division, (ii) energy transduction apparati involving light-driven proton pumping and ion gradient-driven ATP synthesis, (iii) prokaryotic motility and taxis machines that mediate cell movements in response to gradients of chemicals and physical forces, (iv) machines of protein folding, secretion and degradation, (v) metabolasomes carrying out specific chemical reactions, (vi) 24 hour clocks allowing bacteria to coordinate their metabolic activities with the daily solar cycle and (vii) proteinaceous membrane compartmentalized structures such as sulfur granules and gas vacuoles. Membrane-bounded prokaryotic organelles were considered in a recent JMMB written symposium concerned with membraneous compartmentalization in bacteria [Saier and Bogdanov, 2013]. By contrast, in this symposium, we focus on proteinaceous microcompartments. These two symposia, taken together, provide the interested reader with an objective view of the remarkable complexity of what was once thought of as a simple non-compartmentalized cell. PMID:23920489
Effects of pole flux distribution in a homopolar linear synchronous machine
NASA Astrophysics Data System (ADS)
Balchin, M. J.; Eastham, J. F.; Coles, P. C.
1994-05-01
Linear forms of synchronous electrical machine are at present being considered as the propulsion means in high-speed, magnetically levitated (Maglev) ground transportation systems. A homopolar form of machine is considered in which the primary member, which carries both ac and dc windings, is supported on the vehicle. Test results and theoretical predictions are presented for a design of machine intended for driving a 100 passenger vehicle at a top speed of 400 km/h. The layout of the dc magnetic circuit is examined to locate the best position for the dc winding from the point of view of minimum core weight. Measurements of flux build-up under the machine at different operating speeds are given for two types of secondary pole: solid and laminated. The solid pole results, which are confirmed theoretically, show that this form of construction is impractical for high-speed drives. Measured motoring characteristics are presented for a short length of machine which simulates conditions at the leading and trailing ends of the full-sized machine. Combination of the results with those from a cylindrical version of the machine make it possible to infer the performance of the full-sized traction machine. This gives 0.8 pf and 0.9 efficiency at 300 km/h, which is much better than the reported performance of a comparable linear induction motor (0.52 pf and 0.82 efficiency). It is therefore concluded that in any projected high-speed Maglev systems, a linear synchronous machine should be the first choice as the propulsion means.
Reactive power compensating system
Williams, Timothy J.; El-Sharkawi, Mohamed A.; Venkata, Subrahmanyam S.
1987-01-01
The reactive power of an induction machine is compensated by providing fixed capacitors on each phase line for the minimum compensation required, sensing the current on one line at the time its voltage crosses zero to determine the actual compensation required for each phase, and selecting switched capacitors on each line to provide the balance of the compensation required.
NASA Astrophysics Data System (ADS)
Sanga, Ramesh; Srinivasan, V. S.; Sivaramakrishna, M.; Prabhakara Rao, G.
2018-07-01
In rotating machinery due to continuous rotational induced wear and tear, metallic debris will be produced and mixes with the in-service lubricant oil over the course of time. This debris gives the sign of potential machine failure due to the aging of critical parts like gears and bearings. The size and type of wear debris has a direct relationship with the degree of wear in the machine and gives information about the healthiness of equipment. This article presents an inductive quasi-digital sensor to detect the metallic debris, its type; size in the lubrication oil of rotating machinery. A microcontroller based low cost, low power, high resolution and high precise instrument with alarm indication and LCD is developed to detect ferrous debris of sizes from 30 µm and non-ferrous debris of 50 µm. It is thoroughly tested and calibrated with ferrous, non-ferrous debris of different sizes in the air environment. Finally, an experiment is conducted to check the performance of the instrument by circulating lubricant oil containing ferrous, non-ferrous debris through the sensor.
Real time PI-backstepping induction machine drive with efficiency optimization.
Farhani, Fethi; Ben Regaya, Chiheb; Zaafouri, Abderrahmen; Chaari, Abdelkader
2017-09-01
This paper describes a robust and efficient speed control of a three phase induction machine (IM) subjected to load disturbances. First, a Multiple-Input Multiple-Output (MIMO) PI-Backstepping controller is proposed for a robust and highly accurate tracking of the mechanical speed and rotor flux. Asymptotic stability of the control scheme is proven by Lyapunov Stability Theory. Second, an active online optimization algorithm is used to optimize the efficiency of the drive system. The efficiency improvement approach consists of adjusting the rotor flux with respect to the load torque in order to minimize total losses in the IM. A dSPACE DS1104 R&D board is used to implement the proposed solution. The experimental results released on 3kW squirrel cage IM, show that the reference speed as well as the rotor flux are rapidly achieved with a fast transient response and without overshoot. A good load disturbances rejection response and IM parameters variation are fairly handled. The improvement of drive system efficiency reaches up to 180% at light load. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Coaxial Helicity Injection experiments in NSTX*
NASA Astrophysics Data System (ADS)
Raman, R.; Jarboe, T. R.; Gates, D.; Mueller, D.; Schaffer, M. J.; Maqueda, R.; Nelson, B. A.; Menard, J.; Soukhanovskii, V.; Paul, S.; Jardin, S.; Skinner, C. H.; Sabbagh, S.; Paoletti, F.; Stutman, D.; Lao, L.; Nagata, M.
2001-10-01
Coaxial helicity injection (CHI) can potentially eliminate inductive startup and thus the induction solenoid in spherical tori (ST), thereby greatly improving the ST fusion concept. CHI experiments on NSTX have produced 360 kA of toroidal current using about 25 kA of injector current. These have been produced in the preferred 'narrow flux foot print' condition in pulses that were sustained for 300 ms. A rotating n=1 mode, previously observed in optimized discharges on smaller STs driven by CHI and deemed necessary for transporting edge driven current to the interior of the discharge, has been observed for the first time in NSTX CHI discharges. The flux utilization efficiency continues to be high, approaching 100%. EFIT and TSC codes are being used to assess flux closure. This work is supported by the US DOE contract numbers: DE-AC02-76CH03073 and DE-AC05-00R22725.
Using a theory-driven conceptual framework in qualitative health research.
Macfarlane, Anne; O'Reilly-de Brún, Mary
2012-05-01
The role and merits of highly inductive research designs in qualitative health research are well established, and there has been a powerful proliferation of grounded theory method in the field. However, tight qualitative research designs informed by social theory can be useful to sensitize researchers to concepts and processes that they might not necessarily identify through inductive processes. In this article, we provide a reflexive account of our experience of using a theory-driven conceptual framework, the Normalization Process Model, in a qualitative evaluation of general practitioners' uptake of a free, pilot, language interpreting service in the Republic of Ireland. We reflect on our decisions about whether or not to use the Model, and describe our actual use of it to inform research questions, sampling, coding, and data analysis. We conclude with reflections on the added value that the Model and tight design brought to our research.
Dynamic Performance of Subway Vehicle with Linear Induction Motor System
NASA Astrophysics Data System (ADS)
Wu, Pingbo; Luo, Ren; Hu, Yan; Zeng, Jing
The light rail vehicle with Linear Induction Motor (LIM) bogie, which is a new type of urban rail traffic tool, has the advantages of low costs, wide applicability, low noise, simple maintenance and better dynamic behavior. This kind of vehicle, supported and guided by the wheel and rail, is not driven by the wheel/rail adhesion force, but driven by the electromagnetic force between LIM and reaction plate. In this paper, three different types of suspensions and their characteristic are discussed with considering the interactions both between wheel and rail and between LIM and reaction plate. A nonlinear mathematical model of the vehicle with LIM bogie is set up by using the software SIMPACK, and the electromechanical model is also set up on Simulink roof. Then the running behavior of the LIM vehicle is simulated, and the influence of suspension on the vehicle dynamic performance is investigated.
NASA Astrophysics Data System (ADS)
Berger, Andrew J.; Edwards, Eric R. J.; Nembach, Hans T.; Karenowska, Alexy D.; Weiler, Mathias; Silva, Thomas J.
2018-03-01
Functional spintronic devices rely on spin-charge interconversion effects, such as the reciprocal processes of electric field-driven spin torque and magnetization dynamics-driven spin and charge flow. Both dampinglike and fieldlike spin-orbit torques have been observed in the forward process of current-driven spin torque and dampinglike inverse spin-orbit torque has been well studied via spin pumping into heavy metal layers. Here, we demonstrate that established microwave transmission spectroscopy of ferromagnet/normal metal bilayers under ferromagnetic resonance can be used to inductively detect the ac charge currents driven by the inverse spin-charge conversion processes. This technique relies on vector network analyzer ferromagnetic resonance (VNA-FMR) measurements. We show that in addition to the commonly extracted spectroscopic information, VNA-FMR measurements can be used to quantify the magnitude and phase of all ac charge currents in the sample, including those due to spin pumping and spin-charge conversion. Our findings reveal that Ni80Fe20/Pt bilayers exhibit both dampinglike and fieldlike inverse spin-orbit torques. While the magnitudes of both the dampinglike and fieldlike inverse spin-orbit torque are of comparable scale to prior reported values for similar material systems, we observed a significant dependence of the dampinglike magnitude on the order of deposition. This suggests interface quality plays an important role in the overall strength of the dampinglike spin-to-charge conversion.
Code of Federal Regulations, 2011 CFR
2011-07-01
... beading, straightening, corrugating, flanging, or bending rolls; and hot or cold rolling mills. (ii) All... area between the dies; power presses; and plate punches. (iii) All bending machines, such as apron...
Integrative relational machine-learning for understanding drug side-effect profiles
2013-01-01
Background Drug side effects represent a common reason for stopping drug development during clinical trials. Improving our ability to understand drug side effects is necessary to reduce attrition rates during drug development as well as the risk of discovering novel side effects in available drugs. Today, most investigations deal with isolated side effects and overlook possible redundancy and their frequent co-occurrence. Results In this work, drug annotations are collected from SIDER and DrugBank databases. Terms describing individual side effects reported in SIDER are clustered with a semantic similarity measure into term clusters (TCs). Maximal frequent itemsets are extracted from the resulting drug x TC binary table, leading to the identification of what we call side-effect profiles (SEPs). A SEP is defined as the longest combination of TCs which are shared by a significant number of drugs. Frequent SEPs are explored on the basis of integrated drug and target descriptors using two machine learning methods: decision-trees and inductive-logic programming. Although both methods yield explicit models, inductive-logic programming method performs relational learning and is able to exploit not only drug properties but also background knowledge. Learning efficiency is evaluated by cross-validation and direct testing with new molecules. Comparison of the two machine-learning methods shows that the inductive-logic-programming method displays a greater sensitivity than decision trees and successfully exploit background knowledge such as functional annotations and pathways of drug targets, thereby producing rich and expressive rules. All models and theories are available on a dedicated web site. Conclusions Side effect profiles covering significant number of drugs have been extracted from a drug ×side-effect association table. Integration of background knowledge concerning both chemical and biological spaces has been combined with a relational learning method for discovering rules which explicitly characterize drug-SEP associations. These rules are successfully used for predicting SEPs associated with new drugs. PMID:23802887
Integrative relational machine-learning for understanding drug side-effect profiles.
Bresso, Emmanuel; Grisoni, Renaud; Marchetti, Gino; Karaboga, Arnaud Sinan; Souchet, Michel; Devignes, Marie-Dominique; Smaïl-Tabbone, Malika
2013-06-26
Drug side effects represent a common reason for stopping drug development during clinical trials. Improving our ability to understand drug side effects is necessary to reduce attrition rates during drug development as well as the risk of discovering novel side effects in available drugs. Today, most investigations deal with isolated side effects and overlook possible redundancy and their frequent co-occurrence. In this work, drug annotations are collected from SIDER and DrugBank databases. Terms describing individual side effects reported in SIDER are clustered with a semantic similarity measure into term clusters (TCs). Maximal frequent itemsets are extracted from the resulting drug x TC binary table, leading to the identification of what we call side-effect profiles (SEPs). A SEP is defined as the longest combination of TCs which are shared by a significant number of drugs. Frequent SEPs are explored on the basis of integrated drug and target descriptors using two machine learning methods: decision-trees and inductive-logic programming. Although both methods yield explicit models, inductive-logic programming method performs relational learning and is able to exploit not only drug properties but also background knowledge. Learning efficiency is evaluated by cross-validation and direct testing with new molecules. Comparison of the two machine-learning methods shows that the inductive-logic-programming method displays a greater sensitivity than decision trees and successfully exploit background knowledge such as functional annotations and pathways of drug targets, thereby producing rich and expressive rules. All models and theories are available on a dedicated web site. Side effect profiles covering significant number of drugs have been extracted from a drug ×side-effect association table. Integration of background knowledge concerning both chemical and biological spaces has been combined with a relational learning method for discovering rules which explicitly characterize drug-SEP associations. These rules are successfully used for predicting SEPs associated with new drugs.
Retention system and method for the blades of a rotary machine
Pedersen, Poul D.; Glynn, Christopher C.; Walker, Roger C.
2002-01-01
A retention system and method for the blades of a rotary machine for preventing forward or aft axial movement of the rotor blades includes a circumferential hub slot formed about a circumference of the machine hub. The rotor blades have machined therein a blade retention slot which is aligned with the circumferential hub slot when the blades are received in correspondingly shaped openings in the hub. At least one ring segment is secured in the blade retention slots and the circumferential hub slot to retain the blades from axial movement. A key assembly is used to secure the ring segments in the aligned slots via a hook portion receiving the ring segments and a threaded portion that is driven radially outwardly by a nut. A cap may be provided to provide a redundant back-up load path for the centrifugal loads on the key. Alternatively, the key assembly may be formed in the blade dovetail.
Residual Error Based Anomaly Detection Using Auto-Encoder in SMD Machine Sound.
Oh, Dong Yul; Yun, Il Dong
2018-04-24
Detecting an anomaly or an abnormal situation from given noise is highly useful in an environment where constantly verifying and monitoring a machine is required. As deep learning algorithms are further developed, current studies have focused on this problem. However, there are too many variables to define anomalies, and the human annotation for a large collection of abnormal data labeled at the class-level is very labor-intensive. In this paper, we propose to detect abnormal operation sounds or outliers in a very complex machine along with reducing the data-driven annotation cost. The architecture of the proposed model is based on an auto-encoder, and it uses the residual error, which stands for its reconstruction quality, to identify the anomaly. We assess our model using Surface-Mounted Device (SMD) machine sound, which is very complex, as experimental data, and state-of-the-art performance is successfully achieved for anomaly detection.
Modeling Geomagnetic Variations using a Machine Learning Framework
NASA Astrophysics Data System (ADS)
Cheung, C. M. M.; Handmer, C.; Kosar, B.; Gerules, G.; Poduval, B.; Mackintosh, G.; Munoz-Jaramillo, A.; Bobra, M.; Hernandez, T.; McGranaghan, R. M.
2017-12-01
We present a framework for data-driven modeling of Heliophysics time series data. The Solar Terrestrial Interaction Neural net Generator (STING) is an open source python module built on top of state-of-the-art statistical learning frameworks (traditional machine learning methods as well as deep learning). To showcase the capability of STING, we deploy it for the problem of predicting the temporal variation of geomagnetic fields. The data used includes solar wind measurements from the OMNI database and geomagnetic field data taken by magnetometers at US Geological Survey observatories. We examine the predictive capability of different machine learning techniques (recurrent neural networks, support vector machines) for a range of forecasting times (minutes to 12 hours). STING is designed to be extensible to other types of data. We show how STING can be used on large sets of data from different sensors/observatories and adapted to tackle other problems in Heliophysics.
A computer architecture for intelligent machines
NASA Technical Reports Server (NTRS)
Lefebvre, D. R.; Saridis, G. N.
1991-01-01
The Theory of Intelligent Machines proposes a hierarchical organization for the functions of an autonomous robot based on the Principle of Increasing Precision With Decreasing Intelligence. An analytic formulation of this theory using information-theoretic measures of uncertainty for each level of the intelligent machine has been developed in recent years. A computer architecture that implements the lower two levels of the intelligent machine is presented. The architecture supports an event-driven programming paradigm that is independent of the underlying computer architecture and operating system. Details of Execution Level controllers for motion and vision systems are addressed, as well as the Petri net transducer software used to implement Coordination Level functions. Extensions to UNIX and VxWorks operating systems which enable the development of a heterogeneous, distributed application are described. A case study illustrates how this computer architecture integrates real-time and higher-level control of manipulator and vision systems.
Evaluation of half wave induction motor drive for use in passenger vehicles
NASA Technical Reports Server (NTRS)
Hoft, R. G.; Kawamura, A.; Goodarzi, A.; Yang, G. Q.; Erickson, C. L.
1985-01-01
Research performed at the University of Missouri-Columbia to devise and design a lower cost inverter induction motor drive for electrical propulsion of passenger vehicles is described. A two phase inverter motor system is recommended. The new design is predicted to provide comparable vehicle performance, improved reliability and a cost advantage for a high production vehicle, decreased total rating of the power semiconductor switches, and a somewhat simpler control hardware compared to the conventional three phase bridge inverter motor drive system. The major disadvantages of the two phase inverter motor drive are that it is larger and more expensive than a three phase machine, the design of snubbers for the power leakage inductances produce higher transient voltages, and the torque pulsations are relatively large because of the necessity to limit the inverter switching frequency to achieve high efficiency.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lee, Seong T; Burress, Timothy A; Hsu, John S
2009-01-01
This paper introduces a new method for calculating the power factor with consideration of the cross saturation between the direct-axis (d-axis) and the quadrature-axis (q-axis) of an interior permanent magnet synchronous motor (IPMSM). The conventional two-axis IPMSM model is modified to include the cross-saturation effect by adding the cross-coupled inductance terms. This paper also contains the new method of calculating the cross-coupled inductance values as well as self-inductance values in d- and q-axes. The analyzed motor is a high-speed brushless field excitation machine that offers high torque per ampere per core length at low speed and weakened flux at highmore » speed, which was developed for the traction motor of a hybrid electric vehicle.« less
Knowledge discovery with classification rules in a cardiovascular dataset.
Podgorelec, Vili; Kokol, Peter; Stiglic, Milojka Molan; Hericko, Marjan; Rozman, Ivan
2005-12-01
In this paper we study an evolutionary machine learning approach to data mining and knowledge discovery based on the induction of classification rules. A method for automatic rules induction called AREX using evolutionary induction of decision trees and automatic programming is introduced. The proposed algorithm is applied to a cardiovascular dataset consisting of different groups of attributes which should possibly reveal the presence of some specific cardiovascular problems in young patients. A case study is presented that shows the use of AREX for the classification of patients and for discovering possible new medical knowledge from the dataset. The defined knowledge discovery loop comprises a medical expert's assessment of induced rules to drive the evolution of rule sets towards more appropriate solutions. The final result is the discovery of a possible new medical knowledge in the field of pediatric cardiology.
Learning temporal rules to forecast instability in continuously monitored patients
Dubrawski, Artur; Wang, Donghan; Hravnak, Marilyn; Clermont, Gilles; Pinsky, Michael R
2017-01-01
Inductive machine learning, and in particular extraction of association rules from data, has been successfully used in multiple application domains, such as market basket analysis, disease prognosis, fraud detection, and protein sequencing. The appeal of rule extraction techniques stems from their ability to handle intricate problems yet produce models based on rules that can be comprehended by humans, and are therefore more transparent. Human comprehension is a factor that may improve adoption and use of data-driven decision support systems clinically via face validity. In this work, we explore whether we can reliably and informatively forecast cardiorespiratory instability (CRI) in step-down unit (SDU) patients utilizing data from continuous monitoring of physiologic vital sign (VS) measurements. We use a temporal association rule extraction technique in conjunction with a rule fusion protocol to learn how to forecast CRI in continuously monitored patients. We detail our approach and present and discuss encouraging empirical results obtained using continuous multivariate VS data from the bedside monitors of 297 SDU patients spanning 29 346 hours (3.35 patient-years) of observation. We present example rules that have been learned from data to illustrate potential benefits of comprehensibility of the extracted models, and we analyze the empirical utility of each VS as a potential leading indicator of an impending CRI event. PMID:27274020
Intense X-ray machine for penetrating radiography
NASA Astrophysics Data System (ADS)
Lucht, Roy A.; Eckhouse, Shimon
Penetrating radiography has been used for many years in the nuclear weapons research programs. Infrequently penetrating radiography has been used in conventional weapons research programs. For example the Los Alamos PHERMEX machine was used to view uranium rods penetrating steel for the GAU-8 program, and the Ector machine was used to see low density regions in forming metal jets. The armor/anti-armor program at Los Alamos has created a need for an intense flash X-ray machine that can be dedicated to conventional weapons research. The Balanced Technology Initiative, through DARPA, has funded the design and construction of such a machine at Los Alamos. It will be an 8- to 10-MeV diode machine capable of delivering a dose of 500 R at 1 m with a spot size of less than 5 mm. The machine used an 87.5-stage low inductance Marx generator that charges up a 7.4-(Omega), 32-ns water line. The water line is discharged through a self-breakdown oil switch into a 12.4-(Omega) water line that rings up the voltage into the high impendance X-ray diode. A long (233-cm) vacuum drift tube is used to separate the large diameter oil-insulated diode region from the X-ray source area that may be exposed to high overpressures by the explosive experiments. The electron beam is selffocused at the target area using a low pressure background gas.
A New Apparatus for Measuring the Temperature at Machine Parts Rotating at High Speeds
NASA Technical Reports Server (NTRS)
Gnam, E.
1945-01-01
After a brief survey of the available methods for measuring the temperatures of machine parts at high speed, in particular turbine blades and rotors, an apparatus is described which is constructed on the principle of induction. Transmission of the measuring current by sliding contacts therefore is avoided. Up-to-date experiments show that it is possible to give the apparatus a high degree of sensitivity and accuracy. In comparison with sliding contact types, the present apparatus shows the important advantage that it operates for any length of time without wear, and that the contact difficulties, particularly occurring at high sliding speeds,are avoided.
Inductive storage for quasi-steady MPD thrusters
NASA Technical Reports Server (NTRS)
Clark, K. E.
1978-01-01
Experiments in which a quasi-steady MPD thruster is driven by a large inductor demonstrate the feasibility of using inductive energy storage to couple an intermittent high power plasma thruster to a lower power steady state supply, such as a thermionic converter. Switching between inductor charging and MPD thrusting phases of the current cycle occurs smoothly, with the voltage spike generated during switching sufficient to initiate the arc discharge in the thruster without an auxiliary starting circuit. Further, the current waveforms delivered by the inductor are of a shape suitable for the quasi-steady thrusting process, and they agree with analytical estimates, indicating that the interaction between the thruster impedance and the inductive source is dynamically stable.
An Efficient Fuzzy Controller Design for Parallel Connected Induction Motor Drives
NASA Astrophysics Data System (ADS)
Usha, S.; Subramani, C.
2018-04-01
Generally, an induction motors are highly non-linear and has a complex time varying dynamics. This makes the speed control of an induction motor a challenging issue in the industries. But, due to the recent trends in the power electronic devices and intelligent controllers, the speed control of the induction motor is achieved by including non-linear characteristics also. Conventionally a single inverter is used to run one induction motor in industries. In the traction applications, two or more inductions motors are operated in parallel to reduce the size and cost of induction motors. In this application, the parallel connected induction motors can be driven by a single inverter unit. The stability problems may introduce in the parallel operation under low speed operating conditions. Hence, the speed deviations should be reduce with help of suitable controllers. The speed control of the parallel connected system is performed by PID controller and fuzzy logic controller. In this paper the speed response of the induction motor for the rating of IHP, 1440 rpm, and 50Hz with these controller are compared in time domain specifications. The stability analysis of the system also performed under low speed using matlab platform. The hardware model is developed for speed control using fuzzy logic controller which exhibited superior performances over the other controller.
NASA Astrophysics Data System (ADS)
Chen, Yu-Fan; Wang, Yen-Hung; Tsai, Jui-che
2018-03-01
This work has developed an approach to construct a corner cube retroreflector (CCR). A two-dimensional cutout pattern is first fabricated with wire electrical discharge machining process. It is then folded up into a three-dimensional CCR suspended on a cantilever beam. The folded-up CCR may be driven through external actuators for optical modulation; it can also mechanically respond to perturbation, acceleration, etc., to function as a sensor. Mechanical (static and dynamic modeling) and optical (ray tracing) analyses are also performed.
Software Tools for Emittance Measurement and Matching for 12 GeV CEBAF
DOE Office of Scientific and Technical Information (OSTI.GOV)
Turner, Dennis L.
2016-05-01
This paper discusses model-driven setup of the Continuous Electron Beam Accelerator Facility (CEBAF) for the 12GeV era, focusing on qsUtility. qsUtility is a set of software tools created to perform emittance measurements, analyze those measurements, and compute optics corrections based upon the measurements.qsUtility was developed as a toolset to facilitate reducing machine configuration time and reproducibility by way of an accurate accelerator model, and to provide Operations staff with tools to measure and correct machine optics with little or no assistance from optics experts.
Are we at a crossroads or a plateau? Radiomics and machine learning in abdominal oncology imaging.
Summers, Ronald M
2018-05-05
Advances in radiomics and machine learning have driven a technology boom in the automated analysis of radiology images. For the past several years, expectations have been nearly boundless for these new technologies to revolutionize radiology image analysis and interpretation. In this editorial, I compare the expectations with the realities with particular attention to applications in abdominal oncology imaging. I explore whether these technologies will leave us at a crossroads to an exciting future or to a sustained plateau and disillusionment.
NASA Astrophysics Data System (ADS)
Hribernik, Božo
1984-02-01
This paper describes an iterative algorithm for the simulation of various real magnetic materials in a small induction motor and their influence on the flux distribution in the air gap. Two standard materials, fully-, and semi-processed steel strips were used. The nonlinearity of the magnetization curve, the influence of cutting strains and magnetic anisotropy are also considered. All these influences bring out the facts that the uniformly rotated and sine form exitation causes a nonuniformly rotated and deformed magnetic field in the air gap of the machine and that the magnetization current is winding place dependent.
Fractography of induction-hardened steel fractured in fatigue and overload
DOE Office of Scientific and Technical Information (OSTI.GOV)
Santos, C.G.; Laird, C.
1997-07-01
The fracture surfaces of induction-hardened steel specimens obtained from an auto axle were characterized, macroscopically and microscopically, after being fractured in fatigue and monotonic overload. Specimens were tested in cyclic three-point bending under load control, and the S-N curve was established for specimens that had been notched by spark machining to facilitate fractography. Scanning electron microscopy of the fractured surfaces obtained for lives spanning the range 17,000 to 418,000 cycles revealed diverse fracture morphologies, including intergranular fracture and transgranular fatigue fracture. The results are being offered to assist in the analysis of complex field failures in strongly hardened steel.
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.
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.
A New Multivariate Approach for Prognostics Based on Extreme Learning Machine and Fuzzy Clustering.
Javed, Kamran; Gouriveau, Rafael; Zerhouni, Noureddine
2015-12-01
Prognostics is a core process of prognostics and health management (PHM) discipline, that estimates the remaining useful life (RUL) of a degrading machinery to optimize its service delivery potential. However, machinery operates in a dynamic environment and the acquired condition monitoring data are usually noisy and subject to a high level of uncertainty/unpredictability, which complicates prognostics. The complexity further increases, when there is absence of prior knowledge about ground truth (or failure definition). For such issues, data-driven prognostics can be a valuable solution without deep understanding of system physics. This paper contributes a new data-driven prognostics approach namely, an "enhanced multivariate degradation modeling," which enables modeling degrading states of machinery without assuming a homogeneous pattern. In brief, a predictability scheme is introduced to reduce the dimensionality of the data. Following that, the proposed prognostics model is achieved by integrating two new algorithms namely, the summation wavelet-extreme learning machine and subtractive-maximum entropy fuzzy clustering to show evolution of machine degradation by simultaneous predictions and discrete state estimation. The prognostics model is equipped with a dynamic failure threshold assignment procedure to estimate RUL in a realistic manner. To validate the proposition, a case study is performed on turbofan engines data from PHM challenge 2008 (NASA), and results are compared with recent publications.
Burner Rig in the Material and Stresses Building
1969-11-21
A burner rig heats up a material sample in the Materials and Stresses Building at the National Aeronautics and Space Administration (NASA) Lewis Research Center. Materials technology is an important element in the successful development of advanced airbreathing and rocket propulsion systems. Different types of engines operate in different environments so an array of dependable materials is needed. NASA Lewis began investigating the characteristics of different materials shortly after World War II. In 1949 the materials group was expanded into its own division. The Lewis researchers sought to study and test materials in environments that simulate the environment in which they would operate. The Materials and Stresses Building, built in 1949, contained a number of laboratories to analyze the materials. They are subjected to high temperatures, high stresses, corrosion, irradiation, and hot gasses. The Physics of Solids Laboratory included a cyclotron, cloud chamber, helium cryostat, and metallurgy cave. The Metallographic Laboratory possessed six x-ray diffraction machines, two metalloscopes, and other equipment. The Furnace Room had two large induction machines, a 4500⁰ F graphite furnace, and heat treating equipment. The Powder Laboratory included 60-ton and 3000-ton presses. The Stresses Laboratory included stress rupture machines, fatigue machines, and tensile strength machines.
The history of articulators: the wonderful world of "grinders," Part 2.
Starcke, Edgar N; Engelmeier, Robert L
2012-04-01
This is the second article in a three-part series on the history of denture grinding devices. The first article reviewed the earliest attempts to mechanically grind the occlusion of artificial teeth from the manipulation of simple articulators to very elaborate and complex machines powered by hand cranks. This article explores motor-driven grinders, most driven by way of a belt-driven pulley powered by an external source. A few were self-contained; that is, the motor was mounted on the grinder base. There were basically two types of grinders: those with cast holders for mounting processed dentures and those with provisions for using articulators for that purpose. © 2012 by the American College of Prosthodontists.
Mimicking Nonequilibrium Steady States with Time-Periodic Driving
NASA Astrophysics Data System (ADS)
Raz, O.; Subaşı, Y.; Jarzynski, C.
2016-04-01
Under static conditions, a system satisfying detailed balance generically relaxes to an equilibrium state in which there are no currents. To generate persistent currents, either detailed balance must be broken or the system must be driven in a time-dependent manner. A stationary system that violates detailed balance evolves to a nonequilibrium steady state (NESS) characterized by fixed currents. Conversely, a system that satisfies instantaneous detailed balance but is driven by the time-periodic variation of external parameters—also known as a stochastic pump (SP)—reaches a periodic state with nonvanishing currents. In both cases, these currents are maintained at the cost of entropy production. Are these two paradigmatic scenarios effectively equivalent? For discrete-state systems, we establish a mapping between nonequilibrium stationary states and stochastic pumps. Given a NESS characterized by a particular set of stationary probabilities, currents, and entropy production rates, we show how to construct a SP with exactly the same (time-averaged) values. The mapping works in the opposite direction as well. These results establish a proof of principle: They show that stochastic pumps are able to mimic the behavior of nonequilibrium steady states, and vice versa, within the theoretical framework of discrete-state stochastic thermodynamics. Nonequilibrium steady states and stochastic pumps are often used to model, respectively, biomolecular motors driven by chemical reactions and artificial molecular machines steered by the variation of external, macroscopic parameters. Our results loosely suggest that anything a biomolecular machine can do, an artificial molecular machine can do equally well. We illustrate this principle by showing that kinetic proofreading, a NESS mechanism that explains the low error rates in biochemical reactions, can be effectively mimicked by a constrained periodic driving.
A survey of the three-dimensional high Reynolds number transonic wind tunnel
NASA Technical Reports Server (NTRS)
Takashima, K.; Sawada, H.; Aoki, T.
1982-01-01
The facilities for aerodynamic testing of airplane models at transonic speeds and high Reynolds numbers are surveyed. The need for high Reynolds number testing is reviewed, using some experimental results. Some approaches to high Reynolds number testing such as the cryogenic wind tunnel, the induction driven wind tunnel, the Ludwieg tube, the Evans clean tunnel and the hydraulic driven wind tunnel are described. The level of development of high Reynolds number testing facilities in Japan is discussed.
FGF-mediated mesoderm induction involves the Src-family kinase Laloo.
Weinstein, D C; Marden, J; Carnevali, F; Hemmati-Brivanlou, A
1998-08-27
During embryogenesis, inductive interactions underlie the development of much of the body plan. In Xenopus laevis, factors secreted from the vegetal pole induce mesoderm in the adjacent marginal zone; members of both the transforming growth factor-beta (TGF-beta) and fibroblast growth factor (FGF) ligand families seem to have critical roles in this process. Here we report the identification and characterization of laloo, a novel participant in the signal transduction cascade linking extracellular, mesoderm-inducing signals to the nucleus, where alteration of cell fate is driven by changes in gene expression. Overexpression of laloo, a member of the Src-related gene family, in Xenopus embryos gives rise to ectopic posterior structures that frequently contain axial tissue. Laloo induces mesoderm in Xenopus ectodermal explants; this induction is blocked by reagents that disrupt the FGF signalling pathway. Conversely, expression of a dominant-inhibitory Laloo mutant blocks mesoderm induction by FGF and causes severe posterior truncations in vivo. This work provides the first evidence that a Src-related kinase is involved in vertebrate mesoderm induction.
Electric Machine with Boosted Inductance to Stabilize Current Control
NASA Technical Reports Server (NTRS)
Abel, Steve
2013-01-01
High-powered motors typically have very low resistance and inductance (R and L) in their windings. This makes the pulse-width modulated (PWM) control of the current very difficult, especially when the bus voltage (V) is high. These R and L values are dictated by the motor size, torque (Kt), and back-emf (Kb) constants. These constants are in turn set by the voltage and the actuation torque-speed requirements. This problem is often addressed by placing inductive chokes within the controller. This approach is undesirable in that space is taken and heat is added to the controller. By keeping the same motor frame, reducing the wire size, and placing a correspondingly larger number of turns in each slot, the resistance, inductance, torque constant, and back-emf constant are all increased. The increased inductance aids the current control but ruins the Kt and Kb selections. If, however, a fraction of the turns is moved from their "correct slot" to an "incorrect slot," the increased R and L values are retained, but the Kt and Kb values are restored to the desired values. This approach assumes that increased resistance is acceptable to a degree. In effect, the heat allocated to the added inductance has been moved from the controller to the motor body, which in some cases is preferred.
Inductive displacement sensors with a notch filter for an active magnetic bearing system.
Chen, Seng-Chi; Le, Dinh-Kha; Nguyen, Van-Sum
2014-07-15
Active magnetic bearing (AMB) systems support rotating shafts without any physical contact, using electromagnetic forces. Each radial AMB uses two pairs of electromagnets at opposite sides of the rotor. This allows the rotor to float in the air gap, and the machine to operate without frictional losses. In active magnetic suspension, displacement sensors are necessary to detect the radial and axial movement of the suspended object. In a high-speed rotating machine equipped with an AMB, the rotor bending modes may be limited to the operating range. The natural frequencies of the rotor can cause instability. Thus, notch filters are a useful circuit for stabilizing the system. In addition, commercial displacement sensors are sometimes not suitable for AMB design, and cannot filter the noise caused by the natural frequencies of rotor. Hence, implementing displacement sensors based on the AMB structure is necessary to eliminate noises caused by natural frequency disturbances. The displacement sensor must be highly sensitive in the desired working range, and also exhibit a low interference noise, high stability, and low cost. In this study, we used the differential inductive sensor head and lock-in amplifier for synchronous demodulation. In addition, an active low-pass filter and a notch filter were used to eliminate disturbances, which caused by natural frequencies. As a consequence, the inductive displacement sensor achieved satisfactory linearity, high sensitivity, and disturbance elimination. This sensor can be easily produced for AMB applications. A prototype of these displacement sensors was built and tested.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lawler, J.S.
2001-10-29
An inverter topology and control scheme has been developed that can drive low-inductance, surface-mounted permanent magnet motors over the wide constant power speed range required in electric vehicle applications. This new controller is called the dual-mode inverter control (DMIC) [1]. The DMIC can drive either the Permanent Magnet Synchronous Machine (PMSM) with sinusoidal back emf, or the brushless dc machine (BDCM) with trapezoidal emf in the motoring and regenerative braking modes. In this paper we concentrate on the BDCM under high-speed motoring conditions. Simulation results show that if all motor and inverter loss mechanisms are neglected, the constant power speedmore » range of the DMIC is infinite. The simulation results are supported by closed form expressions for peak and rms motor current and average power derived from analytical solution to the differential equations governing the DMIC/BDCM drive for the lossless case. The analytical solution shows that the range of motor inductance that can be accommodated by the DMIC is more than an order of magnitude such that the DMIC is compatible with both low- and high-inductance BDCMs. Finally, method is given for integrating the classical hysteresis band current control, used for motor control below base speed, with the phase advance of DMIC that is applied above base speed. The power versus speed performance of the DMIC is then simulated across the entire speed range.« less
NASA Astrophysics Data System (ADS)
Stavisky, Sergey D.; Kao, Jonathan C.; Nuyujukian, Paul; Ryu, Stephen I.; Shenoy, Krishna V.
2015-06-01
Objective. Brain-machine interfaces (BMIs) seek to enable people with movement disabilities to directly control prosthetic systems with their neural activity. Current high performance BMIs are driven by action potentials (spikes), but access to this signal often diminishes as sensors degrade over time. Decoding local field potentials (LFPs) as an alternative or complementary BMI control signal may improve performance when there is a paucity of spike signals. To date only a small handful of LFP decoding methods have been tested online; there remains a need to test different LFP decoding approaches and improve LFP-driven performance. There has also not been a reported demonstration of a hybrid BMI that decodes kinematics from both LFP and spikes. Here we first evaluate a BMI driven by the local motor potential (LMP), a low-pass filtered time-domain LFP amplitude feature. We then combine decoding of both LMP and spikes to implement a hybrid BMI. Approach. Spikes and LFP were recorded from two macaques implanted with multielectrode arrays in primary and premotor cortex while they performed a reaching task. We then evaluated closed-loop BMI control using biomimetic decoders driven by LMP, spikes, or both signals together. Main results. LMP decoding enabled quick and accurate cursor control which surpassed previously reported LFP BMI performance. Hybrid decoding of both spikes and LMP improved performance when spikes signal quality was mediocre to poor. Significance. These findings show that LMP is an effective BMI control signal which requires minimal power to extract and can substitute for or augment impoverished spikes signals. Use of this signal may lengthen the useful lifespan of BMIs and is therefore an important step towards clinically viable BMIs.
Microcompartments and protein machines in prokaryotes.
Saier, Milton H
2013-01-01
The prokaryotic cell was once thought of as a 'bag of enzymes' with little or no intracellular compartmentalization. In this view, most reactions essential for life occurred as a consequence of random molecular collisions involving substrates, cofactors and cytoplasmic enzymes. Our current conception of a prokaryote is far from this view. We now consider a bacterium or an archaeon as a highly structured, nonrandom collection of functional membrane-embedded and proteinaceous molecular machines, each of which serves a specialized function. In this article we shall present an overview of such microcompartments including (1) the bacterial cytoskeleton and the apparati allowing DNA segregation during cell division; (2) energy transduction apparati involving light-driven proton pumping and ion gradient-driven ATP synthesis; (3) prokaryotic motility and taxis machines that mediate cell movements in response to gradients of chemicals and physical forces; (4) machines of protein folding, secretion and degradation; (5) metabolosomes carrying out specific chemical reactions; (6) 24-hour clocks allowing bacteria to coordinate their metabolic activities with the daily solar cycle, and (7) proteinaceous membrane compartmentalized structures such as sulfur granules and gas vacuoles. Membrane-bound prokaryotic organelles were considered in a recent Journal of Molecular Microbiology and Biotechnology written symposium concerned with membranous compartmentalization in bacteria [J Mol Microbiol Biotechnol 2013;23:1-192]. By contrast, in this symposium, we focus on proteinaceous microcompartments. These two symposia, taken together, provide the interested reader with an objective view of the remarkable complexity of what was once thought of as a simple noncompartmentalized cell. Copyright © 2013 S. Karger AG, Basel.
Code of Federal Regulations, 2014 CFR
2014-07-01
... constitute an integral part of a circuit for transmitting electrical energy. (d) Cable reels for shuttle cars... MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Construction and Design Requirements § 18.45 Cable reels. (a) A self-propelled machine, that receives electrical energy through a portable...
Code of Federal Regulations, 2013 CFR
2013-07-01
... constitute an integral part of a circuit for transmitting electrical energy. (d) Cable reels for shuttle cars... MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Construction and Design Requirements § 18.45 Cable reels. (a) A self-propelled machine, that receives electrical energy through a portable...
Code of Federal Regulations, 2012 CFR
2012-07-01
... constitute an integral part of a circuit for transmitting electrical energy. (d) Cable reels for shuttle cars... MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Construction and Design Requirements § 18.45 Cable reels. (a) A self-propelled machine, that receives electrical energy through a portable...
Code of Federal Regulations, 2013 CFR
2013-07-01
... handcarrying any carcass or half carcass of beef, pork, horse, deer, or buffalo, or any quarter carcass of beef... preservation and flavoring of meat, including poultry, by curing materials. It does not include a workroom or...
Code of Federal Regulations, 2012 CFR
2012-07-01
... handcarrying any carcass or half carcass of beef, pork, horse, deer, or buffalo, or any quarter carcass of beef... preservation and flavoring of meat, including poultry, by curing materials. It does not include a workroom or...
Code of Federal Regulations, 2014 CFR
2014-07-01
... handcarrying any carcass or half carcass of beef, pork, horse, deer, or buffalo, or any quarter carcass of beef... preservation and flavoring of meat, including poultry, by curing materials. It does not include a workroom or...
Code of Federal Regulations, 2010 CFR
2010-07-01
... constitute an integral part of a circuit for transmitting electrical energy. (d) Cable reels for shuttle cars... MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Construction and Design Requirements § 18.45 Cable reels. (a) A self-propelled machine, that receives electrical energy through a portable...
Code of Federal Regulations, 2011 CFR
2011-07-01
... constitute an integral part of a circuit for transmitting electrical energy. (d) Cable reels for shuttle cars... MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Construction and Design Requirements § 18.45 Cable reels. (a) A self-propelled machine, that receives electrical energy through a portable...
Zhao, Ming; Rattanatamrong, Prapaporn; DiGiovanna, Jack; Mahmoudi, Babak; Figueiredo, Renato J; Sanchez, Justin C; Príncipe, José C; Fortes, José A B
2008-01-01
Dynamic data-driven brain-machine interfaces (DDDBMI) have great potential to advance the understanding of neural systems and improve the design of brain-inspired rehabilitative systems. This paper presents a novel cyberinfrastructure that couples in vivo neurophysiology experimentation with massive computational resources to provide seamless and efficient support of DDDBMI research. Closed-loop experiments can be conducted with in vivo data acquisition, reliable network transfer, parallel model computation, and real-time robot control. Behavioral experiments with live animals are supported with real-time guarantees. Offline studies can be performed with various configurations for extensive analysis and training. A Web-based portal is also provided to allow users to conveniently interact with the cyberinfrastructure, conducting both experimentation and analysis. New motor control models are developed based on this approach, which include recursive least square based (RLS) and reinforcement learning based (RLBMI) algorithms. The results from an online RLBMI experiment shows that the cyberinfrastructure can successfully support DDDBMI experiments and meet the desired real-time requirements.
Robust Operation of Tendon-Driven Robot Fingers Using Force and Position-Based Control Laws
NASA Technical Reports Server (NTRS)
Hargrave, Brian (Inventor); Abdallah, Muhammad E (Inventor); Reiland, Matthew J (Inventor); Diftler, Myron A (Inventor); Strawser, Philip A (Inventor); Platt, Jr., Robert J. (Inventor); Ihrke, Chris A. (Inventor)
2013-01-01
A robotic system includes a tendon-driven finger and a control system. The system controls the finger via a force-based control law when a tension sensor is available, and via a position-based control law when a sensor is not available. Multiple tendons may each have a corresponding sensor. The system selectively injects a compliance value into the position-based control law when only some sensors are available. A control system includes a host machine and a non-transitory computer-readable medium having a control process, which is executed by the host machine to control the finger via the force- or position-based control law. A method for controlling the finger includes determining the availability of a tension sensor(s), and selectively controlling the finger, using the control system, via the force or position-based control law. The position control law allows the control system to resist disturbances while nominally maintaining the initial state of internal tendon tensions.
Push-pull switching power amplifier
NASA Technical Reports Server (NTRS)
Cuk, Slobodan M. (Inventor)
1980-01-01
A true push-pull switching power amplifier is disclosed utilizing two dc-to-dc converters. Each converter is comprised of two inductances, one inductance in series with a DC source and the other inductor in series with the output load, and an electrical energy transferring device with storage capability, namely storage capacitance, with suitable switching means between the inductances to obtain DC level conversion, where the switching means allows bidirectional current (and power) flow, and the switching means of one dc-to-dc converter is driven by the complement of a square-wave switching signal for the other dc-to-dc converter for true push-pull operation. For reduction of current ripple, the inductances in each of the two converters may be coupled, and with proper design of the coupling, the ripple can be reduced to zero at either the input or the output, but preferably the output.
Multiple beam induction accelerators for heavy ion fusion
NASA Astrophysics Data System (ADS)
Seidl, Peter A.; Barnard, John J.; Faltens, Andris; Friedman, Alex; Waldron, William L.
2014-01-01
Induction accelerators are appealing for heavy-ion driven inertial fusion energy (HIF) because of their high efficiency and their demonstrated capability to accelerate high beam current (≥10 kA in some applications). For the HIF application, accomplishments and challenges are summarized. HIF research and development has demonstrated the production of single ion beams with the required emittance, current, and energy suitable for injection into an induction linear accelerator. Driver scale beams have been transported in quadrupole channels of the order of 10% of the number of quadrupoles of a driver. We review the design and operation of induction accelerators and the relevant aspects of their use as drivers for HIF. We describe intermediate research steps that would provide the basis for a heavy-ion research facility capable of heating matter to fusion relevant temperatures and densities, and also to test and demonstrate an accelerator architecture that scales well to a fusion power plant.
Low pressure EGR system having full range capability
Easley, Jr., William Lanier; Milam, David Michael; Roozenboom, Stephan Donald; Bond, Michael Steven; Kapic, Amir
2009-09-22
An exhaust treatment system for an engine is disclosed and may have an air induction circuit, an exhaust circuit, and an exhaust recirculation circuit. The air induction circuit may be configured to direct air into the engine. The exhaust circuit may be configured to direct exhaust from the engine and include a turbine driven by the exhaust, a particulate filter disposed in series with and downstream of the turbine, and a catalytic device disposed in series with and downstream of the particulate filter. The exhaust recirculation circuit may be configured to selectively redirect at least some of the exhaust from between the particulate filter and the catalytic device to the air induction circuit. The catalytic device is selected to create backpressure within the exhaust circuit sufficient to ensure that, under normal engine operating conditions above low idle, exhaust can flow into the air induction circuit without throttling of the air.
NASA Astrophysics Data System (ADS)
Brinovar, Iztok; Srpčič, Gregor; Seme, Sebastijan; Štumberger, Bojan; Hadžiselimović, Miralem
2017-07-01
This article deals with the classification of explosion-proof protected induction motors, which are used in hazardous areas, into adequate temperature and efficiency class. Hazardous areas are defined as locations with a potentially explosive atmosphere where explosion may occur due to present of flammable gasses, liquids or combustible dusts (industrial plants, mines, etc.). Electric motors and electrical equipment used in such locations must be specially designed and tested to prevent electrical initiation of explosion due to high surface temperature and arcing contacts. This article presents the basic tests of three-phase explosion-proof protected induction motor with special emphasis on the measuring system and temperature rise test. All the measurements were performed with high-accuracy instrumentation and accessory equipment and carried out at the Institute of energy technology in the Electric machines and drives laboratory and Applied electrical engineering laboratory.
NASA Astrophysics Data System (ADS)
Steiner, Adam M.; Yager-Elorriaga, David A.; Patel, Sonal G.; Jordan, Nicholas M.; Gilgenbach, Ronald M.; Safronova, Alla S.; Kantsyrev, Victor L.; Shlyaptseva, Veronica V.; Shrestha, Ishor; Schmidt-Petersen, Maximillian T.
2016-10-01
Implosions of planar wire arrays were performed on the Michigan Accelerator for Inductive Z-pinch Experiments, a linear transformer driver (LTD) at the University of Michigan. These experiments were characterized by lower than expected peak currents and significantly longer risetimes compared to studies performed on higher impedance machines. A circuit analysis showed that the load inductance has a significant impact on the current output due to the comparatively low impedance of the driver; the long risetimes were also attributed to high variability in LTD switch closing times. A circuit model accounting for these effects was employed to measure changes in load inductance as a function of time to determine plasma pinch timing and calculate a minimum effective current-carrying radius. These calculations showed good agreement with available shadowgraphy and x-ray diode measurements.
Arun Dominic, D; Chelliah, Thanga Raj
2014-09-01
To obtain high dynamic performance on induction motor drives (IMD), variable voltage and variable frequency operation has to be performed by measuring speed of rotation and stator currents through sensors and fed back them to the controllers. When the sensors are undergone a fault, the stability of control system, may be designed for an industrial process, is disturbed. This paper studies the negative effects on a 12.5 hp induction motor drives when the field oriented control system is subjected to sensor faults. To illustrate the importance of this study mine hoist load diagram is considered as shaft load of the tested machine. The methods to recover the system from sensor faults are discussed. In addition, the various speed sensorless schemes are reviewed comprehensively. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
Simulation-driven machine learning: Bearing fault classification
NASA Astrophysics Data System (ADS)
Sobie, Cameron; Freitas, Carina; Nicolai, Mike
2018-01-01
Increasing the accuracy of mechanical fault detection has the potential to improve system safety and economic performance by minimizing scheduled maintenance and the probability of unexpected system failure. Advances in computational performance have enabled the application of machine learning algorithms across numerous applications including condition monitoring and failure detection. Past applications of machine learning to physical failure have relied explicitly on historical data, which limits the feasibility of this approach to in-service components with extended service histories. Furthermore, recorded failure data is often only valid for the specific circumstances and components for which it was collected. This work directly addresses these challenges for roller bearings with race faults by generating training data using information gained from high resolution simulations of roller bearing dynamics, which is used to train machine learning algorithms that are then validated against four experimental datasets. Several different machine learning methodologies are compared starting from well-established statistical feature-based methods to convolutional neural networks, and a novel application of dynamic time warping (DTW) to bearing fault classification is proposed as a robust, parameter free method for race fault detection.
NASA Astrophysics Data System (ADS)
Drid, S.; Nait-Said, M.-S.; Tadjine, M.; Makouf, A.
2008-06-01
There is an increasing interest in electric vehicles due to environmental concerns. Recent efforts are directed toward developing an improved propulsion system for electric vehicles applications with minimal power losses. This paper deals with the high efficient vector control for the reduction of copper losses of the doubly fed motor. Firstly, the feedback linearization control based on Lyapunov approach is employed to design the underlying controller achieving the double fluxes orientation. The fluxes controllers are designed independently of the speed. The speed controller is designed using the Lyapunov method especially employed to the unknown load torques. The global asymptotic stability of the overall system is theoretically proven. Secondly, a new Torque Copper Losses Factor is proposed to deal with the problem of the machine copper losses. Its main function is to optimize the torque in keeping the machine saturation at an acceptable level. This leads to a reduction in machine currents and therefore their accompanied copper losses guaranteeing improved machine efficiency. The simulation results in comparative presentation confirm largely the effectiveness of the proposed DFIM control with a very interesting energy saving contribution.
Noninductively Driven Tokamak Plasmas at Near-Unity Toroidal Beta
Schlossberg, David J.; Bodner, Grant M.; Bongard, Michael W.; ...
2017-07-01
Access to and characterization of sustained, toroidally confined plasmas with a very high plasma-to-magnetic pressure ratio (β t), low internal inductance, high elongation, and nonsolenoidal current drive is a central goal of present tokamak plasma research. Stable access to this desirable parameter space is demonstrated in plasmas with ultralow aspect ratio and high elongation. Local helicity injection provides nonsolenoidal sustainment, low internal inductance, and ion heating. Equilibrium analyses indicate β t up to ~100% with a minimum |B| well spanning up to ~50% of the plasma volume.
Modelling high frequency phenomena in the rotor of induction motors under no-load test conditions
NASA Astrophysics Data System (ADS)
Boglietti, Aldo; Bottauscio, Oriano; Chiampi, Mario; Lazzari, Mario
2003-01-01
The paper aims to deep the electromagnetic phenomena in the rotor of induction motors produced during the no-load test by the high-order harmonics of the spatial distribution of magnetic flux. The analysis is carried out by a flux driven finite element procedure, which can take into account the hysteresis of magnetic material, the induced currents in rotor cage and the eddy currents in the laminations. The computed results, including losses and local waveforms of electrical and magnetic quantities, are finally discussed.
Prostate organogenesis: tissue induction, hormonal regulation and cell type specification
Toivanen, Roxanne
2017-01-01
Prostate organogenesis is a complex process that is primarily mediated by the presence of androgens and subsequent mesenchyme-epithelial interactions. The investigation of prostate development is partly driven by its potential relevance to prostate cancer, in particular the apparent re-awakening of key developmental programs that occur during tumorigenesis. However, our current knowledge of the mechanisms that drive prostate organogenesis is far from complete. Here, we provide a comprehensive overview of prostate development, focusing on recent findings regarding sexual dimorphism, bud induction, branching morphogenesis and cellular differentiation. PMID:28400434
Noninductively Driven Tokamak Plasmas at Near-Unity Toroidal Beta.
Schlossberg, D J; Bodner, G M; Bongard, M W; Burke, M G; Fonck, R J; Perry, J M; Reusch, J A
2017-07-21
Access to and characterization of sustained, toroidally confined plasmas with a very high plasma-to-magnetic pressure ratio (β_{t}), low internal inductance, high elongation, and nonsolenoidal current drive is a central goal of present tokamak plasma research. Stable access to this desirable parameter space is demonstrated in plasmas with ultralow aspect ratio and high elongation. Local helicity injection provides nonsolenoidal sustainment, low internal inductance, and ion heating. Equilibrium analyses indicate β_{t} up to ∼100% with a minimum |B| well spanning up to ∼50% of the plasma volume.
Method of Optimizing the Construction of Machining, Assembly and Control Devices
NASA Astrophysics Data System (ADS)
Iordache, D. M.; Costea, A.; Niţu, E. L.; Rizea, A. D.; Babă, A.
2017-10-01
Industry dynamics, driven by economic and social requirements, must generate more interest in technological optimization, capable of ensuring a steady development of advanced technical means to equip machining processes. For these reasons, the development of tools, devices, work equipment and control, as well as the modernization of machine tools, is the certain solution to modernize production systems that require considerable time and effort. This type of approach is also related to our theoretical, experimental and industrial applications of recent years, presented in this paper, which have as main objectives the elaboration and use of mathematical models, new calculation methods, optimization algorithms, new processing and control methods, as well as some structures for the construction and configuration of technological equipment with a high level of performance and substantially reduced costs..
Pan, Yan; Brown, Leonid; Konermann, Lars
2011-12-21
Many proteins act as molecular machines that are fuelled by a nonthermal energy source. Examples include transmembrane pumps and stator-rotor complexes. These systems undergo cyclic motions (CMs) that are being driven along a well-defined conformational trajectory. Superimposed on these CMs are thermal fluctuations (TFs) that are coupled to stochastic motions of the solvent. Here we explore whether the TFs of a molecular machine are affected by the occurrence of CMs. Bacteriorhodopsin (BR) is a light-driven proton pump that serves as a model system in this study. The function of BR is based on a photocycle that involves trans/cis isomerization of a retinal chromophore, as well as motions of transmembrane helices. Hydrogen/deuterium exchange (HDX) mass spectrometry was used to monitor the TFs of BR, focusing on the monomeric form of the protein. Comparative HDX studies were conducted under illumination and in the dark. The HDX kinetics of BR are dramatically accelerated in the presence of light. The isotope exchange rates and the number of backbone amides involved in EX2 opening transitions increase roughly 2-fold upon illumination. In contrast, light/dark control experiments on retinal-free protein produced no discernible differences. It can be concluded that the extent of TFs in BR strongly depends on photon-driven CMs. The light-induced differences in HDX behavior are ascribed to protein destabilization. Specifically, the thermodynamic stability of the dark-adapted protein is estimated to be 5.5 kJ mol(-1) under the conditions of our work. This value represents the free energy difference between the folded state F and a significantly unfolded conformer U. Illumination reduces the stability of F by 2.2 kJ mol(-1). Mechanical agitation caused by isomerization of the chromophore is transferred to the surrounding protein scaffold, and subsequently, the energy dissipates into the solvent. Light-induced retinal motions therefore act analogously to an internal heat source that promotes the occurrence of TFs. Overall, our data highlight the potential of HDX methods for probing the structural dynamics of molecular machines under "engine on" and "engine off" conditions. © 2011 American Chemical Society
Ion energy spread and current measurements of the rf-driven multicusp ion source
NASA Astrophysics Data System (ADS)
Lee, Y.; Gough, R. A.; Kunkel, W. B.; Leung, K. N.; Perkins, L. T.; Pickard, D. S.; Sun, L.; Vujic, J.; Williams, M. D.; Wutte, D.
1997-03-01
Axial energy spread and useful beam current of positive ion beams have been carried out using a radio frequency (rf)-driven multicusp ion source. Operating the source with a 13.56 MHz induction discharge, the axial energy spread is found to be approximately 3.2 eV. The extractable beam current of the rf-driven source is found to be comparable to that of filament-discharge sources. With a 0.6 mm diameter extraction aperture, a positive hydrogen ion beam current density of 80 mA/cm2 can be obtained at a rf input power of 2.5 kW. The expected source lifetime is much longer than that of filament discharges.
Coaxial fast metal-to-metal switch for high current.
Boissady, C; Rioux-Damidau, F
1978-11-01
A fast mechanical switch of coaxial configuration, driven by a magnetic field, is described. It presents a low inductance (6 nH), a low resistance (3 muOmega) and delay-times of 25 micros with a jitter of 0.08 micros.
Maxillary-driven simultaneous maxillo-mandibular distraction for hemifacial microsomia.
Nakajima, Hideo; Sakamoto, Yoshiaki; Tamada, Ikkei; Ogata, Hisao; Kishi, Kazuo; Sakamoto, Teruo
2011-12-01
We treat hemifacial microsomia with a combination of surgery and orthodontic treatment during the growth period, resulting in early improvement in facial asymmetry and the induction of normal growth. We previously used gradual distraction of the mandibular ramus for Pruzansky's type II classification (Pruzansky, 1969). In type II cases, the maxilla should also be treated actively as, using this technique, improvement of the occlusal plane is difficult to achieve, resulting in a cross bite and difficulties in post-operative orthodontic treatment-especially in older patients. Morphologically, the mandibular angle region of the operative side is flat, and the angle of the mouth remains elevated. We performed mandibular-driven simultaneous maxillo-mandibular distraction while the occlusion was maintained using intermaxillary anchorage. However, mandibular-driven distraction tended to elongate the face because the mandible only elongated downwards and the mandibular ramus did not reach the glenoid. Furthermore, external distraction devices produce significant distress for patients until removal of the device and cause scars on the face. We developed a new internal distraction device with a variable angle and performed maxillary-driven simultaneous maxillo-mandibular distraction using this device. The result was morphologically satisfactory and solved the above problems. Because the patient was in the growth period, careful follow-up and induction to normal growth were important while the inferior growth of the affected side was monitored. Copyright © 2010 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.
Induction of appropriate Th-cell phenotypes: cellular decision-making in heterogeneous environments.
van den Ham, H-J; Andeweg, A C; de Boer, R J
2013-11-01
Helper T (Th)-cell differentiation is a key event in the development of the adaptive immune response. By the production of a range of cytokines, Th cells determine the type of immune response that is raised against an invading pathogen. Th cells can adopt many different phenotypes, and Th-cell phenotype decision-making is crucial in mounting effective host responses. This review discusses the different Th-cell phenotypes that have been identified and how Th cells adopt a particular phenotype. The regulation of Th-cell phenotypes has been studied extensively using mathematical models, which have explored the role of regulatory mechanisms such as autocrine cytokine signalling and cross-inhibition between self-activating transcription factors. At the single cell level, Th responses tend to be heterogeneous, but corrections can be made soon after T-cell activation. Although pathogens and the innate immune system provide signals that direct the induction of Th-cell phenotypes, these instructive mechanisms could be easily subverted by pathogens. We discuss that a model of success-driven feedback would select the most appropriate phenotype for clearing a pathogen. Given the heterogeneity in the induction phase of the Th response, such a success-driven feedback loop would allow the selection of effective Th-cell phenotypes while terminating incorrect responses. © 2013 John Wiley & Sons Ltd.
Electronically commutated motors for vehicle applications
NASA Astrophysics Data System (ADS)
Echolds, E. F.
1980-02-01
Two permanent magnet electronically commutated motors for electric vehicle traction are discussed. One, based on existing technology, produces 23 kW (peak) at 26,000 rpm, and 11 kW continuous at 18,000 rpm. The motor has a conventional design: a four-pole permanent magnet rotor and a three-phase stator similar to those used on ordinary induction motors. The other, advanced technology motor, is rated at 27 kW (peak) at 14,000 rpm, and 11 kW continuous at 10,500 rpm. The machine employs a permanent magnet rotor and a novel ironless stator design in an axial air gap, homopolar configuration. Comparison of the new motors with conventional brush type machines indicates potential for substantial cost savings.
Field-Oriented Control Of Induction Motors
NASA Technical Reports Server (NTRS)
Burrows, Linda M.; Roth, Mary Ellen; Zinger, Don S.
1993-01-01
Field-oriented control system provides for feedback control of torque or speed or both. Developed for use with commercial three-phase, 400-Hz, 208-V, 5-hp motor. Systems include resonant power supply operating at 20 kHz. Pulse-population-modulation subsystem selects individual pulses of 20-kHz single-phase waveform as needed to synthesize three waveforms of appropriate lower frequency applied to three phase windings of motor. Electric actuation systems using technology currently being built to peak powers of 70 kW. Amplitude of voltage of effective machine-frequency waveform determined by momentary frequency of pulses, while machine frequency determined by rate of repetition of overall temporal pattern of pulses. System enables independent control of both voltage and frequency.
Method of forming shrink-fit compression seal
NASA Technical Reports Server (NTRS)
Podgorski, T. J. (Inventor)
1977-01-01
A method for making a glass-to-metal seal is described. A domed metal enclosure having a machined seal ring is fitted to a glass post machined to a slight taper and to a desired surface finish. The metal part is then heated by induction in a vacuum. As the metal part heats and expands relative to the glass post, the metal seal ring, possessing a higher coefficient of expansion than the glass post, slides down the tapered post. Upon cooling, the seal ring crushes against the glass post forming the seal. The method results in a glass-to-metal seal possessing extremely good leak resistance, while the parts are kept clean and free of the contaminants.
Torque-balanced vibrationless rotary coupling
Miller, Donald M.
1980-01-01
This disclosure describes a torque-balanced vibrationless rotary coupling for transmitting rotary motion without unwanted vibration into the spindle of a machine tool. A drive member drives a driven member using flexible connecting loops which are connected tangentially and at diametrically opposite connecting points through a free floating ring.
Andreassi, Maria Grazia; Borghini, Andrea; Pulignani, Silvia; Baffigi, Federica; Fulgentini, Lorenzo; Koester, Petra; Cresci, Monica; Vecoli, Cecilia; Lamia, Debora; Russo, Giorgio; Panetta, Daniele; Tripodi, Maria; Gizzi, Leonida A; Labate, Luca
2016-09-01
Laser-driven electron accelerators are capable of producing high-energy electron bunches in shorter distances than conventional radiofrequency accelerators. To date, our knowledge of the radiobiological effects in cells exposed to electrons using a laser-plasma accelerator is still very limited. In this study, we compared the dose-response curves for micronucleus (MN) frequency and telomere length in peripheral blood lymphocytes exposed to laser-driven electron pulse and X-ray radiations. Additionally, we evaluated the effects on cell survival of in vitro tumor cells after exposure to laser-driven electron pulse compared to electron beams produced by a conventional radiofrequency accelerator used for intraoperative radiation therapy. Blood samples from two different donors were exposed to six radiation doses ranging from 0 to 2 Gy. Relative biological effectiveness (RBE) for micronucleus induction was calculated from the alpha coefficients for electrons compared to X rays (RBE = alpha laser/alpha X rays). Cell viability was monitored in the OVCAR-3 ovarian cancer cell line using trypan blue exclusion assay at day 3, 5 and 7 postirradiation (2, 4, 6, 8 and 10 Gy). The RBE values obtained by comparing the alpha values were 1.3 and 1.2 for the two donors. Mean telomere length was also found to be reduced in a significant dose-dependent manner after irradiation with both electrons and X rays in both donors studied. Our findings showed a radiobiological response as mirrored by the induction of micronuclei and shortening of telomere as well as by the reduction of cell survival in blood samples and cancer cells exposed in vitro to laser-generated electron bunches. Additional studies are needed to improve preclinical validation of the radiobiological characteristics and efficacy of laser-driven electron accelerators in the future.
Numerical Modeling and Testing of an Inductively-Driven and High-Energy Pulsed Plasma Thrusters
NASA Technical Reports Server (NTRS)
Parma, Brian
2004-01-01
Pulsed Plasma Thrusters (PPTs) are advanced electric space propulsion devices that are characterized by simplicity and robustness. They suffer, however, from low thrust efficiencies. This summer, two approaches to improve the thrust efficiency of PPTs will be investigated through both numerical modeling and experimental testing. The first approach, an inductively-driven PPT, uses a double-ignition circuit to fire two PPTs in succession. This effectively changes the PPTs configuration from an LRC circuit to an LR circuit. The LR circuit is expected to provide better impedance matching and improving the efficiency of the energy transfer to the plasma. An added benefit of the LR circuit is an exponential decay of the current, whereas a traditional PPT s under damped LRC circuit experiences the characteristic "ringing" of its current. The exponential decay may provide improved lifetime and sustained electromagnetic acceleration. The second approach, a high-energy PPT, is a traditional PPT with a variable size capacitor bank. This PPT will be simulated and tested at energy levels between 100 and 450 joules in order to investigate the relationship between efficiency and energy level. Arbitrary Coordinate Hydromagnetic (MACH2) code is used. The MACH2 code, designed by the Center for Plasma Theory and Computation at the Air Force Research Laboratory, has been used to gain insight into a variety of plasma problems, including electric plasma thrusters. The goals for this summer include numerical predictions of performance for both the inductively-driven PPT and high-energy PFT, experimental validation of the numerical models, and numerical optimization of the designs. These goals will be met through numerical and experimental investigation of the PPTs current waveforms, mass loss (or ablation), and impulse bit characteristics.
Closed-loop torque feedback for a universal field-oriented controller
DOE Office of Scientific and Technical Information (OSTI.GOV)
De Doncker, R.W.A.A.; King, R.D.; Sanza, P.C.
A torque feedback system is employed in a universal field-oriented (UFO) controller to tune a torque-producing current command and a slip frequency command in order to achieve robust torque control of an induction machine even in the event of current regulator errors and during transitions between pulse width modulated (PWM) and square wave modes of operation. 1 figure.
Closed-loop torque feedback for a universal field-oriented controller
De Doncker, R.W.A.A.; King, R.D.; Sanza, P.C.; Haefner, K.B.
1992-11-24
A torque feedback system is employed in a universal field-oriented (UFO) controller to tune a torque-producing current command and a slip frequency command in order to achieve robust torque control of an induction machine even in the event of current regulator errors and during transitions between pulse width modulated (PWM) and square wave modes of operation. 1 figure.
Closed-loop torque feedback for a universal field-oriented controller
DOE Office of Scientific and Technical Information (OSTI.GOV)
De Doncker, Rik W. A. A.; King, Robert D.; Sanza, Peter C.
A torque feedback system is employed in a universal field-oriented (UFO) controller to tune a torque-producing current command and a slip frequency command in order to achieve robust torque control of an induction machine even in the event of current regulator errors and during transitions between pulse width modulated (PWM) and square wave modes of operation.
NASA Astrophysics Data System (ADS)
Shinohara, Katsuji; Shinhatsubo, Kurato; Iimori, Kenichi; Yamamoto, Kichiro; Saruban, Takamichi; Yamaemori, Takahiro
In recent year, consciousness of environmental problems is enhancing, and the price of the electric power purchased by an electric power company is established expensive for the power plant utilizing the natural energy. So, the introduction of the wind power generation is promoted in Japan. Generally, squirrel-cage induction machines are widely used as a generator in wind power generation system because of its small size, lightweight and low-cost. However, the induction machines do not have a source of excitation. Thus, it causes the inrush currents and the instantaneous voltage drop when the generator is directly connected to a power grid. To reduce the inrush currents, an AC power regulator is used. Wind power generations are frequently connected to and disconnected from the power grid. However, when the inrush currents are reduced, harmonic currents are caused by phase control of the AC power regulator. And the phase control of AC power regulator cannot control the power factor. Therefore, we propose the use of the AC power regulator to compensate for the harmonic currents and reactive power in the wind power generation system, and demonstrate the validity of its system by simulated and experimental results.
Integrating machine learning and physician knowledge to improve the accuracy of breast biopsy.
Dutra, I; Nassif, H; Page, D; Shavlik, J; Strigel, R M; Wu, Y; Elezaby, M E; Burnside, E
2011-01-01
In this work we show that combining physician rules and machine learned rules may improve the performance of a classifier that predicts whether a breast cancer is missed on percutaneous, image-guided breast core needle biopsy (subsequently referred to as "breast core biopsy"). Specifically, we show how advice in the form of logical rules, derived by a sub-specialty, i.e. fellowship trained breast radiologists (subsequently referred to as "our physicians") can guide the search in an inductive logic programming system, and improve the performance of a learned classifier. Our dataset of 890 consecutive benign breast core biopsy results along with corresponding mammographic findings contains 94 cases that were deemed non-definitive by a multidisciplinary panel of physicians, from which 15 were upgraded to malignant disease at surgery. Our goal is to predict upgrade prospectively and avoid surgery in women who do not have breast cancer. Our results, some of which trended toward significance, show evidence that inductive logic programming may produce better results for this task than traditional propositional algorithms with default parameters. Moreover, we show that adding knowledge from our physicians into the learning process may improve the performance of the learned classifier trained only on data.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gährs, Maike; Roos, Robert; Andersson, Patrik L.
Polychlorinated biphenyls (PCBs) are among the most ubiquitously detectable ‘persistent organic pollutants’. In contrast to ‘dioxinlike’ (DL) PCBs, less is known about the molecular mode of action of the larger group of the ‘non-dioxinlike’ (NDL) PCBs. Owing to the life-long exposure of the human population, a carcinogenic, i.e., tumor-promoting potency of NDL-PCBs has to be considered in human risk assessment. A major problem in risk assessment of NDL-PCBs is dioxin-like impurities that can occur in commercially available NDL-PCB standards. In the present study, we analyzed the induction of CYP2B1 and CYP3A1 in primary rat hepatocytes using a number of highlymore » purified NDL-PCBs with various degrees of chlorination and substitution patterns. Induction of these enzymes is mediated by the nuclear xenobiotic receptors CAR (Constitutive androstane receptor) and PXR (Pregnane X receptor). For CYP2B1 induction, concentration–response analysis revealed a very narrow window of EC{sub 50} estimates, being in the range of 1–4 μM for PCBs 28 and 52, and between 0.4 and 1 μM for PCBs 101, 138, 153 and 180. CYP3A1 induction was less sensitive to NDL-PCBs, the most pronounced induction being achieved at 100 μM with the higher chlorinated congeners. Using okadaic acid and small interfering RNAs targeting CAR and PXR, we could demonstrate that CAR plays a major role and PXR a minor role in NDL-PCB-driven induction of CYPs, both effects showing no stringent structure–activity relationship. As the only obvious relevant determinant, the degree of chlorination was found to be positively correlated with the inducing potency of the congeners. - Highlights: • We analyzed six highly purified NDL-PCBs for CYP2B1 and CYP3A1 expression. • CAR plays a major, PXR a minor role in NDL-PCB-driven induction of CYPs. • The degree of chlorination seems to be the major parameter for the inducing potency. • There exists a competition between CAR and PXR. • Activated PXR may antagonize CAR binding to the CYP2B1 promoter.« less
Perspective: Interactive material property databases through aggregation of literature data
NASA Astrophysics Data System (ADS)
Seshadri, Ram; Sparks, Taylor D.
2016-05-01
Searchable, interactive, databases of material properties, particularly those relating to functional materials (magnetics, thermoelectrics, photovoltaics, etc.) are curiously missing from discussions of machine-learning and other data-driven methods for advancing new materials discovery. Here we discuss the manual aggregation of experimental data from the published literature for the creation of interactive databases that allow the original experimental data as well additional metadata to be visualized in an interactive manner. The databases described involve materials for thermoelectric energy conversion, and for the electrodes of Li-ion batteries. The data can be subject to machine-learning, accelerating the discovery of new materials.
Wind utilization in remote regions: An economic study. [for comparison with diesel engines
NASA Technical Reports Server (NTRS)
Vansant, J. H.
1973-01-01
A wind driven generator was considered as a supplement to a diesel group, for the purpose of economizing fuel when wind power is available. A specific location on Hudson's Bay, Povognituk, was selected. Technical and economic data available for a wind machine of 10-kilowatt nominal capacity and available wind data for that region were used for the study. After subtracting the yearly wind machine costs from savings in fuel costs, a net savings of $1400 per year is realized. These values are approximate, but are though to be highly conservative.
Non-inductively driven tokamak plasmas at near-unity βt in the Pegasus toroidal experiment
NASA Astrophysics Data System (ADS)
Reusch, J. A.; Bodner, G. M.; Bongard, M. W.; Burke, M. G.; Fonck, R. J.; Pachicano, J. L.; Perry, J. M.; Pierren, C.; Rhodes, A. T.; Richner, N. J.; Rodriguez Sanchez, C.; Schlossberg, D. J.; Weberski, J. D.
2018-05-01
A major goal of the spherical tokamak (ST) research program is accessing a state of low internal inductance ℓi, high elongation κ, and high toroidal and normalized beta ( βt and βN) without solenoidal current drive. Local helicity injection (LHI) in the Pegasus ST [Garstka et al., Nucl. Fusion 46, S603 (2006)] provides non-solenoidally driven plasmas that exhibit these characteristics. LHI utilizes compact, edge-localized current sources for plasma startup and sustainment. It results in hollow current density profiles with low ℓi. The low aspect ratio ( R0/a ˜1.2 ) of Pegasus allows access to high κ and high normalized plasma currents ( IN=Ip/a BT>14 ). Magnetic reconnection during LHI provides auxiliary ion heating. Together, these features provide access to very high βt plasmas. Equilibrium analyses indicate that βt up to ˜100% is achieved. These high βt discharges disrupt at the ideal no-wall β limit at βN˜7.
NASA Astrophysics Data System (ADS)
Beaumont, Samuel; Otero, Toribio F.
2018-07-01
Polypyrrole film electrodes are constituted by multielectronic electrochemical molecular machines (every polymeric molecule) counterions and water, mimicking the intracellular matrix of muscular cells. The influence of the electrolyte concentration on the reversible oxidation/reduction of polypyrrole films was studied in NaCl aqueous solutions by consecutive square potential waves. The consumed redox charge and the consumed electrical energy change as a function of the concentration. That means that the extension (the consumed charge) of the reaction involving conformational, or allosteric, movements of the reacting polymeric chains (molecular machines) responds to (senses) the chemical energy of the reaction ambient. A theoretical description of the attained empirical results is presented getting the sensing equations and the concomitant sensitivities. Those results could indicate the origin and nature of the neural signals sent to the brain from biological haptic muscles working by cooperative actuation of the actin-myosin molecular machines driven by chemical reactions and sensing, simultaneously, the fatigue state of the muscle.
Positional reference system for ultraprecision machining
Arnold, J.B.; Burleson, R.R.; Pardue, R.M.
1980-09-12
A stable positional reference system for use in improving the cutting tool-to-part contour position in numerical controlled-multiaxis metal turning machines is provided. The reference system employs a plurality of interferometers referenced to orthogonally disposed metering bars which are substantially isolated from machine strain induced position errors for monitoring the part and tool positions relative to the metering bars. A microprocessor-based control system is employed in conjunction with the plurality of positions interferometers and part contour description data input to calculate error components for each axis of movement and output them to corresponding axis driven with appropriate scaling and error compensation. Real-time position control, operating in combination with the reference system, makes possible the positioning of the cutting points of a tool along a part locus with a substantially greater degree of accuracy than has been attained previously in the art by referencing and then monitoring only the tool motion relative to a reference position located on the machine base.
Comparing Characteristics of Highly Circulated Titles for Demand-Driven Collection Development.
ERIC Educational Resources Information Center
Britten, William A; Webster, Judith D.
1992-01-01
Describes methodology for analyzing MARC (machine-readable cataloging) records of highly circulating titles to document common characteristics for collection development purposes. Application of the methodology in a university library is discussed, and data are presented on commonality of subject heading, author, language, and imprint date for…
30 CFR 18.48 - Circuit-interrupting devices.
Code of Federal Regulations, 2010 CFR
2010-07-01
..., AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Construction and.... Such a switch shall be designed to prevent electrical connection to the machine frame when the cable is... motor in the event the belt is stopped, or abnormally slowed down. Note: Short transfer-type conveyors...
18 CFR 367.3940 - Account 394, Tools, shop and garage equipment.
Code of Federal Regulations, 2010 CFR
2010-04-01
...) Ladders. (21) Lathes. (22) Machine tools. (23) Motor-driven tools. (24) Motors. (25) Pipe threading and..., shop and garage equipment. 367.3940 Section 367.3940 Conservation of Power and Water Resources FEDERAL... equipment. (a) This account must include the cost of tools, implements, and equipment used in construction...
Location-Driven Image Retrieval for Images Collected by a Mobile Robot
NASA Astrophysics Data System (ADS)
Tanaka, Kanji; Hirayama, Mitsuru; Okada, Nobuhiro; Kondo, Eiji
Mobile robot teleoperation is a method for a human user to interact with a mobile robot over time and distance. Successful teleoperation depends on how well images taken by the mobile robot are visualized to the user. To enhance the efficiency and flexibility of the visualization, an image retrieval system on such a robot’s image database would be very useful. The main difference of the robot’s image database from standard image databases is that various relevant images exist due to variety of viewing conditions. The main contribution of this paper is to propose an efficient retrieval approach, named location-driven approach, utilizing correlation between visual features and real world locations of images. Combining the location-driven approach with the conventional feature-driven approach, our goal can be viewed as finding an optimal classifier between relevant and irrelevant feature-location pairs. An active learning technique based on support vector machine is extended for this aim.
Condition monitoring of Electric Components
NASA Astrophysics Data System (ADS)
Zaman, Ishtiaque
A universal non-intrusive model of a flexible antenna array is presented in this paper to monitor and identify the failures in electric machines. This adjustable antenna is designed to serve the purpose of condition monitoring of a vast range of electrical components including Induction Motor (IM), Printed Circuit Board (PCB), Synchronous Reluctance Motor (SRM), Permanent Magnet Synchronous Machine (PMSM) etc. by capturing the low frequency magnetic field radiated around these machines. The basic design and specification of the proposed antenna array for low frequency components is portrayed first. The design of the antenna is adjustable to fit for an extensive variety of segments. Subsequent to distinguishing the design and specifications of the antenna, the ideal area of the most delicate stray field has been identified for healthy current streaming around the machineries. Following this, short circuit representing faulty situation has been introduced and compared with the healthy cases. Precision has been found recognizing the faults using this one generic model of Antenna and the results are presented for three different machines i.e. IM, SRM and PMSM. Finite element method has been used to design the antenna and detect the optimum location and faults in the machines. Finally, a 3D Printer is proposed to be employed to build the antenna as per the details tended to in this paper contingent upon the power segments.
NASA Astrophysics Data System (ADS)
Alzubaidi, Mohammad; Balasubramanian, Vineeth; Patel, Ameet; Panchanathan, Sethuraman; Black, John A., Jr.
2012-03-01
Inductive learning refers to machine learning algorithms that learn a model from a set of training data instances. Any test instance is then classified by comparing it to the learned model. When the set of training instances lend themselves well to modeling, the use of a model substantially reduces the computation cost of classification. However, some training data sets are complex, and do not lend themselves well to modeling. Transductive learning refers to machine learning algorithms that classify test instances by comparing them to all of the training instances, without creating an explicit model. This can produce better classification performance, but at a much higher computational cost. Medical images vary greatly across human populations, constituting a data set that does not lend itself well to modeling. Our previous work showed that the wide variations seen across training sets of "normal" chest radiographs make it difficult to successfully classify test radiographs with an inductive (modeling) approach, and that a transductive approach leads to much better performance in detecting atypical regions. The problem with the transductive approach is its high computational cost. This paper develops and demonstrates a novel semi-transductive framework that can address the unique challenges of atypicality detection in chest radiographs. The proposed framework combines the superior performance of transductive methods with the reduced computational cost of inductive methods. Our results show that the proposed semitransductive approach provides both effective and efficient detection of atypical regions within a set of chest radiographs previously labeled by Mayo Clinic expert thoracic radiologists.
Effective switching frequency multiplier inverter
Su, Gui-Jia [Oak Ridge, TN; Peng, Fang Z [Okemos, MI
2007-08-07
A switching frequency multiplier inverter for low inductance machines that uses parallel connection of switches and each switch is independently controlled according to a pulse width modulation scheme. The effective switching frequency is multiplied by the number of switches connected in parallel while each individual switch operates within its limit of switching frequency. This technique can also be used for other power converters such as DC/DC, AC/DC converters.
Torque Generation Mechanism of F1-ATPase upon NTP Binding
Arai, Hidenobu C.; Yukawa, Ayako; Iwatate, Ryu John; Kamiya, Mako; Watanabe, Rikiya; Urano, Yasuteru; Noji, Hiroyuki
2014-01-01
Molecular machines fueled by NTP play pivotal roles in a wide range of cellular activities. One common feature among NTP-driven molecular machines is that NTP binding is a major force-generating step among the elementary reaction steps comprising NTP hydrolysis. To understand the mechanism in detail,in this study, we conducted a single-molecule rotation assay of the ATP-driven rotary motor protein F1-ATPase using uridine triphosphate (UTP) and a base-free nucleotide (ribose triphosphate) to investigate the impact of a pyrimidine base or base depletion on kinetics and force generation. Although the binding rates of UTP and ribose triphosphate were 103 and 106 times, respectively, slower than that of ATP, they supported rotation, generating torque comparable to that generated by ATP. Affinity change of F1 to UTP coupled with rotation was determined, and the results again were comparable to those for ATP, suggesting that F1 exerts torque upon the affinity change to UTP via rotation similar to ATP-driven rotation. Thus, the adenine-ring significantly enhances the binding rate, although it is not directly involved in force generation. Taking into account the findings from another study on F1 with mutated phosphate-binding residues, it was proposed that progressive bond formation between the phosphate region and catalytic residues is responsible for the rotation-coupled change in affinity. PMID:24988350
Th and U fuel photofission study by NTD for AD-MSR subcritical assembly
NASA Astrophysics Data System (ADS)
Sajo-Bohus, Laszlo; Greaves, Eduardo D.; Davila, Jesus; Barros, Haydn; Pino, Felix; Barrera, Maria T.; Farina, Fulvio
2015-07-01
During the last decade a considerable effort has been devoted for developing energy generating systems based on advanced nuclear technology within the design concepts of GEN-IV. Thorium base fuel systems such as accelerator driven nuclear reactors are one of the often mentioned attractive and affordable options. Several radiotherapy linear accelerators are on the market and due to their reliability, they could be employed as drivers for subcritical liquid fuel assemblies. Bremsstrahlung photons with energies above 5.5MeV, induce (γ,n) and (e,e'n) reactions in the W-target. Resulting gamma radiation and photo or fission neutrons may be absorbed in target materials such as thorium and uranium isotopes to induce sustained fission or nuclear transmutation in waste radioactive materials. Relevant photo driven and photo-fission reaction cross sections are important for actinides 232Th, 238U and 237Np in the radiotherapy machines energy range of 10-20 MV. In this study we employ passive nuclear track detectors (NTD) to determine fission rates and neutron production rates with the aim to establish the feasibility for gamma and photo-neutron driven subcritical assemblies. To cope with these objectives a 20 MV radiotherapy machine has been employed with a mixed fuel target. Results will support further development for a subcritical assembly employing a thorium containing liquid fuel. It is expected that acquired technological knowledge will contribute to the Venezuelan nuclear energy program.
Evolving rule-based systems in two medical domains using genetic programming.
Tsakonas, Athanasios; Dounias, Georgios; Jantzen, Jan; Axer, Hubertus; Bjerregaard, Beth; von Keyserlingk, Diedrich Graf
2004-11-01
To demonstrate and compare the application of different genetic programming (GP) based intelligent methodologies for the construction of rule-based systems in two medical domains: the diagnosis of aphasia's subtypes and the classification of pap-smear examinations. Past data representing (a) successful diagnosis of aphasia's subtypes from collaborating medical experts through a free interview per patient, and (b) correctly classified smears (images of cells) by cyto-technologists, previously stained using the Papanicolaou method. Initially a hybrid approach is proposed, which combines standard genetic programming and heuristic hierarchical crisp rule-base construction. Then, genetic programming for the production of crisp rule based systems is attempted. Finally, another hybrid intelligent model is composed by a grammar driven genetic programming system for the generation of fuzzy rule-based systems. Results denote the effectiveness of the proposed systems, while they are also compared for their efficiency, accuracy and comprehensibility, to those of an inductive machine learning approach as well as to those of a standard genetic programming symbolic expression approach. The proposed GP-based intelligent methodologies are able to produce accurate and comprehensible results for medical experts performing competitive to other intelligent approaches. The aim of the authors was the production of accurate but also sensible decision rules that could potentially help medical doctors to extract conclusions, even at the expense of a higher classification score achievement.
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.
Cheek, Julianne; Lipschitz, David L; Abrams, Elizabeth M; Vago, David R; Nakamura, Yoshio
2015-06-01
Dynamic reflexivity is central to enabling flexible and emergent qualitatively driven inductive mixed-method and multiple methods research designs. Yet too often, such reflexivity, and how it is used at various points of a study, is absent when we write our research reports. Instead, reports of mixed-method and multiple methods research focus on what was done rather than how it came to be done. This article seeks to redress this absence of emphasis on the reflexive thinking underpinning the way that mixed- and multiple methods, qualitatively driven research approaches are thought about and subsequently used throughout a project. Using Morse's notion of an armchair walkthrough, we excavate and explore the layers of decisions we made about how, and why, to use qualitatively driven mixed-method and multiple methods research in a study of mindfulness training (MT) in schoolchildren. © The Author(s) 2015.
Grumman WS33 wind system: prototype construction and testing, Phase II technical report
DOE Office of Scientific and Technical Information (OSTI.GOV)
Adler, F.M.; Henton, P.; King, P.W.
1980-11-01
The prototype fabrication and testing of the 8 kW small wind energy conversion system are reported. The turbine is a three-bladed, down-wind machine designed to interface directly with an electrical utility network. The machine as finally fabricated is rated at 15 kW at 24 mpH and peak power of 18 kW at 35 mph. Utility compatible electrical power is generated in winds between a cut-in speed of 9 mph and a cut-out speed of 35 mph by using the torque characteristics of the unit's induction generator combined with the rotor aerodynamics to maintain essentially constant speed. Inspection procedures, pre-delivery testing,more » and a cost analysis are included.« less
Dental cutting behaviour of mica-based and apatite-based machinable glass-ceramics.
Taira, M; Wakasa, K; Yamaki, M; Matsui, A
1990-09-01
Some recently developed industrial ceramics have excellent machinability properties. The objective of this study was to evaluate the dental cutting behaviour of two machinable glass-ceramics, mica-containing Macor-M and apatite- and diopside-containing Bioram-M, and to compare them with the cutting behaviour of a composite resin typodont tooth enamel and bovine enamel. Weight-load cutting tests were conducted, using a diamond point driven by an air-turbine handpiece, While the transverse load applied on the point was varied, the handpiece speed during cutting and the volume of removal upon cutting were measured. In general, an increase in the applied load caused a decrease in cutting speed and an increase in cutting volume. However, the intensity of this trend was found to differ between four workpieces. Cutting Macor-M resulted in the second-most reduced cutting speed and the maximum cutting volume. Cutting Bioram-M gave the least reduced cutting speed and the minimum cutting volume. It was suggested that two machinable glass-ceramics could be employed as typodont teeth. This study may also contribute to the development of new restorative dental ceramic materials, prepared by machining.
NASA Technical Reports Server (NTRS)
Laue, H. H.; Clough, L. G. (Inventor)
1973-01-01
An electrodeless lamp circuit with a coil surrounding a krypton lamp is driven by an RF input source. A coil surrounding a mercury lamp is tapped across the connection of the input central to the krypton-lamp coil. Each coil is connected in parallel with separate capacitors which form resonant circuits at the input frequency.
TAL effector driven induction of a SWEET gene confers susceptibility to bacterial blight of cotton
USDA-ARS?s Scientific Manuscript database
Bacterial blight of cotton (BBC), caused by Xanthomonas citri subsp. malvacearum (Xcm), is among the most destructive diseases in cotton (Gossypium spp.). Transcription activator-like (TAL) effectors from Xcm are essential for BBC disease progression. Here, we carried out whole-genome PacBio-seque...
Generalized SMO algorithm for SVM-based multitask learning.
Cai, Feng; Cherkassky, Vladimir
2012-06-01
Exploiting additional information to improve traditional inductive learning is an active research area in machine learning. In many supervised-learning applications, training data can be naturally separated into several groups, and incorporating this group information into learning may improve generalization. Recently, Vapnik proposed a general approach to formalizing such problems, known as "learning with structured data" and its support vector machine (SVM) based optimization formulation called SVM+. Liang and Cherkassky showed the connection between SVM+ and multitask learning (MTL) approaches in machine learning, and proposed an SVM-based formulation for MTL called SVM+MTL for classification. Training the SVM+MTL classifier requires the solution of a large quadratic programming optimization problem which scales as O(n(3)) with sample size n. So there is a need to develop computationally efficient algorithms for implementing SVM+MTL. This brief generalizes Platt's sequential minimal optimization (SMO) algorithm to the SVM+MTL setting. Empirical results show that, for typical SVM+MTL problems, the proposed generalized SMO achieves over 100 times speed-up, in comparison with general-purpose optimization routines.
Kennedy, Deborah A.; Cooley, Kieran; Einarson, Thomas R.; Seely, Dugald
2012-01-01
Ionic footbaths are often used in holistic health centres and spas to aid in detoxification; however, claims that these machines eliminate toxins from the body have not been rigorously evaluated. In this proof-of-principle study, we sought to measure the release of potentially toxic elements from ionic footbaths into distilled and tap water with and without feet. Water samples were collected and analyzed following 30-minute ionic footbath sessions without feet using both distilled (n = 1) and tap water (n = 6) and following four ionic footbaths using tap water (once/week for 4 weeks) in six healthy participants. Urine collection samples were analyzed at four points during the study. Hair samples were analyzed for element concentrations at baseline and study conclusion. Contrary to claims made for the machine, there does not appear to be any specific induction of toxic element release through the feet when running the machine according to specifications. PMID:22174728
Code of Federal Regulations, 2010 CFR
2010-07-01
..., art work, work in advertising departments, window trimming, and comparative shopping; (3) Price...) Cashiering, selling, modeling, art work, work in advertising departments, window trimming, and comparative... or portable machines or tools driven by power and used or designed for cutting, shaping, forming...
From Sci-Fi to Reality--Mobile Robots Get the Job Done
ERIC Educational Resources Information Center
Roman, Harry T.
2006-01-01
Robots are simply computers that can interact with their environment. Some are fixed in place in industrial assembly plants for cars, appliances, micro electronic circuitry, and pharmaceuticals. Another important category of robots is the mobiles, machines that can be driven to the workplace, often designed for hazardous duty operation or…
30 CFR 18.99 - Notice of approval or disapproval; letters of approval and approval plates.
Code of Federal Regulations, 2010 CFR
2010-07-01
... approval or disapproval of the machine. (a) If the qualified electrical representative recommends field..., DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Field Approval of Electrically Operated Mining Equipment § 18.99 Notice of approval or...
30 CFR 18.99 - Notice of approval or disapproval; letters of approval and approval plates.
Code of Federal Regulations, 2011 CFR
2011-07-01
... approval or disapproval of the machine. (a) If the qualified electrical representative recommends field..., DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Field Approval of Electrically Operated Mining Equipment § 18.99 Notice of approval or...
A new software-based architecture for quantum computer
NASA Astrophysics Data System (ADS)
Wu, Nan; Song, FangMin; Li, Xiangdong
2010-04-01
In this paper, we study a reliable architecture of a quantum computer and a new instruction set and machine language for the architecture, which can improve the performance and reduce the cost of the quantum computing. We also try to address some key issues in detail in the software-driven universal quantum computers.
Sklar, A E; Sarter, N B
1999-12-01
Observed breakdowns in human-machine communication can be explained, in part, by the nature of current automation feedback, which relies heavily on focal visual attention. Such feedback is not well suited for capturing attention in case of unexpected changes and events or for supporting the parallel processing of large amounts of data in complex domains. As suggested by multiple-resource theory, one possible solution to this problem is to distribute information across various sensory modalities. A simulator study was conducted to compare the effectiveness of visual, tactile, and redundant visual and tactile cues for indicating unexpected changes in the status of an automated cockpit system. Both tactile conditions resulted in higher detection rates for, and faster response times to, uncommanded mode transitions. Tactile feedback did not interfere with, nor was its effectiveness affected by, the performance of concurrent visual tasks. The observed improvement in task-sharing performance indicates that the introduction of tactile feedback is a promising avenue toward better supporting human-machine communication in event-driven, information-rich domains.
Dissipative structures, machines, and organisms: A perspective
NASA Astrophysics Data System (ADS)
Kondepudi, Dilip; Kay, Bruce; Dixon, James
2017-10-01
Self-organization in nonequilibrium systems resulting in the formation of dissipative structures has been studied in a variety of systems, most prominently in chemical systems. We present a study of a voltage-driven dissipative structure consisting of conducting beads immersed in a viscous medium of oil. In this simple system, we observed remarkably complex organism-like behavior. The dissipative structure consists of a tree structure that spontaneously forms and moves like a worm and exhibits many features characteristic of living organisms. The complex motion of the beads driven by the applied field, the dipole-dipole interaction between the beads, and the hydrodynamic flow of the viscous medium result in a time evolution of the tree structure towards states of lower resistance or higher dissipation and thus higher rates of entropy production. The resulting end-directed evolution manifests as the tree moving to locations seeking higher current, the current that sustains its structure and dynamics. The study of end-directed evolution in the dissipative structure gives us a means to distinguish the fundamental difference between machines and organisms and opens a path for the formulation of physics of organisms.
Janet, Jon Paul; Chan, Lydia; Kulik, Heather J
2018-03-01
Machine learning (ML) has emerged as a powerful complement to simulation for materials discovery by reducing time for evaluation of energies and properties at accuracy competitive with first-principles methods. We use genetic algorithm (GA) optimization to discover unconventional spin-crossover complexes in combination with efficient scoring from an artificial neural network (ANN) that predicts spin-state splitting of inorganic complexes. We explore a compound space of over 5600 candidate materials derived from eight metal/oxidation state combinations and a 32-ligand pool. We introduce a strategy for error-aware ML-driven discovery by limiting how far the GA travels away from the nearest ANN training points while maximizing property (i.e., spin-splitting) fitness, leading to discovery of 80% of the leads from full chemical space enumeration. Over a 51-complex subset, average unsigned errors (4.5 kcal/mol) are close to the ANN's baseline 3 kcal/mol error. By obtaining leads from the trained ANN within seconds rather than days from a DFT-driven GA, this strategy demonstrates the power of ML for accelerating inorganic material discovery.
A Machine-Learning-Driven Sky Model.
Satylmys, Pynar; Bashford-Rogers, Thomas; Chalmers, Alan; Debattista, Kurt
2017-01-01
Sky illumination is responsible for much of the lighting in a virtual environment. A machine-learning-based approach can compactly represent sky illumination from both existing analytic sky models and from captured environment maps. The proposed approach can approximate the captured lighting at a significantly reduced memory cost and enable smooth transitions of sky lighting to be created from a small set of environment maps captured at discrete times of day. The author's results demonstrate accuracy close to the ground truth for both analytical and capture-based methods. The approach has a low runtime overhead, so it can be used as a generic approach for both offline and real-time applications.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Randolph, B.
Composite liners have been fabricated for the Los Alamos liner driven HEDP experiments using impactors formed by physical vapor deposition (PVD), electroplating, machining and shrink fitting. Chemical vapor deposition (CVD) has been proposed for some ATLAS liner applications. This paper describes the processes used to fabricate machined and shrink fitted impactors which have been used for copper impactors in 1100 aluminum liners and 6061 T-6 aluminum impactors in 1100 aluminum liners. The most successful processes have been largely empirically developed and rely upon a combination of shrink fitted and light press fitting. The processes used to date will be describedmore » along with some considerations for future composite liners requirements in the HEDP Program.« less
Solazzi, Massimiliano; Loconsole, Claudio; Barsotti, Michele
2016-01-01
This paper illustrates the application of emerging technologies and human-machine interfaces to the neurorehabilitation and motor assistance fields. The contribution focuses on wearable technologies and in particular on robotic exoskeleton as tools for increasing freedom to move and performing Activities of Daily Living (ADLs). This would result in a deep improvement in quality of life, also in terms of improved function of internal organs and general health status. Furthermore, the integration of these robotic systems with advanced bio-signal driven human-machine interface can increase the degree of participation of patient in robotic training allowing to recognize user's intention and assisting the patient in rehabilitation tasks, thus representing a fundamental aspect to elicit motor learning PMID:28484314
NASA Astrophysics Data System (ADS)
Glazebrook, R. T.
2016-10-01
1. Electrostatics: fundamental facts; 2. Electricity as a measurable quantity; 3. Measurement of electric force and potential; 4. Condensers; 5. Electrical machines; 6. Measurement of potential and electric force; 7. Magnetic attraction and repulsion; 8. Laws of magnetic force; 9. Experiments with magnets; 10. Magnetic calculations; 11. Magnetic measurements; 12. Terrestrial magnetism; 13. The electric current; 14. Relation between electromagnetic force and current; 15. Measurement of current; 16. Measurement of resistance and electromotive force; 17. Measurement of quantity of electricity, condensers; 18. Thermal activity of a current; 19. The voltaic cell (theory); 20. Electromagnetism; 21. Magnetisation of iron; 22. Electromagnetic instruments; 23. Electromagnetic induction; 24. Applications of electromagnetic induction; 25. Telegraphy and telephony; 26. Electric waves; 27. Transference of electricity through gases: corpuscles and electrons; Answers to examples; Index.
On controlling the flow behavior driven by induction electrohydrodynamics in microfluidic channels.
Li, Yanbo; Ren, Yukun; Liu, Weiyu; Chen, Xiaoming; Tao, Ye; Jiang, Hongyuan
2017-04-01
In this study, we develop a nondimensional physical model to demonstrate fluid flow at the micrometer dimension driven by traveling-wave induction electrohydrodynamics (EHD) through direct numerical simulation. In order to realize an enhancement in the pump flow rate as well as a flexible adjustment of anisotropy of flow behavior generated by induction EHD in microchannels, while not adding the risk of causing dielectric breakdown of working solution and material for insulation, a pair of synchronized traveling-wave voltage signals are imposed on double-sided electrode arrays that are mounted on the top and bottom insulating substrate, respectively. Accordingly, we present a model evidence, that not only the pump performance is improved evidently, but a variety of flow profiles, including the symmetrical and parabolic curve, plug-like shape and even biased flow behavior of quite high anisotropy are produced by the device design of "mix-type", "superimposition-type" and "adjustable-type" proposed herein as well, with the resulting controllable fluid motion being able to greatly facilitate an on-demand transportation mode of on-chip bio-microfluidic samples. Besides, automatic conversion in the direction of pump flow is achievable by switching on and off a second voltage wave. Our results provide utilitarian guidelines for constructing flexible electrokinetic framework useful in controllable transportation of particle and fluid samples in modern microfluidic systems. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Ardila-Rey, Jorge Alfredo; Rojas-Moreno, Mónica Victoria; Martínez-Tarifa, Juan Manuel; Robles, Guillermo
2014-02-19
Partial discharge (PD) detection is a standardized technique to qualify electrical insulation in machines and power cables. Several techniques that analyze the waveform of the pulses have been proposed to discriminate noise from PD activity. Among them, spectral power ratio representation shows great flexibility in the separation of the sources of PD. Mapping spectral power ratios in two-dimensional plots leads to clusters of points which group pulses with similar characteristics. The position in the map depends on the nature of the partial discharge, the setup and the frequency response of the sensors. If these clusters are clearly separated, the subsequent task of identifying the source of the discharge is straightforward so the distance between clusters can be a figure of merit to suggest the best option for PD recognition. In this paper, two inductive sensors with different frequency responses to pulsed signals, a high frequency current transformer and an inductive loop sensor, are analyzed to test their performance in detecting and separating the sources of partial discharges.
NASA Astrophysics Data System (ADS)
Aziri, Hasif; Patakor, Fizatul Aini; Sulaiman, Marizan; Salleh, Zulhisyam
2017-09-01
This paper presents the simulation of three-phase induction motor drives using Indirect Field Oriented Control (IFOC) in PSIM environment. The asynchronous machine is well known about natural limitations fact of highly nonlinearity and complexity of motor model. In order to resolve these problems, the IFOC is applied to control the instantaneous electrical quantities such as torque and flux component. As FOC is controlling the stator current that represented by a vector, the torque component is aligned with d coordinate while the flux component is aligned with q coordinate. There are five levels of the incremental system are gradually built up to verify and testing the software module in the system. Indeed, all of system build levels are verified and successfully tested in PSIM environment. Moreover, the corresponding system of five build levels are simulated in PSIM environment which is user-friendly for simulation studies in order to explore the performance of speed responses based on IFOC algorithm for three-phase induction motor drives.
Predictive modeling for corrective maintenance of imaging devices from machine logs.
Patil, Ravindra B; Patil, Meru A; Ravi, Vidya; Naik, Sarif
2017-07-01
In the cost sensitive healthcare industry, an unplanned downtime of diagnostic and therapy imaging devices can be a burden on the financials of both the hospitals as well as the original equipment manufacturers (OEMs). In the current era of connectivity, it is easier to get these devices connected to a standard monitoring station. Once the system is connected, OEMs can monitor the health of these devices remotely and take corrective actions by providing preventive maintenance thereby avoiding major unplanned downtime. In this article, we present an overall methodology of predicting failure of these devices well before customer experiences it. We use data-driven approach based on machine learning to predict failures in turn resulting in reduced machine downtime, improved customer satisfaction and cost savings for the OEMs. One of the use-case of predicting component failure of PHILIPS iXR system is explained in this article.
Distinguishing Asthma Phenotypes Using Machine Learning Approaches.
Howard, Rebecca; Rattray, Magnus; Prosperi, Mattia; Custovic, Adnan
2015-07-01
Asthma is not a single disease, but an umbrella term for a number of distinct diseases, each of which are caused by a distinct underlying pathophysiological mechanism. These discrete disease entities are often labelled as 'asthma endotypes'. The discovery of different asthma subtypes has moved from subjective approaches in which putative phenotypes are assigned by experts to data-driven ones which incorporate machine learning. This review focuses on the methodological developments of one such machine learning technique-latent class analysis-and how it has contributed to distinguishing asthma and wheezing subtypes in childhood. It also gives a clinical perspective, presenting the findings of studies from the past 5 years that used this approach. The identification of true asthma endotypes may be a crucial step towards understanding their distinct pathophysiological mechanisms, which could ultimately lead to more precise prevention strategies, identification of novel therapeutic targets and the development of effective personalized therapies.
Image Reconstruction is a New Frontier of Machine Learning.
Wang, Ge; Ye, Jong Chu; Mueller, Klaus; Fessler, Jeffrey A
2018-06-01
Over past several years, machine learning, or more generally artificial intelligence, has generated overwhelming research interest and attracted unprecedented public attention. As tomographic imaging researchers, we share the excitement from our imaging perspective [item 1) in the Appendix], and organized this special issue dedicated to the theme of "Machine learning for image reconstruction." This special issue is a sister issue of the special issue published in May 2016 of this journal with the theme "Deep learning in medical imaging" [item 2) in the Appendix]. While the previous special issue targeted medical image processing/analysis, this special issue focuses on data-driven tomographic reconstruction. These two special issues are highly complementary, since image reconstruction and image analysis are two of the main pillars for medical imaging. Together we cover the whole workflow of medical imaging: from tomographic raw data/features to reconstructed images and then extracted diagnostic features/readings.
Quantum ensembles of quantum classifiers.
Schuld, Maria; Petruccione, Francesco
2018-02-09
Quantum machine learning witnesses an increasing amount of quantum algorithms for data-driven decision making, a problem with potential applications ranging from automated image recognition to medical diagnosis. Many of those algorithms are implementations of quantum classifiers, or models for the classification of data inputs with a quantum computer. Following the success of collective decision making with ensembles in classical machine learning, this paper introduces the concept of quantum ensembles of quantum classifiers. Creating the ensemble corresponds to a state preparation routine, after which the quantum classifiers are evaluated in parallel and their combined decision is accessed by a single-qubit measurement. This framework naturally allows for exponentially large ensembles in which - similar to Bayesian learning - the individual classifiers do not have to be trained. As an example, we analyse an exponentially large quantum ensemble in which each classifier is weighed according to its performance in classifying the training data, leading to new results for quantum as well as classical machine learning.
Empathy promotes altruistic behavior in economic interactions
Klimecki, Olga M.; Mayer, Sarah V.; Jusyte, Aiste; Scheeff , Jonathan; Schönenberg, Michael
2016-01-01
What are the determinants of altruism? While economists assume that altruism is mainly driven by fairness norms, social psychologists consider empathy to be a key motivator for altruistic behavior. To unite these two theories, we conducted an experiment in which we compared behavior in a standard economic game that assesses altruism (the so-called Dictator Game) with a Dictator Game in which participants’ behavioral choices were preceded either by an empathy induction or by a control condition without empathy induction. The results of this within-subject manipulation show that the empathy induction substantially increased altruistic behavior. Moreover, the increase in experienced empathy predicted over 40% of the increase in sharing behavior. These data extend standard economic theories that altruism is based on fairness considerations, by showing that empathic feelings can be a key motivator for altruistic behavior in economic interactions. PMID:27578563
Welding of Aluminum Alloys to Steels: An Overview
2013-08-01
and deformations are a few examples of the unwanted consequences which somehow would lead to brittle fracture, fatigue fracture, shape instability...was made under the copper tips of the spot welding machine. The fatigue results showed higher fatigue strength of the joints with transition layer...kHz ultrasonic butt welding system with a vibration source applying eight bolt-clamped Langevin type PZT transducers and a 50 kW static induction
NASA Astrophysics Data System (ADS)
Nieten, Joseph L.; Burke, Roger
1993-03-01
The system diagnostic builder (SDB) is an automated knowledge acquisition tool using state- of-the-art artificial intelligence (AI) technologies. The SDB uses an inductive machine learning technique to generate rules from data sets that are classified by a subject matter expert (SME). Thus, data is captured from the subject system, classified by an expert, and used to drive the rule generation process. These rule-bases are used to represent the observable behavior of the subject system, and to represent knowledge about this system. The rule-bases can be used in any knowledge based system which monitors or controls a physical system or simulation. The SDB has demonstrated the utility of using inductive machine learning technology to generate reliable knowledge bases. In fact, we have discovered that the knowledge captured by the SDB can be used in any number of applications. For example, the knowledge bases captured from the SMS can be used as black box simulations by intelligent computer aided training devices. We can also use the SDB to construct knowledge bases for the process control industry, such as chemical production, or oil and gas production. These knowledge bases can be used in automated advisory systems to ensure safety, productivity, and consistency.
Fuzzy – PI controller to control the velocity parameter of Induction Motor
NASA Astrophysics Data System (ADS)
Malathy, R.; Balaji, V.
2018-04-01
The major application of Induction motor includes the usage of the same in industries because of its high robustness, reliability, low cost, highefficiency and good self-starting capability. Even though it has the above mentioned advantages, it also have some limitations: (1) the standard motor is not a true constant-speed machine, itsfull-load slip varies less than 1 % (in high-horsepower motors).And (2) it is not inherently capable of providing variable-speedoperation. In order to solve the above mentioned problem smart motor controls and variable speed controllers are used. Motor applications involve non linearity features, which can be controlled by Fuzzy logic controller as it is capable of handling those features with high efficiency and it act similar to human operator. This paper presents individuality of the plant modelling. The fuzzy logic controller (FLC)trusts on a set of linguistic if-then rules, a rule-based Mamdani for closed loop Induction Motor model. Themotor model is designed and membership functions are chosenaccording to the parameters of the motor model. Simulation results contains non linearity in induction motor model. A conventional PI controller iscompared practically to fuzzy logic controller using Simulink.
Xu, Wenjun; Chen, Jie; Lau, Henry Y K; Ren, Hongliang
2017-09-01
Accurate motion control of flexible surgical manipulators is crucial in tissue manipulation tasks. The tendon-driven serpentine manipulator (TSM) is one of the most widely adopted flexible mechanisms in minimally invasive surgery because of its enhanced maneuverability in torturous environments. TSM, however, exhibits high nonlinearities and conventional analytical kinematics model is insufficient to achieve high accuracy. To account for the system nonlinearities, we applied a data driven approach to encode the system inverse kinematics. Three regression methods: extreme learning machine (ELM), Gaussian mixture regression (GMR) and K-nearest neighbors regression (KNNR) were implemented to learn a nonlinear mapping from the robot 3D position states to the control inputs. The performance of the three algorithms was evaluated both in simulation and physical trajectory tracking experiments. KNNR performed the best in the tracking experiments, with the lowest RMSE of 2.1275 mm. The proposed inverse kinematics learning methods provide an alternative and efficient way to accurately model the tendon driven flexible manipulator. Copyright © 2016 John Wiley & Sons, Ltd.
A comparison of machine learning and Bayesian modelling for molecular serotyping.
Newton, Richard; Wernisch, Lorenz
2017-08-11
Streptococcus pneumoniae is a human pathogen that is a major cause of infant mortality. Identifying the pneumococcal serotype is an important step in monitoring the impact of vaccines used to protect against disease. Genomic microarrays provide an effective method for molecular serotyping. Previously we developed an empirical Bayesian model for the classification of serotypes from a molecular serotyping array. With only few samples available, a model driven approach was the only option. In the meanwhile, several thousand samples have been made available to us, providing an opportunity to investigate serotype classification by machine learning methods, which could complement the Bayesian model. We compare the performance of the original Bayesian model with two machine learning algorithms: Gradient Boosting Machines and Random Forests. We present our results as an example of a generic strategy whereby a preliminary probabilistic model is complemented or replaced by a machine learning classifier once enough data are available. Despite the availability of thousands of serotyping arrays, a problem encountered when applying machine learning methods is the lack of training data containing mixtures of serotypes; due to the large number of possible combinations. Most of the available training data comprises samples with only a single serotype. To overcome the lack of training data we implemented an iterative analysis, creating artificial training data of serotype mixtures by combining raw data from single serotype arrays. With the enhanced training set the machine learning algorithms out perform the original Bayesian model. However, for serotypes currently lacking sufficient training data the best performing implementation was a combination of the results of the Bayesian Model and the Gradient Boosting Machine. As well as being an effective method for classifying biological data, machine learning can also be used as an efficient method for revealing subtle biological insights, which we illustrate with an example.
Quantitative Machine Learning Analysis of Brain MRI Morphology throughout Aging.
Shamir, Lior; Long, Joe
2016-01-01
While cognition is clearly affected by aging, it is unclear whether the process of brain aging is driven solely by accumulation of environmental damage, or involves biological pathways. We applied quantitative image analysis to profile the alteration of brain tissues during aging. A dataset of 463 brain MRI images taken from a cohort of 416 subjects was analyzed using a large set of low-level numerical image content descriptors computed from the entire brain MRI images. The correlation between the numerical image content descriptors and the age was computed, and the alterations of the brain tissues during aging were quantified and profiled using machine learning. The comprehensive set of global image content descriptors provides high Pearson correlation of ~0.9822 with the chronological age, indicating that the machine learning analysis of global features is sensitive to the age of the subjects. Profiling of the predicted age shows several periods of mild changes, separated by shorter periods of more rapid alterations. The periods with the most rapid changes were around the age of 55, and around the age of 65. The results show that the process of brain aging of is not linear, and exhibit short periods of rapid aging separated by periods of milder change. These results are in agreement with patterns observed in cognitive decline, mental health status, and general human aging, suggesting that brain aging might not be driven solely by accumulation of environmental damage. Code and data used in the experiments are publicly available.
Design and Analysis of a Sensor System for Cutting Force Measurement in Machining Processes
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
Fingelkurts, Andrew A; Fingelkurts, Alexander A; Neves, Carlos F H
2012-01-05
Instead of using low-level neurophysiology mimicking and exploratory programming methods commonly used in the machine consciousness field, the hierarchical operational architectonics (OA) framework of brain and mind functioning proposes an alternative conceptual-theoretical framework as a new direction in the area of model-driven machine (robot) consciousness engineering. The unified brain-mind theoretical OA model explicitly captures (though in an informal way) the basic essence of brain functional architecture, which indeed constitutes a theory of consciousness. The OA describes the neurophysiological basis of the phenomenal level of brain organization. In this context the problem of producing man-made "machine" consciousness and "artificial" thought is a matter of duplicating all levels of the operational architectonics hierarchy (with its inherent rules and mechanisms) found in the brain electromagnetic field. We hope that the conceptual-theoretical framework described in this paper will stimulate the interest of mathematicians and/or computer scientists to abstract and formalize principles of hierarchy of brain operations which are the building blocks for phenomenal consciousness and thought. Copyright © 2010 Elsevier B.V. All rights reserved.
Open Architecture Data System for NASA Langley Combined Loads Test System
NASA Technical Reports Server (NTRS)
Lightfoot, Michael C.; Ambur, Damodar R.
1998-01-01
The Combined Loads Test System (COLTS) is a new structures test complex that is being developed at NASA Langley Research Center (LaRC) to test large curved panels and cylindrical shell structures. These structural components are representative of aircraft fuselage sections of subsonic and supersonic transport aircraft and cryogenic tank structures of reusable launch vehicles. Test structures are subjected to combined loading conditions that simulate realistic flight load conditions. The facility consists of two pressure-box test machines and one combined loads test machine. Each test machine possesses a unique set of requirements or research data acquisition and real-time data display. Given the complex nature of the mechanical and thermal loads to be applied to the various research test articles, each data system has been designed with connectivity attributes that support both data acquisition and data management functions. This paper addresses the research driven data acquisition requirements for each test machine and demonstrates how an open architecture data system design not only meets those needs but provides robust data sharing between data systems including the various control systems which apply spectra of mechanical and thermal loading profiles.
NASA Astrophysics Data System (ADS)
Afolalu, S. A.; Abioye, O. P.; Salawu, E. Y.; Okokpujie, I. P.; Abioye, A. A.; Omotosho, O. A.; Ajayi., O. O.
2018-04-01
Carburization is one the best heat treatment that responded well to hardening with Palm Kernel Shell giving the best hardness value. This work studied the influence of carburization on HSStool(ASTM A600) and its behaviour during machining of mild steel (ASTM A36). Composition of the samples (12 pieces of 180 × 12 × 12 mm) HSS tools were checked using UV-VIS spectrometer and the tools were carburized with PKS at holding temperatures and time of 800, 850, 900, 950 °C and 60,90 120 minutes using muffle furnance. The micro structural analysis, surface and core hardnessof the treated samples gave better results than the untreated samples when checked withsoft driven and optical microscope. It wasalso observed that increase in the feed rate and depth for length of cut of 50 mm significantly reduces the wear progression and thereby gave best machining time at maximum carburizing temperature and time(950 °C / 120 minutes) when it was used to cut mild steelon the lathe machine.
Design and Analysis of a Sensor System for Cutting Force Measurement in Machining Processes.
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.
Desired machines: cinema and the world in its own image.
Canales, Jimena
2011-09-01
In 1895 when the Lumière brothers unveiled their cinematographic camera, many scientists were elated. Scientists hoped that the machine would fulfill a desire that had driven research for nearly half a century: that of capturing the world in its own image. But their elation was surprisingly short-lived, and many researchers quickly distanced themselves from the new medium. The cinematographic camera was soon split into two machines, one for recording and one for projecting, enabling it to further escape from the laboratory. The philosopher Henri Bergson joined scientists, such as Etienne-Jules Marey, who found problems with the new cinematographic order. Those who had worked to make the dream come true found that their efforts had been subverted. This essay focuses on the desire to build a cinematographic camera, with the purpose of elucidating how dreams and reality mix in the development of science and technology. It is about desired machines and their often unexpected results. The interplay between what "is" (the technical), what "ought" (the ethical), and what "could" be (the fantastical) drives scientific research.
Certification of highly complex safety-related systems.
Reinert, D; Schaefer, M
1999-01-01
The BIA has now 15 years of experience with the certification of complex electronic systems for safety-related applications in the machinery sector. Using the example of machining centres this presentation will show the systematic procedure for verifying and validating control systems using Application Specific Integrated Circuits (ASICs) and microcomputers for safety functions. One section will describe the control structure of machining centres with control systems using "integrated safety." A diverse redundant architecture combined with crossmonitoring and forced dynamization is explained. In the main section the steps of the systematic certification procedure are explained showing some results of the certification of drilling machines. Specification reviews, design reviews with test case specification, statistical analysis, and walk-throughs are the analytical measures in the testing process. Systematic tests based on the test case specification, Electro Magnetic Interference (EMI), and environmental testing, and site acceptance tests on the machines are the testing measures for validation. A complex software driven system is always undergoing modification. Most of the changes are not safety-relevant but this has to be proven. A systematic procedure for certifying software modifications is presented in the last section of the paper.
NASA Astrophysics Data System (ADS)
Matsunaga, Y.; Sugita, Y.
2018-06-01
A data-driven modeling scheme is proposed for conformational dynamics of biomolecules based on molecular dynamics (MD) simulations and experimental measurements. In this scheme, an initial Markov State Model (MSM) is constructed from MD simulation trajectories, and then, the MSM parameters are refined using experimental measurements through machine learning techniques. The second step can reduce the bias of MD simulation results due to inaccurate force-field parameters. Either time-series trajectories or ensemble-averaged data are available as a training data set in the scheme. Using a coarse-grained model of a dye-labeled polyproline-20, we compare the performance of machine learning estimations from the two types of training data sets. Machine learning from time-series data could provide the equilibrium populations of conformational states as well as their transition probabilities. It estimates hidden conformational states in more robust ways compared to that from ensemble-averaged data although there are limitations in estimating the transition probabilities between minor states. We discuss how to use the machine learning scheme for various experimental measurements including single-molecule time-series trajectories.
Applying machine learning to identify autistic adults using imitation: An exploratory study.
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.
Han, Arnold; Newell, Evan W.; Glanville, Jacob; Fernandez-Becker, Nielsen; Khosla, Chaitan; Chien, Yueh-hsiu; Davis, Mark M.
2013-01-01
Celiac disease is an intestinal autoimmune disease driven by dietary gluten and gluten-specific CD4+ T-cell responses. In celiac patients on a gluten-free diet, exposure to gluten induces the appearance of gluten-specific CD4+ T cells with gut-homing potential in the peripheral blood. Here we show that gluten exposure also induces the appearance of activated, gut-homing CD8+ αβ and γδ T cells in the peripheral blood. Single-cell T-cell receptor sequence analysis indicates that both of these cell populations have highly focused T-cell receptor repertoires, indicating that their induction is antigen-driven. These results reveal a previously unappreciated role of antigen in the induction of CD8+ αβ and γδ T cells in celiac disease and demonstrate a coordinated response by all three of the major types of T cells. More broadly, these responses may parallel adaptive immune responses to viral pathogens and other systemic autoimmune diseases. PMID:23878218
Non-inductively driven tokamak plasmas at near-unity β t in the Pegasus toroidal experiment
Reusch, Joshua A.; Bodner, Grant M.; Bongard, Michael W.; ...
2018-03-14
Amore » major goal of the spherical tokamak (ST) research program is accessing a state of low internal inductance ℓ i , high elongation κ , and high toroidal and normalized beta ( β t and β N ) without solenoidal current drive. Local helicity injection (LHI) in the Pegasus ST [Garstka et al., Nucl. Fusion 46, S603 (2006)] provides non-solenoidally driven plasmas that exhibit these characteristics. LHI utilizes compact, edge-localized current sources for plasma startup and sustainment. It results in hollow current density profiles with low ℓ i . The low aspect ratio ( R 0 / a ~ 1.2 ) of Pegasus allows access to high κ and high normalized plasma currents I N = I p / a B T > 14 ). Magnetic reconnection during LHI provides auxiliary ion heating. Together, these features provide access to very high β t plasmas. Equilibrium analyses indicate that β t up to ~100% is achieved. Finally, these high β t discharges disrupt at the ideal no-wall β limit at β N ~ 7. « less
Non-inductively driven tokamak plasmas at near-unity β t in the Pegasus toroidal experiment
DOE Office of Scientific and Technical Information (OSTI.GOV)
Reusch, Joshua A.; Bodner, Grant M.; Bongard, Michael W.
Amore » major goal of the spherical tokamak (ST) research program is accessing a state of low internal inductance ℓ i , high elongation κ , and high toroidal and normalized beta ( β t and β N ) without solenoidal current drive. Local helicity injection (LHI) in the Pegasus ST [Garstka et al., Nucl. Fusion 46, S603 (2006)] provides non-solenoidally driven plasmas that exhibit these characteristics. LHI utilizes compact, edge-localized current sources for plasma startup and sustainment. It results in hollow current density profiles with low ℓ i . The low aspect ratio ( R 0 / a ~ 1.2 ) of Pegasus allows access to high κ and high normalized plasma currents I N = I p / a B T > 14 ). Magnetic reconnection during LHI provides auxiliary ion heating. Together, these features provide access to very high β t plasmas. Equilibrium analyses indicate that β t up to ~100% is achieved. Finally, these high β t discharges disrupt at the ideal no-wall β limit at β N ~ 7. « less
Steps toward Learning Mechanics Using Fan Cart Video Demonstrations
ERIC Educational Resources Information Center
Lattery, Mark
2011-01-01
The Newtonian force concept is very difficult for introductory students to learn. One obstacle to learning is a premature focus on gravity-driven motions, such as vertical free fall, rolling motion on an inclined plane, and the Atwood's machine. In each case, the main agent of motion ("gravity") cannot be seen, heard, or controlled by the student.…
Remote Photoregulated Ring Gliding in a [2]Rotaxane via a Molecular Effector.
Tron, Arnaud; Pianet, Isabelle; Martinez-Cuezva, Alberto; Tucker, James H R; Pisciottani, Luca; Alajarin, Mateo; Berna, Jose; McClenaghan, Nathan D
2017-01-06
A molecular barbiturate messenger, which is reversibly released/captured by a photoswitchable artificial molecular receptor, is shown to act as an effector to control ring gliding on a distant hydrogen-bonding [2]rotaxane. Thus, light-driven chemical communication governing the operation of a remote molecular machine is demonstrated using an information-rich neutral molecule.
Cutting Tool For Shaving Weld Beads
NASA Technical Reports Server (NTRS)
Hoffman, David S.; Mcferrin, David C.; Daniel, Ronald L., Jr.; Coby, John B., Jr.; Dawson, Sidney G.
1995-01-01
Cutting tool proposed for use in shaving weld beads flush with adjacent surfaces of weldments. Modified version of commercial pneumatically driven rotary cutting tool, cutting wheel of which turns at speeds sufficient for machining nickel alloys, titanium, and stainless steels. Equipped with forward-mounted handle and rear-mounted skid plate to maximize control and reduce dependence on skill of technician.
ERIC Educational Resources Information Center
Scherer, Marge
2015-01-01
After watching a shirt being wafted into the air as it dries over a hearth, the tinkerer Joseph Montgolfier decides to try lighting a fire under a balloon--and creates the first flying machine. After observing an art object swinging from a cathedral's ceiling, Galileo mulls over the mechanisms of a pendulum-driven clock--and produces one 50…
NASA Technical Reports Server (NTRS)
Ramachandran, Rahul; Word, Andrea; Nair, Udasysankar
2014-01-01
Threshold concepts in any discipline are the core concepts an individual must understand in order to master a discipline. By their very nature, these concepts are troublesome, irreversible, integrative, bounded, discursive, and reconstitutive. Although grasping threshold concepts can be extremely challenging for each learner as s/he moves through stages of cognitive development relative to a given discipline, the learner's grasp of these concepts determines the extent to which s/he is prepared to work competently and creatively within the field itself. The movement of individuals from a state of ignorance of these core concepts to one of mastery occurs not along a linear path but in iterative cycles of knowledge creation and adjustment in liminal spaces - conceptual spaces through which learners move from the vaguest awareness of concepts to mastery, accompanied by understanding of their relevance, connectivity, and usefulness relative to questions and constructs in a given discipline. For example, challenges in the teaching and learning of atmospheric science can be traced to threshold concepts in fluid dynamics. In particular, Dynamic Meteorology is one of the most challenging courses for graduate students and undergraduates majoring in Atmospheric Science. Dynamic Meteorology introduces threshold concepts - those that prove troublesome for the majority of students but that are essential, associated with fundamental relationships between forces and motion in the atmosphere and requiring the application of basic classical statics, dynamics, and thermodynamic principles to the three dimensionally varying atmospheric structure. With the explosive growth of data available in atmospheric science, driven largely by satellite Earth observations and high-resolution numerical simulations, paradigms such as that of dataintensive science have emerged. These paradigm shifts are based on the growing realization that current infrastructure, tools and processes will not allow us to analyze and fully utilize the complex and voluminous data that is being gathered. In this emerging paradigm, the scientific discovery process is driven by knowledge extracted from large volumes of data. In this presentation, we contend that this paradigm naturally lends to inquiry-driven pedagogy where knowledge is discovered through inductive engagement with large volumes of data rather than reached through traditional, deductive, hypothesis-driven analyses. In particular, data-intensive techniques married with an inductive methodology allow for exploration on a scale that is not possible in the traditional classroom with its typical problem sets and static, limited data samples. In addition, we identify existing gaps and possible solutions for addressing the infrastructure and tools as well as a pedagogical framework through which to implement this inductive approach.
Metal Solidification Imaging Process by Magnetic Induction Tomography.
Ma, Lu; Spagnul, Stefano; Soleimani, Manuchehr
2017-11-06
There are growing number of important applications that require a contactless method for monitoring an object surrounded inside a metallic enclosure. Imaging metal solidification is a great example for which there is no real time monitoring technique at present. This paper introduces a technique - magnetic induction tomography - for the real time in-situ imaging of the metal solidification process. Rigorous experimental verifications are presented. Firstly, a single inductive coil is placed on the top of a melting wood alloy to examine the changes of its inductance during solidification process. Secondly, an array of magnetic induction coils are designed to investigate the feasibility of a tomographic approach, i.e., when one coil is driven by an alternating current as a transmitter and a vector of phase changes are measured from the remaining of the coils as receivers. Phase changes are observed when the wood alloy state changes from liquid to solid. Thirdly, a series of static cold phantoms are created to represent various liquid/solid interfaces to verify the system performance. Finally, a powerful temporal reconstruction method is applied to realise real time in-situ visualisation of the solidification and the measurement of solidified shell thickness, a first report of its kind.
A temperature characteristic research and compensation design for micro-machined gyroscope
NASA Astrophysics Data System (ADS)
Fu, Qiang; di, Xin-Peng; Chen, Wei-Ping; Yin, Liang; Liu, Xiao-Wei
2017-02-01
The all temperature range stability is the most important technology of MEMS angular velocity sensor according to the principle of capacity detecting. The correlation between driven force and zero-point of sensor is summarized according to the temperature characteristic of the air-damping and resonant frequency of sensor header. A constant trans-conductance high-linearity amplifier is designed to realize the low phase-drift and low amplitude-drift interface circuit at all-temperature range. The chip is fabricated in a standard 0.5 μm CMOS process. Compensation achieved by driven force to zero-point drift caused by the stiffness of physical construction and air-damping is adopted. Moreover, the driven force can be obtained from the drive-circuit to avoid the complex sampling. The test result shows that the zero-point drift is lower than 30∘/h (1-sigma) at the temperature range from -40∘C to 60∘C after three-order compensation made by driven force.
The NDCX-II engineering design
NASA Astrophysics Data System (ADS)
Waldron, W. L.; Abraham, W. J.; Arbelaez, D.; Friedman, A.; Galvin, J. E.; Gilson, E. P.; Greenway, W. G.; Grote, D. P.; Jung, J.-Y.; Kwan, J. W.; Leitner, M.; Lidia, S. M.; Lipton, T. M.; Reginato, L. L.; Regis, M. J.; Roy, P. K.; Sharp, W. M.; Stettler, M. W.; Takakuwa, J. H.; Volmering, J.; Vytla, V. K.
2014-01-01
The Neutralized Drift Compression Experiment (NDCX-II) is a user facility located at Lawrence Berkeley National Laboratory which is uniquely designed for ion-beam-driven high energy density laboratory physics and heavy ion fusion research. Construction was completed in March 2012 and the facility is now in the commissioning phase. A significant amount of engineering was carried out in order to meet the performance parameters required for a wide range of target heating experiments while making the most cost-effective use of high-value hardware available from a decommissioned high current electron induction accelerator. The technical challenges and design of this new ion induction accelerator facility are described.
Emittance Growth in the DARHT-II Linear Induction Accelerator
NASA Astrophysics Data System (ADS)
Ekdahl, Carl; Carlson, Carl A.; Frayer, Daniel K.; McCuistian, B. Trent; Mostrom, Christopher B.; Schulze, Martin E.; Thoma, Carsten H.
2017-11-01
The Dual-Axis Radiographic Hydrotest (DARHT) facility uses bremsstrahlung radiation source spots produced by the focused electron beams from two linear induction accelerators (LIAs) to radiograph large hydrodynamic experiments driven by high explosives. Radiographic resolution is determined by the size of the source spot, and beam emittance is the ultimate limitation to spot size. Some of the possible causes for the emittance growth in the DARHT LIA have been investigated using particle-in-cell (PIC) codes, and are discussed in this article. The results suggest that the most likely source of emittance growth is a mismatch of the beam to the magnetic transport, which can cause beam halo.
Non Invasive Sensors for Monitoring the Efficiency of AC Electrical Rotating Machines
Zidat, Farid; Lecointe, Jean-Philippe; Morganti, Fabrice; Brudny, Jean-François; Jacq, Thierry; Streiff, Frédéric
2010-01-01
This paper presents a non invasive method for estimating the energy efficiency of induction motors used in industrial applications. This method is innovative because it is only based on the measurement of the external field emitted by the motor. The paper describes the sensors used, how they should be placed around the machine in order to decouple the external field components generated by both the air gap flux and the winding end-windings. The study emphasizes the influence of the eddy currents flowing in the yoke frame on the sensor position. A method to estimate the torque from the external field use is proposed. The measurements are transmitted by a wireless module (Zig-Bee) and they are centralized and stored on a PC computer. PMID:22163631
2013-05-01
an 18 inch gap diameter has roughly a 2 foot outer diameter 2 “ Brushless Permanent...require PMs include wound rotor DC (brush and brushless ), Variable or Switched reluctance (VR or SR) machines and squirrel cage induction motors...Trades have identified Brushless DC PM and SR machines are of primary interest. Both motors can use sensorless commutation methods. A VR resolver can
Non invasive sensors for monitoring the efficiency of AC electrical rotating machines.
Zidat, Farid; Lecointe, Jean-Philippe; Morganti, Fabrice; Brudny, Jean-François; Jacq, Thierry; Streiff, Frédéric
2010-01-01
This paper presents a non invasive method for estimating the energy efficiency of induction motors used in industrial applications. This method is innovative because it is only based on the measurement of the external field emitted by the motor. The paper describes the sensors used, how they should be placed around the machine in order to decouple the external field components generated by both the air gap flux and the winding end-windings. The study emphasizes the influence of the eddy currents flowing in the yoke frame on the sensor position. A method to estimate the torque from the external field use is proposed. The measurements are transmitted by a wireless module (Zig-Bee) and they are centralized and stored on a PC computer.
Event-driven contrastive divergence for spiking neuromorphic systems.
Neftci, Emre; Das, Srinjoy; Pedroni, Bruno; Kreutz-Delgado, Kenneth; Cauwenberghs, Gert
2013-01-01
Restricted Boltzmann Machines (RBMs) and Deep Belief Networks have been demonstrated to perform efficiently in a variety of applications, such as dimensionality reduction, feature learning, and classification. Their implementation on neuromorphic hardware platforms emulating large-scale networks of spiking neurons can have significant advantages from the perspectives of scalability, power dissipation and real-time interfacing with the environment. However, the traditional RBM architecture and the commonly used training algorithm known as Contrastive Divergence (CD) are based on discrete updates and exact arithmetics which do not directly map onto a dynamical neural substrate. Here, we present an event-driven variation of CD to train a RBM constructed with Integrate & Fire (I&F) neurons, that is constrained by the limitations of existing and near future neuromorphic hardware platforms. Our strategy is based on neural sampling, which allows us to synthesize a spiking neural network that samples from a target Boltzmann distribution. The recurrent activity of the network replaces the discrete steps of the CD algorithm, while Spike Time Dependent Plasticity (STDP) carries out the weight updates in an online, asynchronous fashion. We demonstrate our approach by training an RBM composed of leaky I&F neurons with STDP synapses to learn a generative model of the MNIST hand-written digit dataset, and by testing it in recognition, generation and cue integration tasks. Our results contribute to a machine learning-driven approach for synthesizing networks of spiking neurons capable of carrying out practical, high-level functionality.
Event-driven contrastive divergence for spiking neuromorphic systems
Neftci, Emre; Das, Srinjoy; Pedroni, Bruno; Kreutz-Delgado, Kenneth; Cauwenberghs, Gert
2014-01-01
Restricted Boltzmann Machines (RBMs) and Deep Belief Networks have been demonstrated to perform efficiently in a variety of applications, such as dimensionality reduction, feature learning, and classification. Their implementation on neuromorphic hardware platforms emulating large-scale networks of spiking neurons can have significant advantages from the perspectives of scalability, power dissipation and real-time interfacing with the environment. However, the traditional RBM architecture and the commonly used training algorithm known as Contrastive Divergence (CD) are based on discrete updates and exact arithmetics which do not directly map onto a dynamical neural substrate. Here, we present an event-driven variation of CD to train a RBM constructed with Integrate & Fire (I&F) neurons, that is constrained by the limitations of existing and near future neuromorphic hardware platforms. Our strategy is based on neural sampling, which allows us to synthesize a spiking neural network that samples from a target Boltzmann distribution. The recurrent activity of the network replaces the discrete steps of the CD algorithm, while Spike Time Dependent Plasticity (STDP) carries out the weight updates in an online, asynchronous fashion. We demonstrate our approach by training an RBM composed of leaky I&F neurons with STDP synapses to learn a generative model of the MNIST hand-written digit dataset, and by testing it in recognition, generation and cue integration tasks. Our results contribute to a machine learning-driven approach for synthesizing networks of spiking neurons capable of carrying out practical, high-level functionality. PMID:24574952
Tu, Junchao; Zhang, Liyan
2018-01-12
A new solution to the problem of galvanometric laser scanning (GLS) system calibration is presented. Under the machine learning framework, we build a single-hidden layer feedforward neural network (SLFN)to represent the GLS system, which takes the digital control signal at the drives of the GLS system as input and the space vector of the corresponding outgoing laser beam as output. The training data set is obtained with the aid of a moving mechanism and a binocular stereo system. The parameters of the SLFN are efficiently solved in a closed form by using extreme learning machine (ELM). By quantitatively analyzing the regression precision with respective to the number of hidden neurons in the SLFN, we demonstrate that the proper number of hidden neurons can be safely chosen from a broad interval to guarantee good generalization performance. Compared to the traditional model-driven calibration, the proposed calibration method does not need a complex modeling process and is more accurate and stable. As the output of the network is the space vectors of the outgoing laser beams, it costs much less training time and can provide a uniform solution to both laser projection and 3D-reconstruction, in contrast with the existing data-driven calibration method which only works for the laser triangulation problem. Calibration experiment, projection experiment and 3D reconstruction experiment are respectively conducted to test the proposed method, and good results are obtained.
NASA Astrophysics Data System (ADS)
Kotelnikov, E. V.; Milov, V. R.
2018-05-01
Rule-based learning algorithms have higher transparency and easiness to interpret in comparison with neural networks and deep learning algorithms. These properties make it possible to effectively use such algorithms to solve descriptive tasks of data mining. The choice of an algorithm depends also on its ability to solve predictive tasks. The article compares the quality of the solution of the problems with binary and multiclass classification based on the experiments with six datasets from the UCI Machine Learning Repository. The authors investigate three algorithms: Ripper (rule induction), C4.5 (decision trees), In-Close (formal concept analysis). The results of the experiments show that In-Close demonstrates the best quality of classification in comparison with Ripper and C4.5, however the latter two generate more compact rule sets.
NASA Tech Briefs, December 2013
NASA Technical Reports Server (NTRS)
2013-01-01
Topics include: Microwave Kinetic Inductance Detector With; Selective Polarization Coupling; Flexible Microstrip Circuits for; Superconducting Electronics; CFD Extraction Tool for TecPlot From DPLR Solutions; RECOVIR Software for Identifying Viruses; Enhanced Contact Graph Routing (ECGR) MACHETE Simulation Model; Orbital Debris Engineering Model (ORDEM) v.3; Scatter-Reducing Sounding Filtration Using a Genetic Algorithm and Mean Monthly Standard Deviation; Thermo-Mechanical Methodology for Stabilizing Shape Memory Alloy Response; Hermetic Seal Designs for Sample Return Sample Tubes; Silicon Alignment Pins: An Easy Way To Realize a Wafer-to-Wafer Alignment; Positive-Buoyancy Rover for Under Ice Mobility; Electric Machine With Boosted Inductance to Stabilize Current Control; International Space Station-Based Electromagnetic Launcher for Space Science Payloads; Advanced Hybrid Spacesuit Concept Featuring Integrated Open Loop and Closed Loop Ventilation Systems; Data Quality Screening Service.
Inductive System Health Monitoring
NASA Technical Reports Server (NTRS)
Iverson, David L.
2004-01-01
The Inductive Monitoring System (IMS) software was developed to provide a technique to automatically produce health monitoring knowledge bases for systems that are either difficult to model (simulate) with a computer or which require computer models that are too complex to use for real time monitoring. IMS uses nominal data sets collected either directly from the system or from simulations to build a knowledge base that can be used to detect anomalous behavior in the system. Machine learning and data mining techniques are used to characterize typical system behavior by extracting general classes of nominal data from archived data sets. IMS is able to monitor the system by comparing real time operational data with these classes. We present a description of learning and monitoring method used by IMS and summarize some recent IMS results.
Content addressable memory project
NASA Technical Reports Server (NTRS)
Hall, Josh; Levy, Saul; Smith, D.; Wei, S.; Miyake, K.; Murdocca, M.
1991-01-01
The progress on the Rutgers CAM (Content Addressable Memory) Project is described. The overall design of the system is completed at the architectural level and described. The machine is composed of two kinds of cells: (1) the CAM cells which include both memory and processor, and support local processing within each cell; and (2) the tree cells, which have smaller instruction set, and provide global processing over the CAM cells. A parameterized design of the basic CAM cell is completed. Progress was made on the final specification of the CPS. The machine architecture was driven by the design of algorithms whose requirements are reflected in the resulted instruction set(s). A few of these algorithms are described.
Progress toward a unified kJ-machine CANDY
NASA Astrophysics Data System (ADS)
Kitagawa, Yoneyoshi; Mori, Yoshitaka; Komeda, Osamu; Hanayama, Ryohei; Ishii, Katsuhiro; Okihara, Shinichiro; Fujita, Kazuhisa; Nakayama, Suisei; Sekine, Takashi; Sato, Nakahiro; Kurita, Takashi; Kawashima, Toshiyuki; Watari, Takeshi; Kan, Hirofumi; Nakamura, Naoki; Kondo, Takuya; Fujine, Manabu; Azuma, Hirozumi; Motohiro, Tomoyoshi; Hioki, Tatsumi; Kakeno, Mitsutaka; Nishimura, Yasuhiko; Sunahara, Atsushi; Sentoku, Yasuhiko; Miura, Eisuke; Arikawa, Yasunobu; Nagai, Takahiro; Abe, Yuki; Ozaki, Satoshi; Noda, Akira
2016-03-01
To construct a unified experimental machine CANDY using a kJ DPSSL driver in the fast-ignition scheme, the Laser for Fast Ignition Experiment (LFEX) at Osaka is used, showing that the laser-driven ions heat the preimploded core of a deuterated polystyrene (CD) shell target from 0.8 keV to 2 keV, resulting in 5 x 108 DD neutrons best ever obtained in the scheme. 4-J/10-Hz DPSSL laser HAMA is for the first time applied to the CD shell implosion- core heating experiments in the fast ignition scheme to yield neutrons and also to a continuous target injection, which yields neutrons of 3 x 105 n/4πsr n/shot.
New generation emerging technologies for neurorehabilitation and motor assistance.
Frisoli, Antonio; Solazzi, Massimiliano; Loconsole, Claudio; Barsotti, Michele
2016-12-01
This paper illustrates the application of emerging technologies and human-machine interfaces to the neurorehabilitation and motor assistance fields. The contribution focuses on wearable technologies and in particular on robotic exoskeleton as tools for increasing freedom to move and performing Activities of Daily Living (ADLs). This would result in a deep improvement in quality of life, also in terms of improved function of internal organs and general health status. Furthermore, the integration of these robotic systems with advanced bio-signal driven human-machine interface can increase the degree of participation of patient in robotic training allowing to recognize user's intention and assisting the patient in rehabilitation tasks, thus representing a fundamental aspect to elicit motor learning.
Molecular graph convolutions: moving beyond fingerprints
NASA Astrophysics Data System (ADS)
Kearnes, Steven; McCloskey, Kevin; Berndl, Marc; Pande, Vijay; Riley, Patrick
2016-08-01
Molecular "fingerprints" encoding structural information are the workhorse of cheminformatics and machine learning in drug discovery applications. However, fingerprint representations necessarily emphasize particular aspects of the molecular structure while ignoring others, rather than allowing the model to make data-driven decisions. We describe molecular graph convolutions, a machine learning architecture for learning from undirected graphs, specifically small molecules. Graph convolutions use a simple encoding of the molecular graph—atoms, bonds, distances, etc.—which allows the model to take greater advantage of information in the graph structure. Although graph convolutions do not outperform all fingerprint-based methods, they (along with other graph-based methods) represent a new paradigm in ligand-based virtual screening with exciting opportunities for future improvement.
Molecular graph convolutions: moving beyond fingerprints.
Kearnes, Steven; McCloskey, Kevin; Berndl, Marc; Pande, Vijay; Riley, Patrick
2016-08-01
Molecular "fingerprints" encoding structural information are the workhorse of cheminformatics and machine learning in drug discovery applications. However, fingerprint representations necessarily emphasize particular aspects of the molecular structure while ignoring others, rather than allowing the model to make data-driven decisions. We describe molecular graph convolutions, a machine learning architecture for learning from undirected graphs, specifically small molecules. Graph convolutions use a simple encoding of the molecular graph-atoms, bonds, distances, etc.-which allows the model to take greater advantage of information in the graph structure. Although graph convolutions do not outperform all fingerprint-based methods, they (along with other graph-based methods) represent a new paradigm in ligand-based virtual screening with exciting opportunities for future improvement.
Cardiac imaging: working towards fully-automated machine analysis & interpretation.
Slomka, Piotr J; Dey, Damini; Sitek, Arkadiusz; Motwani, Manish; Berman, Daniel S; Germano, Guido
2017-03-01
Non-invasive imaging plays a critical role in managing patients with cardiovascular disease. Although subjective visual interpretation remains the clinical mainstay, quantitative analysis facilitates objective, evidence-based management, and advances in clinical research. This has driven developments in computing and software tools aimed at achieving fully automated image processing and quantitative analysis. In parallel, machine learning techniques have been used to rapidly integrate large amounts of clinical and quantitative imaging data to provide highly personalized individual patient-based conclusions. Areas covered: This review summarizes recent advances in automated quantitative imaging in cardiology and describes the latest techniques which incorporate machine learning principles. The review focuses on the cardiac imaging techniques which are in wide clinical use. It also discusses key issues and obstacles for these tools to become utilized in mainstream clinical practice. Expert commentary: Fully-automated processing and high-level computer interpretation of cardiac imaging are becoming a reality. Application of machine learning to the vast amounts of quantitative data generated per scan and integration with clinical data also facilitates a move to more patient-specific interpretation. These developments are unlikely to replace interpreting physicians but will provide them with highly accurate tools to detect disease, risk-stratify, and optimize patient-specific treatment. However, with each technological advance, we move further from human dependence and closer to fully-automated machine interpretation.
NASA Astrophysics Data System (ADS)
Susmitha, M.; Sharan, P.; Jyothi, P. N.
2016-09-01
Friction between work piece-cutting tool-chip generates heat in the machining zone. The heat generated reduces the tool life, increases surface roughness and decreases the dimensional sensitiveness of work material. This can be overcome by using cutting fluids during machining. They are used to provide lubrication and cooling effects between cutting tool and work piece and cutting tool and chip during machining operation. As a result, important benefits would be achieved such longer tool life, easy chip flow and higher machining quality in the machining processes. Non-edible vegetable oils have received considerable research attention in the last decades owing to their remarkable improved tribological characteristics and due to increasing attention to environmental issues, have driven the lubricant industry toward eco friendly products from renewable sources. In the present work, different non-edible vegetable oils are used as cutting fluid during drilling of Mild steel work piece. Non-edible vegetable oils, used are Karanja oil (Honge), Neem oil and blend of these two oils. The effect of these cutting fluids on chip formation, surface roughness and cutting force are investigated and the results obtained are compared with results obtained with petroleum based cutting fluids and dry conditions.
2007-06-01
images,” IEEE Trans. Pattern Analysis Machine Intelligence, vol. 13, no. 2, pp. 99–113, 1991. [15] C. Bouman and M. Shapiro, “A multiscale random...including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing...this project was on developing new statistical algorithms for analysis of electromagnetic induction (EMI) and magnetometer data measured at actual
Kelledes, William L.; St. John, Don K.
1992-01-01
The present invention maintains constant torque in an inverter driven AC induction motor during variations in rotor temperature. It is known that the torque output of a given AC induction motor is dependent upon rotor temperature. At rotor temperatures higher than the nominal operating condition the rotor impedance increases, reducing the rotor current and motor torque. In a similar fashion, the rotor impedance is reduced resulting in increased rotor current and motor torque when the rotor temperature is lower than the nominal operating condition. The present invention monitors the bus current from the DC supply to the inverter and adjusts the slip frequency of the inverter drive to maintain a constant motor torque. This adjustment is based upon whether predetermined conditions implying increased rotor temperature or decreased rotor temperature exist for longer that a predetermined interval of time.
Neural network based control of Doubly Fed Induction Generator in wind power generation
NASA Astrophysics Data System (ADS)
Barbade, Swati A.; Kasliwal, Prabha
2012-07-01
To complement the other types of pollution-free generation wind energy is a viable option. Previously wind turbines were operated at constant speed. The evolution of technology related to wind systems industry leaded to the development of a generation of variable speed wind turbines that present many advantages compared to the fixed speed wind turbines. In this paper the phasor model of DFIG is used. This paper presents a study of a doubly fed induction generator driven by a wind turbine connected to the grid, and controlled by artificial neural network ANN controller. The behaviour of the system is shown with PI control, and then as controlled by ANN. The effectiveness of the artificial neural network controller is compared to that of a PI controller. The SIMULINK/MATLAB simulation for Doubly Fed Induction Generator and corresponding results and waveforms are displayed.
Wong, Jeffrey L; Obermajer, Nataša; Odunsi, Kunle; Edwards, Robert P; Kalinski, Pawel
2016-04-01
Maintenance of CTL-, Th1-, and NK cell-mediated type-1 immunity is essential for effective antitumor responses. Unexpectedly, we observed that the critical soluble mediators of type-1 immune effector cells, IFNγ and TNFα, synergize in the induction of cyclooxygenase 2 (COX2), the key enzyme in prostaglandin (PG)E2 synthesis, and the subsequent hyperactivation of myeloid-derived suppressor cells (MDSC) within the tumor microenvironment (TME) of ovarian cancer patients. MDSC hyperactivation by type-1 immunity and the resultant overexpression of indoleamine 2,3-dioxygenase (IDO), inducible nitric oxide synthase (iNOS/NOS2), IL10, and additional COX2 result in strong feedback suppression of type-1 immune responses. This paradoxical immune suppression driven by type-1 immune cell activation was found to depend on the synergistic action of IFNγ and TNFα, and could not be reproduced by either of these factors alone. Importantly, from a therapeutic standpoint, these negative feedback limiting type-1 responses could be eliminated by COX2 blockade, allowing amplification of type-1 immunity in the ovarian cancer TME. Our data demonstrate a new mechanism underlying the self-limiting nature of type-1 immunity in the human TME, driven by the synergistic induction of COX2 by IFNγ and TNFα, and provide a rationale for targeting the COX2-PGE2 axis to enhance the effectiveness of cancer immunotherapies. ©2016 American Association for Cancer Research.
NASA Astrophysics Data System (ADS)
Paradis, Daniel; Lefebvre, René; Gloaguen, Erwan; Rivera, Alfonso
2015-01-01
The spatial heterogeneity of hydraulic conductivity (K) exerts a major control on groundwater flow and solute transport. The heterogeneous spatial distribution of K can be imaged using indirect geophysical data as long as reliable relations exist to link geophysical data to K. This paper presents a nonparametric learning machine approach to predict aquifer K from cone penetrometer tests (CPT) coupled with a soil moisture and resistivity probe (SMR) using relevance vector machines (RVMs). The learning machine approach is demonstrated with an application to a heterogeneous unconsolidated littoral aquifer in a 12 km2 subwatershed, where relations between K and multiparameters CPT/SMR soundings appear complex. Our approach involved fuzzy clustering to define hydrofacies (HF) on the basis of CPT/SMR and K data prior to the training of RVMs for HFs recognition and K prediction on the basis of CPT/SMR data alone. The learning machine was built from a colocated training data set representative of the study area that includes K data from slug tests and CPT/SMR data up-scaled at a common vertical resolution of 15 cm with K data. After training, the predictive capabilities of the learning machine were assessed through cross validation with data withheld from the training data set and with K data from flowmeter tests not used during the training process. Results show that HF and K predictions from the learning machine are consistent with hydraulic tests. The combined use of CPT/SMR data and RVM-based learning machine proved to be powerful and efficient for the characterization of high-resolution K heterogeneity for unconsolidated aquifers.
Applying machine learning classification techniques to automate sky object cataloguing
NASA Astrophysics Data System (ADS)
Fayyad, Usama M.; Doyle, Richard J.; Weir, W. Nick; Djorgovski, Stanislav
1993-08-01
We describe the application of an Artificial Intelligence machine learning techniques to the development of an automated tool for the reduction of a large scientific data set. The 2nd Mt. Palomar Northern Sky Survey is nearly completed. This survey provides comprehensive coverage of the northern celestial hemisphere in the form of photographic plates. The plates are being transformed into digitized images whose quality will probably not be surpassed in the next ten to twenty years. The images are expected to contain on the order of 107 galaxies and 108 stars. Astronomers wish to determine which of these sky objects belong to various classes of galaxies and stars. Unfortunately, the size of this data set precludes analysis in an exclusively manual fashion. Our approach is to develop a software system which integrates the functions of independently developed techniques for image processing and data classification. Digitized sky images are passed through image processing routines to identify sky objects and to extract a set of features for each object. These routines are used to help select a useful set of attributes for classifying sky objects. Then GID3 (Generalized ID3) and O-B Tree, two inductive learning techniques, learns classification decision trees from examples. These classifiers will then be applied to new data. These developmnent process is highly interactive, with astronomer input playing a vital role. Astronomers refine the feature set used to construct sky object descriptions, and evaluate the performance of the automated classification technique on new data. This paper gives an overview of the machine learning techniques with an emphasis on their general applicability, describes the details of our specific application, and reports the initial encouraging results. The results indicate that our machine learning approach is well-suited to the problem. The primary benefit of the approach is increased data reduction throughput. Another benefit is consistency of classification. The classification rules which are the product of the inductive learning techniques will form an objective, examinable basis for classifying sky objects. A final, not to be underestimated benefit is that astronomers will be freed from the tedium of an intensely visual task to pursue more challenging analysis and interpretation problems based on automatically catalogued data.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Saleh, Z; Tang, X; Song, Y
Purpose: To investigate the long term stability and viability of using EPID-based daily output QA via in-house and vendor driven protocol, to replace conventional QA tools and improve QA efficiency. Methods: Two Varian TrueBeam machines (TB1&TB2) equipped with electronic portal imaging devices (EPID) were employed in this study. Both machines were calibrated per TG-51 and used clinically since Oct 2014. Daily output measurement for 6/15 MV beams were obtained using SunNuclear DailyQA3 device as part of morning QA. In addition, in-house protocol was implemented for EPID output measurement (10×10 cm fields, 100 MU, 100cm SID, output defined over an ROImore » of 2×2 cm around central axis). Moreover, the Varian Machine Performance Check (MPC) was used on both machines to measure machine output. The EPID and DailyQA3 based measurements of the relative machine output were compared and cross-correlated with monthly machine output as measured by an A12 Exradin 0.65cc Ion Chamber (IC) serving as ground truth. The results were correlated using Pearson test. Results: The correlations among DailyQA3, in-house EPID and Varian MPC output measurements, with the IC for 6/15 MV were similar for TB1 (0.83–0.95) and TB2 (0.55–0.67). The machine output for the 6/15MV beams on both machines showed a similar trend, namely an increase over time as indicated by all measurements, requiring a machine recalibration after 6 months. This drift is due to a known issue with pressurized monitor chamber which tends to leak over time. MPC failed occasionally but passed when repeated. Conclusion: The results indicate that the use of EPID for daily output measurements has the potential to become a viable and efficient tool for daily routine LINAC QA, thus eliminating weather (T,P) and human setup variability and increasing efficiency of the QA process.« less
Thermocouple and infrared sensor-based measurement of temperature distribution in metal cutting.
Kus, Abdil; Isik, Yahya; Cakir, M Cemal; Coşkun, Salih; Özdemir, Kadir
2015-01-12
In metal cutting, the magnitude of the temperature at the tool-chip interface is a function of the cutting parameters. This temperature directly affects production; therefore, increased research on the role of cutting temperatures can lead to improved machining operations. In this study, tool temperature was estimated by simultaneous temperature measurement employing both a K-type thermocouple and an infrared radiation (IR) pyrometer to measure the tool-chip interface temperature. Due to the complexity of the machining processes, the integration of different measuring techniques was necessary in order to obtain consistent temperature data. The thermal analysis results were compared via the ANSYS finite element method. Experiments were carried out in dry machining using workpiece material of AISI 4140 alloy steel that was heat treated by an induction process to a hardness of 50 HRC. A PVD TiAlN-TiN-coated WNVG 080404-IC907 carbide insert was used during the turning process. The results showed that with increasing cutting speed, feed rate and depth of cut, the tool temperature increased; the cutting speed was found to be the most effective parameter in assessing the temperature rise. The heat distribution of the cutting tool, tool-chip interface and workpiece provided effective and useful data for the optimization of selected cutting parameters during orthogonal machining.
Thermocouple and Infrared Sensor-Based Measurement of Temperature Distribution in Metal Cutting
Kus, Abdil; Isik, Yahya; Cakir, M. Cemal; Coşkun, Salih; Özdemir, Kadir
2015-01-01
In metal cutting, the magnitude of the temperature at the tool-chip interface is a function of the cutting parameters. This temperature directly affects production; therefore, increased research on the role of cutting temperatures can lead to improved machining operations. In this study, tool temperature was estimated by simultaneous temperature measurement employing both a K-type thermocouple and an infrared radiation (IR) pyrometer to measure the tool-chip interface temperature. Due to the complexity of the machining processes, the integration of different measuring techniques was necessary in order to obtain consistent temperature data. The thermal analysis results were compared via the ANSYS finite element method. Experiments were carried out in dry machining using workpiece material of AISI 4140 alloy steel that was heat treated by an induction process to a hardness of 50 HRC. A PVD TiAlN-TiN-coated WNVG 080404-IC907 carbide insert was used during the turning process. The results showed that with increasing cutting speed, feed rate and depth of cut, the tool temperature increased; the cutting speed was found to be the most effective parameter in assessing the temperature rise. The heat distribution of the cutting tool, tool-chip interface and workpiece provided effective and useful data for the optimization of selected cutting parameters during orthogonal machining. PMID:25587976
USDA-ARS?s Scientific Manuscript database
Information embodied in ecological site descriptions and their state-and-transition models is crucial to effective land management, and as such is needed now. There is not time (or money) to employ a traditional research-based approach (i.e., inductive/deductive, hypothesis driven inference) to addr...
Solar powered actuator with continuously variable auxiliary power control
NASA Technical Reports Server (NTRS)
Nola, F. J. (Inventor)
1984-01-01
A solar powered system is disclosed in which a load such as a compressor is driven by a main induction motor powered by a solar array. An auxiliary motor shares the load with the solar powered motor in proportion to the amount of sunlight available, is provided with a power factor controller for controlling voltage applied to the auxiliary motor in accordance with the loading on that motor. In one embodiment, when sufficient power is available from the solar cell, the auxiliary motor is driven as a generator by excess power from the main motor so as to return electrical energy to the power company utility lines.
Machine Learning for Education: Learning to Teach
2016-12-01
such as commercial aviation, healthcare, and military operations. In the context of military applications, serious gaming – the training warfighters...problems. Playing these games not only allowed the warfighter to discover and learn new tactics, techniques, and procedures, but also allowed the...collecting information across relevant sample sizes have motivated a data-driven, game - based simulation approach. For example, industry and academia alike
Machine Beats Experts: Automatic Discovery of Skill Models for Data-Driven Online Course Refinement
ERIC Educational Resources Information Center
Matsuda, Noboru; Furukawa, Tadanobu; Bier, Norman; Faloutsos, Christos
2015-01-01
How can we automatically determine which skills must be mastered for the successful completion of an online course? Large-scale online courses (e.g., MOOCs) often contain a broad range of contents frequently intended to be a semester's worth of materials; this breadth often makes it difficult to articulate an accurate set of skills and knowledge…
1981-09-01
The expres- sions for the rotor torque for a Darrieus machine can be found in Reference 4.16. The Darrieus wind turbine offers the following... turbine generators, wind -driven turbines , power conditioning, wind power, energy conservation, windmills, economic ana \\sis. 20 ABS 1"ACT (Conti,on... turbines , power conditioning requirements, siting requirements, and the economics of wind power under different conditions. Three examples are given to
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pin, F.G.; de Saussure, G.; Spelt, P.F.
1988-01-01
This paper describes recent research activities at the Center for Engineering Systems Advanced Research (CESAR) in the area of sensor based reasoning, with emphasis being given to their application and implementation on our HERMIES-IIB autonomous mobile vehicle. These activities, including navigation and exploration in a-priori unknown and dynamic environments, goal recognition, vision-guided manipulation and sensor-driven machine learning, are discussed within the framework of a scenario in which an autonomous robot is asked to navigate through an unknown dynamic environment, explore, find and dock at the panel, read and understand the status of the panel's meters and dials, learn the functioningmore » of a process control panel, and successfully manipulate the control devices of the panel to solve a maintenance emergency problems. A demonstration of the successful implementation of the algorithms on our HERMIES-IIB autonomous robot for resolution of this scenario is presented. Conclusions are drawn concerning the applicability of the methodologies to more general classes of problems and implications for future work on sensor-driven reasoning for autonomous robots are discussed. 8 refs., 3 figs.« less
Predicting the trajectories and intensities of hurricanes by applying machine learning techniques
NASA Astrophysics Data System (ADS)
Sujithkumar, A.; King, A. W.; Kovilakam, M.; Graves, D.
2017-12-01
The world has witnessed an escalation of devastating hurricanes and tropical cyclones over the last three decades. Hurricanes and tropical cyclones of very high magnitude will likely be even more frequent in a warmer world. Thus, precise forecasting of the track and intensity of hurricane/tropical cyclones remains one of the meteorological community's top priorities. However, comprehensive prediction of hurricane/ tropical cyclone is a difficult problem due to the many complexities of underlying physical processes with many variables and complex relations. The availability of global meteorological and hurricane/tropical storm climatological data opens new opportunities for data-driven approaches to hurricane/tropical cyclone modeling. Here we report initial results from two data-driven machine learning techniques, specifically, random forest (RF) and Bayesian learning (BL) to predict the trajectory and intensity of hurricanes and tropical cyclones. We used International Best Track Archive for Climate Stewardship (IBTrACS) data along with weather data from NOAA in a 50 km buffer surrounding each of the reported hurricane and tropical cyclone tracts to train the model. Initial results reveal that both RF and BL are skillful in predicting storm intensity. We will also present results for the more complicated trajectory prediction.
Virtual screening of inorganic materials synthesis parameters with deep learning
NASA Astrophysics Data System (ADS)
Kim, Edward; Huang, Kevin; Jegelka, Stefanie; Olivetti, Elsa
2017-12-01
Virtual materials screening approaches have proliferated in the past decade, driven by rapid advances in first-principles computational techniques, and machine-learning algorithms. By comparison, computationally driven materials synthesis screening is still in its infancy, and is mired by the challenges of data sparsity and data scarcity: Synthesis routes exist in a sparse, high-dimensional parameter space that is difficult to optimize over directly, and, for some materials of interest, only scarce volumes of literature-reported syntheses are available. In this article, we present a framework for suggesting quantitative synthesis parameters and potential driving factors for synthesis outcomes. We use a variational autoencoder to compress sparse synthesis representations into a lower dimensional space, which is found to improve the performance of machine-learning tasks. To realize this screening framework even in cases where there are few literature data, we devise a novel data augmentation methodology that incorporates literature synthesis data from related materials systems. We apply this variational autoencoder framework to generate potential SrTiO3 synthesis parameter sets, propose driving factors for brookite TiO2 formation, and identify correlations between alkali-ion intercalation and MnO2 polymorph selection.
Simulations of optically switchable molecular machines for particle transport.
Raeker, Tim; Jansen, Björn; Behrens, Dominik; Hartke, Bernd
2018-03-24
A promising application for design and deployment of molecular machines is nanoscale transport, driven by artificial cilia. In this contribution, we present several further steps toward this goal, beyond our first-generation artificial cilium (Raeker et al., J. Phys. Chem. A 2012, 116, 11241). Promising new azobenzene-derivatives were tested for use as cilium motors. Using a QM/MM partitioning in on-the-fly photodynamics, excited-state surface-hopping trajectories were calculated for each isomerization direction and each motor version. The methods used were reparametrized semiempirical quantum chemistry together with floating-occupation configuration interaction as the QM part and the OPLSAA-L forcefield as MM part. In addition, we simulated actual particle transport by a single cilium attached to a model surface, with varying attachment strengths and modes, and with transport targets ranging from single atoms to multi-molecule arrangements. Our results provide valuable design guidelines for cilia-driven nanoscale transport and emphasize the need to carefully select the whole setup (not just the cilium itself, but also its surface attachment and the dynamic cilium-target interaction) to achieve true transport. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.
Machine Learning-based discovery of closures for reduced models of dynamical systems
NASA Astrophysics Data System (ADS)
Pan, Shaowu; Duraisamy, Karthik
2017-11-01
Despite the successful application of machine learning (ML) in fields such as image processing and speech recognition, only a few attempts has been made toward employing ML to represent the dynamics of complex physical systems. Previous attempts mostly focus on parameter calibration or data-driven augmentation of existing models. In this work we present a ML framework to discover closure terms in reduced models of dynamical systems and provide insights into potential problems associated with data-driven modeling. Based on exact closure models for linear system, we propose a general linear closure framework from viewpoint of optimization. The framework is based on trapezoidal approximation of convolution term. Hyperparameters that need to be determined include temporal length of memory effect, number of sampling points, and dimensions of hidden states. To circumvent the explicit specification of memory effect, a general framework inspired from neural networks is also proposed. We conduct both a priori and posteriori evaluations of the resulting model on a number of non-linear dynamical systems. This work was supported in part by AFOSR under the project ``LES Modeling of Non-local effects using Statistical Coarse-graining'' with Dr. Jean-Luc Cambier as the technical monitor.
Hotz, Christine S; Templeton, Steven J; Christopher, Mary M
2005-03-01
A rule-based expert system using CLIPS programming language was created to classify body cavity effusions as transudates, modified transudates, exudates, chylous, and hemorrhagic effusions. The diagnostic accuracy of the rule-based system was compared with that produced by 2 machine-learning methods: Rosetta, a rough sets algorithm and RIPPER, a rule-induction method. Results of 508 body cavity fluid analyses (canine, feline, equine) obtained from the University of California-Davis Veterinary Medical Teaching Hospital computerized patient database were used to test CLIPS and to test and train RIPPER and Rosetta. The CLIPS system, using 17 rules, achieved an accuracy of 93.5% compared with pathologist consensus diagnoses. Rosetta accurately classified 91% of effusions by using 5,479 rules. RIPPER achieved the greatest accuracy (95.5%) using only 10 rules. When the original rules of the CLIPS application were replaced with those of RIPPER, the accuracy rates were identical. These results suggest that both rule-based expert systems and machine-learning methods hold promise for the preliminary classification of body fluids in the clinical laboratory.