The possibility of evaluating turbo-set bearing misalignment defects on the basis of bearing trajectory features

NASA Astrophysics Data System (ADS)

Rybczyński, Józef

2011-02-01

This paper presents the results of computer simulation of bearing misalignment defects in a power turbogenerator. This malfunction is typical for great multi-rotor and multi-bearing rotating machines and very common in power turbo-sets. Necessary calculations were carried out by the computer code system MESWIR, developed and used at the IFFM in Gdansk for calculating dynamics of rotors supported on oil bearings. The results are presented in the form of a set of journal and bush trajectories of all turbo-set bearings. Our analysis focuses on the vibrational effects of displacing the two most vulnerable machine bearings in horizontal and vertical directions by the maximum acceptable range calculated with regard to bearing vibration criterion. This assumption required preliminary assessment of the maximum values for the permissible bearing dislocations. We show the relations between the attributes of the particular bearing trajectories and the bearing displacements in relation to their base design position. The shape and dimensions of bearing trajectories are interpreted based on the theory of hydrodynamic lubrication of oil bearings. It was shown that the relative journal trajectories and absolute bush trajectories carry much important information about the dynamic state of the machine, indicating also the way in which bearings are loaded. Therefore, trajectories can be a source of information about the position and direction of bearing misalignments. This article indicates the potential of using trajectory patterns for diagnosing misalignment defects in rotating machines and suggests including sets of trajectory patterns to the knowledge base of a machine diagnostic system.

Structural Considerations of a 20MW Multi-Rotor Wind Energy System

NASA Astrophysics Data System (ADS)

Jamieson, P.; Branney, M.

2014-12-01

The drive to upscale offshore wind turbines relates especially to possiblereductions in O&M and electrical interconnection costs per MW of installed capacity.Even with best current technologies, designs with rated capacity above about 3 MW are less cost effective exfactory per rated MW(turbine system costs) than smaller machines.Very large offshore wind turbines are thereforejustifiedprimarily by overall offshore project economics. Furthermore, continuing progress in materials and structures has been essential to avoid severe penalties in the power/mass ratio of large multi-MW machines.The multi-rotor concept employs many small rotors to maximise energy capture area withminimum systemvolume. Previous work has indicated that this can enablea very large reduction in the total weight and cost of rotors and drive trains compared to an equivalent large single rotor system.Thus the multi rotor concept may enable rated capacities of 20 MW or more at a single maintenancesite. Establishing the cost benefit of a multi rotor system requires examination of solutions for the support structure and yawing, ensuring aerodynamic losses from rotor interaction are not significant and that overall logistics, with much increased part count (more reliable components) and less consequence of single failuresare favourable. This paper addresses the viability of a support structure in respect of structural concept and likely weight as one necessary step in exploring the potential of the multi rotor concept.

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

NASA Astrophysics Data System (ADS)

Le, Loc Xuan

1987-09-01

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

DPM — efficient storage in diverse environments

NASA Astrophysics Data System (ADS)

Hellmich, Martin; Furano, Fabrizio; Smith, David; Brito da Rocha, Ricardo; Álvarez Ayllón, Alejandro; Manzi, Andrea; Keeble, Oliver; Calvet, Ivan; Regala, Miguel Antonio

2014-06-01

Recent developments, including low power devices, cluster file systems and cloud storage, represent an explosion in the possibilities for deploying and managing grid storage. In this paper we present how different technologies can be leveraged to build a storage service with differing cost, power, performance, scalability and reliability profiles, using the popular storage solution Disk Pool Manager (DPM/dmlite) as the enabling technology. The storage manager DPM is designed for these new environments, allowing users to scale up and down as they need it, and optimizing their computing centers energy efficiency and costs. DPM runs on high-performance machines, profiting from multi-core and multi-CPU setups. It supports separating the database from the metadata server, the head node, largely reducing its hard disk requirements. Since version 1.8.6, DPM is released in EPEL and Fedora, simplifying distribution and maintenance, but also supporting the ARM architecture beside i386 and x86_64, allowing it to run the smallest low-power machines such as the Raspberry Pi or the CuBox. This usage is facilitated by the possibility to scale horizontally using a main database and a distributed memcached-powered namespace cache. Additionally, DPM supports a variety of storage pools in the backend, most importantly HDFS, S3-enabled storage, and cluster file systems, allowing users to fit their DPM installation exactly to their needs. In this paper, we investigate the power-efficiency and total cost of ownership of various DPM configurations. We develop metrics to evaluate the expected performance of a setup both in terms of namespace and disk access considering the overall cost including equipment, power consumptions, or data/storage fees. The setups tested range from the lowest scale using Raspberry Pis with only 700MHz single cores and a 100Mbps network connections, over conventional multi-core servers to typical virtual machine instances in cloud settings. We evaluate the combinations of different name server setups, for example load-balanced clusters, with different storage setups, from using a classic local configuration to private and public clouds.

Numerical modelling of multi-vane expander operating conditions in ORC system

NASA Astrophysics Data System (ADS)

Rak, Józef; Błasiak, Przemysław; Kolasiński, Piotr

2017-11-01

Multi-vane expanders are positive displacement volumetric machines which are nowadays considered for application in micro-power domestic ORC systems as promising alternative to micro turbines and other volumetric expanders. The multi-vane expander features very simple design, low gas flow capacity, low expansion ratios, an advantageous ratio of the power output to the external dimensions and are insensitive to the negative influence of the gas-liquid mixture expansion. Moreover, the multi-vane expander can be easily hermetically sealed, which is one of the key issues in the ORC system design. A literature review indicates that issues concerning the application of multi-vane expanders in such systems, especially related to operating of multi-vane expander with different low-boiling working fluids, are innovative, not fully scientifically described and have the potential for practical implementation. In this paper the results of numerical investigations on multi-vane expander operating conditions are presented. The analyses were performed on three-dimensional numerical model of the expander in ANSYS CFX software. The numerical model of the expander was validated using the data obtained from the experiment carried out on a lab test-stand. Then a series of computational analysis were performed using expanders' numerical model in order to determine its operating conditions under various flow conditions of different working fluids.

Performance prediction: A case study using a multi-ring KSR-1 machine

NASA Technical Reports Server (NTRS)

Sun, Xian-He; Zhu, Jianping

1995-01-01

While computers with tens of thousands of processors have successfully delivered high performance power for solving some of the so-called 'grand-challenge' applications, the notion of scalability is becoming an important metric in the evaluation of parallel machine architectures and algorithms. In this study, the prediction of scalability and its application are carefully investigated. A simple formula is presented to show the relation between scalability, single processor computing power, and degradation of parallelism. A case study is conducted on a multi-ring KSR1 shared virtual memory machine. Experimental and theoretical results show that the influence of topology variation of an architecture is predictable. Therefore, the performance of an algorithm on a sophisticated, heirarchical architecture can be predicted and the best algorithm-machine combination can be selected for a given application.

Use seismic colored inversion and power law committee machine based on imperial competitive algorithm for improving porosity prediction in a heterogeneous reservoir

NASA Astrophysics Data System (ADS)

Ansari, Hamid Reza

2014-09-01

In this paper we propose a new method for predicting rock porosity based on a combination of several artificial intelligence systems. The method focuses on one of the Iranian carbonate fields in the Persian Gulf. Because there is strong heterogeneity in carbonate formations, estimation of rock properties experiences more challenge than sandstone. For this purpose, seismic colored inversion (SCI) and a new approach of committee machine are used in order to improve porosity estimation. The study comprises three major steps. First, a series of sample-based attributes is calculated from 3D seismic volume. Acoustic impedance is an important attribute that is obtained by the SCI method in this study. Second, porosity log is predicted from seismic attributes using common intelligent computation systems including: probabilistic neural network (PNN), radial basis function network (RBFN), multi-layer feed forward network (MLFN), ε-support vector regression (ε-SVR) and adaptive neuro-fuzzy inference system (ANFIS). Finally, a power law committee machine (PLCM) is constructed based on imperial competitive algorithm (ICA) to combine the results of all previous predictions in a single solution. This technique is called PLCM-ICA in this paper. The results show that PLCM-ICA model improved the results of neural networks, support vector machine and neuro-fuzzy system.

The IHMC CmapTools software in research and education: a multi-level use case in Space Meteorology

NASA Astrophysics Data System (ADS)

Messerotti, Mauro

2010-05-01

The IHMC (Institute for Human and Machine Cognition, Florida University System, USA) CmapTools software is a powerful multi-platform tool for knowledge modelling in graphical form based on concept maps. In this work we present its application for the high-level development of a set of multi-level concept maps in the framework of Space Meteorology to act as the kernel of a space meteorology domain ontology. This is an example of a research use case, as a domain ontology coded in machine-readable form via e.g. OWL (Web Ontology Language) is suitable to be an active layer of any knowledge management system embedded in a Virtual Observatory (VO). Apart from being manageable at machine level, concept maps developed via CmapTools are intrinsically human-readable and can embed hyperlinks and objects of many kinds. Therefore they are suitable to be published on the web: the coded knowledge can be exploited for educational purposes by the students and the public, as the level of information can be naturally organized among linked concept maps in progressively increasing complexity levels. Hence CmapTools and its advanced version COE (Concept-map Ontology Editor) represent effective and user-friendly software tools for high-level knowledge represention in research and education.

Methods and Research for Multi-Component Cutting Force Sensing Devices and Approaches in Machining

PubMed Central

Liang, Qiaokang; Zhang, Dan; Wu, Wanneng; Zou, Kunlin

2016-01-01

Multi-component cutting force sensing systems in manufacturing processes applied to cutting tools are gradually becoming the most significant monitoring indicator. Their signals have been extensively applied to evaluate the machinability of workpiece materials, predict cutter breakage, estimate cutting tool wear, control machine tool chatter, determine stable machining parameters, and improve surface finish. Robust and effective sensing systems with capability of monitoring the cutting force in machine operations in real time are crucial for realizing the full potential of cutting capabilities of computer numerically controlled (CNC) tools. The main objective of this paper is to present a brief review of the existing achievements in the field of multi-component cutting force sensing systems in modern manufacturing. PMID:27854322

Methods and Research for Multi-Component Cutting Force Sensing Devices and Approaches in Machining.

PubMed

Liang, Qiaokang; Zhang, Dan; Wu, Wanneng; Zou, Kunlin

2016-11-16

Multi-component cutting force sensing systems in manufacturing processes applied to cutting tools are gradually becoming the most significant monitoring indicator. Their signals have been extensively applied to evaluate the machinability of workpiece materials, predict cutter breakage, estimate cutting tool wear, control machine tool chatter, determine stable machining parameters, and improve surface finish. Robust and effective sensing systems with capability of monitoring the cutting force in machine operations in real time are crucial for realizing the full potential of cutting capabilities of computer numerically controlled (CNC) tools. The main objective of this paper is to present a brief review of the existing achievements in the field of multi-component cutting force sensing systems in modern manufacturing.

Machine Learning Based Multi-Physical-Model Blending for Enhancing Renewable Energy Forecast -- Improvement via Situation Dependent Error Correction

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

Lu, Siyuan; Hwang, Youngdeok; Khabibrakhmanov, Ildar

With increasing penetration of solar and wind energy to the total energy supply mix, the pressing need for accurate energy forecasting has become well-recognized. Here we report the development of a machine-learning based model blending approach for statistically combining multiple meteorological models for improving the accuracy of solar/wind power forecast. Importantly, we demonstrate that in addition to parameters to be predicted (such as solar irradiance and power), including additional atmospheric state parameters which collectively define weather situations as machine learning input provides further enhanced accuracy for the blended result. Functional analysis of variance shows that the error of individual modelmore » has substantial dependence on the weather situation. The machine-learning approach effectively reduces such situation dependent error thus produces more accurate results compared to conventional multi-model ensemble approaches based on simplistic equally or unequally weighted model averaging. Validation over an extended period of time results show over 30% improvement in solar irradiance/power forecast accuracy compared to forecasts based on the best individual model.« less

Energy Survey of Machine Tools: Separating Power Information of the Main Transmission System During Machining Process

NASA Astrophysics Data System (ADS)

Liu, Shuang; Liu, Fei; Hu, Shaohua; Yin, Zhenbiao

The major power information of the main transmission system in machine tools (MTSMT) during machining process includes effective output power (i.e. cutting power), input power and power loss from the mechanical transmission system, and the main motor power loss. These information are easy to obtain in the lab but difficult to evaluate in a manufacturing process. To solve this problem, a separation method is proposed here to extract the MTSMT power information during machining process. In this method, the energy flow and the mathematical models of major power information of MTSMT during the machining process are set up first. Based on the mathematical models and the basic data tables obtained from experiments, the above mentioned power information during machining process can be separated just by measuring the real time total input power of the spindle motor. The operation program of this method is also given.

A machine-learning approach for damage detection in aircraft structures using self-powered sensor data

NASA Astrophysics Data System (ADS)

Salehi, Hadi; Das, Saptarshi; Chakrabartty, Shantanu; Biswas, Subir; Burgueño, Rigoberto

2017-04-01

This study proposes a novel strategy for damage identification in aircraft structures. The strategy was evaluated based on the simulation of the binary data generated from self-powered wireless sensors employing a pulse switching architecture. The energy-aware pulse switching communication protocol uses single pulses instead of multi-bit packets for information delivery resulting in discrete binary data. A system employing this energy-efficient technology requires dealing with time-delayed binary data due to the management of power budgets for sensing and communication. This paper presents an intelligent machine-learning framework based on combination of the low-rank matrix decomposition and pattern recognition (PR) methods. Further, data fusion is employed as part of the machine-learning framework to take into account the effect of data time delay on its interpretation. Simulated time-delayed binary data from self-powered sensors was used to determine damage indicator variables. Performance and accuracy of the damage detection strategy was examined and tested for the case of an aircraft horizontal stabilizer. Damage states were simulated on a finite element model by reducing stiffness in a region of the stabilizer's skin. The proposed strategy shows satisfactory performance to identify the presence and location of the damage, even with noisy and incomplete data. It is concluded that PR is a promising machine-learning algorithm for damage detection for time-delayed binary data from novel self-powered wireless sensors.

Methods, systems and apparatus for adjusting duty cycle of pulse width modulated (PWM) waveforms

DOEpatents

Gallegos-Lopez, Gabriel; Kinoshita, Michael H; Ransom, Ray M; Perisic, Milun

2013-05-21

Embodiments of the present invention relate to methods, systems and apparatus for controlling operation of a multi-phase machine in a vector controlled motor drive system when the multi-phase machine operates in an overmodulation region. The disclosed embodiments provide a mechanism for adjusting a duty cycle of PWM waveforms so that the correct phase voltage command signals are applied at the angle transitions. This can reduce variations/errors in the phase voltage command signals applied to the multi-phase machine so that phase current may be properly regulated thus reducing current/torque oscillation, which can in turn improve machine efficiency and performance, as well as utilization of the DC voltage source.

Multi-class Mode of Action Classification of Toxic Compounds Using Logic Based Kernel Methods.

PubMed

Lodhi, Huma; Muggleton, Stephen; Sternberg, Mike J E

2010-09-17

Toxicity prediction is essential for drug design and development of effective therapeutics. In this paper we present an in silico strategy, to identify the mode of action of toxic compounds, that is based on the use of a novel logic based kernel method. The technique uses support vector machines in conjunction with the kernels constructed from first order rules induced by an Inductive Logic Programming system. It constructs multi-class models by using a divide and conquer reduction strategy that splits multi-classes into binary groups and solves each individual problem recursively hence generating an underlying decision list structure. In order to evaluate the effectiveness of the approach for chemoinformatics problems like predictive toxicology, we apply it to toxicity classification in aquatic systems. The method is used to identify and classify 442 compounds with respect to the mode of action. The experimental results show that the technique successfully classifies toxic compounds and can be useful in assessing environmental risks. Experimental comparison of the performance of the proposed multi-class scheme with the standard multi-class Inductive Logic Programming algorithm and multi-class Support Vector Machine yields statistically significant results and demonstrates the potential power and benefits of the approach in identifying compounds of various toxic mechanisms. Copyright © 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Energy efficient lighting and communications

NASA Astrophysics Data System (ADS)

Zhou, Z.; Kavehrad, M.; Deng, P.

2012-01-01

As Light-Emitting Diode (LED)'s increasingly displace incandescent lighting over the next few years, general applications of Visible Light Communication (VLC) technology are expected to include wireless internet access, vehicle-to-vehicle communications, broadcast from LED signage, and machine-to-machine communications. An objective in this paper is to reveal the influence of system parameters on the power distribution and communication quality, in a general plural sources VLC system. It is demonstrated that sources' Half-Power Angles (HPA), receivers' Field-Of Views (FOV), sources layout and the power distribution among sources are significant impact factors. Based on our findings, we developed a method to adaptively change working status of each LED respectively according to users' locations. The program minimizes total power emitted while simultaneously ensuring sufficient light intensity and communication quality for each user. The paper also compares Orthogonal Frequency-Division Multiplexing (OFDM) and On-Off Keying (OOK) signals performance in indoor optical wireless communications. The simulation is carried out for different locations where different impulse response distortions are experienced. OFDM seems a better choice than prevalent OOK for indoor VLC due to its high resistance to multi-path effect and delay spread. However, the peak-to-average power limitations of the method must be investigated for lighting LEDs.

Coordinated Control Strategy of a Battery Energy Storage System to Support a Wind Power Plant Providing Multi-Timescale Frequency Ancillary Services

DOE PAGES

Tan, Jin; Zhang, Yingchen

2017-02-02

With increasing penetrations of wind generation on electric grids, wind power plants (WPPs) are encouraged to provide frequency ancillary services (FAS); however, it is a challenge to ensure that variable wind generation can reliably provide these ancillary services. This paper proposes using a battery energy storage system (BESS) to ensure the WPPs' commitment to FAS. This method also focuses on reducing the BESS's size and extending its lifetime. In this paper, a state-machine-based coordinated control strategy is developed to utilize a BESS to support the obliged FAS of a WPP (including both primary and secondary frequency control). This method takesmore » into account the operational constraints of the WPP (e.g., real-time reserve) and the BESS (e.g., state of charge [SOC], charge and discharge rate) to provide reliable FAS. Meanwhile, an adaptive SOC-feedback control is designed to maintain SOC at the optimal value as much as possible and thus reduce the size and extend the lifetime of the BESS. In conclusion, the effectiveness of the control strategy is validated with an innovative, multi-area, interconnected power system simulation platform that can mimic realistic power systems operation and control by simulating real-time economic dispatch, regulating reserve scheduling, multi-area automatic generation control, and generators' dynamic response.« less

Coordinated Control Strategy of a Battery Energy Storage System to Support a Wind Power Plant Providing Multi-Timescale Frequency Ancillary Services

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

Tan, Jin; Zhang, Yingchen

With increasing penetrations of wind generation on electric grids, wind power plants (WPPs) are encouraged to provide frequency ancillary services (FAS); however, it is a challenge to ensure that variable wind generation can reliably provide these ancillary services. This paper proposes using a battery energy storage system (BESS) to ensure the WPPs' commitment to FAS. This method also focuses on reducing the BESS's size and extending its lifetime. In this paper, a state-machine-based coordinated control strategy is developed to utilize a BESS to support the obliged FAS of a WPP (including both primary and secondary frequency control). This method takesmore » into account the operational constraints of the WPP (e.g., real-time reserve) and the BESS (e.g., state of charge [SOC], charge and discharge rate) to provide reliable FAS. Meanwhile, an adaptive SOC-feedback control is designed to maintain SOC at the optimal value as much as possible and thus reduce the size and extend the lifetime of the BESS. In conclusion, the effectiveness of the control strategy is validated with an innovative, multi-area, interconnected power system simulation platform that can mimic realistic power systems operation and control by simulating real-time economic dispatch, regulating reserve scheduling, multi-area automatic generation control, and generators' dynamic response.« less

A decision tree-based on-line preventive control strategy for power system transient instability prevention

NASA Astrophysics Data System (ADS)

Xu, Yan; Dong, Zhao Yang; Zhang, Rui; Wong, Kit Po

2014-02-01

Maintaining transient stability is a basic requirement for secure power system operations. Preventive control deals with modifying the system operating point to withstand probable contingencies. In this article, a decision tree (DT)-based on-line preventive control strategy is proposed for transient instability prevention of power systems. Given a stability database, a distance-based feature estimation algorithm is first applied to identify the critical generators, which are then used as features to develop a DT. By interpreting the splitting rules of DT, preventive control is realised by formulating the rules in a standard optimal power flow model and solving it. The proposed method is transparent in control mechanism, on-line computation compatible and convenient to deal with multi-contingency. The effectiveness and efficiency of the method has been verified on New England 10-machine 39-bus test system.

Fundamental studies on initiation and evolution of multi-channel discharges and their application to next generation pulsed power machines.

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

Model based PI power system stabilizer design for damping low frequency oscillations in power systems.

PubMed

Salgotra, Aprajita; Pan, Somnath

2018-05-01

This paper explores a two-level control strategy by blending local controller with centralized controller for the low frequency oscillations in a power system. The proposed control scheme provides stabilization of local modes using a local controller and minimizes the effect of inter-connection of sub-systems performance through a centralized control. For designing the local controllers in the form of proportional-integral power system stabilizer (PI-PSS), a simple and straight forward frequency domain direct synthesis method is considered that works on use of a suitable reference model which is based on the desired requirements. Several examples both on one machine infinite bus and multi-machine systems taken from the literature are illustrated to show the efficacy of the proposed PI-PSS. The effective damping of the systems is found to be increased remarkably which is reflected in the time-responses; even unstable operation has been stabilized with improved damping after applying the proposed controller. The proposed controllers give remarkable improvement in damping the oscillations in all the illustrations considered here and as for example, the value of damping factor has been increased from 0.0217 to 0.666 in Example 1. The simulation results obtained by the proposed control strategy are favourably compared with some controllers prevalent in the literature. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Stability Assessment of a System Comprising a Single Machine and Inverter with Scalable Ratings

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

Johnson, Brian B; Lin, Yashen; Gevorgian, Vahan

From the inception of power systems, synchronous machines have acted as the foundation of large-scale electrical infrastructures and their physical properties have formed the cornerstone of system operations. However, power electronics interfaces are playing a growing role as they are the primary interface for several types of renewable energy sources and storage technologies. As the role of power electronics in systems continues to grow, it is crucial to investigate the properties of bulk power systems in low inertia settings. In this paper, we assess the properties of coupled machine-inverter systems by studying an elementary system comprised of a synchronous generator,more » three-phase inverter, and a load. Furthermore, the inverter model is formulated such that its power rating can be scaled continuously across power levels while preserving its closed-loop response. Accordingly, the properties of the machine-inverter system can be assessed for varying ratios of machine-to-inverter power ratings and, hence, differing levels of inertia. After linearizing the model and assessing its eigenvalues, we show that system stability is highly dependent on the interaction between the inverter current controller and machine exciter, thus uncovering a key concern with mixed machine-inverter systems and motivating the need for next-generation grid-stabilizing inverter controls.« less

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Enabling Low-Power, Multi-Modal Neural Interfaces Through a Common, Low-Bandwidth Feature Space.

PubMed

Irwin, Zachary T; Thompson, David E; Schroeder, Karen E; Tat, Derek M; Hassani, Ali; Bullard, Autumn J; Woo, Shoshana L; Urbanchek, Melanie G; Sachs, Adam J; Cederna, Paul S; Stacey, William C; Patil, Parag G; Chestek, Cynthia A

2016-05-01

Brain-Machine Interfaces (BMIs) have shown great potential for generating prosthetic control signals. Translating BMIs into the clinic requires fully implantable, wireless systems; however, current solutions have high power requirements which limit their usability. Lowering this power consumption typically limits the system to a single neural modality, or signal type, and thus to a relatively small clinical market. Here, we address both of these issues by investigating the use of signal power in a single narrow frequency band as a decoding feature for extracting information from electrocorticographic (ECoG), electromyographic (EMG), and intracortical neural data. We have designed and tested the Multi-modal Implantable Neural Interface (MINI), a wireless recording system which extracts and transmits signal power in a single, configurable frequency band. In prerecorded datasets, we used the MINI to explore low frequency signal features and any resulting tradeoff between power savings and decoding performance losses. When processing intracortical data, the MINI achieved a power consumption 89.7% less than a more typical system designed to extract action potential waveforms. When processing ECoG and EMG data, the MINI achieved similar power reductions of 62.7% and 78.8%. At the same time, using the single signal feature extracted by the MINI, we were able to decode all three modalities with less than a 9% drop in accuracy relative to using high-bandwidth, modality-specific signal features. We believe this system architecture can be used to produce a viable, cost-effective, clinical BMI.

Robotic inspection of fiber reinforced composites using phased array UT

NASA Astrophysics Data System (ADS)

Stetson, Jeffrey T.; De Odorico, Walter

2014-02-01

Ultrasound is the current NDE method of choice to inspect large fiber reinforced airframe structures. Over the last 15 years Cartesian based scanning machines using conventional ultrasound techniques have been employed by all airframe OEMs and their top tier suppliers to perform these inspections. Technical advances in both computing power and commercially available, multi-axis robots now facilitate a new generation of scanning machines. These machines use multiple end effector tools taking full advantage of phased array ultrasound technologies yielding substantial improvements in inspection quality and productivity. This paper outlines the general architecture for these new robotic scanning systems as well as details the variety of ultrasonic techniques available for use with them including advances such as wide area phased array scanning and sound field adaptation for non-flat, non-parallel surfaces.

Research on the EDM Technology for Micro-holes at Complex Spatial Locations

NASA Astrophysics Data System (ADS)

Y Liu, J.; Guo, J. M.; Sun, D. J.; Cai, Y. H.; Ding, L. T.; Jiang, H.

2017-12-01

For the demands on machining micro-holes at complex spatial location, several key technical problems are conquered such as micro-Electron Discharge Machining (micro-EDM) power supply system’s development, the host structure’s design and machining process technical. Through developing low-voltage power supply circuit, high-voltage circuit, micro and precision machining circuit and clearance detection system, the narrow pulse and high frequency six-axis EDM machining power supply system is developed to meet the demands on micro-hole discharging machining. With the method of combining the CAD structure design, CAE simulation analysis, modal test, ODS (Operational Deflection Shapes) test and theoretical analysis, the host construction and key axes of the machine tool are optimized to meet the position demands of the micro-holes. Through developing the special deionized water filtration system to make sure that the machining process is stable enough. To verify the machining equipment and processing technical developed in this paper through developing the micro-hole’s processing flow and test on the real machine tool. As shown in the final test results: the efficient micro-EDM machining pulse power supply system, machine tool host system, deionized filtration system and processing method developed in this paper meet the demands on machining micro-holes at complex spatial locations.

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

NASA Technical Reports Server (NTRS)

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

1983-01-01

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

Intelligent power management in a vehicular system with multiple power sources

NASA Astrophysics Data System (ADS)

Murphey, Yi L.; Chen, ZhiHang; Kiliaris, Leonidas; Masrur, M. Abul

This paper presents an optimal online power management strategy applied to a vehicular power system that contains multiple power sources and deals with largely fluctuated load requests. The optimal online power management strategy is developed using machine learning and fuzzy logic. A machine learning algorithm has been developed to learn the knowledge about minimizing power loss in a Multiple Power Sources and Loads (M_PS&LD) system. The algorithm exploits the fact that different power sources used to deliver a load request have different power losses under different vehicle states. The machine learning algorithm is developed to train an intelligent power controller, an online fuzzy power controller, FPC_MPS, that has the capability of finding combinations of power sources that minimize power losses while satisfying a given set of system and component constraints during a drive cycle. The FPC_MPS was implemented in two simulated systems, a power system of four power sources, and a vehicle system of three power sources. Experimental results show that the proposed machine learning approach combined with fuzzy control is a promising technology for intelligent vehicle power management in a M_PS&LD power system.

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

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

A Power Transformers Fault Diagnosis Model Based on Three DGA Ratios and PSO Optimization SVM

NASA Astrophysics Data System (ADS)

Ma, Hongzhe; Zhang, Wei; Wu, Rongrong; Yang, Chunyan

2018-03-01

In order to make up for the shortcomings of existing transformer fault diagnosis methods in dissolved gas-in-oil analysis (DGA) feature selection and parameter optimization, a transformer fault diagnosis model based on the three DGA ratios and particle swarm optimization (PSO) optimize support vector machine (SVM) is proposed. Using transforming support vector machine to the nonlinear and multi-classification SVM, establishing the particle swarm optimization to optimize the SVM multi classification model, and conducting transformer fault diagnosis combined with the cross validation principle. The fault diagnosis results show that the average accuracy of test method is better than the standard support vector machine and genetic algorithm support vector machine, and the proposed method can effectively improve the accuracy of transformer fault diagnosis is proved.

Stability Assessment of a System Comprising a Single Machine and Inverter with Scalable Ratings

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

Johnson, Brian B; Lin, Yashen; Gevorgian, Vahan

Synchronous machines have traditionally acted as the foundation of large-scale electrical infrastructures and their physical properties have formed the cornerstone of system operations. However, with the increased integration of distributed renewable resources and energy-storage technologies, there is a need to systematically acknowledge the dynamics of power-electronics inverters - the primary energy-conversion interface in such systems - in all aspects of modeling, analysis, and control of the bulk power network. In this paper, we assess the properties of coupled machine-inverter systems by studying an elementary system comprised of a synchronous generator, three-phase inverter, and a load. The inverter model is formulatedmore » such that its power rating can be scaled continuously across power levels while preserving its closed-loop response. Accordingly, the properties of the machine-inverter system can be assessed for varying ratios of machine-to-inverter power ratings. After linearizing the model and assessing its eigenvalues, we show that system stability is highly dependent on the inverter current controller and machine exciter, thus uncovering a key concern with mixed machine-inverter systems and motivating the need for next-generation grid-stabilizing inverter controls.« less

Assessing Advanced Technology in CENATE

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

Tallent, Nathan R.; Barker, Kevin J.; Gioiosa, Roberto

PNNL's Center for Advanced Technology Evaluation (CENATE) is a new U.S. Department of Energy center whose mission is to assess and facilitate access to emerging computing technology. CENATE is assessing a range of advanced technologies, from evolutionary to disruptive. Technologies of interest include the processor socket (homogeneous and accelerated systems), memories (dynamic, static, memory cubes), motherboards, networks (network interface cards and switches), and input/output and storage devices. CENATE is developing a multi-perspective evaluation process based on integrating advanced system instrumentation, performance measurements, and modeling and simulation. We show evaluations of two emerging network technologies: silicon photonics interconnects and the Datamore » Vortex network. CENATE's evaluation also addresses the question of which machine is best for a given workload under certain constraints. We show a performance-power tradeoff analysis of a well-known machine learning application on two systems.« less

Methods, systems and apparatus for controlling third harmonic voltage when operating a multi-space machine in an overmodulation region

DOEpatents

Perisic, Milun; Kinoshita, Michael H; Ranson, Ray M; Gallegos-Lopez, Gabriel

2014-06-03

Methods, system and apparatus are provided for controlling third harmonic voltages when operating a multi-phase machine in an overmodulation region. The multi-phase machine can be, for example, a five-phase machine in a vector controlled motor drive system that includes a five-phase PWM controlled inverter module that drives the five-phase machine. Techniques for overmodulating a reference voltage vector are provided. For example, when the reference voltage vector is determined to be within the overmodulation region, an angle of the reference voltage vector can be modified to generate a reference voltage overmodulation control angle, and a magnitude of the reference voltage vector can be modified, based on the reference voltage overmodulation control angle, to generate a modified magnitude of the reference voltage vector. By modifying the reference voltage vector, voltage command signals that control a five-phase inverter module can be optimized to increase output voltages generated by the five-phase inverter module.

Methods to Control EMI Noises Produced in Power Converter Systems

NASA Astrophysics Data System (ADS)

Mutoh, Nobuyoshi; Ogata, Mitukatu

A new method to control EMI noises produced in power converters (rectifier and inverter) composed of IPMs (Intelligent Power Modules) is studied especially focusing on differential mode noises. The differential mode noises are occurred due to switching operations of the PWM control. As they are diffused into the ground through stray capacitors distributed between the ground and the power transmission lines and machine frames, differential mode noises should be confined and suppressed within the smallest area where power converters are laid out. It is impossible to control differential mode noises easily occurring diffusion by the conventional methods like filtering techniques. So, a new EMI noise control method using a multi-power circuit technique is proposed. The proposed method of the effectiveness has been verified through simulations and experiments.

Delivering key signals to the machine: seeking the electric signal that muscles emanate

NASA Astrophysics Data System (ADS)

Bani Hashim, A. Y.; Maslan, M. N.; Izamshah, R.; Mohamad, I. S.

2014-11-01

Due to the limitation of electric power generation in the human body, present human-machine interfaces have not been successful because of the nature of standard electronics circuit designs, which do not consider the specifications of signals that resulted from the skin. In general, the outcomes and applications of human-machine interfaces are limited to custom-designed subsystems, such as neuroprosthesis. We seek to model the bio dynamical of sub skin into equivalent mathematical definitions, descriptions, and theorems. Within the human skin, there are networks of nerves that permit the skin to function as a multi dimension transducer. We investigate the nature of structural skin. Apart from multiple networks of nerves, there are other segments within the skin such as minute muscles. We identify the segments that are active when there is an electromyography activity. When the nervous system is firing signals, the muscle is being stimulated. We evaluate the phenomena of biodynamic of the muscles that is concerned with the electromyography activity of the nervous system. In effect, we design a relationship between the human somatosensory and synthetic systems sensory as the union of a complete set of the new domain of the functional system. This classifies electromyogram waveforms linked to intent thought of an operator. The system will become the basis for delivering key signals to machine such that the machine is under operator's intent, hence slavery.

Performance Analysis of a Hybrid Overset Multi-Block Application on Multiple Architectures

NASA Technical Reports Server (NTRS)

Djomehri, M. Jahed; Biswas, Rupak

2003-01-01

This paper presents a detailed performance analysis of a multi-block overset grid compu- tational fluid dynamics app!ication on multiple state-of-the-art computer architectures. The application is implemented using a hybrid MPI+OpenMP programming paradigm that exploits both coarse and fine-grain parallelism; the former via MPI message passing and the latter via OpenMP directives. The hybrid model also extends the applicability of multi-block programs to large clusters of SNIP nodes by overcoming the restriction that the number of processors be less than the number of grid blocks. A key kernel of the application, namely the LU-SGS linear solver, had to be modified to enhance the performance of the hybrid approach on the target machines. Investigations were conducted on cacheless Cray SX6 vector processors, cache-based IBM Power3 and Power4 architectures, and single system image SGI Origin3000 platforms. Overall results for complex vortex dynamics simulations demonstrate that the SX6 achieves the highest performance and outperforms the RISC-based architectures; however, the best scaling performance was achieved on the Power3.

Resilient guaranteed cost control of a power system.

PubMed

Soliman, Hisham M; Soliman, Mostafa H; Hassan, Mohammad F

2014-05-01

With the development of power system interconnection, the low-frequency oscillation is becoming more and more prominent which may cause system separation and loss of energy to consumers. This paper presents an innovative robust control for power systems in which the operating conditions are changing continuously due to load changes. However, practical implementation of robust control can be fragile due to controller inaccuracies (tolerance of resistors used with operational amplifiers). A new design of resilient (non-fragile) robust control is given that takes into consideration both model and controller uncertainties by an iterative solution of a set of linear matrix inequalities (LMI). Both uncertainties are cast into a norm-bounded structure. A sufficient condition is derived to achieve the desired settling time for damping power system oscillations in face of plant and controller uncertainties. Furthermore, an improved controller design, resilient guaranteed cost controller, is derived to achieve oscillations damping in a guaranteed cost manner. The effectiveness of the algorithm is shown for a single machine infinite bus system, and then, it is extended to multi-area power system.

Laser Measurements Based for Volumetric Accuracy Improvement of Multi-axis Systems

NASA Astrophysics Data System (ADS)

Vladimir, Sokolov; Konstantin, Basalaev

The paper describes a new developed approach to CNC-controlled multi-axis systems geometric errors compensation based on optimal error correction strategy. Multi-axis CNC-controlled systems - machine-tools and CMM's are the basis of modern engineering industry. Similar design principles of both technological and measurement equipment allow usage of similar approaches to precision management. The approach based on geometric errors compensation are widely used at present time. The paper describes a system for compensation of geometric errors of multi-axis equipment based on the new approach. The hardware basis of the developed system is a multi-function laser interferometer. The principles of system's implementation, results of measurements and system's functioning simulation are described. The effectiveness of application of described principles to multi-axis equipment of different sizes and purposes for different machining directions and zones within workspace is presented. The concepts of optimal correction strategy is introduced and dynamic accuracy control is proposed.

A Novel Degradation Identification Method for Wind Turbine Pitch System

NASA Astrophysics Data System (ADS)

Guo, Hui-Dong

2018-04-01

It’s difficult for traditional threshold value method to identify degradation of operating equipment accurately. An novel degradation evaluation method suitable for wind turbine condition maintenance strategy implementation was proposed in this paper. Based on the analysis of typical variable-speed pitch-to-feather control principle and monitoring parameters for pitch system, a multi input multi output (MIMO) regression model was applied to pitch system, where wind speed, power generation regarding as input parameters, wheel rotation speed, pitch angle and motor driving currency for three blades as output parameters. Then, the difference between the on-line measurement and the calculated value from the MIMO regression model applying least square support vector machines (LSSVM) method was defined as the Observed Vector of the system. The Gaussian mixture model (GMM) was applied to fitting the distribution of the multi dimension Observed Vectors. Applying the model established, the Degradation Index was calculated using the SCADA data of a wind turbine damaged its pitch bearing retainer and rolling body, which illustrated the feasibility of the provided method.

Analytical Assessment for Transient Stability Under Stochastic Continuous Disturbances

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

Ju, Ping; Li, Hongyu; Gan, Chun

Here, with the growing integration of renewable power generation, plug-in electric vehicles, and other sources of uncertainty, increasing stochastic continuous disturbances are brought to power systems. The impact of stochastic continuous disturbances on power system transient stability attracts significant attention. To address this problem, this paper proposes an analytical assessment method for transient stability of multi-machine power systems under stochastic continuous disturbances. In the proposed method, a probability measure of transient stability is presented and analytically solved by stochastic averaging. Compared with the conventional method (Monte Carlo simulation), the proposed method is many orders of magnitude faster, which makes itmore » very attractive in practice when many plans for transient stability must be compared or when transient stability must be analyzed quickly. Also, it is found that the evolution of system energy over time is almost a simple diffusion process by the proposed method, which explains the impact mechanism of stochastic continuous disturbances on transient stability in theory.« less

Development of a Multi-Centre Clinical Trial Data Archiving and Analysis Platform for Functional Imaging

NASA Astrophysics Data System (ADS)

Driscoll, Brandon; Jaffray, David; Coolens, Catherine

2014-03-01

Purpose: To provide clinicians & researchers participating in multi-centre clinical trials with a central repository for large volume dynamic imaging data as well as a set of tools for providing end-to-end testing and image analysis standards of practice. Methods: There are three main pieces to the data archiving and analysis system; the PACS server, the data analysis computer(s) and the high-speed networks that connect them. Each clinical trial is anonymized using a customizable anonymizer and is stored on a PACS only accessible by AE title access control. The remote analysis station consists of a single virtual machine per trial running on a powerful PC supporting multiple simultaneous instances. Imaging data management and analysis is performed within ClearCanvas Workstation® using custom designed plug-ins for kinetic modelling (The DCE-Tool®), quality assurance (The DCE-QA Tool) and RECIST. Results: A framework has been set up currently serving seven clinical trials spanning five hospitals with three more trials to be added over the next six months. After initial rapid image transfer (+ 2 MB/s), all data analysis is done server side making it robust and rapid. This has provided the ability to perform computationally expensive operations such as voxel-wise kinetic modelling on very large data archives (+20 GB/50k images/patient) remotely with minimal end-user hardware. Conclusions: This system is currently in its proof of concept stage but has been used successfully to send and analyze data from remote hospitals. Next steps will involve scaling up the system with a more powerful PACS and multiple high powered analysis machines as well as adding real-time review capabilities.

Evaluation of an Integrated Multi-Task Machine Learning System with Humans in the Loop

DTIC Science & Technology

2007-01-01

machine learning components natural language processing, and optimization...was examined with a test explicitly developed to measure the impact of integrated machine learning when used by a human user in a real world setting...study revealed that integrated machine learning does produce a positive impact on overall performance. This paper also discusses how specific machine learning components contributed to human-system

Representability of algebraic topology for biomolecules in machine learning based scoring and virtual screening

PubMed Central

Mu, Lin

2018-01-01

This work introduces a number of algebraic topology approaches, including multi-component persistent homology, multi-level persistent homology, and electrostatic persistence for the representation, characterization, and description of small molecules and biomolecular complexes. In contrast to the conventional persistent homology, multi-component persistent homology retains critical chemical and biological information during the topological simplification of biomolecular geometric complexity. Multi-level persistent homology enables a tailored topological description of inter- and/or intra-molecular interactions of interest. Electrostatic persistence incorporates partial charge information into topological invariants. These topological methods are paired with Wasserstein distance to characterize similarities between molecules and are further integrated with a variety of machine learning algorithms, including k-nearest neighbors, ensemble of trees, and deep convolutional neural networks, to manifest their descriptive and predictive powers for protein-ligand binding analysis and virtual screening of small molecules. Extensive numerical experiments involving 4,414 protein-ligand complexes from the PDBBind database and 128,374 ligand-target and decoy-target pairs in the DUD database are performed to test respectively the scoring power and the discriminatory power of the proposed topological learning strategies. It is demonstrated that the present topological learning outperforms other existing methods in protein-ligand binding affinity prediction and ligand-decoy discrimination. PMID:29309403

Cells, Agents, and Support Vectors in Interaction - Modeling Urban Sprawl based on Machine Learning and Artificial Intelligence Techniques in a Post-Industrial Region

NASA Astrophysics Data System (ADS)

Rienow, A.; Menz, G.

2015-12-01

Since the beginning of the millennium, artificial intelligence techniques as cellular automata (CA) and multi-agent systems (MAS) have been incorporated into land-system simulations to address the complex challenges of transitions in urban areas as open, dynamic systems. The study presents a hybrid modeling approach for modeling the two antagonistic processes of urban sprawl and urban decline at once. The simulation power of support vector machines (SVM), cellular automata (CA) and multi-agent systems (MAS) are integrated into one modeling framework and applied to the largest agglomeration of Central Europe: the Ruhr. A modified version of SLEUTH (short for Slope, Land-use, Exclusion, Urban, Transport, and Hillshade) functions as the CA component. SLEUTH makes use of historic urban land-use data sets and growth coefficients for the purpose of modeling physical urban expansion. The machine learning algorithm of SVM is applied in order to enhance SLEUTH. Thus, the stochastic variability of the CA is reduced and information about the human and ecological forces driving the local suitability of urban sprawl is incorporated. Subsequently, the supported CA is coupled with the MAS ReHoSh (Residential Mobility and the Housing Market of Shrinking City Systems). The MAS models population patterns, housing prices, and housing demand in shrinking regions based on interactions between household and city agents. Semi-explicit urban weights are introduced as a possibility of modeling from and to the pixel simultaneously. Three scenarios of changing housing preferences reveal the urban development of the region in terms of quantity and location. They reflect the dissemination of sustainable thinking among stakeholders versus the steady dream of owning a house in sub- and exurban areas. Additionally, the outcomes are transferred into a digital petri dish reflecting a synthetic environment with perfect conditions of growth. Hence, the generic growth elements affecting the future face of post-industrial cities are revealed. Finally, the advantages and limitations of linking pixels and people by combining AI and machine learning techniques in a multi-scale geosimulation approach are to be discussed.

Multiple-Swarm Ensembles: Improving the Predictive Power and Robustness of Predictive Models and Its Use in Computational Biology.

PubMed

Alves, Pedro; Liu, Shuang; Wang, Daifeng; Gerstein, Mark

2018-01-01

Machine learning is an integral part of computational biology, and has already shown its use in various applications, such as prognostic tests. In the last few years in the non-biological machine learning community, ensembling techniques have shown their power in data mining competitions such as the Netflix challenge; however, such methods have not found wide use in computational biology. In this work, we endeavor to show how ensembling techniques can be applied to practical problems, including problems in the field of bioinformatics, and how they often outperform other machine learning techniques in both predictive power and robustness. Furthermore, we develop a methodology of ensembling, Multi-Swarm Ensemble (MSWE) by using multiple particle swarm optimizations and demonstrate its ability to further enhance the performance of ensembles.

Scaling NS-3 DCE Experiments on Multi-Core Servers

DTIC Science & Technology

2016-06-15

that work well together. 3.2 Simulation Server Details We ran the simulations on a Dell® PowerEdge M520 blade server[8] running Ubuntu Linux 14.04...To minimize the amount of time needed to complete all of the simulations, we planned to run multiple simulations at the same time on a blade server...MacBook was running the simulation inside a virtual machine (Ubuntu 14.04), while the blade server was running the same operating system directly on

Electric machine for hybrid motor vehicle

DOEpatents

Hsu, John Sheungchun

2007-09-18

A power system for a motor vehicle having an internal combustion engine and an electric machine is disclosed. The electric machine has a stator, a permanent magnet rotor, an uncluttered rotor spaced from the permanent magnet rotor, and at least one secondary core assembly. The power system also has a gearing arrangement for coupling the internal combustion engine to wheels on the vehicle thereby providing a means for the electric machine to both power assist and brake in relation to the output of the internal combustion engine.

Virtualization - A Key Cost Saver in NASA Multi-Mission Ground System Architecture

NASA Technical Reports Server (NTRS)

Swenson, Paul; Kreisler, Stephen; Sager, Jennifer A.; Smith, Dan

2014-01-01

With science team budgets being slashed, and a lack of adequate facilities for science payload teams to operate their instruments, there is a strong need for innovative new ground systems that are able to provide necessary levels of capability processing power, system availability and redundancy while maintaining a small footprint in terms of physical space, power utilization and cooling.The ground system architecture being presented is based off of heritage from several other projects currently in development or operations at Goddard, but was designed and built specifically to meet the needs of the Science and Planetary Operations Control Center (SPOCC) as a low-cost payload command, control, planning and analysis operations center. However, this SPOCC architecture was designed to be generic enough to be re-used partially or in whole by other labs and missions (since its inception that has already happened in several cases!)The SPOCC architecture leverages a highly available VMware-based virtualization cluster with shared SAS Direct-Attached Storage (DAS) to provide an extremely high-performing, low-power-utilization and small-footprint compute environment that provides Virtual Machine resources shared among the various tenant missions in the SPOCC. The storage is also expandable, allowing future missions to chain up to 7 additional 2U chassis of storage at an extremely competitive cost if they require additional archive or virtual machine storage space.The software architecture provides a fully-redundant GMSEC-based message bus architecture based on the ActiveMQ middleware to track all health and safety status within the SPOCC ground system. All virtual machines utilize the GMSEC system agents to report system host health over the GMSEC bus, and spacecraft payload health is monitored using the Hammers Integrated Test and Operations System (ITOS) Galaxy Telemetry and Command (TC) system, which performs near-real-time limit checking and data processing on the downlinked data stream and injects messages into the GMSEC bus that are monitored to automatically page the on-call operator or Systems Administrator (SA) when an off-nominal condition is detected. This architecture, like the LTSP thin clients, are shared across all tenant missions.Other required IT security controls are implemented at the ground system level, including physical access controls, logical system-level authentication authorization management, auditing and reporting, network management and a NIST 800-53 FISMA-Moderate IT Security plan Risk Assessment Contingency Plan, helping multiple missions share the cost of compliance with agency-mandated directives.The SPOCC architecture provides science payload control centers and backup mission operations centers with a cost-effective, standardized approach to virtualizing and monitoring resources that were traditionally multiple racks full of physical machines. The increased agility in deploying new virtual systems and thin client workstations can provide significant savings in personnel costs for maintaining the ground system. The cost savings in procurement, power, rack footprint and cooling as well as the shared multi-mission design greatly reduces upfront cost for missions moving into the facility. Overall, the authors hope that this architecture will become a model for how future NASA operations centers are constructed!

Development of an implantable wireless ECoG 128ch recording device for clinical brain machine interface.

PubMed

Matsushita, Kojiro; Hirata, Masayuki; Suzuki, Takafumi; Ando, Hiroshi; Ota, Yuki; Sato, Fumihiro; Morris, Shyne; Yoshida, Takeshi; Matsuki, Hidetoshi; Yoshimine, Toshiki

2013-01-01

Brain Machine Interface (BMI) is a system that assumes user's intention by analyzing user's brain activities and control devices with the assumed intention. It is considered as one of prospective tools to enhance paralyzed patients' quality of life. In our group, we especially focus on ECoG (electro-corti-gram)-BMI, which requires surgery to place electrodes on the cortex. We try to implant all the devices within the patient's head and abdomen and to transmit the data and power wirelessly. Our device consists of 5 parts: (1) High-density multi-electrodes with a 3D shaped sheet fitting to the individual brain surface to effectively record the ECoG signals; (2) A small circuit board with two integrated circuit chips functioning 128 [ch] analogue amplifiers and A/D converters for ECoG signals; (3) A Wifi data communication & control circuit with the target PC; (4) A non-contact power supply transmitting electrical power minimum 400[mW] to the device 20[mm] away. We developed those devices, integrated them, and, investigated the performance.

Deep convolutional neural network training enrichment using multi-view object-based analysis of Unmanned Aerial systems imagery for wetlands classification

NASA Astrophysics Data System (ADS)

Liu, Tao; Abd-Elrahman, Amr

2018-05-01

Deep convolutional neural network (DCNN) requires massive training datasets to trigger its image classification power, while collecting training samples for remote sensing application is usually an expensive process. When DCNN is simply implemented with traditional object-based image analysis (OBIA) for classification of Unmanned Aerial systems (UAS) orthoimage, its power may be undermined if the number training samples is relatively small. This research aims to develop a novel OBIA classification approach that can take advantage of DCNN by enriching the training dataset automatically using multi-view data. Specifically, this study introduces a Multi-View Object-based classification using Deep convolutional neural network (MODe) method to process UAS images for land cover classification. MODe conducts the classification on multi-view UAS images instead of directly on the orthoimage, and gets the final results via a voting procedure. 10-fold cross validation results show the mean overall classification accuracy increasing substantially from 65.32%, when DCNN was applied on the orthoimage to 82.08% achieved when MODe was implemented. This study also compared the performances of the support vector machine (SVM) and random forest (RF) classifiers with DCNN under traditional OBIA and the proposed multi-view OBIA frameworks. The results indicate that the advantage of DCNN over traditional classifiers in terms of accuracy is more obvious when these classifiers were applied with the proposed multi-view OBIA framework than when these classifiers were applied within the traditional OBIA framework.

An SVM-based solution for fault detection in wind turbines.

PubMed

Santos, Pedro; Villa, Luisa F; Reñones, Aníbal; Bustillo, Andres; Maudes, Jesús

2015-03-09

Research into fault diagnosis in machines with a wide range of variable loads and speeds, such as wind turbines, is of great industrial interest. Analysis of the power signals emitted by wind turbines for the diagnosis of mechanical faults in their mechanical transmission chain is insufficient. A successful diagnosis requires the inclusion of accelerometers to evaluate vibrations. This work presents a multi-sensory system for fault diagnosis in wind turbines, combined with a data-mining solution for the classification of the operational state of the turbine. The selected sensors are accelerometers, in which vibration signals are processed using angular resampling techniques and electrical, torque and speed measurements. Support vector machines (SVMs) are selected for the classification task, including two traditional and two promising new kernels. This multi-sensory system has been validated on a test-bed that simulates the real conditions of wind turbines with two fault typologies: misalignment and imbalance. Comparison of SVM performance with the results of artificial neural networks (ANNs) shows that linear kernel SVM outperforms other kernels and ANNs in terms of accuracy, training and tuning times. The suitability and superior performance of linear SVM is also experimentally analyzed, to conclude that this data acquisition technique generates linearly separable datasets.

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

NASA Astrophysics Data System (ADS)

Datta, Jinia; Chowdhuri, Sumana; Bera, Jitendranath

2016-12-01

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

Methods, systems and apparatus for controlling operation of two alternating current (AC) machines

DOEpatents

Gallegos-Lopez, Gabriel [Torrance, CA; Nagashima, James M [Cerritos, CA; Perisic, Milun [Torrance, CA; Hiti, Silva [Redondo Beach, CA

2012-06-05

A system is provided for controlling two alternating current (AC) machines via a five-phase PWM inverter module. The system comprises a first control loop, a second control loop, and a current command adjustment module. The current command adjustment module operates in conjunction with the first control loop and the second control loop to continuously adjust current command signals that control the first AC machine and the second AC machine such that they share the input voltage available to them without compromising the target mechanical output power of either machine. This way, even when the phase voltage available to either one of the machines decreases, that machine outputs its target mechanical output power.

Efficient provisioning for multi-core applications with LSF

NASA Astrophysics Data System (ADS)

Dal Pra, Stefano

2015-12-01

Tier-1 sites providing computing power for HEP experiments are usually tightly designed for high throughput performances. This is pursued by reducing the variety of supported use cases and tuning for performances those ones, the most important of which have been that of singlecore jobs. Moreover, the usual workload is saturation: each available core in the farm is in use and there are queued jobs waiting for their turn to run. Enabling multi-core jobs thus requires dedicating a number of hosts where to run, and waiting for them to free the needed number of cores. This drain-time introduces a loss of computing power driven by the number of unusable empty cores. As an increasing demand for multi-core capable resources have emerged, a Task Force have been constituted in WLCG, with the goal to define a simple and efficient multi-core resource provisioning model. This paper details the work done at the INFN Tier-1 to enable multi-core support for the LSF batch system, with the intent of reducing to the minimum the average number of unused cores. The adopted strategy has been that of dedicating to multi-core a dynamic set of nodes, whose dimension is mainly driven by the number of pending multi-core requests and fair-share priority of the submitting user. The node status transition, from single to multi core et vice versa, is driven by a finite state machine which is implemented in a custom multi-core director script, running in the cluster. After describing and motivating both the implementation and the details specific to the LSF batch system, results about performance are reported. Factors having positive and negative impact on the overall efficiency are discussed and solutions to reduce at most the negative ones are proposed.

A New Approach to Geoengineering: Manna From Heaven

NASA Astrophysics Data System (ADS)

Ellery, Alex

2015-04-01

Geo-engineering, although controversial, has become an emerging factor in coping with climate change. Although most are terrestrial-based technologies, I focus on a space-based approach implemented through a solar shield system. I present several new elements that essentially render the high-cost criticism moot. Of special relevance are two seemingly unrelated technologies - the Resource Prospector Mission (RPM) to the Moon in 2018 that shall implement a technology demonstration of simple material resource extraction from lunar regolith, and the emergence of multi-material 3D printing technology that promises unprecedented robotic manufacturing capabilities. My research group has begun theoretical and experimentation work in developing the concept of a 3D printed electric motor system from lunar-type resources. The electric motor underlies every universal mechanical machine. Together with 3D printed electronics, I submit that this would enable self-replicating machines to be realised. A detailed exposition on how this may be achieved will be outlined. Such self-replicating machines could construct the spacecraft required to implement a solar shield and solar power satellites in large numbers from lunar resources with the same underlying technologies at extremely low cost.

Description of a 20 kilohertz power distribution system

NASA Technical Reports Server (NTRS)

Hansen, I. G.

1986-01-01

A single phase, 440 VRMS, 20 kHz power distribution system with a regulated sinusoidal wave form is discussed. A single phase power system minimizes the wiring, sensing, and control complexities required in a multi-sourced redundantly distributed power system. The single phase addresses only the distribution links multiphase lower frequency inputs and outputs accommodation techniques are described. While the 440 V operating potential was initially selected for aircraft operating below 50,000 ft, this potential also appears suitable for space power systems. This voltage choice recognizes a reasonable upper limit for semiconductor ratings, yet will direct synthesis of 220 V, 3 power. A 20 kHz operating frequency was selected to be above the range of audibility, minimize the weight of reactive components, yet allow the construction of single power stages of 25 to 30 kW. The regulated sinusoidal distribution system has several advantages. With a regulated voltage, most ac/dc conversions involve rather simple transformer rectifier applications. A sinusoidal distribution system, when used in conjunction with zero crossing switching, represents a minimal source of EMI. The present state of 20 kHz power technology includes computer controls of voltage and/or frequency, low inductance cable, current limiting circuit protection, bi-directional power flow, and motor/generator operating using standard induction machines. A status update and description of each of these items and their significance is presented.

Description of a 20 Kilohertz power distribution system

NASA Technical Reports Server (NTRS)

Hansen, I. G.

1986-01-01

A single phase, 440 VRMS, 20 kHz power distribution system with a regulated sinusoidal wave form is discussed. A single phase power system minimizes the wiring, sensing, and control complexities required in a multi-sourced redundantly distributed power system. The single phase addresses only the distribution link; mulitphase lower frequency inputs and outputs accommodation techniques are described. While the 440 V operating potential was initially selected for aircraft operating below 50,000 ft, this potential also appears suitable for space power systems. This voltage choice recognizes a reasonable upper limit for semiconductor ratings, yet will direct synthesis of 220 V, 3 power. A 20 kHz operating frequency was selected to be above the range of audibility, minimize the weight of reactive components, yet allow the construction of single power stages of 25 to 30 kW. The regulated sinusoidal distribution system has several advantages. With a regulated voltage, most ac/dc conversions involve rather simple transformer rectifier applications. A sinusoidal distribution system, when used in conjunction with zero crossing switching, represents a minimal source of EMI. The present state of 20 kHz power technology includes computer controls of voltage and/or frequency, low inductance cable, current limiting circuit protection, bi-directional power flow, and motor/generator operating using standard induction machines. A status update and description of each of these items and their significance is presented.

Flexible feature-space-construction architecture and its VLSI implementation for multi-scale object detection

NASA Astrophysics Data System (ADS)

Luo, Aiwen; An, Fengwei; Zhang, Xiangyu; Chen, Lei; Huang, Zunkai; Jürgen Mattausch, Hans

2018-04-01

Feature extraction techniques are a cornerstone of object detection in computer-vision-based applications. The detection performance of vison-based detection systems is often degraded by, e.g., changes in the illumination intensity of the light source, foreground-background contrast variations or automatic gain control from the camera. In order to avoid such degradation effects, we present a block-based L1-norm-circuit architecture which is configurable for different image-cell sizes, cell-based feature descriptors and image resolutions according to customization parameters from the circuit input. The incorporated flexibility in both the image resolution and the cell size for multi-scale image pyramids leads to lower computational complexity and power consumption. Additionally, an object-detection prototype for performance evaluation in 65 nm CMOS implements the proposed L1-norm circuit together with a histogram of oriented gradients (HOG) descriptor and a support vector machine (SVM) classifier. The proposed parallel architecture with high hardware efficiency enables real-time processing, high detection robustness, small chip-core area as well as low power consumption for multi-scale object detection.

Estimating Power System Dynamic States Using Extended Kalman Filter

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

Huang, Zhenyu; Schneider, Kevin P.; Nieplocha, Jaroslaw

2014-10-31

Abstract—The state estimation tools which are currently deployed in power system control rooms are based on a steady state assumption. As a result, the suite of operational tools that rely on state estimation results as inputs do not have dynamic information available and their accuracy is compromised. This paper investigates the application of Extended Kalman Filtering techniques for estimating dynamic states in the state estimation process. The new formulated “dynamic state estimation” includes true system dynamics reflected in differential equations, not like previously proposed “dynamic state estimation” which only considers the time-variant snapshots based on steady state modeling. This newmore » dynamic state estimation using Extended Kalman Filter has been successfully tested on a multi-machine system. Sensitivity studies with respect to noise levels, sampling rates, model errors, and parameter errors are presented as well to illustrate the robust performance of the developed dynamic state estimation process.« less

The Simulation Computer Based Learning (SCBL) for Short Circuit Multi Machine Power System Analysis

NASA Astrophysics Data System (ADS)

Rahmaniar; Putri, Maharani

2018-03-01

Strengthening Competitiveness of human resources become the reply of college as a conductor of high fomal education. Electrical Engineering Program UNPAB (Prodi TE UNPAB) as one of the department of electrical engineering that manages the field of electrical engineering expertise has a very important part in preparing human resources (HR), Which is required by where graduates are produced by DE UNPAB, Is expected to be able to compete globally, especially related to the implementation of Asean Economic Community (AEC) which requires the active participation of graduates with competence and quality of human resource competitiveness. Preparation of HR formation Competitive is done with the various strategies contained in the Seven (7) Higher Education Standard, one part of which is the implementation of teaching and learning process in Electrical system analysis with short circuit analysis (SCA) This course is a course The core of which is the basis for the competencies of other subjects in the advanced semester at Development of Computer Based Learning model (CBL) is done in the learning of interference analysis of multi-machine short circuit which includes: (a) Short-circuit One phase, (B) Two-phase Short Circuit Disruption, (c) Ground Short Circuit Disruption, (d) Short Circuit Disruption One Ground Floor Development of CBL learning model for Electrical System Analysis course provides space for students to be more active In learning in solving complex (complicated) problems, so it is thrilling Ilkan flexibility of student learning how to actively solve the problem of short-circuit analysis and to form the active participation of students in learning (Student Center Learning, in the course of electrical power system analysis.

Real English: A Translator to Enable Natural Language Man-Machine Conversation.

ERIC Educational Resources Information Center

Gautin, Harvey

This dissertation presents a pragmatic interpreter/translator called Real English to serve as a natural language man-machine communication interface in a multi-mode on-line information retrieval system. This multi-mode feature affords the user a library-like searching tool by giving him access to a dictionary, lexicon, thesaurus, synonym table,…

Self-Learning Power Control in Wireless Sensor Networks.

PubMed

Chincoli, Michele; Liotta, Antonio

2018-01-27

Current trends in interconnecting myriad smart objects to monetize on Internet of Things applications have led to high-density communications in wireless sensor networks. This aggravates the already over-congested unlicensed radio bands, calling for new mechanisms to improve spectrum management and energy efficiency, such as transmission power control. Existing protocols are based on simplistic heuristics that often approach interference problems (i.e., packet loss, delay and energy waste) by increasing power, leading to detrimental results. The scope of this work is to investigate how machine learning may be used to bring wireless nodes to the lowest possible transmission power level and, in turn, to respect the quality requirements of the overall network. Lowering transmission power has benefits in terms of both energy consumption and interference. We propose a protocol of transmission power control through a reinforcement learning process that we have set in a multi-agent system. The agents are independent learners using the same exploration strategy and reward structure, leading to an overall cooperative network. The simulation results show that the system converges to an equilibrium where each node transmits at the minimum power while respecting high packet reception ratio constraints. Consequently, the system benefits from low energy consumption and packet delay.

Self-Learning Power Control in Wireless Sensor Networks

PubMed Central

Liotta, Antonio

2018-01-01

Current trends in interconnecting myriad smart objects to monetize on Internet of Things applications have led to high-density communications in wireless sensor networks. This aggravates the already over-congested unlicensed radio bands, calling for new mechanisms to improve spectrum management and energy efficiency, such as transmission power control. Existing protocols are based on simplistic heuristics that often approach interference problems (i.e., packet loss, delay and energy waste) by increasing power, leading to detrimental results. The scope of this work is to investigate how machine learning may be used to bring wireless nodes to the lowest possible transmission power level and, in turn, to respect the quality requirements of the overall network. Lowering transmission power has benefits in terms of both energy consumption and interference. We propose a protocol of transmission power control through a reinforcement learning process that we have set in a multi-agent system. The agents are independent learners using the same exploration strategy and reward structure, leading to an overall cooperative network. The simulation results show that the system converges to an equilibrium where each node transmits at the minimum power while respecting high packet reception ratio constraints. Consequently, the system benefits from low energy consumption and packet delay. PMID:29382072

Periodical capacity setting methods for make-to-order multi-machine production systems

PubMed Central

Altendorfer, Klaus; Hübl, Alexander; Jodlbauer, Herbert

2014-01-01

The paper presents different periodical capacity setting methods for make-to-order, multi-machine production systems with stochastic customer required lead times and stochastic processing times to improve service level and tardiness. These methods are developed as decision support when capacity flexibility exists, such as, a certain range of possible working hours a week for example. The methods differ in the amount of information used whereby all are based on the cumulated capacity demand at each machine. In a simulation study the methods’ impact on service level and tardiness is compared to a constant provided capacity for a single and a multi-machine setting. It is shown that the tested capacity setting methods can lead to an increase in service level and a decrease in average tardiness in comparison to a constant provided capacity. The methods using information on processing time and customer required lead time distribution perform best. The results found in this paper can help practitioners to make efficient use of their flexible capacity. PMID:27226649

Load Balancing Strategies for Multi-Block Overset Grid Applications

NASA Technical Reports Server (NTRS)

Djomehri, M. Jahed; Biswas, Rupak; Lopez-Benitez, Noe; Biegel, Bryan (Technical Monitor)

2002-01-01

The multi-block overset grid method is a powerful technique for high-fidelity computational fluid dynamics (CFD) simulations about complex aerospace configurations. The solution process uses a grid system that discretizes the problem domain by using separately generated but overlapping structured grids that periodically update and exchange boundary information through interpolation. For efficient high performance computations of large-scale realistic applications using this methodology, the individual grids must be properly partitioned among the parallel processors. Overall performance, therefore, largely depends on the quality of load balancing. In this paper, we present three different load balancing strategies far overset grids and analyze their effects on the parallel efficiency of a Navier-Stokes CFD application running on an SGI Origin2000 machine.

Failure Analysis of a Complex Learning Framework Incorporating Multi-Modal and Semi-Supervised Learning

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

Pullum, Laura L; Symons, Christopher T

2011-01-01

Machine learning is used in many applications, from machine vision to speech recognition to decision support systems, and is used to test applications. However, though much has been done to evaluate the performance of machine learning algorithms, little has been done to verify the algorithms or examine their failure modes. Moreover, complex learning frameworks often require stepping beyond black box evaluation to distinguish between errors based on natural limits on learning and errors that arise from mistakes in implementation. We present a conceptual architecture, failure model and taxonomy, and failure modes and effects analysis (FMEA) of a semi-supervised, multi-modal learningmore » system, and provide specific examples from its use in a radiological analysis assistant system. The goal of the research described in this paper is to provide a foundation from which dependability analysis of systems using semi-supervised, multi-modal learning can be conducted. The methods presented provide a first step towards that overall goal.« less

Quantum machine learning.

PubMed

Biamonte, Jacob; Wittek, Peter; Pancotti, Nicola; Rebentrost, Patrick; Wiebe, Nathan; Lloyd, Seth

2017-09-13

Fuelled by increasing computer power and algorithmic advances, machine learning techniques have become powerful tools for finding patterns in data. Quantum systems produce atypical patterns that classical systems are thought not to produce efficiently, so it is reasonable to postulate that quantum computers may outperform classical computers on machine learning tasks. The field of quantum machine learning explores how to devise and implement quantum software that could enable machine learning that is faster than that of classical computers. Recent work has produced quantum algorithms that could act as the building blocks of machine learning programs, but the hardware and software challenges are still considerable.

Quantum machine learning

NASA Astrophysics Data System (ADS)

Biamonte, Jacob; Wittek, Peter; Pancotti, Nicola; Rebentrost, Patrick; Wiebe, Nathan; Lloyd, Seth

2017-09-01

Fuelled by increasing computer power and algorithmic advances, machine learning techniques have become powerful tools for finding patterns in data. Quantum systems produce atypical patterns that classical systems are thought not to produce efficiently, so it is reasonable to postulate that quantum computers may outperform classical computers on machine learning tasks. The field of quantum machine learning explores how to devise and implement quantum software that could enable machine learning that is faster than that of classical computers. Recent work has produced quantum algorithms that could act as the building blocks of machine learning programs, but the hardware and software challenges are still considerable.

Control system for, and a method of, heating an operator station of a work machine

DOEpatents

Baker, Thomas M.; Hoff, Brian D.; Akasam, Sivaprasad

2005-04-05

There are situations in which an operator remains in an operator station of a work machine when an engine of the work machine is inactive. The present invention includes a control system for, and a method of, heating the operator station when the engine is inactive. A heating system of the work machine includes an electrically-powered coolant pump, a power source, and at least one piece of warmed machinery. An operator heat controller is moveable between a first and a second position, and is operable to connect the electrically-powered coolant pump to the power source when the engine is inactive and the operator heat controller is in the first position. Thus, by deactivating the engine and then moving the operator heat controller to the first position, the operator may supply electrical energy to the electrically-powered coolant pump, which is operably coupled to heat the operator station.

Designing a mathematical model for integrating dynamic cellular manufacturing into supply chain system

NASA Astrophysics Data System (ADS)

Aalaei, Amin; Davoudpour, Hamid

2012-11-01

This article presents designing a new mathematical model for integrating dynamic cellular manufacturing into supply chain system with an extensive coverage of important manufacturing features consideration of multiple plants location, multi-markets allocation, multi-period planning horizons with demand and part mix variation, machine capacity, and the main constraints are demand of markets satisfaction in each period, machine availability, machine time-capacity, worker assignment, available time of worker, production volume for each plant and the amounts allocated to each market. The aim of the proposed model is to minimize holding and outsourcing costs, inter-cell material handling cost, external transportation cost, procurement & maintenance and overhead cost of machines, setup cost, reconfiguration cost of machines installation and removal, hiring, firing and salary worker costs. Aimed to prove the potential benefits of such a design, presented an example is shown using a proposed model.

ARMAX-Based Transfer Function Model Identification Using Wide-Area Measurement for Adaptive and Coordinated Damping Control

DOE PAGES

Liu, Hesen; Zhu, Lin; Pan, Zhuohong; ...

2015-09-14

One of the main drawbacks of the existing oscillation damping controllers that are designed based on offline dynamic models is adaptivity to the power system operating condition. With the increasing availability of wide-area measurements and the rapid development of system identification techniques, it is possible to identify a measurement-based transfer function model online that can be used to tune the oscillation damping controller. Such a model could capture all dominant oscillation modes for adaptive and coordinated oscillation damping control. our paper describes a comprehensive approach to identify a low-order transfer function model of a power system using a multi-input multi-outputmore » (MIMO) autoregressive moving average exogenous (ARMAX) model. This methodology consists of five steps: 1) input selection; 2) output selection; 3) identification trigger; 4) model estimation; and 5) model validation. The proposed method is validated by using ambient data and ring-down data in the 16-machine 68-bus Northeast Power Coordinating Council system. Our results demonstrate that the measurement-based model using MIMO ARMAX can capture all the dominant oscillation modes. Compared with the MIMO subspace state space model, the MIMO ARMAX model has equivalent accuracy but lower order and improved computational efficiency. The proposed model can be applied for adaptive and coordinated oscillation damping control.« less

Identifying associations between pig pathologies using a multi-dimensional machine learning methodology.

PubMed

Sanchez-Vazquez, Manuel J; Nielen, Mirjam; Edwards, Sandra A; Gunn, George J; Lewis, Fraser I

2012-08-31

Abattoir detected pathologies are of crucial importance to both pig production and food safety. Usually, more than one pathology coexist in a pig herd although it often remains unknown how these different pathologies interrelate to each other. Identification of the associations between different pathologies may facilitate an improved understanding of their underlying biological linkage, and support the veterinarians in encouraging control strategies aimed at reducing the prevalence of not just one, but two or more conditions simultaneously. Multi-dimensional machine learning methodology was used to identify associations between ten typical pathologies in 6485 batches of slaughtered finishing pigs, assisting the comprehension of their biological association. Pathologies potentially associated with septicaemia (e.g. pericarditis, peritonitis) appear interrelated, suggesting on-going bacterial challenges by pathogens such as Haemophilus parasuis and Streptococcus suis. Furthermore, hepatic scarring appears interrelated with both milk spot livers (Ascaris suum) and bacteria-related pathologies, suggesting a potential multi-pathogen nature for this pathology. The application of novel multi-dimensional machine learning methodology provided new insights into how typical pig pathologies are potentially interrelated at batch level. The methodology presented is a powerful exploratory tool to generate hypotheses, applicable to a wide range of studies in veterinary research.

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

Borges, Raymond Charles; Beaver, Justin M; Buckner, Mark A

Power system disturbances are inherently complex and can be attributed to a wide range of sources, including both natural and man-made events. Currently, the power system operators are heavily relied on to make decisions regarding the causes of experienced disturbances and the appropriate course of action as a response. In the case of cyber-attacks against a power system, human judgment is less certain since there is an overt attempt to disguise the attack and deceive the operators as to the true state of the system. To enable the human decision maker, we explore the viability of machine learning as amore » means for discriminating types of power system disturbances, and focus specifically on detecting cyber-attacks where deception is a core tenet of the event. We evaluate various machine learning methods as disturbance discriminators and discuss the practical implications for deploying machine learning systems as an enhancement to existing power system architectures.« less

Multi-Fault Diagnosis of Rolling Bearings via Adaptive Projection Intrinsically Transformed Multivariate Empirical Mode Decomposition and High Order Singular Value Decomposition

PubMed Central

Lv, Yong; Song, Gangbing

2018-01-01

Rolling bearings are important components in rotary machinery systems. In the field of multi-fault diagnosis of rolling bearings, the vibration signal collected from single channels tends to miss some fault characteristic information. Using multiple sensors to collect signals at different locations on the machine to obtain multivariate signal can remedy this problem. The adverse effect of a power imbalance between the various channels is inevitable, and unfavorable for multivariate signal processing. As a useful, multivariate signal processing method, Adaptive-projection has intrinsically transformed multivariate empirical mode decomposition (APIT-MEMD), and exhibits better performance than MEMD by adopting adaptive projection strategy in order to alleviate power imbalances. The filter bank properties of APIT-MEMD are also adopted to enable more accurate and stable intrinsic mode functions (IMFs), and to ease mode mixing problems in multi-fault frequency extractions. By aligning IMF sets into a third order tensor, high order singular value decomposition (HOSVD) can be employed to estimate the fault number. The fault correlation factor (FCF) analysis is used to conduct correlation analysis, in order to determine effective IMFs; the characteristic frequencies of multi-faults can then be extracted. Numerical simulations and the application of multi-fault situation can demonstrate that the proposed method is promising in multi-fault diagnoses of multivariate rolling bearing signal. PMID:29659510

Multi-Fault Diagnosis of Rolling Bearings via Adaptive Projection Intrinsically Transformed Multivariate Empirical Mode Decomposition and High Order Singular Value Decomposition.

PubMed

Yuan, Rui; Lv, Yong; Song, Gangbing

2018-04-16

Rolling bearings are important components in rotary machinery systems. In the field of multi-fault diagnosis of rolling bearings, the vibration signal collected from single channels tends to miss some fault characteristic information. Using multiple sensors to collect signals at different locations on the machine to obtain multivariate signal can remedy this problem. The adverse effect of a power imbalance between the various channels is inevitable, and unfavorable for multivariate signal processing. As a useful, multivariate signal processing method, Adaptive-projection has intrinsically transformed multivariate empirical mode decomposition (APIT-MEMD), and exhibits better performance than MEMD by adopting adaptive projection strategy in order to alleviate power imbalances. The filter bank properties of APIT-MEMD are also adopted to enable more accurate and stable intrinsic mode functions (IMFs), and to ease mode mixing problems in multi-fault frequency extractions. By aligning IMF sets into a third order tensor, high order singular value decomposition (HOSVD) can be employed to estimate the fault number. The fault correlation factor (FCF) analysis is used to conduct correlation analysis, in order to determine effective IMFs; the characteristic frequencies of multi-faults can then be extracted. Numerical simulations and the application of multi-fault situation can demonstrate that the proposed method is promising in multi-fault diagnoses of multivariate rolling bearing signal.

Oil-free centrifugal hydrogen compression technology demonstration

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

Heshmat, Hooshang

2014-05-31

One of the key elements in realizing a mature market for hydrogen vehicles is the deployment of a safe and efficient hydrogen production and delivery infrastructure on a scale that can compete economically with current fuels. The challenge, however, is that hydrogen, being the lightest and smallest of gases with a lower viscosity and density than natural gas, readily migrates through small spaces and is difficult to compresses efficiently. While efficient and cost effective compression technology is crucial to effective pipeline delivery of hydrogen, the compression methods used currently rely on oil lubricated positive displacement (PD) machines. PD compression technologymore » is very costly, has poor reliability and durability, especially for components subjected to wear (e.g., valves, rider bands and piston rings) and contaminates hydrogen with lubricating fluid. Even so called “oil-free” machines use oil lubricants that migrate into and contaminate the gas path. Due to the poor reliability of PD compressors, current hydrogen producers often install duplicate units in order to maintain on-line times of 98-99%. Such machine redundancy adds substantially to system capital costs. As such, DOE deemed that low capital cost, reliable, efficient and oil-free advanced compressor technologies are needed. MiTi’s solution is a completely oil-free, multi-stage, high-speed, centrifugal compressor designed for flow capacity of 500,000 kg/day with a discharge pressure of 1200 psig. The design employs oil-free compliant foil bearings and seals to allow for very high operating speeds, totally contamination free operation, long life and reliability. This design meets the DOE’s performance targets and achieves an extremely aggressive, specific power metric of 0.48 kW-hr/kg and provides significant improvements in reliability/durability, energy efficiency, sealing and freedom from contamination. The multi-stage compressor system concept has been validated through full scale performance testing of a single stage with helium similitude gas at full speed in accordance with ASME PTC-10. The experimental results indicated that aerodynamic performance, with respect to compressor discharge pressure, flow, power and efficiency exceeded theoretical prediction. Dynamic testing of a simulated multistage centrifugal compressor was also completed under a parallel program to validate the integrity and viability of the system concept. The results give strong confidence in the feasibility of the multi-stage design for use in hydrogen gas transportation and delivery from production locations to point of use.« less

A novel multi-model neuro-fuzzy-based MPPT for three-phase grid-connected photovoltaic system

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

Chaouachi, Aymen; Kamel, Rashad M.; Nagasaka, Ken

This paper presents a novel methodology for Maximum Power Point Tracking (MPPT) of a grid-connected 20 kW photovoltaic (PV) system using neuro-fuzzy network. The proposed method predicts the reference PV voltage guarantying optimal power transfer between the PV generator and the main utility grid. The neuro-fuzzy network is composed of a fuzzy rule-based classifier and three multi-layered feed forwarded Artificial Neural Networks (ANN). Inputs of the network (irradiance and temperature) are classified before they are fed into the appropriated ANN for either training or estimation process while the output is the reference voltage. The main advantage of the proposed methodology,more » comparing to a conventional single neural network-based approach, is the distinct generalization ability regarding to the nonlinear and dynamic behavior of a PV generator. In fact, the neuro-fuzzy network is a neural network based multi-model machine learning that defines a set of local models emulating the complex and nonlinear behavior of a PV generator under a wide range of operating conditions. Simulation results under several rapid irradiance variations proved that the proposed MPPT method fulfilled the highest efficiency comparing to a conventional single neural network and the Perturb and Observe (P and O) algorithm dispositive. (author)« less

A Multi-scale, Multi-Model, Machine-Learning Solar Forecasting Technology

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

Hamann, Hendrik F.

The goal of the project was the development and demonstration of a significantly improved solar forecasting technology (short: Watt-sun), which leverages new big data processing technologies and machine-learnt blending between different models and forecast systems. The technology aimed demonstrating major advances in accuracy as measured by existing and new metrics which themselves were developed as part of this project. Finally, the team worked with Independent System Operators (ISOs) and utilities to integrate the forecasts into their operations.

Advanced Propulsion Power Distribution System for Next Generation Electric/Hybrid Vehicle. Phase 1; Preliminary System Studies

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.

Method and system for fault accommodation of machines

NASA Technical Reports Server (NTRS)

Goebel, Kai Frank (Inventor); Subbu, Rajesh Venkat (Inventor); Rausch, Randal Thomas (Inventor); Frederick, Dean Kimball (Inventor)

2011-01-01

A method for multi-objective fault accommodation using predictive modeling is disclosed. The method includes using a simulated machine that simulates a faulted actual machine, and using a simulated controller that simulates an actual controller. A multi-objective optimization process is performed, based on specified control settings for the simulated controller and specified operational scenarios for the simulated machine controlled by the simulated controller, to generate a Pareto frontier-based solution space relating performance of the simulated machine to settings of the simulated controller, including adjustment to the operational scenarios to represent a fault condition of the simulated machine. Control settings of the actual controller are adjusted, represented by the simulated controller, for controlling the actual machine, represented by the simulated machine, in response to a fault condition of the actual machine, based on the Pareto frontier-based solution space, to maximize desirable operational conditions and minimize undesirable operational conditions while operating the actual machine in a region of the solution space defined by the Pareto frontier.

Impact of Offshore Wind Power Integrated by VSC-HVDC on Power Angle Stability of Power Systems

NASA Astrophysics Data System (ADS)

Lu, Haiyang; Tang, Xisheng

2017-05-01

Offshore wind farm connected to grid by VSC-HVDC loses frequency support for power system, so adding frequency control in wind farm and VSC-HVDC system is an effective measure, but it will change wind farm VSC-HVDC’s transient stability on power system. Through theoretical analysis, concluding the relationship between equivalent mechanical power and electromagnetic power of two-machine system with the active power of wind farm VSC-HVDC, then analyzing the impact of wind farm VSC-HVDC with or without frequency control and different frequency control parameters on angle stability of synchronous machine by EEAC. The validity of theoretical analysis has been demonstrated through simulation in PSCAD/EMTDC.

Correlation between use time of machine and decline curve for emerging enterprise information systems

NASA Astrophysics Data System (ADS)

Chang, Yao-Chung; Lai, Chin-Feng; Chuang, Chi-Cheng; Hou, Cheng-Yu

2018-04-01

With the progress of science and technology, more and more machines are adpot to help human life better and more convenient. When the machines have been used for a longer period of time so that the machine components are getting old, the amount of power comsumption will increase and easily cause the machine to overheat. This also causes a waste of invisible resources. If the Internet of Everything (IoE) technologies are able to be applied into the enterprise information systems for monitoring the machines use time, it can not only make energy can be effectively used, but aslo create a safer living environment. To solve the above problem, the correlation predict model is established to collect the data of power consumption converted into power eigenvalues. This study takes the power eigenvalue as the independent variable and use time as the dependent variable in order to establish the decline curve. Ultimately, the scoring and estimation modules are employed to seek the best power eigenvalue as the independent variable. To predict use time, the correlation is discussed between the use time and the decline curve to improve the entire behavioural analysis of the facilitate recognition of the use time of machines.

CANcer-specific Evaluation System (CANES): a high-accuracy platform, for preclinical single/multi-biomarker discovery

PubMed Central

Kwon, Min-Seok; Nam, Seungyoon; Lee, Sungyoung; Ahn, Young Zoo; Chang, Hae Ryung; Kim, Yon Hui; Park, Taesung

2017-01-01

The recent creation of enormous, cancer-related “Big Data” public depositories represents a powerful means for understanding tumorigenesis. However, a consistently accurate system for clinically evaluating single/multi-biomarkers remains lacking, and it has been asserted that oft-failed clinical advancement of biomarkers occurs within the very early stages of biomarker assessment. To address these challenges, we developed a clinically testable, web-based tool, CANcer-specific single/multi-biomarker Evaluation System (CANES), to evaluate biomarker effectiveness, across 2,134 whole transcriptome datasets, from 94,147 biological samples (from 18 tumor types). For user-provided single/multi-biomarkers, CANES evaluates the performance of single/multi-biomarker candidates, based on four classification methods, support vector machine, random forest, neural networks, and classification and regression trees. In addition, CANES offers several advantages over earlier analysis tools, including: 1) survival analysis; 2) evaluation of mature miRNAs as markers for user-defined diagnostic or prognostic purposes; and 3) provision of a “pan-cancer” summary view, based on each single marker. We believe that such “landscape” evaluation of single/multi-biomarkers, for diagnostic therapeutic/prognostic decision-making, will be highly valuable for the discovery and “repurposing” of existing biomarkers (and their specific targeted therapies), leading to improved patient therapeutic stratification, a key component of targeted therapy success for the avoidance of therapy resistance. PMID:29050243

Collective Machine Learning: Team Learning and Classification in Multi-Agent Systems

ERIC Educational Resources Information Center

Gifford, Christopher M.

2009-01-01

This dissertation focuses on the collaboration of multiple heterogeneous, intelligent agents (hardware or software) which collaborate to learn a task and are capable of sharing knowledge. The concept of collaborative learning in multi-agent and multi-robot systems is largely under studied, and represents an area where further research is needed to…

An SVM-Based Solution for Fault Detection in Wind Turbines

PubMed Central

Santos, Pedro; Villa, Luisa F.; Reñones, Aníbal; Bustillo, Andres; Maudes, Jesús

2015-01-01

Research into fault diagnosis in machines with a wide range of variable loads and speeds, such as wind turbines, is of great industrial interest. Analysis of the power signals emitted by wind turbines for the diagnosis of mechanical faults in their mechanical transmission chain is insufficient. A successful diagnosis requires the inclusion of accelerometers to evaluate vibrations. This work presents a multi-sensory system for fault diagnosis in wind turbines, combined with a data-mining solution for the classification of the operational state of the turbine. The selected sensors are accelerometers, in which vibration signals are processed using angular resampling techniques and electrical, torque and speed measurements. Support vector machines (SVMs) are selected for the classification task, including two traditional and two promising new kernels. This multi-sensory system has been validated on a test-bed that simulates the real conditions of wind turbines with two fault typologies: misalignment and imbalance. Comparison of SVM performance with the results of artificial neural networks (ANNs) shows that linear kernel SVM outperforms other kernels and ANNs in terms of accuracy, training and tuning times. The suitability and superior performance of linear SVM is also experimentally analyzed, to conclude that this data acquisition technique generates linearly separable datasets. PMID:25760051

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

A Fully Integrated Wireless Compressed Sensing Neural Signal Acquisition System for Chronic Recording and Brain Machine Interface.

PubMed

Liu, Xilin; Zhang, Milin; Xiong, Tao; Richardson, Andrew G; Lucas, Timothy H; Chin, Peter S; Etienne-Cummings, Ralph; Tran, Trac D; Van der Spiegel, Jan

2016-07-18

Reliable, multi-channel neural recording is critical to the neuroscience research and clinical treatment. However, most hardware development of fully integrated, multi-channel wireless neural recorders to-date, is still in the proof-of-concept stage. To be ready for practical use, the trade-offs between performance, power consumption, device size, robustness, and compatibility need to be carefully taken into account. This paper presents an optimized wireless compressed sensing neural signal recording system. The system takes advantages of both custom integrated circuits and universal compatible wireless solutions. The proposed system includes an implantable wireless system-on-chip (SoC) and an external wireless relay. The SoC integrates 16-channel low-noise neural amplifiers, programmable filters and gain stages, a SAR ADC, a real-time compressed sensing module, and a near field wireless power and data transmission link. The external relay integrates a 32 bit low-power microcontroller with Bluetooth 4.0 wireless module, a programming interface, and an inductive charging unit. The SoC achieves high signal recording quality with minimized power consumption, while reducing the risk of infection from through-skin connectors. The external relay maximizes the compatibility and programmability. The proposed compressed sensing module is highly configurable, featuring a SNDR of 9.78 dB with a compression ratio of 8×. The SoC has been fabricated in a 180 nm standard CMOS technology, occupying 2.1 mm × 0.6 mm silicon area. A pre-implantable system has been assembled to demonstrate the proposed paradigm. The developed system has been successfully used for long-term wireless neural recording in freely behaving rhesus monkey.

Coordinated control of wind generation and energy storage for power system frequency regulation

NASA Astrophysics Data System (ADS)

Baone, Chaitanya Ashok

Large-scale centralized synchronous generators have long been the primary actors in exercising active power and frequency control, and much of the existing grid control framework is predicated upon their dynamic terminal characteristics. Important among these characteristics is the inertia of such generators. These play key roles in determining the electromechanical stability of the electric power grid. Modern wind generator systems are partially or fully connected to the grid through power electronic interfaces, and hence do not present the same level of inertial coupling. The absence of inertial frequency response from modern wind generator systems is a topic of growing concern in power engineering practice, as the penetration of wind generation is expected to grow dramatically in the next few years. Solutions proposed in the literature have sought to address this problem by seeking to mimic the inherent inertial response characteristics of traditional synchronous generators via control loops added to wind generators. Recent literature has raised concerns regarding this approach, and the work here will further examine its shortcomings, motivating approaches that seek to optimally design for the characteristics of the equipment exercising the control, rather than forcing new technologies to mimic the characteristics of synchronous machines. In particular, this work will develop a new approach to power system frequency regulation, with features suited to distributed energy storage devices such as grid-scale batteries and wind turbine speed and blade pitch control. The dynamic characteristics of these new technologies are treated along with existing mechanisms, such as synchronous machine governor control, to develop a comprehensive multi-input control design approach. To make the method practically feasible for geographically distributed power systems, an observer-based distributed control design utilizing phasor measurement unit (PMU) signals along with local measurements is developed. In addition to the system-wide objective of frequency regulation, a local objective of reducing the wind turbine drivetrain stress is considered. Also, an algorithm is proposed to characterize the modal degrees of controllability and observability on a subspace of critical modes of the system, so that the most effective sensor and actuator locations to be used in the control design can be found.

Design description of the Schuchuli Village photovoltaic power system

NASA Technical Reports Server (NTRS)

Ratajczak, A. F.; Vasicek, R. W.; Delombard, R.

1981-01-01

A stand alone photovoltaic (PV) power system for the village of Schuchuli (Gunsight), Arizona, on the Papago Indian Reservation is a limited energy, all 120 V (d.c.) system to which loads cannot be arbitrarily added and consists of a 3.5 kW (peak) PV array, 2380 ampere-hours of battery storage, an electrical equipment building, a 120 V (d.c.) electrical distribution network, and equipment and automatic controls to provide control power for pumping water into an existing water system; operating 15 refrigerators, a clothes washing machine, a sewing machine, and lights for each of the homes and communal buildings. A solar hot water heater supplies hot water for the washing machine and communal laundry. Automatic control systems provide voltage control by limiting the number of PV strings supplying power during system operation and battery charging, and load management for operating high priority at the expense of low priority loads as the main battery becomes depleted.

Implementation and performance of parallel Prolog interpreter

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

Wei, S.; Kale, L.V.; Balkrishna, R.

1988-01-01

In this paper, the authors discuss the implementation of a parallel Prolog interpreter on different parallel machines. The implementation is based on the REDUCE--OR process model which exploits both AND and OR parallelism in logic programs. It is machine independent as it runs on top of the chare-kernel--a machine-independent parallel programming system. The authors also give the performance of the interpreter running a diverse set of benchmark pargrams on parallel machines including shared memory systems: an Alliant FX/8, Sequent and a MultiMax, and a non-shared memory systems: Intel iPSC/32 hypercube, in addition to its performance on a multiprocessor simulation system.

Three-dimensional tool radius compensation for multi-axis peripheral milling

NASA Astrophysics Data System (ADS)

Chen, Youdong; Wang, Tianmiao

2013-05-01

Few function about 3D tool radius compensation is applied to generating executable motion control commands in the existing computer numerical control (CNC) systems. Once the tool radius is changed, especially in the case of tool size changing with tool wear in machining, a new NC program has to be recreated. A generic 3D tool radius compensation method for multi-axis peripheral milling in CNC systems is presented. The offset path is calculated by offsetting the tool path along the direction of the offset vector with a given distance. The offset vector is perpendicular to both the tangent vector of the tool path and the orientation vector of the tool axis relative to the workpiece. The orientation vector equations of the tool axis relative to the workpiece are obtained through homogeneous coordinate transformation matrix and forward kinematics of generalized kinematics model of multi-axis machine tools. To avoid cutting into the corner formed by the two adjacent tool paths, the coordinates of offset path at the intersection point have been calculated according to the transition type that is determined by the angle between the two tool path tangent vectors at the corner. Through the verification by the solid cutting simulation software VERICUT® with different tool radiuses on a table-tilting type five-axis machine tool, and by the real machining experiment of machining a soup spoon on a five-axis machine tool with the developed CNC system, the effectiveness of the proposed 3D tool radius compensation method is confirmed. The proposed compensation method can be suitable for all kinds of three- to five-axis machine tools as a general form.

Mechanical design of walking machines.

PubMed

Arikawa, Keisuke; Hirose, Shigeo

2007-01-15

The performance of existing actuators, such as electric motors, is very limited, be it power-weight ratio or energy efficiency. In this paper, we discuss the method to design a practical walking machine under this severe constraint with focus on two concepts, the gravitationally decoupled actuation (GDA) and the coupled drive. The GDA decouples the driving system against the gravitational field to suppress generation of negative power and improve energy efficiency. On the other hand, the coupled drive couples the driving system to distribute the output power equally among actuators and maximize the utilization of installed actuator power. First, we depict the GDA and coupled drive in detail. Then, we present actual machines, TITAN-III and VIII, quadruped walking machines designed on the basis of the GDA, and NINJA-I and II, quadruped wall walking machines designed on the basis of the coupled drive. Finally, we discuss walking machines that travel on three-dimensional terrain (3D terrain), which includes the ground, walls and ceiling. Then, we demonstrate with computer simulation that we can selectively leverage GDA and coupled drive by walking posture control.

Dynamic remedial action scheme using online transient stability analysis

NASA Astrophysics Data System (ADS)

Shrestha, Arun

Economic pressure and environmental factors have forced the modern power systems to operate closer to their stability limits. However, maintaining transient stability is a fundamental requirement for the operation of interconnected power systems. In North America, power systems are planned and operated to withstand the loss of any single or multiple elements without violating North American Electric Reliability Corporation (NERC) system performance criteria. For a contingency resulting in the loss of multiple elements (Category C), emergency transient stability controls may be necessary to stabilize the power system. Emergency control is designed to sense abnormal conditions and subsequently take pre-determined remedial actions to prevent instability. Commonly known as either Remedial Action Schemes (RAS) or as Special/System Protection Schemes (SPS), these emergency control approaches have been extensively adopted by utilities. RAS are designed to address specific problems, e.g. to increase power transfer, to provide reactive support, to address generator instability, to limit thermal overloads, etc. Possible remedial actions include generator tripping, load shedding, capacitor and reactor switching, static VAR control, etc. Among various RAS types, generation shedding is the most effective and widely used emergency control means for maintaining system stability. In this dissertation, an optimal power flow (OPF)-based generation-shedding RAS is proposed. This scheme uses online transient stability calculation and generator cost function to determine appropriate remedial actions. For transient stability calculation, SIngle Machine Equivalent (SIME) technique is used, which reduces the multimachine power system model to a One-Machine Infinite Bus (OMIB) equivalent and identifies critical machines. Unlike conventional RAS, which are designed using offline simulations, online stability calculations make the proposed RAS dynamic and adapting to any power system configuration and operating state. The generation-shedding cost is calculated using pre-RAS and post-RAS OPF costs. The criteria for selecting generators to trip is based on the minimum cost rather than minimum amount of generation to shed. For an unstable Category C contingency, the RAS control action that results in stable system with minimum generation shedding cost is selected among possible candidate solutions. The RAS control actions update whenever there is a change in operating condition, system configuration, or cost functions. The effectiveness of the proposed technique is demonstrated by simulations on the IEEE 9-bus system, the IEEE 39-bus system, and IEEE 145-bus system. This dissertation also proposes an improved, yet relatively simple, technique for solving Transient Stability-Constrained Optimal Power Flow (TSC-OPF) problem. Using the SIME method, the sets of dynamic and transient stability constraints are reduced to a single stability constraint, decreasing the overall size of the optimization problem. The transient stability constraint is formulated using the critical machines' power at the initial time step, rather than using the machine rotor angles. This avoids the addition of machine steady state stator algebraic equations in the conventional OPF algorithm. A systematic approach to reach an optimal solution is developed by exploring the quasi-linear behavior of critical machine power and stability margin. The proposed method shifts critical machines active power based on generator costs using an OPF algorithm. Moreover, the transient stability limit is based on stability margin, and not on a heuristically set limit on OMIB rotor angle. As a result, the proposed TSC-OPF solution is more economical and transparent. The proposed technique enables the use of fast and robust commercial OPF tool and time-domain simulation software for solving large scale TSC-OPF problem, which makes the proposed method also suitable for real-time application.

Integrated manufacture of a freeform off-axis multi-reflective imaging system without optical alignment.

PubMed

Li, Zexiao; Liu, Xianlei; Fang, Fengzhou; Zhang, Xiaodong; Zeng, Zhen; Zhu, Linlin; Yan, Ning

2018-03-19

Multi-reflective imaging systems find wide applications in optical imaging and space detection. However, it is faced with difficulties in adjusting the freeform mirrors with high accuracy to guarantee the optical function. Motivated by this, an alignment-free manufacture approach is proposed to machine the optical system. The direct optical performance-guided manufacture route is established without measuring the form error of freeform optics. An analytical model is established to investigate the effects of machine errors to serve the error identification and compensation in machining. Based on the integrated manufactured system, an ingenious self-designed testing configuration is constructed to evaluate the optical performance by directly measuring the wavefront aberration. Experiments are carried out to manufacture a three-mirror anastigmat, surface topographical details and optical performance shows agreement to the designed expectation. The final system works as an off-axis infrared imaging system. Results validate the feasibility of the proposed method to achieve excellent optical application.

A Loader for Executing Multi-Binary Applications on the Thinking Machines CM-5: It's Not Just for SPMD Anymore

NASA Technical Reports Server (NTRS)

Becker, Jeffrey C.

1995-01-01

The Thinking Machines CM-5 platform was designed to run single program, multiple data (SPMD) applications, i.e., to run a single binary across all nodes of a partition, with each node possibly operating on different data. Certain classes of applications, such as multi-disciplinary computational fluid dynamics codes, are facilitated by the ability to have subsets of the partition nodes running different binaries. In order to extend the CM-5 system software to permit such applications, a multi-program loader was developed. This system is based on the dld loader which was originally developed for workstations. This paper provides a high level description of dld, and describes how it was ported to the CM-5 to provide support for multi-binary applications. Finally, it elaborates how the loader has been used to implement the CM-5 version of MPIRUN, a portable facility for running multi-disciplinary/multi-zonal MPI (Message-Passing Interface Standard) codes.

76 FR 81518 - Notice of Issuance of Final Determination Concerning Laser-Based Multi-Function Office Machines

Federal Register 2010, 2011, 2012, 2013, 2014

2011-12-28

... Determination Concerning Laser-Based Multi-Function Office Machines AGENCY: U.S. Customs and Border Protection... country of origin of laser-based multi-function office machines. Based upon the facts presented, CBP has... essential character of the laser-based multi-function office machine, and it is at their assembly and...

A Survey of Recent MARTe Based Systems

NASA Astrophysics Data System (ADS)

Neto, André C.; Alves, Diogo; Boncagni, Luca; Carvalho, Pedro J.; Valcarcel, Daniel F.; Barbalace, Antonio; De Tommasi, Gianmaria; Fernandes, Horácio; Sartori, Filippo; Vitale, Enzo; Vitelli, Riccardo; Zabeo, Luca

2011-08-01

The Multithreaded Application Real-Time executor (MARTe) is a data driven framework environment for the development and deployment of real-time control algorithms. The main ideas which led to the present version of the framework were to standardize the development of real-time control systems, while providing a set of strictly bounded standard interfaces to the outside world and also accommodating a collection of facilities which promote the speed and ease of development, commissioning and deployment of such systems. At the core of every MARTe based application, is a set of independent inter-communicating software blocks, named Generic Application Modules (GAM), orchestrated by a real-time scheduler. The platform independence of its core library provides MARTe the necessary robustness and flexibility for conveniently testing applications in different environments including non-real-time operating systems. MARTe is already being used in several machines, each with its own peculiarities regarding hardware interfacing, supervisory control configuration, operating system and target control application. This paper presents and compares the most recent results of systems using MARTe: the JET Vertical Stabilization system, which uses the Real Time Application Interface (RTAI) operating system on Intel multi-core processors; the COMPASS plasma control system, driven by Linux RT also on Intel multi-core processors; ISTTOK real-time tomography equilibrium reconstruction which shares the same support configuration of COMPASS; JET error field correction coils based on VME, PowerPC and VxWorks; FTU LH reflected power system running on VME, Intel with RTAI.

Development of a low energy micro sheet forming machine

NASA Astrophysics Data System (ADS)

Razali, A. R.; Ann, C. T.; Shariff, H. M.; Kasim, N. I.; Musa, M. A.; Ahmad, A. F.

2017-10-01

It is expected that with the miniaturization of materials being processed, energy consumption is also being `miniaturized' proportionally. The focus of this study was to design a low energy micro-sheet-forming machine for thin sheet metal application and fabricate a low direct current powered micro-sheet-forming machine. A prototype of low energy system for a micro-sheet-forming machine which includes mechanical and electronic elements was developed. The machine was tested for its performance in terms of natural frequency, punching forces, punching speed and capability, energy consumption (single punch and frequency-time based). Based on the experiments, the machine can do 600 stroke per minute and the process is unaffected by the machine's natural frequency. It was also found that sub-Joule of power was required for a single stroke of punching/blanking process. Up to 100micron thick carbon steel shim was successfully tested and punched. It concludes that low power forming machine is feasible to be developed and be used to replace high powered machineries to form micro-products/parts.

Study on on-machine defects measuring system on high power laser optical elements

NASA Astrophysics Data System (ADS)

Luo, Chi; Shi, Feng; Lin, Zhifan; Zhang, Tong; Wang, Guilin

2017-10-01

The influence of surface defects on high power laser optical elements will cause some harm to the performances of imaging system, including the energy consumption and the damage of film layer. To further increase surface defects on high power laser optical element, on-machine defects measuring system was investigated. Firstly, the selection and design are completed by the working condition analysis of the on-machine defects detection system. By designing on processing algorithms to realize the classification recognition and evaluation of surface defects. The calibration experiment of the scratch was done by using the self-made standard alignment plate. Finally, the detection and evaluation of surface defects of large diameter semi-cylindrical silicon mirror are realized. The calibration results show that the size deviation is less than 4% that meet the precision requirement of the detection of the defects. Through the detection of images the on-machine defects detection system can realize the accurate identification of surface defects.

Simultaneous Scheduling of Jobs, AGVs and Tools Considering Tool Transfer Times in Multi Machine FMS By SOS Algorithm

NASA Astrophysics Data System (ADS)

Sivarami Reddy, N.; Ramamurthy, D. V., Dr.; Prahlada Rao, K., Dr.

2017-08-01

This article addresses simultaneous scheduling of machines, AGVs and tools where machines are allowed to share the tools considering transfer times of jobs and tools between machines, to generate best optimal sequences that minimize makespan in a multi-machine Flexible Manufacturing System (FMS). Performance of FMS is expected to improve by effective utilization of its resources, by proper integration and synchronization of their scheduling. Symbiotic Organisms Search (SOS) algorithm is a potent tool which is a better alternative for solving optimization problems like scheduling and proven itself. The proposed SOS algorithm is tested on 22 job sets with makespan as objective for scheduling of machines and tools where machines are allowed to share tools without considering transfer times of jobs and tools and the results are compared with the results of existing methods. The results show that the SOS has outperformed. The same SOS algorithm is used for simultaneous scheduling of machines, AGVs and tools where machines are allowed to share tools considering transfer times of jobs and tools to determine the best optimal sequences that minimize makespan.

Calculation of force and power during bench throws using a Smith machine: the importance of considering the effect of counterweights.

PubMed

Kobayashi, Y; Narazaki, K; Akagi, R; Nakagaki, K; Kawamori, N; Ohta, K

2013-09-01

For achieving accurate and safe measurements of the force and power exerted on a load during resistance exercise, the Smith machine has been used instead of free weights. However, because some Smith machines possess counterweights, the equation for the calculation of force and power in this system should be different from the one used for free weights. The purpose of this investigation was to calculate force and power using an equation derived from a dynamic equation for a Smith machine with counterweights and to determine the differences in force and power calculated using 2 different equations. One equation was established ignoring the effect of the counterweights (Method 1). The other equation was derived from a dynamic equation for a barbell and counterweight system (Method 2). 9 female collegiate judo athletes performed bench throws using a Smith machine with a counterweight at 6 different loading conditions. Barbell displacement was recorded using a linear position transducer. The force and power were subsequently calculated by Methods 1 and 2. The results showed that the mean and peak power and force in Method 1 were significantly lower relative to those of Method 2 under all loading conditions. These results indicate that the mean and peak power and force during bench throwing using a Smith machine with counterweights would be underestimated when the calculations used to determine these parameters do not account for the effect of counterweights. © Georg Thieme Verlag KG Stuttgart · New York.

Public Data Set: Control and Automation of the Pegasus Multi-point Thomson Scattering System

DOE Data Explorer

Bodner, Grant M. [University of Wisconsin-Madison] (ORCID:0000000324979172); Bongard, Michael W. [University of Wisconsin-Madison] (ORCID:0000000231609746); Fonck, Raymond J. [University of Wisconsin-Madison] (ORCID:0000000294386762); Reusch, Joshua A. [University of Wisconsin-Madison] (ORCID:0000000284249422); Rodriguez Sanchez, Cuauhtemoc [University of Wisconsin-Madison] (ORCID:0000000334712586); Schlossberg, David J. [University of Wisconsin-Madison] (ORCID:0000000287139448)

2016-08-12

This public data set contains openly-documented, machine readable digital research data corresponding to figures published in G.M. Bodner et al., 'Control and Automation of the Pegasus Multi-point Thomson Scattering System,' Rev. Sci. Instrum. 87, 11E523 (2016).

Accuracy Improvement of Multi-Axis Systems Based on Laser Correction of Volumetric Geometric Errors

NASA Astrophysics Data System (ADS)

Teleshevsky, V. I.; Sokolov, V. A.; Pimushkin, Ya I.

2018-04-01

The article describes a volumetric geometric errors correction method for CNC- controlled multi-axis systems (machine-tools, CMMs etc.). The Kalman’s concept of “Control and Observation” is used. A versatile multi-function laser interferometer is used as Observer in order to measure machine’s error functions. A systematic error map of machine’s workspace is produced based on error functions measurements. The error map results into error correction strategy. The article proposes a new method of error correction strategy forming. The method is based on error distribution within machine’s workspace and a CNC-program postprocessor. The postprocessor provides minimal error values within maximal workspace zone. The results are confirmed by error correction of precision CNC machine-tools.

Information integration and diagnosis analysis of equipment status and production quality for machining process

NASA Astrophysics Data System (ADS)

Zan, Tao; Wang, Min; Hu, Jianzhong

2010-12-01

Machining status monitoring technique by multi-sensors can acquire and analyze the machining process information to implement abnormity diagnosis and fault warning. Statistical quality control technique is normally used to distinguish abnormal fluctuations from normal fluctuations through statistical method. In this paper by comparing the advantages and disadvantages of the two methods, the necessity and feasibility of integration and fusion is introduced. Then an approach that integrates multi-sensors status monitoring and statistical process control based on artificial intelligent technique, internet technique and database technique is brought forward. Based on virtual instrument technique the author developed the machining quality assurance system - MoniSysOnline, which has been used to monitoring the grinding machining process. By analyzing the quality data and AE signal information of wheel dressing process the reason of machining quality fluctuation has been obtained. The experiment result indicates that the approach is suitable for the status monitoring and analyzing of machining process.

Emotion Recognition from Single-Trial EEG Based on Kernel Fisher's Emotion Pattern and Imbalanced Quasiconformal Kernel Support Vector Machine

PubMed Central

Liu, Yi-Hung; Wu, Chien-Te; Cheng, Wei-Teng; Hsiao, Yu-Tsung; Chen, Po-Ming; Teng, Jyh-Tong

2014-01-01

Electroencephalogram-based emotion recognition (EEG-ER) has received increasing attention in the fields of health care, affective computing, and brain-computer interface (BCI). However, satisfactory ER performance within a bi-dimensional and non-discrete emotional space using single-trial EEG data remains a challenging task. To address this issue, we propose a three-layer scheme for single-trial EEG-ER. In the first layer, a set of spectral powers of different EEG frequency bands are extracted from multi-channel single-trial EEG signals. In the second layer, the kernel Fisher's discriminant analysis method is applied to further extract features with better discrimination ability from the EEG spectral powers. The feature vector produced by layer 2 is called a kernel Fisher's emotion pattern (KFEP), and is sent into layer 3 for further classification where the proposed imbalanced quasiconformal kernel support vector machine (IQK-SVM) serves as the emotion classifier. The outputs of the three layer EEG-ER system include labels of emotional valence and arousal. Furthermore, to collect effective training and testing datasets for the current EEG-ER system, we also use an emotion-induction paradigm in which a set of pictures selected from the International Affective Picture System (IAPS) are employed as emotion induction stimuli. The performance of the proposed three-layer solution is compared with that of other EEG spectral power-based features and emotion classifiers. Results on 10 healthy participants indicate that the proposed KFEP feature performs better than other spectral power features, and IQK-SVM outperforms traditional SVM in terms of the EEG-ER accuracy. Our findings also show that the proposed EEG-ER scheme achieves the highest classification accuracies of valence (82.68%) and arousal (84.79%) among all testing methods. PMID:25061837

Emotion recognition from single-trial EEG based on kernel Fisher's emotion pattern and imbalanced quasiconformal kernel support vector machine.

PubMed

Liu, Yi-Hung; Wu, Chien-Te; Cheng, Wei-Teng; Hsiao, Yu-Tsung; Chen, Po-Ming; Teng, Jyh-Tong

2014-07-24

Electroencephalogram-based emotion recognition (EEG-ER) has received increasing attention in the fields of health care, affective computing, and brain-computer interface (BCI). However, satisfactory ER performance within a bi-dimensional and non-discrete emotional space using single-trial EEG data remains a challenging task. To address this issue, we propose a three-layer scheme for single-trial EEG-ER. In the first layer, a set of spectral powers of different EEG frequency bands are extracted from multi-channel single-trial EEG signals. In the second layer, the kernel Fisher's discriminant analysis method is applied to further extract features with better discrimination ability from the EEG spectral powers. The feature vector produced by layer 2 is called a kernel Fisher's emotion pattern (KFEP), and is sent into layer 3 for further classification where the proposed imbalanced quasiconformal kernel support vector machine (IQK-SVM) serves as the emotion classifier. The outputs of the three layer EEG-ER system include labels of emotional valence and arousal. Furthermore, to collect effective training and testing datasets for the current EEG-ER system, we also use an emotion-induction paradigm in which a set of pictures selected from the International Affective Picture System (IAPS) are employed as emotion induction stimuli. The performance of the proposed three-layer solution is compared with that of other EEG spectral power-based features and emotion classifiers. Results on 10 healthy participants indicate that the proposed KFEP feature performs better than other spectral power features, and IQK-SVM outperforms traditional SVM in terms of the EEG-ER accuracy. Our findings also show that the proposed EEG-ER scheme achieves the highest classification accuracies of valence (82.68%) and arousal (84.79%) among all testing methods.

Heat engine generator control system

DOEpatents

Rajashekara, K.; Gorti, B.V.; McMullen, S.R.; Raibert, R.J.

1998-05-12

An electrical power generation system includes a heat engine having an output member operatively coupled to the rotor of a dynamoelectric machine. System output power is controlled by varying an electrical parameter of the dynamoelectric machine. A power request signal is related to an engine speed and the electrical parameter is varied in accordance with a speed control loop. Initially, the sense of change in the electrical parameter in response to a change in the power request signal is opposite that required to effectuate a steady state output power consistent with the power request signal. Thereafter, the electrical parameter is varied to converge the output member speed to the speed known to be associated with the desired electrical output power. 8 figs.

Heat engine generator control system

DOEpatents

Rajashekara, Kaushik; Gorti, Bhanuprasad Venkata; McMullen, Steven Robert; Raibert, Robert Joseph

1998-01-01

An electrical power generation system includes a heat engine having an output member operatively coupled to the rotor of a dynamoelectric machine. System output power is controlled by varying an electrical parameter of the dynamoelectric machine. A power request signal is related to an engine speed and the electrical parameter is varied in accordance with a speed control loop. Initially, the sense of change in the electrical parameter in response to a change in the power request signal is opposite that required to effectuate a steady state output power consistent with the power request signal. Thereafter, the electrical parameter is varied to converge the output member speed to the speed known to be associated with the desired electrical output power.

Fast 3D NIR systems for facial measurement and lip-reading

NASA Astrophysics Data System (ADS)

Brahm, Anika; Ramm, Roland; Heist, Stefan; Rulff, Christian; Kühmstedt, Peter; Notni, Gunther

2017-05-01

Structured-light projection is a well-established optical method for the non-destructive contactless three-dimensional (3D) measurement of object surfaces. In particular, there is a great demand for accurate and fast 3D scans of human faces or facial regions of interest in medicine, safety, face modeling, games, virtual life, or entertainment. New developments of facial expression detection and machine lip-reading can be used for communication tasks, future machine control, or human-machine interactions. In such cases, 3D information may offer more detailed information than 2D images which can help to increase the power of current facial analysis algorithms. In this contribution, we present new 3D sensor technologies based on three different methods of near-infrared projection technologies in combination with a stereo vision setup of two cameras. We explain the optical principles of an NIR GOBO projector, an array projector and a modified multi-aperture projection method and compare their performance parameters to each other. Further, we show some experimental measurement results of applications where we realized fast, accurate, and irritation-free measurements of human faces.

Triangular Quantum Loop Topography for Machine Learning

NASA Astrophysics Data System (ADS)

Zhang, Yi; Kim, Eun-Ah

Despite rapidly growing interest in harnessing machine learning in the study of quantum many-body systems there has been little success in training neural networks to identify topological phases. The key challenge is in efficiently extracting essential information from the many-body Hamiltonian or wave function and turning the information into an image that can be fed into a neural network. When targeting topological phases, this task becomes particularly challenging as topological phases are defined in terms of non-local properties. Here we introduce triangular quantum loop (TQL) topography: a procedure of constructing a multi-dimensional image from the ''sample'' Hamiltonian or wave function using two-point functions that form triangles. Feeding the TQL topography to a fully-connected neural network with a single hidden layer, we demonstrate that the architecture can be effectively trained to distinguish Chern insulator and fractional Chern insulator from trivial insulators with high fidelity. Given the versatility of the TQL topography procedure that can handle different lattice geometries, disorder, interaction and even degeneracy our work paves the route towards powerful applications of machine learning in the study of topological quantum matters.

Improved Power System Stability Using Backtracking Search Algorithm for Coordination Design of PSS and TCSC Damping Controller.

PubMed

Niamul Islam, Naz; Hannan, M A; Mohamed, Azah; Shareef, Hussain

2016-01-01

Power system oscillation is a serious threat to the stability of multimachine power systems. The coordinated control of power system stabilizers (PSS) and thyristor-controlled series compensation (TCSC) damping controllers is a commonly used technique to provide the required damping over different modes of growing oscillations. However, their coordinated design is a complex multimodal optimization problem that is very hard to solve using traditional tuning techniques. In addition, several limitations of traditionally used techniques prevent the optimum design of coordinated controllers. In this paper, an alternate technique for robust damping over oscillation is presented using backtracking search algorithm (BSA). A 5-area 16-machine benchmark power system is considered to evaluate the design efficiency. The complete design process is conducted in a linear time-invariant (LTI) model of a power system. It includes the design formulation into a multi-objective function from the system eigenvalues. Later on, nonlinear time-domain simulations are used to compare the damping performances for different local and inter-area modes of power system oscillations. The performance of the BSA technique is compared against that of the popular particle swarm optimization (PSO) for coordinated design efficiency. Damping performances using different design techniques are compared in term of settling time and overshoot of oscillations. The results obtained verify that the BSA-based design improves the system stability significantly. The stability of the multimachine power system is improved by up to 74.47% and 79.93% for an inter-area mode and a local mode of oscillation, respectively. Thus, the proposed technique for coordinated design has great potential to improve power system stability and to maintain its secure operation.

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

PubMed

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

2012-07-01

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

MIC-SVM: Designing A Highly Efficient Support Vector Machine For Advanced Modern Multi-Core and Many-Core Architectures

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

You, Yang; Song, Shuaiwen; Fu, Haohuan

2014-08-16

Support Vector Machine (SVM) has been widely used in data-mining and Big Data applications as modern commercial databases start to attach an increasing importance to the analytic capabilities. In recent years, SVM was adapted to the field of High Performance Computing for power/performance prediction, auto-tuning, and runtime scheduling. However, even at the risk of losing prediction accuracy due to insufficient runtime information, researchers can only afford to apply offline model training to avoid significant runtime training overhead. To address the challenges above, we designed and implemented MICSVM, a highly efficient parallel SVM for x86 based multi-core and many core architectures,more » such as the Intel Ivy Bridge CPUs and Intel Xeon Phi coprocessor (MIC).« less

High-precision micro/nano-scale machining system

DOEpatents

Kapoor, Shiv G.; Bourne, Keith Allen; DeVor, Richard E.

2014-08-19

A high precision micro/nanoscale machining system. A multi-axis movement machine provides relative movement along multiple axes between a workpiece and a tool holder. A cutting tool is disposed on a flexible cantilever held by the tool holder, the tool holder being movable to provide at least two of the axes to set the angle and distance of the cutting tool relative to the workpiece. A feedback control system uses measurement of deflection of the cantilever during cutting to maintain a desired cantilever deflection and hence a desired load on the cutting tool.

Ultra-Compact Transputer-Based Controller for High-Level, Multi-Axis Coordination

NASA Technical Reports Server (NTRS)

Zenowich, Brian; Crowell, Adam; Townsend, William T.

2013-01-01

The design of machines that rely on arrays of servomotors such as robotic arms, orbital platforms, and combinations of both, imposes a heavy computational burden to coordinate their actions to perform coherent tasks. For example, the robotic equivalent of a person tracing a straight line in space requires enormously complex kinematics calculations, and complexity increases with the number of servo nodes. A new high-level architecture for coordinated servo-machine control enables a practical, distributed transputer alternative to conventional central processor electronics. The solution is inherently scalable, dramatically reduces bulkiness and number of conductor runs throughout the machine, requires only a fraction of the power, and is designed for cooling in a vacuum.

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

Resource Management in Constrained Dynamic Situations

NASA Astrophysics Data System (ADS)

Seok, Jinwoo

Resource management is considered in this dissertation for systems with limited resources, possibly combined with other system constraints, in unpredictably dynamic environments. Resources may represent fuel, power, capabilities, energy, and so on. Resource management is important for many practical systems; usually, resources are limited, and their use must be optimized. Furthermore, systems are often constrained, and constraints must be satisfied for safe operation. Simplistic resource management can result in poor use of resources and failure of the system. Furthermore, many real-world situations involve dynamic environments. Many traditional problems are formulated based on the assumptions of given probabilities or perfect knowledge of future events. However, in many cases, the future is completely unknown, and information on or probabilities about future events are not available. In other words, we operate in unpredictably dynamic situations. Thus, a method is needed to handle dynamic situations without knowledge of the future, but few formal methods have been developed to address them. Thus, the goal is to design resource management methods for constrained systems, with limited resources, in unpredictably dynamic environments. To this end, resource management is organized hierarchically into two levels: 1) planning, and 2) control. In the planning level, the set of tasks to be performed is scheduled based on limited resources to maximize resource usage in unpredictably dynamic environments. In the control level, the system controller is designed to follow the schedule by considering all the system constraints for safe and efficient operation. Consequently, this dissertation is mainly divided into two parts: 1) planning level design, based on finite state machines, and 2) control level methods, based on model predictive control. We define a recomposable restricted finite state machine to handle limited resource situations and unpredictably dynamic environments for the planning level. To obtain a policy, dynamic programing is applied, and to obtain a solution, limited breadth-first search is applied to the recomposable restricted finite state machine. A multi-function phased array radar resource management problem and an unmanned aerial vehicle patrolling problem are treated using recomposable restricted finite state machines. Then, we use model predictive control for the control level, because it allows constraint handling and setpoint tracking for the schedule. An aircraft power system management problem is treated that aims to develop an integrated control system for an aircraft gas turbine engine and electrical power system using rate-based model predictive control. Our results indicate that at the planning level, limited breadth-first search for recomposable restricted finite state machines generates good scheduling solutions in limited resource situations and unpredictably dynamic environments. The importance of cooperation in the planning level is also verified. At the control level, a rate-based model predictive controller allows good schedule tracking and safe operations. The importance of considering the system constraints and interactions between the subsystems is indicated. For the best resource management in constrained dynamic situations, the planning level and the control level need to be considered together.

The LET Procedure for Prosthetic Myocontrol: Towards Multi-DOF Control Using Single-DOF Activations.

PubMed

Nowak, Markus; Castellini, Claudio

2016-01-01

Simultaneous and proportional myocontrol of dexterous hand prostheses is to a large extent still an open problem. With the advent of commercially and clinically available multi-fingered hand prostheses there are now more independent degrees of freedom (DOFs) in prostheses than can be effectively controlled using surface electromyography (sEMG), the current standard human-machine interface for hand amputees. In particular, it is uncertain, whether several DOFs can be controlled simultaneously and proportionally by exclusively calibrating the intended activation of single DOFs. The problem is currently solved by training on all required combinations. However, as the number of available DOFs grows, this approach becomes overly long and poses a high cognitive burden on the subject. In this paper we present a novel approach to overcome this problem. Multi-DOF activations are artificially modelled from single-DOF ones using a simple linear combination of sEMG signals, which are then added to the training set. This procedure, which we named LET (Linearly Enhanced Training), provides an augmented data set to any machine-learning-based intent detection system. In two experiments involving intact subjects, one offline and one online, we trained a standard machine learning approach using the full data set containing single- and multi-DOF activations as well as using the LET-augmented data set in order to evaluate the performance of the LET procedure. The results indicate that the machine trained on the latter data set obtains worse results in the offline experiment compared to the full data set. However, the online implementation enables the user to perform multi-DOF tasks with almost the same precision as single-DOF tasks without the need of explicitly training multi-DOF activations. Moreover, the parameters involved in the system are statistically uniform across subjects.

Closed Brayton Cycle (CBC) Power Generation from an Electric Systems Perspective

NASA Astrophysics Data System (ADS)

Halsey, David G.; Fox, David A.

2006-01-01

Several forms of closed cycle heat engines exist to produce electrical energy suitable for space exploration or planetary surface applications. These engines include Stirling and Closed Brayton Cycle (CBC). Of these two, CBC has often been cited as providing the best balance of mass and efficiency for deep space or planetary power systems. Combined with an alternator on the same shaft, the hermetically sealed system provides the potential for long life and reliable operation. There is also a list of choices for the type of alternator. Choices include wound rotor machines, induction machines, switched reluctance machines, and permanent magnet generators (PMGs). In trades involving size, mass and efficiency the PMG is a favorable solution. This paper will discuss the consequences of using a CBC-PMG source for an electrical power system, and the system parameters that must be defined and controlled to provide a stable, useful power source. Considerations of voltage, frequency (including DC), and power quality will be discussed. Load interactions and constraints for various power types will also be addressed. Control of the CBC-PMG system during steady state operation and startup is also a factor.s

Design and analysis of an unconventional permanent magnet linear machine for energy harvesting

NASA Astrophysics Data System (ADS)

Zeng, Peng

This Ph.D. dissertation proposes an unconventional high power density linear electromagnetic kinetic energy harvester, and a high-performance two-stage interface power electronics to maintain maximum power abstraction from the energy source and charge the Li-ion battery load with constant current. The proposed machine architecture is composed of a double-sided flat type silicon steel stator with winding slots, a permanent magnet mover, coil windings, a linear motion guide and an adjustable spring bearing. The unconventional design of the machine is that NdFeB magnet bars in the mover are placed with magnetic fields in horizontal direction instead of vertical direction and the same magnetic poles are facing each other. The derived magnetic equivalent circuit model proves the average air-gap flux density of the novel topology is as high as 0.73 T with 17.7% improvement over that of the conventional topology at the given geometric dimensions of the proof-of-concept machine. Subsequently, the improved output voltage and power are achieved. The dynamic model of the linear generator is also developed, and the analytical equations of output maximum power are derived for the case of driving vibration with amplitude that is equal, smaller and larger than the relative displacement between the mover and the stator of the machine respectively. Furthermore, the finite element analysis (FEA) model has been simulated to prove the derived analytical results and the improved power generation capability. Also, an optimization framework is explored to extend to the multi-Degree-of-Freedom (n-DOF) vibration based linear energy harvesting devices. Moreover, a boost-buck cascaded switch mode converter with current controller is designed to extract the maximum power from the harvester and charge the Li-ion battery with trickle current. Meanwhile, a maximum power point tracking (MPPT) algorithm is proposed and optimized for low frequency driving vibrations. Finally, a proof-of-concept unconventional permanent magnet (PM) linear generator is prototyped and tested to verify the simulation results of the FEA model. For the coil windings of 33, 66 and 165 turns, the output power of the machine is tested to have the output power of 65.6 mW, 189.1 mW, and 497.7 mW respectively with the maximum power density of 2.486 mW/cm3.

Dynamic cellular manufacturing system considering machine failure and workload balance

NASA Astrophysics Data System (ADS)

Rabbani, Masoud; Farrokhi-Asl, Hamed; Ravanbakhsh, Mohammad

2018-02-01

Machines are a key element in the production system and their failure causes irreparable effects in terms of cost and time. In this paper, a new multi-objective mathematical model for dynamic cellular manufacturing system (DCMS) is provided with consideration of machine reliability and alternative process routes. In this dynamic model, we attempt to resolve the problem of integrated family (part/machine cell) formation as well as the operators' assignment to the cells. The first objective minimizes the costs associated with the DCMS. The second objective optimizes the labor utilization and, finally, a minimum value of the variance of workload between different cells is obtained by the third objective function. Due to the NP-hard nature of the cellular manufacturing problem, the problem is initially validated by the GAMS software in small-sized problems, and then the model is solved by two well-known meta-heuristic methods including non-dominated sorting genetic algorithm and multi-objective particle swarm optimization in large-scaled problems. Finally, the results of the two algorithms are compared with respect to five different comparison metrics.

Towards the application of one-dimensional sonomyography for powered upper-limb prosthetic control using machine learning models.

PubMed

Guo, Jing-Yi; Zheng, Yong-Ping; Xie, Hong-Bo; Koo, Terry K

2013-02-01

The inherent properties of surface electromyography limit its potential for multi-degrees of freedom control. Our previous studies demonstrated that wrist angle could be predicted by muscle thickness measured from B-mode ultrasound, and hence, it could be an alternative signal for prosthetic control. However, an ultrasound imaging machine is too bulky and expensive. We aim to utilize a portable A-mode ultrasound system to examine the feasibility of using one-dimensional sonomyography (i.e. muscle thickness signals detected by A-mode ultrasound) to predict wrist angle with three different machine learning models - (1) support vector machine (SVM), (2) radial basis function artificial neural network (RBF ANN), and (3) back-propagation artificial neural network (BP ANN). Feasibility study using nine healthy subjects. Each subject performed wrist extension guided at 15, 22.5, and 30 cycles/minute, respectively. Data obtained from 22.5 cycles/minute trials was used to train the models and the remaining trials were used for cross-validation. Prediction accuracy was quantified by relative root mean square error (RMSE) and correlation coefficients (CC). Excellent prediction was noted using SVM (RMSE = 13%, CC = 0.975), which outperformed the other methods. It appears that one-dimensional sonomyography could be an alternative signal for prosthetic control. Clinical relevance Surface electromyography has inherent limitations that prohibit its full functional use for prosthetic control. Research that explores alternative signals to improve prosthetic control (such as the one-dimensional sonomyography signals evaluated in this study) may revolutionize powered prosthesis design and ultimately benefit amputee patients.

Robotics technology discipline

NASA Technical Reports Server (NTRS)

Montemerlo, Melvin D.

1990-01-01

Viewgraphs on robotics technology discipline for Space Station Freedom are presented. Topics covered include: mechanisms; sensors; systems engineering processes for integrated robotics; man/machine cooperative control; 3D-real-time machine perception; multiple arm redundancy control; manipulator control from a movable base; multi-agent reasoning; and surfacing evolution technologies.

Control and protection system for an installation for the combined production of electrical and thermal energy

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

Agazzone, U.; Ausiello, F.P.

1981-06-23

A power-generating installation comprises a plurality of modular power plants each comprised of an internal combustion engine connected to an electric machine. The electric machine is used to start the engine and thereafter operates as a generator supplying power to an electrical network common to all the modular plants. The installation has a control and protection system comprising a plurality of control modules each associated with a respective plant, and a central unit passing control signals to the modules to control starting and stopping of the individual power plants. Upon the detection of abnormal operation or failure of its associatedmore » power plant, each control module transmits an alarm signal back to the central unit which thereupon stops, or prevents the starting, of the corresponding power plant. Parameters monitored by each control module include generated current and inter-winding leakage current of the electric machine.« less

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.

Mechanical Fault Diagnosis of High Voltage Circuit Breakers Based on Variational Mode Decomposition and Multi-Layer Classifier.

PubMed

Huang, Nantian; Chen, Huaijin; Cai, Guowei; Fang, Lihua; Wang, Yuqiang

2016-11-10

Mechanical fault diagnosis of high-voltage circuit breakers (HVCBs) based on vibration signal analysis is one of the most significant issues in improving the reliability and reducing the outage cost for power systems. The limitation of training samples and types of machine faults in HVCBs causes the existing mechanical fault diagnostic methods to recognize new types of machine faults easily without training samples as either a normal condition or a wrong fault type. A new mechanical fault diagnosis method for HVCBs based on variational mode decomposition (VMD) and multi-layer classifier (MLC) is proposed to improve the accuracy of fault diagnosis. First, HVCB vibration signals during operation are measured using an acceleration sensor. Second, a VMD algorithm is used to decompose the vibration signals into several intrinsic mode functions (IMFs). The IMF matrix is divided into submatrices to compute the local singular values (LSV). The maximum singular values of each submatrix are selected as the feature vectors for fault diagnosis. Finally, a MLC composed of two one-class support vector machines (OCSVMs) and a support vector machine (SVM) is constructed to identify the fault type. Two layers of independent OCSVM are adopted to distinguish normal or fault conditions with known or unknown fault types, respectively. On this basis, SVM recognizes the specific fault type. Real diagnostic experiments are conducted with a real SF₆ HVCB with normal and fault states. Three different faults (i.e., jam fault of the iron core, looseness of the base screw, and poor lubrication of the connecting lever) are simulated in a field experiment on a real HVCB to test the feasibility of the proposed method. Results show that the classification accuracy of the new method is superior to other traditional methods.

Mechanical Fault Diagnosis of High Voltage Circuit Breakers Based on Variational Mode Decomposition and Multi-Layer Classifier

PubMed Central

Huang, Nantian; Chen, Huaijin; Cai, Guowei; Fang, Lihua; Wang, Yuqiang

2016-01-01

Mechanical fault diagnosis of high-voltage circuit breakers (HVCBs) based on vibration signal analysis is one of the most significant issues in improving the reliability and reducing the outage cost for power systems. The limitation of training samples and types of machine faults in HVCBs causes the existing mechanical fault diagnostic methods to recognize new types of machine faults easily without training samples as either a normal condition or a wrong fault type. A new mechanical fault diagnosis method for HVCBs based on variational mode decomposition (VMD) and multi-layer classifier (MLC) is proposed to improve the accuracy of fault diagnosis. First, HVCB vibration signals during operation are measured using an acceleration sensor. Second, a VMD algorithm is used to decompose the vibration signals into several intrinsic mode functions (IMFs). The IMF matrix is divided into submatrices to compute the local singular values (LSV). The maximum singular values of each submatrix are selected as the feature vectors for fault diagnosis. Finally, a MLC composed of two one-class support vector machines (OCSVMs) and a support vector machine (SVM) is constructed to identify the fault type. Two layers of independent OCSVM are adopted to distinguish normal or fault conditions with known or unknown fault types, respectively. On this basis, SVM recognizes the specific fault type. Real diagnostic experiments are conducted with a real SF6 HVCB with normal and fault states. Three different faults (i.e., jam fault of the iron core, looseness of the base screw, and poor lubrication of the connecting lever) are simulated in a field experiment on a real HVCB to test the feasibility of the proposed method. Results show that the classification accuracy of the new method is superior to other traditional methods. PMID:27834902

Brief analysis of Jiangsu grid security and stability based on multi-infeed DC index in power system

NASA Astrophysics Data System (ADS)

Zhang, Wenjia; Wang, Quanquan; Ge, Yi; Huang, Junhui; Chen, Zhengfang

2018-02-01

The impact of Multi-infeed HVDC has gradually increased to security and stability operating in Jiangsu power grid. In this paper, an appraisal method of Multi-infeed HVDC power grid security and stability is raised with Multi-Infeed Effective Short Circuit Ratio, Multi-Infeed Interaction Factor and Commutation Failure Immunity Index. These indices are adopted in security and stability simulating calculation of Jiangsu Multi-infeed HVDC system. The simulation results indicate that Jiangsu power grid is operating with a strong DC system. It has high level of power grid security and stability, and meet the safety running requirements. Jinpin-Suzhou DC system is located in the receiving end with huge capacity, which is easily leading to commutation failure of the transmission line. In order to resolve this problem, dynamic reactive power compensation can be applied in power grid near Jinpin-Suzhou DC system. Simulation result shows this method is feasible to commutation failure.

Machine vision system for measuring conifer seedling morphology

NASA Astrophysics Data System (ADS)

Rigney, Michael P.; Kranzler, Glenn A.

1995-01-01

A PC-based machine vision system providing rapid measurement of bare-root tree seedling morphological features has been designed. The system uses backlighting and a 2048-pixel line- scan camera to acquire images with transverse resolutions as high as 0.05 mm for precise measurement of stem diameter. Individual seedlings are manually loaded on a conveyor belt and inspected by the vision system in less than 0.25 seconds. Designed for quality control and morphological data acquisition by nursery personnel, the system provides a user-friendly, menu-driven graphical interface. The system automatically locates the seedling root collar and measures stem diameter, shoot height, sturdiness ratio, root mass length, projected shoot and root area, shoot-root area ratio, and percent fine roots. Sample statistics are computed for each measured feature. Measurements for each seedling may be stored for later analysis. Feature measurements may be compared with multi-class quality criteria to determine sample quality or to perform multi-class sorting. Statistical summary and classification reports may be printed to facilitate the communication of quality concerns with grading personnel. Tests were conducted at a commercial forest nursery to evaluate measurement precision. Four quality control personnel measured root collar diameter, stem height, and root mass length on each of 200 conifer seedlings. The same seedlings were inspected four times by the machine vision system. Machine stem diameter measurement precision was four times greater than that of manual measurements. Machine and manual measurements had comparable precision for shoot height and root mass length.

Reactive power generation in high speed induction machines by continuously occurring space-transients

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.

Real-Time Spaceborne Synthetic Aperture Radar Float-Point Imaging System Using Optimized Mapping Methodology and a Multi-Node Parallel Accelerating Technique

PubMed Central

Li, Bingyi; Chen, Liang; Yu, Wenyue; Xie, Yizhuang; Bian, Mingming; Zhang, Qingjun; Pang, Long

2018-01-01

With the development of satellite load technology and very large-scale integrated (VLSI) circuit technology, on-board real-time synthetic aperture radar (SAR) imaging systems have facilitated rapid response to disasters. A key goal of the on-board SAR imaging system design is to achieve high real-time processing performance under severe size, weight, and power consumption constraints. This paper presents a multi-node prototype system for real-time SAR imaging processing. We decompose the commonly used chirp scaling (CS) SAR imaging algorithm into two parts according to the computing features. The linearization and logic-memory optimum allocation methods are adopted to realize the nonlinear part in a reconfigurable structure, and the two-part bandwidth balance method is used to realize the linear part. Thus, float-point SAR imaging processing can be integrated into a single Field Programmable Gate Array (FPGA) chip instead of relying on distributed technologies. A single-processing node requires 10.6 s and consumes 17 W to focus on 25-km swath width, 5-m resolution stripmap SAR raw data with a granularity of 16,384 × 16,384. The design methodology of the multi-FPGA parallel accelerating system under the real-time principle is introduced. As a proof of concept, a prototype with four processing nodes and one master node is implemented using a Xilinx xc6vlx315t FPGA. The weight and volume of one single machine are 10 kg and 32 cm × 24 cm × 20 cm, respectively, and the power consumption is under 100 W. The real-time performance of the proposed design is demonstrated on Chinese Gaofen-3 stripmap continuous imaging. PMID:29495637

Public Data Set: A Novel, Cost-Effective, Multi-Point Thomson Scattering System on the Pegasus Toroidal Experiment

DOE Data Explorer

Schlossberg, David J. [University of Wisconsin-Madison] (ORCID:0000000287139448); Bodner, Grant M. [University of Wisconsin-Madison] (ORCID:0000000324979172); Reusch, Joshua A. [University of Wisconsin-Madison] (ORCID:0000000284249422); Bongard, Michael W. [University of Wisconsin-Madison] (ORCID:0000000231609746); Fonck, Raymond J. [University of Wisconsin-Madison] (ORCID:0000000294386762); Rodriguez Sanchez, Cuauhtemoc [University of Wisconsin-Madison] (ORCID:0000000334712586)

2016-09-16

This public data set contains openly-documented, machine readable digital research data corresponding to figures published in D.J. Schlossberg et. al., 'A Novel, Cost-Effective, Multi-Point Thomson Scattering System on the Pegasus Toroidal Experiment,' Rev. Sci. Instrum. 87, 11E403 (2016).

Detection and Learning of Unexpected Behaviors of Systems of Dynamical Systems by Using the Q2 Abstractions

DTIC Science & Technology

2017-11-01

Finite State Machine ............................................... 21 9 Main Ontological Concepts for Representing Structure of a Multi -Agent...19 NetLogo Simulation of persistent surveillance of circular plume by 4 UAVs ........................36 20 Flocking Emergent Behaviors in Multi -UAV...Region) - Undesirable Group Formation ................................................................................... 40 24 Two UAVs Moving in

Optical system for UV-laser technological equipment

NASA Astrophysics Data System (ADS)

Fedosov, Yuri V.; Romanova, Galina E.; Afanasev, Maxim Ya.

2017-09-01

Recently there has been an intensive development of intelligent industrial equipment that is highly automated and can be rapidly adjusted for certain details. This equipment can be robotics systems, automatic wrappers and markers, CNC machines and 3D printers. The work equipment considered is the system for selective curing of photopolymers using a UV-laser and UV-radiation in such equipment that leads to additional technical difficulties. In many cases for transporting the radiation from the laser to the point processed, a multi-mirror system is used: however, such systems are usually difficult to adjust. Additionally, such multi-mirror systems are usually used as a part of the equipment for laser cutting of metals using high-power IR-lasers. For the UV-lasers, using many mirrors leads to crucial radiation losses because of many reflections. Therefore, during the development of the optical system for technological equipment using UV-laser we need to solve two main problems: to transfer the radiation for the working point with minimum losses and to include the system for controlling/handling the radiation spot position. We introduce a system for working with UV-lasers with 450mW of power and a wavelength of 0.45 μm based on a fiber system. In our modelling and design, we achieve spot sizes of about 300 μm, and the designed optical and mechanical systems (prototypes) were manufactured and assembled. In this paper, we present the layout of the technological unit, the results of the theoretical modelling of some parts of the system and some experimental results.

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

Pierre, John W.; Wies, Richard; Trudnowski, Daniel

Time-synchronized measurements provide rich information for estimating a power-system's electromechanical modal properties via advanced signal processing. This information is becoming critical for the improved operational reliability of interconnected grids. A given mode's properties are described by its frequency, damping, and shape. Modal frequencies and damping are useful indicators of power-system stress, usually declining with increased load or reduced grid capacity. Mode shape provides critical information for operational control actions. This project investigated many advanced techniques for power system identification from measured data focusing on mode frequency and damping ratio estimation. Investigators from the three universities coordinated their effort with Pacificmore » Northwest National Laboratory (PNNL). Significant progress was made on developing appropriate techniques for system identification with confidence intervals and testing those techniques on field measured data and through simulation. Experimental data from the western area power system was provided by PNNL and Bonneville Power Administration (BPA) for both ambient conditions and for signal injection tests. Three large-scale tests were conducted for the western area in 2005 and 2006. Measured field PMU (Phasor Measurement Unit) data was provided to the three universities. A 19-machine simulation model was enhanced for testing the system identification algorithms. Extensive simulations were run with this model to test the performance of the algorithms. University of Wyoming researchers participated in four primary activities: (1) Block and adaptive processing techniques for mode estimation from ambient signals and probing signals, (2) confidence interval estimation, (3) probing signal design and injection method analysis, and (4) performance assessment and validation from simulated and field measured data. Subspace based methods have been use to improve previous results from block processing techniques. Bootstrap techniques have been developed to estimate confidence intervals for the electromechanical modes from field measured data. Results were obtained using injected signal data provided by BPA. A new probing signal was designed that puts more strength into the signal for a given maximum peak to peak swing. Further simulations were conducted on a model based on measured data and with the modifications of the 19-machine simulation model. Montana Tech researchers participated in two primary activities: (1) continued development of the 19-machine simulation test system to include a DC line; and (2) extensive simulation analysis of the various system identification algorithms and bootstrap techniques using the 19 machine model. Researchers at the University of Alaska-Fairbanks focused on the development and testing of adaptive filter algorithms for mode estimation using data generated from simulation models and on data provided in collaboration with BPA and PNNL. There efforts consist of pre-processing field data, testing and refining adaptive filter techniques (specifically the Least Mean Squares (LMS), the Adaptive Step-size LMS (ASLMS), and Error Tracking (ET) algorithms). They also improved convergence of the adaptive algorithms by using an initial estimate from block processing AR method to initialize the weight vector for LMS. Extensive testing was performed on simulated data from the 19 machine model. This project was also extensively involved in the WECC (Western Electricity Coordinating Council) system wide tests carried out in 2005 and 2006. These tests involved injecting known probing signals into the western power grid. One of the primary goals of these tests was the reliable estimation of electromechanical mode properties from measured PMU data. Applied to the system were three types of probing inputs: (1) activation of the Chief Joseph Dynamic Brake, (2) mid-level probing at the Pacific DC Intertie (PDCI), and (3) low-level probing on the PDCI. The Chief Joseph Dynamic Brake is a 1400 MW disturbance to the system and is injected for a half of a second. For the mid and low-level probing, the Celilo terminal of the PDCI is modulated with a known probing signal. Similar but less extensive tests were conducted in June of 2000. The low-level probing signals were designed at the University of Wyoming. A number of important design factors are considered. The designed low-level probing signal used in the tests is a multi-sine signal. Its frequency content is focused in the range of the inter-area electromechanical modes. The most frequently used of these low-level multi-sine signals had a period of over two minutes, a root-mean-square (rms) value of 14 MW, and a peak magnitude of 20 MW. Up to 15 cycles of this probing signal were injected into the system resulting in a processing gain of 15. The resulting measured response at points throughout the system was not much larger than the ambient noise present in the measurements.« less

[Research on infrared safety protection system for machine tool].

PubMed

Zhang, Shuan-Ji; Zhang, Zhi-Ling; Yan, Hui-Ying; Wang, Song-De

2008-04-01

In order to ensure personal safety and prevent injury accident in machine tool operation, an infrared machine tool safety system was designed with infrared transmitting-receiving module, memory self-locked relay and voice recording-playing module. When the operator does not enter the danger area, the system has no response. Once the operator's whole or part of body enters the danger area and shades the infrared beam, the system will alarm and output an control signal to the machine tool executive element, and at the same time, the system makes the machine tool emergency stop to prevent equipment damaged and person injured. The system has a module framework, and has many advantages including safety, reliability, common use, circuit simplicity, maintenance convenience, low power consumption, low costs, working stability, easy debugging, vibration resistance and interference resistance. It is suitable for being installed and used in different machine tools such as punch machine, pour plastic machine, digital control machine, armor plate cutting machine, pipe bending machine, oil pressure machine etc.

Automatic control in multidrive electrotechnical complexes with semiconductor converters

NASA Astrophysics Data System (ADS)

Vasilev, B. U.; Mardashov, D. V.

2017-01-01

The frequency convertor and the automatic control system, which can be used in the multi-drive electromechanical system with a few induction motions, are considered. The paper presents the structure of existing modern multi-drive electric drives inverters, namely, electric drives with a total frequency converter and few electric motions, and an electric drive, in which the converter is used for power supply and control of the independent frequency. It was shown that such technical solutions of frequency converters possess a number of drawbacks. The drawbacks are given. It was shown that the control of technological processes using the electric drive of this structure may be provided under very limited conditions, as the energy efficiency and the level of electromagnetic compatibility of electric drives is low. The authors proposed using a multi-inverter structure with an active rectifier in multidrive electric drives with induction motors frequency converters. The application of such frequency converter may solve the problem of electromagnetic compatibility, namely, consumption of sinusoidal currents from the network and the maintenance of a sinusoidal voltage and energy compatibility, namely, consumption of practically active energy from the network. Also, the paper proposes the use of the automatic control system, which by means of a multi-inverter frequency converter provides separate control of drive machines and flexible regulation of technological processes. The authors present oscillograms, which confirm the described characteristics of the developed electrical drive. The possible subsequent ways to improve the multi-motor drives are also described.

Flexible architecture of data acquisition firmware based on multi-behaviors finite state machine

NASA Astrophysics Data System (ADS)

Arpaia, Pasquale; Cimmino, Pasquale

2016-11-01

A flexible firmware architecture for different kinds of data acquisition systems, ranging from high-precision bench instruments to low-cost wireless transducers networks, is presented. The key component is a multi-behaviors finite state machine, easily configurable to both low- and high-performance requirements, to diverse operating systems, as well as to on-line and batch measurement algorithms. The proposed solution was validated experimentally on three case studies with data acquisition architectures: (i) concentrated, in a high-precision instrument for magnetic measurements at CERN, (ii) decentralized, for telemedicine remote monitoring of patients at home, and (iii) distributed, for remote monitoring of building's energy loss.

High-power picosecond laser with 400W average power for large scale applications

NASA Astrophysics Data System (ADS)

Du, Keming; Brüning, Stephan; Gillner, Arnold

2012-03-01

Laser processing is generally known for low thermal influence, precise energy processing and the possibility to ablate every type of material independent on hardness and vaporisation temperature. The use of ultra-short pulsed lasers offers new possibilities in the manufacturing of high end products with extra high processing qualities. For achieving a sufficient and economical processing speed, high average power is needed. To scale the power for industrial uses the picosecond laser system has been developed, which consists of a seeder, a preamplifier and an end amplifier. With the oscillator/amplifier system more than 400W average power and maximum pulse energy 1mJ was obtained. For study of high speed processing of large embossing metal roller two different ps laser systems have been integrated into a cylinder engraving machine. One of the ps lasers has an average power of 80W while the other has 300W. With this high power ps laser fluencies of up to 30 J/cm2 at pulse repetition rates in the multi MHz range have been achieved. Different materials (Cu, Ni, Al, steel) have been explored for parameters like ablation rate per pulse, ablation geometry, surface roughness, influence of pulse overlap and number of loops. An enhanced ablation quality and an effective ablation rate of 4mm3/min have been achieved by using different scanning systems and an optimized processing strategy. The max. achieved volume rate is 20mm3/min.

Electron beam machining using rotating and shaped beam power distribution

DOEpatents

Elmer, John W.; O'Brien, Dennis W.

1996-01-01

An apparatus and method for electron beam (EB) machining (drilling, cutting and welding) that uses conventional EB guns, power supplies, and welding machine technology without the need for fast bias pulsing technology. The invention involves a magnetic lensing (EB optics) system and electronic controls to: 1) concurrently bend, focus, shape, scan, and rotate the beam to protect the EB gun and to create a desired effective power-density distribution, and 2) rotate or scan this shaped beam in a controlled way. The shaped beam power-density distribution can be measured using a tomographic imaging system. For example, the EB apparatus of this invention has the ability to drill holes in metal having a diameter up to 1000 .mu.m (1 mm or larger), compared to the 250 .mu.m diameter of laser drilling.

Supercomputers ready for use as discovery machines for neuroscience.

PubMed

Helias, Moritz; Kunkel, Susanne; Masumoto, Gen; Igarashi, Jun; Eppler, Jochen Martin; Ishii, Shin; Fukai, Tomoki; Morrison, Abigail; Diesmann, Markus

2012-01-01

NEST is a widely used tool to simulate biological spiking neural networks. Here we explain the improvements, guided by a mathematical model of memory consumption, that enable us to exploit for the first time the computational power of the K supercomputer for neuroscience. Multi-threaded components for wiring and simulation combine 8 cores per MPI process to achieve excellent scaling. K is capable of simulating networks corresponding to a brain area with 10(8) neurons and 10(12) synapses in the worst case scenario of random connectivity; for larger networks of the brain its hierarchical organization can be exploited to constrain the number of communicating computer nodes. We discuss the limits of the software technology, comparing maximum filling scaling plots for K and the JUGENE BG/P system. The usability of these machines for network simulations has become comparable to running simulations on a single PC. Turn-around times in the range of minutes even for the largest systems enable a quasi interactive working style and render simulations on this scale a practical tool for computational neuroscience.

Supercomputers Ready for Use as Discovery Machines for Neuroscience

PubMed Central

Helias, Moritz; Kunkel, Susanne; Masumoto, Gen; Igarashi, Jun; Eppler, Jochen Martin; Ishii, Shin; Fukai, Tomoki; Morrison, Abigail; Diesmann, Markus

2012-01-01

NEST is a widely used tool to simulate biological spiking neural networks. Here we explain the improvements, guided by a mathematical model of memory consumption, that enable us to exploit for the first time the computational power of the K supercomputer for neuroscience. Multi-threaded components for wiring and simulation combine 8 cores per MPI process to achieve excellent scaling. K is capable of simulating networks corresponding to a brain area with 108 neurons and 1012 synapses in the worst case scenario of random connectivity; for larger networks of the brain its hierarchical organization can be exploited to constrain the number of communicating computer nodes. We discuss the limits of the software technology, comparing maximum filling scaling plots for K and the JUGENE BG/P system. The usability of these machines for network simulations has become comparable to running simulations on a single PC. Turn-around times in the range of minutes even for the largest systems enable a quasi interactive working style and render simulations on this scale a practical tool for computational neuroscience. PMID:23129998

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-07-18

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

NREL and IBM Improve Solar Forecasting with Big Data | Energy Systems

Science.gov Websites

forecasting model using deep-machine-learning technology. The multi-scale, multi-model tool, named Watt-sun the first standard suite of metrics for this purpose. Validating Watt-sun at multiple sites across the

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

Power training using pneumatic machines vs. plate-loaded machines to improve muscle power in older adults.

PubMed

Balachandran, Anoop T; Gandia, Kristine; Jacobs, Kevin A; Streiner, David L; Eltoukhy, Moataz; Signorile, Joseph F

2017-11-01

Power training has been shown to be more effective than conventional resistance training for improving physical function in older adults; however, most trials have used pneumatic machines during training. Considering that the general public typically has access to plate-loaded machines, the effectiveness and safety of power training using plate-loaded machines compared to pneumatic machines is an important consideration. The purpose of this investigation was to compare the effects of high-velocity training using pneumatic machines (Pn) versus standard plate-loaded machines (PL). Independently-living older adults, 60years or older were randomized into two groups: pneumatic machine (Pn, n=19) and plate-loaded machine (PL, n=17). After 12weeks of high-velocity training twice per week, groups were analyzed using an intention-to-treat approach. Primary outcomes were lower body power measured using a linear transducer and upper body power using medicine ball throw. Secondary outcomes included lower and upper body muscle muscle strength, the Physical Performance Battery (PPB), gallon jug test, the timed up-and-go test, and self-reported function using the Patient Reported Outcomes Measurement Information System (PROMIS) and an online video questionnaire. Outcome assessors were blinded to group membership. Lower body power significantly improved in both groups (Pn: 19%, PL: 31%), with no significant difference between the groups (Cohen's d=0.4, 95% CI (-1.1, 0.3)). Upper body power significantly improved only in the PL group, but showed no significant difference between the groups (Pn: 3%, PL: 6%). For balance, there was a significant difference between the groups favoring the Pn group (d=0.7, 95% CI (0.1, 1.4)); however, there were no statistically significant differences between groups for PPB, gallon jug transfer, muscle muscle strength, timed up-and-go or self-reported function. No serious adverse events were reported in either of the groups. Pneumatic and plate-loaded machines were effective in improving lower body power and physical function in older adults. The results suggest that power training can be safely and effectively performed by older adults using either pneumatic or plate-loaded machines. Copyright © 2017 Elsevier Inc. All rights reserved.

Final Environmental Assessment for Proposed Multi-Purpose Machine Gun Range at Joint Base McGuire-Dix-Lakehurst (JB MDL), New Jersey

DTIC Science & Technology

2015-09-01

Proposed MPMGR July 2015 JB MDL, New Jersey 2-2 Heating would be accomplished through electrical, geothermal , heat pump, or solar power. No fuel storage...emissions. Further, to the extent feasible, renewable energy (including, but not limited to solar, wind, geothermal 1 biogas, and biomass) and

Defect inspection in hot slab surface: multi-source CCD imaging based fuzzy-rough sets method

NASA Astrophysics Data System (ADS)

Zhao, Liming; Zhang, Yi; Xu, Xiaodong; Xiao, Hong; Huang, Chao

2016-09-01

To provide an accurate surface defects inspection method and make the automation of robust image region of interests(ROI) delineation strategy a reality in production line, a multi-source CCD imaging based fuzzy-rough sets method is proposed for hot slab surface quality assessment. The applicability of the presented method and the devised system are mainly tied to the surface quality inspection for strip, billet and slab surface etcetera. In this work we take into account the complementary advantages in two common machine vision (MV) systems(line array CCD traditional scanning imaging (LS-imaging) and area array CCD laser three-dimensional (3D) scanning imaging (AL-imaging)), and through establishing the model of fuzzy-rough sets in the detection system the seeds for relative fuzzy connectedness(RFC) delineation for ROI can placed adaptively, which introduces the upper and lower approximation sets for RIO definition, and by which the boundary region can be delineated by RFC region competitive classification mechanism. For the first time, a Multi-source CCD imaging based fuzzy-rough sets strategy is attempted for CC-slab surface defects inspection that allows an automatic way of AI algorithms and powerful ROI delineation strategies to be applied to the MV inspection field.

Method and apparatus for characterizing and enhancing the dynamic performance of machine tools

DOEpatents

Barkman, William E; Babelay, Jr., Edwin F

2013-12-17

Disclosed are various systems and methods for assessing and improving the capability of a machine tool. The disclosure applies to machine tools having at least one slide configured to move along a motion axis. Various patterns of dynamic excitation commands are employed to drive the one or more slides, typically involving repetitive short distance displacements. A quantification of a measurable merit of machine tool response to the one or more patterns of dynamic excitation commands is typically derived for the machine tool. Examples of measurable merits of machine tool performance include dynamic one axis positional accuracy of the machine tool, dynamic cross-axis stability of the machine tool, and dynamic multi-axis positional accuracy of the machine tool.

Development of an After-Sales Support Inter-Enterprise Collaboration System Using Information Technologies

NASA Astrophysics Data System (ADS)

Kimura, Toshiaki; Kasai, Fumio; Kamio, Yoichi; Kanda, Yuichi

This research paper discusses a manufacturing support system which supports not only maintenance services but also consulting services for manufacturing systems consisting of multi-vendor machine tools. In order to do this system enables inter-enterprise collaboration between engineering companies and machine tool vendors. The system is called "After-Sales Support Inter-enterprise collaboration System using information Technologies" (ASSIST). This paper describes the concept behind the planned ASSIST, the development of a prototype of the system, and discusses test operation results of the system.

A real time status monitor for transistor bank driver power limit resistor in boost injection kicker power supply

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

Mi, J.; Tan, Y.; Zhang, W.

2011-03-28

For years suffering of Booster Injection Kicker transistor bank driver regulator troubleshooting, a new real time monitor system has been developed. A simple and floating circuit has been designed and tested. This circuit monitor system can monitor the driver regulator power limit resistor status in real time and warn machine operator if the power limit resistor changes values. This paper will mainly introduce the power supply and the new designed monitoring system. This real time resistor monitor circuit shows a useful method to monitor some critical parts in the booster pulse power supply. After two years accelerator operation, it showsmore » that this monitor works well. Previously, we spent a lot of time in booster machine trouble shooting. We will reinstall all 4 PCB into Euro Card Standard Chassis when the power supply system will be updated.« less

Electron beam machining using rotating and shaped beam power distribution

DOEpatents

Elmer, J.W.; O`Brien, D.W.

1996-07-09

An apparatus and method are disclosed for electron beam (EB) machining (drilling, cutting and welding) that uses conventional EB guns, power supplies, and welding machine technology without the need for fast bias pulsing technology. The invention involves a magnetic lensing (EB optics) system and electronic controls to: (1) concurrently bend, focus, shape, scan, and rotate the beam to protect the EB gun and to create a desired effective power-density distribution, and (2) rotate or scan this shaped beam in a controlled way. The shaped beam power-density distribution can be measured using a tomographic imaging system. For example, the EB apparatus of this invention has the ability to drill holes in metal having a diameter up to 1,000 {micro}m (1 mm or larger), compared to the 250 {micro}m diameter of laser drilling. 5 figs.

Power Supply Changes for NSTX Resistive Wall Mode Coils

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

Ramakrishnan, S S.

The National Spherical Torus Experiment (NSTX) has been designed and installed in the existing facilities at Princeton Plasma Physics Laboratory (PPPL). Most of the hardware, plant facilities, auxiliary sub-systems, and power systems originally used for the Tokamak Fusion Test Reactor (TFTR) have been used with suitable modifications to reflect NSTX needs. Prior to 2004, the NSTX power system was feeding twelve (12) circuits in the machine. In 2004 the Resistive Wall Mode (RWM) Coils were installed on the machine to correct error fields. There are six of these coils installed around the machine in the mid-plane. Since these coils needmore » fast and accurate controls, a Switching Power Amplifier (SPA) with three sub-units was procured, installed and commissioned along with other power loop components. Two RWM Coils were connected in series and fed from one SPA sub-unit. After the initial RWM campaign, operational requirements evolved such that each of the RWM coils now requires separate power and control. Hence a second SPA with three sub-units has been procured and installed. The second unit is of improved design and has the controls and power components completely isolated. The existing thyristor rectifier is used as DC Link to both of the Switching Power Amplifiers. The controls for the RWM are integrated into the overall computer control of the DC Power systems for NSTX. This paper describes the design changes in the RWM Power system for NSTX.« less

Virtual Machine Language 2.1

NASA Technical Reports Server (NTRS)

Riedel, Joseph E.; Grasso, Christopher A.

2012-01-01

VML (Virtual Machine Language) is an advanced computing environment that allows spacecraft to operate using mechanisms ranging from simple, time-oriented sequencing to advanced, multicomponent reactive systems. VML has developed in four evolutionary stages. VML 0 is a core execution capability providing multi-threaded command execution, integer data types, and rudimentary branching. VML 1 added named parameterized procedures, extensive polymorphism, data typing, branching, looping issuance of commands using run-time parameters, and named global variables. VML 2 added for loops, data verification, telemetry reaction, and an open flight adaptation architecture. VML 2.1 contains major advances in control flow capabilities for executable state machines. On the resource requirements front, VML 2.1 features a reduced memory footprint in order to fit more capability into modestly sized flight processors, and endian-neutral data access for compatibility with Intel little-endian processors. Sequence packaging has been improved with object-oriented programming constructs and the use of implicit (rather than explicit) time tags on statements. Sequence event detection has been significantly enhanced with multi-variable waiting, which allows a sequence to detect and react to conditions defined by complex expressions with multiple global variables. This multi-variable waiting serves as the basis for implementing parallel rule checking, which in turn, makes possible executable state machines. The new state machine feature in VML 2.1 allows the creation of sophisticated autonomous reactive systems without the need to develop expensive flight software. Users specify named states and transitions, along with the truth conditions required, before taking transitions. Transitions with the same signal name allow separate state machines to coordinate actions: the conditions distributed across all state machines necessary to arm a particular signal are evaluated, and once found true, that signal is raised. The selected signal then causes all identically named transitions in all present state machines to be taken simultaneously. VML 2.1 has relevance to all potential space missions, both manned and unmanned. It was under consideration for use on Orion.

Power Electronics and Electric Machines Publications | Transportation

Science.gov Websites

electric machines. For more information about the following publications, contact Sreekant Narumanchi. A , NREL Software Spray System Evaluation (Software 1.1 MB) Papers 2017 Electric Motor Thermal Management Source: Douglas DeVoto. 2017. 14 pp. NREL/MP-5400-67117. Power Electronics Thermal Management Research

30 CFR 27.24 - Power-shutoff component.

Code of Federal Regulations, 2010 CFR

2010-07-01

... APPROVAL OF MINING PRODUCTS METHANE-MONITORING SYSTEMS Construction and Design Requirements § 27.24 Power... the machine or equipment when actuated by the methane detector at a methane concentration of 2.0... actuated by the methane detector, cause a control circuit to shut down the machine or equipment on which it...

Contention Modeling for Multithreaded Distributed Shared Memory Machines: The Cray XMT

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

Secchi, Simone; Tumeo, Antonino; Villa, Oreste

Distributed Shared Memory (DSM) machines are a wide class of multi-processor computing systems where a large virtually-shared address space is mapped on a network of physically distributed memories. High memory latency and network contention are two of the main factors that limit performance scaling of such architectures. Modern high-performance computing DSM systems have evolved toward exploitation of massive hardware multi-threading and fine-grained memory hashing to tolerate irregular latencies, avoid network hot-spots and enable high scaling. In order to model the performance of such large-scale machines, parallel simulation has been proved to be a promising approach to achieve good accuracy inmore » reasonable times. One of the most critical factors in solving the simulation speed-accuracy trade-off is network modeling. The Cray XMT is a massively multi-threaded supercomputing architecture that belongs to the DSM class, since it implements a globally-shared address space abstraction on top of a physically distributed memory substrate. In this paper, we discuss the development of a contention-aware network model intended to be integrated in a full-system XMT simulator. We start by measuring the effects of network contention in a 128-processor XMT machine and then investigate the trade-off that exists between simulation accuracy and speed, by comparing three network models which operate at different levels of accuracy. The comparison and model validation is performed by executing a string-matching algorithm on the full-system simulator and on the XMT, using three datasets that generate noticeably different contention patterns.« less

LDRD Report: Topological Design Optimization of Convolutes in Next Generation Pulsed Power Devices.

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

Cyr, Eric C.; von Winckel, Gregory John; Kouri, Drew Philip

This LDRD project was developed around the ambitious goal of applying PDE-constrained opti- mization approaches to design Z-machine components whose performance is governed by elec- tromagnetic and plasma models. This report documents the results of this LDRD project. Our differentiating approach was to use topology optimization methods developed for structural design and extend them for application to electromagnetic systems pertinent to the Z-machine. To achieve this objective a suite of optimization algorithms were implemented in the ROL library part of the Trilinos framework. These methods were applied to standalone demonstration problems and the Drekar multi-physics research application. Out of thismore » exploration a new augmented Lagrangian approach to structural design problems was developed. We demonstrate that this approach has favorable mesh-independent performance. Both the final design and the algorithmic performance were independent of the size of the mesh. In addition, topology optimization formulations for the design of conducting networks were developed and demonstrated. Of note, this formulation was used to develop a design for the inner magnetically insulated transmission line on the Z-machine. The resulting electromagnetic device is compared with theoretically postulated designs.« less

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

PubMed

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

2012-01-01

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

StruLocPred: structure-based protein subcellular localisation prediction using multi-class support vector machine.

PubMed

Zhou, Wengang; Dickerson, Julie A

2012-01-01

Knowledge of protein subcellular locations can help decipher a protein's biological function. This work proposes new features: sequence-based: Hybrid Amino Acid Pair (HAAP) and two structure-based: Secondary Structural Element Composition (SSEC) and solvent accessibility state frequency. A multi-class Support Vector Machine is developed to predict the locations. Testing on two established data sets yields better prediction accuracies than the best available systems. Comparisons with existing methods show comparable results to ESLPred2. When StruLocPred is applied to the entire Arabidopsis proteome, over 77% of proteins with known locations match the prediction results. An implementation of this system is at http://wgzhou.ece. iastate.edu/StruLocPred/.

Compact Superconducting Power Systems for Airborne Applications (Postprint)

DTIC Science & Technology

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

Multi-reactor power system configurations for multimegawatt nuclear electric propulsion

NASA Technical Reports Server (NTRS)

George, Jeffrey A.

1991-01-01

A modular, multi-reactor power system and vehicle configuration for piloted nuclear electric propulsion (NEP) missions to Mars is presented. Such a design could provide enhanced system and mission reliability, allowing a comfortable safety margin for early manned flights, and would allow a range of piloted and cargo missions to be performed with a single power system design. Early use of common power modules for cargo missions would also provide progressive flight experience and validation of standardized systems for use in later piloted applications. System and mission analysis are presented to compare single and multi-reactor configurations for piloted Mars missions. A conceptual design for the Hydra modular multi-reactor NEP vehicle is presented.

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.

Diverse applications of advanced man-telerobot interfaces

NASA Technical Reports Server (NTRS)

Mcaffee, Douglas A.

1991-01-01

Advancements in man-machine interfaces and control technologies used in space telerobotics and teleoperators have potential application wherever human operators need to manipulate multi-dimensional spatial relationships. Bilateral six degree-of-freedom position and force cues exchanged between the user and a complex system can broaden and improve the effectiveness of several diverse man-machine interfaces.

Freeform diamond machining of complex monolithic metal optics for integral field systems

NASA Astrophysics Data System (ADS)

Dubbeldam, Cornelis M.; Robertson, David J.; Preuss, Werner

2004-09-01

Implementation of the optical designs of image slicing Integral Field Systems requires accurate alignment of a large number of small (and therefore difficult to manipulate) optical components. In order to facilitate the integration of these complex systems, the Astronomical Instrumentation Group (AIG) of the University of Durham, in collaboration with the Labor für Mikrozerspanung (Laboratory for Precision Machining - LFM) of the University of Bremen, have developed a technique for fabricating monolithic multi-faceted mirror arrays using freeform diamond machining. Using this technique, the inherent accuracy of the diamond machining equipment is exploited to achieve the required relative alignment accuracy of the facets, as well as an excellent optical surface quality for each individual facet. Monolithic arrays manufactured using this freeform diamond machining technique were successfully applied in the Integral Field Unit for the GEMINI Near-InfraRed Spectrograph (GNIRS IFU), which was recently installed at GEMINI South. Details of their fabrication process and optical performance are presented in this paper. In addition, the direction of current development work, conducted under the auspices of the Durham Instrumentation R&D Program supported by the UK Particle Physics and Astronomy Research Council (PPARC), will be discussed. The main emphasis of this research is to improve further the optical performance of diamond machined components, as well as to streamline the production and quality control processes with a view to making this technique suitable for multi-IFU instruments such as KMOS etc., which require series production of large quantities of optical components.

Proceedings of the 1984 IEEE international conference on systems, man and cybernetics

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

Not Available

1984-01-01

This conference contains papers on artificial intelligence, pattern recognition, and man-machine systems. Topics considered include concurrent minimization, a robot programming system, system modeling and simulation, camera calibration, thermal power plants, image processing, fault diagnosis, knowledge-based systems, power systems, hydroelectric power plants, expert systems, and electrical transients.

Real-Time Load-Side Control of Electric Power Systems

NASA Astrophysics Data System (ADS)

Zhao, Changhong

Two trends are emerging from modern electric power systems: the growth of renewable (e.g., solar and wind) generation, and the integration of information technologies and advanced power electronics. The former introduces large, rapid, and random fluctuations in power supply, demand, frequency, and voltage, which become a major challenge for real-time operation of power systems. The latter creates a tremendous number of controllable intelligent endpoints such as smart buildings and appliances, electric vehicles, energy storage devices, and power electronic devices that can sense, compute, communicate, and actuate. Most of these endpoints are distributed on the load side of power systems, in contrast to traditional control resources such as centralized bulk generators. This thesis focuses on controlling power systems in real time, using these load side resources. Specifically, it studies two problems. (1) Distributed load-side frequency control: We establish a mathematical framework to design distributed frequency control algorithms for flexible electric loads. In this framework, we formulate a category of optimization problems, called optimal load control (OLC), to incorporate the goals of frequency control, such as balancing power supply and demand, restoring frequency to its nominal value, restoring inter-area power flows, etc., in a way that minimizes total disutility for the loads to participate in frequency control by deviating from their nominal power usage. By exploiting distributed algorithms to solve OLC and analyzing convergence of these algorithms, we design distributed load-side controllers and prove stability of closed-loop power systems governed by these controllers. This general framework is adapted and applied to different types of power systems described by different models, or to achieve different levels of control goals under different operation scenarios. We first consider a dynamically coherent power system which can be equivalently modeled with a single synchronous machine. We then extend our framework to a multi-machine power network, where we consider primary and secondary frequency controls, linear and nonlinear power flow models, and the interactions between generator dynamics and load control. (2) Two-timescale voltage control: The voltage of a power distribution system must be maintained closely around its nominal value in real time, even in the presence of highly volatile power supply or demand. For this purpose, we jointly control two types of reactive power sources: a capacitor operating at a slow timescale, and a power electronic device, such as a smart inverter or a D-STATCOM, operating at a fast timescale. Their control actions are solved from optimal power flow problems at two timescales. Specifically, the slow-timescale problem is a chance-constrained optimization, which minimizes power loss and regulates the voltage at the current time instant while limiting the probability of future voltage violations due to stochastic changes in power supply or demand. This control framework forms the basis of an optimal sizing problem, which determines the installation capacities of the control devices by minimizing the sum of power loss and capital cost. We develop computationally efficient heuristics to solve the optimal sizing problem and implement real-time control. Numerical experiments show that the proposed sizing and control schemes significantly improve the reliability of voltage control with a moderate increase in cost.

[Extension of cardiac monitoring function by used of ordinary ECG machine].

PubMed

Chen, Zhencheng; Jiang, Yong; Ni, Lili; Wang, Hongyan

2002-06-01

This paper deals with a portable monitor system on liquid crystal display (LCD) based on this available ordinary ECG machine, which is low power and suitable for China's specific condition. Apart from developing the overall scheme of the system, this paper also has completed the design of the hardware and the software. The 80c196 single chip microcomputer is taken as the central microprocessor and real time electrocardiac single is data treated and analyzed in the system. With the performance of ordinary monitor, this machine also possesses the following functions: five types of arrhythmia analysis, alarm, freeze, and record of automatic pappering, convenient in carrying, with alternate-current (AC) or direct-current (DC) powered. The hardware circuit is simplified and the software structure is optimized in this paper. Multiple low power designs and LCD unit design are adopted and completed in it. Popular in usage, low in cost price, the portable monitor system will have a valuable influence on China's monitor system field.

A review on machine learning principles for multi-view biological data integration.

PubMed

Li, Yifeng; Wu, Fang-Xiang; Ngom, Alioune

2018-03-01

Driven by high-throughput sequencing techniques, modern genomic and clinical studies are in a strong need of integrative machine learning models for better use of vast volumes of heterogeneous information in the deep understanding of biological systems and the development of predictive models. How data from multiple sources (called multi-view data) are incorporated in a learning system is a key step for successful analysis. In this article, we provide a comprehensive review on omics and clinical data integration techniques, from a machine learning perspective, for various analyses such as prediction, clustering, dimension reduction and association. We shall show that Bayesian models are able to use prior information and model measurements with various distributions; tree-based methods can either build a tree with all features or collectively make a final decision based on trees learned from each view; kernel methods fuse the similarity matrices learned from individual views together for a final similarity matrix or learning model; network-based fusion methods are capable of inferring direct and indirect associations in a heterogeneous network; matrix factorization models have potential to learn interactions among features from different views; and a range of deep neural networks can be integrated in multi-modal learning for capturing the complex mechanism of biological systems.

Assessing Multi-Person and Person-Machine Distributed Decision Making Using an Extended Psychological Distancing Model

DTIC Science & Technology

1990-02-01

human-to- human communication patterns during situation assessment and cooperative problem solving tasks. The research proposed for the second URRP year...Hardware development. In order to create an environment within which to study multi-channeled human-to- human communication , a multi-media observation...that machine-to- human communication can be used to increase cohesion between humans and intelligent machines and to promote human-machine team

Data Processing And Machine Learning Methods For Multi-Modal Operator State Classification Systems

NASA Technical Reports Server (NTRS)

Hearn, Tristan A.

2015-01-01

This document is intended as an introduction to a set of common signal processing learning methods that may be used in the software portion of a functional crew state monitoring system. This includes overviews of both the theory of the methods involved, as well as examples of implementation. Practical considerations are discussed for implementing modular, flexible, and scalable processing and classification software for a multi-modal, multi-channel monitoring system. Example source code is also given for all of the discussed processing and classification methods.

Optimizing cutting conditions on sustainable machining of aluminum alloy to minimize power consumption

NASA Astrophysics Data System (ADS)

Nur, Rusdi; Suyuti, Muhammad Arsyad; Susanto, Tri Agus

2017-06-01

Aluminum is widely utilized in the industrial sector. There are several advantages of aluminum, i.e. good flexibility and formability, high corrosion resistance and electrical conductivity, and high heat. Despite of these characteristics, however, pure aluminum is rarely used because of its lacks of strength. Thus, most of the aluminum used in the industrial sectors was in the form of alloy form. Sustainable machining can be considered to link with the transformation of input materials and energy/power demand into finished goods. Machining processes are responsible for environmental effects accepting to their power consumption. The cutting conditions have been optimized to minimize the cutting power, which is the power consumed for cutting. This paper presents an experimental study of sustainable machining of Al-11%Si base alloy that was operated without any cooling system to assess the capacity in reducing power consumption. The cutting force was measured and the cutting power was calculated. Both of cutting force and cutting power were analyzed and modeled by using the central composite design (CCD). The result of this study indicated that the cutting speed has an effect on machining performance and that optimum cutting conditions have to be determined, while sustainable machining can be followed in terms of minimizing power consumption and cutting force. The model developed from this study can be used for evaluation process and optimization to determine optimal cutting conditions for the performance of the whole process.

Social and Economic Impact of Solar Electricity at Schuchuli Village

NASA Technical Reports Server (NTRS)

Bifano, W. J.; Ratajczak, A. F.; Bahr, D. M.; Garrett, B. G.

1979-01-01

Schuchuli, a small remote village on the Papago Indian Reservation in southwest Arizona, is 27 kilometers (17 miles) from the nearest available utility power. Its lack of conventional power is due to the prohibitive cost of supplying a small electrical load with a long-distance distribution line. Furthermore, alternate energy sources are expensive and place a burden on the resources of the villagers. On December 16, 1978, as part of a federally funded project, a solar cell power system was put into operation at Schuchuli. The system powers the village water pump, lighting for homes and other village buildings, family refrigerators and a communal washing machine and sewing machine.

The Mod-2 wind turbine development project

NASA Technical Reports Server (NTRS)

Linscott, B. S.; Dennett, J. T.; Gordon, L. H.

1981-01-01

A major phase of the Federal Wind Energy Program, the Mod-2 wind turbine, a second-generation machine developed by the Boeing Engineering and Construction Co. for the U.S. Department of Energy and the Lewis Research Center of the National Aeronautics and Space Administration, is described. The Mod-2 is a large (2.5-MW power rating) horizontal-axis wind turbine designed for the generation of electrical power on utility networks. Three machines were built and are located in a cluster at Goodnoe Hills, Washington. All technical aspects of the project are described: design approach, significant innovation features, the mechanical system, the electrical power system, the control system, and the safety system.

An Attachable Electromagnetic Energy Harvester Driven Wireless Sensing System Demonstrating Milling-Processes and Cutter-Wear/Breakage-Condition Monitoring.

PubMed

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.

An Attachable Electromagnetic Energy Harvester Driven Wireless Sensing System Demonstrating Milling-Processes and Cutter-Wear/Breakage-Condition Monitoring

PubMed Central

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

13. Interior detail, Blacksmith Shop, showing a portion of the ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

13. Interior detail, Blacksmith Shop, showing a portion of the original overhead belt drive system that powered machine tools in the adjacent Machine Shop, Roundhouse Machine Shop Extension, Southern Pacific Railroad Carlin Shops, view to west, 135mm lens. - Southern Pacific Railroad, Carlin Shops, Roundhouse Machine Shop Extension, Foot of Sixth Street, Carlin, Elko County, NV

Machine for applying a two component resin to a roadway surface

DOEpatents

Huszagh, Donald W.

1985-01-01

A portable machine for spraying two component resins onto a roadway, the machine having a pneumatic control system, including apparatus for purging the machine of mixed resin with air and then removing remaining resin with solvent. Interlocks prevent contamination of solvent and resin, and mixed resin can be purged in the event of a power failure.

Machine for applying a two component resin to a roadway surface

DOEpatents

Huszagh, D.W.

1984-01-01

A portable machine for spraying two component resins onto a roadway, the machine having a pneumatic control system, including means for purging the machine of mixed resin with air and then removing remaining resin with solvent. Interlocks prevent contamination of solvent and resin, and mixed resin can be purged in the event of a power failure.

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 of electric control system for automatic vegetable bundling machine

NASA Astrophysics Data System (ADS)

Bao, Yan

2017-06-01

A design can meet the requirements of automatic bale food structure and has the advantages of simple circuit, and the volume is easy to enhance the electric control system of machine carrying bunch of dishes and low cost. The bundle of vegetable machine should meet the sensor to detect and control, in order to meet the control requirements; binding force can be adjusted by the button to achieve; strapping speed also can be adjusted, by the keys to set; sensors and mechanical line connection, convenient operation; can be directly connected with the plug, the 220V power supply can be connected to a power source; if, can work, by the transmission signal sensor, MCU to control the motor, drive and control procedures for small motor. The working principle of LED control circuit and temperature control circuit is described. The design of electric control system of automatic dish machine.

Compensation for Harmonic Currents and Reactive Power in Wind Power Generation System using PWM Inverter

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.

Coreference analysis in clinical notes: a multi-pass sieve with alternate anaphora resolution modules.

PubMed

Jonnalagadda, Siddhartha Reddy; Li, Dingcheng; Sohn, Sunghwan; Wu, Stephen Tze-Inn; Wagholikar, Kavishwar; Torii, Manabu; Liu, Hongfang

2012-01-01

This paper describes the coreference resolution system submitted by Mayo Clinic for the 2011 i2b2/VA/Cincinnati shared task Track 1C. The goal of the task was to construct a system that links the markables corresponding to the same entity. The task organizers provided progress notes and discharge summaries that were annotated with the markables of treatment, problem, test, person, and pronoun. We used a multi-pass sieve algorithm that applies deterministic rules in the order of preciseness and simultaneously gathers information about the entities in the documents. Our system, MedCoref, also uses a state-of-the-art machine learning framework as an alternative to the final, rule-based pronoun resolution sieve. The best system that uses a multi-pass sieve has an overall score of 0.836 (average of B(3), MUC, Blanc, and CEAF F score) for the training set and 0.843 for the test set. A supervised machine learning system that typically uses a single function to find coreferents cannot accommodate irregularities encountered in data especially given the insufficient number of examples. On the other hand, a completely deterministic system could lead to a decrease in recall (sensitivity) when the rules are not exhaustive. The sieve-based framework allows one to combine reliable machine learning components with rules designed by experts. Using relatively simple rules, part-of-speech information, and semantic type properties, an effective coreference resolution system could be designed. The source code of the system described is available at https://sourceforge.net/projects/ohnlp/files/MedCoref.

Improving machine operation management efficiency via improving the vehicle park structure and using the production operation information database

NASA Astrophysics Data System (ADS)

Koptev, V. Yu

2017-02-01

The work represents the results of studying basic interconnected criteria of separate equipment units of the transport network machines fleet, depending on production and mining factors to improve the transport systems management. Justifying the selection of a control system necessitates employing new methodologies and models, augmented with stability and transport flow criteria, accounting for mining work development dynamics on mining sites. A necessary condition is the accounting of technical and operating parameters related to vehicle operation. Modern open pit mining dispatching systems must include such kinds of the information database. An algorithm forming a machine fleet is presented based on multi-variation task solution in connection with defining reasonable operating features of a machine working as a part of a complex. Proposals cited in the work may apply to mining machines (drilling equipment, excavators) and construction equipment (bulldozers, cranes, pile-drivers), city transport and other types of production activities using machine fleet.

Method and apparatus for operating a powertrain system upon detecting a stuck-closed clutch

DOEpatents

Hansen, R. Anthony

2014-02-18

A powertrain system includes a multi-mode transmission having a plurality of torque machines. A method for controlling the powertrain system includes identifying all presently applied clutches including commanded applied clutches and the stuck-closed clutch upon detecting one of the torque-transfer clutches is in a stuck-closed condition. A closed-loop control system is employed to control operation of the multi-mode transmission accounting for all the presently applied clutches.

Next-Generation Machine Learning for Biological Networks.

PubMed

Camacho, Diogo M; Collins, Katherine M; Powers, Rani K; Costello, James C; Collins, James J

2018-06-14

Machine learning, a collection of data-analytical techniques aimed at building predictive models from multi-dimensional datasets, is becoming integral to modern biological research. By enabling one to generate models that learn from large datasets and make predictions on likely outcomes, machine learning can be used to study complex cellular systems such as biological networks. Here, we provide a primer on machine learning for life scientists, including an introduction to deep learning. We discuss opportunities and challenges at the intersection of machine learning and network biology, which could impact disease biology, drug discovery, microbiome research, and synthetic biology. Copyright © 2018 Elsevier Inc. All rights reserved.

Multi-agent grid system Agent-GRID with dynamic load balancing of cluster nodes

NASA Astrophysics Data System (ADS)

Satymbekov, M. N.; Pak, I. T.; Naizabayeva, L.; Nurzhanov, Ch. A.

2017-12-01

In this study the work presents the system designed for automated load balancing of the contributor by analysing the load of compute nodes and the subsequent migration of virtual machines from loaded nodes to less loaded ones. This system increases the performance of cluster nodes and helps in the timely processing of data. A grid system balances the work of cluster nodes the relevance of the system is the award of multi-agent balancing for the solution of such problems.

Intelligent microchip networks: an agent-on-chip synthesis framework for the design of smart and robust sensor networks

NASA Astrophysics Data System (ADS)

Bosse, Stefan

2013-05-01

Sensorial materials consisting of high-density, miniaturized, and embedded sensor networks require new robust and reliable data processing and communication approaches. Structural health monitoring is one major field of application for sensorial materials. Each sensor node provides some kind of sensor, electronics, data processing, and communication with a strong focus on microchip-level implementation to meet the goals of miniaturization and low-power energy environments, a prerequisite for autonomous behaviour and operation. Reliability requires robustness of the entire system in the presence of node, link, data processing, and communication failures. Interaction between nodes is required to manage and distribute information. One common interaction model is the mobile agent. An agent approach provides stronger autonomy than a traditional object or remote-procedure-call based approach. Agents can decide for themselves, which actions are performed, and they are capable of flexible behaviour, reacting on the environment and other agents, providing some degree of robustness. Traditionally multi-agent systems are abstract programming models which are implemented in software and executed on program controlled computer architectures. This approach does not well scale to micro-chip level and requires full equipped computers and communication structures, and the hardware architecture does not consider and reflect the requirements for agent processing and interaction. We propose and demonstrate a novel design paradigm for reliable distributed data processing systems and a synthesis methodology and framework for multi-agent systems implementable entirely on microchip-level with resource and power constrained digital logic supporting Agent-On-Chip architectures (AoC). The agent behaviour and mobility is fully integrated on the micro-chip using pipelined communicating processes implemented with finite-state machines and register-transfer logic. The agent behaviour, interaction (communication), and mobility features are modelled and specified on a machine-independent abstract programming level using a state-based agent behaviour language (APL). With this APL a high-level agent compiler is able to synthesize a hardware model (RTL, VHDL), a software model (C, ML), or a simulation model (XML) suitable to simulate a multi-agent system using the SeSAm simulator framework. Agent communication is provided by a simple tuple-space database implemented on node level providing fault tolerant access of global data. A novel synthesis development kit (SynDK) based on a graph-structured database approach is introduced to support the rapid development of compilers and synthesis tools, used for example for the design and implementation of the APL compiler.

Workout Machine

NASA Technical Reports Server (NTRS)

1995-01-01

The Orbotron is a tri-axle exercise machine patterned after a NASA training simulator for astronaut orientation in the microgravity of space. It has three orbiting rings corresponding to roll, pitch and yaw. The user is in the middle of the inner ring with the stomach remaining in the center of all axes, eliminating dizziness. Human power starts the rings spinning, unlike the NASA air-powered system. Marketed by Fantasy Factory (formerly Orbotron, Inc.), the machine can improve aerobic capacity, strength and endurance in five to seven minute workouts.

A low cost implementation of multi-parameter patient monitor using intersection kernel support vector machine classifier

NASA Astrophysics Data System (ADS)

Mohan, Dhanya; Kumar, C. Santhosh

2016-03-01

Predicting the physiological condition (normal/abnormal) of a patient is highly desirable to enhance the quality of health care. Multi-parameter patient monitors (MPMs) using heart rate, arterial blood pressure, respiration rate and oxygen saturation (S pO2) as input parameters were developed to monitor the condition of patients, with minimum human resource utilization. The Support vector machine (SVM), an advanced machine learning approach popularly used for classification and regression is used for the realization of MPMs. For making MPMs cost effective, we experiment on the hardware implementation of the MPM using support vector machine classifier. The training of the system is done using the matlab environment and the detection of the alarm/noalarm condition is implemented in hardware. We used different kernels for SVM classification and note that the best performance was obtained using intersection kernel SVM (IKSVM). The intersection kernel support vector machine classifier MPM has outperformed the best known MPM using radial basis function kernel by an absoute improvement of 2.74% in accuracy, 1.86% in sensitivity and 3.01% in specificity. The hardware model was developed based on the improved performance system using Verilog Hardware Description Language and was implemented on Altera cyclone-II development board.

Method and system for providing work machine multi-functional user interface

DOEpatents

Hoff, Brian D [Peoria, IL; Akasam, Sivaprasad [Peoria, IL; Baker, Thomas M [Peoria, IL

2007-07-10

A method is performed to provide a multi-functional user interface on a work machine for displaying suggested corrective action. The process includes receiving status information associated with the work machine and analyzing the status information to determine an abnormal condition. The process also includes displaying a warning message on the display device indicating the abnormal condition and determining one or more corrective actions to handle the abnormal condition. Further, the process includes determining an appropriate corrective action among the one or more corrective actions and displaying a recommendation message on the display device reflecting the appropriate corrective action. The process may also include displaying a list including the remaining one or more corrective actions on the display device to provide alternative actions to an operator.

Enter the machine

NASA Astrophysics Data System (ADS)

Palittapongarnpim, Pantita; Sanders, Barry C.

2018-05-01

Quantum tomography infers quantum states from measurement data, but it becomes infeasible for large systems. Machine learning enables tomography of highly entangled many-body states and suggests a new powerful approach to this problem.

Index-based reactive power compensation scheme for voltage regulation

NASA Astrophysics Data System (ADS)

Dike, Damian Obioma

2008-10-01

Increasing demand for electrical power arising from deregulation and the restrictions posed to the construction of new transmission lines by environment, socioeconomic, and political issues had led to higher grid loading. Consequently, voltage instability has become a major concern, and reactive power support is vital to enhance transmission grid performance. Improved reactive power support to distressed grid is possible through the application of relatively unfamiliar emerging technologies of "Flexible AC Transmission Systems (FACTS)" devices and "Distributed Energy Resources (DERS)." In addition to these infrastructure issues, a lack of situational awareness by system operators can cause major power outages as evidenced by the August 14, 2003 widespread North American blackout. This and many other recent major outages have highlighted the inadequacies of existing power system indexes. In this work, a novel "Index-based reactive compensation scheme" appropriate for both on-line and off-line computation of grid status has been developed. A new voltage stability index (Ls-index) suitable for long transmission lines was developed, simulated, and compared to the existing two-machine modeled L-index. This showed the effect of long distance power wheeling amongst regional transmission organizations. The dissertation further provided models for index modulated voltage source converters (VSC) and index-based load flow analysis of both FACTS and microgrid interconnected power systems using the Newton-Raphson's load flow model incorporated with multi-FACTS devices. The developed package has been made user-friendly through the embodiment of interactive graphical user interface and implemented on the IEEE 14, 30, and 300 bus systems. The results showed reactive compensation has system wide-effect, provided readily accessible system status indicators, ensured seamless DERs interconnection through new islanding modes and enhanced VSC utilization. These outcomes may contribute to optimal utilization of compensation devices and available transfer capability as well as reduce system outages through better regulation of power operating voltages.

A Machine Learning Method for Power Prediction on the Mobile Devices.

PubMed

Chen, Da-Ren; Chen, You-Shyang; Chen, Lin-Chih; Hsu, Ming-Yang; Chiang, Kai-Feng

2015-10-01

Energy profiling and estimation have been popular areas of research in multicore mobile architectures. While short sequences of system calls have been recognized by machine learning as pattern descriptions for anomalous detection, power consumption of running processes with respect to system-call patterns are not well studied. In this paper, we propose a fuzzy neural network (FNN) for training and analyzing process execution behaviour with respect to series of system calls, parameters and their power consumptions. On the basis of the patterns of a series of system calls, we develop a power estimation daemon (PED) to analyze and predict the energy consumption of the running process. In the initial stage, PED categorizes sequences of system calls as functional groups and predicts their energy consumptions by FNN. In the operational stage, PED is applied to identify the predefined sequences of system calls invoked by running processes and estimates their energy consumption.

Development of 70 MW class superconducting generator with quick-response excitation

NASA Astrophysics Data System (ADS)

Miyaike, Kiyoshi; Kitajima, Toshio; Ito, Tetsuo

2002-03-01

The development of a superconducting generator had been carried out for 12 years under the first stage of a Super GM project. The 70 MW class model machine with quick response excitation was manufactured and evaluated in the project. This type of superconducting generator improves power system stability against rapid load fluctuations at the power system faults. This model machine achieved all development targets including high stability during rapid excitation control. It was also connected to the actual 77 kV electrical power grid as a synchronous condenser and proved advantages and high-operation reliability of the superconducting generator.

Multi-Cultural Competency-Based Vocational Curricula. Machine Trades. Multi-Cultural Competency-Based Vocational/Technical Curricula Series.

ERIC Educational Resources Information Center

Hepburn, Larry; Shin, Masako

This document, one of eight in a multi-cultural competency-based vocational/technical curricula series, is on machine trades. This program is designed to run 36 weeks and cover 6 instructional areas: use of measuring tools; benchwork/tool bit grinding; lathe work; milling work; precision grinding; and combination machine work. A duty-task index…

Real power regulation design for multi-terminal VSC-HVDC systems

NASA Astrophysics Data System (ADS)

Li, Guo-Jie; Ruan, Si-Ye; Lie, Tek Tjing

2013-06-01

A multi-terminal voltage-source-converter (VSC) based high voltage direct current (HVDC) system is concerned for its flexibility and reliability. In this study, a control strategy for multiple VSCs is proposed to auto-share the real power variation without changing control mode, which is based on "dc voltage droop" power regulation functions. With the proposed power regulation design, the multiple VSCs automatically share the real power change and the VSC-HVDC system is stable even under loss of any one converter while there is no overloading for any individual converter. Simulation results show that it is effective to balance real power for power disturbance and thus improves operation reliability for the multi-terminal VSC-HVDC system by the proposed control strategy.

A FPGA-Based, Granularity-Variable Neuromorphic Processor and Its Application in a MIMO Real-Time Control System.

PubMed

Zhang, Zhen; Ma, Cheng; Zhu, Rong

2017-08-23

Artificial Neural Networks (ANNs), including Deep Neural Networks (DNNs), have become the state-of-the-art methods in machine learning and achieved amazing success in speech recognition, visual object recognition, and many other domains. There are several hardware platforms for developing accelerated implementation of ANN models. Since Field Programmable Gate Array (FPGA) architectures are flexible and can provide high performance per watt of power consumption, they have drawn a number of applications from scientists. In this paper, we propose a FPGA-based, granularity-variable neuromorphic processor (FBGVNP). The traits of FBGVNP can be summarized as granularity variability, scalability, integrated computing, and addressing ability: first, the number of neurons is variable rather than constant in one core; second, the multi-core network scale can be extended in various forms; third, the neuron addressing and computing processes are executed simultaneously. These make the processor more flexible and better suited for different applications. Moreover, a neural network-based controller is mapped to FBGVNP and applied in a multi-input, multi-output, (MIMO) real-time, temperature-sensing and control system. Experiments validate the effectiveness of the neuromorphic processor. The FBGVNP provides a new scheme for building ANNs, which is flexible, highly energy-efficient, and can be applied in many areas.

A FPGA-Based, Granularity-Variable Neuromorphic Processor and Its Application in a MIMO Real-Time Control System

PubMed Central

Zhang, Zhen; Zhu, Rong

2017-01-01

Artificial Neural Networks (ANNs), including Deep Neural Networks (DNNs), have become the state-of-the-art methods in machine learning and achieved amazing success in speech recognition, visual object recognition, and many other domains. There are several hardware platforms for developing accelerated implementation of ANN models. Since Field Programmable Gate Array (FPGA) architectures are flexible and can provide high performance per watt of power consumption, they have drawn a number of applications from scientists. In this paper, we propose a FPGA-based, granularity-variable neuromorphic processor (FBGVNP). The traits of FBGVNP can be summarized as granularity variability, scalability, integrated computing, and addressing ability: first, the number of neurons is variable rather than constant in one core; second, the multi-core network scale can be extended in various forms; third, the neuron addressing and computing processes are executed simultaneously. These make the processor more flexible and better suited for different applications. Moreover, a neural network-based controller is mapped to FBGVNP and applied in a multi-input, multi-output, (MIMO) real-time, temperature-sensing and control system. Experiments validate the effectiveness of the neuromorphic processor. The FBGVNP provides a new scheme for building ANNs, which is flexible, highly energy-efficient, and can be applied in many areas. PMID:28832522

Using Ontologies to Formalize Services Specifications in Multi-Agent Systems

NASA Technical Reports Server (NTRS)

Breitman, Karin Koogan; Filho, Aluizio Haendchen; Haeusler, Edward Hermann

2004-01-01

One key issue in multi-agent systems (MAS) is their ability to interact and exchange information autonomously across applications. To secure agent interoperability, designers must rely on a communication protocol that allows software agents to exchange meaningful information. In this paper we propose using ontologies as such communication protocol. Ontologies capture the semantics of the operations and services provided by agents, allowing interoperability and information exchange in a MAS. Ontologies are a formal, machine processable, representation that allows to capture the semantics of a domain and, to derive meaningful information by way of logical inference. In our proposal we use a formal knowledge representation language (OWL) that translates into Description Logics (a subset of first order logic), thus eliminating ambiguities and providing a solid base for machine based inference. The main contribution of this approach is to make the requirements explicit, centralize the specification in a single document (the ontology itself), at the same that it provides a formal, unambiguous representation that can be processed by automated inference machines.

High-precision laser microcutting and laser microdrilling using diffractive beam-splitting and high-precision flexible beam alignment

NASA Astrophysics Data System (ADS)

Zibner, F.; Fornaroli, C.; Holtkamp, J.; Shachaf, Lior; Kaplan, Natan; Gillner, A.

2017-08-01

High-precision laser micro machining gains more importance in industrial applications every month. Optical systems like the helical optics offer highest quality together with controllable and adjustable drilling geometry, thus as taper angle, aspect ratio and heat effected zone. The helical optics is based on a rotating Dove-prism which is mounted in a hollow shaft engine together with other optical elements like wedge prisms and plane plates. Although the achieved quality can be interpreted as extremely high the low process efficiency is a main reason that this manufacturing technology has only limited demand within the industrial market. The objective of the research studies presented in this paper is to dramatically increase process efficiency as well as process flexibility. During the last years, the average power of commercial ultra-short pulsed laser sources has increased significantly. The efficient utilization of the high average laser power in the field of material processing requires an effective distribution of the laser power onto the work piece. One approach to increase the efficiency is the application of beam splitting devices to enable parallel processing. Multi beam processing is used to parallelize the fabrication of periodic structures as most application only require a partial amount of the emitted ultra-short pulsed laser power. In order to achieve highest flexibility while using multi beam processing the single beams are diverted and re-guided in a way that enables the opportunity to process with each partial beam on locally apart probes or semimanufactures.

Mapping groundwater contamination risk of multiple aquifers using multi-model ensemble of machine learning algorithms.

PubMed

Barzegar, Rahim; Moghaddam, Asghar Asghari; Deo, Ravinesh; Fijani, Elham; Tziritis, Evangelos

2018-04-15

Constructing accurate and reliable groundwater risk maps provide scientifically prudent and strategic measures for the protection and management of groundwater. The objectives of this paper are to design and validate machine learning based-risk maps using ensemble-based modelling with an integrative approach. We employ the extreme learning machines (ELM), multivariate regression splines (MARS), M5 Tree and support vector regression (SVR) applied in multiple aquifer systems (e.g. unconfined, semi-confined and confined) in the Marand plain, North West Iran, to encapsulate the merits of individual learning algorithms in a final committee-based ANN model. The DRASTIC Vulnerability Index (VI) ranged from 56.7 to 128.1, categorized with no risk, low and moderate vulnerability thresholds. The correlation coefficient (r) and Willmott's Index (d) between NO 3 concentrations and VI were 0.64 and 0.314, respectively. To introduce improvements in the original DRASTIC method, the vulnerability indices were adjusted by NO 3 concentrations, termed as the groundwater contamination risk (GCR). Seven DRASTIC parameters utilized as the model inputs and GCR values utilized as the outputs of individual machine learning models were served in the fully optimized committee-based ANN-predictive model. The correlation indicators demonstrated that the ELM and SVR models outperformed the MARS and M5 Tree models, by virtue of a larger d and r value. Subsequently, the r and d metrics for the ANN-committee based multi-model in the testing phase were 0.8889 and 0.7913, respectively; revealing the superiority of the integrated (or ensemble) machine learning models when compared with the original DRASTIC approach. The newly designed multi-model ensemble-based approach can be considered as a pragmatic step for mapping groundwater contamination risks of multiple aquifer systems with multi-model techniques, yielding the high accuracy of the ANN committee-based model. Copyright © 2017 Elsevier B.V. All rights reserved.

A Machine Learns to Predict the Stability of Tightly Packed Planetary Systems

NASA Astrophysics Data System (ADS)

Tamayo, Daniel; Silburt, Ari; Valencia, Diana; Menou, Kristen; Ali-Dib, Mohamad; Petrovich, Cristobal; Huang, Chelsea X.; Rein, Hanno; van Laerhoven, Christa; Paradise, Adiv; Obertas, Alysa; Murray, Norman

2016-12-01

The requirement that planetary systems be dynamically stable is often used to vet new discoveries or set limits on unconstrained masses or orbital elements. This is typically carried out via computationally expensive N-body simulations. We show that characterizing the complicated and multi-dimensional stability boundary of tightly packed systems is amenable to machine-learning methods. We find that training an XGBoost machine-learning algorithm on physically motivated features yields an accurate classifier of stability in packed systems. On the stability timescale investigated (107 orbits), it is three orders of magnitude faster than direct N-body simulations. Optimized machine-learning classifiers for dynamical stability may thus prove useful across the discipline, e.g., to characterize the exoplanet sample discovered by the upcoming Transiting Exoplanet Survey Satellite. This proof of concept motivates investing computational resources to train algorithms capable of predicting stability over longer timescales and over broader regions of phase space.

Hybrid integral-differential simulator of EM force interactions/scenario-assessment tool with pre-computed influence matrix in applications to ITER

NASA Astrophysics Data System (ADS)

Rozov, V.; Alekseev, A.

2015-08-01

A necessity to address a wide spectrum of engineering problems in ITER determined the need for efficient tools for modeling of the magnetic environment and force interactions between the main components of the magnet system. The assessment of the operating window for the machine, determined by the electro-magnetic (EM) forces, and the check of feasibility of particular scenarios play an important role for ensuring the safety of exploitation. Such analysis-powered prevention of damages forms an element of the Machine Operations and Investment Protection strategy. The corresponding analysis is a necessary step in preparation of the commissioning, which finalizes the construction phase. It shall be supported by the development of the efficient and robust simulators and multi-physics/multi-system integration of models. The developed numerical model of interactions in the ITER magnetic system, based on the use of pre-computed influence matrices, facilitated immediate and complete assessment and systematic specification of EM loads on magnets in all foreseen operating regimes, their maximum values, envelopes and the most critical scenarios. The common principles of interaction in typical bilateral configurations have been generalized for asymmetry conditions, inspired by the plasma and by the hardware, including asymmetric plasma event and magnetic system fault cases. The specification of loads is supported by the technology of functional approximation of nodal and distributed data by continuous patterns/analytical interpolants. The global model of interactions together with the mesh-independent analytical format of output provides the source of self-consistent and transferable data on the spatial distribution of the system of forces for assessments of structural performance of the components, assemblies and supporting structures. The numerical model used is fully parametrized, which makes it very suitable for multi-variant and sensitivity studies (positioning, off-normal events, asymmetry, etc). The obtained results and matrices form a basis for a relatively simple and robust force processor as a specialized module of a global simulator for diagnostic, operational instrumentation, monitoring and control, as well as a scenario assessment tool. This paper gives an overview of the model, applied technique, assessed problems and obtained qualitative and quantitative results.

Utilization of rotor kinetic energy storage for hybrid vehicles

DOEpatents

Hsu, John S [Oak Ridge, TN

2011-05-03

A power system for a motor vehicle having an internal combustion engine, the power system comprises an electric machine (12) further comprising a first excitation source (47), a permanent magnet rotor (28) and a magnetic coupling rotor (26) spaced from the permanent magnet rotor and at least one second excitation source (43), the magnetic coupling rotor (26) also including a flywheel having an inertial mass to store kinetic energy during an initial acceleration to an operating speed; and wherein the first excitation source is electrically connected to the second excitation source for power cycling such that the flywheel rotor (26) exerts torque on the permanent magnet rotor (28) to assist braking and acceleration of the permanent magnet rotor (28) and consequently, the vehicle. An axial gap machine and a radial gap machine are disclosed and methods of the invention are also disclosed.

Game-powered machine learning

PubMed Central

Barrington, Luke; Turnbull, Douglas; Lanckriet, Gert

2012-01-01

Searching for relevant content in a massive amount of multimedia information is facilitated by accurately annotating each image, video, or song with a large number of relevant semantic keywords, or tags. We introduce game-powered machine learning, an integrated approach to annotating multimedia content that combines the effectiveness of human computation, through online games, with the scalability of machine learning. We investigate this framework for labeling music. First, a socially-oriented music annotation game called Herd It collects reliable music annotations based on the “wisdom of the crowds.” Second, these annotated examples are used to train a supervised machine learning system. Third, the machine learning system actively directs the annotation games to collect new data that will most benefit future model iterations. Once trained, the system can automatically annotate a corpus of music much larger than what could be labeled using human computation alone. Automatically annotated songs can be retrieved based on their semantic relevance to text-based queries (e.g., “funky jazz with saxophone,” “spooky electronica,” etc.). Based on the results presented in this paper, we find that actively coupling annotation games with machine learning provides a reliable and scalable approach to making searchable massive amounts of multimedia data. PMID:22460786

Game-powered machine learning.

PubMed

Barrington, Luke; Turnbull, Douglas; Lanckriet, Gert

2012-04-24

Searching for relevant content in a massive amount of multimedia information is facilitated by accurately annotating each image, video, or song with a large number of relevant semantic keywords, or tags. We introduce game-powered machine learning, an integrated approach to annotating multimedia content that combines the effectiveness of human computation, through online games, with the scalability of machine learning. We investigate this framework for labeling music. First, a socially-oriented music annotation game called Herd It collects reliable music annotations based on the "wisdom of the crowds." Second, these annotated examples are used to train a supervised machine learning system. Third, the machine learning system actively directs the annotation games to collect new data that will most benefit future model iterations. Once trained, the system can automatically annotate a corpus of music much larger than what could be labeled using human computation alone. Automatically annotated songs can be retrieved based on their semantic relevance to text-based queries (e.g., "funky jazz with saxophone," "spooky electronica," etc.). Based on the results presented in this paper, we find that actively coupling annotation games with machine learning provides a reliable and scalable approach to making searchable massive amounts of multimedia data.

Biosleeve Human-Machine Interface

NASA Technical Reports Server (NTRS)

Assad, Christopher (Inventor)

2016-01-01

Systems and methods for sensing human muscle action and gestures in order to control machines or robotic devices are disclosed. One exemplary system employs a tight fitting sleeve worn on a user arm and including a plurality of electromyography (EMG) sensors and at least one inertial measurement unit (IMU). Power, signal processing, and communications electronics may be built into the sleeve and control data may be transmitted wirelessly to the controlled machine or robotic device.

Vacation model for Markov machine repair problem with two heterogeneous unreliable servers and threshold recovery

NASA Astrophysics Data System (ADS)

Jain, Madhu; Meena, Rakesh Kumar

2018-03-01

Markov model of multi-component machining system comprising two unreliable heterogeneous servers and mixed type of standby support has been studied. The repair job of broken down machines is done on the basis of bi-level threshold policy for the activation of the servers. The server returns back to render repair job when the pre-specified workload of failed machines is build up. The first (second) repairman turns on only when the work load of N1 (N2) failed machines is accumulated in the system. The both servers may go for vacation in case when all the machines are in good condition and there are no pending repair jobs for the repairmen. Runge-Kutta method is implemented to solve the set of governing equations used to formulate the Markov model. Various system metrics including the mean queue length, machine availability, throughput, etc., are derived to determine the performance of the machining system. To provide the computational tractability of the present investigation, a numerical illustration is provided. A cost function is also constructed to determine the optimal repair rate of the server by minimizing the expected cost incurred on the system. The hybrid soft computing method is considered to develop the adaptive neuro-fuzzy inference system (ANFIS). The validation of the numerical results obtained by Runge-Kutta approach is also facilitated by computational results generated by ANFIS.

Method and apparatus for lead-unity-lag electric power generation system

NASA Technical Reports Server (NTRS)

Ganev, Evgeni (Inventor); Warr, William (Inventor); Salam, Mohamed (Arif) (Inventor)

2013-01-01

A method employing a lead-unity-lag adjustment on a power generation system is disclosed. The method may include calculating a unity power factor point and adjusting system parameters to shift a power factor angle to substantially match an operating power angle creating a new unity power factor point. The method may then define operation parameters for a high reactance permanent magnet machine based on the adjusted power level.

Object recognition through a multi-mode fiber

NASA Astrophysics Data System (ADS)

Takagi, Ryosuke; Horisaki, Ryoichi; Tanida, Jun

2017-04-01

We present a method of recognizing an object through a multi-mode fiber. A number of speckle patterns transmitted through a multi-mode fiber are provided to a classifier based on machine learning. We experimentally demonstrated binary classification of face and non-face targets based on the method. The measurement process of the experimental setup was random and nonlinear because a multi-mode fiber is a typical strongly scattering medium and any reference light was not used in our setup. Comparisons between three supervised learning methods, support vector machine, adaptive boosting, and neural network, are also provided. All of those learning methods achieved high accuracy rates at about 90% for the classification. The approach presented here can realize a compact and smart optical sensor. It is practically useful for medical applications, such as endoscopy. Also our study indicated a promising utilization of artificial intelligence, which has rapidly progressed, for reducing optical and computational costs in optical sensing systems.

A Hierarchical Framework for Demand-Side Frequency Control

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

Moya, Christian; Zhang, Wei; Lian, Jianming

2014-06-02

With large-scale plans to integrate renewable generation, more resources will be needed to compensate for the uncertainty associated with intermittent generation resources. Under such conditions, performing frequency control using only supply-side resources become not only prohibitively expensive but also technically difficult. It is therefore important to explore how a sufficient proportion of the loads could assume a routine role in frequency control to maintain the stability of the system at an acceptable cost. In this paper, a novel hierarchical decentralized framework for frequency based load control is proposed. The framework involves two decision layers. The top decision layer determines themore » optimal droop gain required from the aggregated load response on each bus using a robust decentralized control approach. The second layer consists of a large number of devices, which switch probabilistically during contingencies so that the aggregated power change matches the desired droop amount according to the updated gains. The proposed framework is based on the classical nonlinear multi-machine power system model, and can deal with timevarying system operating conditions while respecting the physical constraints of individual devices. Realistic simulation results based on a 68-bus system are provided to demonstrate the effectiveness of the proposed strategy.« less

The monitoring of transient regimes on machine tools based on speed, acceleration and active electric power absorbed by motors

NASA Astrophysics Data System (ADS)

Horodinca, M.

2016-08-01

This paper intend to propose some new results related with computer aided monitoring of transient regimes on machine-tools based on the evolution of active electrical power absorbed by the electric motor used to drive the main kinematic chains and the evolution of rotational speed and acceleration of the main shaft. The active power is calculated in numerical format using the evolution of instantaneous voltage and current delivered by electrical power system to the electric motor. The rotational speed and acceleration of the main shaft are calculated based on the signal delivered by a sensor. Three real-time analogic signals are acquired with a very simple computer assisted setup which contains a voltage transformer, a current transformer, an AC generator as rotational speed sensor, a data acquisition system and a personal computer. The data processing and analysis was done using Matlab software. Some different transient regimes were investigated; several important conclusions related with the advantages of this monitoring technique were formulated. Many others features of the experimental setup are also available: to supervise the mechanical loading of machine-tools during cutting processes or for diagnosis of machine-tools condition by active electrical power signal analysis in frequency domain.

Application of Electro Chemical Machining for materials used in extreme conditions

NASA Astrophysics Data System (ADS)

Pandilov, Z.

2018-03-01

Electro-Chemical Machining (ECM) is the generic term for a variety of electrochemical processes. ECM is used to machine work pieces from metal and metal alloys irrespective of their hardness, strength or thermal properties, through the anodic dissolution, in aerospace, automotive, construction, medical equipment, micro-systems and power supply industries. The Electro Chemical Machining is extremely suitable for machining of materials used in extreme conditions. General overview of the Electro-Chemical Machining and its application for different materials used in extreme conditions is presented.

Control system of mutually coupled switched reluctance motor drive of mining machines in generator mode

NASA Astrophysics Data System (ADS)

Ivanov, A. S.; Kalanchin, I. Yu; Pugacheva, E. E.

2017-09-01

One of the first electric motors, based on the use of electromagnets, was a reluctance motor in the XIX century. Due to the complexities in the implementation of control system the development of switched reluctance electric machines was repeatedly initiated only in 1960 thanks to the development of computers and power electronic devices. The main feature of these machines is the capacity to work both in engine mode and in generator mode. Thanks to a simple and reliable design in which there is no winding of the rotor, commutator, permanent magnets, a reactive gate-inductor electric drive operating in the engine mode is actively being introduced into various areas such as car industry, production of household appliances, wind power engineering, as well as responsible production processes in the oil and mining industries. However, the existing shortcomings of switched reluctance electric machines, such as nonlinear pulsations of electromagnetic moment, the presence of three or four phase supply system and sensor of rotor position prevent wide distribution of this kind of electric machines.

Description of photovoltaic village power systems in the United States and Africa

NASA Technical Reports Server (NTRS)

Ratajczak, A. F.; Bifano, W. J.

1979-01-01

Photovoltaic power systems in remote villages in the United States and Africa are described. These projects were undertaken to demonstrate that existing photovoltaic system technology is capable of providing electrical power for basic domestic services for the millions of small, remote communities in both developed and developing countries. One system is located in the Papago Indian Village of Schuchuli in southwest Arizona (U. S.) and became operational 16 December 1978. The other system is located in Tangaye, a rural village in Upper Volta, Africa. It became operational 1 March 1979. The Schuchuli system has a 3.5 kW (peak) solar array which provides electric power for village water pumping, a refrigerator for each family, lights in the village buildings, and a community washing machine and sewing machine. The 1.8 kW (peak) Tangaye system provides power for community water pumping, flour milling and lights in the milling building. These are both stand-alone systems (i.e., no back-up power source) which are being operated and maintained by local personnel. Both systems are instrumented. Systems operations are being monitored by NASA to measure design adequacy and to refine designs for future systems.

Multi-kilowatt modularized spacecraft power processing system development

NASA Technical Reports Server (NTRS)

Andrews, R. E.; Hayden, J. H.; Hedges, R. T.; Rehmann, D. W.

1975-01-01

A review of existing information pertaining to spacecraft power processing systems and equipment was accomplished with a view towards applicability to the modularization of multi-kilowatt power processors. Power requirements for future spacecraft were determined from the NASA mission model-shuttle systems payload data study which provided the limits for modular power equipment capabilities. Three power processing systems were compared to evaluation criteria to select the system best suited for modularity. The shunt regulated direct energy transfer system was selected by this analysis for a conceptual design effort which produced equipment specifications, schematics, envelope drawings, and power module configurations.

A Wireless 32-Channel Implantable Bidirectional Brain Machine Interface

PubMed Central

Su, Yi; Routhu, Sudhamayee; Moon, Kee S.; Lee, Sung Q.; Youm, WooSub; Ozturk, Yusuf

2016-01-01

All neural information systems (NIS) rely on sensing neural activity to supply commands and control signals for computers, machines and a variety of prosthetic devices. Invasive systems achieve a high signal-to-noise ratio (SNR) by eliminating the volume conduction problems caused by tissue and bone. An implantable brain machine interface (BMI) using intracortical electrodes provides excellent detection of a broad range of frequency oscillatory activities through the placement of a sensor in direct contact with cortex. This paper introduces a compact-sized implantable wireless 32-channel bidirectional brain machine interface (BBMI) to be used with freely-moving primates. The system is designed to monitor brain sensorimotor rhythms and present current stimuli with a configurable duration, frequency and amplitude in real time to the brain based on the brain activity report. The battery is charged via a novel ultrasonic wireless power delivery module developed for efficient delivery of power into a deeply-implanted system. The system was successfully tested through bench tests and in vivo tests on a behaving primate to record the local field potential (LFP) oscillation and stimulate the target area at the same time. PMID:27669264

Analysis on the multi-dimensional spectrum of the thrust force for the linear motor feed drive system in machine tools

NASA Astrophysics Data System (ADS)

Yang, Xiaojun; Lu, Dun; Ma, Chengfang; Zhang, Jun; Zhao, Wanhua

2017-01-01

The motor thrust force has lots of harmonic components due to the nonlinearity of drive circuit and motor itself in the linear motor feed drive system. What is more, in the motion process, these thrust force harmonics may vary with the position, velocity, acceleration and load, which affects the displacement fluctuation of the feed drive system. Therefore, in this paper, on the basis of the thrust force spectrum obtained by the Maxwell equation and the electromagnetic energy method, the multi-dimensional variation of each thrust harmonic is analyzed under different motion parameters. Then the model of the servo system is established oriented to the dynamic precision. The influence of the variation of the thrust force spectrum on the displacement fluctuation is discussed. At last the experiments are carried out to verify the theoretical analysis above. It can be found that the thrust harmonics show multi-dimensional spectrum characteristics under different motion parameters and loads, which should be considered to choose the motion parameters and optimize the servo control parameters in the high-speed and high-precision machine tools equipped with the linear motor feed drive system.

Development of German-English Machine Translation System.

ERIC Educational Resources Information Center

Lehmann, Winifred P.; Stachowitz, Rolf

This report documents efforts over a five-month period toward completion of a pilot system for machine translation of German scientific and technical literature into English. The report is divided into three areas: grammar formalism, programming, and linguistics. Work on grammar formalism concentrated mainly on increasing the power of the…

Conceptual Study of Permanent Magnet Machine Ship Propulsion Systems

DTIC Science & Technology

1977-12-01

cycloconverter subsystem is designed using advanced thyristors and can be either water or air cooled. The machine-cycloconverter, many-phase or parallel...Turnb, Phase, Poles, Air Gap ................................. 3-9 3-5 Machine Characteristics Versus Number of Poles (large machine, 40 000 hp). Poles...cylindrical permanent magnet generator forces the power conditioner to provide for both frequency change and voltage control. The complexity of this dual

Design of a Closed-Loop, Bidirectional Brain Machine Interface System With Energy Efficient Neural Feature Extraction and PID Control.

PubMed

Liu, Xilin; Zhang, Milin; Richardson, Andrew G; Lucas, Timothy H; Van der Spiegel, Jan

2017-08-01

This paper presents a bidirectional brain machine interface (BMI) microsystem designed for closed-loop neuroscience research, especially experiments in freely behaving animals. The system-on-chip (SoC) consists of 16-channel neural recording front-ends, neural feature extraction units, 16-channel programmable neural stimulator back-ends, in-channel programmable closed-loop controllers, global analog-digital converters (ADC), and peripheral circuits. The proposed neural feature extraction units includes 1) an ultra low-power neural energy extraction unit enabling a 64-step natural logarithmic domain frequency tuning, and 2) a current-mode action potential (AP) detection unit with time-amplitude window discriminator. A programmable proportional-integral-derivative (PID) controller has been integrated in each channel enabling a various of closed-loop operations. The implemented ADCs include a 10-bit voltage-mode successive approximation register (SAR) ADC for the digitization of the neural feature outputs and/or local field potential (LFP) outputs, and an 8-bit current-mode SAR ADC for the digitization of the action potential outputs. The multi-mode stimulator can be programmed to perform monopolar or bipolar, symmetrical or asymmetrical charge balanced stimulation with a maximum current of 4 mA in an arbitrary channel configuration. The chip has been fabricated in 0.18 μ m CMOS technology, occupying a silicon area of 3.7 mm 2 . The chip dissipates 56 μW/ch on average. General purpose low-power microcontroller with Bluetooth module are integrated in the system to provide wireless link and SoC configuration. Methods, circuit techniques and system topology proposed in this work can be used in a wide range of relevant neurophysiology research, especially closed-loop BMI experiments.

17. TRACTOR ENGINE POWERING SHAFT SYSTEM IN FOREGROUND, BELT CONNECTS ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

17. TRACTOR ENGINE POWERING SHAFT SYSTEM IN FOREGROUND, BELT CONNECTS WITH MAIN SHAFT LOOKING EAST. - W. A. Young & Sons Foundry & Machine Shop, On Water Street along Monongahela River, Rices Landing, Greene County, PA

Developing Ubiquitous Sensor Network Platform Using Internet of Things: Application in Precision Agriculture.

PubMed

Ferrández-Pastor, Francisco Javier; García-Chamizo, Juan Manuel; Nieto-Hidalgo, Mario; Mora-Pascual, Jerónimo; Mora-Martínez, José

2016-07-22

The application of Information Technologies into Precision Agriculture methods has clear benefits. Precision Agriculture optimises production efficiency, increases quality, minimises environmental impact and reduces the use of resources (energy, water); however, there are different barriers that have delayed its wide development. Some of these main barriers are expensive equipment, the difficulty to operate and maintain and the standard for sensor networks are still under development. Nowadays, new technological development in embedded devices (hardware and communication protocols), the evolution of Internet technologies (Internet of Things) and ubiquitous computing (Ubiquitous Sensor Networks) allow developing less expensive systems, easier to control, install and maintain, using standard protocols with low-power consumption. This work develops and test a low-cost sensor/actuator network platform, based in Internet of Things, integrating machine-to-machine and human-machine-interface protocols. Edge computing uses this multi-protocol approach to develop control processes on Precision Agriculture scenarios. A greenhouse with hydroponic crop production was developed and tested using Ubiquitous Sensor Network monitoring and edge control on Internet of Things paradigm. The experimental results showed that the Internet technologies and Smart Object Communication Patterns can be combined to encourage development of Precision Agriculture. They demonstrated added benefits (cost, energy, smart developing, acceptance by agricultural specialists) when a project is launched.

Developing Ubiquitous Sensor Network Platform Using Internet of Things: Application in Precision Agriculture

PubMed Central

Ferrández-Pastor, Francisco Javier; García-Chamizo, Juan Manuel; Nieto-Hidalgo, Mario; Mora-Pascual, Jerónimo; Mora-Martínez, José

2016-01-01

The application of Information Technologies into Precision Agriculture methods has clear benefits. Precision Agriculture optimises production efficiency, increases quality, minimises environmental impact and reduces the use of resources (energy, water); however, there are different barriers that have delayed its wide development. Some of these main barriers are expensive equipment, the difficulty to operate and maintain and the standard for sensor networks are still under development. Nowadays, new technological development in embedded devices (hardware and communication protocols), the evolution of Internet technologies (Internet of Things) and ubiquitous computing (Ubiquitous Sensor Networks) allow developing less expensive systems, easier to control, install and maintain, using standard protocols with low-power consumption. This work develops and test a low-cost sensor/actuator network platform, based in Internet of Things, integrating machine-to-machine and human-machine-interface protocols. Edge computing uses this multi-protocol approach to develop control processes on Precision Agriculture scenarios. A greenhouse with hydroponic crop production was developed and tested using Ubiquitous Sensor Network monitoring and edge control on Internet of Things paradigm. The experimental results showed that the Internet technologies and Smart Object Communication Patterns can be combined to encourage development of Precision Agriculture. They demonstrated added benefits (cost, energy, smart developing, acceptance by agricultural specialists) when a project is launched. PMID:27455265

75 FR 27966 - Airworthiness Directives; The Boeing Company Model 747-400 and 747-400D Series Airplanes

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-19

... operator experienced a multi-power system loss in-flight of 1, 2, and 3 alternating current (AC) electrical... an operator experienced a multi-power system loss in-flight of 1, 2, and 3 AC electrical power... alternating current electrical power systems located in the main equipment center (MEC). The Federal Aviation...

Reasoning about real-time systems with temporal interval logic constraints on multi-state automata

NASA Technical Reports Server (NTRS)

Gabrielian, Armen

1991-01-01

Models of real-time systems using a single paradigm often turn out to be inadequate, whether the paradigm is based on states, rules, event sequences, or logic. A model-based approach to reasoning about real-time systems is presented in which a temporal interval logic called TIL is employed to define constraints on a new type of high level automata. The combination, called hierarchical multi-state (HMS) machines, can be used to model formally a real-time system, a dynamic set of requirements, the environment, heuristic knowledge about planning-related problem solving, and the computational states of the reasoning mechanism. In this framework, mathematical techniques were developed for: (1) proving the correctness of a representation; (2) planning of concurrent tasks to achieve goals; and (3) scheduling of plans to satisfy complex temporal constraints. HMS machines allow reasoning about a real-time system from a model of how truth arises instead of merely depending of what is true in a system.

Scheduling algorithms for automatic control systems for technological processes

NASA Astrophysics Data System (ADS)

Chernigovskiy, A. S.; Tsarev, R. Yu; Kapulin, D. V.

2017-01-01

Wide use of automatic process control systems and the usage of high-performance systems containing a number of computers (processors) give opportunities for creation of high-quality and fast production that increases competitiveness of an enterprise. Exact and fast calculations, control computation, and processing of the big data arrays - all of this requires the high level of productivity and, at the same time, minimum time of data handling and result receiving. In order to reach the best time, it is necessary not only to use computing resources optimally, but also to design and develop the software so that time gain will be maximal. For this purpose task (jobs or operations), scheduling techniques for the multi-machine/multiprocessor systems are applied. Some of basic task scheduling methods for the multi-machine process control systems are considered in this paper, their advantages and disadvantages come to light, and also some usage considerations, in case of the software for automatic process control systems developing, are made.

Westinghouse programs in pulsed homopolar power supplies

NASA Technical Reports Server (NTRS)

Litz, D. C.; Mullan, E.

1984-01-01

This document details Westinghouse's ongoing study of homopolar machines since 1929 with the major effort occurring in the early 1970's to the present. The effort has enabled Westinghouse to develop expertise in the technology required for the design, fabrication and testing of such machines. This includes electrical design, electromagnetic analysis, current collection, mechanical design, advanced cooling, stress analysis, transient rotor performance, bearing analysis and seal technology. Westinghouse is using this capability to explore the use of homopolar machines as pulsed power supplies for future systems in both military and commercial applications.

Coreference analysis in clinical notes: a multi-pass sieve with alternate anaphora resolution modules

PubMed Central

Li, Dingcheng; Sohn, Sunghwan; Wu, Stephen Tze-Inn; Wagholikar, Kavishwar; Torii, Manabu; Liu, Hongfang

2012-01-01

Objective This paper describes the coreference resolution system submitted by Mayo Clinic for the 2011 i2b2/VA/Cincinnati shared task Track 1C. The goal of the task was to construct a system that links the markables corresponding to the same entity. Materials and methods The task organizers provided progress notes and discharge summaries that were annotated with the markables of treatment, problem, test, person, and pronoun. We used a multi-pass sieve algorithm that applies deterministic rules in the order of preciseness and simultaneously gathers information about the entities in the documents. Our system, MedCoref, also uses a state-of-the-art machine learning framework as an alternative to the final, rule-based pronoun resolution sieve. Results The best system that uses a multi-pass sieve has an overall score of 0.836 (average of B3, MUC, Blanc, and CEAF F score) for the training set and 0.843 for the test set. Discussion A supervised machine learning system that typically uses a single function to find coreferents cannot accommodate irregularities encountered in data especially given the insufficient number of examples. On the other hand, a completely deterministic system could lead to a decrease in recall (sensitivity) when the rules are not exhaustive. The sieve-based framework allows one to combine reliable machine learning components with rules designed by experts. Conclusion Using relatively simple rules, part-of-speech information, and semantic type properties, an effective coreference resolution system could be designed. The source code of the system described is available at https://sourceforge.net/projects/ohnlp/files/MedCoref. PMID:22707745

An Adaptive Genetic Association Test Using Double Kernel Machines.

PubMed

Zhan, Xiang; Epstein, Michael P; Ghosh, Debashis

2015-10-01

Recently, gene set-based approaches have become very popular in gene expression profiling studies for assessing how genetic variants are related to disease outcomes. Since most genes are not differentially expressed, existing pathway tests considering all genes within a pathway suffer from considerable noise and power loss. Moreover, for a differentially expressed pathway, it is of interest to select important genes that drive the effect of the pathway. In this article, we propose an adaptive association test using double kernel machines (DKM), which can both select important genes within the pathway as well as test for the overall genetic pathway effect. This DKM procedure first uses the garrote kernel machines (GKM) test for the purposes of subset selection and then the least squares kernel machine (LSKM) test for testing the effect of the subset of genes. An appealing feature of the kernel machine framework is that it can provide a flexible and unified method for multi-dimensional modeling of the genetic pathway effect allowing for both parametric and nonparametric components. This DKM approach is illustrated with application to simulated data as well as to data from a neuroimaging genetics study.

A high performance parallel algorithm for 1-D FFT

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

Agarwal, R.C.; Gustavson, F.G.; Zubair, M.

1994-12-31

In this paper the authors propose a parallel high performance FFT algorithm based on a multi-dimensional formulation. They use this to solve a commonly encountered FFT based kernel on a distributed memory parallel machine, the IBM scalable parallel system, SP1. The kernel requires a forward FFT computation of an input sequence, multiplication of the transformed data by a coefficient array, and finally an inverse FFT computation of the resultant data. They show that the multi-dimensional formulation helps in reducing the communication costs and also improves the single node performance by effectively utilizing the memory system of the node. They implementedmore » this kernel on the IBM SP1 and observed a performance of 1.25 GFLOPS on a 64-node machine.« less

A non-LTE analysis of high energy density Kr plasmas on Z and NIF

NASA Astrophysics Data System (ADS)

Dasgupta, A.; Clark, R. W.; Ouart, N.; Giuliani, J.; Velikovich, A.; Ampleford, D. J.; Hansen, S. B.; Jennings, C.; Harvey-Thompson, A. J.; Jones, B.; Flanagan, T. M.; Bell, K. S.; Apruzese, J. P.; Fournier, K. B.; Scott, H. A.; May, M. J.; Barrios, M. A.; Colvin, J. D.; Kemp, G. E.

2016-10-01

Multi-keV X-ray radiation sources have a wide range of applications, from biomedical studies and research on thermonuclear fusion to materials science and astrophysics. The refurbished Z pulsed power machine at the Sandia National Laboratories produces intense multi-keV X-rays from argon Z-pinches, but for a krypton Z-pinch, the yield decreases much faster with atomic number ZA than similar sources on the National Ignition Facility (NIF) laser at the Lawrence Livermore National Laboratory. To investigate whether fundamental energy deposition differences between pulsed power and lasers could account for the yield differences, we consider the Kr plasma on the two machines. The analysis assumes the plasma not in local thermodynamic equilibrium, with a detailed coupling between the hydrodynamics, the radiation field, and the ionization physics. While for the plasma parameters of interest the details of krypton's M-shell are not crucial, both the L-shell and the K-shell must be modeled in reasonable detail, including the state-specific dielectronic recombination processes that significantly affect Kr's ionization balance and the resulting X-ray spectrum. We present a detailed description of the atomic model, provide synthetic K- and L-shell spectra, and compare these with the available experimental data from the Z-machine and from NIF to show that the K-shell yield behavior versus ZA is indeed related to the energy input characteristics. This work aims at understanding the probable causes that might explain the differences in the X-ray conversion efficiencies of several radiation sources on Z and NIF.

Hamiltonian methods of modeling and control of AC microgrids with spinning machines and inverters

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

Matthews, Ronald C.; Weaver, Wayne W.; Robinett, Rush D.

This study presents a novel approach to the modeling and control of AC microgrids that contain spinning machines, power electronic inverters and energy storage devices. The inverters in the system can adjust their frequencies and power angles very quickly, so the modeling focuses on establishing a common reference frequency and angle in the microgrid based on the spinning machines. From this dynamic model, nonlinear Hamiltonian surface shaping and power flow control method is applied and shown to stabilize. From this approach the energy flow in the system is used to show the energy storage device requirements and limitations for themore » system. This paper first describes the model for a single bus AC microgrid with a Hamiltonian control, then extends this model and control to a more general class of multiple bus AC microgrids. Finally, simulation results demonstrate the efficacy of the approach in stabilizing and optimization of the microgrid.« less

Hamiltonian methods of modeling and control of AC microgrids with spinning machines and inverters

DOE PAGES

Matthews, Ronald C.; Weaver, Wayne W.; Robinett, Rush D.; ...

2017-12-22

This study presents a novel approach to the modeling and control of AC microgrids that contain spinning machines, power electronic inverters and energy storage devices. The inverters in the system can adjust their frequencies and power angles very quickly, so the modeling focuses on establishing a common reference frequency and angle in the microgrid based on the spinning machines. From this dynamic model, nonlinear Hamiltonian surface shaping and power flow control method is applied and shown to stabilize. From this approach the energy flow in the system is used to show the energy storage device requirements and limitations for themore » system. This paper first describes the model for a single bus AC microgrid with a Hamiltonian control, then extends this model and control to a more general class of multiple bus AC microgrids. Finally, simulation results demonstrate the efficacy of the approach in stabilizing and optimization of the microgrid.« less

Hardware Acceleration of Adaptive Neural Algorithms.

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

James, Conrad D.

As tradit ional numerical computing has faced challenges, researchers have turned towards alternative computing approaches to reduce power - per - computation metrics and improve algorithm performance. Here, we describe an approach towards non - conventional computing that strengthens the connection between machine learning and neuroscience concepts. The Hardware Acceleration of Adaptive Neural Algorithms (HAANA) project ha s develop ed neural machine learning algorithms and hardware for applications in image processing and cybersecurity. While machine learning methods are effective at extracting relevant features from many types of data, the effectiveness of these algorithms degrades when subjected to real - worldmore » conditions. Our team has generated novel neural - inspired approa ches to improve the resiliency and adaptability of machine learning algorithms. In addition, we have also designed and fabricated hardware architectures and microelectronic devices specifically tuned towards the training and inference operations of neural - inspired algorithms. Finally, our multi - scale simulation framework allows us to assess the impact of microelectronic device properties on algorithm performance.« less

On the role of exchange of power and information signals in control and stability of the human-robot interaction

NASA Technical Reports Server (NTRS)

Kazerooni, H.

1991-01-01

A human's ability to perform physical tasks is limited, not only by his intelligence, but by his physical strength. If, in an appropriate environment, a machine's mechanical power is closely integrated with a human arm's mechanical power under the control of the human intellect, the resulting system will be superior to a loosely integrated combination of a human and a fully automated robot. Therefore, we must develop a fundamental solution to the problem of 'extending' human mechanical power. The work presented here defines 'extenders' as a class of robot manipulators worn by humans to increase human mechanical strength, while the wearer's intellect remains the central control system for manipulating the extender. The human, in physical contact with the extender, exchanges power and information signals with the extender. The aim is to determine the fundamental building blocks of an intelligent controller, a controller which allows interaction between humans and a broad class of computer-controlled machines via simultaneous exchange of both power and information signals. The prevalent trend in automation has been to physically separate the human from the machine so the human must always send information signals via an intermediary device (e.g., joystick, pushbutton, light switch). Extenders, however are perfect examples of self-powered machines that are built and controlled for the optimal exchange of power and information signals with humans. The human wearing the extender is in physical contact with the machine, so power transfer is unavoidable and information signals from the human help to control the machine. Commands are transferred to the extender via the contact forces and the EMG signals between the wearer and the extender. The extender augments human motor ability without accepting any explicit commands: it accepts the EMG signals and the contact force between the person's arm and the extender, and the extender 'translates' them into a desired position. In this unique configuration, mechanical power transfer between the human and the extender occurs because the human is pushing against the extender. The extender transfers to the human's hand, in feedback fashion, a scaled-down version of the actual external load which the extender is manipulating. This natural feedback force on the human's hand allows him to 'feel' a modified version of the external forces on the extender. The information signals from the human (e.g., EMG signals) to the computer reflect human cognitive ability, and the power transfer between the human and the machine (e.g., physical interaction) reflects human physical ability. Thus the information transfer to the machine augments cognitive ability, and the power transfer augments motor ability. These two actions are coupled through the human cognitive/motor dynamic behavior. The goal is to derive the control rules for a class of computer-controlled machines that augment human physical and cognitive abilities in certain manipulative tasks.

Electric Drive Dynamic Thermal System Model for Advanced Vehicle Propulsion Technologies: Cooperative Research and Development Final Report, CRADA Number CRD-09-360

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

Bennion, K.

Electric drive systems, which include electric machines and power electronics, are a key enabling technology for advanced vehicle propulsion systems that reduce the dependence of the U.S. transportation sector on petroleum. However, to penetrate the market, these electric drive technologies must enable vehicle solutions that are economically viable. The push to make critical electric drivesystems smaller, lighter, and more cost-effective brings respective challenges associated with heat removal and system efficiency. In addition, the wide application of electric drive systems to alternative propulsion technologies ranging from integrated starter generators, to hybrid electric vehicles, to full electric vehicles presents challenges in termsmore » of sizing critical components andthermal management systems over a range of in-use operating conditions. This effort focused on developing a modular modeling methodology to enable multi-scale and multi-physics simulation capabilities leading to generic electric drive system models applicable to alternative vehicle propulsion configurations. The primary benefit for the National Renewable Energy Laboratory (NREL) is the abilityto define operating losses with the respective impact on component sizing, temperature, and thermal management at the component, subsystem, and system level. However, the flexible nature of the model also allows other uses related to evaluating the impacts of alternative component designs or control schemes depending on the interests of other parties.« less

Applications of Multi-Agent Technology to Power Systems

NASA Astrophysics Data System (ADS)

Nagata, Takeshi

Currently, agents are focus of intense on many sub-fields of computer science and artificial intelligence. Agents are being used in an increasingly wide variety of applications. Many important computing applications such as planning, process control, communication networks and concurrent systems will benefit from using multi-agent system approach. A multi-agent system is a structure given by an environment together with a set of artificial agents capable to act on this environment. Multi-agent models are oriented towards interactions, collaborative phenomena, and autonomy. This article presents the applications of multi-agent technology to the power systems.

Solar power generation system for reducing leakage current

NASA Astrophysics Data System (ADS)

Wu, Jinn-Chang; Jou, Hurng-Liahng; Hung, Chih-Yi

2018-04-01

This paper proposes a transformer-less multi-level solar power generation system. This solar power generation system is composed of a solar cell array, a boost power converter, an isolation switch set and a full-bridge inverter. A unipolar pulse-width modulation (PWM) strategy is used in the full-bridge inverter to attenuate the output ripple current. Circuit isolation is accomplished by integrating the isolation switch set between the solar cell array and the utility, to suppress the leakage current. The isolation switch set also determines the DC bus voltage for the full-bridge inverter connecting to the solar cell array or the output of the boost power converter. Accordingly, the proposed transformer-less multi-level solar power generation system generates a five-level voltage, and the partial power of the solar cell array is also converted to AC power using only the full-bridge inverter, so the power efficiency is increased. A prototype is developed to validate the performance of the proposed transformer-less multi-level solar power generation system.

Performance Optimization Control of ECH using Fuzzy Inference Application

NASA Astrophysics Data System (ADS)

Dubey, Abhay Kumar

Electro-chemical honing (ECH) is a hybrid electrolytic precision micro-finishing technology that, by combining physico-chemical actions of electro-chemical machining and conventional honing processes, provides the controlled functional surfaces-generation and fast material removal capabilities in a single operation. Process multi-performance optimization has become vital for utilizing full potential of manufacturing processes to meet the challenging requirements being placed on the surface quality, size, tolerances and production rate of engineering components in this globally competitive scenario. This paper presents an strategy that integrates the Taguchi matrix experimental design, analysis of variances and fuzzy inference system (FIS) to formulate a robust practical multi-performance optimization methodology for complex manufacturing processes like ECH, which involve several control variables. Two methodologies one using a genetic algorithm tuning of FIS (GA-tuned FIS) and another using an adaptive network based fuzzy inference system (ANFIS) have been evaluated for a multi-performance optimization case study of ECH. The actual experimental results confirm their potential for a wide range of machining conditions employed in ECH.

Automated inspection and precision grinding of spiral bevel gears

NASA Technical Reports Server (NTRS)

Frint, Harold

1987-01-01

The results are presented of a four phase MM&T program to define, develop, and evaluate an improved inspection system for spiral bevel gears. The improved method utilizes a multi-axis coordinate measuring machine which maps the working flank of the tooth and compares it to nominal reference values stored in the machine's computer. A unique feature of the system is that corrective grinding machine settings can be automatically calculated and printed out when necessary to correct an errant tooth profile. This new method eliminates most of the subjective decision making involved in the present method, which compares contact patterns obtained when the gear set is run under light load in a rolling test machine. It produces a higher quality gear with significant inspection time and cost savings.

Performance Analyses of 38 kWe Turbo-Machine Unit for Space Reactor Power Systems

NASA Astrophysics Data System (ADS)

Gallo, Bruno M.; El-Genk, Mohamed S.

2008-01-01

This paper developed a design and investigated the performance of 38 kWe turbo-machine unit for space nuclear reactor power systems with Closed Brayton Cycle (CBC) energy conversion. The compressor and turbine of this unit are scaled versions of the NASA's BRU developed in the sixties and seventies. The performance results of turbo-machine unit are calculated for rotational speed up to 45 krpm, variable reactor thermal power and system pressure, and fixed turbine and compressor inlet temperatures of 1144 K and 400 K. The analyses used a detailed turbo-machine model developed at the University of New Mexico that accounts for the various energy losses in the compressor and turbine and the effect of compressibility of the He-Xe (40 mole/g) working fluid with increased flow rate. The model also accounts for the changes in the physical and transport properties of the working fluid with temperature and pressure. Results show that a unit efficiency of 24.5% is achievable at rotation speed of 45 krpm and system pressure of 0.75 MPa, assuming shaft and electrical generator efficiencies of 86.7% and 90%. The corresponding net electric power output of the unit is 38.5 kWe, the flow rate of the working fluid is 1.667 kg/s, the pressure ratio and polytropic efficiency for the compressor are 1.60 and 83.1%, and 1.51 and 88.3% for the turbine.

A Multi-Component Automated Laser-Origami System for Cyber-Manufacturing

NASA Astrophysics Data System (ADS)

Ko, Woo-Hyun; Srinivasa, Arun; Kumar, P. R.

2017-12-01

Cyber-manufacturing systems can be enhanced by an integrated network architecture that is easily configurable, reliable, and scalable. We consider a cyber-physical system for use in an origami-type laser-based custom manufacturing machine employing folding and cutting of sheet material to manufacture 3D objects. We have developed such a system for use in a laser-based autonomous custom manufacturing machine equipped with real-time sensing and control. The basic elements in the architecture are built around the laser processing machine. They include a sensing system to estimate the state of the workpiece, a control system determining control inputs for a laser system based on the estimated data and user’s job requests, a robotic arm manipulating the workpiece in the work space, and middleware, named Etherware, supporting the communication among the systems. We demonstrate automated 3D laser cutting and bending to fabricate a 3D product as an experimental result.

Nightfall: Machine Autonomy in Air-to-Air Combat

DTIC Science & Technology

2014-06-01

without permission. If it is reproduced, the Air and Space Power Journal requests a courtesy line. Report Documentation Page Form ApprovedOMB No. 0704-0188...PAGE unclassified Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 May–June 2014 Air & Space Power Journal | 49 Byrnes Nightfall Feature...systems. May–June 2014 Air & Space Power Journal | 50 Byrnes Nightfall Feature FQ-X Design and Features The form of a machine like FQ-X, whose purpose is to

Installation of the Ignitor Machine at the Caorso Site

NASA Astrophysics Data System (ADS)

Migliori, S.; Pierattini, S.; Bombarda, F.; Faelli, G.; Zucchetti, M.; Coppi, B.

2008-11-01

The actual cost of building a new experiment can be considerably contained if infrastructures are already available on its envisioned site. The facilities of the Caorso site (near Piacenza, Italy) that, at present, houses a spent nuclear power station, have been analyzed in view of their utilization for the operation of the Ignitor machine. The main feature of the site is its robust connection to the electrical national power grid that can take the disturbance caused by Ignitor discharges with the highest magnetic fields and plasma currents, avoiding the need for rotating flywheels generators. Other assets include a vast building that can be modified to house the machine core and the associated diagnostic systems. A layout of the Ignitor plant, including the tritium laboratory and other service areas, the distribution of the components of the electrical power supply system and of the He gas cooling sytem are presented. Relevant safety issues have been analyzed, based on the in depth activation analysis of the machine components carried out by means of the FISPAC code. Waste management and environment impact issues, including risk to the population assessments, have also been addressed.

Quality status display for a vibration welding process

DOEpatents

Spicer, John Patrick; Abell, Jeffrey A.; Wincek, Michael Anthony; Chakraborty, Debejyo; Bracey, Jennifer; Wang, Hui; Tavora, Peter W.; Davis, Jeffrey S.; Hutchinson, Daniel C.; Reardon, Ronald L.; Utz, Shawn

2017-03-28

A system includes a host machine and a status projector. The host machine is in electrical communication with a collection of sensors and with a welding controller that generates control signals for controlling the welding horn. The host machine is configured to execute a method to thereby process the sensory and control signals, as well as predict a quality status of a weld that is formed using the welding horn, including identifying any suspect welds. The host machine then activates the status projector to illuminate the suspect welds. This may occur directly on the welds using a laser projector, or on a surface of the work piece in proximity to the welds. The system and method may be used in the ultrasonic welding of battery tabs of a multi-cell battery pack in a particular embodiment. The welding horn and welding controller may also be part of the system.

Means and method of balancing multi-cylinder reciprocating machines

DOEpatents

Corey, John A.; Walsh, Michael M.

1985-01-01

A virtual balancing axis arrangement is described for multi-cylinder reciprocating piston machines for effectively balancing out imbalanced forces and minimizing residual imbalance moments acting on the crankshaft of such machines without requiring the use of additional parallel-arrayed balancing shafts or complex and expensive gear arrangements. The novel virtual balancing axis arrangement is capable of being designed into multi-cylinder reciprocating piston and crankshaft machines for substantially reducing vibrations induced during operation of such machines with only minimal number of additional component parts. Some of the required component parts may be available from parts already required for operation of auxiliary equipment, such as oil and water pumps used in certain types of reciprocating piston and crankshaft machine so that by appropriate location and dimensioning in accordance with the teachings of the invention, the virtual balancing axis arrangement can be built into the machine at little or no additional cost.

High slot utilization systems for electric machines

DOEpatents

Hsu, John S

2009-06-23

Two new High Slot Utilization (HSU) Systems for electric machines enable the use of form wound coils that have the highest fill factor and the best use of magnetic materials. The epoxy/resin/curing treatment ensures the mechanical strength of the assembly of teeth, core, and coils. In addition, the first HSU system allows the coil layers to be moved inside the slots for the assembly purpose. The second system uses the slided-in teeth instead of the plugged-in teeth. The power density of the electric machine that uses either system can reach its highest limit.

Fluid Power Systems Maintenance and Operation. Instructor's Guide.

ERIC Educational Resources Information Center

Paule, Bob A.

Written to complement the Fluid Power/Basic Hydraulic and Basic Pneumatics guides, this curriculum guide contains materials for a seven-unit course in fluid power systems maintenance and operation. Units, which consist of one to eight lessons, cover these topics: preventive maintenance, repair machine malfunctions, overhaul/recondition hydraulic…

Multi-method automated diagnostics of rotating machines

NASA Astrophysics Data System (ADS)

Kostyukov, A. V.; Boychenko, S. N.; Shchelkanov, A. V.; Burda, E. A.

2017-08-01

The automated machinery diagnostics and monitoring systems utilized within the petrochemical plants are an integral part of the measures taken to ensure safety and, as a consequence, the efficiency of these industrial facilities. Such systems are often limited in their functionality due to the specifics of the diagnostic techniques adopted. As the diagnostic techniques applied in each system are limited, and machinery defects can have different physical nature, it becomes necessary to combine several diagnostics and monitoring systems to control various machinery components. Such an approach is inconvenient, since it requires additional measures to bring the diagnostic results in a single view of the technical condition of production assets. In this case, we mean by a production facility a bonded complex of a process unit, a drive, a power source and lines. A failure of any of these components will cause an outage of the production asset, which is unacceptable. The purpose of the study is to test a combined use of vibration diagnostics and partial discharge techniques within the diagnostic systems of enterprises for automated control of the technical condition of rotating machinery during maintenance and at production facilities. The described solutions allow you to control the condition of mechanical and electrical components of rotating machines. It is shown that the functionality of the diagnostics systems can be expanded with minimal changes in technological chains of repair and operation of rotating machinery. Automation of such systems reduces the influence of the human factor on the quality of repair and diagnostics of the machinery.

International Symposium on Wind Energy Systems, 4th, Stockholm, Sweden, September 21-24, 1982, Proceedings. Volumes 1 & 2

NASA Astrophysics Data System (ADS)

Stephens, H. S.; Goodes, D. H.

Progress in theoretical, meteorological, and hardware development sectors of wind energy utilization is assessed for various national programs. Wind regime characterization studies in Agentina, China, Indonesia, Norway, the U.S., Canada, Sweden, Hawaii, and offshore of the U.K. are reported. Data gained from wind turbine test sites in the U.S., Denmark, Holland, Germany, and the Netherlands are outlined. Attention is focused on the economics of wind turbine production for utility, agricultural, and third party purposes, with mention made of utilizing the resource appropriately for areas of installation of the wind powered machinery. Analyses are made of diurnal wind variations compared to diurnal demands on conventinal electricity generating power stations. Performance projections are made for wind farms featuring multi-MW machines, taking into account grid inteconnection factors, electrical control, power ramps, and environmental considerations. Mention is made of aeroelastics, dynamics, and the aerodynamics of wind turbines and rotor blades. Finally, icing, noise, fatigue failure, and blade throw problem are discussed, together with wind turbine licensing procedures in Denmark. No invidivual items are abstracted in these volumes

Multi-load Groups Coordinated Load Control Strategy Considering Power Network Constraints

NASA Astrophysics Data System (ADS)

Liu, Meng; Zhao, Binchao; Wang, Jun; Zhang, Guohui; Wang, Xin

2017-05-01

Loads with energy storage property can actively participate in power balance for power systems, this paper takes air conditioner as a controllable load example, proposing a multi-load groups coordinated load control strategy considering power network constraints. Firstly, two load control modes considering recovery of load diversity are designed, blocking power oscillation of aggregated air conditioners. As the same time, air conditioner temperature setpoint recovery control strategy is presented to avoid power recovery peak. Considering inherent characteristics of two load control modes, an coordinated load control mode is designed by combining the both. Basing on this, a multi-load groups coordinated load control strategy is proposed. During the implementing of load control, power network constraints should be satisfied. An indice which can reflect the security of power system operating is defined. By minimizing its value through optimization, the change of air conditioning loads’ aggregated power on each load bus can be calculated. Simulations are conducted on an air conditioners group and New England 10-generator 39-bus system, verifying the effectiveness of the proposed multi-load groups coordinated load control strategy considering power network constraints.

Unmanned Aerial System (UAS)-based phenotyping of soybean using multi-sensor data fusion and extreme learning machine

NASA Astrophysics Data System (ADS)

Maimaitijiang, Maitiniyazi; Ghulam, Abduwasit; Sidike, Paheding; Hartling, Sean; Maimaitiyiming, Matthew; Peterson, Kyle; Shavers, Ethan; Fishman, Jack; Peterson, Jim; Kadam, Suhas; Burken, Joel; Fritschi, Felix

2017-12-01

Estimating crop biophysical and biochemical parameters with high accuracy at low-cost is imperative for high-throughput phenotyping in precision agriculture. Although fusion of data from multiple sensors is a common application in remote sensing, less is known on the contribution of low-cost RGB, multispectral and thermal sensors to rapid crop phenotyping. This is due to the fact that (1) simultaneous collection of multi-sensor data using satellites are rare and (2) multi-sensor data collected during a single flight have not been accessible until recent developments in Unmanned Aerial Systems (UASs) and UAS-friendly sensors that allow efficient information fusion. The objective of this study was to evaluate the power of high spatial resolution RGB, multispectral and thermal data fusion to estimate soybean (Glycine max) biochemical parameters including chlorophyll content and nitrogen concentration, and biophysical parameters including Leaf Area Index (LAI), above ground fresh and dry biomass. Multiple low-cost sensors integrated on UASs were used to collect RGB, multispectral, and thermal images throughout the growing season at a site established near Columbia, Missouri, USA. From these images, vegetation indices were extracted, a Crop Surface Model (CSM) was advanced, and a model to extract the vegetation fraction was developed. Then, spectral indices/features were combined to model and predict crop biophysical and biochemical parameters using Partial Least Squares Regression (PLSR), Support Vector Regression (SVR), and Extreme Learning Machine based Regression (ELR) techniques. Results showed that: (1) For biochemical variable estimation, multispectral and thermal data fusion provided the best estimate for nitrogen concentration and chlorophyll (Chl) a content (RMSE of 9.9% and 17.1%, respectively) and RGB color information based indices and multispectral data fusion exhibited the largest RMSE 22.6%; the highest accuracy for Chl a + b content estimation was obtained by fusion of information from all three sensors with an RMSE of 11.6%. (2) Among the plant biophysical variables, LAI was best predicted by RGB and thermal data fusion while multispectral and thermal data fusion was found to be best for biomass estimation. (3) For estimation of the above mentioned plant traits of soybean from multi-sensor data fusion, ELR yields promising results compared to PLSR and SVR in this study. This research indicates that fusion of low-cost multiple sensor data within a machine learning framework can provide relatively accurate estimation of plant traits and provide valuable insight for high spatial precision in agriculture and plant stress assessment.

Feasibility of Using Lasers and Infrared Heaters as UNREP Icing Countermeasures

DTIC Science & Technology

1989-12-29

water lance system out of commission, it is likely that the ship’s machine shop could fabricate the necessary parts for temporary repair. No such back...Sturbridge, MA 01566 High powered C02 laser systems and large inductrial machine tools. Coherent Laser Products (800) 527-3786 3210 Porter Drive P.O...friendly LASAG lasers are for user friendly applications The correct Laser Source for a particular in inoustrial apolications. Machining Task Mair

Evaluation Of Different Power Conditioning Options For Stirling Generators

NASA Astrophysics Data System (ADS)

Garrigos, A.; Blanes, J. M.; Carrasco, J. A.; Maset, E.; Montalban, G.; Ejea, J.; Ferreres, A.; Sanchis, E.

2011-10-01

Free-piston Stirling engines are an interesting alternative for electrical power systems, especially in deep space missions where photovoltaic systems are not feasible. This kind of power generators contains two main parts, the Stirling machine and the linear alternator that converts the mechanical energy from the piston movement to electrical energy. Since the generated power is in AC form, several aspects should be assessed to use such kind of generators in a spacecraft power system: AC/DC topologies, power factor correction, power regulation techniques, integration into the power system, etc. This paper details power generator operation and explores different power conversion approaches.

The Laser MicroJet (LMJ): a multi-solution technology for high quality micro-machining

NASA Astrophysics Data System (ADS)

Mai, Tuan Anh; Richerzhagen, Bernold; Snowdon, Paul C.; Wood, David; Maropoulos, Paul G.

2007-02-01

The field of laser micromachining is highly diverse. There are many different types of lasers available in the market. Due to their differences in irradiating wavelength, output power and pulse characteristic they can be selected for different applications depending on material and feature size [1]. The main issues by using these lasers are heat damages, contamination and low ablation rates. This report examines on the application of the Laser MicroJet(R) (LMJ), a unique combination of a laser beam with a hair-thin water jet as a universal tool for micro-machining of MEMS substrates, as well as ferrous and non-ferrous materials. The materials include gallium arsenide (GaAs) & silicon wafers, steel, tantalum and alumina ceramic. A Nd:YAG laser operating at 1064 nm (infra red) and frequency doubled 532 nm (green) were employed for the micro-machining of these materials.

Methods, systems and apparatus for adjusting modulation index to improve linearity of phase voltage commands

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

Gallegos-Lopez, Gabriel; Perisic, Milun; Kinoshita, Michael H.

2017-03-14

Embodiments of the present invention relate to methods, systems and apparatus for controlling operation of a multi-phase machine in a motor drive system. The disclosed embodiments provide a mechanism for adjusting modulation index of voltage commands to improve linearity of the voltage commands.

A novel torsional exciter for modal vibration testing of large rotating machinery

NASA Astrophysics Data System (ADS)

Sihler, Christof

2006-10-01

A novel exciter for applying a dynamic torsional force to a rotating structure is presented in this paper. It has been developed at IPP in order to perform vibration tests with shaft assemblies of large flywheel generators (synchronous machines). The electromagnetic exciter (shaker) needs no fixture to the rotating shaft because the torque is applied by means of the stator winding of an electrical machine. Therefore, the exciter can most easily be applied in cases where a three-phase electrical machine (a motor or generator) is part of the shaft assembly. The oscillating power for the shaker is generated in a separate current-controlled DC circuit with an inductor acting as a buffer storage of magnetic energy. An AC component with adjustable frequency is superimposed on the inductor current in order to generate pulsating torques acting on the rotating shaft with the desired waveform and frequency. Since this torsional exciter does not require an external power source, can easily be installed (without contact to the rotating structure) and provides dynamic torsional forces which are sufficient for multi-megawatt applications, it is best suited for on-site tests of large rotating machinery.

EV drivetrain inverter with V/HZ optimization

DOEpatents

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).

Electric converters of electromagnetic strike machine with capacitor supply

NASA Astrophysics Data System (ADS)

Usanov, K. M.; Volgin, A. V.; Kargin, V. A.; Moiseev, A. P.; Chetverikov, E. A.

2018-03-01

The application of pulse linear electromagnetic engines in small power strike machines (energy impact is 0.01...1.0 kJ), where the characteristic mode of rare beats (pulse seismic vibrator, the arch crash device bins bulk materials), is quite effective. At the same time, the technical and economic performance of such machines is largely determined by the ability of the power source to provide a large instantaneous power of the supply pulses in the winding of the linear electromagnetic motor. The use of intermediate energy storage devices in power systems of rare-shock LEME makes it possible to obtain easily large instantaneous powers, forced energy conversion, and increase the performance of the machine. A capacitor power supply of a pulsed source of seismic waves is proposed for the exploration of shallow depths. The sections of the capacitor storage (CS) are connected to the winding of the linear electromagnetic motor by thyristor dischargers, the sequence of activation of which is determined by the control device. The charge of the capacitors to the required voltage is made directly from the battery source, or through the converter from a battery source with a smaller number of batteries.

Machine vision systems using machine learning for industrial product inspection

NASA Astrophysics Data System (ADS)

Lu, Yi; Chen, Tie Q.; Chen, Jie; Zhang, Jian; Tisler, Anthony

2002-02-01

Machine vision inspection requires efficient processing time and accurate results. In this paper, we present a machine vision inspection architecture, SMV (Smart Machine Vision). SMV decomposes a machine vision inspection problem into two stages, Learning Inspection Features (LIF), and On-Line Inspection (OLI). The LIF is designed to learn visual inspection features from design data and/or from inspection products. During the OLI stage, the inspection system uses the knowledge learnt by the LIF component to inspect the visual features of products. In this paper we will present two machine vision inspection systems developed under the SMV architecture for two different types of products, Printed Circuit Board (PCB) and Vacuum Florescent Displaying (VFD) boards. In the VFD board inspection system, the LIF component learns inspection features from a VFD board and its displaying patterns. In the PCB board inspection system, the LIF learns the inspection features from the CAD file of a PCB board. In both systems, the LIF component also incorporates interactive learning to make the inspection system more powerful and efficient. The VFD system has been deployed successfully in three different manufacturing companies and the PCB inspection system is the process of being deployed in a manufacturing plant.

Real-Time Smart Grids Control for Preventing Cascading Failures and Blackout using Neural Networks: Experimental Approach for N-1-1 Contingency

NASA Astrophysics Data System (ADS)

Zarrabian, Sina; Belkacemi, Rabie; Babalola, Adeniyi A.

2016-12-01

In this paper, a novel intelligent control is proposed based on Artificial Neural Networks (ANN) to mitigate cascading failure (CF) and prevent blackout in smart grid systems after N-1-1 contingency condition in real-time. The fundamental contribution of this research is to deploy the machine learning concept for preventing blackout at early stages of its occurrence and to make smart grids more resilient, reliable, and robust. The proposed method provides the best action selection strategy for adaptive adjustment of generators' output power through frequency control. This method is able to relieve congestion of transmission lines and prevent consecutive transmission line outage after N-1-1 contingency condition. The proposed ANN-based control approach is tested on an experimental 100 kW test system developed by the authors to test intelligent systems. Additionally, the proposed approach is validated on the large-scale IEEE 118-bus power system by simulation studies. Experimental results show that the ANN approach is very promising and provides accurate and robust control by preventing blackout. The technique is compared to a heuristic multi-agent system (MAS) approach based on communication interchanges. The ANN approach showed more accurate and robust response than the MAS algorithm.

CONFOCAL MICROSCOPY SYSTEM PERFORMANCE: LASER POWER MEASUREMENTS

EPA Science Inventory

Laser power abstract
The reliability of the confocal laser-scanning microscope (CLSM) to obtain intensity measurements and quantify fluorescence data is dependent on using a correctly aligned machine that contains a stable laser power. The laser power test appears to be one ...

Feasibility study for future implantable neural-silicon interface devices.

PubMed

Al-Armaghany, Allann; Yu, Bo; Mak, Terrence; Tong, Kin-Fai; Sun, Yihe

2011-01-01

The emerging neural-silicon interface devices bridge nerve systems with artificial systems and play a key role in neuro-prostheses and neuro-rehabilitation applications. Integrating neural signal collection, processing and transmission on a single device will make clinical applications more practical and feasible. This paper focuses on the wireless antenna part and real-time neural signal analysis part of implantable brain-machine interface (BMI) devices. We propose to use millimeter-wave for wireless connections between different areas of a brain. Various antenna, including microstrip patch, monopole antenna and substrate integrated waveguide antenna are considered for the intra-cortical proximity communication. A Hebbian eigenfilter based method is proposed for multi-channel neuronal spike sorting. Folding and parallel design techniques are employed to explore various structures and make a trade-off between area and power consumption. Field programmable logic arrays (FPGAs) are used to evaluate various structures.

A Multi-scale Cognitive Approach to Intrusion Detection and Response

DTIC Science & Technology

2015-12-28

the behavior of the traffic on the network, either by using mathematical formulas or by replaying packet streams. As a result, simulators depend...large scale. Summary of the most important results We obtained a powerful machine, which has 768 cores and 1.25 TB memory . RBG has been...time. Each client is configured with 1GB memory , 10 GB disk space, and one 100M Ethernet interface. The server nodes include web servers

An efficient abnormal cervical cell detection system based on multi-instance extreme learning machine

NASA Astrophysics Data System (ADS)

Zhao, Lili; Yin, Jianping; Yuan, Lihuan; Liu, Qiang; Li, Kuan; Qiu, Minghui

2017-07-01

Automatic detection of abnormal cells from cervical smear images is extremely demanded in annual diagnosis of women's cervical cancer. For this medical cell recognition problem, there are three different feature sections, namely cytology morphology, nuclear chromatin pathology and region intensity. The challenges of this problem come from feature combination s and classification accurately and efficiently. Thus, we propose an efficient abnormal cervical cell detection system based on multi-instance extreme learning machine (MI-ELM) to deal with above two questions in one unified framework. MI-ELM is one of the most promising supervised learning classifiers which can deal with several feature sections and realistic classification problems analytically. Experiment results over Herlev dataset demonstrate that the proposed method outperforms three traditional methods for two-class classification in terms of well accuracy and less time.

An Operating Environment for the Jellybean Machine

DTIC Science & Technology

1988-05-01

MODEL 48 5.4.4 Restarting a Context The operating system provides one primitive message (RESTART-CONTEXT) and two system calls (XFERID and XFER.ADDR) to...efficient, powerful services is reqired to support this "stem. To provide this supportive operating environment, I developed an operating system kernel that...serves many of the initial needs of our machine. This Jellybean Operating System Software provides an object- based storage model, where typed

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.

State Machine Modeling of the Space Launch System Solid Rocket Boosters

NASA Technical Reports Server (NTRS)

Harris, Joshua A.; Patterson-Hine, Ann

2013-01-01

The Space Launch System is a Shuttle-derived heavy-lift vehicle currently in development to serve as NASA's premiere launch vehicle for space exploration. The Space Launch System is a multistage rocket with two Solid Rocket Boosters and multiple payloads, including the Multi-Purpose Crew Vehicle. Planned Space Launch System destinations include near-Earth asteroids, the Moon, Mars, and Lagrange points. The Space Launch System is a complex system with many subsystems, requiring considerable systems engineering and integration. To this end, state machine analysis offers a method to support engineering and operational e orts, identify and avert undesirable or potentially hazardous system states, and evaluate system requirements. Finite State Machines model a system as a finite number of states, with transitions between states controlled by state-based and event-based logic. State machines are a useful tool for understanding complex system behaviors and evaluating "what-if" scenarios. This work contributes to a state machine model of the Space Launch System developed at NASA Ames Research Center. The Space Launch System Solid Rocket Booster avionics and ignition subsystems are modeled using MATLAB/Stateflow software. This model is integrated into a larger model of Space Launch System avionics used for verification and validation of Space Launch System operating procedures and design requirements. This includes testing both nominal and o -nominal system states and command sequences.

A Low Power, Parallel Wearable Multi-Sensor System for Human Activity Evaluation.

PubMed

Li, Yuecheng; Jia, Wenyan; Yu, Tianjian; Luan, Bo; Mao, Zhi-Hong; Zhang, Hong; Sun, Mingui

2015-04-01

In this paper, the design of a low power heterogeneous wearable multi-sensor system, built with Zynq System-on-Chip (SoC), for human activity evaluation is presented. The powerful data processing capability and flexibility of this SoC represent significant improvements over our previous ARM based system designs. The new system captures and compresses multiple color images and sensor data simultaneously. Several strategies are adopted to minimize power consumption. Our wearable system provides a new tool for the evaluation of human activity, including diet, physical activity and lifestyle.

Study on the adjustment capability of the excitation system located inside superconducting machine electromagnetic shield

NASA Astrophysics Data System (ADS)

Xia, D.; Xia, Z.

2017-12-01

The ability for the excitation system to adjust quickly plays a very important role in maintaining the normal operation of superconducting machines and power systems. However, the eddy currents in the electromagnetic shield of superconducting machines hinder the exciting magnetic field change and weaken the adjustment capability of the excitation system. To analyze this problem, a finite element calculation model for the transient electromagnetic field with moving parts is established. The effects of three different electromagnetic shields on the exciting magnetic field are analyzed using finite element method. The results show that the electromagnetic shield hinders the field changes significantly, the better its conductivity, the greater the effect on the superconducting machine excitation.

Electro-mechanical energy conversion system having a permanent magnet machine with stator, resonant transfer link and energy converter controls

DOEpatents

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.

Adaptive Multi-scale Prognostics and Health Management for Smart Manufacturing Systems

PubMed Central

Choo, Benjamin Y.; Adams, Stephen C.; Weiss, Brian A.; Marvel, Jeremy A.; Beling, Peter A.

2017-01-01

The Adaptive Multi-scale Prognostics and Health Management (AM-PHM) is a methodology designed to enable PHM in smart manufacturing systems. In application, PHM information is not yet fully utilized in higher-level decision-making in manufacturing systems. AM-PHM leverages and integrates lower-level PHM information such as from a machine or component with hierarchical relationships across the component, machine, work cell, and assembly line levels in a manufacturing system. The AM-PHM methodology enables the creation of actionable prognostic and diagnostic intelligence up and down the manufacturing process hierarchy. Decisions are then made with the knowledge of the current and projected health state of the system at decision points along the nodes of the hierarchical structure. To overcome the issue of exponential explosion of complexity associated with describing a large manufacturing system, the AM-PHM methodology takes a hierarchical Markov Decision Process (MDP) approach into describing the system and solving for an optimized policy. A description of the AM-PHM methodology is followed by a simulated industry-inspired example to demonstrate the effectiveness of AM-PHM. PMID:28736651

Analysis of Generator Oscillation Characteristics Based on Multiple Synchronized Phasor Measurements

NASA Astrophysics Data System (ADS)

Hashiguchi, Takuhei; Yoshimoto, Masamichi; Mitani, Yasunori; Saeki, Osamu; Tsuji, Kiichiro

In recent years, there has been considerable interest in the on-line measurement, such as observation of power system dynamics and evaluation of machine parameters. On-line methods are particularly attractive since the machine’s service need not be interrupted and parameter estimation is performed by processing measurements obtained during the normal operation of the machine. Authors placed PMU (Phasor Measurement Unit) connected to 100V outlets in some Universities in the 60Hz power system and examine oscillation characteristics in power system. PMU is synchronized based on the global positioning system (GPS) and measured data are transmitted via Internet. This paper describes an application of PMU for generator oscillation analysis. The purpose of this paper is to show methods for processing phase difference and to estimate damping coeffcient and natural angular frequency from phase difference at steady state.

Systems Performance Laboratory | Energy Systems Integration Facility | NREL

Science.gov Websites

array access Small Commercial Power Hardware in the Loop The small commercial power-hardware-in-the-loop (PHIL) test bay is dedicated to small-scale power hardware-in-the-loop studies of inverters and other , natural gas supply Multi-Inverter Power Hardware in the Loop The multi-inverter test bay is dedicated to

Low Wind Speed Turbine Project Phase II: The Application of Medium-Voltage Electrical Apparatus to the Class of Variable Speed Multi-Megawatt Low Wind Speed Turbines; 15 June 2004--30 April 2005

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

Erdman, W.; Behnke, M.

2005-11-01

Kilowatt ratings of modern wind turbines have progressed rapidly from 50 kW to 1,800 kW over the past 25 years, with 3.0- to 7.5-MW turbines expected in the next 5 years. The premise of this study is simple: The rapid growth of wind turbine power ratings and the corresponding growth in turbine electrical generation systems and associated controls are quickly making low-voltage (LV) electrical design approaches cost-ineffective. This report provides design detail and compares the cost of energy (COE) between commercial LV-class wind power machines and emerging medium-voltage (MV)-class multi-megawatt wind technology. The key finding is that a 2.5% reductionmore » in the COE can be achieved by moving from LV to MV systems. This is a conservative estimate, with a 3% to 3.5% reduction believed to be attainable once purchase orders to support a 250-turbine/year production level are placed. This evaluation considers capital costs as well as installation, maintenance, and training requirements for wind turbine maintenance personnel. Subsystems investigated include the generator, pendant cables, variable-speed converter, and padmount transformer with switchgear. Both current-source and voltage-source converter/inverter MV topologies are compared against their low-voltage, voltage-source counterparts at the 3.0-, 5.0-, and 7.5-MW levels.« less

MultiPhyl: a high-throughput phylogenomics webserver using distributed computing

PubMed Central

Keane, Thomas M.; Naughton, Thomas J.; McInerney, James O.

2007-01-01

With the number of fully sequenced genomes increasing steadily, there is greater interest in performing large-scale phylogenomic analyses from large numbers of individual gene families. Maximum likelihood (ML) has been shown repeatedly to be one of the most accurate methods for phylogenetic construction. Recently, there have been a number of algorithmic improvements in maximum-likelihood-based tree search methods. However, it can still take a long time to analyse the evolutionary history of many gene families using a single computer. Distributed computing refers to a method of combining the computing power of multiple computers in order to perform some larger overall calculation. In this article, we present the first high-throughput implementation of a distributed phylogenetics platform, MultiPhyl, capable of using the idle computational resources of many heterogeneous non-dedicated machines to form a phylogenetics supercomputer. MultiPhyl allows a user to upload hundreds or thousands of amino acid or nucleotide alignments simultaneously and perform computationally intensive tasks such as model selection, tree searching and bootstrapping of each of the alignments using many desktop machines. The program implements a set of 88 amino acid models and 56 nucleotide maximum likelihood models and a variety of statistical methods for choosing between alternative models. A MultiPhyl webserver is available for public use at: http://www.cs.nuim.ie/distributed/multiphyl.php. PMID:17553837

An element search ant colony technique for solving virtual machine placement problem

NASA Astrophysics Data System (ADS)

Srija, J.; Rani John, Rose; Kanaga, Grace Mary, Dr.

2017-09-01

The data centres in the cloud environment play a key role in providing infrastructure for ubiquitous computing, pervasive computing, mobile computing etc. This computing technique tries to utilize the available resources in order to provide services. Hence maintaining the resource utilization without wastage of power consumption has become a challenging task for the researchers. In this paper we propose the direct guidance ant colony system for effective mapping of virtual machines to the physical machine with maximal resource utilization and minimal power consumption. The proposed algorithm has been compared with the existing ant colony approach which is involved in solving virtual machine placement problem and thus the proposed algorithm proves to provide better result than the existing technique.

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-01-07

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

Induction generators for Wind Energy Conversion Systems. Part I: review of induction generator with squirrel cage rotor. Part II: the Double Output Induction Generator (DOIG). Progress report, July-December 1975

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

Hacker tracking Security system for HMI

NASA Astrophysics Data System (ADS)

Chauhan, Rajeev Kumar

2011-12-01

Conventional Supervisory control and data Acquisition (SCADA) systems use PC, notebook, thin client, and PDA as a Client. Nowadays the Process Industries are following multi shift system that's why multi- client of different category have to work at a single human Machine Interface (HMI). They may hack the HMI Display and change setting of the other client. This paper introduces a Hacker tracking security (HTS) System for HMI. This is developed by using the conventional and Biometric authentication. HTS system is developed by using Numeric passwords, Smart card, biometric, blood flow and Finger temperature. This work is also able to identify the hackers.

A multi-machine scaling of halo current rotation

NASA Astrophysics Data System (ADS)

Myers, C. E.; Eidietis, N. W.; Gerasimov, S. N.; Gerhardt, S. P.; Granetz, R. S.; Hender, T. C.; Pautasso, G.; Contributors, JET

2018-01-01

Halo currents generated during unmitigated tokamak disruptions are known to develop rotating asymmetric features that are of great concern to ITER because they can dynamically amplify the mechanical stresses on the machine. This paper presents a multi-machine analysis of these phenomena. More specifically, data from C-Mod, NSTX, ASDEX Upgrade, DIII-D, and JET are used to develop empirical scalings of three key quantities: (1) the machine-specific minimum current quench time, \

A multi-machine scaling of halo current rotation

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

Myers, C. E.; Eidietis, N. W.; Gerasimov, S. N.

Halo currents generated during unmitigated tokamak disruptions are known to develop rotating asymmetric features that are of great concern to ITER because they can dynamically amplify the mechanical stresses on the machine. This paper presents a multi-machine analysis of these phenomena. More specifically, data from C-Mod, NSTX, ASDEX Upgrade, DIII-D, and JET are used to develop empirical scalings of three key quantities: the machine-specific minimum current quench time,more » $$ \

A multi-machine scaling of halo current rotation

DOE PAGES

Myers, C. E.; Eidietis, N. W.; Gerasimov, S. N.; ...

2017-12-12

Halo currents generated during unmitigated tokamak disruptions are known to develop rotating asymmetric features that are of great concern to ITER because they can dynamically amplify the mechanical stresses on the machine. This paper presents a multi-machine analysis of these phenomena. More specifically, data from C-Mod, NSTX, ASDEX Upgrade, DIII-D, and JET are used to develop empirical scalings of three key quantities: the machine-specific minimum current quench time,more » $$ \

Receptive fields and the theory of discriminant operators

NASA Astrophysics Data System (ADS)

Gupta, Madan M.; Hungenahally, Suresh K.

1991-02-01

Biological basis for machine vision is a notion which is being used extensively for the development of machine vision systems for various applications. In this paper we have made an attempt to emulate the receptive fields that exist in the biological visual channels. In particular we have exploited the notion of receptive fields for developing the mathematical functions named as discriminantfunctions for the extraction of transition information from signals and multi-dimensional signals and images. These functions are found to be useful for the development of artificial receptive fields for neuro-vision systems. 1.

On the role of cost-sensitive learning in multi-class brain-computer interfaces.

PubMed

Devlaminck, Dieter; Waegeman, Willem; Wyns, Bart; Otte, Georges; Santens, Patrick

2010-06-01

Brain-computer interfaces (BCIs) present an alternative way of communication for people with severe disabilities. One of the shortcomings in current BCI systems, recently put forward in the fourth BCI competition, is the asynchronous detection of motor imagery versus resting state. We investigated this extension to the three-class case, in which the resting state is considered virtually lying between two motor classes, resulting in a large penalty when one motor task is misclassified into the other motor class. We particularly focus on the behavior of different machine-learning techniques and on the role of multi-class cost-sensitive learning in such a context. To this end, four different kernel methods are empirically compared, namely pairwise multi-class support vector machines (SVMs), two cost-sensitive multi-class SVMs and kernel-based ordinal regression. The experimental results illustrate that ordinal regression performs better than the other three approaches when a cost-sensitive performance measure such as the mean-squared error is considered. By contrast, multi-class cost-sensitive learning enables us to control the number of large errors made between two motor tasks.

Predictive optimized adaptive PSS in a single machine infinite bus.

PubMed

Milla, Freddy; Duarte-Mermoud, Manuel A

2016-07-01

Power System Stabilizer (PSS) devices are responsible for providing a damping torque component to generators for reducing fluctuations in the system caused by small perturbations. A Predictive Optimized Adaptive PSS (POA-PSS) to improve the oscillations in a Single Machine Infinite Bus (SMIB) power system is discussed in this paper. POA-PSS provides the optimal design parameters for the classic PSS using an optimization predictive algorithm, which adapts to changes in the inputs of the system. This approach is part of small signal stability analysis, which uses equations in an incremental form around an operating point. Simulation studies on the SMIB power system illustrate that the proposed POA-PSS approach has better performance than the classical PSS. In addition, the effort in the control action of the POA-PSS is much less than that of other approaches considered for comparison. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

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.

NASA Tech Briefs, February 2007

NASA Technical Reports Server (NTRS)

2007-01-01

Topics covered include: Calibration Test Set for a Phase-Comparison Digital Tracker; Wireless Acoustic Measurement System; Spiral Orbit Tribometer; Arrays of Miniature Microphones for Aeroacoustic Testing; Predicting Rocket or Jet Noise in Real Time; Computational Workbench for Multibody Dynamics; High-Power, High-Efficiency Ka-Band Space Traveling-Wave Tube; Gratings and Random Reflectors for Near-Infrared PIN Diodes; Optically Transparent Split-Ring Antennas for 1 to 10 GHz; Ice-Penetrating Robot for Scientific Exploration; Power-Amplifier Module for 145 to 165 GHz; Aerial Videography From Locally Launched Rockets; SiC Multi-Chip Power Modules as Power-System Building Blocks; Automated Design of Restraint Layer of an Inflatable Vessel; TMS for Instantiating a Knowledge Base With Incomplete Data; Simulating Flights of Future Launch Vehicles and Spacecraft; Control Code for Bearingless Switched- Reluctance Motor; Machine Aided Indexing and the NASA Thesaurus; Arbitrating Control of Control and Display Units; Web-Based Software for Managing Research; Driver Code for Adaptive Optics; Ceramic Paste for Patching High-Temperature Insulation; Fabrication of Polyimide-Matrix/Carbon and Boron-Fiber Tape; Protective Skins for Aerogel Monoliths; Code Assesses Risks Posed by Meteoroids and Orbital Debris; Asymmetric Bulkheads for Cylindrical Pressure Vessels; Self-Regulating Water-Separator System for Fuel Cells; Self-Advancing Step-Tap Drills; Array of Bolometers for Submillimeter- Wavelength Operation; Delta-Doped CCDs as Detector Arrays in Mass Spectrometers; Arrays of Bundles of Carbon Nanotubes as Field Emitters; Staggering Inflation To Stabilize Attitude of a Solar Sail; and Bare Conductive Tether for Decelerating a Spacecraft.

Removal of Lattice Imperfections that Impact the Optical Quality of Ti:Sapphire using Advanced Magnetorheological Finishing Techniques

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

Menapace, J A; Schaffers, K I; Bayramian, A J

2007-10-09

Ti:sapphire has become the premier lasing medium material for use in solid-state femtosecond high-peak power laser systems because of its wide wavelength tuning range. With a tuneable range from 680 to 1100 nm, peaking at 800 nm, Ti:sapphire lasing crystals can easily be tuned to the required pump wavelength and provide very high pump brightness due to their good beam quality and high output power of typically several watts. Femtosecond lasers are used for precision cutting and machining of materials ranging from steel to tooth enamel to delicate heart tissue and high explosives. These ultra-short pulses are too brief tomore » transfer heat or shock to the material being cut, which means that cutting, drilling, and machining occur with virtually no damage to surrounding material. Furthermore, these lasers can cut with high precision, making hairline cuts of less than 100 microns in thick materials along a computer-generated path. Extension of laser output to higher energies is limited by the size of the amplification medium. Yields of high quality large diameter crystals have been constrained by lattice distortions that may appear in the boule limiting the usable area from which high quality optics can be harvested. Lattice distortions affect the transmitted wavefront of these optics which ultimately limits the high-end power output and efficiency of the laser system, particularly when operated in multi-pass mode. To make matters even more complicated, Ti:sapphire is extremely hard (Mohs hardness of 9 with diamond being 10) which makes it extremely difficult to accurately polish using conventional methods without subsurface damage or significant wavefront error. In this presentation, we demonstrate for the first time that Magnetorheological finishing (MRF) can be used to compensate for the lattice distortions in Ti:sapphire by perturbing the transmitted wavefront. The advanced MRF techniques developed allow for precise polishing of the optical inverse of lattice distortions with magnitudes of about 70 nm in optical path difference onto one or both of the optical surfaces to produce high quality optics from otherwise unusable Ti:sapphire crystals. The techniques include interferometric, software, and machine modifications to precisely locate and polish sub-millimeter sites onto the optical surfaces that can not be polished into the optics conventionally. This work may allow extension of Ti:sapphire based systems to peak powers well beyond one petawatt.« less

Volumetric error modeling, identification and compensation based on screw theory for a large multi-axis propeller-measuring machine

NASA Astrophysics Data System (ADS)

Zhong, Xuemin; Liu, Hongqi; Mao, Xinyong; Li, Bin; He, Songping; Peng, Fangyu

2018-05-01

Large multi-axis propeller-measuring machines have two types of geometric error, position-independent geometric errors (PIGEs) and position-dependent geometric errors (PDGEs), which both have significant effects on the volumetric error of the measuring tool relative to the worktable. This paper focuses on modeling, identifying and compensating for the volumetric error of the measuring machine. A volumetric error model in the base coordinate system is established based on screw theory considering all the geometric errors. In order to fully identify all the geometric error parameters, a new method for systematic measurement and identification is proposed. All the PIGEs of adjacent axes and the six PDGEs of the linear axes are identified with a laser tracker using the proposed model. Finally, a volumetric error compensation strategy is presented and an inverse kinematic solution for compensation is proposed. The final measuring and compensation experiments have further verified the efficiency and effectiveness of the measuring and identification method, indicating that the method can be used in volumetric error compensation for large machine tools.

Digital fabrication of multi-material biomedical objects.

PubMed

Cheung, H H; Choi, S H

2009-12-01

This paper describes a multi-material virtual prototyping (MMVP) system for modelling and digital fabrication of discrete and functionally graded multi-material objects for biomedical applications. The MMVP system consists of a DMMVP module, an FGMVP module and a virtual reality (VR) simulation module. The DMMVP module is used to model discrete multi-material (DMM) objects, while the FGMVP module is for functionally graded multi-material (FGM) objects. The VR simulation module integrates these two modules to perform digital fabrication of multi-material objects, which can be subsequently visualized and analysed in a virtual environment to optimize MMLM processes for fabrication of product prototypes. Using the MMVP system, two biomedical objects, including a DMM human spine and an FGM intervertebral disc spacer are modelled and digitally fabricated for visualization and analysis in a VR environment. These studies show that the MMVP system is a practical tool for modelling, visualization, and subsequent fabrication of biomedical objects of discrete and functionally graded multi-materials for biomedical applications. The system may be adapted to control MMLM machines with appropriate hardware for physical fabrication of biomedical objects.

Modeling and simulation of a hybrid ship power system

NASA Astrophysics Data System (ADS)

Doktorcik, Christopher J.

2011-12-01

Optimizing the performance of naval ship power systems requires integrated design and coordination of the respective subsystems (sources, converters, and loads). A significant challenge in the system-level integration is solving the Power Management Control Problem (PMCP). The PMCP entails deciding on subsystem power usages for achieving a trade-off between the error in tracking a desired position/velocity profile, minimizing fuel consumption, and ensuring stable system operation, while at the same time meeting performance limitations of each subsystem. As such, the PMCP naturally arises at a supervisory level of a ship's operation. In this research, several critical steps toward the solution of the PMCP for surface ships have been undertaken. First, new behavioral models have been developed for gas turbine engines, wound rotor synchronous machines, DC super-capacitors, induction machines, and ship propulsion systems. Conventional models describe system inputs and outputs in terms of physical variables such as voltage, current, torque, and force. In contrast, the behavioral models developed herein express system inputs and outputs in terms of power whenever possible. Additionally, the models have been configured to form a hybrid system-level power model (HSPM) of a proposed ship electrical architecture. Lastly, several simulation studies have been completed to expose the capabilities and limitations of the HSPM.

A non-LTE analysis of high energy density Kr plasmas on Z and NIF

DOE PAGES

Dasgupta, A.; Clark, R. W.; Ouart, N.; ...

2016-10-20

We report that multi-keV X-ray radiation sources have a wide range of applications, from biomedical studies and research on thermonuclear fusion to materials science and astrophysics. The refurbished Z pulsed power machine at the Sandia National Laboratories produces intense multi-keV X-rays from argon Z-pinches, but for a krypton Z-pinch, the yield decreases much faster with atomic number Z A than similar sources on the National Ignition Facility (NIF) laser at the Lawrence Livermore National Laboratory. To investigate whether fundamental energy deposition differences between pulsed power and lasers could account for the yield differences, we consider the Kr plasma on themore » two machines. The analysis assumes the plasma not in local thermodynamic equilibrium, with a detailed coupling between the hydrodynamics, the radiation field, and the ionization physics. While for the plasma parameters of interest the details of krypton’s M-shell are not crucial, both the L-shell and the K-shell must be modeled in reasonable detail, including the state-specific dielectronic recombination processes that significantly affect Kr’s ionization balance and the resulting X-ray spectrum. We present a detailed description of the atomic model, provide synthetic K- and L-shell spectra, and compare these with the available experimental data from the Z-machine and from NIF to show that the K-shell yield behavior versus Z A is indeed related to the energy input characteristics. In conclusion, this work aims at understanding the probable causes that might explain the differences in the X-ray conversion efficiencies of several radiation sources on Z and« less

A non-LTE analysis of high energy density Kr plasmas on Z and NIF

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

Dasgupta, A.; Clark, R. W.; Ouart, N.

We report that multi-keV X-ray radiation sources have a wide range of applications, from biomedical studies and research on thermonuclear fusion to materials science and astrophysics. The refurbished Z pulsed power machine at the Sandia National Laboratories produces intense multi-keV X-rays from argon Z-pinches, but for a krypton Z-pinch, the yield decreases much faster with atomic number Z A than similar sources on the National Ignition Facility (NIF) laser at the Lawrence Livermore National Laboratory. To investigate whether fundamental energy deposition differences between pulsed power and lasers could account for the yield differences, we consider the Kr plasma on themore » two machines. The analysis assumes the plasma not in local thermodynamic equilibrium, with a detailed coupling between the hydrodynamics, the radiation field, and the ionization physics. While for the plasma parameters of interest the details of krypton’s M-shell are not crucial, both the L-shell and the K-shell must be modeled in reasonable detail, including the state-specific dielectronic recombination processes that significantly affect Kr’s ionization balance and the resulting X-ray spectrum. We present a detailed description of the atomic model, provide synthetic K- and L-shell spectra, and compare these with the available experimental data from the Z-machine and from NIF to show that the K-shell yield behavior versus Z A is indeed related to the energy input characteristics. In conclusion, this work aims at understanding the probable causes that might explain the differences in the X-ray conversion efficiencies of several radiation sources on Z and« less

Onboard planning for geological investigations using a rover team

NASA Technical Reports Server (NTRS)

Estlin, Tara; Gaines, Daniel; Fisher, Forest; Castano, Rebecca

2004-01-01

This paper describes an integrated system for coordinating multiple rover behavior with the overall goal of collecting planetary surface data. The Multi-Rover Integrated Science Understanding System (MISUS) combines techniques from planning and scheduling with machine learning to perform autonomous scientific exploration with cooperating rovers.

Virtual reality hardware for use in interactive 3D data fusion and visualization

NASA Astrophysics Data System (ADS)

Gourley, Christopher S.; Abidi, Mongi A.

1997-09-01

Virtual reality has become a tool for use in many areas of research. We have designed and built a VR system for use in range data fusion and visualization. One major VR tool is the CAVE. This is the ultimate visualization tool, but comes with a large price tag. Our design uses a unique CAVE whose graphics are powered by a desktop computer instead of a larger rack machine making it much less costly. The system consists of a screen eight feet tall by twenty-seven feet wide giving a variable field-of-view currently set at 160 degrees. A silicon graphics Indigo2 MaxImpact with the impact channel option is used for display. This gives the capability to drive three projectors at a resolution of 640 by 480 for use in displaying the virtual environment and one 640 by 480 display for a user control interface. This machine is also the first desktop package which has built-in hardware texture mapping. This feature allows us to quickly fuse the range and intensity data and other multi-sensory data. The final goal is a complete 3D texture mapped model of the environment. A dataglove, magnetic tracker, and spaceball are to be used for manipulation of the data and navigation through the virtual environment. This system gives several users the ability to interactively create 3D models from multiple range images.

Discovery of a new method for potent drug development using power function of stoichiometry ofhomomeric biocomplexes or biological nanomotors

PubMed Central

Pi, Fengmei; Vieweger, Mario; Zhao, Zhengyi; Wang, Shaoying; Guo, Peixuan

2015-01-01

Introduction Multidrug resistance and the appearance of incurable diseases inspire the quest for potent therapeutics. Areas Covered We review a new methodology in designing potent drugs by targeting multi-subunit homomeric biological motors, machines, or complexes with Z>1 and K=1, where Z is the stoichiometry of the target, and K is the number of drugged subunits required to block the function of the complex. The condition is similar to a series, electrical circuit of Christmas decorations; failure of one light bulb causes the entire lighting system to lose power. In most multisubunit, homomeric biological systems, a sequential coordination or cooperative action mechanism is utilized, thus K equals 1. Drug inhibition depends on the ratio of drugged to nondrugged complexes. When K=1, and Z>1, the inhibition effect follows a power law with respect to Z, leading to enhanced drug potency. The hypothesis that the potency of drug inhibition depends on the stoichiometry of the targeted biological complexes was recently quantified by Yang-Hui's Triangle (or binomial distribution), and proved using a highly sensitive in vitro phi29 viral DNA packaging system. Examples of targeting homomeric bio-complexes with high stoichiometry for potent drug discovery are discussed. Expert Opinion Biomotors with multiple subunits are widespread in viruses, bacteria, and cells, making this approach generally applicable in the development of inhibition drugs with high efficiency. PMID:26307193

Stroke dynamics and frequency of 3 phacoemulsification machines.

PubMed

Tognetto, Daniele; Cecchini, Paolo; Leon, Pia; Di Nicola, Marta; Ravalico, Giuseppe

2012-02-01

To measure the working frequency and the stroke dynamics of the phaco tip of 3 phacoemulsification machines. University Eye Clinic of Trieste, Italy. Experimental study. A video wet fixture was assembled to measure the working frequency using a micro camera and a micropulsed strobe-light system. A different video wet fixture was created to measure tip displacement as vectorial movement at different phaco powers using a microscopic video apparatus. The working frequency of the Infiniti Ozil machine was 43.0 kHz in longitudinal mode and 31.6 kHz in torsional mode. The frequency of the Whitestar Signature machine was 29.0 kHz in longitudinal mode and 38.0 kHz with the Ellips FX handpiece. The Stellaris machine had a frequency of 28.8 kHz. The longitudinal stroke of the 3 machines at different phaco powers was statistically significantly different. The Stellaris machine had the highest stroke extent (139 μm). The lateral movement of the Infiniti Ozil and Whitestar Signature machines differed significantly. No movement on the y-axis was observed for the Infiniti Ozil machine in torsional mode. The elliptical path of the Ellips FX handpiece had different x and y components at different phaco powers. The 3 phaco machines performed differently in terms of working frequency and stroke dynamics. The knowledge of the peculiar lateral and elliptical path strokes of Infiniti and Whitestar Signature machines may allow the surgeon to fully use these features for lens removal. Copyright © 2012 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.

A study of core Thomson scattering measurements in ITER using a multi-laser approach

NASA Astrophysics Data System (ADS)

Kurskiev, G. S.; Sdvizhenskii, P. A.; Bassan, M.; Andrew, P.; Bazhenov, A. N.; Bukreev, I. M.; Chernakov, P. V.; Kochergin, M. M.; Kukushkin, A. B.; Kukushkin, A. S.; Mukhin, E. E.; Razdobarin, A. G.; Samsonov, D. S.; Semenov, V. V.; Tolstyakov, S. Yu.; Kajita, S.; Masyukevich, S. V.

2015-05-01

The electron component is the main channel for anomalous power loss and the main indicator of transient processes in the tokamak plasma. The electron temperature and density profiles mainly determine the operational mode of the machine. This imposes demanding requirements on the precision and on the spatial and temporal resolution of the Thomson scattering (TS) measurements. Measurements of such high electron temperature with good accuracy in a large fusion device such as ITER using TS encounter a number of physical problems. The 40 keV TS spectrum has a significant blue shift. Due to the transmission functions of the fibres and to their darkening that can occur under a strong neutron irradiation, the operational wavelength range is bounded on the blue side. For example, high temperature measurements become impossible with the 1064 nm probing wavelength since the TS signal within the boundaries of the operational window weakly depends on Te. The second problem is connected with the TS calibration. The TS system for a large fusion machine like ITER will have a set of optical components inaccessible for maintenance, and their spectral characteristics may change with time. Since the present concept of the TS system for ITER relies on the classical approach to measuring the shape of the scattered spectra using wide spectral channels, the diagnostic will be very sensitive to the changes in the optical transmission. The third complication is connected with the deviation of the electron velocity distribution function from a Maxwellian that can happen under a strong ECRH/ECCD, and it may additionally hamper the measurements. This paper analyses the advantages of a ‘multi-laser approach’ implementation for the current design of the core TS system. Such an approach assumes simultaneous plasma probing with different wavelengths that allows the measurement accuracy to be improved significantly and to perform the spectral calibration of the TS system. Comparative analysis of the conservative and advanced approaches is given.

Open multi-agent control architecture to support virtual-reality-based man-machine interfaces

NASA Astrophysics Data System (ADS)

Freund, Eckhard; Rossmann, Juergen; Brasch, Marcel

2001-10-01

Projective Virtual Reality is a new and promising approach to intuitively operable man machine interfaces for the commanding and supervision of complex automation systems. The user interface part of Projective Virtual Reality heavily builds on latest Virtual Reality techniques, a task deduction component and automatic action planning capabilities. In order to realize man machine interfaces for complex applications, not only the Virtual Reality part has to be considered but also the capabilities of the underlying robot and automation controller are of great importance. This paper presents a control architecture that has proved to be an ideal basis for the realization of complex robotic and automation systems that are controlled by Virtual Reality based man machine interfaces. The architecture does not just provide a well suited framework for the real-time control of a multi robot system but also supports Virtual Reality metaphors and augmentations which facilitate the user's job to command and supervise a complex system. The developed control architecture has already been used for a number of applications. Its capability to integrate sensor information from sensors of different levels of abstraction in real-time helps to make the realized automation system very responsive to real world changes. In this paper, the architecture will be described comprehensively, its main building blocks will be discussed and one realization that is built based on an open source real-time operating system will be presented. The software design and the features of the architecture which make it generally applicable to the distributed control of automation agents in real world applications will be explained. Furthermore its application to the commanding and control of experiments in the Columbus space laboratory, the European contribution to the International Space Station (ISS), is only one example which will be described.

Optimal Resource Allocation under Fair QoS in Multi-tier Server Systems

NASA Astrophysics Data System (ADS)

Akai, Hirokazu; Ushio, Toshimitsu; Hayashi, Naoki

Recent development of network technology realizes multi-tier server systems, where several tiers perform functionally different processing requested by clients. It is an important issue to allocate resources of the systems to clients dynamically based on their current requests. On the other hand, Q-RAM has been proposed for resource allocation in real-time systems. In the server systems, it is important that execution results of all applications requested by clients are the same QoS(quality of service) level. In this paper, we extend Q-RAM to multi-tier server systems and propose a method for optimal resource allocation with fairness of the QoS levels of clients’ requests. We also consider an assignment problem of physical machines to be sleep in each tier sothat the energy consumption is minimized.

Human Activity Recognition from Smart-Phone Sensor Data using a Multi-Class Ensemble Learning in Home Monitoring.

PubMed

Ghose, Soumya; Mitra, Jhimli; Karunanithi, Mohan; Dowling, Jason

2015-01-01

Home monitoring of chronically ill or elderly patient can reduce frequent hospitalisations and hence provide improved quality of care at a reduced cost to the community, therefore reducing the burden on the healthcare system. Activity recognition of such patients is of high importance in such a design. In this work, a system for automatic human physical activity recognition from smart-phone inertial sensors data is proposed. An ensemble of decision trees framework is adopted to train and predict the multi-class human activity system. A comparison of our proposed method with a multi-class traditional support vector machine shows significant improvement in activity recognition accuracies.

An Adaptive Genetic Association Test Using Double Kernel Machines

PubMed Central

Zhan, Xiang; Epstein, Michael P.; Ghosh, Debashis

2014-01-01

Recently, gene set-based approaches have become very popular in gene expression profiling studies for assessing how genetic variants are related to disease outcomes. Since most genes are not differentially expressed, existing pathway tests considering all genes within a pathway suffer from considerable noise and power loss. Moreover, for a differentially expressed pathway, it is of interest to select important genes that drive the effect of the pathway. In this article, we propose an adaptive association test using double kernel machines (DKM), which can both select important genes within the pathway as well as test for the overall genetic pathway effect. This DKM procedure first uses the garrote kernel machines (GKM) test for the purposes of subset selection and then the least squares kernel machine (LSKM) test for testing the effect of the subset of genes. An appealing feature of the kernel machine framework is that it can provide a flexible and unified method for multi-dimensional modeling of the genetic pathway effect allowing for both parametric and nonparametric components. This DKM approach is illustrated with application to simulated data as well as to data from a neuroimaging genetics study. PMID:26640602

Runtime Performance and Virtual Network Control Alternatives in VM-Based High-Fidelity Network Simulations

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

Yoginath, Srikanth B; Perumalla, Kalyan S; Henz, Brian J

2012-01-01

In prior work (Yoginath and Perumalla, 2011; Yoginath, Perumalla and Henz, 2012), the motivation, challenges and issues were articulated in favor of virtual time ordering of Virtual Machines (VMs) in network simulations hosted on multi-core machines. Two major components in the overall virtualization challenge are (1) virtual timeline establishment and scheduling of VMs, and (2) virtualization of inter-VM communication. Here, we extend prior work by presenting scaling results for the first component, with experiment results on up to 128 VMs scheduled in virtual time order on a single 12-core host. We also explore the solution space of design alternatives formore » the second component, and present performance results from a multi-threaded, multi-queue implementation of inter-VM network control for synchronized execution with VM scheduling, incorporated in our NetWarp simulation system.« less

Interlock system for machine protection of the KOMAC 100-MeV proton linac

NASA Astrophysics Data System (ADS)

Song, Young-Gi

2015-02-01

The 100-MeV proton linear accelerator of the Korea Multi-purpose Accelerator Complex (KOMAC) has been developed. The beam service started this year after performing the beam commissioning. If the very sensitive and essential equipment is to be protected during machine operation, a machine interlock system is required, and the interlock system has been implemented. The purpose of the interlock system is to shut off the beam when the radio-frequency (RF) and ion source are unstable or a beam loss occurs. The interlock signal of the KOMAC linac includes a variety of sources, such as the beam loss, RF and high-voltage converter modulator faults, and fast closing valves of the vacuum window at the beam lines and so on. This system consists of a hardware-based interlock system using analog circuits and a software-based interlock system using an industrial programmable logic controller (PLC). The hardware-based interlock system has been fabricated, and the requirement has been satisfied with the results being within 10 µs. The software logic interlock system using the PLC has been connected to the framework of with the experimental physics and industrial control system (EPICS) to integrate a variety of interlock signals and to control the machine components when an interlock occurs. This paper will describe the design and the construction of the machine interlock system for the KOMAC 100-MeV linac.

Obstacle Recognition Based on Machine Learning for On-Chip LiDAR Sensors in a Cyber-Physical System

PubMed Central

Beruvides, Gerardo

2017-01-01

Collision avoidance is an important feature in advanced driver-assistance systems, aimed at providing correct, timely and reliable warnings before an imminent collision (with objects, vehicles, pedestrians, etc.). The obstacle recognition library is designed and implemented to address the design and evaluation of obstacle detection in a transportation cyber-physical system. The library is integrated into a co-simulation framework that is supported on the interaction between SCANeR software and Matlab/Simulink. From the best of the authors’ knowledge, two main contributions are reported in this paper. Firstly, the modelling and simulation of virtual on-chip light detection and ranging sensors in a cyber-physical system, for traffic scenarios, is presented. The cyber-physical system is designed and implemented in SCANeR. Secondly, three specific artificial intelligence-based methods for obstacle recognition libraries are also designed and applied using a sensory information database provided by SCANeR. The computational library has three methods for obstacle detection: a multi-layer perceptron neural network, a self-organization map and a support vector machine. Finally, a comparison among these methods under different weather conditions is presented, with very promising results in terms of accuracy. The best results are achieved using the multi-layer perceptron in sunny and foggy conditions, the support vector machine in rainy conditions and the self-organized map in snowy conditions. PMID:28906450

Obstacle Recognition Based on Machine Learning for On-Chip LiDAR Sensors in a Cyber-Physical System.

PubMed

Castaño, Fernando; Beruvides, Gerardo; Haber, Rodolfo E; Artuñedo, Antonio

2017-09-14

Collision avoidance is an important feature in advanced driver-assistance systems, aimed at providing correct, timely and reliable warnings before an imminent collision (with objects, vehicles, pedestrians, etc.). The obstacle recognition library is designed and implemented to address the design and evaluation of obstacle detection in a transportation cyber-physical system. The library is integrated into a co-simulation framework that is supported on the interaction between SCANeR software and Matlab/Simulink. From the best of the authors' knowledge, two main contributions are reported in this paper. Firstly, the modelling and simulation of virtual on-chip light detection and ranging sensors in a cyber-physical system, for traffic scenarios, is presented. The cyber-physical system is designed and implemented in SCANeR. Secondly, three specific artificial intelligence-based methods for obstacle recognition libraries are also designed and applied using a sensory information database provided by SCANeR. The computational library has three methods for obstacle detection: a multi-layer perceptron neural network, a self-organization map and a support vector machine. Finally, a comparison among these methods under different weather conditions is presented, with very promising results in terms of accuracy. The best results are achieved using the multi-layer perceptron in sunny and foggy conditions, the support vector machine in rainy conditions and the self-organized map in snowy conditions.

Start-up and control method and apparatus for resonant free piston Stirling engine

DOEpatents

Walsh, Michael M.

1984-01-01

A resonant free-piston Stirling engine having a new and improved start-up and control method and system. A displacer linear electrodynamic machine is provided having an armature secured to and movable with the displacer and having a stator supported by the Stirling engine housing in juxtaposition to the armature. A control excitation circuit is provided for electrically exciting the displacer linear electrodynamic machine with electrical excitation signals having substantially the same frequency as the desired frequency of operation of the Stirling engine. The excitation control circuit is designed so that it selectively and controllably causes the displacer electrodynamic machine to function either as a generator load to extract power from the displacer or the control circuit selectively can be operated to cause the displacer electrodynamic machine to operate as an electric drive motor to apply additional input power to the displacer in addition to the thermodynamic power feedback to the displacer whereby the displacer linear electrodynamic machine also is used in the electric drive motor mode as a means for initially starting the resonant free-piston Stirling engine.

High-Performance Multi-Fuel AMTEC Power System

DTIC Science & Technology

2000-12-01

AMTEC technology has demonstrated thermal to electric conversion efficiencies and power densities which make it an attractive option for meso-scaic...power generation. This report details development of an integrated, logistics-fueled, 500 W AMTEC power supply. The development targeted 2O% AMTEC ...cylindrical multi-tube/single cell AMTEC configuration with effective management of alkali metal flow; scaling down and integrating a multi-fuel micro-combustor

A distributed control approach for power and energy management in a notional shipboard power system

NASA Astrophysics Data System (ADS)

Shen, Qunying

The main goal of this thesis is to present a power control module (PCON) based approach for power and energy management and to examine its control capability in shipboard power system (SPS). The proposed control scheme is implemented in a notional medium voltage direct current (MVDC) integrated power system (IPS) for electric ship. To realize the control functions such as ship mode selection, generator launch schedule, blackout monitoring, and fault ride-through, a PCON based distributed power and energy management system (PEMS) is developed. The control scheme is proposed as two-layer hierarchical architecture with system level on the top as the supervisory control and zonal level on the bottom as the decentralized control, which is based on the zonal distribution characteristic of the notional MVDC IPS that was proposed as one of the approaches for Next Generation Integrated Power System (NGIPS) by Norbert Doerry. Several types of modules with different functionalities are used to derive the control scheme in detail for the notional MVDC IPS. Those modules include the power generation module (PGM) that controls the function of generators, the power conversion module (PCM) that controls the functions of DC/DC or DC/AC converters, etc. Among them, the power control module (PCON) plays a critical role in the PEMS. It is the core of the control process. PCONs in the PEMS interact with all the other modules, such as power propulsion module (PPM), energy storage module (ESM), load shedding module (LSHED), and human machine interface (HMI) to realize the control algorithm in PEMS. The proposed control scheme is implemented in real time using the real time digital simulator (RTDS) to verify its validity. To achieve this, a system level energy storage module (SESM) and a zonal level energy storage module (ZESM) are developed in RTDS to cooperate with PCONs to realize the control functionalities. In addition, a load shedding module which takes into account the reliability of power supply (in terms of quality of service) is developed. This module can supply uninterruptible power to the mission critical loads. In addition, a multi-agent system (MAS) based framework is proposed to implement the PCON based PEMS through a hardware setup that is composed of MAMBA boards and FPGA interface. Agents are implemented using Java Agent DEvelopment Framework (JADE). Various test scenarios were tested to validate the approach.

A Unified Multi-Functional Dynamic Spectrum Access Framework: Tutorial, Theory and Multi-GHz Wideband Testbed

PubMed Central

Qiu, Robert; Guo, Nan; Li, Husheng; Wu, Zhiqiang; Chakravarthy, Vasu; Song, Yu; Hu, Zhen; Zhang, Peng; Chen, Zhe

2009-01-01

Dynamic spectrum access is a must-have ingredient for future sensors that are ideally cognitive. The goal of this paper is a tutorial treatment of wideband cognitive radio and radar—a convergence of (1) algorithms survey, (2) hardware platforms survey, (3) challenges for multi-function (radar/communications) multi-GHz front end, (4) compressed sensing for multi-GHz waveforms—revolutionary A/D, (5) machine learning for cognitive radio/radar, (6) quickest detection, and (7) overlay/underlay cognitive radio waveforms. One focus of this paper is to address the multi-GHz front end, which is the challenge for the next-generation cognitive sensors. The unifying theme of this paper is to spell out the convergence for cognitive radio, radar, and anti-jamming. Moore’s law drives the system functions into digital parts. From a system viewpoint, this paper gives the first comprehensive treatment for the functions and the challenges of this multi-function (wideband) system. This paper brings together the inter-disciplinary knowledge. PMID:22454598

Elastic Multi-scale Mechanisms: Computation and Biological Evolution.

PubMed

Diaz Ochoa, Juan G

2018-01-01

Explanations based on low-level interacting elements are valuable and powerful since they contribute to identify the key mechanisms of biological functions. However, many dynamic systems based on low-level interacting elements with unambiguous, finite, and complete information of initial states generate future states that cannot be predicted, implying an increase of complexity and open-ended evolution. Such systems are like Turing machines, that overlap with dynamical systems that cannot halt. We argue that organisms find halting conditions by distorting these mechanisms, creating conditions for a constant creativity that drives evolution. We introduce a modulus of elasticity to measure the changes in these mechanisms in response to changes in the computed environment. We test this concept in a population of predators and predated cells with chemotactic mechanisms and demonstrate how the selection of a given mechanism depends on the entire population. We finally explore this concept in different frameworks and postulate that the identification of predictive mechanisms is only successful with small elasticity modulus.

Powering the programmed nanostructure and function of gold nanoparticles with catenated DNA machines

NASA Astrophysics Data System (ADS)

Elbaz, Johann; Cecconello, Alessandro; Fan, Zhiyuan; Govorov, Alexander O.; Willner, Itamar

2013-06-01

DNA nanotechnology is a rapidly developing research area in nanoscience. It includes the development of DNA machines, tailoring of DNA nanostructures, application of DNA nanostructures for computing, and more. Different DNA machines were reported in the past and DNA-guided assembly of nanoparticles represents an active research effort in DNA nanotechnology. Several DNA-dictated nanoparticle structures were reported, including a tetrahedron, a triangle or linear nanoengineered nanoparticle structures; however, the programmed, dynamic reversible switching of nanoparticle structures and, particularly, the dictated switchable functions emerging from the nanostructures, are missing elements in DNA nanotechnology. Here we introduce DNA catenane systems (interlocked DNA rings) as molecular DNA machines for the programmed, reversible and switchable arrangement of different-sized gold nanoparticles. We further demonstrate that the machine-powered gold nanoparticle structures reveal unique emerging switchable spectroscopic features, such as plasmonic coupling or surface-enhanced fluorescence.

Wireless Infrastructure M2M Network For Distributed Power Grid Monitoring

PubMed Central

Gharavi, Hamid; Hu, Bin

2018-01-01

With the massive integration of distributed renewable energy sources (RESs) into the power system, the demand for timely and reliable network quality monitoring, control, and fault analysis is rapidly growing. Following the successful deployment of Phasor Measurement Units (PMUs) in transmission systems for power monitoring, a new opportunity to utilize PMU measurement data for power quality assessment in distribution grid systems is emerging. The main problem however, is that a distribution grid system does not normally have the support of an infrastructure network. Therefore, the main objective in this paper is to develop a Machine-to-Machine (M2M) communication network that can support wide ranging sensory data, including high rate synchrophasor data for real-time communication. In particular, we evaluate the suitability of the emerging IEEE 802.11ah standard by exploiting its important features, such as classifying the power grid sensory data into different categories according to their traffic characteristics. For performance evaluation we use our hardware in the loop grid communication network testbed to access the performance of the network. PMID:29503505

Wireless Infrastructure M2M Network For Distributed Power Grid Monitoring.

PubMed

Gharavi, Hamid; Hu, Bin

2017-01-01

With the massive integration of distributed renewable energy sources (RESs) into the power system, the demand for timely and reliable network quality monitoring, control, and fault analysis is rapidly growing. Following the successful deployment of Phasor Measurement Units (PMUs) in transmission systems for power monitoring, a new opportunity to utilize PMU measurement data for power quality assessment in distribution grid systems is emerging. The main problem however, is that a distribution grid system does not normally have the support of an infrastructure network. Therefore, the main objective in this paper is to develop a Machine-to-Machine (M2M) communication network that can support wide ranging sensory data, including high rate synchrophasor data for real-time communication. In particular, we evaluate the suitability of the emerging IEEE 802.11ah standard by exploiting its important features, such as classifying the power grid sensory data into different categories according to their traffic characteristics. For performance evaluation we use our hardware in the loop grid communication network testbed to access the performance of the network.

Multi-Target Tracking for Swarm vs. Swarm UAV Systems

DTIC Science & Technology

2012-09-01

Uhlmann, “Using covariance intersection for SLAM,” Robotics and Autonomous Systems, vol. 55, pp. 3–20, Jan. 2007. [10] R. B. G. Wolfgang Niehsen... Krause , J. Leskovec, and C. Guestrin, “Data association for topic intensity track- ing,” Proceedings of the 23rd international conference on Machine

A Formal Characterization of Relevant Information in Multi-Agent Systems

DTIC Science & Technology

2009-10-01

Conference iTrust. (2004) [17] Sadek, D.: Le dialogue homme-machine : de l’ ergonomie des interfaces à l’ agent intelligent dia- loguant. In: Nouvelles interfaces hommemachine, Lavoisier Editeur, Arago 18 (1996) 277–321

Experiments in cooperative manipulation: A system perspective

NASA Technical Reports Server (NTRS)

Schneider, Stanley A.; Cannon, Robert H., Jr.

1989-01-01

In addition to cooperative dynamic control, the system incorporates real time vision feedback, a novel programming technique, and a graphical high level user interface. By focusing on the vertical integration problem, not only these subsystems are examined, but also their interfaces and interactions. The control system implements a multi-level hierarchical structure; the techniques developed for operator input, strategic command, and cooperative dynamic control are presented. At the highest level, a mouse-based graphical user interface allows an operator to direct the activities of the system. Strategic command is provided by a table-driven finite state machine; this methodology provides a powerful yet flexible technique for managing the concurrent system interactions. The dynamic controller implements object impedance control; an extension of Nevill Hogan's impedance control concept to cooperative arm manipulation of a single object. Experimental results are presented, showing the system locating and identifying a moving object catching it, and performing a simple cooperative assembly. Results from dynamic control experiments are also presented, showing the controller's excellent dynamic trajectory tracking performance, while also permitting control of environmental contact force.

Underwater cleaning techniqued used for removal of zebra mussels at the FitzPatrick Nuclear Power Plant

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

Hobbs, B.; Kahabka, J.

1995-06-01

This paper discusses the use of a mechanical brush cleaning technology recently used to remove biofouling from the Circulating Water (CW) System at New York Power Authority`s James A. FitzPatrick Nuclear Power Plant. The FitzPatrick plant had previously used chemical molluscicide to treat zebra mussels in the CW system. Full system treatment was performed in 1992 with limited forebay/screenwell treatment in 1993. The New York Power Authority (NYPA) decided to conduct a mechanical cleaning of the intake system in 1994. Specific project objectives included: (1) Achieve a level of surface cleaniness greater than 98%; (2) Remove 100% of debris, bothmore » existing sediment and debris generated as a result of cleaning; (3) Inspect all surfaces and components, identifying any problem areas; (4) Complete the task in a time frame within the 1994-95 refueling outage schedule window, and; (5) Determine if underwater mechanical cleaning is a cost-effective zebra mussel control method suitable for future application at FitzPatrick. A pre-cleaning inspection, including underwater video photography, was conducted of each area. Cleaning was accomplished using diver-controlled, multi-brush equipment included the electro-hydraulic powered Submersible Cleaning and Maintenance Platform (SCAMP), and several designs of hand-held machines. The brushes swept all zebra mussels off surfaces, restoring concrete and metal substrates to their original condition. Sensitive areas including pump housings, standpipes, sensor piping and chlorine injection tubing, were cleaned without degradation. Submersible vortex vacuum pumps were used to remove debris from the cavity. More than 46,000 ft{sup 2} of surface area was cleaned and over 460 cubic yards of dewatered debris were removed. As each area was completed, a post-clean inspection with photos and video was performed.« less

Machine Learning Toolkit for Extreme Scale

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

2014-03-31

Support Vector Machines (SVM) is a popular machine learning technique, which has been applied to a wide range of domains such as science, finance, and social networks for supervised learning. MaTEx undertakes the challenge of designing a scalable parallel SVM training algorithm for large scale systems, which includes commodity multi-core machines, tightly connected supercomputers and cloud computing systems. Several techniques are proposed for improved speed and memory space usage including adaptive and aggressive elimination of samples for faster convergence , and sparse format representation of data samples. Several heuristics for earliest possible to lazy elimination of non-contributing samples are consideredmore » in MaTEx. In many cases, where an early sample elimination might result in a false positive, low overhead mechanisms for reconstruction of key data structures are proposed. The proposed algorithm and heuristics are implemented and evaluated on various publicly available datasets« less

Development of an Organic Rankine Cycle system for exhaust energy recovery in internal combustion engines

NASA Astrophysics Data System (ADS)

Cipollone, Roberto; Bianchi, Giuseppe; Gualtieri, Angelo; Di Battista, Davide; Mauriello, Marco; Fatigati, Fabio

2015-11-01

Road transportation is currently one of the most influencing sectors for global energy consumptions and CO2 emissions. Nevertheless, more than one third of the fuel energy supplied to internal combustion engines is still rejected to the environment as thermal waste at the exhaust. Therefore, a greater fuel economy might be achieved recovering the energy from exhaust gases and converting it into useful power on board. In the current research activity, an ORC-based energy recovery system was developed and coupled with a diesel engine. The innovative feature of the recovery power unit relies upon the usage of sliding vane rotary machines as pump and expander. After a preliminary exhaust gas mapping, which allowed to assess the magnitude of the thermal power to be recovered, a thermodynamic analysis was carried out to design the ORC system and the sliding vane machines using R236fa as working fluid. An experimental campaign was eventually performed at different operating regimes according to the ESC procedure and investigated the recovery potential of the power unit at design and off-design conditions. Mechanical power recovered ranged from 0.7 kW up to 1.9 kW, with an overall cycle efficiency from 3.8% up to 4.8% respectively. These results candidate sliding vane machines as efficient and reliable devices for waste heat recovery applications.

30 CFR 18.21 - Machines equipped with powered dust collectors.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Machines equipped with powered dust collectors... Construction and Design Requirements § 18.21 Machines equipped with powered dust collectors. Powered dust collectors on machines submitted for approval shall meet the applicable requirements of Part 33 of this...

Optical design of laser transmission system

NASA Astrophysics Data System (ADS)

Zhang, Yulan; Feng, Jinliang; Li, Yongliang; Yang, Jiandong

1998-08-01

This paper discusses a design of optical transfer system used in carbon-dioxide laser therapeutic machine. The design of this system is according to the requirement of the therapeutic machine. The therapeutic machine requires the movement of laser transfer system is similar to the movement of human beings arms, which possesses 7 rotating hinges. We use optical hinges, which is composed of 45 degree mirrors. Because the carbon-dioxide laser mode is not good, light beam diameter at focus and divergence angle dissemination are big, we use a collecting lens at the transfer system output part in order to make the light beam diameter at focus in 0.2 to approximately 0.3 mm. For whole system the focus off-axis error is less than 0.5 mm, the transfer power consumption is smaller than 10%. The system can move in three dimension space freely and satisfies the therapeutic machine requirement.

Discrete particle swarm optimization to solve multi-objective limited-wait hybrid flow shop scheduling problem

NASA Astrophysics Data System (ADS)

Santosa, B.; Siswanto, N.; Fiqihesa

2018-04-01

This paper proposes a discrete Particle Swam Optimization (PSO) to solve limited-wait hybrid flowshop scheduing problem with multi objectives. Flow shop schedulimg represents the condition when several machines are arranged in series and each job must be processed at each machine with same sequence. The objective functions are minimizing completion time (makespan), total tardiness time, and total machine idle time. Flow shop scheduling model always grows to cope with the real production system accurately. Since flow shop scheduling is a NP-Hard problem then the most suitable method to solve is metaheuristics. One of metaheuristics algorithm is Particle Swarm Optimization (PSO), an algorithm which is based on the behavior of a swarm. Originally, PSO was intended to solve continuous optimization problems. Since flow shop scheduling is a discrete optimization problem, then, we need to modify PSO to fit the problem. The modification is done by using probability transition matrix mechanism. While to handle multi objectives problem, we use Pareto Optimal (MPSO). The results of MPSO is better than the PSO because the MPSO solution set produced higher probability to find the optimal solution. Besides the MPSO solution set is closer to the optimal solution

Balance in machine architecture: Bandwidth on board and offboard, integer/control speed and flops versus memory

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

Fischler, M.

1992-04-01

The issues to be addressed here are those of balance'' in machine architecture. By this, we mean how much emphasis must be placed on various aspects of the system to maximize its usefulness for physics. There are three components that contribute to the utility of a system: How the machine can be used, how big a problem can be attacked, and what the effective capabilities (power) of the hardware are like. The effective power issue is a matter of evaluating the impact of design decisions trading off architectural features such as memory bandwidth and interprocessor communication capabilities. What is studiedmore » is the effect these machine parameters have on how quickly the system can solve desired problems. There is a reasonable method for studying this: One selects a few representative algorithms and computes the impact of changing memory bandwidths, and so forth. The only room for controversy here is in the selection of representative problems. The issue of how big a problem can be attacked boils down to a balance of memory size versus power. Although this is a balance issue it is very different than the effective power situation, because no firm answer can be given at this time. The power to memory ratio is highly problem dependent, and optimizing it requires several pieces of physics input, including: how big a lattice is needed for interesting results; what sort of algorithms are best to use; and how many sweeps are needed to get valid results. We seem to be at the threshold of learning things about these issues, but for now, the memory size issue will necessarily be addressed in terms of best guesses, rules of thumb, and researchers' opinions.« less

Balance in machine architecture: Bandwidth on board and offboard, integer/control speed and flops versus memory

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

Fischler, M.

1992-04-01

The issues to be addressed here are those of ``balance`` in machine architecture. By this, we mean how much emphasis must be placed on various aspects of the system to maximize its usefulness for physics. There are three components that contribute to the utility of a system: How the machine can be used, how big a problem can be attacked, and what the effective capabilities (power) of the hardware are like. The effective power issue is a matter of evaluating the impact of design decisions trading off architectural features such as memory bandwidth and interprocessor communication capabilities. What is studiedmore » is the effect these machine parameters have on how quickly the system can solve desired problems. There is a reasonable method for studying this: One selects a few representative algorithms and computes the impact of changing memory bandwidths, and so forth. The only room for controversy here is in the selection of representative problems. The issue of how big a problem can be attacked boils down to a balance of memory size versus power. Although this is a balance issue it is very different than the effective power situation, because no firm answer can be given at this time. The power to memory ratio is highly problem dependent, and optimizing it requires several pieces of physics input, including: how big a lattice is needed for interesting results; what sort of algorithms are best to use; and how many sweeps are needed to get valid results. We seem to be at the threshold of learning things about these issues, but for now, the memory size issue will necessarily be addressed in terms of best guesses, rules of thumb, and researchers` opinions.« less

High power gas laser - Applications and future developments

NASA Technical Reports Server (NTRS)

Hertzberg, A.

1977-01-01

Fast flow can be used to create the population inversion required for lasing action, or can be used to improve laser operation, for example by the removal of waste heat. It is pointed out that at the present time all lasers which are capable of continuous high-average power employ flow as an indispensable aspect of operation. High power laser systems are discussed, taking into account the gasdynamic laser, the HF supersonic diffusion laser, and electric discharge lasers. Aerodynamics and high power lasers are considered, giving attention to flow effects in high-power gas lasers, aerodynamic windows and beam manipulation, and the Venus machine. Applications of high-power laser technology reported are related to laser material working, the employment of the laser in controlled fusion machines, laser isotope separation and photochemistry, and laser power transmission.

Concurrent Probabilistic Simulation of High Temperature Composite Structural Response

NASA Technical Reports Server (NTRS)

Abdi, Frank

1996-01-01

A computational structural/material analysis and design tool which would meet industry's future demand for expedience and reduced cost is presented. This unique software 'GENOA' is dedicated to parallel and high speed analysis to perform probabilistic evaluation of high temperature composite response of aerospace systems. The development is based on detailed integration and modification of diverse fields of specialized analysis techniques and mathematical models to combine their latest innovative capabilities into a commercially viable software package. The technique is specifically designed to exploit the availability of processors to perform computationally intense probabilistic analysis assessing uncertainties in structural reliability analysis and composite micromechanics. The primary objectives which were achieved in performing the development were: (1) Utilization of the power of parallel processing and static/dynamic load balancing optimization to make the complex simulation of structure, material and processing of high temperature composite affordable; (2) Computational integration and synchronization of probabilistic mathematics, structural/material mechanics and parallel computing; (3) Implementation of an innovative multi-level domain decomposition technique to identify the inherent parallelism, and increasing convergence rates through high- and low-level processor assignment; (4) Creating the framework for Portable Paralleled architecture for the machine independent Multi Instruction Multi Data, (MIMD), Single Instruction Multi Data (SIMD), hybrid and distributed workstation type of computers; and (5) Market evaluation. The results of Phase-2 effort provides a good basis for continuation and warrants Phase-3 government, and industry partnership.

Multi-temporal Land Use Mapping of Coastal Wetlands Area using Machine Learning in Google Earth Engine

NASA Astrophysics Data System (ADS)

Farda, N. M.

2017-12-01

Coastal wetlands provide ecosystem services essential to people and the environment. Changes in coastal wetlands, especially on land use, are important to monitor by utilizing multi-temporal imagery. The Google Earth Engine (GEE) provides many machine learning algorithms (10 algorithms) that are very useful for extracting land use from imagery. The research objective is to explore machine learning in Google Earth Engine and its accuracy for multi-temporal land use mapping of coastal wetland area. Landsat 3 MSS (1978), Landsat 5 TM (1991), Landsat 7 ETM+ (2001), and Landsat 8 OLI (2014) images located in Segara Anakan lagoon are selected to represent multi temporal images. The input for machine learning are visible and near infrared bands, PCA band, invers PCA bands, bare soil index, vegetation index, wetness index, elevation from ASTER GDEM, and GLCM (Harralick) texture, and also polygon samples in 140 locations. There are 10 machine learning algorithms applied to extract coastal wetlands land use from Landsat imagery. The algorithms are Fast Naive Bayes, CART (Classification and Regression Tree), Random Forests, GMO Max Entropy, Perceptron (Multi Class Perceptron), Winnow, Voting SVM, Margin SVM, Pegasos (Primal Estimated sub-GrAdient SOlver for Svm), IKPamir (Intersection Kernel Passive Aggressive Method for Information Retrieval, SVM). Machine learning in Google Earth Engine are very helpful in multi-temporal land use mapping, the highest accuracy for land use mapping of coastal wetland is CART with 96.98 % Overall Accuracy using K-Fold Cross Validation (K = 10). GEE is particularly useful for multi-temporal land use mapping with ready used image and classification algorithms, and also very challenging for other applications.

Power System Transient Stability Improvement by the Interline Power Flow Controller (IPFC)

NASA Astrophysics Data System (ADS)

Zhang, Jun; Yokoyama, Akihiko

This paper presents a study on the power system transient stability improvement by means of interline power flow controller (IPFC). The power injection model of IPFC in transient analysis is proposed and can be easily incorporated into existing power systems. Based on the energy function analysis, the operation of IPFC should guarantee that the time derivative of the global energy of the system is not greater than zero in order to damp the electromechanical oscillations. Accordingly, control laws of IPFC are proposed for its application to the single-machine infinite-bus (SMIB) system and the multimachine systems, respectively. Numerical simulations on the corresponding model power systems are presented to demonstrate their effectiveness in improving power system transient stability.

FEMA and RAM Analysis for the Multi Canister Overpack (MCO) Handling Machine

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

SWENSON, C.E.

2000-06-01

The Failure Modes and Effects Analysis and the Reliability, Availability, and Maintainability Analysis performed for the Multi-Canister Overpack Handling Machine (MHM) has shown that the current design provides for a safe system, but the reliability of the system (primarily due to the complexity of the interlocks and permissive controls) is relatively low. No specific failure modes were identified where significant consequences to the public occurred, or where significant impact to nearby workers should be expected. The overall reliability calculation for the MHM shows a 98.1 percent probability of operating for eight hours without failure, and an availability of the MHMmore » of 90 percent. The majority of the reliability issues are found in the interlocks and controls. The availability of appropriate spare parts and maintenance personnel, coupled with well written operating procedures, will play a more important role in successful mission completion for the MHM than other less complicated systems.« less

Research on multi - channel interactive virtual assembly system for power equipment under the “VR+” era

NASA Astrophysics Data System (ADS)

Ren, Yilong; Duan, Xitong; Wu, Lei; He, Jin; Xu, Wu

2017-06-01

With the development of the “VR+” era, the traditional virtual assembly system of power equipment has been unable to satisfy our growing needs. In this paper, based on the analysis of the traditional virtual assembly system of electric power equipment and the application of VR technology in the virtual assembly system of electric power equipment in our country, this paper puts forward the scheme of establishing the virtual assembly system of power equipment: At first, we should obtain the information of power equipment, then we should using OpenGL and multi texture technology to build 3D solid graphics library. After the completion of three-dimensional modeling, we can use the dynamic link library DLL package three-dimensional solid graphics generation program to realize the modularization of power equipment model library and power equipment model library generated hidden algorithm. After the establishment of 3D power equipment model database, we set up the virtual assembly system of 3D power equipment to separate the assembly operation of the power equipment from the space. At the same time, aiming at the deficiency of the traditional gesture recognition algorithm, we propose a gesture recognition algorithm based on improved PSO algorithm for BP neural network data glove. Finally, the virtual assembly system of power equipment can really achieve multi-channel interaction function.

Amputations

MedlinePlus

... powered and non-powered conveyors, printing presses, roll-forming and roll- bending machines, food slicers, meat grinders, ... processing machines, paper products machines, woodworking machines, metal-forming machines, and meat slicers. How can I get ...

Consequences of nonclassical measurement for the algorithmic description of continuous dynamical systems

NASA Technical Reports Server (NTRS)

Fields, Chris

1989-01-01

Continuous dynamical systems intuitively seem capable of more complex behavior than discrete systems. If analyzed in the framework of the traditional theory of computation, a continuous dynamical system with countably many quasistable states has at least the computational power of a universal Turing machine. Such an analysis assumes, however, the classical notion of measurement. If measurement is viewed nonclassically, a continuous dynamical system cannot, even in principle, exhibit behavior that cannot be simulated by a universal Turing machine.

Consequences of nonclassical measurement for the algorithmic description of continuous dynamical systems

NASA Technical Reports Server (NTRS)

Fields, Chris

1989-01-01

Continuous dynamical systems intuitively seem capable of more complex behavior than discrete systems. If analyzed in the framework of the traditional theory of computation, a continuous dynamical system with countablely many quasistable states has at least the computational power of a universal Turing machine. Such an analyses assumes, however, the classical notion of measurement. If measurement is viewed nonclassically, a continuous dynamical system cannot, even in principle, exhibit behavior that cannot be simulated by a universal Turing machine.

Industrial femtosecond lasers for machining of heat-sensitive polymers (Conference Presentation)

NASA Astrophysics Data System (ADS)

Hendricks, Frank; Bernard, Benjamin; Matylitsky, Victor V.

2017-03-01

Heat-sensitive materials, such as polymers, are used increasingly in various industrial sectors such as medical device manufacturing and organic electronics. Medical applications include implantable devices like stents, catheters and wires, which need to be structured and cut with minimum heat damage. Also the flat panel display market moves from LCD displays to organic LED (OLED) solutions, which utilize heat-sensitive polymer substrates. In both areas, the substrates often consist of multilayer stacks with different types of materials, such as metals, dielectric layers and polymers with different physical characteristic. The different thermal behavior and laser absorption properties of the materials used makes these stacks difficult to machine using conventional laser sources. Femtosecond lasers are an enabling technology for micromachining of these materials since it is possible to machine ultrafine structures with minimum thermal impact and very precise control over material removed. An industrial femtosecond Spirit HE laser system from Spectra-Physics with pulse duration <400 fs, pulse energies of >120 μJ and average output powers of >16 W is an ideal tool for industrial micromachining of a wide range of materials with highest quality and efficiency. The laser offers process flexibility with programmable pulse energy, repetition rate, and pulse width. In this paper, we provide an overview of machining heat-sensitive materials using Spirit HE laser. In particular, we show how the laser parameters (e.g. laser wavelength, pulse duration, applied energy and repetition rate) and the processing strategy (gas assisted single pass cut vs. multi-scan process) influence the efficiency and quality of laser processing.

Design of Ultra-High-Power-Density Machine Optimized for Future Aircraft

NASA Technical Reports Server (NTRS)

Choi, Benjamin B.

2004-01-01

The NASA Glenn Research Center's Structural Mechanics and Dynamics Branch is developing a compact, nonpolluting, bearingless electric machine with electric power supplied by fuel cells for future "more-electric" aircraft with specific power in the projected range of 50 hp/lb, whereas conventional electric machines generate usually 0.2 hp/lb. The use of such electric drives for propulsive fans or propellers depends on the successful development of ultra-high-power-density machines. One possible candidate for such ultra-high-power-density machines, a round-rotor synchronous machine with an engineering current density as high as 20,000 A/sq cm, was selected to investigate how much torque and power can be produced.

Method and system for controlling a permanent magnet machine during fault conditions

DOEpatents

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.

A Novel Vaping Machine Dedicated to Fully Controlling the Generation of E-Cigarette Emissions

PubMed Central

Soulet, Sébastien; Pairaud, Charly; Lalo, Hélène

2017-01-01

The accurate study of aerosol composition and nicotine release by electronic cigarettes is a major issue. In order to fully and correctly characterize aerosol, emission generation has to be completely mastered. This study describes an original vaping machine named Universal System for Analysis of Vaping (U-SAV), dedicated to vaping product study, enabling the control and real-time monitoring of applied flow rate and power. Repeatability and stability of the machine are demonstrated on flow rate, power regulation and e-liquid consumption. The emission protocol used to characterize the vaping machine is based on the AFNOR-XP-D90-300-3 standard (15 W power, 1 Ω atomizer resistance, 100 puffs collected per session, 1.1 L/min airflow rate). Each of the parameters has been verified with two standardized liquids by studying mass variations, power regulation and flow rate stability. U-SAV presents the required and necessary stability for the full control of emission generation. The U-SAV is recognised by the French association for standardization (AFNOR), European Committee for Standardization (CEN) and International Standards Organisation (ISO) as a vaping machine. It can be used to highlight the influence of the e-liquid composition, user behaviour and nature of the device, on the e-liquid consumption and aerosol composition. PMID:29036888

A Novel Vaping Machine Dedicated to Fully Controlling the Generation of E-Cigarette Emissions.

PubMed

Soulet, Sébastien; Pairaud, Charly; Lalo, Hélène

2017-10-14

The accurate study of aerosol composition and nicotine release by electronic cigarettes is a major issue. In order to fully and correctly characterize aerosol, emission generation has to be completely mastered. This study describes an original vaping machine named Universal System for Analysis of Vaping (U-SAV), dedicated to vaping product study, enabling the control and real-time monitoring of applied flow rate and power. Repeatability and stability of the machine are demonstrated on flow rate, power regulation and e-liquid consumption. The emission protocol used to characterize the vaping machine is based on the AFNOR-XP-D90-300-3 standard (15 W power, 1 Ω atomizer resistance, 100 puffs collected per session, 1.1 L/min airflow rate). Each of the parameters has been verified with two standardized liquids by studying mass variations, power regulation and flow rate stability. U-SAV presents the required and necessary stability for the full control of emission generation. The U-SAV is recognised by the French association for standardization (AFNOR), European Committee for Standardization (CEN) and International Standards Organisation (ISO) as a vaping machine. It can be used to highlight the influence of the e-liquid composition, user behaviour and nature of the device, on the e-liquid consumption and aerosol composition.

Cast iron cutting with nano TiN and multilayer TiN-CrN coated inserts

NASA Astrophysics Data System (ADS)

Perucca, M.; Durante, S.; Semmler, U.; Rüger, C.; Fuentes, G. G.; Almandoz, E.

2012-09-01

During the past decade great success has been achieved in the development of duplex and multilayer multi-functional surface systems. Among these surface systems outstanding properties have nanoscale multilayer coatings. Within the framework of the M3-2S project funded in the 7th European Framework Programme, several nanoscale multilayer coatings have been developed and investigated for experimental and industrial validation. This paper shows the performance of TiN and TiN/CrN nanoscale multilayer coatings on WC cutting inserts when machining GJL250 cast iron. The thin films have been deposited by cathodic arc evaporation in an industrial PVD system. The multilayer deposition characteristic and its properties are shown. The inserts have been investigated in systematic cutting experiments of cast iron bars on a turning machine specifically equipped for force measurements, accompanied by wear determination. Furthermore, equivalent experiments have been carried out on an industrial turning unit. Industrial validation criteria have been applied to assess the comparative performance of the coatings. The choice of the material and the machined parts is driven by an interest in automotive applications. The industrial tests show the need to further optimise the multi-scale modelling approach in order to reduce the lead time of the coating development as well as to improve simulation reliability.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

A Multi-TeV Linear Collider Based on CLIC Technology : CLIC Conceptual Design Report

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

Aicheler, M; Burrows, P.; Draper, M.

This report describes the accelerator studies for a future multi-TeV e +e - collider based on the Compact Linear Collider (CLIC) technology. The CLIC concept as described in the report is based on high gradient normal-conducting accelerating structures where the RF power for the acceleration of the colliding beams is extracted from a high-current Drive Beam that runs parallel with the main linac. The focus of CLIC R&D over the last years has been on addressing a set of key feasibility issues that are essential for proving the fundamental validity of the CLIC concept. The status of these feasibility studiesmore » are described and summarized. The report also includes a technical description of the accelerator components and R&D to develop the most important parts and methods, as well as a description of the civil engineering and technical services associated with the installation. Several larger system tests have been performed to validate the two-beam scheme, and of particular importance are the results from the CLIC test facility at CERN (CTF3). Both the machine and detector/physics studies for CLIC have primarily focused on the 3 TeV implementation of CLIC as a benchmark for the CLIC feasibility. This report also includes specific studies for an initial 500 GeV machine, and some discussion of possible intermediate energy stages. The performance and operation issues related to operation at reduced energy compared to the nominal, and considerations of a staged construction program are included in the final part of the report. The CLIC accelerator study is organized as an international collaboration with 43 partners in 22 countries. An associated report describes the physics potential and experiments at CLIC and a shorter report in preparation will focus on the CLIC implementation strategy, together with a plan for the CLIC R&D studies 2012–2016. Critical and important implementation issues such as cost, power and schedule will be addressed there.« less

Induction machine bearing faults detection based on a multi-dimensional MUSIC algorithm and maximum likelihood estimation.

PubMed

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.

Modelling of Robotized Manufacturing Systems Using MultiAgent Formalism

NASA Astrophysics Data System (ADS)

Foit, K.; Gwiazda, A.; Banaś, W.

2016-08-01

The evolution of manufacturing systems has greatly accelerated due to development of sophisticated control systems. On top of determined, one way production flow the need of decision making has arisen as a result of growing product range that are manufactured simultaneously, using the same resources. On the other hand, the intelligent flow control could address the “bottleneck” problem caused by the machine failure. This sort of manufacturing systems uses advanced control algorithms that are introduced by the use of logic controllers. The complex algorithms used in the control systems requires to employ appropriate methods during the modelling process, like the agent-based one, which is the subject of this paper. The concept of an agent is derived from the object-based methodology of modelling, so it meets the requirements of representing the physical properties of the machines as well as the logical form of control systems. Each agent has a high level of autonomy and could be considered separately. The multi-agent system consists of minimum two agents that can interact and modify the environment, where they act. This may lead to the creation of self-organizing structure, what could be interesting feature during design and test of manufacturing system.

Space Station man-machine automation trade-off analysis

NASA Technical Reports Server (NTRS)

Zimmerman, W. F.; Bard, J.; Feinberg, A.

1985-01-01

The man machine automation tradeoff methodology presented is of four research tasks comprising the autonomous spacecraft system technology (ASST) project. ASST was established to identify and study system level design problems for autonomous spacecraft. Using the Space Station as an example spacecraft system requiring a certain level of autonomous control, a system level, man machine automation tradeoff methodology is presented that: (1) optimizes man machine mixes for different ground and on orbit crew functions subject to cost, safety, weight, power, and reliability constraints, and (2) plots the best incorporation plan for new, emerging technologies by weighing cost, relative availability, reliability, safety, importance to out year missions, and ease of retrofit. A fairly straightforward approach is taken by the methodology to valuing human productivity, it is still sensitive to the important subtleties associated with designing a well integrated, man machine system. These subtleties include considerations such as crew preference to retain certain spacecraft control functions; or valuing human integration/decision capabilities over equivalent hardware/software where appropriate.

A joint precoding scheme for indoor downlink multi-user MIMO VLC systems

NASA Astrophysics Data System (ADS)

Zhao, Qiong; Fan, Yangyu; Kang, Bochao

2017-11-01

In this study, we aim to improve the system performance and reduce the implementation complexity of precoding scheme for visible light communication (VLC) systems. By incorporating the power-method algorithm and the block diagonalization (BD) algorithm, we propose a joint precoding scheme for indoor downlink multi-user multi-input-multi-output (MU-MIMO) VLC systems. In this scheme, we apply the BD algorithm to eliminate the co-channel interference (CCI) among users firstly. Secondly, the power-method algorithm is used to search the precoding weight for each user based on the optimal criterion of signal to interference plus noise ratio (SINR) maximization. Finally, the optical power restrictions of VLC systems are taken into account to constrain the precoding weight matrix. Comprehensive computer simulations in two scenarios indicate that the proposed scheme always has better bit error rate (BER) performance and lower computation complexity than that of the traditional scheme.

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

Meneses, Esteban; Ni, Xiang; Jones, Terry R

The unprecedented computational power of cur- rent supercomputers now makes possible the exploration of complex problems in many scientific fields, from genomic analysis to computational fluid dynamics. Modern machines are powerful because they are massive: they assemble millions of cores and a huge quantity of disks, cards, routers, and other components. But it is precisely the size of these machines that glooms the future of supercomputing. A system that comprises many components has a high chance to fail, and fail often. In order to make the next generation of supercomputers usable, it is imperative to use some type of faultmore » tolerance platform to run applications on large machines. Most fault tolerance strategies can be optimized for the peculiarities of each system and boost efficacy by keeping the system productive. In this paper, we aim to understand how failure characterization can improve resilience in several layers of the software stack: applications, runtime systems, and job schedulers. We examine the Titan supercomputer, one of the fastest systems in the world. We analyze a full year of Titan in production and distill the failure patterns of the machine. By looking into Titan s log files and using the criteria of experts, we provide a detailed description of the types of failures. In addition, we inspect the job submission files and describe how the system is used. Using those two sources, we cross correlate failures in the machine to executing jobs and provide a picture of how failures affect the user experience. We believe such characterization is fundamental in developing appropriate fault tolerance solutions for Cray systems similar to Titan.« less

Use of microsecond current prepulse for dramatic improvements of wire array Z-pinch implosion

NASA Astrophysics Data System (ADS)

Calamy, H.; Lassalle, F.; Loyen, A.; Zucchini, F.; Chittenden, J. P.; Hamann, F.; Maury, P.; Georges, A.; Bedoch, J. P.; Morell, A.

2008-01-01

The Sphinx machine [F. Lassalle et al., "Status on the SPHINX machine based on the 1microsecond LTD technology"] based on microsecond linear transformer driver (LTD) technology is used to implode an aluminium wire array with an outer diameter up to 140mm and maximum current from 3.5to5MA. 700to800ns implosion Z-pinch experiments are performed on this driver essentially with aluminium. Best results obtained before the improvement described in this paper were 1-3TW radial total power, 100-300kJ total yield, and 20-30kJ energy above 1keV. An auxiliary generator was added to the Sphinx machine in order to allow a multi microsecond current to be injected through the wire array load before the start of the main current. Amplitude and duration of this current prepulse are adjustable, with maxima ˜10kA and 50μs. This prepulse dramatically changes the ablation phase leading to an improvement of the axial homogeneity of both the implosion and the final radiating column. Total power was multiplied by a factor of 6, total yield by a factor of 2.5 with a reproducible behavior. This paper presents experimental results, magnetohydrodynamic simulations, and analysis of the effect of such a long current prepulse.

Software platform virtualization in chemistry research and university teaching

PubMed Central

2009-01-01

Background Modern chemistry laboratories operate with a wide range of software applications under different operating systems, such as Windows, LINUX or Mac OS X. Instead of installing software on different computers it is possible to install those applications on a single computer using Virtual Machine software. Software platform virtualization allows a single guest operating system to execute multiple other operating systems on the same computer. We apply and discuss the use of virtual machines in chemistry research and teaching laboratories. Results Virtual machines are commonly used for cheminformatics software development and testing. Benchmarking multiple chemistry software packages we have confirmed that the computational speed penalty for using virtual machines is low and around 5% to 10%. Software virtualization in a teaching environment allows faster deployment and easy use of commercial and open source software in hands-on computer teaching labs. Conclusion Software virtualization in chemistry, mass spectrometry and cheminformatics is needed for software testing and development of software for different operating systems. In order to obtain maximum performance the virtualization software should be multi-core enabled and allow the use of multiprocessor configurations in the virtual machine environment. Server consolidation, by running multiple tasks and operating systems on a single physical machine, can lead to lower maintenance and hardware costs especially in small research labs. The use of virtual machines can prevent software virus infections and security breaches when used as a sandbox system for internet access and software testing. Complex software setups can be created with virtual machines and are easily deployed later to multiple computers for hands-on teaching classes. We discuss the popularity of bioinformatics compared to cheminformatics as well as the missing cheminformatics education at universities worldwide. PMID:20150997

Software platform virtualization in chemistry research and university teaching.

PubMed

Kind, Tobias; Leamy, Tim; Leary, Julie A; Fiehn, Oliver

2009-11-16

Modern chemistry laboratories operate with a wide range of software applications under different operating systems, such as Windows, LINUX or Mac OS X. Instead of installing software on different computers it is possible to install those applications on a single computer using Virtual Machine software. Software platform virtualization allows a single guest operating system to execute multiple other operating systems on the same computer. We apply and discuss the use of virtual machines in chemistry research and teaching laboratories. Virtual machines are commonly used for cheminformatics software development and testing. Benchmarking multiple chemistry software packages we have confirmed that the computational speed penalty for using virtual machines is low and around 5% to 10%. Software virtualization in a teaching environment allows faster deployment and easy use of commercial and open source software in hands-on computer teaching labs. Software virtualization in chemistry, mass spectrometry and cheminformatics is needed for software testing and development of software for different operating systems. In order to obtain maximum performance the virtualization software should be multi-core enabled and allow the use of multiprocessor configurations in the virtual machine environment. Server consolidation, by running multiple tasks and operating systems on a single physical machine, can lead to lower maintenance and hardware costs especially in small research labs. The use of virtual machines can prevent software virus infections and security breaches when used as a sandbox system for internet access and software testing. Complex software setups can be created with virtual machines and are easily deployed later to multiple computers for hands-on teaching classes. We discuss the popularity of bioinformatics compared to cheminformatics as well as the missing cheminformatics education at universities worldwide.

30 CFR 75.703-2 - Approved grounding mediums.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Approved grounding mediums. 75.703-2 Section 75... mediums. For purposes of grounding offtrack direct-current machines, the following grounding mediums are... alternating current grounding medium where such machines are fed by an ungrounded direct-current power system...

30 CFR 75.703-2 - Approved grounding mediums.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Approved grounding mediums. 75.703-2 Section 75... mediums. For purposes of grounding offtrack direct-current machines, the following grounding mediums are... alternating current grounding medium where such machines are fed by an ungrounded direct-current power system...

30 CFR 75.703-2 - Approved grounding mediums.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Approved grounding mediums. 75.703-2 Section 75... mediums. For purposes of grounding offtrack direct-current machines, the following grounding mediums are... alternating current grounding medium where such machines are fed by an ungrounded direct-current power system...

30 CFR 75.703-2 - Approved grounding mediums.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Approved grounding mediums. 75.703-2 Section 75... mediums. For purposes of grounding offtrack direct-current machines, the following grounding mediums are... alternating current grounding medium where such machines are fed by an ungrounded direct-current power system...

30 CFR 75.703-2 - Approved grounding mediums.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Approved grounding mediums. 75.703-2 Section 75... mediums. For purposes of grounding offtrack direct-current machines, the following grounding mediums are... alternating current grounding medium where such machines are fed by an ungrounded direct-current power system...

Multi-agent Reinforcement Learning Model for Effective Action Selection

NASA Astrophysics Data System (ADS)

Youk, Sang Jo; Lee, Bong Keun

Reinforcement learning is a sub area of machine learning concerned with how an agent ought to take actions in an environment so as to maximize some notion of long-term reward. In the case of multi-agent, especially, which state space and action space gets very enormous in compared to single agent, so it needs to take most effective measure available select the action strategy for effective reinforcement learning. This paper proposes a multi-agent reinforcement learning model based on fuzzy inference system in order to improve learning collect speed and select an effective action in multi-agent. This paper verifies an effective action select strategy through evaluation tests based on Robocop Keep away which is one of useful test-beds for multi-agent. Our proposed model can apply to evaluate efficiency of the various intelligent multi-agents and also can apply to strategy and tactics of robot soccer system.

Load allocation of power plant using multi echelon economic dispatch

NASA Astrophysics Data System (ADS)

Wahyuda, Santosa, Budi; Rusdiansyah, Ahmad

2017-11-01

In this paper, the allocation of power plant load which is usually done with a single echelon as in the load flow calculation, is expanded into a multi echelon. A plant load allocation model based on the integration of economic dispatch and multi-echelon problem is proposed. The resulting model is called as Single Objective Multi Echelon Economic Dispatch (SOME ED). This model allows the distribution of electrical power in more detail in the transmission and distribution substations along the existing network. Considering the interconnection system where the distance between the plant and the load center is usually far away, therefore the loss in this model is seen as a function of distance. The advantages of this model is its capability of allocating electrical loads properly, as well as economic dispatch information with the flexibility of electric power system as a result of using multi-echelon. In this model, the flexibility can be viewed from two sides, namely the supply and demand sides, so that the security of the power system is maintained. The model was tested on a small artificial data. The results demonstrated a good performance. It is still very open to further develop the model considering the integration with renewable energy, multi-objective with environmental issues and applied to the case with a larger scale.

Structural Mechanics and Dynamics Branch

NASA Technical Reports Server (NTRS)

Stefko, George

2003-01-01

The 2002 annual report of the Structural Mechanics and Dynamics Branch reflects the majority of the work performed by the branch staff during the 2002 calendar year. Its purpose is to give a brief review of the branch s technical accomplishments. The Structural Mechanics and Dynamics Branch develops innovative computational tools, benchmark experimental data, and solutions to long-term barrier problems in the areas of propulsion aeroelasticity, active and passive damping, engine vibration control, rotor dynamics, magnetic suspension, structural mechanics, probabilistics, smart structures, engine system dynamics, and engine containment. Furthermore, the branch is developing a compact, nonpolluting, bearingless electric machine with electric power supplied by fuel cells for future "more electric" aircraft. An ultra-high-power-density machine that can generate projected power densities of 50 hp/lb or more, in comparison to conventional electric machines, which generate usually 0.2 hp/lb, is under development for application to electric drives for propulsive fans or propellers. In the future, propulsion and power systems will need to be lighter, to operate at higher temperatures, and to be more reliable in order to achieve higher performance and economic viability. The Structural Mechanics and Dynamics Branch is working to achieve these complex, challenging goals.

An Investigation into the Comparative Costs of Additive Manufacture vs. Machine from Solid for Aero Engine Parts

DTIC Science & Technology

2006-05-01

welding power sources are not totally efficient at converting power drawn from the wall into heat energy used for the welding process . TIG sources are...Powder bed + Laser • Wire + Laser • Wire + Electron Beam • Wire + TIG Each system has its own unique attributes in terms of process variables...relative economics of producing a near net shape by Additive Manufacturing (AM) processes compared with traditional machine from solid processes (MFS

Techniques and potential capabilities of multi-resolutional information (knowledge) processing

NASA Technical Reports Server (NTRS)

Meystel, A.

1989-01-01

A concept of nested hierarchical (multi-resolutional, pyramidal) information (knowledge) processing is introduced for a variety of systems including data and/or knowledge bases, vision, control, and manufacturing systems, industrial automated robots, and (self-programmed) autonomous intelligent machines. A set of practical recommendations is presented using a case study of a multiresolutional object representation. It is demonstrated here that any intelligent module transforms (sometimes, irreversibly) the knowledge it deals with, and this tranformation affects the subsequent computation processes, e.g., those of decision and control. Several types of knowledge transformation are reviewed. Definite conditions are analyzed, satisfaction of which is required for organization and processing of redundant information (knowledge) in the multi-resolutional systems. Providing a definite degree of redundancy is one of these conditions.

Configurable software for satellite graphics

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

Hartzman, P D

An important goal in interactive computer graphics is to provide users with both quick system responses for basic graphics functions and enough computing power for complex calculations. One solution is to have a distributed graphics system in which a minicomputer and a powerful large computer share the work. The most versatile type of distributed system is an intelligent satellite system in which the minicomputer is programmable by the application user and can do most of the work while the large remote machine is used for difficult computations. At New York University, the hardware was configured from available equipment. The levelmore » of system intelligence resulted almost completely from software development. Unlike previous work with intelligent satellites, the resulting system had system control centered in the satellite. It also had the ability to reconfigure software during realtime operation. The design of the system was done at a very high level using set theoretic language. The specification clearly illustrated processor boundaries and interfaces. The high-level specification also produced a compact, machine-independent virtual graphics data structure for picture representation. The software was written in a systems implementation language; thus, only one set of programs was needed for both machines. A user can program both machines in a single language. Tests of the system with an application program indicate that is has very high potential. A major result of this work is the demonstration that a gigantic investment in new hardware is not necessary for computing facilities interested in graphics.« less

Imaging and machine learning techniques for diagnosis of Alzheimer's disease.

PubMed

Mirzaei, Golrokh; Adeli, Anahita; Adeli, Hojjat

2016-12-01

Alzheimer's disease (AD) is a common health problem in elderly people. There has been considerable research toward the diagnosis and early detection of this disease in the past decade. The sensitivity of biomarkers and the accuracy of the detection techniques have been defined to be the key to an accurate diagnosis. This paper presents a state-of-the-art review of the research performed on the diagnosis of AD based on imaging and machine learning techniques. Different segmentation and machine learning techniques used for the diagnosis of AD are reviewed including thresholding, supervised and unsupervised learning, probabilistic techniques, Atlas-based approaches, and fusion of different image modalities. More recent and powerful classification techniques such as the enhanced probabilistic neural network of Ahmadlou and Adeli should be investigated with the goal of improving the diagnosis accuracy. A combination of different image modalities can help improve the diagnosis accuracy rate. Research is needed on the combination of modalities to discover multi-modal biomarkers.

Broiler chickens can benefit from machine learning: support vector machine analysis of observational epidemiological data

PubMed Central

Hepworth, Philip J.; Nefedov, Alexey V.; Muchnik, Ilya B.; Morgan, Kenton L.

2012-01-01

Machine-learning algorithms pervade our daily lives. In epidemiology, supervised machine learning has the potential for classification, diagnosis and risk factor identification. Here, we report the use of support vector machine learning to identify the features associated with hock burn on commercial broiler farms, using routinely collected farm management data. These data lend themselves to analysis using machine-learning techniques. Hock burn, dermatitis of the skin over the hock, is an important indicator of broiler health and welfare. Remarkably, this classifier can predict the occurrence of high hock burn prevalence with accuracy of 0.78 on unseen data, as measured by the area under the receiver operating characteristic curve. We also compare the results with those obtained by standard multi-variable logistic regression and suggest that this technique provides new insights into the data. This novel application of a machine-learning algorithm, embedded in poultry management systems could offer significant improvements in broiler health and welfare worldwide. PMID:22319115

Broiler chickens can benefit from machine learning: support vector machine analysis of observational epidemiological data.

PubMed

Hepworth, Philip J; Nefedov, Alexey V; Muchnik, Ilya B; Morgan, Kenton L

2012-08-07

Machine-learning algorithms pervade our daily lives. In epidemiology, supervised machine learning has the potential for classification, diagnosis and risk factor identification. Here, we report the use of support vector machine learning to identify the features associated with hock burn on commercial broiler farms, using routinely collected farm management data. These data lend themselves to analysis using machine-learning techniques. Hock burn, dermatitis of the skin over the hock, is an important indicator of broiler health and welfare. Remarkably, this classifier can predict the occurrence of high hock burn prevalence with accuracy of 0.78 on unseen data, as measured by the area under the receiver operating characteristic curve. We also compare the results with those obtained by standard multi-variable logistic regression and suggest that this technique provides new insights into the data. This novel application of a machine-learning algorithm, embedded in poultry management systems could offer significant improvements in broiler health and welfare worldwide.

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

PubMed

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

2017-01-01

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

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

PubMed Central

2017-01-01

Predicting the output power of photovoltaic system with nonstationarity and randomness, an output power prediction model for grid-connected PV systems is proposed based on empirical mode decomposition (EMD) and support vector machine (SVM) optimized with an artificial bee colony (ABC) algorithm. First, according to the weather forecast data sets on the prediction date, the time series data of output power on a similar day with 15-minute intervals are built. Second, the time series data of the output power are decomposed into a series of components, including some intrinsic mode components IMFn and a trend component Res, at different scales using EMD. The corresponding SVM prediction model is established for each IMF component and trend component, and the SVM model parameters are optimized with the artificial bee colony algorithm. Finally, the prediction results of each model are reconstructed, and the predicted values of the output power of the grid-connected PV system can be obtained. The prediction model is tested with actual data, and the results show that the power prediction model based on the EMD and ABC-SVM has a faster calculation speed and higher prediction accuracy than do the single SVM prediction model and the EMD-SVM prediction model without optimization. PMID:28912803

Nanotube Heterojunctions and Endo-Fullerenes for Nanoelectronics

NASA Technical Reports Server (NTRS)

Srivastava, Deepak; Menon, M.; Andriotis, Antonis; Cho, K.; Park, Jun; Biegel, Bryan A. (Technical Monitor)

2002-01-01

Topics discussed include: (1) Light-Weight Multi-Functional Materials: Nanomechanics; Nanotubes and Composites; Thermal/Chemical/Electrical Characterization; (2) Biomimetic/Revolutionary Concepts: Evolutionary Computing and Sensing; Self-Heating Materials; (3) Central Computing System: Molecular Electronics; Materials for Quantum Bits; and (4) Molecular Machines.

Minimal universal quantum heat machine.

PubMed

Gelbwaser-Klimovsky, D; Alicki, R; Kurizki, G

2013-01-01

In traditional thermodynamics the Carnot cycle yields the ideal performance bound of heat engines and refrigerators. We propose and analyze a minimal model of a heat machine that can play a similar role in quantum regimes. The minimal model consists of a single two-level system with periodically modulated energy splitting that is permanently, weakly, coupled to two spectrally separated heat baths at different temperatures. The equation of motion allows us to compute the stationary power and heat currents in the machine consistent with the second law of thermodynamics. This dual-purpose machine can act as either an engine or a refrigerator (heat pump) depending on the modulation rate. In both modes of operation, the maximal Carnot efficiency is reached at zero power. We study the conditions for finite-time optimal performance for several variants of the model. Possible realizations of the model are discussed.

High-Performance AC Power Source by Applying Robust Stability Control Technology for Precision Material Machining

NASA Astrophysics Data System (ADS)

Chang, En-Chih

2018-02-01

This paper presents a high-performance AC power source by applying robust stability control technology for precision material machining (PMM). The proposed technology associates the benefits of finite-time convergent sliding function (FTCSF) and firefly optimization algorithm (FOA). The FTCSF maintains the robustness of conventional sliding mode, and simultaneously speeds up the convergence speed of the system state. Unfortunately, when a highly nonlinear loading is applied, the chatter will occur. The chatter results in high total harmonic distortion (THD) output voltage of AC power source, and even deteriorates the stability of PMM. The FOA is therefore used to remove the chatter, and the FTCSF still preserves finite system-state convergence time. By combining FTCSF with FOA, the AC power source of PMM can yield good steady-state and transient performance. Experimental results are performed in support of the proposed technology.

Low Power Multi-Hop Networking Analysis in Intelligent Environments.

PubMed

Etxaniz, Josu; Aranguren, Gerardo

2017-05-19

Intelligent systems are driven by the latest technological advances in many different areas such as sensing, embedded systems, wireless communications or context recognition. This paper focuses on some of those areas. Concretely, the paper deals with wireless communications issues in embedded systems. More precisely, the paper combines the multi-hop networking with Bluetooth technology and a quality of service (QoS) metric, the latency. Bluetooth is a radio license-free worldwide communication standard that makes low power multi-hop wireless networking available. It establishes piconets (point-to-point and point-to-multipoint links) and scatternets (multi-hop networks). As a result, many Bluetooth nodes can be interconnected to set up ambient intelligent networks. Then, this paper presents the results of the investigation on multi-hop latency with park and sniff Bluetooth low power modes conducted over the hardware test bench previously implemented. In addition, the empirical models to estimate the latency of multi-hop communications over Bluetooth Asynchronous Connectionless Links (ACL) in park and sniff mode are given. The designers of devices and networks for intelligent systems will benefit from the estimation of the latency in Bluetooth multi-hop communications that the models provide.

Low Power Multi-Hop Networking Analysis in Intelligent Environments

PubMed Central

Etxaniz, Josu; Aranguren, Gerardo

2017-01-01

Intelligent systems are driven by the latest technological advances in many different areas such as sensing, embedded systems, wireless communications or context recognition. This paper focuses on some of those areas. Concretely, the paper deals with wireless communications issues in embedded systems. More precisely, the paper combines the multi-hop networking with Bluetooth technology and a quality of service (QoS) metric, the latency. Bluetooth is a radio license-free worldwide communication standard that makes low power multi-hop wireless networking available. It establishes piconets (point-to-point and point-to-multipoint links) and scatternets (multi-hop networks). As a result, many Bluetooth nodes can be interconnected to set up ambient intelligent networks. Then, this paper presents the results of the investigation on multi-hop latency with park and sniff Bluetooth low power modes conducted over the hardware test bench previously implemented. In addition, the empirical models to estimate the latency of multi-hop communications over Bluetooth Asynchronous Connectionless Links (ACL) in park and sniff mode are given. The designers of devices and networks for intelligent systems will benefit from the estimation of the latency in Bluetooth multi-hop communications that the models provide. PMID:28534847

A hybrid fuzzy logic and extreme learning machine for improving efficiency of circulating water systems in power generation plant

NASA Astrophysics Data System (ADS)

Aziz, Nur Liyana Afiqah Abdul; Siah Yap, Keem; Afif Bunyamin, Muhammad

2013-06-01

This paper presents a new approach of the fault detection for improving efficiency of circulating water system (CWS) in a power generation plant using a hybrid Fuzzy Logic System (FLS) and Extreme Learning Machine (ELM) neural network. The FLS is a mathematical tool for calculating the uncertainties where precision and significance are applied in the real world. It is based on natural language which has the ability of "computing the word". The ELM is an extremely fast learning algorithm for neural network that can completed the training cycle in a very short time. By combining the FLS and ELM, new hybrid model, i.e., FLS-ELM is developed. The applicability of this proposed hybrid model is validated in fault detection in CWS which may help to improve overall efficiency of power generation plant, hence, consuming less natural recourses and producing less pollutions.

29 CFR 1910.212 - General requirements for all machines.

Code of Federal Regulations, 2014 CFR

2014-07-01

..., DEPARTMENT OF LABOR OCCUPATIONAL SAFETY AND HEALTH STANDARDS Machinery and Machine Guarding § 1910.212...) Alligator shears. (d) Power presses. (e) Milling machines. (f) Power saws. (g) Jointers. (h) Portable power...) Anchoring fixed machinery. Machines designed for a fixed location shall be securely anchored to prevent...

29 CFR 1910.212 - General requirements for all machines.

Code of Federal Regulations, 2013 CFR

2013-07-01

..., DEPARTMENT OF LABOR OCCUPATIONAL SAFETY AND HEALTH STANDARDS Machinery and Machine Guarding § 1910.212...) Alligator shears. (d) Power presses. (e) Milling machines. (f) Power saws. (g) Jointers. (h) Portable power...) Anchoring fixed machinery. Machines designed for a fixed location shall be securely anchored to prevent...

29 CFR 1910.212 - General requirements for all machines.

Code of Federal Regulations, 2012 CFR

2012-07-01

..., DEPARTMENT OF LABOR OCCUPATIONAL SAFETY AND HEALTH STANDARDS Machinery and Machine Guarding § 1910.212...) Alligator shears. (d) Power presses. (e) Milling machines. (f) Power saws. (g) Jointers. (h) Portable power...) Anchoring fixed machinery. Machines designed for a fixed location shall be securely anchored to prevent...

Doubly fed induction machine

DOEpatents

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.

AC/DC Power Systems with Applications for future Lunar/Mars base and Crew Exploration Vehicle

NASA Technical Reports Server (NTRS)

Chowdhury, Badrul H.

2005-01-01

ABSTRACT The Power Systems branch at JSC faces a number of complex issues as it readies itself for the President's initiative on future space exploration beyond low earth orbit. Some of these preliminary issues - those dealing with electric power generation and distribution on board Mars-bound vehicle and that on Lunar and Martian surface may be summarized as follows: Type of prime mover - Because solar power may not be readily available on parts of the Lunar/Mars surface and also during the long duration flight to Mars, the primary source of power will most likely be nuclear power (Uranium fuel rods) with a secondary source of fuel cell (Hydrogen supply). The electric power generation source - With nuclear power being the main prime mover, the electric power generation source will most likely be an ac generator at a yet to be determined frequency. Thus, a critical issue is whether the generator should generate at constant or variable frequency. This will decide what type of generator to use - whether it is a synchronous machine, an asynchronous induction machine or a switched reluctance machine. The type of power distribution system - the distribution frequency, number of wires (3- wire, 4-wire or higher), and ac/dc hybridization. Building redundancy and fault tolerance in the generation and distribution sub-systems so that the system is safe; provides 100% availability to critical loads; continues to operate even with faulted sub-systems; and requires minimal maintenance. This report descril_es results of a summer faculty fellowship spent in the Power Systems Branch with the specific aim of investigating some of the lessons learned in electric power generation and usage from the terrestrial power systems industry, the aerospace industry as well as NASA's on-going missions so as to recommend novel surface and vehicle-based power systems architectures in support of future space exploration initiatives. A hybrid ac/dc architecture with source side and load side redundancies and including emergency generators on both ac and dc sides is proposed. The generation frequency is 400 Hz mostly because of the technology maturity at this frequency in the aerospace industry. Power will be distributed to several ac load distribution buses through solid state variable speed, constant frequency converters on the ac side. A segmented dc ring bus supplied from ac/dc converters and with the capability of connecting/disconnecting the segments will supply power to multiple de load distribution buses. The system will have the capability of reverse flow from dc to ac side in the case of an extreme emergency on the main ac generation side.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

Light-operated machines based on threaded molecular structures.

PubMed

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.

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

PubMed

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

2002-08-01

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

Energy management system for a rotary machine and method therefor

DOEpatents

Bowman, Michael John; Sinha, Gautam; Sheldon, Karl Edward

2004-11-09

In energy management system is provided for a power generating device having a working fluid intake in which the energy management system comprises an electrical dissipation device coupled to the power generating device and a dissipation device cooling system configured to direct a portion of a working fluid to the electrical dissipation device so as to provide thermal control to the electrical dissipation device.

Deep features for efficient multi-biometric recognition with face and ear images

NASA Astrophysics Data System (ADS)

Omara, Ibrahim; Xiao, Gang; Amrani, Moussa; Yan, Zifei; Zuo, Wangmeng

2017-07-01

Recently, multimodal biometric systems have received considerable research interest in many applications especially in the fields of security. Multimodal systems can increase the resistance to spoof attacks, provide more details and flexibility, and lead to better performance and lower error rate. In this paper, we present a multimodal biometric system based on face and ear, and propose how to exploit the extracted deep features from Convolutional Neural Networks (CNNs) on the face and ear images to introduce more powerful discriminative features and robust representation ability for them. First, the deep features for face and ear images are extracted based on VGG-M Net. Second, the extracted deep features are fused by using a traditional concatenation and a Discriminant Correlation Analysis (DCA) algorithm. Third, multiclass support vector machine is adopted for matching and classification. The experimental results show that the proposed multimodal system based on deep features is efficient and achieves a promising recognition rate up to 100 % by using face and ear. In addition, the results indicate that the fusion based on DCA is superior to traditional fusion.

Analytical expressions for maximum wind turbine average power in a Rayleigh wind regime

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

Carlin, P.W.

Average or expectation values for annual power of a wind turbine in a Rayleigh wind regime are calculated and plotted as a function of cut-out wind speed. This wind speed is expressed in multiples of the annual average wind speed at the turbine installation site. To provide a common basis for comparison of all real and imagined turbines, the Rayleigh-Betz wind machine is postulated. This machine is an ideal wind machine operating with the ideal Betz power coefficient of 0.593 in a Rayleigh probability wind regime. All other average annual powers are expressed in fractions of that power. Cases consideredmore » include: (1) an ideal machine with finite power and finite cutout speed, (2) real machines operating in variable speed mode at their maximum power coefficient, and (3) real machines operating at constant speed.« less

Predicting Power Outages Using Multi-Model Ensemble Forecasts

NASA Astrophysics Data System (ADS)

Cerrai, D.; Anagnostou, E. N.; Yang, J.; Astitha, M.

2017-12-01

Power outages affect every year millions of people in the United States, affecting the economy and conditioning the everyday life. An Outage Prediction Model (OPM) has been developed at the University of Connecticut for helping utilities to quickly restore outages and to limit their adverse consequences on the population. The OPM, operational since 2015, combines several non-parametric machine learning (ML) models that use historical weather storm simulations and high-resolution weather forecasts, satellite remote sensing data, and infrastructure and land cover data to predict the number and spatial distribution of power outages. A new methodology, developed for improving the outage model performances by combining weather- and soil-related variables using three different weather models (WRF 3.7, WRF 3.8 and RAMS/ICLAMS), will be presented in this study. First, we will present a performance evaluation of each model variable, by comparing historical weather analyses with station data or reanalysis over the entire storm data set. Hence, each variable of the new outage model version is extracted from the best performing weather model for that variable, and sensitivity tests are performed for investigating the most efficient variable combination for outage prediction purposes. Despite that the final variables combination is extracted from different weather models, this ensemble based on multi-weather forcing and multi-statistical model power outage prediction outperforms the currently operational OPM version that is based on a single weather forcing variable (WRF 3.7), because each model component is the closest to the actual atmospheric state.

Multi-model blending

DOEpatents

Hamann, Hendrik F.; Hwang, Youngdeok; van Kessel, Theodore G.; Khabibrakhmanov, Ildar K.; Muralidhar, Ramachandran

2016-10-18

A method and a system to perform multi-model blending are described. The method includes obtaining one or more sets of predictions of historical conditions, the historical conditions corresponding with a time T that is historical in reference to current time, and the one or more sets of predictions of the historical conditions being output by one or more models. The method also includes obtaining actual historical conditions, the actual historical conditions being measured conditions at the time T, assembling a training data set including designating the two or more set of predictions of historical conditions as predictor variables and the actual historical conditions as response variables, and training a machine learning algorithm based on the training data set. The method further includes obtaining a blended model based on the machine learning algorithm.

Nonlinear control of voltage source converters in AC-DC power system.

PubMed

Dash, P K; Nayak, N

2014-07-01

This paper presents the design of a robust nonlinear controller for a parallel AC-DC power system using a Lyapunov function-based sliding mode control (LYPSMC) strategy. The inputs for the proposed control scheme are the DC voltage and reactive power errors at the converter station and the active and reactive power errors at the inverter station of the voltage-source converter-based high voltage direct current transmission (VSC-HVDC) link. The stability and robust tracking of the system parameters are ensured by applying the Lyapunov direct method. Also the gains of the sliding mode control (SMC) are made adaptive using the stability conditions of the Lyapunov function. The proposed control strategy offers invariant stability to a class of systems having modeling uncertainties due to parameter changes and exogenous inputs. Comprehensive computer simulations are carried out to verify the proposed control scheme under several system disturbances like changes in short-circuit ratio, converter parametric changes, and faults on the converter and inverter buses for single generating system connected to the power grid in a single machine infinite-bus AC-DC network and also for a 3-machine two-area power system. Furthermore, a second order super twisting sliding mode control scheme has been presented in this paper that provides a higher degree of nonlinearity than the LYPSMC and damps faster the converter and inverter voltage and power oscillations. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Analysis of Even Harmonics Generation in an Isolated Electric Power System

NASA Astrophysics Data System (ADS)

Kanao, Norikazu; Hayashi, Yasuhiro; Matsuki, Junya

Harmonics bred from loads are mainly odd order because the current waveform has half-wave symmetry. Since the even harmonics are negligibly small, those are not generally measured in electric power systems. However, even harmonics were measured at a 500/275/154kV substation in Hokuriku Electric Power Company after removal of a transmission line fault. The even harmonics caused malfunctions of protective digital relays because the relays used 4th harmonics at the input filter as automatic supervisory signal. This paper describes the mechanism of generation of the even harmonics by comparing measured waveforms with ATP-EMTP simulation results. As a result of analysis, it is cleared that even harmonics are generated by three causes. The first cause is a magnetizing current of transformers due to flux deviation by DC component of a fault current. The second one is due to harmonic conversion of a synchronous machine which generates even harmonics when direct current component or even harmonic current flow into the machine. The third one is that increase of harmonic impedance due to an isolated power system produces harmonic voltages. The design of the input filter of protective digital relays should consider even harmonics generation in an isolated power system.

Technology Roadmap Instrumentation, Control, and Human-Machine Interface to Support DOE Advanced Nuclear Energy Programs

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

Donald D Dudenhoeffer; Burce P Hallbert

Instrumentation, Controls, and Human-Machine Interface (ICHMI) technologies are essential to ensuring delivery and effective operation of optimized advanced Generation IV (Gen IV) nuclear energy systems. In 1996, the Watts Bar I nuclear power plant in Tennessee was the last U.S. nuclear power plant to go on line. It was, in fact, built based on pre-1990 technology. Since this last U.S. nuclear power plant was designed, there have been major advances in the field of ICHMI systems. Computer technology employed in other industries has advanced dramatically, and computing systems are now replaced every few years as they become functionally obsolete. Functionalmore » obsolescence occurs when newer, more functional technology replaces or supersedes an existing technology, even though an existing technology may well be in working order.Although ICHMI architectures are comprised of much of the same technology, they have not been updated nearly as often in the nuclear power industry. For example, some newer Personal Digital Assistants (PDAs) or handheld computers may, in fact, have more functionality than the 1996 computer control system at the Watts Bar I plant. This illustrates the need to transition and upgrade current nuclear power plant ICHMI technologies.« less

Detection of Real Flaw using Uniform Eddy Current Multi-probe

NASA Astrophysics Data System (ADS)

Fukuoka, Katsuhiro; Hashimoto, Mitsuo

The establishment of the nondestructive inspection technology with plant structures has been stimulated by the recent occurrence of cracks in the nuclear power plant structures. In this research, a uniform eddy current multi-probe to apply to the complex structure and inspect the cracks at high-speed data acquisition was developed. Pick-up coils of the developed probe were arranged on a flexible printed circuit board. This probe was able to obtain clear signal for an EDM (electro-discharge machining) slit with 0.5 mm depth and distinguish EDM slits arranged at 2 mm intervals. It was confirmed that the SCC (stress corrosion cracking) of real flaw was able to be detected with developed uniform eddy current multi-probe by using the ferrite core for the exciting coil and considering the impedance matching of the exciting coil and the flaw detection device.

MARTI: man-machine animation real-time interface

NASA Astrophysics Data System (ADS)

Jones, Christian M.; Dlay, Satnam S.

1997-05-01

The research introduces MARTI (man-machine animation real-time interface) for the realization of natural human-machine interfacing. The system uses simple vocal sound-tracks of human speakers to provide lip synchronization of computer graphical facial models. We present novel research in a number of engineering disciplines, which include speech recognition, facial modeling, and computer animation. This interdisciplinary research utilizes the latest, hybrid connectionist/hidden Markov model, speech recognition system to provide very accurate phone recognition and timing for speaker independent continuous speech, and expands on knowledge from the animation industry in the development of accurate facial models and automated animation. The research has many real-world applications which include the provision of a highly accurate and 'natural' man-machine interface to assist user interactions with computer systems and communication with one other using human idiosyncrasies; a complete special effects and animation toolbox providing automatic lip synchronization without the normal constraints of head-sets, joysticks, and skilled animators; compression of video data to well below standard telecommunication channel bandwidth for video communications and multi-media systems; assisting speech training and aids for the handicapped; and facilitating player interaction for 'video gaming' and 'virtual worlds.' MARTI has introduced a new level of realism to man-machine interfacing and special effect animation which has been previously unseen.

Diagnosis of breast masses from dynamic contrast-enhanced and diffusion-weighted MR: a machine learning approach.

PubMed

Cai, Hongmin; Peng, Yanxia; Ou, Caiwen; Chen, Minsheng; Li, Li

2014-01-01

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is increasingly used for breast cancer diagnosis as supplementary to conventional imaging techniques. Combining of diffusion-weighted imaging (DWI) of morphology and kinetic features from DCE-MRI to improve the discrimination power of malignant from benign breast masses is rarely reported. The study comprised of 234 female patients with 85 benign and 149 malignant lesions. Four distinct groups of features, coupling with pathological tests, were estimated to comprehensively characterize the pictorial properties of each lesion, which was obtained by a semi-automated segmentation method. Classical machine learning scheme including feature subset selection and various classification schemes were employed to build prognostic model, which served as a foundation for evaluating the combined effects of the multi-sided features for predicting of the types of lesions. Various measurements including cross validation and receiver operating characteristics were used to quantify the diagnostic performances of each feature as well as their combination. Seven features were all found to be statistically different between the malignant and the benign groups and their combination has achieved the highest classification accuracy. The seven features include one pathological variable of age, one morphological variable of slope, three texture features of entropy, inverse difference and information correlation, one kinetic feature of SER and one DWI feature of apparent diffusion coefficient (ADC). Together with the selected diagnostic features, various classical classification schemes were used to test their discrimination power through cross validation scheme. The averaged measurements of sensitivity, specificity, AUC and accuracy are 0.85, 0.89, 90.9% and 0.93, respectively. Multi-sided variables which characterize the morphological, kinetic, pathological properties and DWI measurement of ADC can dramatically improve the discriminatory power of breast lesions.

Wind-Friendly Flexible Ramping Product Design in Multi-Timescale Power System Operations

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

Cui, Mingjian; Zhang, Jie; Wu, Hongyu

With increasing wind power penetration in the electricity grid, system operators are recognizing the need for additional flexibility, and some are implementing new ramping products as a type of ancillary service. However, wind is generally thought of as causing the need for ramping services, not as being a potential source for the service. In this paper, a multi-timescale unit commitment and economic dispatch model is developed to consider the wind power ramping product (WPRP). An optimized swinging door algorithm with dynamic programming is applied to identify and forecast wind power ramps (WPRs). Designed as positive characteristics of WPRs, the WPRPmore » is then integrated into the multi-timescale dispatch model that considers new objective functions, ramping capacity limits, active power limits, and flexible ramping requirements. Numerical simulations on the modified IEEE 118-bus system show the potential effectiveness of WPRP in increasing the economic efficiency of power system operations with high levels of wind power penetration. It is found that WPRP not only reduces the production cost by using less ramping reserves scheduled by conventional generators, but also possibly enhances the reliability of power system operations. Moreover, wind power forecasts play an important role in providing high-quality WPRP service.« less

Fault-Tolerant, Real-Time, Multi-Core Computer System

NASA Technical Reports Server (NTRS)

Gostelow, Kim P.

2012-01-01

A document discusses a fault-tolerant, self-aware, low-power, multi-core computer for space missions with thousands of simple cores, achieving speed through concurrency. The proposed machine decides how to achieve concurrency in real time, rather than depending on programmers. The driving features of the system are simple hardware that is modular in the extreme, with no shared memory, and software with significant runtime reorganizing capability. The document describes a mechanism for moving ongoing computations and data that is based on a functional model of execution. Because there is no shared memory, the processor connects to its neighbors through a high-speed data link. Messages are sent to a neighbor switch, which in turn forwards that message on to its neighbor until reaching the intended destination. Except for the neighbor connections, processors are isolated and independent of each other. The processors on the periphery also connect chip-to-chip, thus building up a large processor net. There is no particular topology to the larger net, as a function at each processor allows it to forward a message in the correct direction. Some chip-to-chip connections are not necessarily nearest neighbors, providing short cuts for some of the longer physical distances. The peripheral processors also provide the connections to sensors, actuators, radios, science instruments, and other devices with which the computer system interacts.

Artificial Intelligence in Speech Understanding: Two Applications at C.R.I.N.

ERIC Educational Resources Information Center

Carbonell, N.; And Others

1986-01-01

This article explains how techniques of artificial intelligence are applied to expert systems for acoustic-phonetic decoding, phonological interpretation, and multi-knowledge sources for man-machine dialogue implementation. The basic ideas are illustrated with short examples. (Author/JDH)

Improving Operational System Performance of Internet of Things (IoT) in Indonesia Telecomunication Company

NASA Astrophysics Data System (ADS)

Dachyar, M.; Risky, S. A.

2014-06-01

Telecommunications company have to improve their business performance despite of the increase customers every year. In Indonesia, the telecommunication company have provided best services, improving operational systems by designing a framework for operational systems of the Internet of Things (IoT) other name of Machine to Machine (M2M). This study was conducted with expert opinion which further processed by the Analytic Hierarchy Process (AHP) to obtain important factor for organizations operational systems, and the Interpretive Structural Modeling (ISM) to determine factors of organization which found drives the biggest power. This study resulted, the greatest weight of SLA & KPI handling problems. The M2M current dashboard and current M2M connectivity have power to affect other factors and has important function for M2M operations roomates system which can be effectively carried out.

Enhanced automated spiral bevel gear inspection

NASA Technical Reports Server (NTRS)

Frint, Harold K.; Glasow, Warren

1992-01-01

Presented here are the results of a manufacturing and technology program to define, develop, and evaluate an enhanced inspection system for spiral bevel gears. The method uses a multi-axis coordinate measuring machine which maps the working surface of the tooth and compares it with nominal reference values stored in the machine's computer. The enhanced technique features a means for automatically calculating corrective grinding machine settings, involving both first and second order changes, to control the tooth profile to within specified tolerance limits. This enhanced method eliminates the subjective decision making involved in the tooth patterning method, still in use today, which compares contract patterns obtained when the gear is set to run under light load in a rolling test machine. It produces a higher quality gear with significant inspection time and cost savings.

A comparative study of machine learning models for ethnicity classification

NASA Astrophysics Data System (ADS)

Trivedi, Advait; Bessie Amali, D. Geraldine

2017-11-01

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

Precision molding of advanced glass optics: innovative production technology for lens arrays and free form optics

NASA Astrophysics Data System (ADS)

Pongs, Guido; Bresseler, Bernd; Bergs, Thomas; Menke, Gert

2012-10-01

Today isothermal precision molding of imaging glass optics has become a widely applied and integrated production technology in the optical industry. Especially in consumer electronics (e.g. digital cameras, mobile phones, Blu-ray) a lot of optical systems contain rotationally symmetrical aspherical lenses produced by precision glass molding. But due to higher demands on complexity and miniaturization of optical elements the established process chain for precision glass molding is not sufficient enough. Wafer based molding processes for glass optics manufacturing become more and more interesting for mobile phone applications. Also cylindrical lens arrays can be used in high power laser systems. The usage of unsymmetrical free-form optics allows an increase of efficiency in optical laser systems. Aixtooling is working on different aspects in the fields of mold manufacturing technologies and molding processes for extremely high complex optical components. In terms of array molding technologies, Aixtooling has developed a manufacturing technology for the ultra-precision machining of carbide molds together with European partners. The development covers the machining of multi lens arrays as well as cylindrical lens arrays. The biggest challenge is the molding of complex free-form optics having no symmetrical axis. A comprehensive CAD/CAM data management along the entire process chain is essential to reach high accuracies on the molded lenses. Within a national funded project Aixtooling is working on a consistent data handling procedure in the process chain for precision molding of free-form optics.

Technical Challenges and Potential Solutions for Cross-Country Multi-Terminal Superconducting DC Power Cables

NASA Astrophysics Data System (ADS)

Al-Taie, A.; Graber, L.; Pamidi, S. V.

2017-12-01

Opportunities for applications of high temperature superconducting (HTS) DC power cables for long distance power transmission in increasing the reliability of the electric power grid and to enable easier integration of distributed renewable sources into the grid are discussed. The gaps in the technology developments both in the superconducting cable designs and cryogenic systems as well as power electronic devices are identified. Various technology components in multi-terminal high voltage DC power transmission networks and the available options are discussed. The potential of ongoing efforts in the development of superconducting DC transmission systems is discussed.

Image processing and machine learning for fully automated probabilistic evaluation of medical images.

PubMed

Sajn, Luka; Kukar, Matjaž

2011-12-01

The paper presents results of our long-term study on using image processing and data mining methods in a medical imaging. Since evaluation of modern medical images is becoming increasingly complex, advanced analytical and decision support tools are involved in integration of partial diagnostic results. Such partial results, frequently obtained from tests with substantial imperfections, are integrated into ultimate diagnostic conclusion about the probability of disease for a given patient. We study various topics such as improving the predictive power of clinical tests by utilizing pre-test and post-test probabilities, texture representation, multi-resolution feature extraction, feature construction and data mining algorithms that significantly outperform medical practice. Our long-term study reveals three significant milestones. The first improvement was achieved by significantly increasing post-test diagnostic probabilities with respect to expert physicians. The second, even more significant improvement utilizes multi-resolution image parametrization. Machine learning methods in conjunction with the feature subset selection on these parameters significantly improve diagnostic performance. However, further feature construction with the principle component analysis on these features elevates results to an even higher accuracy level that represents the third milestone. With the proposed approach clinical results are significantly improved throughout the study. The most significant result of our study is improvement in the diagnostic power of the whole diagnostic process. Our compound approach aids, but does not replace, the physician's judgment and may assist in decisions on cost effectiveness of tests. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Hybrid Power Management for Office Equipment

NASA Astrophysics Data System (ADS)

Gingade, Ganesh P.

Office machines (such as printers, scanners, fax, and copiers) can consume significant amounts of power. Few studies have been devoted to power management of office equipment. Most office machines have sleep modes to save power. Power management of these machines are usually timeout-based: a machine sleeps after being idle long enough. Setting the timeout duration can be difficult: if it is too long, the machine wastes power during idleness. If it is too short, the machine sleeps too soon and too often--the wakeup delay can significantly degrade productivity. Thus, power management is a tradeoff between saving energy and keeping short response time. Many power management policies have been published and one policy may outperform another in some scenarios. There is no definite conclusion which policy is always better. This thesis describes two methods for office equipment power management. The first method adaptively reduces power based on a constraint of the wakeup delay. The second method is a hybrid with multiple candidate policies and it selects the most appropriate power management policy. Using six months of request traces from 18 different offices, we demonstrate that the hybrid policy outperforms individual policies. We also discover that power management based on business hours does not produce consistent energy savings.

Automatic 3D power line reconstruction of multi-angular imaging power line inspection system

NASA Astrophysics Data System (ADS)

Zhang, Wuming; Yan, Guangjian; Wang, Ning; Li, Qiaozhi; Zhao, Wei

2007-06-01

We develop a multi-angular imaging power line inspection system. Its main objective is to monitor the relative distance between high voltage power line and around objects, and alert if the warning threshold is exceeded. Our multi-angular imaging power line inspection system generates DSM of the power line passage, which comprises ground surface and ground objects, for example trees and houses, etc. For the purpose of revealing the dangerous regions, where ground objects are too close to the power line, 3D power line information should be extracted at the same time. In order to improve the automation level of extraction, reduce labour costs and human errors, an automatic 3D power line reconstruction method is proposed and implemented. It can be achieved by using epipolar constraint and prior knowledge of pole tower's height. After that, the proper 3D power line information can be obtained by space intersection using found homologous projections. The flight experiment result shows that the proposed method can successfully reconstruct 3D power line, and the measurement accuracy of the relative distance satisfies the user requirement of 0.5m.

A Method for Optimal Load Dispatch of a Multi-zone Power System with Zonal Exchange Constraints

NASA Astrophysics Data System (ADS)

Hazarika, Durlav; Das, Ranjay

2018-04-01

This paper presented a method for economic generation scheduling of a multi-zone power system having inter zonal operational constraints. For this purpose, the generator rescheduling for a multi area power system having inter zonal operational constraints has been represented as a two step optimal generation scheduling problem. At first, the optimal generation scheduling has been carried out for the zone having surplus or deficient generation with proper spinning reserve using co-ordination equation. The power exchange required for the deficit zones and zones having no generation are estimated based on load demand and generation for the zone. The incremental transmission loss formulas for the transmission lines participating in the power transfer process among the zones are formulated. Using these, incremental transmission loss expression in co-ordination equation, the optimal generation scheduling for the zonal exchange has been determined. Simulation is carried out on IEEE 118 bus test system to examine the applicability and validity of the method.

Intelligent Vehicle Power Management Using Machine Learning and Fuzzy Logic

DTIC Science & Technology

2008-06-01

batteries of similar physical size. An ultracapacitor can receive regenerative energy and give power during peak periods. Moreno et al. proposed to...use an ultracapacitor as an auxiliary energy system in combination with a primary source that is unable to accept energy from the regenerative ... braking [22]. There are other power sources that are being considered in HEV research [20-22] and future vehicle systems may use combinations of

Wireless Monitoring of Induction Machine Rotor Physical Variables

PubMed Central

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.

PubMed

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.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

The Knife Machine. Module 15.

ERIC Educational Resources Information Center

South Carolina State Dept. of Education, Columbia. Office of Vocational Education.

This module on the knife machine, one in a series dealing with industrial sewing machines, their attachments, and operation, covers one topic: performing special operations on the knife machine (a single needle or multi-needle machine which sews and cuts at the same time). These components are provided: an introduction, directions, an objective,…

Management Perspectives Pertaining to Root Cause Analyses of Nunn-McCurdy Breaches. Volume 4

DTIC Science & Technology

2013-01-01

the FY2012 NDAA, the Army revised its initial budget request, allocating money from the purchase of new M2 .50 caliber machine guns to the...Quick-change machine gun barrel Explosive reactive armor Linear demolition charge system Full width, surface mine ploughs On-board vehicle power...Quantity Oversight of ACAT II Programs 45 for a restart to the program citing a “critical shortage of serviceable machine guns for our Soldiers who

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

PubMed

Coates, Ewan; Blaszczynski, Alex

2013-12-01

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

Self-powered vision electronic-skin basing on piezo-photodetecting Ppy/PVDF pixel-patterned matrix for mimicking vision.

PubMed

Han, Wuxiao; Zhang, Linlin; He, Haoxuan; Liu, Hongmin; Xing, Lili; Xue, Xinyu

2018-06-22

The development of multifunctional electronic-skin that establishes human-machine interfaces, enhances perception abilities or has other distinct biomedical applications is the key to the realization of artificial intelligence. In this paper, a new self-powered (battery-free) flexible vision electronic-skin has been realized from pixel-patterned matrix of piezo-photodetecting PVDF/Ppy film. The electronic-skin under applied deformation can actively output piezoelectric voltage, and the outputting signal can be significantly influenced by UV illumination. The piezoelectric output can act as both the photodetecting signal and electricity power. The reliability is demonstrated over 200 light on-off cycles. The sensing unit matrix of 6 × 6 pixels on the electronic-skin can realize image recognition through mapping multi-point UV stimuli. This self-powered vision electronic-skin that simply mimics human retina may have potential application in vision substitution.

Self-powered vision electronic-skin basing on piezo-photodetecting Ppy/PVDF pixel-patterned matrix for mimicking vision

NASA Astrophysics Data System (ADS)

Han, Wuxiao; Zhang, Linlin; He, Haoxuan; Liu, Hongmin; Xing, Lili; Xue, Xinyu

2018-06-01

The development of multifunctional electronic-skin that establishes human-machine interfaces, enhances perception abilities or has other distinct biomedical applications is the key to the realization of artificial intelligence. In this paper, a new self-powered (battery-free) flexible vision electronic-skin has been realized from pixel-patterned matrix of piezo-photodetecting PVDF/Ppy film. The electronic-skin under applied deformation can actively output piezoelectric voltage, and the outputting signal can be significantly influenced by UV illumination. The piezoelectric output can act as both the photodetecting signal and electricity power. The reliability is demonstrated over 200 light on–off cycles. The sensing unit matrix of 6 × 6 pixels on the electronic-skin can realize image recognition through mapping multi-point UV stimuli. This self-powered vision electronic-skin that simply mimics human retina may have potential application in vision substitution.

Fluidics and heat generation of Alcon Infiniti and Legacy, Bausch & Lomb Millennium, and advanced medical optics sovereign phacoemulsification systems.

PubMed

Floyd, Michael S; Valentine, Jeremy R; Olson, Randall J

2006-09-01

To study heat generation, vacuum, and flow characteristics of the Alcon Infiniti and Bausch & Lomb Millennium with results compared with the Alcon Legacy and advanced medical optics (AMO) Sovereign machines previously studied. Experimental study. Heat generation with continuous ultrasound was determined with and without a 200-g weight. Flow and vacuum were determined from 12 to 40-ml/min in 2-ml/min steps. The impact of a STAAR Cruise Control was also tested. Millennium created the most heat/20% of power (5.67 +/- 0.51 degrees C unweighted and 6.80 +/- 0.80 degrees C weighted), followed by Sovereign (4.59 +/- 0.70 degrees C unweighted and 5.65 +/- 0.72 degrees C weighted), Infiniti (2.79 +/- 0.62 degrees C unweighted and 3.96 +/- 0.31 degrees C weighted), and Legacy (1.99 +/- 0.49 degrees C unweighted and 4.27 +/- 0.76 degrees C weighted; P < .0001 for all comparisons between machines except Infiniti vs Legacy, both weighted). Flow studies revealed that Millennium Peristaltic was 17% less than indicated (P < .0001 to all other machines), and all other machines were within 3.5% of indicated. Cruise Control decreased flow by 4.1% (P < .0001 for same machine without it). Millennium Venturi had the greatest vacuum (81% more than the least Sovereign; P < .0001), and Cruise Control increased vacuum in a peristaltic machine 35% more than the Venturi system (P < .0001). Percent power is not consistent in regard to heat generation, however, flow was accurate for all machines except Millennium Peristaltic. Restriction with Cruise Control elevates unoccluded vacuum to levels greater than the Venturi system tested.

Multi-Point Thomson Scattering Diagnostic for the Helicity Injected Torus

NASA Astrophysics Data System (ADS)

Liptac, J. E.; Smith, R. J.; Hoffman, C. S.; Jarboe, T. R.; Nelson, B. A.; Leblanc, B. P.; Phillips, P.

1999-11-01

The multi-point Thomson scattering system on the Helicity Injected Torus--II can determine electron temperature and density at 11 radial positions at a single time during the plasma discharge. The system includes components on loan from both PPPL and from the University of Texas. The collection optics and Littrow spectrometer from Princeton, and the 1 GW laser and multi-anode microchannel plate detector from Texas have been integrated into a compact structure, creating a mobile and reliable diagnostic. The mobility of the system allows alignment to occur in a room adjacent to the experiment, greatly reducing the disturbance to normal machine operation. The four main parts of the Thomson scattering system, namely, the laser, the beam line, the collection optics, and the mobile structure are presented and discussed.

The network and transmission of based on the principle of laser multipoint communication

NASA Astrophysics Data System (ADS)

Fu, Qiang; Liu, Xianzhu; Jiang, Huilin; Hu, Yuan; Jiang, Lun

2014-11-01

Space laser communication is the perfectly choose to the earth integrated information backbone network in the future. This paper introduces the structure of the earth integrated information network that is a large capacity integrated high-speed broadband information network, a variety of communications platforms were densely interconnected together, such as the land, sea, air and deep air users or aircraft, the technologies of the intelligent high-speed processing, switching and routing were adopt. According to the principle of maximum effective comprehensive utilization of information resources, get accurately information, fast processing and efficient transmission through inter-satellite, satellite earth, sky and ground station and other links. Namely it will be a space-based, air-based and ground-based integrated information network. It will be started from the trends of laser communication. The current situation of laser multi-point communications were expounded, the transmission scheme of the dynamic multi-point between wireless laser communication n network has been carefully studied, a variety of laser communication network transmission schemes the corresponding characteristics and scope described in detail , described the optical multiplexer machine that based on the multiport form of communication is applied to relay backbone link; the optical multiplexer-based on the form of the segmentation receiver field of view is applied to small angle link, the optical multiplexer-based form of three concentric spheres structure is applied to short distances, motorized occasions, and the multi-point stitching structure based on the rotation paraboloid is applied to inter-satellite communications in detail. The multi-point laser communication terminal apparatus consist of the transmitting and receiving antenna, a relay optical system, the spectroscopic system, communication system and communication receiver transmitter system. The communication forms of optical multiplexer more than four goals or more, the ratio of received power and volume weight will be Obvious advantages, and can track multiple moving targets in flexible.It would to provide reference for the construction of earth integrated information networks.

Distributed state machine supervision for long-baseline gravitational-wave detectors

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

Rollins, Jameson Graef, E-mail: jameson.rollins@ligo.org

The Laser Interferometer Gravitational-wave Observatory (LIGO) consists of two identical yet independent, widely separated, long-baseline gravitational-wave detectors. Each Advanced LIGO detector consists of complex optical-mechanical systems isolated from the ground by multiple layers of active seismic isolation, all controlled by hundreds of fast, digital, feedback control systems. This article describes a novel state machine-based automation platform developed to handle the automation and supervisory control challenges of these detectors. The platform, called Guardian, consists of distributed, independent, state machine automaton nodes organized hierarchically for full detector control. User code is written in standard Python and the platform is designed to facilitatemore » the fast-paced development process associated with commissioning the complicated Advanced LIGO instruments. While developed specifically for the Advanced LIGO detectors, Guardian is a generic state machine automation platform that is useful for experimental control at all levels, from simple table-top setups to large-scale multi-million dollar facilities.« less

Automation of the CCTV-mediated detection of individuals illegally carrying firearms: combining psychological and technological approaches

NASA Astrophysics Data System (ADS)

Darker, Iain T.; Kuo, Paul; Yang, Ming Yuan; Blechko, Anastassia; Grecos, Christos; Makris, Dimitrios; Nebel, Jean-Christophe; Gale, Alastair G.

2009-05-01

Findings from the current UK national research programme, MEDUSA (Multi Environment Deployable Universal Software Application), are presented. MEDUSA brings together two approaches to facilitate the design of an automatic, CCTV-based firearm detection system: psychological-to elicit strategies used by CCTV operators; and machine vision-to identify key cues derived from camera imagery. Potentially effective human- and machine-based strategies have been identified; these will form elements of the final system. The efficacies of these algorithms have been tested on staged CCTV footage in discriminating between firearms and matched distractor objects. Early results indicate the potential for this combined approach.

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

PubMed

Aungkulanon, Pasura; Luangpaiboon, Pongchanun

2016-01-01

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

Benefits of 20 kHz PMAD in a nuclear space station

NASA Technical Reports Server (NTRS)

Sundberg, Gale R.

1987-01-01

Compared to existing systems, high frequency ac power provides higher efficiency, lower cost, and improved safety benefits. The 20 kHz power system has exceptional flexibility, is inherently user friendly, and is compatible with all types of energy sources; photovoltaic, solar dynamic, rotating machines and nuclear. A 25 kW, 20 kHz ac power distribution system testbed was recently (1986) developed. The testbed possesses maximum flexibility, versatility, and transparency to user technology while maintaining high efficiency, low mass, and reduced volume. Several aspects of the 20 kHz power management and distribution (PMAD) system that have particular benefits for a nuclear power Space Station are discussed.

Molecular Dynamics Simulation of a Multi-Walled Carbon Nanotube Based Gear

NASA Technical Reports Server (NTRS)

Han, Jie; Globus, Al; Srivastava, Deepak; Chancellor, Marisa K. (Technical Monitor)

1997-01-01

We used molecular dynamics to investigate the properties of a multi-walled carbon nanotube based gear. Previous work computationally suggested that molecular gears fashioned from (14,0) single-walled carbon nanotubes operate well at 50-100 gigahertz. The gears were formed from nanotubes with teeth added via a benzyne reaction known to occur with C60. A modified, parallelized version of Brenner's potential was used to model interatomic forces within each molecule. A Leonard-Jones 6-12 potential was used for forces between molecules. The gear in this study was based on the smallest multi-walled nanotube supported by some experimental evidence. Each gear was a (52,0) nanotube surrounding a (37,10) nanotube with approximate 20.4 and 16,8 A radii respectively. These sizes were chosen to be consistent with inter-tube spacing observed by and were slightly larger than graphite inter-layer spacings. The benzyne teeth were attached via 2+4 cycloaddition to exterior of the (52,0) tube. 2+4 bonds were used rather than the 2+2 bonds observed by Hoke since 2+4 bonds are preferred by naphthalene and quantum calculations by Jaffe suggest that 2+4 bonds are preferred on carbon nanotubes of sufficient diameter. One gear was 'powered' by forcing the atoms near the end of the outside buckytube to rotate to simulate a motor. A second gear was allowed to rotate by keeping the atoms near the end of its outside buckytube on a cylinder. The ends of both gears were constrained to stay in an approximately constant position relative to each other, simulating a casing, to insure that the gear teeth meshed. The stiff meshing aromatic gear teeth transferred angular momentum from the powered gear to the driven gear. The simulation was performed in a vacuum and with a software thermostat. Preliminary results suggest that the powered gear had trouble turning the driven gear without slip. The larger radius and greater mass of these gears relative to the (14,0) gears previously studied requires a smaller rotation rate and multiple rows of teeth to avoid excessive force on the gear teeth resulting, in slip and failure of the driven gear to turn. We hope that studies such as these will eventually lead to synthesis of components that can be assembled into atomically precise fullerene machines. These machines, in turn, may someday be used in machine-phase fullerene materials with remarkable properties.

Satisloh centering technology developments past to present

NASA Astrophysics Data System (ADS)

Leitz, Ernst Michael; Moos, Steffen

2015-10-01

The centering of an optical lens is the grinding of its edge profile or contour in relationship to its optical axis. This is required to ensure that the lens vertex and radial centers are accurately positioned within an optical system. Centering influences the imaging performance and contrast of an optical system. Historically, lens centering has been a purely manual process. Along its 62 years of assembling centering machines, Satisloh introduced several technological milestones to improve the accuracy and quality of this process. During this time more than 2.500 centering machines were assembled. The development went from bell clamping and diamond grinding to Laser alignment, exchange chuckor -spindle systems, to multi axis CNC machines with integrated metrology and automatic loading systems. With the new centering machine C300, several improvements for the clamping and grinding process were introduced. These improvements include a user friendly software to support the operator, a coolant manifold and "force grinding" technology to ensure excellent grinding quality and process stability. They also include an air bearing directly driven centering spindle to provide a large working range of lenses made of all optical materials and diameters from below 10 mm to 300 mm. The clamping force can be programmed between 7 N and 1200 N to safely center lenses made of delicate materials. The smaller C50 centering machine for lenses below 50 mm diameter is available with an optional CNC loading system for automated production.

Investigation of the shape transferability of nanoscale multi-tip diamond tools in the diamond turning of nanostructures

NASA Astrophysics Data System (ADS)

Luo, Xichun; Tong, Zhen; Liang, Yingchun

2014-12-01

In this article, the shape transferability of using nanoscale multi-tip diamond tools in the diamond turning for scale-up manufacturing of nanostructures has been demonstrated. Atomistic multi-tip diamond tool models were built with different tool geometries in terms of the difference in the tip cross-sectional shape, tip angle, and the feature of tool tip configuration, to determine their effect on the applied forces and the machined nano-groove geometries. The quality of machined nanostructures was characterized by the thickness of the deformed layers and the dimensional accuracy achieved. Simulation results show that diamond turning using nanoscale multi-tip tools offers tremendous shape transferability in machining nanostructures. Both periodic and non-periodic nano-grooves with different cross-sectional shapes can be successfully fabricated using the multi-tip tools. A hypothesis of minimum designed ratio of tool tip distance to tip base width (L/Wf) of the nanoscale multi-tip diamond tool for the high precision machining of nanostructures was proposed based on the analytical study of the quality of the nanostructures fabricated using different types of the multi-tip tools. Nanometric cutting trials using nanoscale multi-tip diamond tools (different in L/Wf) fabricated by focused ion beam (FIB) were then conducted to verify the hypothesis. The investigations done in this work imply the potential of using the nanoscale multi-tip diamond tool for the deterministic fabrication of period and non-periodic nanostructures, which opens up the feasibility of using the process as a versatile manufacturing technique in nanotechnology.

Understanding Power Electronics and Electrical Machines in Multidisciplinary Wind Energy Conversion System Courses

ERIC Educational Resources Information Center

Duran, M. J.; Barrero, F.; Pozo-Ruz, A.; Guzman, F.; Fernandez, J.; Guzman, H.

2013-01-01

Wind energy conversion systems (WECS) nowadays offer an extremely wide range of topologies, including various different types of electrical generators and power converters. Wind energy is also an application of great interest to students and with a huge potential for engineering employment. Making WECS the main center of interest when teaching…

A New Clinical HIFU System (Teleson II)

NASA Astrophysics Data System (ADS)

Ma, Yixin; Symonds-Tayler, Richard; Rivens, Ian H.; ter Haar, Gail R.

2007-05-01

Previous clinical trials with our first prototype HIFU system (Teleson I) for the treatment of liver tumors, demonstrated a major challenge to be treatment of those tumors located behind the ribs. We have designed a new multi-element transducer for rib sparing. Initial simulation and experimental results (using a single channel power amplifier) are very encouraging. A new clinical HIFU system which can drive the multi-element transducer and control each channel independently is being designed and constructed. This second version of a clinical prototype HIFU system consists of a 3D motorised gantry, a multi-channel signal generator, a multi-channel power amplifier, a user interface PC, an embedded controller and auxiliary circuits for real-time interleaving/synchronization control and a to-be-implemented safety monitoring and data logging unit. For multi-element transducers, each element can be individually switched on and off for rib sparing, and phase and amplitude modulated for potential phased array applications. The multi-channel power amplifier can be switched on/off very rapidly at required intervals to interleave with ultrasound B-Scan imaging for HIFU monitoring or radiation force elastography imaging via a dedicated interleaving/timing module. The gantry movement can also be synchronised with power amplifier on/off and phase/amplitude updating for lesion generation under a wide variety of conditions including single lesions, lesion arrays and lesions "tracks" created whilst translating the active transducer. Results from testing the system using excised tissue will be presented.

A fiber optic multi-stress monitoring system for power transformer

NASA Astrophysics Data System (ADS)

Kim, Dae-gil; Sampath, Umesh; Kim, Hyunjin; Song, Minho

2017-04-01

A fiber-optic multi-stress monitoring system which uses 4 FBG sensors and a fiber-optic mandrel acoustic emission sensor is proposed. FBG sensors and a mandrel sensor measure different types of stresses occurring in electrical power transformer, such as temperature and acoustic signals. The sensor system uses single broadband light source to address the outputs of both sensors using single fiber-optic circuitry. An athermal-packaged FBG is used to supply quasi-coherent light for the Sagnac interferometer demodulation which processes the mandrel sensor output. The proposed sensor system could simplify the optical circuit for the multi-stress measurements and enhance the cost-effectiveness of the sensor system.

The use of multi criteria analysis to compare the operating scenarios of the hybrid generation system of wind turbines, photovoltaic modules and a fuel cell

NASA Astrophysics Data System (ADS)

Ceran, Bartosz

2017-11-01

The paper presents the results of the use of multi-criteria analysis to compare hybrid power generation system collaboration scenarios (HSW) consisting of wind turbines, solar panels and energy storage electrolyzer - PEM type fuel cell with electricity system. The following scenarios were examined: the base S-I-hybrid system powers the off-grid mode receiver, S-II, S-III, S-IV scenarios-electricity system covers 25%, 50%, 75% of energy demand by the recipient. The effect of weights of the above-mentioned criteria on the final result of the multi-criteria analysis was examined.

Dynamic Voltage-Frequency and Workload Joint Scaling Power Management for Energy Harvesting Multi-Core WSN Node SoC

PubMed Central

Li, Xiangyu; Xie, Nijie; Tian, Xinyue

2017-01-01

This paper proposes a scheduling and power management solution for energy harvesting heterogeneous multi-core WSN node SoC such that the system continues to operate perennially and uses the harvested energy efficiently. The solution consists of a heterogeneous multi-core system oriented task scheduling algorithm and a low-complexity dynamic workload scaling and configuration optimization algorithm suitable for light-weight platforms. Moreover, considering the power consumption of most WSN applications have the characteristic of data dependent behavior, we introduce branches handling mechanism into the solution as well. The experimental result shows that the proposed algorithm can operate in real-time on a lightweight embedded processor (MSP430), and that it can make a system do more valuable works and make more than 99.9% use of the power budget. PMID:28208730

Dynamic Voltage-Frequency and Workload Joint Scaling Power Management for Energy Harvesting Multi-Core WSN Node SoC.

PubMed

Li, Xiangyu; Xie, Nijie; Tian, Xinyue

2017-02-08

This paper proposes a scheduling and power management solution for energy harvesting heterogeneous multi-core WSN node SoC such that the system continues to operate perennially and uses the harvested energy efficiently. The solution consists of a heterogeneous multi-core system oriented task scheduling algorithm and a low-complexity dynamic workload scaling and configuration optimization algorithm suitable for light-weight platforms. Moreover, considering the power consumption of most WSN applications have the characteristic of data dependent behavior, we introduce branches handling mechanism into the solution as well. The experimental result shows that the proposed algorithm can operate in real-time on a lightweight embedded processor (MSP430), and that it can make a system do more valuable works and make more than 99.9% use of the power budget.

Mission Profiles and Evidential Reasoning for Estimating Information Relevancy in Multi-Agent Supervisory Control Applications

DTIC Science & Technology

2010-06-01

artificial agents, their limited scope and singular purpose lead us to believe that human-machine trust will be very portable. That is, if one operator... Artificial Intelligence Review 2(2), 1988. [E88] M.R. Endsley. Situation awareness global assessment technique (SAGAT). In Proceedings of the National...1995. [F98] J. Ferber, Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence, Addison- Wesley, 1998. [NP01] I. Niles and A

An automated ranking platform for machine learning regression models for meat spoilage prediction using multi-spectral imaging and metabolic profiling.

PubMed

Estelles-Lopez, Lucia; Ropodi, Athina; Pavlidis, Dimitris; Fotopoulou, Jenny; Gkousari, Christina; Peyrodie, Audrey; Panagou, Efstathios; Nychas, George-John; Mohareb, Fady

2017-09-01

Over the past decade, analytical approaches based on vibrational spectroscopy, hyperspectral/multispectral imagining and biomimetic sensors started gaining popularity as rapid and efficient methods for assessing food quality, safety and authentication; as a sensible alternative to the expensive and time-consuming conventional microbiological techniques. Due to the multi-dimensional nature of the data generated from such analyses, the output needs to be coupled with a suitable statistical approach or machine-learning algorithms before the results can be interpreted. Choosing the optimum pattern recognition or machine learning approach for a given analytical platform is often challenging and involves a comparative analysis between various algorithms in order to achieve the best possible prediction accuracy. In this work, "MeatReg", a web-based application is presented, able to automate the procedure of identifying the best machine learning method for comparing data from several analytical techniques, to predict the counts of microorganisms responsible of meat spoilage regardless of the packaging system applied. In particularly up to 7 regression methods were applied and these are ordinary least squares regression, stepwise linear regression, partial least square regression, principal component regression, support vector regression, random forest and k-nearest neighbours. MeatReg" was tested with minced beef samples stored under aerobic and modified atmosphere packaging and analysed with electronic nose, HPLC, FT-IR, GC-MS and Multispectral imaging instrument. Population of total viable count, lactic acid bacteria, pseudomonads, Enterobacteriaceae and B. thermosphacta, were predicted. As a result, recommendations of which analytical platforms are suitable to predict each type of bacteria and which machine learning methods to use in each case were obtained. The developed system is accessible via the link: www.sorfml.com. Copyright © 2017 Elsevier Ltd. All rights reserved.

HTS machines as enabling technology for all-electric airborne vehicles

NASA Astrophysics Data System (ADS)

Masson, P. J.; Brown, G. V.; Soban, D. S.; Luongo, C. A.

2007-08-01

Environmental protection has now become paramount as evidence mounts to support the thesis of human activity-driven global warming. A global reduction of the emissions of pollutants into the atmosphere is therefore needed and new technologies have to be considered. A large part of the emissions come from transportation vehicles, including cars, trucks and airplanes, due to the nature of their combustion-based propulsion systems. Our team has been working for several years on the development of high power density superconducting motors for aircraft propulsion and fuel cell based power systems for aircraft. This paper investigates the feasibility of all-electric aircraft based on currently available technology. Electric propulsion would require the development of high power density electric propulsion motors, generators, power management and distribution systems. The requirements in terms of weight and volume of these components cannot be achieved with conventional technologies; however, the use of superconductors associated with hydrogen-based power plants makes possible the design of a reasonably light power system and would therefore enable the development of all-electric aero-vehicles. A system sizing has been performed both for actuators and for primary propulsion. Many advantages would come from electrical propulsion such as better controllability of the propulsion, higher efficiency, higher availability and less maintenance needs. Superconducting machines may very well be the enabling technology for all-electric aircraft development.

Putting Automated Visual Inspection Systems To Work On The Factory Floor: What's Missing?

NASA Astrophysics Data System (ADS)

Waltz, Frederick M.; Snyder, Michael A.; Batchelor, Bruce G.

1990-02-01

Machine vision systems and other automated visual inspection (AVI) systems have been proving their usefulness in factories for more than a decade. In spite of this, the number of installed systems is far below the number that could profitably be employed. In the opinion of the authors, the primary reason for this is the high cost of customizing vision systems to meet applications requirements. A three-part approach to this problem has proven to be useful: 1. A multi-phase paradigm for customer interaction, system specification, system development, and system installation; 2. A powerful and easy-to-use system development environment, including a a flexible laboratory lighting setup, plus software-based tools to assist in the design of image acquisition systems, b. an image processing environment with a very large repertoire of image processing and feature extraction operations and an easy-to-use command interpreter having macro capabilities, and c. an image analysis environment with high-level constructs, a flexible and powerful syntax, and a "seamless" interface to the image processing level; and 3. A moderately-priced high-speed "target" system fully compatible with the development environment, so that algorithms developed thereon can be transferred directly to the factory environment without further development costs or reprogramming. Items 1 and 2 are covered in other papers1,23,4,5 and are touched on here only briefly. Item 3 is the main subject of this paper. Our major motivation in presenting this paper is to offer suggestions to vendors developing commercial boards and systems, in hopes that the special needs of industrial inspection can be met.

Chemical Equilibrium And Transport (CET)

NASA Technical Reports Server (NTRS)

Mcbride, B. J.

1991-01-01

Powerful, machine-independent program calculates theoretical thermodynamic properties of chemical systems. Aids in design of compressors, turbines, engines, heat exchangers, and chemical processing equipment.

21. INTERIOR VIEW, UNDER THE MAIN FLOOR SHOWING THE LINESHAFT ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

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

Synthetic Space Vector Modulation

DTIC Science & Technology

2013-06-01

especially batteries without fancy controls. Inherently, DC machine commutation is environmentally sensitive and maintenance intensive at well as...reliable DC power supplies especially batteries without fancy controls. Inherently, DC machine commutation is environmentally sensitive and maintenance...Drives and Energy Systems, New Delhi, India , 20-23 December, 2010. [12] PIC18F2331/2431/4331/4431 datasheet DS39616B, Microchip Technology Inc

Machine-learning in grading of gliomas based on multi-parametric magnetic resonance imaging at 3T.

PubMed

Citak-Er, Fusun; Firat, Zeynep; Kovanlikaya, Ilhami; Ture, Ugur; Ozturk-Isik, Esin

2018-06-15

The objective of this study was to assess the contribution of multi-parametric (mp) magnetic resonance imaging (MRI) quantitative features in the machine learning-based grading of gliomas with a multi-region-of-interests approach. Forty-three patients who were newly diagnosed as having a glioma were included in this study. The patients were scanned prior to any therapy using a standard brain tumor magnetic resonance (MR) imaging protocol that included T1 and T2-weighted, diffusion-weighted, diffusion tensor, MR perfusion and MR spectroscopic imaging. Three different regions-of-interest were drawn for each subject to encompass tumor, immediate tumor periphery, and distant peritumoral edema/normal. The normalized mp-MRI features were used to build machine-learning models for differentiating low-grade gliomas (WHO grades I and II) from high grades (WHO grades III and IV). In order to assess the contribution of regional mp-MRI quantitative features to the classification models, a support vector machine-based recursive feature elimination method was applied prior to classification. A machine-learning model based on support vector machine algorithm with linear kernel achieved an accuracy of 93.0%, a specificity of 86.7%, and a sensitivity of 96.4% for the grading of gliomas using ten-fold cross validation based on the proposed subset of the mp-MRI features. In this study, machine-learning based on multiregional and multi-parametric MRI data has proven to be an important tool in grading glial tumors accurately even in this limited patient population. Future studies are needed to investigate the use of machine learning algorithms for brain tumor classification in a larger patient cohort. Copyright © 2018. Published by Elsevier Ltd.

Big genomics and clinical data analytics strategies for precision cancer prognosis.

PubMed

Ow, Ghim Siong; Kuznetsov, Vladimir A

2016-11-07

The field of personalized and precise medicine in the era of big data analytics is growing rapidly. Previously, we proposed our model of patient classification termed Prognostic Signature Vector Matching (PSVM) and identified a 37 variable signature comprising 36 let-7b associated prognostic significant mRNAs and the age risk factor that stratified large high-grade serous ovarian cancer patient cohorts into three survival-significant risk groups. Here, we investigated the predictive performance of PSVM via optimization of the prognostic variable weights, which represent the relative importance of one prognostic variable over the others. In addition, we compared several multivariate prognostic models based on PSVM with classical machine learning techniques such as K-nearest-neighbor, support vector machine, random forest, neural networks and logistic regression. Our results revealed that negative log-rank p-values provides more robust weight values as opposed to the use of other quantities such as hazard ratios, fold change, or a combination of those factors. PSVM, together with the classical machine learning classifiers were combined in an ensemble (multi-test) voting system, which collectively provides a more precise and reproducible patient stratification. The use of the multi-test system approach, rather than the search for the ideal classification/prediction method, might help to address limitations of the individual classification algorithm in specific situation.

The LSST Data Mining Research Agenda

NASA Astrophysics Data System (ADS)

Borne, K.; Becla, J.; Davidson, I.; Szalay, A.; Tyson, J. A.

2008-12-01

We describe features of the LSST science database that are amenable to scientific data mining, object classification, outlier identification, anomaly detection, image quality assurance, and survey science validation. The data mining research agenda includes: scalability (at petabytes scales) of existing machine learning and data mining algorithms; development of grid-enabled parallel data mining algorithms; designing a robust system for brokering classifications from the LSST event pipeline (which may produce 10,000 or more event alerts per night) multi-resolution methods for exploration of petascale databases; indexing of multi-attribute multi-dimensional astronomical databases (beyond spatial indexing) for rapid querying of petabyte databases; and more.

Fundamental aspects of steady-state conversion of heat to work at the nanoscale

NASA Astrophysics Data System (ADS)

Benenti, Giuliano; Casati, Giulio; Saito, Keiji; Whitney, Robert S.

2017-06-01

In recent years, the study of heat to work conversion has been re-invigorated by nanotechnology. Steady-state devices do this conversion without any macroscopic moving parts, through steady-state flows of microscopic particles such as electrons, photons, phonons, etc. This review aims to introduce some of the theories used to describe these steady-state flows in a variety of mesoscopic or nanoscale systems. These theories are introduced in the context of idealized machines which convert heat into electrical power (heat-engines) or convert electrical power into a heat flow (refrigerators). In this sense, the machines could be categorized as thermoelectrics, although this should be understood to include photovoltaics when the heat source is the sun. As quantum mechanics is important for most such machines, they fall into the field of quantum thermodynamics. In many cases, the machines we consider have few degrees of freedom, however the reservoirs of heat and work that they interact with are assumed to be macroscopic. This review discusses different theories which can take into account different aspects of mesoscopic and nanoscale physics, such as coherent quantum transport, magnetic-field induced effects (including topological ones such as the quantum Hall effect), and single electron charging effects. It discusses the efficiency of thermoelectric conversion, and the thermoelectric figure of merit. More specifically, the theories presented are (i) linear response theory with or without magnetic fields, (ii) Landauer scattering theory in the linear response regime and far from equilibrium, (iii) Green-Kubo formula for strongly interacting systems within the linear response regime, (iv) rate equation analysis for small quantum machines with or without interaction effects, (v) stochastic thermodynamic for fluctuating small systems. In all cases, we place particular emphasis on the fundamental questions about the bounds on ideal machines. Can magnetic-fields change the bounds on power or efficiency? What is the relationship between quantum theories of transport and the laws of thermodynamics? Does quantum mechanics place fundamental bounds on heat to work conversion which are absent in the thermodynamics of classical systems?

Methods, systems and apparatus for controlling operation of two alternating current (AC) machines

DOEpatents

Gallegos-Lopez, Gabriel [Torrance, CA; Nagashima, James M [Cerritos, CA; Perisic, Milun [Torrance, CA; Hiti, Silva [Redondo Beach, CA

2012-02-14

A system is provided for controlling two AC machines. The system comprises a DC input voltage source that provides a DC input voltage, a voltage boost command control module (VBCCM), a five-phase PWM inverter module coupled to the two AC machines, and a boost converter coupled to the inverter module and the DC input voltage source. The boost converter is designed to supply a new DC input voltage to the inverter module having a value that is greater than or equal to a value of the DC input voltage. The VBCCM generates a boost command signal (BCS) based on modulation indexes from the two AC machines. The BCS controls the boost converter such that the boost converter generates the new DC input voltage in response to the BCS. When the two AC machines require additional voltage that exceeds the DC input voltage required to meet a combined target mechanical power required by the two AC machines, the BCS controls the boost converter to drive the new DC input voltage generated by the boost converter to a value greater than the DC input voltage.

Efficient RF energy harvesting by using a fractal structured rectenna system

NASA Astrophysics Data System (ADS)

Oh, Sechang; Ramasamy, Mouli; Varadan, Vijay K.

2014-04-01

A rectenna system delivers, collects, and converts RF energy into direct current to power the electronic devices or recharge batteries. It consists of an antenna for receiving RF power, an input filter for processing energy and impedance matching, a rectifier, an output filter, and a load resistor. However, the conventional rectenna systems have drawback in terms of power generation, as the single resonant frequency of an antenna can generate only low power compared to multiple resonant frequencies. A multi band rectenna system is an optimal solution to generate more power. This paper proposes the design of a novel rectenna system, which involves developing a multi band rectenna with a fractal structured antenna to facilitate an increase in energy harvesting from various sources like Wi-Fi, TV signals, mobile networks and other ambient sources, eliminating the limitation of a single band technique. The usage of fractal antennas effects certain prominent advantages in terms of size and multiple resonances. Even though, a fractal antenna incorporates multiple resonances, controlling the resonant frequencies is an important aspect to generate power from the various desired RF sources. Hence, this paper also describes the design parameters of the fractal antenna and the methods to control the multi band frequency.

Operation of Direct Drive Systems: Experiments in Peak Power Tracking and Multi-Thruster Control

NASA Technical Reports Server (NTRS)

Snyder, John Steven; Brophy, John R.

2013-01-01

Direct-drive power and propulsion systems have the potential to significantly reduce the mass of high-power solar electric propulsion spacecraft, among other advantages. Recent experimental direct-drive work has significantly mitigated or retired the technical risks associated with single-thruster operation, so attention is now moving toward systems-level areas of interest. One of those areas is the use of a Hall thruster system as a peak power tracker to fully use the available power from a solar array. A simple and elegant control based on the incremental conductance method, enhanced by combining it with the unique properties of Hall thruster systems, is derived here and it is shown to track peak solar array power very well. Another area of interest is multi-thruster operation and control. Dualthruster operation was investigated in a parallel electrical configuration, with both thrusters operating from discharge power provided by a single solar array. Startup and shutdown sequences are discussed, and it is shown that multi-thruster operation and control is as simple as for a single thruster. Some system architectures require operation of multiple cathodes while they are electrically connected together. Four different methods to control the discharge current emitted by individual cathodes in this configuration are investigated, with cathode flow rate control appearing to be advantageous. Dual-parallel thruster operation with equal cathode current sharing at total powers up to 10 kW is presented.

End-pumped 300 W continuous-wave ytterbium-doped all-fiber laser with master oscillator multi-stage power amplifiers configuration.

PubMed

Yin, Shupeng; Yan, Ping; Gong, Mali

2008-10-27

An end-pumped ytterbium-doped all-fiber laser with 300 W output in continuous regime was reported, which was based on master oscillator multi-stage power amplifiers configuration. Monolithic fiber laser system consisted of an oscillator stage and two amplifier stages. Total optical-optical efficiency of monolithic fiber laser was approximately 65%, corresponding to 462 W of pump power coupled into laser system. We proposed a new method to connect power amplifier stage, which was crucial for the application of end-pumped combiner in high power MOPAs all-fiber laser.

3D hierarchical spatial representation and memory of multimodal sensory data

NASA Astrophysics Data System (ADS)

Khosla, Deepak; Dow, Paul A.; Huber, David J.

2009-04-01

This paper describes an efficient method and system for representing, processing and understanding multi-modal sensory data. More specifically, it describes a computational method and system for how to process and remember multiple locations in multimodal sensory space (e.g., visual, auditory, somatosensory, etc.). The multimodal representation and memory is based on a biologically-inspired hierarchy of spatial representations implemented with novel analogues of real representations used in the human brain. The novelty of the work is in the computationally efficient and robust spatial representation of 3D locations in multimodal sensory space as well as an associated working memory for storage and recall of these representations at the desired level for goal-oriented action. We describe (1) A simple and efficient method for human-like hierarchical spatial representations of sensory data and how to associate, integrate and convert between these representations (head-centered coordinate system, body-centered coordinate, etc.); (2) a robust method for training and learning a mapping of points in multimodal sensory space (e.g., camera-visible object positions, location of auditory sources, etc.) to the above hierarchical spatial representations; and (3) a specification and implementation of a hierarchical spatial working memory based on the above for storage and recall at the desired level for goal-oriented action(s). This work is most useful for any machine or human-machine application that requires processing of multimodal sensory inputs, making sense of it from a spatial perspective (e.g., where is the sensory information coming from with respect to the machine and its parts) and then taking some goal-oriented action based on this spatial understanding. A multi-level spatial representation hierarchy means that heterogeneous sensory inputs (e.g., visual, auditory, somatosensory, etc.) can map onto the hierarchy at different levels. When controlling various machine/robot degrees of freedom, the desired movements and action can be computed from these different levels in the hierarchy. The most basic embodiment of this machine could be a pan-tilt camera system, an array of microphones, a machine with arm/hand like structure or/and a robot with some or all of the above capabilities. We describe the approach, system and present preliminary results on a real-robotic platform.

Modeling of a production system using the multi-agent approach

NASA Astrophysics Data System (ADS)

Gwiazda, A.; Sękala, A.; Banaś, W.

2017-08-01

The method that allows for the analysis of complex systems is a multi-agent simulation. The multi-agent simulation (Agent-based modeling and simulation - ABMS) is modeling of complex systems consisting of independent agents. In the case of the model of the production system agents may be manufactured pieces set apart from other types of agents like machine tools, conveyors or replacements stands. Agents are magazines and buffers. More generally speaking, the agents in the model can be single individuals, but you can also be defined as agents of collective entities. They are allowed hierarchical structures. It means that a single agent could belong to a certain class. Depending on the needs of the agent may also be a natural or physical resource. From a technical point of view, the agent is a bundle of data and rules describing its behavior in different situations. Agents can be autonomous or non-autonomous in making the decision about the types of classes of agents, class sizes and types of connections between elements of the system. Multi-agent modeling is a very flexible technique for modeling and model creating in the convention that could be adapted to any research problem analyzed from different points of views. One of the major problems associated with the organization of production is the spatial organization of the production process. Secondly, it is important to include the optimal scheduling. For this purpose use can approach multi-purposeful. In this regard, the model of the production process will refer to the design and scheduling of production space for four different elements. The program system was developed in the environment NetLogo. It was also used elements of artificial intelligence. The main agent represents the manufactured pieces that, according to previously assumed rules, generate the technological route and allow preprint the schedule of that line. Machine lines, reorientation stands, conveyors and transport devices also represent the other type of agent that are utilized in the described simulation. The article presents the idea of an integrated program approach and shows the resulting production layout as a virtual model. This model was developed in the NetLogo multi-agent program environment.

Self-assembling fluidic machines

NASA Astrophysics Data System (ADS)

Grzybowski, Bartosz A.; Radkowski, Michal; Campbell, Christopher J.; Lee, Jessamine Ng; Whitesides, George M.

2004-03-01

This letter describes dynamic self-assembly of two-component rotors floating at the interface between liquid and air into simple, reconfigurable mechanical systems ("machines"). The rotors are powered by an external, rotating magnetic field, and their positions within the interface are controlled by: (i) repulsive hydrodynamic interactions between them and (ii) by localized magnetic fields produced by an array of small electromagnets located below the plane of the interface. The mechanical functions of the machines depend on the spatiotemporal sequence of activation of the electromagnets.

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

Tan, Jin; Zhang, Yingchen; Krad, Ibrahim

Power system frequency needs to be maintained close to its nominal value at all times to avoid machine damage, under-frequency load-shedding and even blackouts. Adequate primary frequency response and secondary frequency response are the primary forces to correct an energy imbalance at the second to minute level. As wind energy becomes a larger portion of the world's energy portfolio, there are greater oppotunities for wind to provide frequency response services. This paper addresses one area of frequency control that has been missing in previous work - the reliabilty impacts and interactions between primary and secondary frequency control. The lack ofmore » a commercially available tools to simulate the interaction of these two responses has limited the energy industry's understanding of when the depletion of primary control reserve will impact the performance of secondary conrol response or vice versa. To investigate this issue, in this paper we develop a multi-area frequency response integration model with combined primary and secondary frequency control capabilities.« less

Design and fabrication of the progressive addition lenses

NASA Astrophysics Data System (ADS)

Qin, Linling; Qian, Lin; Yu, Jingchi

2011-11-01

The use of progressive addition lenses (PALs) for the correction of presbyopia has increased dramatically in recent years. These lenses are now being used as the preferred alternative to bifocal and trifocal lenses in many parts of the world. Progressive addition lenses are a kind of opthalmic lenses with freeform surface. The surface curvature of the Progressive addition lenses varies gradually from a minimum value in the upper area, to a maximum value in the lower area. Thus a PAL has a surface with three zones which have very small astigmatism: far-view zone, near-view zone, and intermediate zone. The far view zone and near view zone have relatively constant powers and connected by the intermediate zone with power varies progressively. The design and fabrication technologies of progressive addition lenses have fast progresses because of the massive development of the optical simulation software, multi-axis ultraprecision machining technologies and CNC machining technologies. The design principles of progressive addition lenses are discussed in a historic review. Several kinds of design methods are illustrated, and their advantages and disadvantages are also represented. In the current study, it is shown that the optical characteristics of the different progressive addition lenses designs are significantly different from one another. The different fabrication technologies of Progressive addition lenses are also discussed in the paper. Plastic injection molding and precision-machine turning are the common fabrication technologies for exterior PALs and Interior PALs respectively.

A new digital pulse power supply in heavy ion research facility in Lanzhou

NASA Astrophysics Data System (ADS)

Wang, Rongkun; Chen, Youxin; Huang, Yuzhen; Gao, Daqing; Zhou, Zhongzu; Yan, Huaihai; Zhao, Jiang; Shi, Chunfeng; Wu, Fengjun; Yan, Hongbin; Xia, Jiawen; Yuan, Youjin

2013-11-01

To meet the increasing requirements of the Heavy Ion Research Facility in Lanzhou-Cooler Storage Ring (HIRFL-CSR), a new digital pulse power supply, which employs multi-level converter, was designed. This power supply was applied with a multi H-bridge converters series-parallel connection topology. A new control model named digital power supply regulator system (DPSRS) was proposed, and a pulse power supply prototype based on DPSRS has been built and tested. The experimental results indicate that tracking error and ripple current meet the requirements of this design. The achievement of prototype provides a perfect model for HIRFL-CSR power supply system.

Lunar surface vehicle model competition

NASA Technical Reports Server (NTRS)

1990-01-01

During Fall and Winter quarters, Georgia Tech's School of Mechanical Engineering students designed machines and devices related to Lunar Base construction tasks. These include joint projects with Textile Engineering students. Topics studied included lunar environment simulator via drop tower technology, lunar rated fasteners, lunar habitat shelter, design of a lunar surface trenching machine, lunar support system, lunar worksite illumination (daytime), lunar regolith bagging system, sunlight diffusing tent for lunar worksite, service apparatus for lunar launch vehicles, lunar communication/power cables and teleoperated deployment machine, lunar regolith bag collection and emplacement device, soil stabilization mat for lunar launch/landing site, lunar rated fastening systems for robotic implementation, lunar surface cable/conduit and automated deployment system, lunar regolith bagging system, and lunar rated fasteners and fastening systems. A special topics team of five Spring quarter students designed and constructed a remotely controlled crane implement for the SKITTER model.

MultiMiTar: a novel multi objective optimization based miRNA-target prediction method.

PubMed

Mitra, Ramkrishna; Bandyopadhyay, Sanghamitra

2011-01-01

Machine learning based miRNA-target prediction algorithms often fail to obtain a balanced prediction accuracy in terms of both sensitivity and specificity due to lack of the gold standard of negative examples, miRNA-targeting site context specific relevant features and efficient feature selection process. Moreover, all the sequence, structure and machine learning based algorithms are unable to distribute the true positive predictions preferentially at the top of the ranked list; hence the algorithms become unreliable to the biologists. In addition, these algorithms fail to obtain considerable combination of precision and recall for the target transcripts that are translationally repressed at protein level. In the proposed article, we introduce an efficient miRNA-target prediction system MultiMiTar, a Support Vector Machine (SVM) based classifier integrated with a multiobjective metaheuristic based feature selection technique. The robust performance of the proposed method is mainly the result of using high quality negative examples and selection of biologically relevant miRNA-targeting site context specific features. The features are selected by using a novel feature selection technique AMOSA-SVM, that integrates the multi objective optimization technique Archived Multi-Objective Simulated Annealing (AMOSA) and SVM. MultiMiTar is found to achieve much higher Matthew's correlation coefficient (MCC) of 0.583 and average class-wise accuracy (ACA) of 0.8 compared to the others target prediction methods for a completely independent test data set. The obtained MCC and ACA values of these algorithms range from -0.269 to 0.155 and 0.321 to 0.582, respectively. Moreover, it shows a more balanced result in terms of precision and sensitivity (recall) for the translationally repressed data set as compared to all the other existing methods. An important aspect is that the true positive predictions are distributed preferentially at the top of the ranked list that makes MultiMiTar reliable for the biologists. MultiMiTar is now available as an online tool at www.isical.ac.in/~bioinfo_miu/multimitar.htm. MultiMiTar software can be downloaded from www.isical.ac.in/~bioinfo_miu/multimitar-download.htm.

Contribution a l'etude et a la conception d'une machine synchrone a flux transverse destinee au degivrage d'aeronefs en cours de vol

NASA Astrophysics Data System (ADS)

Boussetoua, Mohammed

During winter, the climate in the northern region is known for its icing and freezing conditions. However, emergency services often use helicopters to reach isolated locations. The difficult situations, generally experiences in the North particularly in Quebec, may prevent rescuers to intervene. The main reason preventing such operations is the lack of a de-icing system in the small helicopter blades. The overall objective of the project is research, development, design and manufacture of a system composed of an on-board rotating low speed generator and heating elements. It consumes a part of the power supplied by the turbine through the axis of the main rotor of the small aircraft and converts it to electrical power to be used by the heating elements. This innovation will allow to fly safely everywhere throughout the year protect the lives of the users even in the worst weather conditions. Firstly, the research focuses on the identification of problems related to the use of protection systems against the hoarfrost on main rotor blades of different aircrafts during flight. In this phase, we specifically focused on the difficulties encountered by the aircraft companies using the existing and operational systems for protection against hoarfrost. Main rotor blades are difficult to protect on helicopters. Several systems were considered by the helicopter manufacturers, such as electrothermal systems, pneumatic systems or using anti-icing fluids. In the current state of technological knowledge, all helicopters that have been certified to fly in icing conditions use electrothermal systems for protection against hoarfrost on their main rotor Small helicopters addressed by this work, are forbidden to fly in icing conditions due to lack of energy source to operate these systems. The electrothermal system has been considered for this thesis work to protect the main rotor blades of small aircraft in-flight. The second part of this thesis is based on the source of power feeding the hearting system. In recent years, numerous research studies have started on the development of electromechanical system converters for various applications, such as transport by road, rail or aviation. The development of new low-speed, low-weight electric machines and their very high degree of compactness has become a very promising alternative. This project strongly interests many industries in the field of air transport. The transverse flux machine is considered as a compact structure having better mass power compared to other electrical machines. The design of transverse flux machine was the subject of an electromagnetic study. Also, the analytical study helped to determine the overall dimensions of the machine. The study was followed by a validation phase of the analytical model using numerical simulations. These two studies were intended to determine changes in the characteristics of the transverse flux machine according to the different geometric dimensions of its active parts. From the calculations made using analytical and numerical models, a prototype of the transverse flux machine (600 W, 320 RPM) was designed and manufactured in the AMIL laboratory at the Universite du Quebec a Chicoutimi (UQAC). A bench test was conducted to compare the theoretical and experimental results. The measurements obtained on this prototype were compared with the theoretical results. This phase of the study demonstrates with satisfaction, the reliability of the theoretical models developed. Finally, a new configuration of this machine has been proposed. Numerical simulation results of this structure are particularly encouraging and require further investigations. For logistical and financial reasons, the prototype of this configuration has not been manufactured. (Abstract shortened by UMI.)

On the Safety of Machine Learning: Cyber-Physical Systems, Decision Sciences, and Data Products.

PubMed

Varshney, Kush R; Alemzadeh, Homa

2017-09-01

Machine learning algorithms increasingly influence our decisions and interact with us in all parts of our daily lives. Therefore, just as we consider the safety of power plants, highways, and a variety of other engineered socio-technical systems, we must also take into account the safety of systems involving machine learning. Heretofore, the definition of safety has not been formalized in a machine learning context. In this article, we do so by defining machine learning safety in terms of risk, epistemic uncertainty, and the harm incurred by unwanted outcomes. We then use this definition to examine safety in all sorts of applications in cyber-physical systems, decision sciences, and data products. We find that the foundational principle of modern statistical machine learning, empirical risk minimization, is not always a sufficient objective. We discuss how four different categories of strategies for achieving safety in engineering, including inherently safe design, safety reserves, safe fail, and procedural safeguards can be mapped to a machine learning context. We then discuss example techniques that can be adopted in each category, such as considering interpretability and causality of predictive models, objective functions beyond expected prediction accuracy, human involvement for labeling difficult or rare examples, and user experience design of software and open data.

Research on intelligent machine self-perception method based on LSTM

NASA Astrophysics Data System (ADS)

Wang, Qiang; Cheng, Tao

2018-05-01

In this paper, we use the advantages of LSTM in feature extraction and processing high-dimensional and complex nonlinear data, and apply it to the autonomous perception of intelligent machines. Compared with the traditional multi-layer neural network, this model has memory, can handle time series information of any length. Since the multi-physical domain signals of processing machines have a certain timing relationship, and there is a contextual relationship between states and states, using this deep learning method to realize the self-perception of intelligent processing machines has strong versatility and adaptability. The experiment results show that the method proposed in this paper can obviously improve the sensing accuracy under various working conditions of the intelligent machine, and also shows that the algorithm can well support the intelligent processing machine to realize self-perception.

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.

CESAR research in intelligent machines

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

Weisbin, C.R.

1986-01-01

The Center for Engineering Systems Advanced Research (CESAR) was established in 1983 as a national center for multidisciplinary, long-range research and development in machine intelligence and advanced control theory for energy-related applications. Intelligent machines of interest here are artificially created operational systems that are capable of autonomous decision making and action. The initial emphasis for research is remote operations, with specific application to dexterous manipulation in unstructured dangerous environments where explosives, toxic chemicals, or radioactivity may be present, or in other environments with significant risk such as coal mining or oceanographic missions. Potential benefits include reduced risk to man inmore » hazardous situations, machine replication of scarce expertise, minimization of human error due to fear or fatigue, and enhanced capability using high resolution sensors and powerful computers. A CESAR goal is to explore the interface between the advanced teleoperation capability of today, and the autonomous machines of the future.« less

Sensitivity of Support Vector Machine Predictions of Passive Microwave Brightness Temperature Over Snow-covered Terrain in High Mountain Asia

NASA Astrophysics Data System (ADS)

Ahmad, J. A.; Forman, B. A.

2017-12-01

High Mountain Asia (HMA) serves as a water supply source for over 1.3 billion people, primarily in south-east Asia. Most of this water originates as snow (or ice) that melts during the summer months and contributes to the run-off downstream. In spite of its critical role, there is still considerable uncertainty regarding the total amount of snow in HMA and its spatial and temporal variation. In this study, the NASA Land Information Systems (LIS) is used to model the hydrologic cycle over the Indus basin. In addition, the ability of support vector machines (SVM), a machine learning technique, to predict passive microwave brightness temperatures at a specific frequency and polarization as a function of LIS-derived land surface model output is explored in a sensitivity analysis. Multi-frequency, multi-polarization passive microwave brightness temperatures as measured by the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) over the Indus basin are used as training targets during the SVM training process. Normalized sensitivity coefficients (NSC) are then computed to assess the sensitivity of a well-trained SVM to each LIS-derived state variable. Preliminary results conform with the known first-order physics. For example, input states directly linked to physical temperature like snow temperature, air temperature, and vegetation temperature have positive NSC's whereas input states that increase volume scattering such as snow water equivalent or snow density yield negative NSC's. Air temperature exhibits the largest sensitivity coefficients due to its inherent, high-frequency variability. Adherence of this machine learning algorithm to the first-order physics bodes well for its potential use in LIS as the observation operator within a radiance data assimilation system aimed at improving regional- and continental-scale snow estimates.

Evolution of the ATLAS Nightly Build System

NASA Astrophysics Data System (ADS)

Undrus, A.

2012-12-01

The ATLAS Nightly Build System is a major component in the ATLAS collaborative software organization, validation, and code approval scheme. For over 10 years of development it has evolved into a factory for automatic release production and grid distribution. The 50 multi-platform branches of ATLAS releases provide vast opportunities for testing new packages, verification of patches to existing software, and migration to new platforms and compilers for ATLAS code that currently contains 2200 packages with 4 million C++ and 1.4 million python scripting lines written by about 1000 developers. Recent development was focused on the integration of ATLAS Nightly Build and Installation systems. The nightly releases are distributed and validated and some are transformed into stable releases used for data processing worldwide. The ATLAS Nightly System is managed by the NICOS control tool on a computing farm with 50 powerful multiprocessor nodes. NICOS provides the fully automated framework for the release builds, testing, and creation of distribution kits. The ATN testing framework of the Nightly System runs unit and integration tests in parallel suites, fully utilizing the resources of multi-core machines, and provides the first results even before compilations complete. The NICOS error detection system is based on several techniques and classifies the compilation and test errors according to their severity. It is periodically tuned to place greater emphasis on certain software defects by highlighting the problems on NICOS web pages and sending automatic e-mail notifications to responsible developers. These and other recent developments will be presented and future plans will be described.

Evaluation of a multi-sensor machine vision system for automated hardwood lumber grading

Treesearch

D. Earl Kline; Chris Surak; Philip A. Araman

2000-01-01

Over the last 10 years, scientists at the Thomas M. Brooks Forest Products Center, the Bradley Department of Electrical Engineering, and the USDA Forest Service have been working on lumber scanning systems that can accurately locate and identify defects in hardwood lumber. Current R&D efforts are targeted toward developing automated lumber grading technologies. The...

Design and Development of an Engineering Prototype Compact X-Ray Scanner (FMS 5000)

DTIC Science & Technology

1989-03-31

machined by "wire-EDM" (electro discharge machining ). Three different slice thicknesses can be selected from the scan menu. The set of slice thicknesses...circuit. This type of circuit is used whenever more than ten kilowatts of power are needed by a machine . For example, lathes and milling machines in a... machine shop usually use this type of input power. A three- phase circuit delivers power more efficiently than a single-phase circuit because three

EEG classification for motor imagery and resting state in BCI applications using multi-class Adaboost extreme learning machine

NASA Astrophysics Data System (ADS)

Gao, Lin; Cheng, Wei; Zhang, Jinhua; Wang, Jue

2016-08-01

Brain-computer interface (BCI) systems provide an alternative communication and control approach for people with limited motor function. Therefore, the feature extraction and classification approach should differentiate the relative unusual state of motion intention from a common resting state. In this paper, we sought a novel approach for multi-class classification in BCI applications. We collected electroencephalographic (EEG) signals registered by electrodes placed over the scalp during left hand motor imagery, right hand motor imagery, and resting state for ten healthy human subjects. We proposed using the Kolmogorov complexity (Kc) for feature extraction and a multi-class Adaboost classifier with extreme learning machine as base classifier for classification, in order to classify the three-class EEG samples. An average classification accuracy of 79.5% was obtained for ten subjects, which greatly outperformed commonly used approaches. Thus, it is concluded that the proposed method could improve the performance for classification of motor imagery tasks for multi-class samples. It could be applied in further studies to generate the control commands to initiate the movement of a robotic exoskeleton or orthosis, which finally facilitates the rehabilitation of disabled people.

Description of photovoltaic village power systems in the United States and Africa

NASA Technical Reports Server (NTRS)

Ratajczak, A. F.; Bifano, W. J.

1979-01-01

The paper describes the designs, hardware, and installations of NASA photovoltaic power systems in the village of Schuchuli in Arizona and Tangaye in Upper Volta, Africa. The projects were designed to demonstrate that current photovoltaic system technology can provide electrical power for domestic services for small, remote communities. The Schuchuli system has a 3.5 kW peak solar array which provides power for water pumping, a refrigerator for each family, lights, and community washing and sewing machines. The 1.8 kW Tangaye system provides power for pumping, flour milling, and lights in the milling building. Both are stand-alone systems operated by local personnel, and they are monitored by NASA to measure design adequacy and refine future designs.

A polyhedral study of production ramping

DOE PAGES

Damci-Kurt, Pelin; Kucukyavuz, Simge; Rajan, Deepak; ...

2015-06-12

Here, we give strong formulations of ramping constraints—used to model the maximum change in production level for a generator or machine from one time period to the next—and production limits. For the two-period case, we give a complete description of the convex hull of the feasible solutions. The two-period inequalities can be readily used to strengthen ramping formulations without the need for separation. For the general case, we define exponential classes of multi-period variable upper bound and multi-period ramping inequalities, and give conditions under which these inequalities define facets of ramping polyhedra. Finally, we present exact polynomial separation algorithms formore » the inequalities and report computational experiments on using them in a branch-and-cut algorithm to solve unit commitment problems in power generation.« less

Adjustable mounting device for high-volume production of beam-shaping systems for high-power diode lasers

NASA Astrophysics Data System (ADS)

Haag, Sebastian; Bernhardt, Henning; Rübenach, Olaf; Haverkamp, Tobias; Müller, Tobias; Zontar, Daniel; Brecher, Christian

2015-02-01

In many applications for high-power diode lasers, the production of beam-shaping and homogenizing optical systems experience rising volumes and dynamical market demands. The automation of assembly processes on flexible and reconfigurable machines can contribute to a more responsive and scalable production. The paper presents a flexible mounting device designed for the challenging assembly of side-tab based optical systems. It provides design elements for precisely referencing and fixating two optical elements in a well-defined geometric relation. Side tabs are presented to the machine allowing the application of glue and a rotating mechanism allows the attachment to the optical elements. The device can be adjusted to fit different form factors and it can be used in high-volume assembly machines. The paper shows the utilization of the device for a collimation module consisting of a fast-axis and a slow-axis collimation lens. Results regarding the repeatability and process capability of bonding side tab assemblies as well as estimates from 3D simulation for overall performance indicators achieved such as cycle time and throughput will be discussed.

Thermal Investigation of Interaction between High-power CW-laser Radiation and a Water-jet

NASA Astrophysics Data System (ADS)

Brecher, Christian; Janssen, Henning; Eckert, Markus; Schmidt, Florian

The technology of a water guided laser beam has been industrially established for micro machining. Pulsed laser radiation is guided via a water jet (diameter: 25-250 μm) using total internal reflection. Due to the cylindrical jet shape the depth of field increases to above 50 mm, enabling parallel kerfs compared to conventional laser systems. However higher material thicknesses and macro geometries cannot be machined economically viable due to low average laser powers. Fraunhofer IPT has successfully combined a high-power continuous-wave (CW) fiber laser (6 kW) and water jet technology. The main challenge of guiding high-power laser radiation in water is the energy transferred to the jet by absorption, decreasing its stability. A model of laser water interaction in the water jet has been developed and validated experimentally. Based on the results an upscaling of system technology to 30 kW is discussed, enabling a high potential in cutting challenging materials at high qualities and high speeds.

Effect of Extended State Observer and Automatic Voltage Regulator on Synchronous Machine Connected to Infinite Bus Power System

NASA Astrophysics Data System (ADS)

Angu, Rittu; Mehta, R. K.

2018-04-01

This paper presents a robust controller known as Extended State Observer (ESO) in order to improve the stability and voltage regulation of a synchronous machine connected to an infinite bus power system through a transmission line. The ESO-based control scheme is implemented with an automatic voltage regulator in conjunction with an excitation system to enhance the damping of low frequency power system oscillations, as the Power System Stabilizer (PSS) does. The implementation of PSS excitation control techniques however requires reliable information about the entire states, though they are not always directly measureable. To address this issue, the proposed ESO provides the estimate of system states as well as disturbance state together in order to improve not only the damping but also compensates system efficiently in presence of parameter uncertainties and external disturbances. The Closed-Loop Poles (CLPs) of the system have been assigned by the symmetric root locus technique, with the desired level of system damping provided by the dominant CLPs. The performance of the system is analyzed through simulating at different operating conditions. The control method is not only capable of providing zero estimation error in steady-state, but also shows robustness in tracking the reference command under parametric variations and external disturbances. Illustrative examples have been provided to demonstrate the effectiveness of the developed methodology.

Self tuning control of wind-diesel power systems

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

Mufti, M.D.; Balasubramanian, R.; Tripathy, S.C.

1995-12-31

This paper proposes some effective self-tuning control strategies for isolated Wind-Diesel power generation systems. Detailed modeling and studies on both single-input single-output (SISO) as well as multi-input multi-output (MIMO) self tuning regulators, applied to a typical system, are reported. Further, the effect of introducing a Super-conducting Magnetic Energy Storage (SMES) unit on the system performance has been investigated. The MIMO self-tuning regulator controlling the hybrid system and the SMES in a coordinated manner exhibits the best performance.

Automation technology for aerospace power management

NASA Technical Reports Server (NTRS)

Larsen, R. L.

1982-01-01

The growing size and complexity of spacecraft power systems coupled with limited space/ground communications necessitate increasingly automated onboard control systems. Research in computer science, particularly artificial intelligence has developed methods and techniques for constructing man-machine systems with problem-solving expertise in limited domains which may contribute to the automation of power systems. Since these systems perform tasks which are typically performed by human experts they have become known as Expert Systems. A review of the current state of the art in expert systems technology is presented, and potential applications in power systems management are considered. It is concluded that expert systems appear to have significant potential for improving the productivity of operations personnel in aerospace applications, and in automating the control of many aerospace systems.

Rule Extraction Based on Extreme Learning Machine and an Improved Ant-Miner Algorithm for Transient Stability Assessment.

PubMed

Li, Yang; Li, Guoqing; Wang, Zhenhao

2015-01-01

In order to overcome the problems of poor understandability of the pattern recognition-based transient stability assessment (PRTSA) methods, a new rule extraction method based on extreme learning machine (ELM) and an improved Ant-miner (IAM) algorithm is presented in this paper. First, the basic principles of ELM and Ant-miner algorithm are respectively introduced. Then, based on the selected optimal feature subset, an example sample set is generated by the trained ELM-based PRTSA model. And finally, a set of classification rules are obtained by IAM algorithm to replace the original ELM network. The novelty of this proposal is that transient stability rules are extracted from an example sample set generated by the trained ELM-based transient stability assessment model by using IAM algorithm. The effectiveness of the proposed method is shown by the application results on the New England 39-bus power system and a practical power system--the southern power system of Hebei province.

Development of SWITCH-Hawaii model: loads and renewable resources.

DOT National Transportation Integrated Search

2016-08-01

This report summarizes work done to configure the SWITCH power system model using data for the Oahu power system. SWITCH is a planning model designed to choose optimal infrastructure investments for power systems over a multi-decade period. Investmen...

Advanced Grid Simulator for Multi-Megawatt Power Converter Testing and Certification

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

Koralewicz, Przemyslaw; Gevorgian, Vahan; Wallen, Robb

2017-02-16

Grid integration testing of inverter-coupled renewable energy technologies is an essential step in the qualification of renewable energy and energy storage systems to ensure the stability of the power system. New types of devices must be thoroughly tested and validated for compliance with relevant grid codes and interconnection requirements. For this purpose, highly specialized custom-made testing equipment is needed to emulate various types of realistic grid conditions that are required by certification bodies or for research purposes. For testing multi-megawatt converters, a high power grid simulator capable of creating controlled grid conditions and meeting both power quality and dynamic characteristicsmore » is needed. This paper describes the new grid simulator concept based on ABB's medium voltage ACS6000 drive technology that utilizes advanced modulation and control techniques to create an unique testing platform for various multi-megawatt power converter systems. Its performance is demonstrated utilizing the test results obtained during commissioning activities at the National Renewable Energy Laboratory in Colorado, USA.« less

Machine learning molecular dynamics for the simulation of infrared spectra.

PubMed

Gastegger, Michael; Behler, Jörg; Marquetand, Philipp

2017-10-01

Machine learning has emerged as an invaluable tool in many research areas. In the present work, we harness this power to predict highly accurate molecular infrared spectra with unprecedented computational efficiency. To account for vibrational anharmonic and dynamical effects - typically neglected by conventional quantum chemistry approaches - we base our machine learning strategy on ab initio molecular dynamics simulations. While these simulations are usually extremely time consuming even for small molecules, we overcome these limitations by leveraging the power of a variety of machine learning techniques, not only accelerating simulations by several orders of magnitude, but also greatly extending the size of systems that can be treated. To this end, we develop a molecular dipole moment model based on environment dependent neural network charges and combine it with the neural network potential approach of Behler and Parrinello. Contrary to the prevalent big data philosophy, we are able to obtain very accurate machine learning models for the prediction of infrared spectra based on only a few hundreds of electronic structure reference points. This is made possible through the use of molecular forces during neural network potential training and the introduction of a fully automated sampling scheme. We demonstrate the power of our machine learning approach by applying it to model the infrared spectra of a methanol molecule, n -alkanes containing up to 200 atoms and the protonated alanine tripeptide, which at the same time represents the first application of machine learning techniques to simulate the dynamics of a peptide. In all of these case studies we find an excellent agreement between the infrared spectra predicted via machine learning models and the respective theoretical and experimental spectra.

Midterm Stability Evaluation of Wide-area Power System by using Synchronized Phasor Measurements

NASA Astrophysics Data System (ADS)

Ota, Yutaka; Ukai, Hiroyuki; Nakamura, Koichi; Fujita, Hideki

In recent years, the PMU (Phasor Measurement Unit) receives a great deal of attention as a synchronized measurement system of power systems. Synchronized phasor angles obtained by the PMU provide the effective information for evaluating the stability of a bulk power system. The aspect of instability phenomena during midterm tends to be more complicated, and the stability analysis using the synchronized phasor measurements is significant in order to keep a complicated power system stable. This paper proposes a midterm stability evaluation method of the wide-area power system by using the synchronized phasor measurements. By clustering and aggregating the power system to some coherent groups, the step-out is effectively predicted on the basis of the two-machine equivalent power system model. The midterm stability of a longitudinal power system model of Japanese 60Hz systems constructed by the PSA, which is a hybrid-type power system simulator, is practically evaluated using the proposed method.