Analiza poslovnega okolja Nemčije in ZDA

OpenAIRE

Podlesnik, Mitja

2017-01-01

V diplomskem projektu predstavljamo in primerjamo poslovno okolje dveh držav, ZDA in Nemčije. Na eni strani ZDA kot ena izmed največjih svetovnih velesil v gospodarstvu in tudi v ostalih dejavnikih, na drugi strani pa Nemčija kot največja gonilna sila gospodarstva v Evropi. Ker je globalizacija vedno bolj občutna in v porastu, zraven pa je še velik razcvet digitalne tehnologije, praktično mej v gospodarstvu več ni. Vedno več podjetij širi in posluje izven svojih domačih meja v želji po prepoz...

Impact of scaling on the performance and reliability degradation of metal-contacts in NEMS devices

KAUST Repository

Dadgour, Hamed F.

2011-04-01

Nano-electro-mechanical switches (NEMS) offer new possibilities for the design of ultra energy-efficient systems; however, thus far, all the fabricated NEMS devices require high supply voltages that limit their applicability for logic designs. Therefore, research is being conducted to lower the operating voltages by scaling down the physical dimensions of these devices. However, the impact of device scaling on the electrical and mechanical properties of metal contacts in NEMS devices has not been thoroughly investigated in the literature. Such a study is essential because metal contacts play a critical role in determining the overall performance and reliability of NEMS. Therefore, the comprehensive analytical study presented in this paper highlights the performance and reliability degradations of such metal contacts caused by scaling. The proposed modeling environment accurately takes into account the impact of roughness of contact surfaces, elastic/plastic deformation of contacting asperities, and various inter-molecular forces between mating surfaces (such as Van der Waals and capillary forces). The modeling results are validated and calibrated using available measurement data. This scaling analysis indicates that the key contact properties of gold contacts (resistance, stiction and wear-out) deteriorate "exponentially" with scaling. Simulation results demonstrate that reliable (stiction-free) operation of very small contact areas (≈ 6nm x 6nm) will be a daunting task due to the existence of strong surface forces. Hence, contact degradation is identified as a major problem to the scaling of NEMS transistors. © 2011 IEEE.

Modeling the size dependent pull-in instability of beam-type NEMS using strain gradient theory

Directory of Open Access Journals (Sweden)

Ali Koochi

Full Text Available It is well recognized that size dependency of materials characteristics, i.e. size-effect, often plays a significant role in the performance of nano-structures. Herein, strain gradient continuum theory is employed to investigate the size dependent pull-in instability of beam-type nano-electromechanical systems (NEMS. Two most common types of NEMS i.e. nano-bridge and nano-cantilever are considered. Effects of electrostatic field and dispersion forces i.e. Casimir and van der Waals (vdW attractions have been considered in the nonlinear governing equations of the systems. Two different solution methods including numerical and Rayleigh-Ritz have been employed to solve the constitutive differential equations of the system. Effect of dispersion forces, the size dependency and the importance of coupling between them on the instability performance are discussed.

Optimization of FIB milling for rapid NEMS prototyping

DEFF Research Database (Denmark)

Malm, Bjarke; Petersen, Dirch Hjorth; Lei, Anders

2011-01-01

We demonstrate an optimized milling technique to focused ion beam (FIB) milling in template silicon membranes for fast prototyping of nanoelectromechanical systems (NEMS). Using a single-pass milling strategy the highly topology dependent sputtering rate is boosted and shorter milling time...... is achieved. Drift independence is obtained for small critical features using a radial scan strategy, and a back scan routine ensures minimal line width deviation removing redeposited material. Milling a design similar to a nano four-point probe with a pitch down to 400nm we display what optimized FIB milling...

Tribo-functionalizing Si and SU8 materials by surface modification for application in MEMS/NEMS actuator-based devices

International Nuclear Information System (INIS)

Singh, R A; Satyanarayana, N; Sinha, S K; Kustandi, T S

2011-01-01

Micro/nano-electro-mechanical-systems (MEMS/NEMS) are miniaturized devices built at micro/nanoscales. At these scales, the surface/interfacial forces are extremely strong and they adversely affect the smooth operation and the useful operating lifetimes of such devices. When these forces manifest in severe forms, they lead to material removal and thereby reduce the wear durability of the devices. In this paper, we present a simple, yet robust, two-step surface modification method to significantly enhance the tribological performance of MEMS/NEMS materials. The two-step method involves oxygen plasma treatment of polymeric films and the application of a nanolubricant, namely perfluoropolyether. We apply the two-step method to the two most important MEMS/NEMS structural materials, namely silicon and SU8 polymer. On applying surface modification to these materials, their initial coefficient of friction reduces by ∼4-7 times and the steady-state coefficient of friction reduces by ∼2.5-3.5 times. Simultaneously, the wear durability of both the materials increases by >1000 times. The two-step method is time effective as each of the steps takes the time duration of approximately 1 min. It is also cost effective as the oxygen plasma treatment is a part of the MEMS/NEMS fabrication process. The two-step method can be readily and easily integrated into MEMS/NEMS fabrication processes. It is anticipated that this method will work for any kind of structural material from which MEMS/NEMS are or can be made.

Tribo-functionalizing Si and SU8 materials by surface modification for application in MEMS/NEMS actuator-based devices

Science.gov (United States)

Singh, R. A.; Satyanarayana, N.; Kustandi, T. S.; Sinha, S. K.

2011-01-01

Micro/nano-electro-mechanical-systems (MEMS/NEMS) are miniaturized devices built at micro/nanoscales. At these scales, the surface/interfacial forces are extremely strong and they adversely affect the smooth operation and the useful operating lifetimes of such devices. When these forces manifest in severe forms, they lead to material removal and thereby reduce the wear durability of the devices. In this paper, we present a simple, yet robust, two-step surface modification method to significantly enhance the tribological performance of MEMS/NEMS materials. The two-step method involves oxygen plasma treatment of polymeric films and the application of a nanolubricant, namely perfluoropolyether. We apply the two-step method to the two most important MEMS/NEMS structural materials, namely silicon and SU8 polymer. On applying surface modification to these materials, their initial coefficient of friction reduces by ~4-7 times and the steady-state coefficient of friction reduces by ~2.5-3.5 times. Simultaneously, the wear durability of both the materials increases by >1000 times. The two-step method is time effective as each of the steps takes the time duration of approximately 1 min. It is also cost effective as the oxygen plasma treatment is a part of the MEMS/NEMS fabrication process. The two-step method can be readily and easily integrated into MEMS/NEMS fabrication processes. It is anticipated that this method will work for any kind of structural material from which MEMS/NEMS are or can be made.

Simulation of Novel NEMS Contact Switch Using MRTD with Alterable Steps

Directory of Open Access Journals (Sweden)

Wen-Ge Yu

2010-01-01

Full Text Available In order to apply Radio Frequency Micro-nano-Electro-Mechanical System (MEMS/NEMS technologies to produce miniature, high isolation, low insertion loss, good linear characteristic, and low power consumption microwave switches, we present a novel NEMS switch with nanoscaling in this paper through the analysis of electrics and mechanics of the RF switch. The measured data show the pull-in voltage of 24.1 V and the good RF performance of the insertion loss of below −10 dB at 0 GHz on the “on” state, and the isolation of beyond –40 dB at 0–40 GHz on the “off” state, indicating that the witch is suitable for the 0–40 GHz applications. Our analysis shows that the NEMS switch not only can work in wide frequency bands, but also has better isolation performance in lower frequency, thus extending the application to the lower band. The Haar-wavelet-based multiresolution time domain (MRTD with compactly supported scaling function is used for modeling and analyzing the nanomachine switch for the first time. The major advantage of the MRTD algorithms is their capability to develop real-time time and space adaptive grids through the efficient thresholding of the wavelet coefficients. The error between the measured and computed results is below 5%, this indicated that the Haar-wavelet-based multiresolution time domain was suitable for simulating the nano-scaling contact switch.

Design and analysis of compact ultra energy-efficient logic gates using laterally-actuated double-electrode NEMS

KAUST Repository

Dadgour, Hamed F.

2010-01-01

Nano-Electro-Mechanical Switches (NEMS) are among the most promising emerging devices due to their near-zero subthreshold-leakage currents. This paper reports device fabrication and modeling, as well as novel logic gate design using "laterally-actuated double-electrode NEMS" structures. The new device structure has several advantages over existing NEMS architectures such as being immune to impact bouncing and release vibrations (unlike a vertically-actuated NEMS) and offer higher flexibility to implement compact logic gates (unlike a single-electrode NEMS). A comprehensive analytical framework is developed to model different properties of these devices by solving the Euler-Bernoulli\\'s beam equation. The proposed model is validated using measurement data for the fabricated devices. It is shown that by ignoring the non-uniformity of the electrostatic force distribution, the existing models "underestimate" the actual value of Vpull-in and Vpull-out. Furthermore, novel energy efficient NEMS-based circuit topologies are introduced to implement compact inverter, NAND, NOR and XOR gates. For instance, the proposed XOR gate can be implemented by using only two NEMS devices compared to that of a static CMOS-based XOR gate that requires at least 10 transistors. © Copyright 2010 ACM.

Nanotechnology: MEMS and NEMS and their applications to smart systems and devices

Science.gov (United States)

Varadan, Vijay K.

2003-10-01

The microelectronics industry has seen explosive growth during the last thirty years. Extremely large markets for logic and memory devices have driven the development of new materials, and technologies for the fabrication of even more complex devices with features sizes now down at the sub micron and nanometer level. Recent interest has arisen in employing these materials, tools and technologies for the fabrication of miniature sensors and actuators and their integration with electronic circuits to produce smart devices and systems. This effort offers the promise of: (1) increasing the performance and manufacturability of both sensors and actuators by exploiting new batch fabrication processes developed including micro stereo lithographic and micro molding techniques; (2) developing novel classes of materials and mechanical structures not possible previously, such as diamond like carbon, silicon carbide and carbon nanotubes, micro-turbines and micro-engines; (3) development of technologies for the system level and wafer level integration of micro components at the nanometer precision, such as self-assembly techniques and robotic manipulation; (4) development of control and communication systems for MEMS devices, such as optical and RF wireless, and power delivery systems, etc. A novel composite structure can be tailored by functionalizing carbon nano tubes and chemically bonding them with the polymer matrix e.g. block or graft copolymer, or even cross-linked copolymer, to impart exceptional structural, electronic and surface properties. Bio- and Mechanical-MEMS devices derived from this hybrid composite provide a new avenue for future smart systems. The integration of NEMS (NanoElectroMechanical Systems), MEMS, IDTs (Interdigital Transducers) and required microelectronics and conformal antenna in the multifunctional smart materials and composites results in a smart system suitable for sending and control of a variety functions in automobile, aerospace, marine and

Effect of intermolecular force on the static/dynamic behaviour of M/NEM devices

Science.gov (United States)

Kim, Namjung; Aluru, N. R.

2014-12-01

Advances made in the fabrication of micro/nano-electromechanical (M/NEM) devices over the last ten years necessitate the understanding of the attractive force that arises from quantum fluctuations (generally referred to as Casimir effects) [Casimir H B G 1948 Proc. K. Ned. Akad. Wet. 51 793]. The fundamental mechanisms underlying quantum fluctuations have been actively investigated through various theoretical and experimental approaches. However, the effect of the force on M/NEM devices has not been fully understood yet, especially in the transition region involving gaps ranging from 10 nm to 1 μm, due to the complexity of the force. Here, we numerically calculate the Casimir effects in M/NEM devices by using the Lifshitz formula, the general expression for the Casimir effects [Lifshitz E 1956 Sov. Phys. JETP 2 73]. Since the Casimir effects are highly dependent on the permittivity of the materials, the Kramer-Kronig relation [Landau L D, Lifshitz E M and Pitaevskii L P 1984 Electrodynamics of Continuous Media (New York: Pergamon Press)] and the optical data for metals and dielectrics are used in order to obtain the permittivity. Several simplified models for the permittivity of the materials, such as the Drude and Lorentz models [Jackson J D 1975 Classical Electrodynamics (New York: Wiley)], are also used to extrapolate the optical data. Important characteristic values of M/NEM devices, such as the pull-in voltage, pull-in gap, detachment length, etc, are calculated for devices operating in the transition region. Our results show that accurate predictions for the pull-in behaviour are possible when the Lifshitz formula is used instead of the idealized expressions for Casimir effects. We expand this study into the dynamics of M/NEM devices, so that the time and frequency response of M/NEM devices with Casimir effects can be explored.

Effect of intermolecular force on the static/dynamic behaviour of M/NEM devices

International Nuclear Information System (INIS)

Kim, Namjung; Aluru, N R

2014-01-01

Advances made in the fabrication of micro/nano-electromechanical (M/NEM) devices over the last ten years necessitate the understanding of the attractive force that arises from quantum fluctuations (generally referred to as Casimir effects) [Casimir H B G 1948 Proc. K. Ned. Akad. Wet. 51 793]. The fundamental mechanisms underlying quantum fluctuations have been actively investigated through various theoretical and experimental approaches. However, the effect of the force on M/NEM devices has not been fully understood yet, especially in the transition region involving gaps ranging from 10 nm to 1 μm, due to the complexity of the force. Here, we numerically calculate the Casimir effects in M/NEM devices by using the Lifshitz formula, the general expression for the Casimir effects [Lifshitz E 1956 Sov. Phys. JETP 2 73]. Since the Casimir effects are highly dependent on the permittivity of the materials, the Kramer–Kronig relation [Landau L D, Lifshitz E M and Pitaevskii L P 1984 Electrodynamics of Continuous Media (New York: Pergamon Press)] and the optical data for metals and dielectrics are used in order to obtain the permittivity. Several simplified models for the permittivity of the materials, such as the Drude and Lorentz models [Jackson J D 1975 Classical Electrodynamics (New York: Wiley)], are also used to extrapolate the optical data. Important characteristic values of M/NEM devices, such as the pull-in voltage, pull-in gap, detachment length, etc, are calculated for devices operating in the transition region. Our results show that accurate predictions for the pull-in behaviour are possible when the Lifshitz formula is used instead of the idealized expressions for Casimir effects. We expand this study into the dynamics of M/NEM devices, so that the time and frequency response of M/NEM devices with Casimir effects can be explored. (paper)

Model documentation report: Industrial sector demand module of the National Energy Modeling System

International Nuclear Information System (INIS)

1997-01-01

This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Industrial Demand Model. The report catalogues and describes model assumptions, computational methodology, parameter estimation techniques, and model source code. This document serves three purposes. First, it is a reference document providing a detailed description of the NEMS Industrial Model for model analysts, users, and the public. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its models. Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements as future projects. The NEMS Industrial Demand Model is a dynamic accounting model, bringing together the disparate industries and uses of energy in those industries, and putting them together in an understandable and cohesive framework. The Industrial Model generates mid-term (up to the year 2015) forecasts of industrial sector energy demand as a component of the NEMS integrated forecasting system. From the NEMS system, the Industrial Model receives fuel prices, employment data, and the value of industrial output. Based on the values of these variables, the Industrial Model passes back to the NEMS system estimates of consumption by fuel types

Highly tunable NEMS shallow arches

KAUST Repository

Kazmi, Syed N. R.

2017-11-30

We report highly tunable nanoelectromechanical systems NEMS shallow arches under dc excitation voltages. Silicon based in-plane doubly clamped bridges, slightly curved as shallow arches, are fabricated using standard electron beam lithography and surface nanomachining of a highly conductive device layer on a silicon-on-insulator wafer. By designing the structures to have gap to thickness ratio of more than four, the mid-plane stretching of the nano arches is maximized such that an increase in the dc bias voltage will result into continuous increase in the resonance frequency of the resonators to wide ranges. This is confirmed analytically based on a nonlinear beam model. The experimental results are found to be in good agreement with that of the results from developed analytical model. A maximum tunability of 108.14% for a 180 nm thick arch with an initially designed gap of 1 μm between the beam and the driving/sensing electrodes is achieved. Furthermore, a tunable narrow bandpass filter is demonstrated, which opens up opportunities for designing such structures as filtering elements in high frequency ranges.

A new paradigm in the design of energy-efficient digital circuits using laterally-actuated double-gate NEMS

KAUST Repository

Dadgour, Hamed F.

2010-01-01

Nano-Electro-Mechanical Switches (NEMS) offer the prospect of improved energy-efficiency in digital circuits due to their near-zero subthreshold leakage and extremely low subthreshold swing values. Among the different approaches of implementing NEMS, laterallyactuated double-gate NEMS devices have attracted much attention as they provide unique and exciting circuit design opportunities. For instance, this paper demonstrates that compact XOR/XNOR gates can be implemented using only two such NEMS transistors. While this in itself is a major improvement, its implications for minimizing Boolean functions using Karnaugh maps (K-maps) are even more significant. In the standard K-map technique, which is used in digital circuit design, adjacent "1s" (minterms) are grouped only in horizontal and/or vertical directions; the diagonal (or zig-zag) grouping of adjacent "1s" is not an option due to the absence of compact XOR/XNOR gates. However, this work demonstrates, for the first time ever, that in lateral double-gate NEMS-based circuits, grouping of minterms is possible in horizontal and vertical as well as diagonal fashions. This is because the diagonal groupings of minterms require XOR/XNOR operations, which are available in such NEMS-based circuits at minimal costs. This novel design paradigm facilitates more compact implementations of Boolean functions and thus, considerably improves their energy-efficiency. For example, a lateral NEMS-based full-adder is implemented using less than half the number of transistors, which is required by a CMOS-based full-adder. Furthermore, circuit simulations are performed to evaluate the energy-efficiencies of the NEMS-based 32-bit carry-save adders compared to their standard CMOS-based counterparts. Copyright 2010 ACM.

Escherichia coli NemA is an efficient chromate reductase that can be biologically immobilized to provide a cell free system for remediation of hexavalent chromium.

Directory of Open Access Journals (Sweden)

Katherine J Robins

Full Text Available Hexavalent chromium is a serious and widespread environmental pollutant. Although many bacteria have been identified that can transform highly water-soluble and toxic Cr(VI to insoluble and relatively non-toxic Cr(III, bacterial bioremediation of Cr(VI pollution is limited by a number of issues, in particular chromium toxicity to the remediating cells. To address this we sought to develop an immobilized enzymatic system for Cr(VI remediation. To identify novel Cr(VI reductase enzymes we first screened cell extracts from an Escherichia coli library of soluble oxidoreductases derived from a range of bacteria, but found that a number of these enzymes can reduce Cr(VI indirectly, via redox intermediates present in the crude extracts. Instead, activity assays for 15 candidate enzymes purified as His6-tagged proteins identified E. coli NemA as a highly efficient Cr(VI reductase (k(cat/K(M= 1.1×10(5 M(-1 s(-1 with NADH as cofactor. Fusion of nemA to the polyhydroxyalkanoate synthase gene phaC from Ralstonia eutropha enabled high-level biosynthesis of functionalized polyhydroxyalkanoate granules displaying stable and active NemA on their surface. When these granules were combined with either Bacillus subtilis glucose dehydrogenase or Candida boidinii formate dehydrogenase as a cofactor regenerating partner, high levels of chromate transformation were observed with only low initial concentrations of expensive NADH cofactor being required, the overall reaction being powered by consumption of the cheap sacrificial substrates glucose or formic acid, respectively. This system therefore offers promise as an economic solution for ex situ Cr(VI remediation.

Back End of Line Nanorelays for Ultra-low Power Monolithic Integrated NEMS-CMOS Circuits

KAUST Repository

Lechuga Aranda, Jesus Javier

2016-05-01

Since the introduction of Complementary-Metal-Oxide-Semiconductor (CMOS) technology, the chip industry has enjoyed many benefits of transistor feature size scaling, including higher speed and device density and improved energy efficiency. However, in the recent years, the IC designers have encountered a few roadblocks, namely reaching the physical limits of scaling and also increased device leakage which has resulted in a slow-down of supply voltage and power density scaling. Therefore, there has been an extensive hunt for alternative circuit architectures and switching devices that can alleviate or eliminate the current crisis in the semiconductor industry. The Nano-Electro-Mechanical (NEM) relay is a promising alternative switch that offers zero leakage and abrupt turn-on behaviour. Even though these devices are intrinsically slower than CMOS transistors, new circuit design techniques tailored for the electromechanical properties of such devices can be leveraged to design medium performance, ultra-low power integrated circuits. In this thesis, we deal with a new generation of such devices that is built in the back end of line (BEOL) CMOS process and is an ideal option for full integration with current CMOS transistor technology. Simulation and verification at the circuit and system level is a critical step in the design flow of microelectronic circuits, and this is especially important for new technologies that lack the standard design infrastructure and well-known verification platforms. Although most of the physical and electrical properties of NEM structures can be simulated using standard electronic automation software, there is no report of a reliable behavioural model for NEMS switches that enable large circuit simulations. In this work, we present an optimised model of a BEOL nano relay that encompasses all the electromechanical characteristics of the device and is robust and lightweight enough for VLSI applications that require simulation of thousands of

Implementation of new capacities in TRAC-BF1/NEM for the simulation of transient with injection of boron; Implementacion de nuevas capacidades en TRAC-BF1/NEM para la simulacion de transitorios con inyeccion de Boro

Energy Technology Data Exchange (ETDEWEB)

Jambrina, A.; Barrachina, T.; Miro, R.; Verdu, G.

2011-07-01

This article is a step in the simulation of the injection, transport and mixing of boron in the reactor, increasing the capabilities of the TRACBF1/NEM code. This article presents the changes in the source code for TRACBF1/NEM, to be able to simulate the injection of boron in a more realistic way.

Model developer`s appendix to the model documentation report: NEMS macroeconomic activity module

Energy Technology Data Exchange (ETDEWEB)

NONE

1994-07-15

The NEMS Macroeconomic Activity Module (MAM) tested here was used to generate the Annual Energy Outlook 1994 (AEO94). MAM is a response surface model, not a structural model, composed of three submodules: the National Submodule, the Interindustry Submodule, and the Regional Submodule. Contents of this report are as follows: properties of the mathematical solution; NEMS MAM empirical basis; and scenario analysis. Scenario analysis covers: expectations for scenario analysis; historical world oil price scenario; AEO94 high world oil price scenario; AEO94 low world oil price scenario; and immediate increase world oil price scenario.

Least cost, utility scale abatement from Australia's NEM (National Electricity Market). Part 2: Scenarios and policy implications

International Nuclear Information System (INIS)

Brear, M.J.; Jeppesen, M.; Chattopadhyay, D.; Manzie, C.; Alpcan, T.; Dargaville, R.

2016-01-01

This paper is the second of a two part study that considers least cost, greenhouse gas abatement pathways for an electricity system. Part 1 of this study formulated a model for determining these abatement pathways, and applied this model to Australia's NEM (National Electricity Market) for a single reference scenario. Part 2 of this study applies this model to different scenarios and considers the policy implications. These include cases where nuclear power generation and CCS (carbon capture and storage) are implemented in Australia, which is presently not the case, as well as a more detailed examination of how an extended, RPS (renewable portfolio standard) might perform. The effect of future fuel costs and different discount rates are also examined. Several results from this study are thought to be significant. Most importantly, this study suggests that Australia already has utility scale technologies, renewable and non-renewable resources, an electricity market design and an abatement policy that permit continued progress towards deep greenhouse gas abatement in its electricity sector. In particular, a RPS (renewable portfolio standard) appears to be close to optimal as a greenhouse gas abatement policy for Australia's electricity sector for at least the next 10–15 years. - Highlights: • Considers scenarios and policy implications for Australia's NEM (National Electricity Market). • An extended form of RPS (renewable portfolio standard) appears near optimal until roughly 2030. • For up to 80% abatement, the inclusion of nuclear achieves only marginal benefit by 2050. • CCS (Carbon capture and storage) does not appear competitive with current cost estimates.

Model documentation, Coal Market Module of the National Energy Modeling System

Energy Technology Data Exchange (ETDEWEB)

NONE

1998-01-01

This report documents the objectives and the conceptual and methodological approach used in the development of the National Energy Modeling System`s (NEMS) Coal Market Module (CMM) used to develop the Annual Energy Outlook 1998 (AEO98). This report catalogues and describes the assumptions, methodology, estimation techniques, and source code of CMM`s two submodules. These are the Coal Production Submodule (CPS) and the Coal Distribution Submodule (CDS). CMM provides annual forecasts of prices, production, and consumption of coal for NEMS. In general, the CDS integrates the supply inputs from the CPS to satisfy demands for coal from exogenous demand models. The international area of the CDS forecasts annual world coal trade flows from major supply to major demand regions and provides annual forecasts of US coal exports for input to NEMS. Specifically, the CDS receives minemouth prices produced by the CPS, demand and other exogenous inputs from other NEMS components, and provides delivered coal prices and quantities to the NEMS economic sectors and regions.

Nanogenerators for self-powering nanosystems and piezotronics for smart MEMS/NEMS

KAUST Repository

Wang, Zhong Lin

2011-01-01

Two new fields are introduced to MEMS/NEMS: a nanogenerator that harvests mechanical energy for powering nanosystems, and strained induced piezotronics for smart MEMS. Fundamentally, due to the polarization of ions in a crystal that has non

Nonlinear iterative strategy for NEM refinement and extension

International Nuclear Information System (INIS)

Engrand, P.R.; Maldonado, G.I.; Al-Chalabi, R.; Turinsky, P.J.

1992-01-01

The work discussed in this paper is related to the nonlinear iterative strategy developed by Smith to solve the nodal expansion method (NEM) representation of the neutron diffusion equations. The authors show how it is possible to save computation time by taking advantage of the reducibility of the matrices that have to be inverted when employing this strategy. In addition, they show how this strategy can be adapted in an easy and efficient manner to time-dependent problems

Efecte de les tècniques de conreu en la producció del cànem (Cannabis sativa L.) i efecte del cànem com a cultiu precedent del blat (Triticum aestivum L.)

OpenAIRE

Gorchs i Altarriba, Gil

2006-01-01

El cànem (Cannabis sativa L.) és un cultiu que desperta en l'actualitat un gran interès per ser font de múltiples productes industrials renovables i tenir el perfil adequat per ajudar a establir sistemes agrícoles sostenibles, a més de ser un cultiu respectuós amb el medi ambient. L'objectiu principal d'aquesta tesi és estudiar agronòmicament diferents aspectes el cànem. En particular es pretén: i) estudiar l'efecte d'algunes tècniques culturals (adob nitrogenat, dosi sembra i data collita, a...

Novel Material Integration for Reliable and Energy-Efficient NEM Relay Technology

Science.gov (United States)

Chen, I.-Ru

Energy-efficient switching devices have become ever more important with the emergence of ubiquitous computing. NEM relays are promising to complement CMOS transistors as circuit building blocks for future ultra-low-power information processing, and as such have recently attracted significant attention from the semiconductor industry and researchers. Relay technology potentially can overcome the energy efficiency limit for conventional CMOS technology due to several key characteristics, including zero OFF-state leakage, abrupt switching behavior, and potentially very low active energy consumption. However, two key issues must be addressed for relay technology to reach its full potential: surface oxide formation at the contacting surfaces leading to increased ON-state resistance after switching, and high switching voltages due to strain gradient present within the relay structure. This dissertation advances NEM relay technology by investigating solutions to both of these pressing issues. Ruthenium, whose native oxide is conductive, is proposed as the contacting material to improve relay ON-state resistance stability. Ruthenium-contact relays are fabricated after overcoming several process integration challenges, and show superior ON-state resistance stability in electrical measurements and extended device lifetime. The relay structural film is optimized via stress matching among all layers within the structure, to provide lower strain gradient (below 10E-3/microm -1) and hence lower switching voltage. These advancements in relay technology, along with the integration of a metallic interconnect layer, enable complex relay-based circuit demonstration. In addition to the experimental efforts, this dissertation theoretically analyzes the energy efficiency limit of a NEM switch, which is generally believed to be limited by the surface adhesion energy. New compact (electronic device technology.

Hybrid of Natural Element Method (NEM with Genetic Algorithm (GA to find critical slip surface

Directory of Open Access Journals (Sweden)

Shahriar Shahrokhabadi

2014-06-01

Full Text Available One of the most important issues in geotechnical engineering is the slope stability analysis for determination of the factor of safety and the probable slip surface. Finite Element Method (FEM is well suited for numerical study of advanced geotechnical problems. However, mesh requirements of FEM creates some difficulties for solution processing in certain problems. Recently, motivated by these limitations, several new Meshfree methods such as Natural Element Method (NEM have been used to analyze engineering problems. This paper presents advantages of using NEM in 2D slope stability analysis and Genetic Algorithm (GA optimization to determine the probable slip surface and the related factor of safety. The stress field is produced under plane strain condition using natural element formulation to simulate material behavior analysis utilized in conjunction with a conventional limit equilibrium method. In order to justify the preciseness and convergence of the proposed method, two kinds of examples, homogenous and non-homogenous, are conducted and results are compared with FEM and conventional limit equilibrium methods. The results show the robustness of the NEM in slope stability analysis.

Knjiga in njen pomen v nemško govorečem pregnanstvu 1933–1945

Directory of Open Access Journals (Sweden)

Johann Georg Lughofer

2010-12-01

Full Text Available Članek skuša s pomočjo različnih literarnih odlomkov pokazati na pomembno mesto, ki ga je imela knjiga – kot objekt in subjekt – v literarni produkciji nemško govorečih pregnancev. Kot razloge za to obravnava funkcije literature kot so antifašistični boj, izobraževanje, dokumentiranje, terapija in samoterapija. Osredotoči se na sežiganja knjig v Nemčiji leta 1933 in pokaže, kako so ti zgodovinski dogodki iz knjige naredili simbol antifašističnega pregnanstva.

MC EMiNEM maps the interaction landscape of the Mediator

OpenAIRE

Niederberger, Theresa; Etzold, Stefanie; Lidschreiber, Michael; Maier, Kerstin C.; Martin, Dietmar E.; Fröhlich, Holger; Cramer, Patrick; Tresch, Achim

2012-01-01

The Mediator is a highly conserved, large multiprotein complex that is involved essentially in the regulation of eukaryotic mRNA transcription. It acts as a general transcription factor by integrating regulatory signals from gene-specific activators or repressors to the RNA Polymerase II. The internal network of interactions between Mediator subunits that conveys these signals is largely unknown. Here, we introduce MC EMiNEM, a novel method for the retrieval of functional dependencies between...

Non-linear iterative strategy for nem refinement and extension

International Nuclear Information System (INIS)

Engrand, P.R.; Maldonado, G.I.; Al-Chalabi, R.; Turinsky, P.J.

1994-10-01

The following work is related to the non-linear iterative strategy developed by K. Smith to solve the Nodal Expansion Method (NEM) representation of the neutron diffusion equations. We show how to improve this strategy and how to adapt it to time dependant problems. This work has been done in the NESTLE code, developed at North Carolina State University. When using Smith's strategy, one ends up with a two-node problem which corresponds to a matrix with a fixed structure and a size of 16 x 16 (for a 2 group representation). We show how to reduce this matrix into 2 equivalent systems which sizes are 4 x 4 and 8 x 8. The whole problem needs many of these 2 node problems solution. Therefore the gain in CPU time reaches 45% in the nodal part of the code. To adapt Smith's strategy to time dependent problems, the idea is to get the same structure of the 2 node problem system as in steady-state calculation. To achieve this, one has to approximate the values of the past time-step and of the previous by a second order polynomial and to treat it as a source term. We show here how to make this approximation consistent and accurate. (authors). 1 tab., 2 refs

TORC1 regulates Pah1 phosphatidate phosphatase activity via the Nem1/Spo7 protein phosphatase complex.

Directory of Open Access Journals (Sweden)

Emmanuelle Dubots

Full Text Available The evolutionarily conserved target of rapamycin complex 1 (TORC1 controls growth-related processes such as protein, nucleotide, and lipid metabolism in response to growth hormones, energy/ATP levels, and amino acids. Its deregulation is associated with cancer, type 2 diabetes, and obesity. Among other substrates, mammalian TORC1 directly phosphorylates and inhibits the phosphatidate phosphatase lipin-1, a central enzyme in lipid metabolism that provides diacylglycerol for the synthesis of membrane phospholipids and/or triacylglycerol as neutral lipid reserve. Here, we show that yeast TORC1 inhibits the function of the respective lipin, Pah1, to prevent the accumulation of triacylglycerol. Surprisingly, TORC1 regulates Pah1 in part indirectly by controlling the phosphorylation status of Nem1 within the Pah1-activating, heterodimeric Nem1-Spo7 protein phosphatase module. Our results delineate a hitherto unknown TORC1 effector branch that controls lipin function in yeast, which, given the recent discovery of Nem1-Spo7 orthologous proteins in humans, may be conserved.

A 2D/1D coupling neutron transport method based on the matrix MOC and NEM methods

International Nuclear Information System (INIS)

Zhang, H.; Zheng, Y.; Wu, H.; Cao, L.

2013-01-01

A new 2D/1D coupling method based on the matrix MOC method (MMOC) and nodal expansion method (NEM) is proposed for solving the three-dimensional heterogeneous neutron transport problem. The MMOC method, used for radial two-dimensional calculation, constructs a response matrix between source and flux with only one sweep and then solves the linear system by using the restarted GMRES algorithm instead of the traditional trajectory sweeping process during within-group iteration for angular flux update. Long characteristics are generated by using the customization of commercial software AutoCAD. A one-dimensional diffusion calculation is carried out in the axial direction by employing the NEM method. The 2D and ID solutions are coupled through the transverse leakage items. The 3D CMFD method is used to ensure the global neutron balance and adjust the different convergence properties of the radial and axial solvers. A computational code is developed based on these theories. Two benchmarks are calculated to verify the coupling method and the code. It is observed that the corresponding numerical results agree well with references, which indicates that the new method is capable of solving the 3D heterogeneous neutron transport problem directly. (authors)

A 2D/1D coupling neutron transport method based on the matrix MOC and NEM methods

Energy Technology Data Exchange (ETDEWEB)

Zhang, H.; Zheng, Y.; Wu, H.; Cao, L. [School of Nuclear Science and Technology, Xi' an Jiaotong University, No. 28, Xianning West Road, Xi' an, Shaanxi 710049 (China)

2013-07-01

A new 2D/1D coupling method based on the matrix MOC method (MMOC) and nodal expansion method (NEM) is proposed for solving the three-dimensional heterogeneous neutron transport problem. The MMOC method, used for radial two-dimensional calculation, constructs a response matrix between source and flux with only one sweep and then solves the linear system by using the restarted GMRES algorithm instead of the traditional trajectory sweeping process during within-group iteration for angular flux update. Long characteristics are generated by using the customization of commercial software AutoCAD. A one-dimensional diffusion calculation is carried out in the axial direction by employing the NEM method. The 2D and ID solutions are coupled through the transverse leakage items. The 3D CMFD method is used to ensure the global neutron balance and adjust the different convergence properties of the radial and axial solvers. A computational code is developed based on these theories. Two benchmarks are calculated to verify the coupling method and the code. It is observed that the corresponding numerical results agree well with references, which indicates that the new method is capable of solving the 3D heterogeneous neutron transport problem directly. (authors)

Nanogenerators for self-powering nanosystems and piezotronics for smart MEMS/NEMS

KAUST Repository

Wang, Zhong Lin

2011-01-01

Two new fields are introduced to MEMS/NEMS: a nanogenerator that harvests mechanical energy for powering nanosystems, and strained induced piezotronics for smart MEMS. Fundamentally, due to the polarization of ions in a crystal that has non-central symmetry, such as ZnO, GaN and InN, a piezoelectric potential (piezopotential) is created in the crystal by applying a stress. The principle of harvesting irregular mechanical energy by the nanogenerator relies on the piezopotenital driven transient flow of electrons in external load, which can be resulted from body motion, muscle stretching, breathing, tiny mechanical vibration/disturbance, sonic wave etc. As of today, a gentle straining can output 1-3 V at an instant output power of ∼2 μW from an integrated nanogenerator of a very thin sheet of 1 cm2 in size. This technology has the potential applications for power MEMS/NEMS that requires a power in the μW to mW range. Furthermore, we have replaced the externally applied gate voltage to a CMOS field effect transistor by the strain induced piezopotential as a "gate" voltage to tune/control the charge transport from source to drain. The devices fabricated by this principle are called piezotronics, with applications in strain/force/pressure triggered/controlled electronic devices, sensors and logic units.

Impact of scaling on the performance and reliability degradation of metal-contacts in NEMS devices

KAUST Repository

Dadgour, Hamed F.; Hussain, Muhammad Mustafa; Cassell, Alan M.; Singh, Navab R.; Banerjee, Kaustav

2011-01-01

thoroughly investigated in the literature. Such a study is essential because metal contacts play a critical role in determining the overall performance and reliability of NEMS. Therefore, the comprehensive analytical study presented in this paper highlights

Nanostructured 2D cellular materials in silicon by sidewall transfer lithography NEMS

Science.gov (United States)

Syms, Richard R. A.; Liu, Dixi; Ahmad, Munir M.

2017-07-01

Sidewall transfer lithography (STL) is demonstrated as a method for parallel fabrication of 2D nanostructured cellular solids in single-crystal silicon. The linear mechanical properties of four lattices (perfect and defected diamond; singly and doubly periodic honeycomb) with low effective Young’s moduli and effective Poisson’s ratio ranging from positive to negative are modelled using analytic theory and the matrix stiffness method with an emphasis on boundary effects. The lattices are fabricated with a minimum feature size of 100 nm and an aspect ratio of 40:1 using single- and double-level STL and deep reactive ion etching of bonded silicon-on-insulator. Nanoelectromechanical systems (NEMS) containing cellular materials are used to demonstrate stretching, bending and brittle fracture. Predicted edge effects are observed, theoretical values of Poisson’s ratio are verified and failure patterns are described.

Efecto del hidróxido de calcio sobre comunidades de nemátodos marinos

OpenAIRE

Cornejo, Mare

2003-01-01

Efecto del Hidróxido de Calcio sobre comunidades de nemátodos marinos El hidróxido de calcio es un compuesto químico utilizado para neutralizar la acidez del suelo e incrementar la alcalinidad total y la dureza total de los estanques de acuicultura pobremente tamponados.

PWR in-core nuclear fuel management optimization utilizing nodal (non-linear NEM) generalized perturbation theory

International Nuclear Information System (INIS)

Maldonado, G.I.; Turinsky, P.J.; Kropaczek, D.J.

1993-01-01

The computational capability of efficiently and accurately evaluate reactor core attributes (i.e., k eff and power distributions as a function of cycle burnup) utilizing a second-order accurate advanced nodal Generalized Perturbation Theory (GPT) model has been developed. The GPT model is derived from the forward non-linear iterative Nodal Expansion Method (NEM) strategy, thereby extending its inherent savings in memory storage and high computational efficiency to also encompass GPT via the preservation of the finite-difference matrix structure. The above development was easily implemented into the existing coarse-mesh finite-difference GPT-based in-core fuel management optimization code FORMOSA-P, thus combining the proven robustness of its adaptive Simulated Annealing (SA) multiple-objective optimization algorithm with a high-fidelity NEM GPT neutronics model to produce a powerful computational tool used to generate families of near-optimum loading patterns for PWRs. (orig.)

Design and analysis of compact ultra energy-efficient logic gates using laterally-actuated double-electrode NEMS

KAUST Repository

Dadgour, Hamed F.; Hussain, Muhammad Mustafa; Smith, Casey Eben; Banerjee, Kaustav

2010-01-01

Nano-Electro-Mechanical Switches (NEMS) are among the most promising emerging devices due to their near-zero subthreshold-leakage currents. This paper reports device fabrication and modeling, as well as novel logic gate design using "laterally

Nemški Pavliha im Vergleich zu seiner Vorlage Tyll Eulenspiegels wunderbare und seltsame Historien

Directory of Open Access Journals (Sweden)

Marija Javor Briški

2017-12-01

Full Text Available Unter Berücksichtigung des soziohistorischen Hintergrundes der Zielleser befasst sich der Beitrag auf inhaltlicher, struktureller, medialer und phraseologischer Ebene mit dem Vergleich der slowenischen Übersetzung Nemški Pavliha und seiner wiederentdeckten Vorlage Tyll Eulenspiegels wunderbare und seltsame Historien.

Resistencia antihelmíntica en los Nemátodos Gastrointestinales del bovino

OpenAIRE

Torres Vásquez, Patricia; Prada Sanmiguel, Germán Alonso; Márquez Lara, Dildo

2007-01-01

Los nemátodos gastrointestinales (NGI) en los animales domésticos, especialmente en los bovinos, son un factor muy importante que afecta su productividad ya que los sistemas de producción ganaderos han intervenido en la relación de los parásitos gastrointestinales (PGI) con los hospederos, lo cual ha llevado a que se rompa el equilibrio ecológico entre ambos. Esto se debe a que en muchas ocasiones se ha favorecido el desarrollo de las poblaciones parasitarias o en otras se ha tratado de lleva...

The Implementation of NEMS GFS Aerosol Component (NGAC) Version 1.0 for Global Dust Forecasting at NOAA NCEP

Science.gov (United States)

Lu, Cheng-Hsuan; Da Silva, Arlindo M.; Wang, Jun; Moorthi, Shrinivas; Chin, Mian; Colarco, Peter; Tang, Youhua; Bhattacharjee, Partha S.; Chen, Shen-Po; Chuang, Hui-Ya;

Natural gas transmission and distribution model of the National Energy Modeling System

International Nuclear Information System (INIS)

1997-02-01

The Natural Gas Transmission and Distribution Model (NGTDM) is the component of the National Energy Modeling System (NEMS) that is used to represent the domestic natural gas transmission and distribution system. NEMS was developed in the Office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA). NEMS is the third in a series of computer-based, midterm energy modeling systems used since 1974 by the EIA and its predecessor, the Federal Energy Administration, to analyze domestic energy-economy markets and develop projections. From 1982 through 1993, the Intermediate Future Forecasting System (IFFS) was used by the EIA for its analyses, and the Gas Analysis Modeling System (GAMS) was used within IFFS to represent natural gas markets. Prior to 1982, the Midterm Energy Forecasting System (MEFS), also referred to as the Project Independence Evaluation System (PIES), was employed. NEMS was developed to enhance and update EIA's modeling capability by internally incorporating models of energy markets that had previously been analyzed off-line. In addition, greater structural detail in NEMS permits the analysis of a broader range of energy issues. The time horizon of NEMS is the midterm period (i.e., through 2015). In order to represent the regional differences in energy markets, the component models of NEMS function at regional levels appropriate for the markets represented, with subsequent aggregation/disaggregation to the Census Division level for reporting purposes

Natural gas transmission and distribution model of the National Energy Modeling System

Energy Technology Data Exchange (ETDEWEB)

NONE

1997-02-01

The Natural Gas Transmission and Distribution Model (NGTDM) is the component of the National Energy Modeling System (NEMS) that is used to represent the domestic natural gas transmission and distribution system. NEMS was developed in the Office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA). NEMS is the third in a series of computer-based, midterm energy modeling systems used since 1974 by the EIA and its predecessor, the Federal Energy Administration, to analyze domestic energy-economy markets and develop projections. From 1982 through 1993, the Intermediate Future Forecasting System (IFFS) was used by the EIA for its analyses, and the Gas Analysis Modeling System (GAMS) was used within IFFS to represent natural gas markets. Prior to 1982, the Midterm Energy Forecasting System (MEFS), also referred to as the Project Independence Evaluation System (PIES), was employed. NEMS was developed to enhance and update EIA`s modeling capability by internally incorporating models of energy markets that had previously been analyzed off-line. In addition, greater structural detail in NEMS permits the analysis of a broader range of energy issues. The time horizon of NEMS is the midterm period (i.e., through 2015). In order to represent the regional differences in energy markets, the component models of NEMS function at regional levels appropriate for the markets represented, with subsequent aggregation/disaggregation to the Census Division level for reporting purposes.

Modeling of battery energy storage in the National Energy Modeling System

Energy Technology Data Exchange (ETDEWEB)

Swaminathan, S.; Flynn, W.T.; Sen, R.K. [Sentech, Inc., Bethesda, MD (United States)

1997-12-01

The National Energy Modeling System (NEMS) developed by the U.S. Department of Energy`s Energy Information Administration is a well-recognized model that is used to project the potential impact of new electric generation technologies. The NEMS model does not presently have the capability to model energy storage on the national grid. The scope of this study was to assess the feasibility of, and make recommendations for, the modeling of battery energy storage systems in the Electricity Market of the NEMS. Incorporating storage within the NEMS will allow the national benefits of storage technologies to be evaluated.

Model documentation Renewable Fuels Module of the National Energy Modeling System

Energy Technology Data Exchange (ETDEWEB)

NONE

1996-01-01

This report documents the objectives, analaytical approach and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the 1996 Annual Energy Outlook forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs, and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described.

Model documentation Coal Market Module of the National Energy Modeling System

Energy Technology Data Exchange (ETDEWEB)

NONE

1996-04-30

This report documents objectives and conceptual and methodological approach used in the development of the National Energy Modeling System (NEMS) Coal Market Module (CMM) used to develop the Annual Energy Outlook 1996 (AEO96). This report catalogues and describes the assumptions, methodology, estimation techniques, and source code of CMM`s three submodules: Coal Production Submodule, Coal Export Submodule, and Coal Distribution Submodule.

Transportation Sector Model of the National Energy Modeling System. Volume 1

Energy Technology Data Exchange (ETDEWEB)

NONE

1998-01-01

This report documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Transportation Model (TRAN). The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated by the model. The NEMS Transportation Model comprises a series of semi-independent models which address different aspects of the transportation sector. The primary purpose of this model is to provide mid-term forecasts of transportation energy demand by fuel type including, but not limited to, motor gasoline, distillate, jet fuel, and alternative fuels (such as CNG) not commonly associated with transportation. The current NEMS forecast horizon extends to the year 2010 and uses 1990 as the base year. Forecasts are generated through the separate consideration of energy consumption within the various modes of transport, including: private and fleet light-duty vehicles; aircraft; marine, rail, and truck freight; and various modes with minor overall impacts, such as mass transit and recreational boating. This approach is useful in assessing the impacts of policy initiatives, legislative mandates which affect individual modes of travel, and technological developments. The model also provides forecasts of selected intermediate values which are generated in order to determine energy consumption. These elements include estimates of passenger travel demand by automobile, air, or mass transit; estimates of the efficiency with which that demand is met; projections of vehicle stocks and the penetration of new technologies; and estimates of the demand for freight transport which are linked to forecasts of industrial output. Following the estimation of energy demand, TRAN produces forecasts of vehicular emissions of the following pollutants by source: oxides of sulfur, oxides of nitrogen, total carbon, carbon dioxide, carbon monoxide, and volatile organic compounds.

ERKEN DÖNEM YAHUDİ KAYNAKLARINA GÖRE TANAH’IN KANONİZE EDİLMESİ

Directory of Open Access Journals (Sweden)

Eldar HASANOĞLU HASANOĞLU

2015-12-01

Full Text Available Yahudi  kutsal  kitabı  Tanah’ın  standart  metin  haline  getirilmesi  süreç  içerisinde  gerçekleşmiştir. Erken dönem Yahudi kaynaklarında Tanah’ın içeriğiyle ilgili farklı görüşler geçmektedir. Yahudilikte kanon meselesi asırlar boyunca tartışma konusu olmamıştır. XIX. yüzyıldan itibaren kanonizasyonun ne zaman gerçekleştiği konusunda farklı görüşler dile getirilmiştir. Bir kitabın kanonik  listeye  alınması  sırasında  rabbiler  tarafından  dile  getirilen  söylemlerde  dinî,  mezhepsel  ve asabiyetçi  kaygıların  hâkim  olduğu  görülmektedir.  Bu  çalışmanın  amacı  erken  dönem  Yahudi kaynaklarda  Tanah’ın  standart  metni  ve  rabbilerin  kanon  algısı  meselelerini  tanıtmak,  XIX -XX. yüzyıla ait kanonizasyonla ilgili görüşleri sunmaktır. Sonuç kısmında kanonizasyonla ilgili kanaatimiz beyan edilmiştir.

A nonlinear complementarity approach for the national energy modeling system

International Nuclear Information System (INIS)

Gabriel, S.A.; Kydes, A.S.

1995-01-01

The National Energy Modeling System (NEMS) is a large-scale mathematical model that computes equilibrium fuel prices and quantities in the U.S. energy sector. At present, to generate these equilibrium values, NEMS sequentially solves a collection of linear programs and nonlinear equations. The NEMS solution procedure then incorporates the solutions of these linear programs and nonlinear equations in a nonlinear Gauss-Seidel approach. The authors describe how the current version of NEMS can be formulated as a particular nonlinear complementarity problem (NCP), thereby possibly avoiding current convergence problems. In addition, they show that the NCP format is equally valid for a more general form of NEMS. They also describe several promising approaches for solving the NCP form of NEMS based on recent Newton type methods for general NCPs. These approaches share the feature of needing to solve their direction-finding subproblems only approximately. Hence, they can effectively exploit the sparsity inherent in the NEMS NCP

Derivation of NEM2 affected human embryonic stem cell line Genea079

Directory of Open Access Journals (Sweden)

Biljana Dumevska

2016-03-01

Full Text Available The Genea079 human embryonic stem cell line was derived from a donated, fully commercially consented ART blastocyst, carrying compound heterozygous mutations in the NEB gene, exon 55 deletion & c.15110dupA, indicative of Nemaline Myopathy Type 2 (NEM2. Following ICM outgrowth on inactivated human feeders, karyotype was confirmed as 46, XY and STR analysis demonstrated a male Allele pattern. The hESC line had pluripotent cell morphology, 86% of cells expressed Nanog, 95% Oct4, 54% Tra1-60 and 98% SSEA4 and gave a PluriTest Pluripotency score of 30.25, Novelty of 1.21. The cell line was negative for Mycoplasma and visible contamination.

The implementation of NEMS GFS Aerosol Component (NGAC) Version 1.0 for global dust forecasting at NOAA/NCEP.

Science.gov (United States)

Lu, Cheng-Hsuan; da Silva, Arlindo; Wang, Jun; Moorthi, Shrinivas; Chin, Mian; Colarco, Peter; Tang, Youhua; Bhattacharjee, Partha S; Chen, Shen-Po; Chuang, Hui-Ya; Juang, Hann-Ming Henry; McQueen, Jeffery; Iredell, Mark

2016-01-01

The NOAA National Centers for Environmental Prediction (NCEP) implemented NEMS GFS Aerosol Component (NGAC) for global dust forecasting in collaboration with NASA Goddard Space Flight Center (GSFC). NGAC Version 1.0 has been providing 5 day dust forecasts at 1°×1° resolution on a global scale, once per day at 00:00 Coordinated Universal Time (UTC), since September 2012. This is the first global system capable of interactive atmosphere aerosol forecasting at NCEP. The implementation of NGAC V1.0 reflects an effective and efficient transitioning of NASA research advances to NCEP operations, paving the way for NCEP to provide global aerosol products serving a wide range of stakeholders as well as to allow the effects of aerosols on weather forecasts and climate prediction to be considered.

CMOS-NEMS Copper Switches Monolithically Integrated Using a 65 nm CMOS Technology

Directory of Open Access Journals (Sweden)

Jose Luis Muñoz-Gamarra

2016-02-01

Full Text Available This work demonstrates the feasibility to obtain copper nanoelectromechanical (NEMS relays using a commercial complementary metal oxide semiconductor (CMOS technology (ST 65 nm following an intra CMOS-MEMS approach. We report experimental demonstration of contact-mode nano-electromechanical switches obtaining low operating voltage (5.5 V, good ION/IOFF (103 ratio, abrupt subthreshold swing (4.3 mV/decade and minimum dimensions (3.50 μm × 100 nm × 180 nm, and gap of 100 nm. With these dimensions, the operable Cell area of the switch will be 3.5 μm (length × 0.2 μm (100 nm width + 100 nm gap = 0.7 μm2 which is the smallest reported one using a top-down fabrication approach.

Ženski pari moških poimenovanj v slovenskem knjižnem jeziku 16. stoletja

OpenAIRE

Merše, Majda

2018-01-01

V prispevku je zarisan obseg rabe feminativov v slovenskem knjižnem jeziku 16. stoletja. Predstavljene so osnovne pomenske skupine feminativov ter načini njihove tvorbe. Ženski pari moških poimenovanj so primerjalno z moškimi preverjeni glede pomenske skladnosti in glede pogostosti rabe. Predstavljene in vzročno pojasnjene so skupine samo moških in samo ženskih poimenovanj. Opozorjeno je tudi na način izbire zastopnikov skupin, sestavljenih iz moških in ženskih členov.

Model documentation report: Macroeconomic Activity Module (MAM) of the National Energy Modeling System

Energy Technology Data Exchange (ETDEWEB)

NONE

1997-02-01

This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Macroeconomic Activity Module (MAM) used to develop the Annual Energy Outlook for 1997 (AEO 97). The report catalogues and describes the module assumptions, computations, methodology, parameter estimation techniques, and mainframe source code. This document serves three purposes. First it is a reference document providing a detailed description of the NEMS MAM used for the AEO 1997 production runs for model analysts, users, and the public. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its models. Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements as future projects.

Nem tudo que reluz é ouro: turismo e conflitos

Directory of Open Access Journals (Sweden)

Andrea de Albuquerque Vianna

2015-07-01

Full Text Available O estudo objetiva uma reflexão acerca da ação dos movimentos socioambientais a partir dos conflitos provocados pelo turismo e a compreensão sobre as respostas dadas pela cidade às alterações a que é submetida, sendo estas, observações relevantes para ampliar o conhecimento sobre o tema. A análise da atividade turística e sua relação direta com a localidade que a acolhe é questão de grande importância para a compreensão dos impactos causados por ela, tanto no cotidiano dos moradores quanto nos aspectos concretos da cidade. Entretanto, fazer o caminho inverso, partindo da ação dos movimentos socioambientais em resposta às alterações urbanas decorrentes do turismo, certamente permite um aprofundamento na questão, revelando aspectos que ultrapassam os benefícios econômicos que a atividade supostamente proporcionaria a toda a cidade, uma vez que, quando o fator econômico se sobrepõe ao social, nem tudo que reluz é ouro.

Nuevos registros de nemátodes parásitos de animales de vida silvestre en el Perú

Directory of Open Access Journals (Sweden)

Manuel Tantaleán

2014-06-01

Full Text Available Se registran, por primera vez para el Perú, 4 especies de nemátodes: Dipetalonema graciliformis Freitas, 1964 parásito de Saguinus labiatus; Evaginuris branickii (McCiure, 1932 Quentín, 1973 de Dinomys branickii; Alaeuris caudatus (Lent & Freitas, 1948 de Iguana iguana y Serpinema amazonicus de Podocnemis expansa. También, se considera a Saguinus labiatus como un nuevo huésped para Dipetalonema graciliformis.

Model documentation: Renewable Fuels Module of the National Energy Modeling System

Energy Technology Data Exchange (ETDEWEB)

1994-04-01

This report documents the objectives, analytical approach, and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it related to the production of the 1994 Annual Energy Outlook (AEO94) forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs, and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described. This documentation report serves two purposes. First, it is a reference document for model analysts, model users, and the public interested in the construction and application of the RFM. Second, it meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its models. The RFM consists of six analytical submodules that represent each of the major renewable energy resources -- wood, municipal solid waste (MSW), solar energy, wind energy, geothermal energy, and alcohol fuels. Of these six, four are documented in the following chapters: municipal solid waste, wind, solar and biofuels. Geothermal and wood are not currently working components of NEMS. The purpose of the RFM is to define the technological and cost characteristics of renewable energy technologies, and to pass these characteristics to other NEMS modules for the determination of mid-term forecasted renewable energy demand.

Model documentation renewable fuels module of the National Energy Modeling System

Science.gov (United States)

1995-06-01

This report documents the objectives, analytical approach, and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the 1995 Annual Energy Outlook (AEO95) forecasts. The report catalogs and describes modeling assumptions, computational methodologies, data inputs, and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described. The RFM consists of six analytical submodules that represent each of the major renewable energy resources -- wood, municipal solid waste (MSW), solar energy, wind energy, geothermal energy, and alcohol fuels. The RFM also reads in hydroelectric facility capacities and capacity factors from a data file for use by the NEMS Electricity Market Module (EMM). The purpose of the RFM is to define the technological, cost, and resource size characteristics of renewable energy technologies. These characteristics are used to compute a levelized cost to be competed against other similarly derived costs from other energy sources and technologies. The competition of these energy sources over the NEMS time horizon determines the market penetration of these renewable energy technologies. The characteristics include available energy capacity, capital costs, fixed operating costs, variable operating costs, capacity factor, heat rate, construction lead time, and fuel product price.

Model documentation renewable fuels module of the National Energy Modeling System

Energy Technology Data Exchange (ETDEWEB)

NONE

1995-06-01

This report documents the objectives, analytical approach, and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the 1995 Annual Energy Outlook (AEO95) forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs, and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described. The RFM consists of six analytical submodules that represent each of the major renewable energy resources--wood, municipal solid waste (MSW), solar energy, wind energy, geothermal energy, and alcohol fuels. The RFM also reads in hydroelectric facility capacities and capacity factors from a data file for use by the NEMS Electricity Market Module (EMM). The purpose of the RFM is to define the technological, cost and resource size characteristics of renewable energy technologies. These characteristics are used to compute a levelized cost to be competed against other similarly derived costs from other energy sources and technologies. The competition of these energy sources over the NEMS time horizon determines the market penetration of these renewable energy technologies. The characteristics include available energy capacity, capital costs, fixed operating costs, variable operating costs, capacity factor, heat rate, construction lead time, and fuel product price.

Investigation of Procedures for Automatic Resonance Extraction from Noisy Transient Electromagnetics Data. Volume III. Translation of Prony’s Original Paper and Bibliography of Prony’s Method

Science.gov (United States)

1981-08-17

Van Blaricum, "On the Source of Parameter Bias in Prony’s Method," 1980 NEM Conference, Disneyland Hotel, August 1980. Auton, J.R., "An Unbiased...Method for the Estimation of the SEM Parameters of an Electromagnetic System," 1980 NEM Conference, Disneyland Hotel, August 1980. Auton, J.R. and M.L...34 1980 NEM Conference, Disneyland Hotel, August 5-7, 1980. Chuang, C.W. and D.L. Moffatt, "Complex Natural Responances of Radar Targets via Prony’s

Short-term differences in drug prices after implementation of the national essential medicines system: A case study in rural Jiangxi Province, China.

Science.gov (United States)

Wang, Junyong; Liu, Xia; Wang, Suzhen; Chen, Heli; Wang, Xun; Zhou, Wei; Wang, Li; Zhu, Yanchen; Zheng, Xianping; Hao, Mo

2015-01-01

China's 2009 national essential medicine system (NEMS) was designed to reduce prices through a zero-markup policy and a centralized bidding system. To analyze NEMS's short-term impact on drug prices, we estimated the retail and wholesale prices before and after the reform at health institutions in rural Jiangxi Province. We undertook two cross-sectional surveys of prices of 39 medicines in November 2008 and May 2010, calculated inflation adjusted prices, and used the Wilcoxon signed-rank and rank-sum tests to examine price changes at different health institutions. Retail prices at pilot (P health centers decreased significantly, whereas the declines at retail pharmacies (P = 0.57) and village clinics (P = 0.29) were insignificant. The decline at pilot township health centers was the largest, compared with other kinds of health institutions (P health institutions, the centralized bidding system was insufficient to lower wholesale prices. A drug price management system should be constructed to control medicine prices and a long-term price information system is needed to monitor price changes.

Graphitization in Carbon MEMS and Carbon NEMS

Science.gov (United States)

Sharma, Swati

Carbon MEMS (CMEMS) and Carbon NEMS (CNEMS) are an emerging class of miniaturized devices. Due to the numerous advantages such as scalable manufacturing processes, inexpensive and readily available precursor polymer materials, tunable surface properties and biocompatibility, carbon has become a preferred material for a wide variety of future sensing applications. Single suspended carbon nanowires (CNWs) integrated on CMEMS structures fabricated by electrospinning of SU8 photoresist on photolithographially patterned SU8 followed by pyrolysis are utilized for understanding the graphitization process in micro and nano carbon materials. These monolithic CNW-CMEMS structures enable the fabrication of very high aspect ratio CNWs of predefined length. The CNWs thus fabricated display core---shell structures having a graphitic shell with a glassy carbon core. The electrical conductivity of these CNWs is increased by about 100% compared to glassy carbon as a result of enhanced graphitization. We explore various tunable fabrication and pyrolysis parameters to improve graphitization in the resulting CNWs. We also suggest gas-sensing application of the thus fabricated single suspended CNW-CMEMS devices by using the CNW as a nano-hotplate for local chemical vapor deposition. In this thesis we also report on results from an optimization study of SU8 photoresist derived carbon electrodes. These electrodes were applied to the simultaneous detection of traces of Cd(II) and Pb(II) through anodic stripping voltammetry and detection limits as low as 0.7 and 0.8 microgL-1 were achieved. To further improve upon the electrochemical behavior of the carbon electrodes we elucidate a modified pyrolysis technique featuring an ultra-fast temperature ramp for obtaining bubbled porous carbon from lithographically patterned SU8. We conclude this dissertation by suggesting the possible future works on enhancing graphitization as well as on electrochemical applications

Electrohidrodinámica de cristales líquidos nemáticos

Directory of Open Access Journals (Sweden)

Rosalío F. Rodríguez

2001-01-01

Full Text Available Se presenta un formalismo analítico que permite describir una amplia variedad de fenómenos ópticos no lineales que ocurren cuando una onda electromagnética se propaga en un cristal líquido. A partir de propiedades termodinámicas y de simetría, primero se construye un conjunto cerrado de ecuaciones hidrodinámicas que proporcionan una descripción completa de la dinámica de un nemático de bajo peso molecular en ausencia de campos externos. Posteriormente, se incluye la presencia de un campo electromagnético externo que se propaga en el fluido. Se discute el carácter no lineal y acoplado de las ecuaciones y, para resolverlas, se propone un método iterativo de aproximaciones sistemáticas en términos de potencias de parámetros con una interpretación física precisa. Se concluye discutiendo las ventajas y limitaciones del punto de vista adoptado en este trabajo..

Carleman estimates for some elliptic systems

International Nuclear Information System (INIS)

Eller, M

2008-01-01

A Carleman estimate for a certain first order elliptic system is proved. The proof is elementary and does not rely on pseudo-differential calculus. This estimate is used to prove Carleman estimates for the isotropic Lame system as well as for the isotropic Maxwell system with C 1 coefficients

Árboles y nemátodos gastrointestinales en bovinos jóvenes: Un nuevo enfoque de las investigaciones Trees and gastrointestinal nematodes in young cattle: a new research approach

Directory of Open Access Journals (Sweden)

Mildrey Soca

2007-12-01

Full Text Available Con el objetivo de evaluar el comportamiento de los nemátodos gastrointestinales de los bovinos jóvenes en diferentes sistemas silvopastoriles, se desarrollaron en dos fases varias investigaciones que dieron origen a estos resultados: una etapa experimental en la Estación Experimental de Pastos y Forrajes "Indio Hatuey", y una etapa de validación de los resultados en las Empresas Pecuarias "El Cangre" y "Valle del Perú", en la provincia de La Habana. Los géneros de nemátodos encontrados, en orden de importancia, fueron: Haemonchus, Oesophagostomum, Trichostrongylus, Cooperia y Ostertagia, con valores de 60, 15, 13, 10 y 2%, respectivamente. El conteo fecal de huevos (CFH mostró diferencias significativas (PWith the objective of evaluating the behavior of the gastrointestinal nematodes of young cattle in different silvopastoral systems, several studies were developed in two stages which brought about these results: an experimental stage at the Experimental Station of Pastures and Forages "Indio Hatuey", and a stage of validation of the results in the Livestock Production Firms "El Cangre" and "Valle del Perú", in Havana province. The genera of nematodes found, in order of importance, were: Haemonchus, Oesophagostomum, Trichostrongylus, Cooperia and Ostertagia, with values of 60, 15, 13, 10 and 2%, respectively. The fecal count of eggs (FCE showed significant differences (P<0,01 from the second month of evaluation in favor of the silvopastoral. Estos resultados forman parte de la tesis presentada por la primera autora en opción al grado científico de Doctor en Ciencias Veterinarias, titulada "Los nemátodos gastrointestinales de los bovinos jóvenes. Comportamiento en los sistemas silvopastoriles cubanos". system (SS, with values below 600 epg, as compared to the system without trees in which it was maintained over 1 000 epg. No effects of the weight or the sex of the animals on this behavior were found. However, significant

Compact MEMS/NEMS characterization platform using a DVD optical pick-up unit with optical imaging function

DEFF Research Database (Denmark)

Chen, Ching-Hsiu; Liao, Hsien-Shun; Hwang, Ing-Shouh

2013-01-01

/NEMS samples and detection laser spot, which makes laser alignment on measurement target easier. The DVD OPU is used for detection of resonant frequency measurements of the samples. Working bandwidth and noise level of the OPU are 100 MHz and 1.3 pmHz"2, respectively. Furthermore, the OPU has a laser spot size...... of 560 run (full width at half maximum, FWHM), which is capable of measuring cantilevers and strings with sub-micron width. A homemade nano-scale resolution X-Y-Z positioner with working distances of 12, 12, 5 mm is responsible for laser-sample alignment. Both thermal and excited resonant frequencies...

Model documentation report: Commercial Sector Demand Module of the National Energy Modeling System

Energy Technology Data Exchange (ETDEWEB)

NONE

1998-01-01

This report documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Commercial Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components. The NEMS Commercial Sector Demand Module is a simulation tool based upon economic and engineering relationships that models commercial sector energy demands at the nine Census Division level of detail for eleven distinct categories of commercial buildings. Commercial equipment selections are performed for the major fuels of electricity, natural gas, and distillate fuel, for the major services of space heating, space cooling, water heating, ventilation, cooking, refrigeration, and lighting. The algorithm also models demand for the minor fuels of residual oil, liquefied petroleum gas, steam coal, motor gasoline, and kerosene, the renewable fuel sources of wood and municipal solid waste, and the minor services of office equipment. Section 2 of this report discusses the purpose of the model, detailing its objectives, primary input and output quantities, and the relationship of the Commercial Module to the other modules of the NEMS system. Section 3 of the report describes the rationale behind the model design, providing insights into further assumptions utilized in the model development process to this point. Section 3 also reviews alternative commercial sector modeling methodologies drawn from existing literature, providing a comparison to the chosen approach. Section 4 details the model structure, using graphics and text to illustrate model flows and key computations.

State estimation in networked systems

NARCIS (Netherlands)

Sijs, J.

2012-01-01

This thesis considers state estimation strategies for networked systems. State estimation refers to a method for computing the unknown state of a dynamic process by combining sensor measurements with predictions from a process model. The most well known method for state estimation is the Kalman

Low mass MEMS/NEMS switch for a substitute of CMOS transistor using single-walled carbon nanotube thin film

Science.gov (United States)

Jang, Min-Woo

psec switching delay and as low as a 3 V dc pull-in. From this we confirmed that the SWNT-based thin films have the potential to make fast MEMS switches with a low operation voltage due to its low mass density and high stiffness. However, the copolymer caused a serious reliability issue and a copolymer-free SWNT film deposition method was developed by replacing positive copolymer with a dispersion of positively functionalized SWNTs. The electrical and physical properties of pure single-walled carbon nanotube thin films deposited through a copolymer-free LbL self-assembly process are then discussed. The film thickness was proportional to the number of dipping cycles. The film resistivity was estimated as 2.19x10-3 Ω-cm after thermal treatments were performed. The estimated specific contact resistance to gold electrodes was 6.33x10-9 Ω-m2 from contact chain measurements. The fabricated 3-terminal MEMS switches using these films functioned as a beam for multiple switching cycles with a 4.5V pull-in voltage, which was operated like a 2-input NAND gate. The SWNT-based thin film switch is promising for a variety of applications to high-end nanoelectronics and high- performance MEMS/NEMS.

Çeşitli Ekmeklerin Protein, Yağ, Nem, Kül, Karbonhidrat ve Enerji Değerleri

Directory of Open Access Journals (Sweden)

Nilgün Karaağaoğlu

2015-02-01

Full Text Available Araştırma, Ankara il merkezinden elde edilen 33 ekmek üzerinde gerçekleştirilmiştir. Ekmeklerden alınan ikili veya üçlü örneklerde kül, nem, yağ ve azot (N tayini yapılmıştır. Analiz sonucunda elde edilen N miktarları, tahıl çeşitleri için önerilen katsayılar ile çarpılarak protein miktarları belirlenmiştir. Karbonhidrat ve enerji değerleri ise hesaplanarak bulunmuştur. Beyaz (BE, tam buğday ve köy (TE, kepekli (KE, yulaf (YE ve çavdar (ÇE olmak üzere 5 grupta toplanan ekmek çeşitlerinin protein miktarları arasındaki fark önemli bulunmamıştır (p>0.05. KE grubundaki ekmeklerin yağ miktarı en düşük düzeydedir ve YE ile TE grubundaki ekmeklerle arasındaki fark önemlidir (p<0.05. TE ve KE grubundaki ekmeklerdeki kül miktarı, BE grubundakilerden daha yüksektir (p<0.05. Sonuçlar, beyaz ekmeklerin yapımında kullanılan unlarda, öğütme sırasında kayıpların oluştuğunu göstermektedir. Tam buğday, kepekli, yulaf ve çavdar ekmekleri, içerdikleri diyet posası türleri ve miktarları da düşünüldüğünde, sağlık üzerindeki olumlu etkileri nedeniyle beyaz ekmeğe göre daha iyi seçeneklerdir.

Reliability Estimation for Digital Instrument/Control System

Energy Technology Data Exchange (ETDEWEB)

Yang, Yaguang; Sydnor, Russell [U.S. Nuclear Regulatory Commission, Washington, D.C. (United States)

2011-08-15

Digital instrumentation and controls (DI and C) systems are widely adopted in various industries because of their flexibility and ability to implement various functions that can be used to automatically monitor, analyze, and control complicated systems. It is anticipated that the DI and C will replace the traditional analog instrumentation and controls (AI and C) systems in all future nuclear reactor designs. There is an increasing interest for reliability and risk analyses for safety critical DI and C systems in regulatory organizations, such as The United States Nuclear Regulatory Commission. Developing reliability models and reliability estimation methods for digital reactor control and protection systems will involve every part of the DI and C system, such as sensors, signal conditioning and processing components, transmission lines and digital communication systems, D/A and A/D converters, computer system, signal processing software, control and protection software, power supply system, and actuators. Some of these components are hardware, such as sensors and actuators, their failure mechanisms are well understood, and the traditional reliability model and estimation methods can be directly applied. But many of these components are firmware which has software embedded in the hardware, and software needs special consideration because its failure mechanism is unique, and the reliability estimation method for a software system will be different from the ones used for hardware systems. In this paper, we will propose a reliability estimation method for the entire DI and C system reliability using a recently developed software reliability estimation method and a traditional hardware reliability estimation method.

Reliability Estimation for Digital Instrument/Control System

International Nuclear Information System (INIS)

Yang, Yaguang; Sydnor, Russell

2011-01-01

Digital instrumentation and controls (DI and C) systems are widely adopted in various industries because of their flexibility and ability to implement various functions that can be used to automatically monitor, analyze, and control complicated systems. It is anticipated that the DI and C will replace the traditional analog instrumentation and controls (AI and C) systems in all future nuclear reactor designs. There is an increasing interest for reliability and risk analyses for safety critical DI and C systems in regulatory organizations, such as The United States Nuclear Regulatory Commission. Developing reliability models and reliability estimation methods for digital reactor control and protection systems will involve every part of the DI and C system, such as sensors, signal conditioning and processing components, transmission lines and digital communication systems, D/A and A/D converters, computer system, signal processing software, control and protection software, power supply system, and actuators. Some of these components are hardware, such as sensors and actuators, their failure mechanisms are well understood, and the traditional reliability model and estimation methods can be directly applied. But many of these components are firmware which has software embedded in the hardware, and software needs special consideration because its failure mechanism is unique, and the reliability estimation method for a software system will be different from the ones used for hardware systems. In this paper, we will propose a reliability estimation method for the entire DI and C system reliability using a recently developed software reliability estimation method and a traditional hardware reliability estimation method

Buzağılarda Preruminant Dönem Beslenmesinin Rumen Gelişimi Üzerine Etkisi

OpenAIRE

Gümüş, Erinç

2018-01-01

Beslenme, hızlı gelişen ve yüksek verime sahip hayvanların elde edilmesinde genetik faktörler kadar önem taşımaktadır. Buzağılarda, özellikle sütten kesim öncesinde sağlıklı bir rumen gelişimi sağlamak, hem kuru yem tüketimine geçişi hızlandırarak maliyeti azaltmada, hem de fizyolojik gelişimi hızlandırmada fayda sağlamaktadır. Buzağıların sütten kesim öncesi beslenmesinde katı gıdalar rumen gelişimi açısından büyük öneme sahiptir. Yapılan çalışmalarda konsantre yemlerin içerdikleri bütirik v...

MEMS- and NEMS-based complex adaptive smart devices and systems

Science.gov (United States)

Varadan, Vijay K.

2001-10-01

The microelectronics industry has seen explosive growth during the last thirty years. Extremely large markets for logic and memory devices have driven the development of new materials, and technologies for the fabrication of even more complex devices with feature sizes now down at the sub micron and nanometer level. Recent interest has arisen in employing these materials, tools and technologies for the fabrication of miniature sensors and actuators and their integration with electronic circuits to produce smart devices and systems. This effort offers the promise of: 1) increasing the performance and manufacturability of both sensors and actuators by exploiting new batch fabrication processes developed including micro stereo lithographic and micro molding techniques; 2) developing novel classes of materials and mechanical structures not possible previously, such as diamond like carbon, silicon carbide and carbon nanotubes, micro-turbines and micro-engines; 3) development of technologies for the system level and wafer level integration of micro components at the nanometer precision, such as self-assembly techniques and robotic manipulation; 4) development of control and communication systems for MEMS devices, such as optical and RF wireless, and power delivery systems, etc. A novel composite structure can be tailored by functionalizing carbon nanotubes and chemically bonding them with the polymer matrix e.g. block or graft copolymer, or even cross-linked copolymer, to impart exceptional structural, electronic and surface properties. Bio- and mechanical-MEMS devices derived from this hybrid composite provide a new avenue for future smart systems.

A new approach for modeling the peak utility impacts from a proposed CUAC standard

Energy Technology Data Exchange (ETDEWEB)

LaCommare, Kristina Hamachi; Gumerman, Etan; Marnay, Chris; Chan, Peter; Coughlin, Katie

2004-08-01

This report describes a new Berkeley Lab approach for modeling the likely peak electricity load reductions from proposed energy efficiency programs in the National Energy Modeling System (NEMS). This method is presented in the context of the commercial unitary air conditioning (CUAC) energy efficiency standards. A previous report investigating the residential central air conditioning (RCAC) load shapes in NEMS revealed that the peak reduction results were lower than expected. This effect was believed to be due in part to the presence of the squelch, a program algorithm designed to ensure changes in the system load over time are consistent with the input historic trend. The squelch applies a system load-scaling factor that scales any differences between the end-use bottom-up and system loads to maintain consistency with historic trends. To obtain more accurate peak reduction estimates, a new approach for modeling the impact of peaky end uses in NEMS-BT has been developed. The new approach decrements the system load directly, reducing the impact of the squelch on the final results. This report also discusses a number of additional factors, in particular non-coincidence between end-use loads and system loads as represented within NEMS, and their impacts on the peak reductions calculated by NEMS. Using Berkeley Lab's new double-decrement approach reduces the conservation load factor (CLF) on an input load decrement from 25% down to 19% for a SEER 13 CUAC trial standard level, as seen in NEMS-BT output. About 4 GW more in peak capacity reduction results from this new approach as compared to Berkeley Lab's traditional end-use decrement approach, which relied solely on lowering end use energy consumption. The new method has been fully implemented and tested in the Annual Energy Outlook 2003 (AEO2003) version of NEMS and will routinely be applied to future versions. This capability is now available for use in future end-use efficiency or other policy analysis

Control and estimation of piecewise affine systems

CERN Document Server

Xu, Jun

2014-01-01

As a powerful tool to study nonlinear systems and hybrid systems, piecewise affine (PWA) systems have been widely applied to mechanical systems. Control and Estimation of Piecewise Affine Systems presents several research findings relating to the control and estimation of PWA systems in one unified view. Chapters in this title discuss stability results of PWA systems, using piecewise quadratic Lyapunov functions and piecewise homogeneous polynomial Lyapunov functions. Explicit necessary and sufficient conditions for the controllability and reachability of a class of PWA systems are

Dose assessment of HeberNem to control of Meloidogyne incognita Chitwood in greenhouses

Directory of Open Access Journals (Sweden)

Mario Fleitas Díaz

2016-02-01

Full Text Available In the houses of protected crops Agricultural Company República Dominicana, Carlos Manuel de Céspedes municipality, Camagüey, an experiment was developed to evaluate different doses of bionematicide HeberNem in controlling the nematode Meloidogyne incognita Chitwood and his participation in the growth and development of the tomato (Solanum lycopersicum crop, the experimental design was in randomized blocks, the test was composed of 8 treatments replicated twice, evaluating a total of 40 plants for each treatment which were measured: plant height, stem diameter the number of leaflets, the number of clusters per plant, number of flowers per cluster and number of fruits per bunch, they were made weekly. Also at the end of the campaign took root degree determined according to the scale indicated by Zeck, (1971. Data were analyzed using analysis of variance and determined the levels of statistical significance at 5%, by dócima Tukey multiple range. We found an inverse relationship between the parameters of growth and development weighed against the presence of M. incognita Chitwood. At doses of 8 l / ha, 12 l / ha and 16 l / ha were achieved better results in controlling the nematode M. incognita Chitwood.

System and method for traffic signal timing estimation

KAUST Repository

Dumazert, Julien; Claudel, Christian G.

2015-01-01

A method and system for estimating traffic signals. The method and system can include constructing trajectories of probe vehicles from GPS data emitted by the probe vehicles, estimating traffic signal cycles, combining the estimates, and computing the traffic signal timing by maximizing a scoring function based on the estimates. Estimating traffic signal cycles can be based on transition times of the probe vehicles starting after a traffic signal turns green.

System and method for traffic signal timing estimation

KAUST Repository

Dumazert, Julien

2015-12-30

A method and system for estimating traffic signals. The method and system can include constructing trajectories of probe vehicles from GPS data emitted by the probe vehicles, estimating traffic signal cycles, combining the estimates, and computing the traffic signal timing by maximizing a scoring function based on the estimates. Estimating traffic signal cycles can be based on transition times of the probe vehicles starting after a traffic signal turns green.

New developments in state estimation for Nonlinear Systems

DEFF Research Database (Denmark)

Nørgård, Peter Magnus; Poulsen, Niels Kjølstad; Ravn, Ole

2000-01-01

Based on an interpolation formula, accurate state estimators for nonlinear systems can be derived. The estimators do not require derivative information which makes them simple to implement.; State estimators for nonlinear systems are derived based on polynomial approximations obtained with a mult......-known estimators, such as the extended Kalman filter (EKF) and its higher-order relatives, in most practical applications....

Enzyme II/sup Mtl/ of the Escherichia coli phosphoenolpyruvate-dependent phosphotransferase system: identification of the activity-linked cysteine on the mannitol carrier

International Nuclear Information System (INIS)

Pas, H.H.; Robillard, G.T.

1988-01-01

The cysteine of the membrane-bound mannitol-specific enzyme II (EII/sup Mtl/) of the Escherichia coli phosphoenolpyruvate-dependent phosphotransferase system have been labeled with 4-vinylpyridine. After proteolytic breakdown and reversed-phase HPLC, the peptides containing cysteines 110, 384, and 571 could be identified. N-Ethylmaleimide (NEM) treatment of the native unphosphorylated enzyme results in incorporation of one NEM label per molecule and loss of enzymatic activity. NEM treatment and inactivation prevented 4-vinylpyridine incorporation into the Cys-384-containing peptide, identifying this residue as the activity-linked cysteine. Both oxidation and phosphorylation of the native enzyme protected the enzyme against NEM labeling of Cys-384. Positive identification of the activity-linked cysteine was accomplished by inactivation with [ 14 C]iodoacetamide, proteolytic fragmentation, isolation of the peptide, and amino acid sequencing

Energy-Efficient Channel Estimation in MIMO Systems

Directory of Open Access Journals (Sweden)

2006-01-01

Full Text Available The emergence of MIMO communications systems as practical high-data-rate wireless communications systems has created several technical challenges to be met. On the one hand, there is potential for enhancing system performance in terms of capacity and diversity. On the other hand, the presence of multiple transceivers at both ends has created additional cost in terms of hardware and energy consumption. For coherent detection as well as to do optimization such as water filling and beamforming, it is essential that the MIMO channel is known. However, due to the presence of multiple transceivers at both the transmitter and receiver, the channel estimation problem is more complicated and costly compared to a SISO system. Several solutions have been proposed to minimize the computational cost, and hence the energy spent in channel estimation of MIMO systems. We present a novel method of minimizing the overall energy consumption. Unlike existing methods, we consider the energy spent during the channel estimation phase which includes transmission of training symbols, storage of those symbols at the receiver, and also channel estimation at the receiver. We develop a model that is independent of the hardware or software used for channel estimation, and use a divide-and-conquer strategy to minimize the overall energy consumption.

Fabrication of 3D Carbon Microelectromechanical Systems (C-MEMS).

Science.gov (United States)

Pramanick, Bidhan; Martinez-Chapa, Sergio O; Madou, Marc; Hwang, Hyundoo

2017-06-17

A wide range of carbon sources are available in nature, with a variety of micro-/nanostructure configurations. Here, a novel technique to fabricate long and hollow glassy carbon microfibers derived from human hairs is introduced. The long and hollow carbon structures were made by the pyrolysis of human hair at 900 °C in a N2 atmosphere. The morphology and chemical composition of natural and pyrolyzed human hairs were investigated using scanning electron microscopy (SEM) and electron-dispersive X-ray spectroscopy (EDX), respectively, to estimate the physical and chemical changes due to pyrolysis. Raman spectroscopy was used to confirm the glassy nature of the carbon microstructures. Pyrolyzed hair carbon was introduced to modify screen-printed carbon electrodes ; the modified electrodes were then applied to the electrochemical sensing of dopamine and ascorbic acid. Sensing performance of the modified sensors was improved as compared to the unmodified sensors. To obtain the desired carbon structure design, carbon micro-/nanoelectromechanical system (C-MEMS/C-NEMS) technology was developed. The most common C-MEMS/C-NEMS fabrication process consists of two steps: (i) the patterning of a carbon-rich base material, such as a photosensitive polymer, using photolithography; and (ii) carbonization through the pyrolysis of the patterned polymer in an oxygen-free environment. The C-MEMS/NEMS process has been widely used to develop microelectronic devices for various applications, including in micro-batteries, supercapacitors, glucose sensors, gas sensors, fuel cells, and triboelectric nanogenerators. Here, recent developments of a high-aspect ratio solid and hollow carbon microstructures with SU8 photoresists are discussed. The structural shrinkage during pyrolysis was investigated using confocal microscopy and SEM. Raman spectroscopy was used to confirm the crystallinity of the structure, and the atomic percentage of the elements present in the material before and after

MILITARY MISSION COMBAT EFFICIENCY ESTIMATION SYSTEM

Directory of Open Access Journals (Sweden)

Ighoyota B. AJENAGHUGHRURE

2017-04-01

Full Text Available Military infantry recruits, although trained, lacks experience in real-time combat operations, despite the combat simulations training. Therefore, the choice of including them in military operations is a thorough and careful process. This has left top military commanders with the tough task of deciding, the best blend of inexperienced and experienced infantry soldiers, for any military operation, based on available information on enemy strength and capability. This research project delves into the design of a mission combat efficiency estimator (MCEE. It is a decision support system that aids top military commanders in estimating the best combination of soldiers suitable for different military operations, based on available information on enemy’s combat experience. Hence, its advantages consist of reducing casualties and other risks that compromises the entire operation overall success, and also boosting the morals of soldiers in an operation, with such information as an estimation of combat efficiency of their enemies. The system was developed using Microsoft Asp.Net and Sql server backend. A case study test conducted with the MECEE system, reveals clearly that the MECEE system is an efficient tool for military mission planning in terms of team selection. Hence, when the MECEE system is fully deployed it will aid military commanders in the task of decision making on team members’ combination for any given operation based on enemy personnel information that is well known beforehand. Further work on the MECEE will be undertaken to explore fire power types and impact in mission combat efficiency estimation.

Model documentation: Natural gas transmission and distribution model of the National Energy Modeling System. Volume 1

International Nuclear Information System (INIS)

1995-01-01

The Natural Gas Transmission and Distribution Model (NGTDM) is the component of the National Energy Modeling System (NEMS) that is used to represent the domestic natural gas transmission and distribution system. NEMS was developed in the Office of integrated Analysis and Forecasting of the Energy information Administration (EIA). NEMS is the third in a series of computer-based, midterm energy modeling systems used since 1974 by the EIA and its predecessor, the Federal Energy Administration, to analyze domestic energy-economy markets and develop projections. The NGTDM is the model within the NEMS that represents the transmission, distribution, and pricing of natural gas. The model also includes representations of the end-use demand for natural gas, the production of domestic natural gas, and the availability of natural gas traded on the international market based on information received from other NEMS models. The NGTDM determines the flow of natural gas in an aggregate, domestic pipeline network, connecting domestic and foreign supply regions with 12 demand regions. The methodology employed allows the analysis of impacts of regional capacity constraints in the interstate natural gas pipeline network and the identification of pipeline capacity expansion requirements. There is an explicit representation of core and noncore markets for natural gas transmission and distribution services, and the key components of pipeline tariffs are represented in a pricing algorithm. Natural gas pricing and flow patterns are derived by obtaining a market equilibrium across the three main elements of the natural gas market: the supply element, the demand element, and the transmission and distribution network that links them. The NGTDM consists of four modules: the Annual Flow Module, the Capacity F-expansion Module, the Pipeline Tariff Module, and the Distributor Tariff Module. A model abstract is provided in Appendix A

Model documentation: Natural gas transmission and distribution model of the National Energy Modeling System. Volume 1

Energy Technology Data Exchange (ETDEWEB)

NONE

1995-02-17

The Natural Gas Transmission and Distribution Model (NGTDM) is the component of the National Energy Modeling System (NEMS) that is used to represent the domestic natural gas transmission and distribution system. NEMS was developed in the Office of integrated Analysis and Forecasting of the Energy information Administration (EIA). NEMS is the third in a series of computer-based, midterm energy modeling systems used since 1974 by the EIA and its predecessor, the Federal Energy Administration, to analyze domestic energy-economy markets and develop projections. The NGTDM is the model within the NEMS that represents the transmission, distribution, and pricing of natural gas. The model also includes representations of the end-use demand for natural gas, the production of domestic natural gas, and the availability of natural gas traded on the international market based on information received from other NEMS models. The NGTDM determines the flow of natural gas in an aggregate, domestic pipeline network, connecting domestic and foreign supply regions with 12 demand regions. The methodology employed allows the analysis of impacts of regional capacity constraints in the interstate natural gas pipeline network and the identification of pipeline capacity expansion requirements. There is an explicit representation of core and noncore markets for natural gas transmission and distribution services, and the key components of pipeline tariffs are represented in a pricing algorithm. Natural gas pricing and flow patterns are derived by obtaining a market equilibrium across the three main elements of the natural gas market: the supply element, the demand element, and the transmission and distribution network that links them. The NGTDM consists of four modules: the Annual Flow Module, the Capacity F-expansion Module, the Pipeline Tariff Module, and the Distributor Tariff Module. A model abstract is provided in Appendix A.

Natural Gas Transmission and Distribution Model of the National Energy Modeling System. Volume 1

Energy Technology Data Exchange (ETDEWEB)

NONE

1998-01-01

The Natural Gas Transmission and Distribution Model (NGTDM) is the component of the National Energy Modeling System (NEMS) that is used to represent the domestic natural gas transmission and distribution system. The NGTDM is the model within the NEMS that represents the transmission, distribution, and pricing of natural gas. The model also includes representations of the end-use demand for natural gas, the production of domestic natural gas, and the availability of natural gas traded on the international market based on information received from other NEMS models. The NGTDM determines the flow of natural gas in an aggregate, domestic pipeline network, connecting domestic and foreign supply regions with 12 demand regions. The purpose of this report is to provide a reference document for model analysts, users, and the public that defines the objectives of the model, describes its basic design, provides detail on the methodology employed, and describes the model inputs, outputs, and key assumptions. Subsequent chapters of this report provide: an overview of NGTDM; a description of the interface between the NEMS and NGTDM; an overview of the solution methodology of the NGTDM; the solution methodology for the Annual Flow Module; the solution methodology for the Distributor Tariff Module; the solution methodology for the Capacity Expansion Module; the solution methodology for the Pipeline Tariff Module; and a description of model assumptions, inputs, and outputs.

Vibrations of Elastic Systems With Applications to MEMS and NEMS

CERN Document Server

Magrab, Edward B

2012-01-01

This work presents a unified approach to the vibrations of elastic systems as applied to MEMS devices, mechanical components, and civil structures. Applications include atomic force microscopes, energy harvesters, and carbon nanotubes and consider such complicating effects as squeeze film damping, viscous fluid loading, in-plane forces, and proof mass interactions with their elastic supports. These effects are analyzed as single degree-of-freedom models and as more realistic elastic structures. The governing equations and boundary conditions for beams, plates, and shells with interior and boundary attachments are derived by applying variational calculus to an expression describing the energy of the system. The advantages of this approach regarding the generation of orthogonal functions and the Rayleigh-Ritz method are demonstrated. A large number of graphs and tables are given to show the impact of various factors on the systems’ natural frequencies, mode shapes, and responses.

Development of radioactivity estimation system considering radioactive nuclide movement

International Nuclear Information System (INIS)

Fukumura, Nobuo; Miyamoto, Yoshiaki

2010-01-01

A radioactivity estimation system considering radioactive nuclide movement is developed to integrate the established codes and the code system for decommissioning of sodium cooled fast reactor (FBR). The former are the codes for estimation of radioactivity movement in sodium coolant of fast reactor which are named SAFFIRE, PSYCHE and TTT. The latter code system is to estimate neutron irradiation activity (COSMARD-RRADO). It is paid special attention to keep the consistency of input data used among these codes and also the simplification of their interface. A new function is added to the estimation system, to estimate minor FP inventory caused by the fission of impurities contained in the coolant and slight fuel material attached on the fuel cladding. To check the evaluation system, the system is applied with radioactivity data of the preceding FBR such as BN-350, JOYO and Monju. Agreement between the analysis results and the measurement is well satisfactory. The uncertainty of the code system is within several tens per cent for the activation of primary coolant (Na-22) and factor of 2-4 for the estimation of radioactivity inventory in sodium coolant. (author)

Posture estimation system for underground mine vehicles

CSIR Research Space (South Africa)

Hlophe, K

2010-09-01

Full Text Available Page 1 of 8 25th International Conference of CAD/CAM, Robotics & Factories of the Future Conference, 13-16 July 2010, Pretoria, South Africa A POSTURE ESTIMATION SYSTEM FOR UNDERGROUND MINE VEHICLES Khonzumusa Hlophe1, Gideon Ferreira2... and the transmitter. The main difference between the three systems is their implementation. This paper describes an implementation of a posture estimation system for underground mine vehicles. The paper is organized as follows. In the next section, a brief...

Power system static state estimation using Kalman filter algorithm

Directory of Open Access Journals (Sweden)

Saikia Anupam

2016-01-01

Full Text Available State estimation of power system is an important tool for operation, analysis and forecasting of electric power system. In this paper, a Kalman filter algorithm is presented for static estimation of power system state variables. IEEE 14 bus system is employed to check the accuracy of this method. Newton Raphson load flow study is first carried out on our test system and a set of data from the output of load flow program is taken as measurement input. Measurement inputs are simulated by adding Gaussian noise of zero mean. The results of Kalman estimation are compared with traditional Weight Least Square (WLS method and it is observed that Kalman filter algorithm is numerically more efficient than traditional WLS method. Estimation accuracy is also tested for presence of parametric error in the system. In addition, numerical stability of Kalman filter algorithm is tested by considering inclusion of zero mean errors in the initial estimates.

A Comparative Study of Distribution System Parameter Estimation Methods

Energy Technology Data Exchange (ETDEWEB)

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

2016-07-17

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

Introduction to State Estimation of High-Rate System Dynamics.

Science.gov (United States)

Hong, Jonathan; Laflamme, Simon; Dodson, Jacob; Joyce, Bryan

2018-01-13

Engineering systems experiencing high-rate dynamic events, including airbags, debris detection, and active blast protection systems, could benefit from real-time observability for enhanced performance. However, the task of high-rate state estimation is challenging, in particular for real-time applications where the rate of the observer's convergence needs to be in the microsecond range. This paper identifies the challenges of state estimation of high-rate systems and discusses the fundamental characteristics of high-rate systems. A survey of applications and methods for estimators that have the potential to produce accurate estimations for a complex system experiencing highly dynamic events is presented. It is argued that adaptive observers are important to this research. In particular, adaptive data-driven observers are advantageous due to their adaptability and lack of dependence on the system model.

Performance estimates for personnel access control systems

International Nuclear Information System (INIS)

Bradley, R.G.

1980-10-01

Current performance estimates for personnel access control systems use estimates of Type I and Type II verification errors. A system performance equation which addresses normal operation, the insider, and outside adversary attack is developed. Examination of this equation reveals the inadequacy of classical Type I and II error evaluations which require detailed knowledge of the adversary threat scenario for each specific installation. Consequently, new performance measures which are consistent with the performance equation and independent of the threat are developed as an aid in selecting personnel access control systems

A Web-Based System for Bayesian Benchmark Dose Estimation.

Science.gov (United States)

Shao, Kan; Shapiro, Andrew J

2018-01-11

Benchmark dose (BMD) modeling is an important step in human health risk assessment and is used as the default approach to identify the point of departure for risk assessment. A probabilistic framework for dose-response assessment has been proposed and advocated by various institutions and organizations; therefore, a reliable tool is needed to provide distributional estimates for BMD and other important quantities in dose-response assessment. We developed an online system for Bayesian BMD (BBMD) estimation and compared results from this software with U.S. Environmental Protection Agency's (EPA's) Benchmark Dose Software (BMDS). The system is built on a Bayesian framework featuring the application of Markov chain Monte Carlo (MCMC) sampling for model parameter estimation and BMD calculation, which makes the BBMD system fundamentally different from the currently prevailing BMD software packages. In addition to estimating the traditional BMDs for dichotomous and continuous data, the developed system is also capable of computing model-averaged BMD estimates. A total of 518 dichotomous and 108 continuous data sets extracted from the U.S. EPA's Integrated Risk Information System (IRIS) database (and similar databases) were used as testing data to compare the estimates from the BBMD and BMDS programs. The results suggest that the BBMD system may outperform the BMDS program in a number of aspects, including fewer failed BMD and BMDL calculations and estimates. The BBMD system is a useful alternative tool for estimating BMD with additional functionalities for BMD analysis based on most recent research. Most importantly, the BBMD has the potential to incorporate prior information to make dose-response modeling more reliable and can provide distributional estimates for important quantities in dose-response assessment, which greatly facilitates the current trend for probabilistic risk assessment. https://doi.org/10.1289/EHP1289.

Estimation of Faults in DC Electrical Power System

Science.gov (United States)

Gorinevsky, Dimitry; Boyd, Stephen; Poll, Scott

2009-01-01

This paper demonstrates a novel optimization-based approach to estimating fault states in a DC power system. Potential faults changing the circuit topology are included along with faulty measurements. Our approach can be considered as a relaxation of the mixed estimation problem. We develop a linear model of the circuit and pose a convex problem for estimating the faults and other hidden states. A sparse fault vector solution is computed by using 11 regularization. The solution is computed reliably and efficiently, and gives accurate diagnostics on the faults. We demonstrate a real-time implementation of the approach for an instrumented electrical power system testbed, the ADAPT testbed at NASA ARC. The estimates are computed in milliseconds on a PC. The approach performs well despite unmodeled transients and other modeling uncertainties present in the system.

Dynamic state estimation assisted power system monitoring and protection

Science.gov (United States)

Cui, Yinan

The advent of phasor measurement units (PMUs) has unlocked several novel methods to monitor, control, and protect bulk electric power systems. This thesis introduces the concept of "Dynamic State Estimation" (DSE), aided by PMUs, for wide-area monitoring and protection of power systems. Unlike traditional State Estimation where algebraic variables are estimated from system measurements, DSE refers to a process to estimate the dynamic states associated with synchronous generators. This thesis first establishes the viability of using particle filtering as a technique to perform DSE in power systems. The utility of DSE for protection and wide-area monitoring are then shown as potential novel applications. The work is presented as a collection of several journal and conference papers. In the first paper, we present a particle filtering approach to dynamically estimate the states of a synchronous generator in a multi-machine setting considering the excitation and prime mover control systems. The second paper proposes an improved out-of-step detection method for generators by means of angular difference. The generator's rotor angle is estimated with a particle filter-based dynamic state estimator and the angular separation is then calculated by combining the raw local phasor measurements with this estimate. The third paper introduces a particle filter-based dual estimation method for tracking the dynamic states of a synchronous generator. It considers the situation where the field voltage measurements are not readily available. The particle filter is modified to treat the field voltage as an unknown input which is sequentially estimated along with the other dynamic states. The fourth paper proposes a novel framework for event detection based on energy functions. The key idea is that any event in the system will leave a signature in WAMS data-sets. It is shown that signatures for four broad classes of disturbance events are buried in the components that constitute the

Cost Estimation and Control for Flight Systems

Science.gov (United States)

Hammond, Walter E.; Vanhook, Michael E. (Technical Monitor)

2002-01-01

Good program management practices, cost analysis, cost estimation, and cost control for aerospace flight systems are interrelated and depend upon each other. The best cost control process cannot overcome poor design or poor systems trades that lead to the wrong approach. The project needs robust Technical, Schedule, Cost, Risk, and Cost Risk practices before it can incorporate adequate Cost Control. Cost analysis both precedes and follows cost estimation -- the two are closely coupled with each other and with Risk analysis. Parametric cost estimating relationships and computerized models are most often used. NASA has learned some valuable lessons in controlling cost problems, and recommends use of a summary Project Manager's checklist as shown here.

NASA Administrative Data Base Management Systems, 1984

Science.gov (United States)

Radosevich, J. D. (Editor)

1984-01-01

Strategies for converting to a data base management system (DBMS) and the implementation of the software packages necessary are discussed. Experiences with DBMS at various NASA centers are related including Langley's ADABAS/NATURAL and the NEMS subsystem of the NASA metrology informaton system. The value of the integrated workstation with a personal computer is explored.

Best-estimate analysis development for BWR systems

International Nuclear Information System (INIS)

Sutherland, W.A.; Alamgir, M.; Kalra, S.P.; Beckner, W.D.

1986-01-01

The Full Integral Simulation Test (FIST) Program is a three pronged approach to the development of best-estimate analysis capability for BWR systems. An experimental program in the FIST BWR system simulator facility extends the LOCA data base and adds operational transients data. An analytical method development program with the BWR-TRAC computer program extends the modeling of BWR specific components and major interfacing systems, and improves numerical techniques to reduce computer running time. A method qualification program tests TRAC-B against experiments run in the FIST facility and extends the results to reactor system applications. With the completion and integration of these three activities, the objective of a best-estimate analysis capability has been achieved. (author)

Algorithm of the managing systems state estimation

Directory of Open Access Journals (Sweden)

Skubilin M. D.

2010-02-01

Full Text Available The possibility of an electronic estimation of automatic and automated managing systems state is analyzed. An estimation of a current state (functional readiness of technical equipment and person-operator as integrated system allows to take operatively adequate measures on an exception and-or minimisation of consequences of system’s transition in a supernumerary state. The offered method is universal enough and can be recommended for normalisation of situations on transport, mainly in aircraft.

Estimating Dynamical Systems: Derivative Estimation Hints from Sir Ronald A. Fisher

Science.gov (United States)

Deboeck, Pascal R.

2010-01-01

The fitting of dynamical systems to psychological data offers the promise of addressing new and innovative questions about how people change over time. One method of fitting dynamical systems is to estimate the derivatives of a time series and then examine the relationships between derivatives using a differential equation model. One common…

Nano- and micro-electromechanical systems fundamentals of nano- and microengineering

CERN Document Server

Lyshevski, Sergey Edward

2005-01-01

NANOTECHNOLOGY AND MICROTECHNOLOGY (NANO- AND MICRO- SCIENCE, ENGINEERING AND TECHNOLOGY), AND BEYOND Introduction and Overview: From Micro- to Nano- and Beyond to Stringo-Scale Introductory Definitions to the Subjects Current Developments and Needs for Coherent Revolutionary Developments Societal Challenges and Implications NANO- AND MICROSCALE SYSTEMS, DEVICES, AND STRUCTURES Sizing Features: From Micro- to Nano-, and from Nano- to Stringo-Scale MEMS and NEMS Definitions Introduction to Taxonomy of Nano- and Microsystem Synthesis and Design Introduction to Design and Optimization of Nano- and Microsystems in the Behavioral Domain NANO- AND MICROSYSTEMS: CLASSIFICATION AND CONSIDERATION Biomimetics, Biological Analogies,and Design of NEMS and MEMS Micro- and Nanoelectromechanical Systems: Scaling Laws and Mathematical Modeling MEMS Examples and MEMS Architectures Introduction to Microfabrication and Micromachining FUNDAMENTALS OF MICROFABRICATION AND MEMS FABRICATION TECHNOLOGIES Introducti...

A Simulation-Based Soft Error Estimation Methodology for Computer Systems

OpenAIRE

Sugihara, Makoto; Ishihara, Tohru; Hashimoto, Koji; Muroyama, Masanori

2006-01-01

This paper proposes a simulation-based soft error estimation methodology for computer systems. Accumulating soft error rates (SERs) of all memories in a computer system results in pessimistic soft error estimation. This is because memory cells are used spatially and temporally and not all soft errors in them make the computer system faulty. Our soft-error estimation methodology considers the locations and the timings of soft errors occurring at every level of memory hierarchy and estimates th...

PROBABILISTIC ESTIMATION OF VIBRATION INFLUENCE ON SENSITIVE SYSTEM ELEMENTS

Directory of Open Access Journals (Sweden)

A. A. Lobaty

2009-01-01

Full Text Available The paper considers a problem pertaining to an estimation of vibration influence on sensitive system elements. Dependences of intensity and probability of a process exit characterizing a condition of a system element for the preset range that allow to estimate serviceability and no-failure operation of the system have been obtained analytically in the paper

System state estimation and optimal energy control framework for multicell lithium-ion battery system

International Nuclear Information System (INIS)

Wei, Jingwen; Dong, Guangzhong; Chen, Zonghai; Kang, Yu

2017-01-01

Highlights: • Employed a dual-scale EKF based estimator for in-pack cells’ SOC values. • Proposed a two-stage hybrid state-feedback and output-feedback equalization algorithm. • A switchable balance current mode is designed in the equalization topology. • Verified the performance of proposed method under two conditions. - Abstract: Cell variations caused by the inevitable inconsistency during manufacture and use of battery cells have significant impacts on battery capacity, security and durability for battery energy storage systems. Thus, the battery equalization systems are essentially required to reduce variations of in-pack cells and increase battery pack capability. In order to protect all in-pack cells from damaging, estimate battery state and reduce variations, a system state estimation and energy optimal control framework for multicell lithium-ion battery system is proposed. The state-of-charge (SOC) values of all in-pack cells are firstly estimated using a dual-scale extended Kalman filtering (EKF) to improve estimation accuracy and reduce computation simultaneously. These estimated SOC values provide specific details of battery system, which cannot only be used to protect cells from over-charging/over-discharging, but also be employed to design state-feedback controller for battery equalization system. A two-stage hybrid state-feedback and output-feedback equalization algorithm is proposed. The state-feedback controller is firstly employed for coarse-grained adjustment to reduce equalization time cost with large current. However, due to the inevitable SOC estimation errors, the output-feedback controller is then used for fine-grained adjustment with trickle current. Experimental results show that the proposed framework can provide an effectively estimation and energy control for multicell battery systems. Finally, the implementation of the proposed method is further discussed for the real applications.

Dependent systems reliability estimation by structural reliability approach

DEFF Research Database (Denmark)

Kostandyan, Erik; Sørensen, John Dalsgaard

2014-01-01

Estimation of system reliability by classical system reliability methods generally assumes that the components are statistically independent, thus limiting its applicability in many practical situations. A method is proposed for estimation of the system reliability with dependent components, where...... the leading failure mechanism(s) is described by physics of failure model(s). The proposed method is based on structural reliability techniques and accounts for both statistical and failure effect correlations. It is assumed that failure of any component is due to increasing damage (fatigue phenomena...... identification. Application of the proposed method can be found in many real world systems....

Integrating Unified Gravity Wave Physics into the NOAA Next Generation Global Prediction System

Science.gov (United States)

Alpert, J. C.; Yudin, V.; Fuller-Rowell, T. J.; Akmaev, R. A.

2017-12-01

The Unified Gravity Wave Physics (UGWP) project for the Next Generation Global Prediction System (NGGPS) is a NOAA collaborative effort between the National Centers for Environmental Prediction (NCEP), Environemntal Modeling Center (EMC) and the University of Colorado, Cooperative Institute for Research in Environmental Sciences (CU-CIRES) to support upgrades and improvements of GW dynamics (resolved scales) and physics (sub-grid scales) in the NOAA Environmental Modeling System (NEMS)†. As envisioned the global climate, weather and space weather models of NEMS will substantially improve their predictions and forecasts with the resolution-sensitive (scale-aware) formulations planned under the UGWP framework for both orographic and non-stationary waves. In particular, the planned improvements for the Global Forecast System (GFS) model of NEMS are: calibration of model physics for higher vertical and horizontal resolution and an extended vertical range of simulations, upgrades to GW schemes, including the turbulent heating and eddy mixing due to wave dissipation and breaking, and representation of the internally-generated QBO. The main priority of the UGWP project is unified parameterization of orographic and non-orographic GW effects including momentum deposition in the middle atmosphere and turbulent heating and eddies due to wave dissipation and breaking. The latter effects are not currently represented in NOAA atmosphere models. The team has tested and evaluated four candidate GW solvers integrating the selected GW schemes into the NGGPS model. Our current work and planned activity is to implement the UGWP schemes in the first available GFS/FV3 (open FV3) configuration including adapted GFDL modification for sub-grid orography in GFS. Initial global model results will be shown for the operational and research GFS configuration for spectral and FV3 dynamical cores. †http://www.emc.ncep.noaa.gov/index.php?branch=NEMS

Conventional estimating method of earthquake response of mechanical appendage system

International Nuclear Information System (INIS)

Aoki, Shigeru; Suzuki, Kohei

1981-01-01

Generally, for the estimation of the earthquake response of appendage structure system installed in main structure system, the method of floor response analysis using the response spectra at the point of installing the appendage system has been used. On the other hand, the research on the estimation of the earthquake response of appendage system by the statistical procedure based on probability process theory has been reported. The development of a practical method for simply estimating the response is an important subject in aseismatic engineering. In this study, the method of estimating the earthquake response of appendage system in the general case that the natural frequencies of both structure systems were different was investigated. First, it was shown that floor response amplification factor was able to be estimated simply by giving the ratio of the natural frequencies of both structure systems, and its statistical property was clarified. Next, it was elucidated that the procedure of expressing acceleration, velocity and displacement responses with tri-axial response spectra simultaneously was able to be applied to the expression of FRAF. The applicability of this procedure to nonlinear system was examined. (Kako, I.)

Channel estimation for physical layer network coding systems

CERN Document Server

Gao, Feifei; Wang, Gongpu

2014-01-01

This SpringerBrief presents channel estimation strategies for the physical later network coding (PLNC) systems. Along with a review of PLNC architectures, this brief examines new challenges brought by the special structure of bi-directional two-hop transmissions that are different from the traditional point-to-point systems and unidirectional relay systems. The authors discuss the channel estimation strategies over typical fading scenarios, including frequency flat fading, frequency selective fading and time selective fading, as well as future research directions. Chapters explore the performa

PWR system simulation and parameter estimation with neural networks

Energy Technology Data Exchange (ETDEWEB)

Akkurt, Hatice; Colak, Uener E-mail: uc@nuke.hacettepe.edu.tr

2002-11-01

A detailed nonlinear model for a typical PWR system has been considered for the development of simulation software. Each component in the system has been represented by appropriate differential equations. The SCILAB software was used for solving nonlinear equations to simulate steady-state and transient operational conditions. Overall system has been constructed by connecting individual components to each other. The validity of models for individual components and overall system has been verified. The system response against given transients have been analyzed. A neural network has been utilized to estimate system parameters during transients. Different transients have been imposed in training and prediction stages with neural networks. Reactor power and system reactivity during the transient event have been predicted by the neural network. Results show that neural networks estimations are in good agreement with the calculated response of the reactor system. The maximum errors are within {+-}0.254% for power and between -0.146 and 0.353% for reactivity prediction cases. Steam generator parameters, pressure and water level, are also successfully predicted by the neural network employed in this study. The noise imposed on the input parameters of the neural network deteriorates the power estimation capability whereas the reactivity estimation capability is not significantly affected.

PWR system simulation and parameter estimation with neural networks

International Nuclear Information System (INIS)

Akkurt, Hatice; Colak, Uener

2002-01-01

A detailed nonlinear model for a typical PWR system has been considered for the development of simulation software. Each component in the system has been represented by appropriate differential equations. The SCILAB software was used for solving nonlinear equations to simulate steady-state and transient operational conditions. Overall system has been constructed by connecting individual components to each other. The validity of models for individual components and overall system has been verified. The system response against given transients have been analyzed. A neural network has been utilized to estimate system parameters during transients. Different transients have been imposed in training and prediction stages with neural networks. Reactor power and system reactivity during the transient event have been predicted by the neural network. Results show that neural networks estimations are in good agreement with the calculated response of the reactor system. The maximum errors are within ±0.254% for power and between -0.146 and 0.353% for reactivity prediction cases. Steam generator parameters, pressure and water level, are also successfully predicted by the neural network employed in this study. The noise imposed on the input parameters of the neural network deteriorates the power estimation capability whereas the reactivity estimation capability is not significantly affected

Modeling and Parameter Estimation of a Small Wind Generation System

Directory of Open Access Journals (Sweden)

Carlos A. Ramírez Gómez

2013-11-01

Full Text Available The modeling and parameter estimation of a small wind generation system is presented in this paper. The system consists of a wind turbine, a permanent magnet synchronous generator, a three phase rectifier, and a direct current load. In order to estimate the parameters wind speed data are registered in a weather station located in the Fraternidad Campus at ITM. Wind speed data were applied to a reference model programed with PSIM software. From that simulation, variables were registered to estimate the parameters. The wind generation system model together with the estimated parameters is an excellent representation of the detailed model, but the estimated model offers a higher flexibility than the programed model in PSIM software.

Model documentation report: Transportation sector model of the National Energy Modeling System

Energy Technology Data Exchange (ETDEWEB)

1994-03-01

This report documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Transportation Model (TRAN). The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated by the model. This document serves three purposes. First, it is a reference document providing a detailed description of TRAN for model analysts, users, and the public. Second, this report meets the legal requirements of the Energy Information Administration (EIA) to provide adequate documentation in support of its statistical and forecast reports (Public Law 93-275, 57(b)(1)). Third, it permits continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements.

Teletactile System Based on Mechanical Properties Estimation

Directory of Open Access Journals (Sweden)

Mauro M. Sette

2011-01-01

Full Text Available Tactile feedback is a major missing feature in minimally invasive procedures; it is an essential means of diagnosis and orientation during surgical procedures. Previous works have presented a remote palpation feedback system based on the coupling between a pressure sensor and a general haptic interface. Here a new approach is presented based on the direct estimation of the tissue mechanical properties and finally their presentation to the operator by means of a haptic interface. The approach presents different technical difficulties and some solutions are proposed: the implementation of a fast Young’s modulus estimation algorithm, the implementation of a real time finite element model, and finally the implementation of a stiffness estimation approach in order to guarantee the system’s stability. The work is concluded with an experimental evaluation of the whole system.

Vision Aided State Estimation for Helicopter Slung Load System

DEFF Research Database (Denmark)

Bisgaard, Morten; Bendtsen, Jan Dimon; la Cour-Harbo, Anders

2007-01-01

This paper presents the design and verification of a state estimator for a helicopter based slung load system. The estimator is designed to augment the IMU driven estimator found in many helicopter UAV s and uses vision based updates only. The process model used for the estimator is a simple 4...

Estimating the state of large spatio-temporally chaotic systems

International Nuclear Information System (INIS)

Ott, E.; Hunt, B.R.; Szunyogh, I.; Zimin, A.V.; Kostelich, E.J.; Corazza, M.; Kalnay, E.; Patil, D.J.; Yorke, J.A.

2004-01-01

We consider the estimation of the state of a large spatio-temporally chaotic system from noisy observations and knowledge of a system model. Standard state estimation techniques using the Kalman filter approach are not computationally feasible for systems with very many effective degrees of freedom. We present and test a new technique (called a Local Ensemble Kalman Filter), generally applicable to large spatio-temporally chaotic systems for which correlations between system variables evaluated at different points become small at large separation between the points

UM OLHAR SOBRE O DIABETES NA INFÂNCIA E NA JUVENTUDE: NEM TODOS SÃO TIPO 1

Directory of Open Access Journals (Sweden)

ANGHEBEM-OLIVEIRA

2013-12-01

Full Text Available O Diabetes mellitus (DM é caracterizado como um quadro de hiperglicemia crônica, que com os anos causa disfunção endotelial e sérias complicações vasculares, como a retinopatia, nefropatia e o infarto agudo do miocárdio. À medida que a ciência avança na compreensão da fisiopatologia e das características clínico-laboratoriais do diabetes, sua classificação tem sido adaptada, justamente porque a correta classificação do diabetes vai impactará no prognóstico e tratamento do paciente. Atualmente, o diabetes é classificado em DM tipo 1, DM tipo 2, DM gestacional e Outros Tipos Específicos, que inclui a categoria MODY (do inglês, Maturity Onset Diabetes of the Young ou diabetes da maturidade com início na juventude. O que esta revisão pretende mostrar é quem nem todo diabetes diagnosticado na infância e na juventude é DM tipo 1

Power system frequency estimation based on an orthogonal decomposition method

Science.gov (United States)

Lee, Chih-Hung; Tsai, Men-Shen

2018-06-01

In recent years, several frequency estimation techniques have been proposed by which to estimate the frequency variations in power systems. In order to properly identify power quality issues under asynchronously-sampled signals that are contaminated with noise, flicker, and harmonic and inter-harmonic components, a good frequency estimator that is able to estimate the frequency as well as the rate of frequency changes precisely is needed. However, accurately estimating the fundamental frequency becomes a very difficult task without a priori information about the sampling frequency. In this paper, a better frequency evaluation scheme for power systems is proposed. This method employs a reconstruction technique in combination with orthogonal filters, which may maintain the required frequency characteristics of the orthogonal filters and improve the overall efficiency of power system monitoring through two-stage sliding discrete Fourier transforms. The results showed that this method can accurately estimate the power system frequency under different conditions, including asynchronously sampled signals contaminated by noise, flicker, and harmonic and inter-harmonic components. The proposed approach also provides high computational efficiency.

Model documentation renewable fuels module of the National Energy Modeling System

Energy Technology Data Exchange (ETDEWEB)

NONE

1997-04-01

This report documents the objectives, analytical approach, and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the 1997 Annual Energy Outlook forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs. and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described. This documentation report serves three purposes. First, it is a reference document for model analysts, model users, and the public interested in the construction and application of the RFM. Second, it meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its models. Finally, such documentation facilitates continuity in EIA model development by providing information sufficient to perform model enhancements and data updates as part of EIA`s ongoing mission to provide analytical and forecasting information systems.

Model documentation renewable fuels module of the National Energy Modeling System

International Nuclear Information System (INIS)

1997-04-01

This report documents the objectives, analytical approach, and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the 1997 Annual Energy Outlook forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs. and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described. This documentation report serves three purposes. First, it is a reference document for model analysts, model users, and the public interested in the construction and application of the RFM. Second, it meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its models. Finally, such documentation facilitates continuity in EIA model development by providing information sufficient to perform model enhancements and data updates as part of EIA's ongoing mission to provide analytical and forecasting information systems

Time-to-impact estimation in passive missile warning systems

Science.gov (United States)

Şahıngıl, Mehmet Cihan

2017-05-01

A missile warning system can detect the incoming missile threat(s) and automatically cue the other Electronic Attack (EA) systems in the suit, such as Directed Infrared Counter Measure (DIRCM) system and/or Counter Measure Dispensing System (CMDS). Most missile warning systems are currently based on passive sensor technology operating in either Solar Blind Ultraviolet (SBUV) or Midwave Infrared (MWIR) bands on which there is an intensive emission from the exhaust plume of the threatening missile. Although passive missile warning systems have some clear advantages over pulse-Doppler radar (PDR) based active missile warning systems, they show poorer performance in terms of time-to-impact (TTI) estimation which is critical for optimizing the countermeasures and also "passive kill assessment". In this paper, we consider this problem, namely, TTI estimation from passive measurements and present a TTI estimation scheme which can be used in passive missile warning systems. Our problem formulation is based on Extended Kalman Filter (EKF). The algorithm uses the area parameter of the threat plume which is derived from the used image frame.

View Estimation Based on Value System

Science.gov (United States)

Takahashi, Yasutake; Shimada, Kouki; Asada, Minoru

Estimation of a caregiver's view is one of the most important capabilities for a child to understand the behavior demonstrated by the caregiver, that is, to infer the intention of behavior and/or to learn the observed behavior efficiently. We hypothesize that the child develops this ability in the same way as behavior learning motivated by an intrinsic reward, that is, he/she updates the model of the estimated view of his/her own during the behavior imitated from the observation of the behavior demonstrated by the caregiver based on minimizing the estimation error of the reward during the behavior. From this view, this paper shows a method for acquiring such a capability based on a value system from which values can be obtained by reinforcement learning. The parameters of the view estimation are updated based on the temporal difference error (hereafter TD error: estimation error of the state value), analogous to the way such that the parameters of the state value of the behavior are updated based on the TD error. Experiments with simple humanoid robots show the validity of the method, and the developmental process parallel to young children's estimation of its own view during the imitation of the observed behavior of the caregiver is discussed.

MODELING THE DEMAND FOR E85 IN THE UNITED STATES

Energy Technology Data Exchange (ETDEWEB)

Liu, Changzheng [ORNL; Greene, David L [ORNL

2013-10-01

How demand for E85 might evolve in the future in response to changing economics and policies is an important subject to include in the National Energy Modeling System (NEMS). This report summarizes a study to develop an E85 choice model for NEMS. Using the most recent data from the states of Minnesota, North Dakota, and Iowa, this study estimates a logit model that represents E85 choice as a function of prices of E10 and E85, as well as fuel availability of E85 relative to gasoline. Using more recent data than previous studies allows a better estimation of non-fleet demand and indicates that the price elasticity of E85 choice appears to be higher than previously estimated. Based on the results of the econometric analysis, a model for projecting E85 demand at the regional level is specified. In testing, the model produced plausible predictions of US E85 demand to 2040.

Fuzzy filter for state estimation of a glucoregulatory system.

Science.gov (United States)

Trajanoski, Z; Wach, P

1996-08-01

A filter based on fuzzy logic for state estimation of a glucoregulatory system is presented. A published non-linear model for the dynamics of glucose and its hormonal control including a single glucose compartment, five insulin compartments and a glucagon compartment was used for simulation. The simulated data were corrupted by an additive white noise with zero mean and a coefficient of variation (CV) of between 2 and 20% and then submitted to the state estimation procedure using a fuzzy filter (FF). The performance of the FF was compared with an extended Kalman filter (EKF) for state estimation. Both the FF and the EKF were evaluated in the following cases: (a) five state variables are measurable; three plasma variables are measurable; only plasma glucose is measurable; (b) for different measurement noise levels (CV of 2-20%); and (c) a mismatch between the glucoregulatory system and the given mathematical model (uncertain or approximate model). In contrast to the FF, in the case of approximate model of the glucose system, the EKF failed to achieve useful state estimation. Moreover, the performance of the FF was independent of the noise level. In conclusion, the FF approach is a viable alternative for state estimation in a noisy environment and with an uncertain mathematical model of the glucoregulatory system.

Noise level estimation in weakly nonlinear slowly time-varying systems

International Nuclear Information System (INIS)

Aerts, J R M; Dirckx, J J J; Lataire, J; Pintelon, R

2008-01-01

Recently, a method using multisine excitation was proposed for estimating the frequency response, the nonlinear distortions and the disturbing noise of weakly nonlinear time-invariant systems. This method has been demonstrated on the measurement of nonlinear distortions in the vibration of acoustically driven systems such as a latex membrane, which is a good example of a time-invariant system [1]. However, not all systems are perfectly time invariant, e.g. biomechanical systems. This time variation can be misinterpreted as an elevated noise floor, and the classical noise estimation method gives a wrong result. Two improved methods to retrieve the correct noise information from the measurements are presented. Both of them make use of multisine excitations. First, it is demonstrated that the improved methods give the same result as the classical noise estimation method when applied to a time-invariant system (high-quality microphone membrane). Next, it is demonstrated that the new methods clearly give an improved estimate of the noise level on time-varying systems. As an application example results for the vibration response of an eardrum are shown

Statistical estimation Monte Carlo for unreliability evaluation of highly reliable system

International Nuclear Information System (INIS)

Xiao Gang; Su Guanghui; Jia Dounan; Li Tianduo

2000-01-01

Based on analog Monte Carlo simulation, statistical Monte Carlo methods for unreliable evaluation of highly reliable system are constructed, including direct statistical estimation Monte Carlo method and weighted statistical estimation Monte Carlo method. The basal element is given, and the statistical estimation Monte Carlo estimators are derived. Direct Monte Carlo simulation method, bounding-sampling method, forced transitions Monte Carlo method, direct statistical estimation Monte Carlo and weighted statistical estimation Monte Carlo are used to evaluate unreliability of a same system. By comparing, weighted statistical estimation Monte Carlo estimator has smallest variance, and has highest calculating efficiency

Attitude Estimation in Fractionated Spacecraft Cluster Systems

Science.gov (United States)

Hadaegh, Fred Y.; Blackmore, James C.

2011-01-01

An attitude estimation was examined in fractioned free-flying spacecraft. Instead of a single, monolithic spacecraft, a fractionated free-flying spacecraft uses multiple spacecraft modules. These modules are connected only through wireless communication links and, potentially, wireless power links. The key advantage of this concept is the ability to respond to uncertainty. For example, if a single spacecraft module in the cluster fails, a new one can be launched at a lower cost and risk than would be incurred with onorbit servicing or replacement of the monolithic spacecraft. In order to create such a system, however, it is essential to know what the navigation capabilities of the fractionated system are as a function of the capabilities of the individual modules, and to have an algorithm that can perform estimation of the attitudes and relative positions of the modules with fractionated sensing capabilities. Looking specifically at fractionated attitude estimation with startrackers and optical relative attitude sensors, a set of mathematical tools has been developed that specify the set of sensors necessary to ensure that the attitude of the entire cluster ( cluster attitude ) can be observed. Also developed was a navigation filter that can estimate the cluster attitude if these conditions are satisfied. Each module in the cluster may have either a startracker, a relative attitude sensor, or both. An extended Kalman filter can be used to estimate the attitude of all modules. A range of estimation performances can be achieved depending on the sensors used and the topology of the sensing network.

Asymptotic optimality of RESTART estimators in highly dependable systems

International Nuclear Information System (INIS)

Villén-Altamirano, J.

2014-01-01

We consider a wide class of models that includes the highly reliable Markovian systems (HRMS) often used to represent the evolution of multi-component systems in reliability settings. Repair times and component lifetimes are random variables that follow a general distribution, and the repair service adopts a priority repair rule based on system failure risk. Since crude simulation has proved to be inefficient for highly-dependable systems, the RESTART method is used for the estimation of steady-state unavailability and other reliability measures. In this method, a number of simulation retrials are performed when the process enters regions of the state space where the chance of occurrence of a rare event (e.g., a system failure) is higher. The main difficulty involved in applying this method is finding a suitable function, called the importance function, to define the regions. In this paper we introduce an importance function which, for unbalanced systems, represents a great improvement over the importance function used in previous papers. We also demonstrate the asymptotic optimality of RESTART estimators in these models. Several examples are presented to show the effectiveness of the new approach, and probabilities up to the order of 10 −42 are accurately estimated with little computational effort. - Highlights: • Rare event probabilities of highly reliable systems are estimated by simulation. • The asymptotic optimality of the application is proved. • A better importance function for highly reliable systems is provided in the paper

Inventory estimation for nuclear fuel reprocessing systems

International Nuclear Information System (INIS)

Beyerlein, A.L.; Geldard, J.F.

1987-01-01

The accuracy of nuclear material accounting methods for nuclear fuel reprocessing facilities is limited by nuclear material inventory variations in the solvent extraction contactors, which affect the separation and purification of uranium and plutonium. Since in-line methods for measuring contactor inventory are not available, simple inventory estimation models are being developed for mixer-settler contactors operating at steady state with a view toward improving the accuracy of nuclear material accounting methods for reprocessing facilities. The authors investigated the following items: (1) improvements in the utility of the inventory estimation models, (2) extension of improvements to inventory estimation for transient nonsteady-state conditions during, for example, process upset or throughput variations, and (3) development of simple inventory estimation models for reprocessing systems using pulsed columns

Fast skin dose estimation system for interventional radiology.

Science.gov (United States)

Takata, Takeshi; Kotoku, Jun'ichi; Maejima, Hideyuki; Kumagai, Shinobu; Arai, Norikazu; Kobayashi, Takenori; Shiraishi, Kenshiro; Yamamoto, Masayoshi; Kondo, Hiroshi; Furui, Shigeru

2018-03-01

To minimise the radiation dermatitis related to interventional radiology (IR), rapid and accurate dose estimation has been sought for all procedures. We propose a technique for estimating the patient skin dose rapidly and accurately using Monte Carlo (MC) simulation with a graphical processing unit (GPU, GTX 1080; Nvidia Corp.). The skin dose distribution is simulated based on an individual patient's computed tomography (CT) dataset for fluoroscopic conditions after the CT dataset has been segmented into air, water and bone based on pixel values. The skin is assumed to be one layer at the outer surface of the body. Fluoroscopic conditions are obtained from a log file of a fluoroscopic examination. Estimating the absorbed skin dose distribution requires calibration of the dose simulated by our system. For this purpose, a linear function was used to approximate the relation between the simulated dose and the measured dose using radiophotoluminescence (RPL) glass dosimeters in a water-equivalent phantom. Differences of maximum skin dose between our system and the Particle and Heavy Ion Transport code System (PHITS) were as high as 6.1%. The relative statistical error (2 σ) for the simulated dose obtained using our system was ≤3.5%. Using a GPU, the simulation on the chest CT dataset aiming at the heart was within 3.49 s on average: the GPU is 122 times faster than a CPU (Core i7-7700K; Intel Corp.). Our system (using the GPU, the log file, and the CT dataset) estimated the skin dose more rapidly and more accurately than conventional methods.

Channel estimation in few mode fiber mode division multiplexing transmission system

Science.gov (United States)

Hei, Yongqiang; Li, Li; Li, Wentao; Li, Xiaohui; Shi, Guangming

2018-03-01

It is abundantly clear that obtaining the channel state information (CSI) is of great importance for the equalization and detection in coherence receivers. However, to the best of the authors' knowledge, in most of the existing literatures, CSI is assumed to be perfectly known at the receiver. So far, few literature discusses the effects of imperfect CSI on MDM system performance caused by channel estimation. Motivated by that, in this paper, the channel estimation in few mode fiber (FMF) mode division multiplexing (MDM) system is investigated, in which two classical channel estimation methods, i.e., least square (LS) method and minimum mean square error (MMSE) method, are discussed with the assumption of the spatially white noise lumped at the receiver side of MDM system. Both the capacity and BER performance of MDM system affected by mode-dependent gain or loss (MDL) with different channel estimation errors have been studied. Simulation results show that the capacity and BER performance can be further deteriorated in MDM system by the channel estimation, and an 1e-3 variance of channel estimation error is acceptable in MDM system with 0-6 dB MDL values.

Conceptual Design of an Online Estimation System for Stigmergic Collaboration and Nodal Intelligence on Distributed DC Systems

Directory of Open Access Journals (Sweden)

DOORSAMY, W.

2017-05-01

Full Text Available The secondary level control of stand-alone distributed energy systems requires accurate online state information for effective coordination of its components. State estimation is possible through several techniques depending on the system's architecture and control philosophy. A conceptual design of an online state estimation system to provide nodal autonomy on DC systems is presented. The proposed estimation system uses local measurements - at each node - to obtain an aggregation of the system's state required for nodal self-control without the need for external communication with other nodes or a central controller. The recursive least-squares technique is used in conjunction with stigmergic collaboration to implement the state estimation system. Numerical results are obtained using a Matlab/Simulink model and experimentally validated in a laboratory setting. Results indicate that the proposed system provides accurate estimation and fast updating during both quasi-static and transient states.

Damping Estimation of Friction Systems in Random Vibrations

DEFF Research Database (Denmark)

Friis, Tobias; Katsanos, Evangelos; Amador, Sandro

Friction is one of the most efficient and economical mechanisms to reduce vibrations in structural mechanics. However, the estimation of the equivalent linear damping of the friction damped systems in experimental modal analysis and operational modal analysis can be adversely affected by several...... assumptions regarding the definition of the linear damping and the identification methods or may be lacking a meaningful interpretation of the damping. Along these lines, this project focuses on assessing the potential to estimate efficiently the equivalent linear damping of friction systems in random...

Generalized synchronization-based multiparameter estimation in modulated time-delayed systems

Science.gov (United States)

Ghosh, Dibakar; Bhattacharyya, Bidyut K.

2011-09-01

We propose a nonlinear active observer based generalized synchronization scheme for multiparameter estimation in time-delayed systems with periodic time delay. A sufficient condition for parameter estimation is derived using Krasovskii-Lyapunov theory. The suggested tool proves to be globally and asymptotically stable by means of Krasovskii-Lyapunov method. With this effective method, parameter identification and generalized synchronization of modulated time-delayed systems with all the system parameters unknown, can be achieved simultaneously. We restrict our study for multiple parameter estimation in modulated time-delayed systems with single state variable only. Theoretical proof and numerical simulation demonstrate the effectiveness and feasibility of the proposed technique. The block diagram of electronic circuit for multiple time delay system shows that the method is easily applicable in practical communication problems.

Virtual Estimator for Piecewise Linear Systems Based on Observability Analysis

Science.gov (United States)

Morales-Morales, Cornelio; Adam-Medina, Manuel; Cervantes, Ilse; Vela-Valdés and, Luis G.; García Beltrán, Carlos Daniel

2013-01-01

This article proposes a virtual sensor for piecewise linear systems based on observability analysis that is in function of a commutation law related with the system's outpu. This virtual sensor is also known as a state estimator. Besides, it presents a detector of active mode when the commutation sequences of each linear subsystem are arbitrary and unknown. For the previous, this article proposes a set of virtual estimators that discern the commutation paths of the system and allow estimating their output. In this work a methodology in order to test the observability for piecewise linear systems with discrete time is proposed. An academic example is presented to show the obtained results. PMID:23447007

4D Trajectory Estimation for Air Traffic Control Automation System Based on Hybrid System Theory

Directory of Open Access Journals (Sweden)

Xin-Min Tang

2012-03-01

Full Text Available To resolve the problem of future airspace management under great traffic flow and high density condition, 4D trajectory estimation has become one of the core technologies of the next new generation air traffic control automation system. According to the flight profile and the dynamics models of different aircraft types under different flight conditions, a hybrid system model that switches the aircraft from one flight stage to another with aircraft state changing continuously in one state is constructed. Additionally, air temperature and wind speed are used to modify aircraft true airspeed as well as ground speed, and the hybrid system evolution simulation is used to estimate aircraft 4D trajectory. The case study proves that 4D trajectory estimated through hybrid system model can image the flight dynamic states of aircraft and satisfy the needs of the planned flight altitude profile.KEY WORDSair traffic management, 4D trajectory estimation, hybrid system model, aircraft dynamic model

A tree biomass and carbon estimation system

Science.gov (United States)

Emily B. Schultz; Thomas G. Matney; Donald L. Grebner

2013-01-01

Appropriate forest management decisions for the developing woody biofuel and carbon credit markets require inventory and growth-and-yield systems reporting component tree dry weight biomass estimates. We have developed an integrated growth-and-yield and biomass/carbon calculator. The objective was to provide Mississippi’s State inventory system with bioenergy economic...

A generic method for estimating system reliability using Bayesian networks

International Nuclear Information System (INIS)

Doguc, Ozge; Ramirez-Marquez, Jose Emmanuel

2009-01-01

This study presents a holistic method for constructing a Bayesian network (BN) model for estimating system reliability. BN is a probabilistic approach that is used to model and predict the behavior of a system based on observed stochastic events. The BN model is a directed acyclic graph (DAG) where the nodes represent system components and arcs represent relationships among them. Although recent studies on using BN for estimating system reliability have been proposed, they are based on the assumption that a pre-built BN has been designed to represent the system. In these studies, the task of building the BN is typically left to a group of specialists who are BN and domain experts. The BN experts should learn about the domain before building the BN, which is generally very time consuming and may lead to incorrect deductions. As there are no existing studies to eliminate the need for a human expert in the process of system reliability estimation, this paper introduces a method that uses historical data about the system to be modeled as a BN and provides efficient techniques for automated construction of the BN model, and hence estimation of the system reliability. In this respect K2, a data mining algorithm, is used for finding associations between system components, and thus building the BN model. This algorithm uses a heuristic to provide efficient and accurate results while searching for associations. Moreover, no human intervention is necessary during the process of BN construction and reliability estimation. The paper provides a step-by-step illustration of the method and evaluation of the approach with literature case examples

A generic method for estimating system reliability using Bayesian networks

Energy Technology Data Exchange (ETDEWEB)

Doguc, Ozge [Stevens Institute of Technology, Hoboken, NJ 07030 (United States); Ramirez-Marquez, Jose Emmanuel [Stevens Institute of Technology, Hoboken, NJ 07030 (United States)], E-mail: jmarquez@stevens.edu

2009-02-15

This study presents a holistic method for constructing a Bayesian network (BN) model for estimating system reliability. BN is a probabilistic approach that is used to model and predict the behavior of a system based on observed stochastic events. The BN model is a directed acyclic graph (DAG) where the nodes represent system components and arcs represent relationships among them. Although recent studies on using BN for estimating system reliability have been proposed, they are based on the assumption that a pre-built BN has been designed to represent the system. In these studies, the task of building the BN is typically left to a group of specialists who are BN and domain experts. The BN experts should learn about the domain before building the BN, which is generally very time consuming and may lead to incorrect deductions. As there are no existing studies to eliminate the need for a human expert in the process of system reliability estimation, this paper introduces a method that uses historical data about the system to be modeled as a BN and provides efficient techniques for automated construction of the BN model, and hence estimation of the system reliability. In this respect K2, a data mining algorithm, is used for finding associations between system components, and thus building the BN model. This algorithm uses a heuristic to provide efficient and accurate results while searching for associations. Moreover, no human intervention is necessary during the process of BN construction and reliability estimation. The paper provides a step-by-step illustration of the method and evaluation of the approach with literature case examples.

Channel estimation in DFT-based offset-QAM OFDM systems.

Science.gov (United States)

Zhao, Jian

2014-10-20

Offset quadrature amplitude modulation (offset-QAM) orthogonal frequency division multiplexing (OFDM) exhibits enhanced net data rates compared to conventional OFDM, and reduced complexity compared to Nyquist FDM (N-FDM). However, channel estimation in discrete-Fourier-transform (DFT) based offset-QAM OFDM is different from that in conventional OFDM and requires particular study. In this paper, we derive a closed-form expression for the demultiplexed signal in DFT-based offset-QAM systems and show that although the residual crosstalk is orthogonal to the decoded signal, its existence degrades the channel estimation performance when the conventional least-square method is applied. We propose and investigate four channel estimation algorithms for offset-QAM OFDM that vary in terms of performance, complexity, and tolerance to system parameters. It is theoretically and experimentally shown that simple channel estimation can be realized in offset-QAM OFDM with the achieved performance close to the theoretical limit. This, together with the existing advantages over conventional OFDM and N-FDM, makes this technology very promising for optical communication systems.

Stochastic linear hybrid systems: Modeling, estimation, and application

Science.gov (United States)

Seah, Chze Eng

Hybrid systems are dynamical systems which have interacting continuous state and discrete state (or mode). Accurate modeling and state estimation of hybrid systems are important in many applications. We propose a hybrid system model, known as the Stochastic Linear Hybrid System (SLHS), to describe hybrid systems with stochastic linear system dynamics in each mode and stochastic continuous-state-dependent mode transitions. We then develop a hybrid estimation algorithm, called the State-Dependent-Transition Hybrid Estimation (SDTHE) algorithm, to estimate the continuous state and discrete state of the SLHS from noisy measurements. It is shown that the SDTHE algorithm is more accurate or more computationally efficient than existing hybrid estimation algorithms. Next, we develop a performance analysis algorithm to evaluate the performance of the SDTHE algorithm in a given operating scenario. We also investigate sufficient conditions for the stability of the SDTHE algorithm. The proposed SLHS model and SDTHE algorithm are illustrated to be useful in several applications. In Air Traffic Control (ATC), to facilitate implementations of new efficient operational concepts, accurate modeling and estimation of aircraft trajectories are needed. In ATC, an aircraft's trajectory can be divided into a number of flight modes. Furthermore, as the aircraft is required to follow a given flight plan or clearance, its flight mode transitions are dependent of its continuous state. However, the flight mode transitions are also stochastic due to navigation uncertainties or unknown pilot intents. Thus, we develop an aircraft dynamics model in ATC based on the SLHS. The SDTHE algorithm is then used in aircraft tracking applications to estimate the positions/velocities of aircraft and their flight modes accurately. Next, we develop an aircraft conformance monitoring algorithm to detect any deviations of aircraft trajectories in ATC that might compromise safety. In this application, the SLHS

Non-parametric estimation of the availability in a general repairable system

International Nuclear Information System (INIS)

Gamiz, M.L.; Roman, Y.

2008-01-01

This work deals with repairable systems with unknown failure and repair time distributions. We focus on the estimation of the instantaneous availability, that is, the probability that the system is functioning at a given time, which we consider as the most significant measure for evaluating the effectiveness of a repairable system. The estimation of the availability function is not, in general, an easy task, i.e., analytical techniques are difficult to apply. We propose a smooth estimation of the availability based on kernel estimator of the cumulative distribution functions (CDF) of the failure and repair times, for which the bandwidth parameters are obtained by bootstrap procedures. The consistency properties of the availability estimator are established by using techniques based on the Laplace transform

Non-parametric estimation of the availability in a general repairable system

Energy Technology Data Exchange (ETDEWEB)

Gamiz, M.L. [Departamento de Estadistica e I.O., Facultad de Ciencias, Universidad de Granada, Granada 18071 (Spain)], E-mail: mgamiz@ugr.es; Roman, Y. [Departamento de Estadistica e I.O., Facultad de Ciencias, Universidad de Granada, Granada 18071 (Spain)

2008-08-15

This work deals with repairable systems with unknown failure and repair time distributions. We focus on the estimation of the instantaneous availability, that is, the probability that the system is functioning at a given time, which we consider as the most significant measure for evaluating the effectiveness of a repairable system. The estimation of the availability function is not, in general, an easy task, i.e., analytical techniques are difficult to apply. We propose a smooth estimation of the availability based on kernel estimator of the cumulative distribution functions (CDF) of the failure and repair times, for which the bandwidth parameters are obtained by bootstrap procedures. The consistency properties of the availability estimator are established by using techniques based on the Laplace transform.

Increased accuracy of cost-estimation using product configuration systems

DEFF Research Database (Denmark)

Rasmussen, Jeppe Bredahl; Hvam, Lars; Mortensen, Niels Henrik

This article describes an approach for utilizing Product Configuration Systems (PCS) for quantifying project costs in project-based companies. It presents a case study demonstrating a method of quantifying costs in a way that makes it possible to configure cost- and time estimates. Piecework costs......, material costs and sub-supplier costs are used as principle cost elements and linked to structural and process elements to facilitate configuration. The cost data are used by the PCS to generate fast and accurate cost-estimates, quotations, time estimates and cost summaries. The described cost...... quantification principles have been used in a Scandinavian SME (Small and Medium-sized Enterprise) since the 90’s, but have since 2011 been adopted to be used in a configuration system. A longitudinal case study was conducted to compare cost and time-estimation accuracy before and after implementation. We...

Power system dynamic state estimation using prediction based evolutionary technique

International Nuclear Information System (INIS)

Basetti, Vedik; Chandel, Ashwani K.; Chandel, Rajeevan

2016-01-01

In this paper, a new robust LWS (least winsorized square) estimator is proposed for dynamic state estimation of a power system. One of the main advantages of this estimator is that it has an inbuilt bad data rejection property and is less sensitive to bad data measurements. In the proposed approach, Brown's double exponential smoothing technique has been utilised for its reliable performance at the prediction step. The state estimation problem is solved as an optimisation problem using a new jDE-self adaptive differential evolution with prediction based population re-initialisation technique at the filtering step. This new stochastic search technique has been embedded with different state scenarios using the predicted state. The effectiveness of the proposed LWS technique is validated under different conditions, namely normal operation, bad data, sudden load change, and loss of transmission line conditions on three different IEEE test bus systems. The performance of the proposed approach is compared with the conventional extended Kalman filter. On the basis of various performance indices, the results thus obtained show that the proposed technique increases the accuracy and robustness of power system dynamic state estimation performance. - Highlights: • To estimate the states of the power system under dynamic environment. • The performance of the EKF method is degraded during anomaly conditions. • The proposed method remains robust towards anomalies. • The proposed method provides precise state estimates even in the presence of anomalies. • The results show that prediction accuracy is enhanced by using the proposed model.

An Evaluation of the Automated Cost Estimating Integrated Tools (ACEIT) System

Science.gov (United States)

1989-09-01

C~4p DTIC S ELECTE fl JAN12 19 .1R ~OF S%. B -U AN EVALUATION OF THE AUTOMATED COST ESTIMATING INTEGRATED TOOLS ( ACEIT ) SYSTEM THESIS Caroline L...Ohio go 91 022 AFIT/GCA/LSQ/89S-5 AN EVALUATION OF THE AUTOMATED COST ESTIMATING INTEGRATED TOOLS ( ACEIT ) SYSTEM THESIS Caroline L. Hanson Major, USAF...Department of Defense. AFIT/GCA/LSQ/89S-5 AN EVALUATION OF THE AUTOMATED COST ESTIMATING INTEGRATED TOOLS ( ACEIT ) SYSTEM THESIS Presented to the

Fault-tolerant embedded system design and optimization considering reliability estimation uncertainty

International Nuclear Information System (INIS)

Wattanapongskorn, Naruemon; Coit, David W.

2007-01-01

In this paper, we model embedded system design and optimization, considering component redundancy and uncertainty in the component reliability estimates. The systems being studied consist of software embedded in associated hardware components. Very often, component reliability values are not known exactly. Therefore, for reliability analysis studies and system optimization, it is meaningful to consider component reliability estimates as random variables with associated estimation uncertainty. In this new research, the system design process is formulated as a multiple-objective optimization problem to maximize an estimate of system reliability, and also, to minimize the variance of the reliability estimate. The two objectives are combined by penalizing the variance for prospective solutions. The two most common fault-tolerant embedded system architectures, N-Version Programming and Recovery Block, are considered as strategies to improve system reliability by providing system redundancy. Four distinct models are presented to demonstrate the proposed optimization techniques with or without redundancy. For many design problems, multiple functionally equivalent software versions have failure correlation even if they have been independently developed. The failure correlation may result from faults in the software specification, faults from a voting algorithm, and/or related faults from any two software versions. Our approach considers this correlation in formulating practical optimization models. Genetic algorithms with a dynamic penalty function are applied in solving this optimization problem, and reasonable and interesting results are obtained and discussed

Estimation of temperature in micromaser-type systems

Science.gov (United States)

Farajollahi, B.; Jafarzadeh, M.; Rangani Jahromi, H.; Amniat-Talab, M.

2018-06-01

We address the estimation of the number of photons and temperature in a micromaser-type system with Fock state and thermal fields. We analyze the behavior of the quantum Fisher information (QFI) for both fields. In particular, we show that in the Fock state field model, the QFI for non-entangled initial state of the atoms increases monotonously with time, while for entangled initial state of the atoms, it shows oscillatory behavior, leading to non-Markovian dynamics. Moreover, it is observed that the QFI, entropy of entanglement and fidelity have collapse and revival behavior. Focusing on each period that the collapses and revivals occur, we see that the optimal points of the QFI and entanglement coincide. In addition, when one of the subsystems evolved state fidelity becomes maximum, the QFI also achieves its maximum. We also address the evolved fidelity versus the initial state as a good witness of non-Markovianity. Moreover, we interestingly find that the entropy of the composite system can be used as a witness of non-Markovian evolution of the subsystems. For the thermal field model, we similarly investigate the relation among the QFI associated with the temperature, von Neumann entropy, and fidelity. In particular, it is found that at the instants when the maximum values of the QFI are achieved, the entanglement between the two-qubit system and the environment is maximized while the entanglement between the probe and its environment is minimized. Moreover, we show that the thermometry may lead to optimal estimation of practical temperatures. Besides, extending our computation to the two-qubit system, we find that using a two-qubit probe generally leads to more effective estimation than the one-qubit scenario. Finally, we show that initial state entanglement plays a key role in the advent of non-Markovianity and determination of its strength in the composite system and its subsystems.

System health monitoring using multiple-model adaptive estimation techniques

Science.gov (United States)

Sifford, Stanley Ryan

Monitoring system health for fault detection and diagnosis by tracking system parameters concurrently with state estimates is approached using a new multiple-model adaptive estimation (MMAE) method. This novel method is called GRid-based Adaptive Parameter Estimation (GRAPE). GRAPE expands existing MMAE methods by using new techniques to sample the parameter space. GRAPE expands on MMAE with the hypothesis that sample models can be applied and resampled without relying on a predefined set of models. GRAPE is initially implemented in a linear framework using Kalman filter models. A more generalized GRAPE formulation is presented using extended Kalman filter (EKF) models to represent nonlinear systems. GRAPE can handle both time invariant and time varying systems as it is designed to track parameter changes. Two techniques are presented to generate parameter samples for the parallel filter models. The first approach is called selected grid-based stratification (SGBS). SGBS divides the parameter space into equally spaced strata. The second approach uses Latin Hypercube Sampling (LHS) to determine the parameter locations and minimize the total number of required models. LHS is particularly useful when the parameter dimensions grow. Adding more parameters does not require the model count to increase for LHS. Each resample is independent of the prior sample set other than the location of the parameter estimate. SGBS and LHS can be used for both the initial sample and subsequent resamples. Furthermore, resamples are not required to use the same technique. Both techniques are demonstrated for both linear and nonlinear frameworks. The GRAPE framework further formalizes the parameter tracking process through a general approach for nonlinear systems. These additional methods allow GRAPE to either narrow the focus to converged values within a parameter range or expand the range in the appropriate direction to track the parameters outside the current parameter range boundary

Estimation of single plane unbalance parameters of a rotor-bearing system using Kalman filtering based force estimation technique

Science.gov (United States)

Shrivastava, Akash; Mohanty, A. R.

2018-03-01

This paper proposes a model-based method to estimate single plane unbalance parameters (amplitude and phase angle) in a rotor using Kalman filter and recursive least square based input force estimation technique. Kalman filter based input force estimation technique requires state-space model and response measurements. A modified system equivalent reduction expansion process (SEREP) technique is employed to obtain a reduced-order model of the rotor system so that limited response measurements can be used. The method is demonstrated using numerical simulations on a rotor-disk-bearing system. Results are presented for different measurement sets including displacement, velocity, and rotational response. Effects of measurement noise level, filter parameters (process noise covariance and forgetting factor), and modeling error are also presented and it is observed that the unbalance parameter estimation is robust with respect to measurement noise.

Internal ellipsoidal estimates of reachable set of impulsive control systems

Energy Technology Data Exchange (ETDEWEB)

Matviychuk, Oksana G. [Institute of Mathematics and Mechanics, Russian Academy of Sciences, 16 S. Kovalevskaya str., Ekaterinburg, 620990, Russia and Ural Federal University, 19 Mira str., Ekaterinburg, 620002 (Russian Federation)

2014-11-18

A problem of estimating reachable sets of linear impulsive control system with uncertainty in initial data is considered. The impulsive controls in the dynamical system belong to the intersection of a special cone with a generalized ellipsoid both taken in the space of functions of bounded variation. Assume that an ellipsoidal state constraints are imposed. The algorithms for constructing internal ellipsoidal estimates of reachable sets for such control systems and numerical simulation results are given.

Simulation-based seismic loss estimation of seaport transportation system

International Nuclear Information System (INIS)

Ung Jin Na; Shinozuka, Masanobu

2009-01-01

Seaport transportation system is one of the major lifeline systems in modern society and its reliable operation is crucial for the well-being of the public. However, past experiences showed that earthquake damage to port components can severely disrupt terminal operation, and thus negatively impact on the regional economy. The main purpose of this study is to provide a methodology for estimating the effects of the earthquake on the performance of the operation system of a container terminal in seaports. To evaluate the economic loss of damaged system, an analytical framework is developed by integrating simulation models for terminal operation and fragility curves of port components in the context of seismic risk analysis. For this purpose, computerized simulation model is developed and verified with actual terminal operation records. Based on the analytical procedure to assess the seismic performance of the terminal, system fragility curves are also developed. This simulation-based loss estimation methodology can be used not only for estimating the seismically induced revenue loss but also serve as a decision-making tool to select specific seismic retrofit technique on the basis of benefit-cost analysis

A Mixed WLS Power System State Estimation Method Integrating a Wide-Area Measurement System and SCADA Technology

Directory of Open Access Journals (Sweden)

Tao Jin

2018-02-01

Full Text Available To address the issue that the phasor measurement units (PMUs of wide area measurement system (WAMS are not sufficient for static state estimation in most existing power systems, this paper proposes a mixed power system weighted least squares (WLS state estimation method integrating a wide-area measurement system and supervisory control and data acquisition (SCADA technology. The hybrid calculation model is established by incorporating phasor measurements (including the node voltage phasors and branch current phasors and the results of the traditional state estimator in a post-processing estimator. The performance assessment is discussed through setting up mathematical models of the distribution network. Based on PMU placement optimization and bias analysis, the effectiveness of the proposed method was proved to be accurate and reliable by simulations of different cases. Furthermore, emulating calculation shows this method greatly improves the accuracy and stability of the state estimation solution, compared with the traditional WLS state estimation.

Parameter estimation of Lorenz chaotic system using a hybrid swarm intelligence algorithm

International Nuclear Information System (INIS)

Lazzús, Juan A.; Rivera, Marco; López-Caraballo, Carlos H.

2016-01-01

A novel hybrid swarm intelligence algorithm for chaotic system parameter estimation is present. For this purpose, the parameters estimation on Lorenz systems is formulated as a multidimensional problem, and a hybrid approach based on particle swarm optimization with ant colony optimization (PSO–ACO) is implemented to solve this problem. Firstly, the performance of the proposed PSO–ACO algorithm is tested on a set of three representative benchmark functions, and the impact of the parameter settings on PSO–ACO efficiency is studied. Secondly, the parameter estimation is converted into an optimization problem on a three-dimensional Lorenz system. Numerical simulations on Lorenz model and comparisons with results obtained by other algorithms showed that PSO–ACO is a very powerful tool for parameter estimation with high accuracy and low deviations. - Highlights: • PSO–ACO combined particle swarm optimization with ant colony optimization. • This study is the first research of PSO–ACO to estimate parameters of chaotic systems. • PSO–ACO algorithm can identify the parameters of the three-dimensional Lorenz system with low deviations. • PSO–ACO is a very powerful tool for the parameter estimation on other chaotic system.

Parameter estimation of Lorenz chaotic system using a hybrid swarm intelligence algorithm

Energy Technology Data Exchange (ETDEWEB)

Lazzús, Juan A., E-mail: jlazzus@dfuls.cl; Rivera, Marco; López-Caraballo, Carlos H.

2016-03-11

A novel hybrid swarm intelligence algorithm for chaotic system parameter estimation is present. For this purpose, the parameters estimation on Lorenz systems is formulated as a multidimensional problem, and a hybrid approach based on particle swarm optimization with ant colony optimization (PSO–ACO) is implemented to solve this problem. Firstly, the performance of the proposed PSO–ACO algorithm is tested on a set of three representative benchmark functions, and the impact of the parameter settings on PSO–ACO efficiency is studied. Secondly, the parameter estimation is converted into an optimization problem on a three-dimensional Lorenz system. Numerical simulations on Lorenz model and comparisons with results obtained by other algorithms showed that PSO–ACO is a very powerful tool for parameter estimation with high accuracy and low deviations. - Highlights: • PSO–ACO combined particle swarm optimization with ant colony optimization. • This study is the first research of PSO–ACO to estimate parameters of chaotic systems. • PSO–ACO algorithm can identify the parameters of the three-dimensional Lorenz system with low deviations. • PSO–ACO is a very powerful tool for the parameter estimation on other chaotic system.

Nanomiemgel--a novel drug delivery system for topical application--in vitro and in vivo evaluation.

Directory of Open Access Journals (Sweden)

Jaganmohan Somagoni

Full Text Available The objective of this study was to formulate and evaluate a unique matrix mixture (nanomiemgel of nanomicelle and nanoemulsion containing aceclofenac and capsaicin using in vitro and in vivo analyses and to compare it to a marketed formulation (Aceproxyvon.Nanomicelles were prepared using Vitamin E TPGS by solvent evaporation method and nanoemulsion was prepared by high-pressure homogenization method. In vitro drug release and human skin permeation studies were performed and analyzed using HPLC. The efficiency of nanomiemgel as a delivery system was investigated using an imiquimod-induced psoriatic like plaque model developed in C57BL/6 mice.Atomic Force Microscopy images of the samples exhibited a globular morphology with an average diameter of 200, 250 and 220 nm for NMI, NEM and NMG, respectively. Nanomiemgel demonstrated a controlled release drug pattern and induced 2.02 and 1.97-fold more permeation of aceclofenac and capsaicin, respectively than Aceproxyvon through dermatomed human skin. Nanomiemgel also showed 2.94 and 2.09-fold greater Cmax of aceclofenac and capsaicin, respectively than Aceproxyvon in skin microdialysis study in rats. The PASI score, ear thickness and spleen weight of the imiquimod-induced psoriatic-like plaque model were significantly (p<0.05 reduced in NMG treated mice compared to free drug, NEM, NMI & Aceproxyvon.Using a new combination of two different drug delivery systems (NEM+NMI, the absorption of the combined system (NMG was found to be better than either of the individual drug delivery systems due to the utilization of the maximum possible paths of absorption available for that particular drug.

Power system low frequency oscillation mode estimation using wide area measurement systems

Directory of Open Access Journals (Sweden)

Papia Ray

2017-04-01

Full Text Available Oscillations in power systems are triggered by a wide variety of events. The system damps most of the oscillations, but a few undamped oscillations may remain which may lead to system collapse. Therefore low frequency oscillations inspection is necessary in the context of recent power system operation and control. Ringdown portion of the signal provides rich information of the low frequency oscillatory modes which has been taken into analysis. This paper provides a practical case study in which seven signal processing based techniques i.e. Prony Analysis (PA, Fast Fourier Transform (FFT, S-Transform (ST, Wigner-Ville Distribution (WVD, Estimation of Signal Parameters by Rotational Invariance Technique (ESPRIT, Hilbert-Huang Transform (HHT and Matrix Pencil Method (MPM were presented for estimating the low frequency modes in a given ringdown signal. Preprocessing of the signal is done by detrending. The application of the signal processing techniques is illustrated using actual wide area measurement systems (WAMS data collected from four different Phasor Measurement Unit (PMU i.e. Dadri, Vindyachal, Kanpur and Moga which are located near the recent disturbance event at the Northern Grid of India. Simulation results show that the seven signal processing technique (FFT, PA, ST, WVD, ESPRIT, HHT and MPM estimates two common oscillatory frequency modes (0.2, 0.5 from the raw signal. Thus, these seven techniques provide satisfactory performance in determining small frequency modes of the signal without losing its valuable property. Also a comparative study of the seven signal processing techniques has been carried out in order to find the best one. It was found that FFT and ESPRIT gives exact frequency modes as compared to other techniques, so they are recommended for estimation of low frequency modes. Further investigations were also carried out to estimate low frequency oscillatory mode with another case study of Eastern Interconnect Phasor Project

Accelerated maximum likelihood parameter estimation for stochastic biochemical systems

Directory of Open Access Journals (Sweden)

Daigle Bernie J

2012-05-01

Full Text Available Abstract Background A prerequisite for the mechanistic simulation of a biochemical system is detailed knowledge of its kinetic parameters. Despite recent experimental advances, the estimation of unknown parameter values from observed data is still a bottleneck for obtaining accurate simulation results. Many methods exist for parameter estimation in deterministic biochemical systems; methods for discrete stochastic systems are less well developed. Given the probabilistic nature of stochastic biochemical models, a natural approach is to choose parameter values that maximize the probability of the observed data with respect to the unknown parameters, a.k.a. the maximum likelihood parameter estimates (MLEs. MLE computation for all but the simplest models requires the simulation of many system trajectories that are consistent with experimental data. For models with unknown parameters, this presents a computational challenge, as the generation of consistent trajectories can be an extremely rare occurrence. Results We have developed Monte Carlo Expectation-Maximization with Modified Cross-Entropy Method (MCEM2: an accelerated method for calculating MLEs that combines advances in rare event simulation with a computationally efficient version of the Monte Carlo expectation-maximization (MCEM algorithm. Our method requires no prior knowledge regarding parameter values, and it automatically provides a multivariate parameter uncertainty estimate. We applied the method to five stochastic systems of increasing complexity, progressing from an analytically tractable pure-birth model to a computationally demanding model of yeast-polarization. Our results demonstrate that MCEM2 substantially accelerates MLE computation on all tested models when compared to a stand-alone version of MCEM. Additionally, we show how our method identifies parameter values for certain classes of models more accurately than two recently proposed computationally efficient methods

PSF Estimation of Space-Variant Ultra-Wide Field of View Imaging Systems

Directory of Open Access Journals (Sweden)

Petr Janout

2017-02-01

Full Text Available Ultra-wide-field of view (UWFOV imaging systems are affected by various aberrations, most of which are highly angle-dependent. A description of UWFOV imaging systems, such as microscopy optics, security camera systems and other special space-variant imaging systems, is a difficult task that can be achieved by estimating the Point Spread Function (PSF of the system. This paper proposes a novel method for modeling the space-variant PSF of an imaging system using the Zernike polynomials wavefront description. The PSF estimation algorithm is based on obtaining field-dependent expansion coefficients of the Zernike polynomials by fitting real image data of the analyzed imaging system using an iterative approach in an initial estimate of the fitting parameters to ensure convergence robustness. The method is promising as an alternative to the standard approach based on Shack–Hartmann interferometry, since the estimate of the aberration coefficients is processed directly in the image plane. This approach is tested on simulated and laboratory-acquired image data that generally show good agreement. The resulting data are compared with the results of other modeling methods. The proposed PSF estimation method provides around 5% accuracy of the optical system model.

Estimation of Model Uncertainties in Closed-loop Systems

DEFF Research Database (Denmark)

Niemann, Hans Henrik; Poulsen, Niels Kjølstad

2008-01-01

This paper describe a method for estimation of parameters or uncertainties in closed-loop systems. The method is based on an application of the dual YJBK (after Youla, Jabr, Bongiorno and Kucera) parameterization of all systems stabilized by a given controller. The dual YJBK transfer function...

Fuel Cell System for Transportation -- 2005 Cost Estimate

Energy Technology Data Exchange (ETDEWEB)

Wheeler, D.

2006-10-01

Independent review report of the methodology used by TIAX to estimate the cost of producing PEM fuel cells using 2005 cell stack technology. The U.S. Department of Energy (DOE) Hydrogen, Fuel Cells and Infrastructure Technologies Program Manager asked the National Renewable Energy Laboratory (NREL) to commission an independent review of the 2005 TIAX cost analysis for fuel cell production. The NREL Systems Integrator is responsible for conducting independent reviews of progress toward meeting the DOE Hydrogen Program (the Program) technical targets. An important technical target of the Program is the proton exchange membrane (PEM) fuel cell cost in terms of dollars per kilowatt ($/kW). The Program's Multi-Year Program Research, Development, and Demonstration Plan established $125/kW as the 2005 technical target. Over the last several years, the Program has contracted with TIAX, LLC (TIAX) to produce estimates of the high volume cost of PEM fuel cell production for transportation use. Since no manufacturer is yet producing PEM fuel cells in the quantities needed for an initial hydrogen-based transportation economy, these estimates are necessary for DOE to gauge progress toward meeting its targets. For a PEM fuel cell system configuration developed by Argonne National Laboratory, TIAX estimated the total cost to be $108/kW, based on assumptions of 500,000 units per year produced with 2005 cell stack technology, vertical integration of cell stack manufacturing, and balance-of-plant (BOP) components purchased from a supplier network. Furthermore, TIAX conducted a Monte Carlo analysis by varying ten key parameters over a wide range of values and estimated with 98% certainty that the mean PEM fuel cell system cost would be below DOE's 2005 target of $125/kW. NREL commissioned DJW TECHNOLOGY, LLC to form an Independent Review Team (the Team) of industry fuel cell experts and to evaluate the cost estimation process and the results reported by TIAX. The results of

Operational Modal Analysis based Stress Estimation in Friction Systems

DEFF Research Database (Denmark)

Tarpø, Marius; Friis, Tobias; Nabuco, Bruna

this assumption. In this paper, the precision of estimating the strain response of a nonlinear system is investigated using the operational response of numerical simulations. Local nonlinearities are introduced by adding friction to the test specimen and this paper finds that this approach of strain estimation...

BIASED BEARINGS-ONIKY PARAMETER ESTIMATION FOR BISTATIC SYSTEM

Institute of Scientific and Technical Information of China (English)

Xu Benlian; Wang Zhiquan

2007-01-01

According to the biased angles provided by the bistatic sensors,the necessary condition of observability and Cramer-Rao low bounds for the bistatic system are derived and analyzed,respectively.Additionally,a dual Kalman filter method is presented with the purpose of eliminating the effect of biased angles on the state variable estimation.Finally,Monte-Carlo simulations are conducted in the observable scenario.Simulation results show that the proposed theory holds true,and the dual Kalman filter method can estimate state variable and biased angles simultaneously.Furthermore,the estimated results can achieve their Cramer-Rao low bounds.

Methodology to estimate parameters of an excitation system based on experimental conditions

Energy Technology Data Exchange (ETDEWEB)

Saavedra-Montes, A.J. [Carrera 80 No 65-223, Bloque M8 oficina 113, Escuela de Mecatronica, Universidad Nacional de Colombia, Medellin (Colombia); Calle 13 No 100-00, Escuela de Ingenieria Electrica y Electronica, Universidad del Valle, Cali, Valle (Colombia); Ramirez-Scarpetta, J.M. [Calle 13 No 100-00, Escuela de Ingenieria Electrica y Electronica, Universidad del Valle, Cali, Valle (Colombia); Malik, O.P. [2500 University Drive N.W., Electrical and Computer Engineering Department, University of Calgary, Calgary, Alberta (Canada)

2011-01-15

A methodology to estimate the parameters of a potential-source controlled rectifier excitation system model is presented in this paper. The proposed parameter estimation methodology is based on the characteristics of the excitation system. A comparison of two pseudo random binary signals, two sampling periods for each one, and three estimation algorithms is also presented. Simulation results from an excitation control system model and experimental results from an excitation system of a power laboratory setup are obtained. To apply the proposed methodology, the excitation system parameters are identified at two different levels of the generator saturation curve. The results show that it is possible to estimate the parameters of the standard model of an excitation system, recording two signals and the system operating in closed loop with the generator. The normalized sum of squared error obtained with experimental data is below 10%, and with simulation data is below 5%. (author)

Nonlinear Parameter Estimation in Microbiological Degradation Systems and Statistic Test for Common Estimation

DEFF Research Database (Denmark)

Sommer, Helle Mølgaard; Holst, Helle; Spliid, Henrik

1995-01-01

Three identical microbiological experiments were carried out and analysed in order to examine the variability of the parameter estimates. The microbiological system consisted of a substrate (toluene) and a biomass (pure culture) mixed together in an aquifer medium. The degradation of the substrate...... and the growth of the biomass are described by the Monod model consisting of two nonlinear coupled first-order differential equations. The objective of this study was to estimate the kinetic parameters in the Monod model and to test whether the parameters from the three identical experiments have the same values....... Estimation of the parameters was obtained using an iterative maximum likelihood method and the test used was an approximative likelihood ratio test. The test showed that the three sets of parameters were identical only on a 4% alpha level....

Estimation of Parametric Fault in Closed-loop Systems

DEFF Research Database (Denmark)

Niemann, Hans Henrik; Poulsen, Niels Kjølstad

2015-01-01

The aim of this paper is to present a method for estimation of parametric faults in closed-loop systems. The key technology applied in this paper is coprime factorization of both the dynamic system as well as the feedback controller. Using the Youla-Jabr-Bongiorno-Kucera (YJBK) parameterization...

Modelling, Estimation and Control of Networked Complex Systems

CERN Document Server

Chiuso, Alessandro; Frasca, Mattia; Rizzo, Alessandro; Schenato, Luca; Zampieri, Sandro

2009-01-01

The paradigm of complexity is pervading both science and engineering, leading to the emergence of novel approaches oriented at the development of a systemic view of the phenomena under study; the definition of powerful tools for modelling, estimation, and control; and the cross-fertilization of different disciplines and approaches. This book is devoted to networked systems which are one of the most promising paradigms of complexity. It is demonstrated that complex, dynamical networks are powerful tools to model, estimate, and control many interesting phenomena, like agent coordination, synchronization, social and economics events, networks of critical infrastructures, resources allocation, information processing, or control over communication networks. Moreover, it is shown how the recent technological advances in wireless communication and decreasing in cost and size of electronic devices are promoting the appearance of large inexpensive interconnected systems, each with computational, sensing and mobile cap...

A Robust WLS Power System State Estimation Method Integrating a Wide-Area Measurement System and SCADA Technology

Directory of Open Access Journals (Sweden)

Tao Jin

2015-04-01

Full Text Available With the development of modern society, the scale of the power system is rapidly increased accordingly, and the framework and mode of running of power systems are trending towards more complexity. It is nowadays much more important for the dispatchers to know exactly the state parameters of the power network through state estimation. This paper proposes a robust power system WLS state estimation method integrating a wide-area measurement system (WAMS and SCADA technology, incorporating phasor measurements and the results of the traditional state estimator in a post-processing estimator, which greatly reduces the scale of the non-linear estimation problem as well as the number of iterations and the processing time per iteration. This paper firstly analyzes the wide-area state estimation model in detail, then according to the issue that least squares does not account for bad data and outliers, the paper proposes a robust weighted least squares (WLS method that combines a robust estimation principle with least squares by equivalent weight. The performance assessment is discussed through setting up mathematical models of the distribution network. The effectiveness of the proposed method was proved to be accurate and reliable by simulations and experiments.

Dynamic state estimation techniques for large-scale electric power systems

International Nuclear Information System (INIS)

Rousseaux, P.; Pavella, M.

1991-01-01

This paper presents the use of dynamic type state estimators for energy management in electric power systems. Various dynamic type estimators have been developed, but have never been implemented. This is primarily because of dimensionality problems posed by the conjunction of an extended Kalman filter with a large scale power system. This paper precisely focuses on how to circumvent the high dimensionality, especially prohibitive in the filtering step, by using a decomposition-aggregation hierarchical scheme; to appropriately model the power system dynamics, the authors introduce new state variables in the prediction step and rely on a load forecasting method. The combination of these two techniques succeeds in solving the overall dynamic state estimation problem not only in a tractable and realistic way, but also in compliance with real-time computational requirements. Further improvements are also suggested, bound to the specifics of the high voltage electric transmission systems

Nonlinear Parameter Estimation in Microbiological Degradation Systems and Statistic Test for Common Estimation

DEFF Research Database (Denmark)

Sommer, Helle Mølgaard; Holst, Helle; Spliid, Henrik

1995-01-01

Three identical microbiological experiments were carried out and analysed in order to examine the variability of the parameter estimates. The microbiological system consisted of a substrate (toluene) and a biomass (pure culture) mixed together in an aquifer medium. The degradation of the substrate...

Accurate Lithium-ion battery parameter estimation with continuous-time system identification methods

International Nuclear Information System (INIS)

Xia, Bing; Zhao, Xin; Callafon, Raymond de; Garnier, Hugues; Nguyen, Truong; Mi, Chris

2016-01-01

Highlights: • Continuous-time system identification is applied in Lithium-ion battery modeling. • Continuous-time and discrete-time identification methods are compared in detail. • The instrumental variable method is employed to further improve the estimation. • Simulations and experiments validate the advantages of continuous-time methods. - Abstract: The modeling of Lithium-ion batteries usually utilizes discrete-time system identification methods to estimate parameters of discrete models. However, in real applications, there is a fundamental limitation of the discrete-time methods in dealing with sensitivity when the system is stiff and the storage resolutions are limited. To overcome this problem, this paper adopts direct continuous-time system identification methods to estimate the parameters of equivalent circuit models for Lithium-ion batteries. Compared with discrete-time system identification methods, the continuous-time system identification methods provide more accurate estimates to both fast and slow dynamics in battery systems and are less sensitive to disturbances. A case of a 2"n"d-order equivalent circuit model is studied which shows that the continuous-time estimates are more robust to high sampling rates, measurement noises and rounding errors. In addition, the estimation by the conventional continuous-time least squares method is further improved in the case of noisy output measurement by introducing the instrumental variable method. Simulation and experiment results validate the analysis and demonstrate the advantages of the continuous-time system identification methods in battery applications.

A Data-Driven Reliability Estimation Approach for Phased-Mission Systems

Directory of Open Access Journals (Sweden)

Hua-Feng He

2014-01-01

Full Text Available We attempt to address the issues associated with reliability estimation for phased-mission systems (PMS and present a novel data-driven approach to achieve reliability estimation for PMS using the condition monitoring information and degradation data of such system under dynamic operating scenario. In this sense, this paper differs from the existing methods only considering the static scenario without using the real-time information, which aims to estimate the reliability for a population but not for an individual. In the presented approach, to establish a linkage between the historical data and real-time information of the individual PMS, we adopt a stochastic filtering model to model the phase duration and obtain the updated estimation of the mission time by Bayesian law at each phase. At the meanwhile, the lifetime of PMS is estimated from degradation data, which are modeled by an adaptive Brownian motion. As such, the mission reliability can be real time obtained through the estimated distribution of the mission time in conjunction with the estimated lifetime distribution. We demonstrate the usefulness of the developed approach via a numerical example.

UM OLHAR SOBRE O DIABETES NA INFÂNCIA E NA JUVENTUDE: NEM TODOS SÃO TIPO 1

Directory of Open Access Journals (Sweden)

Mauren Isfer ANGHEBEM-OLIVEIRA

2013-04-01

Full Text Available O Diabetes mellitus (DM é caracterizado por um quadro de hiperglicemia crônica, que com os anos pode causar disfunção endotelial e sérias complicações vasculares, como a retinopatia, nefropatia e o infarto agudo do miocárdio. À medida que a ciência avança na compreensão da fisiopatologia e das características clínico-laboratoriais do diabetes, sua classificação tem sido adaptada, justamente porque a correta classificação do diabetes impacta no prognóstico e tratamento do paciente. Atualmente, o diabetes é classificado em DM tipo 1, DM tipo 2, DM gestacional e Outros Tipos Específicos, que inclui a categoria MODY (do inglês, Maturity Onset Diabetes of the Young ou diabetes da maturidade com início na juventude. O que esta revisão pretende mostrar é quem nem todo diabetes diagnosticado na infância e na juventude é DM tipo 1. O correto diagnóstico e classificação do DM são fundamentais, uma vez que o prognóstico e o tratamento podem diferir dependendo da causa que predispôs a criança ou adolescente à doença.

A Model-Driven Approach for Hybrid Power Estimation in Embedded Systems Design

Directory of Open Access Journals (Sweden)

Ben Atitallah Rabie

2011-01-01

Full Text Available Abstract As technology scales for increased circuit density and performance, the management of power consumption in system-on-chip (SoC is becoming critical. Today, having the appropriate electronic system level (ESL tools for power estimation in the design flow is mandatory. The main challenge for the design of such dedicated tools is to achieve a better tradeoff between accuracy and speed. This paper presents a consumption estimation approach allowing taking the consumption criterion into account early in the design flow during the system cosimulation. The originality of this approach is that it allows the power estimation for both white-box intellectual properties (IPs using annotated power models and black-box IPs using standalone power estimators. In order to obtain accurate power estimates, our simulations were performed at the cycle-accurate bit-accurate (CABA level, using SystemC. To make our approach fast and not tedious for users, the simulated architectures, including standalone power estimators, were generated automatically using a model driven engineering (MDE approach. Both annotated power models and standalone power estimators can be used together to estimate the consumption of the same architecture, which makes them complementary. The simulation results showed that the power estimates given by both estimation techniques for a hardware component are very close, with a difference that does not exceed 0.3%. This proves that, even when the IP code is not accessible or not modifiable, our approach allows obtaining quite accurate power estimates that early in the design flow thanks to the automation offered by the MDE approach.

Novel Method for 5G Systems NLOS Channels Parameter Estimation

Directory of Open Access Journals (Sweden)

Vladeta Milenkovic

2017-01-01

Full Text Available For the development of new 5G systems to operate in mm bands, there is a need for accurate radio propagation modelling at these bands. In this paper novel approach for NLOS channels parameter estimation will be presented. Estimation will be performed based on LCR performance measure, which will enable us to estimate propagation parameters in real time and to avoid weaknesses of ML and moment method estimation approaches.

Energy-efficient power allocation of two-hop cooperative systems with imperfect channel estimation

KAUST Repository

Amin, Osama

2015-06-08

Recently, much attention has been paid to the green design of wireless communication systems using energy efficiency (EE) metrics that should capture all energy consumption sources to deliver the required data. In this paper, we formulate an accurate EE metric for cooperative two-hop systems that use the amplify-and-forward relaying scheme. Different from the existing research that assumes the availability of perfect channel state information (CSI) at the communication cooperative nodes, we assume a practical scenario, where training pilots are used to estimate the channels. The estimated CSI can be used to adapt the available resources of the proposed system in order to maximize the EE. Two estimation strategies are assumed namely disintegrated channel estimation, which assumes the availability of channel estimator at the relay, and cascaded channel estimation, where the relay is not equipped with channel estimator and only forwards the received pilot(s) in order to let the destination estimate the cooperative link. The channel estimation cost is reflected on the EE metric by including the estimation error in the signal-to-noise term and considering the energy consumption during the estimation phase. Based on the formulated EE metric, we propose an energy-aware power allocation algorithm to maximize the EE of the cooperative system with channel estimation. Furthermore, we study the impact of the estimation parameters on the optimized EE performance via simulation examples.

Full State Estimation for Helicopter Slung Load System

DEFF Research Database (Denmark)

Bisgaard, Morten; la Cour-Harbo, Anders; Bendtsen, Jan Dimon

This paper presents the design of a state estimator system for a generic helicopter based slung load system. The estimator is designed to deliver full rigid body state information for both helicopter and load and is based on the unscented Kalman filter. Two different approaches are investigated......: One based on a parameter free kinematic model and one based on a full aerodynamic helicopter and slung load model. The kinematic model approach uses acceleration and rate information from two Inertial Measurement Units, one on the helicopter and one on the load, to drive a simple kinematic model....... A simple and effective virtual sensor method is developed to maintain the constraints imposed by the wires in the system. The full model based approach uses a complex aerodynamical model to describe the helicopter together with a generic rigid body model. This rigid body model is based on a redundant...

Full State Estimation for Helicopter Slung Load System

DEFF Research Database (Denmark)

Bisgaard, Morten; la Cour-Harbo, Anders; Bendtsen, Jan Dimon

2007-01-01

This paper presents the design of a state estimator system for a generic helicopter based slung load system. The estimator is designed to deliver full rigid body state information for both helicopter and load and is based on the unscented Kalman filter. Two different approaches are investigated......: One based on a parameter free kinematic model and one based on a full aerodynamic helicopter and slung load model. The kinematic model approach uses acceleration and rate information from two Inertial Measurement Units, one on the helicopter and one on the load, to drive a simple kinematic model....... A simple and effective virtual sensor method is developed to maintain the constraints imposed by the wires in the system. The full model based approach uses a complex aerodynamical model to describe the helicopter together with a generic rigid body model. This rigid body model is based on a redundant...

Parameter and State Estimation of Large-Scale Complex Systems Using Python Tools

Directory of Open Access Journals (Sweden)

M. Anushka S. Perera

2015-07-01

Full Text Available This paper discusses the topics related to automating parameter, disturbance and state estimation analysis of large-scale complex nonlinear dynamic systems using free programming tools. For large-scale complex systems, before implementing any state estimator, the system should be analyzed for structural observability and the structural observability analysis can be automated using Modelica and Python. As a result of structural observability analysis, the system may be decomposed into subsystems where some of them may be observable --- with respect to parameter, disturbances, and states --- while some may not. The state estimation process is carried out for those observable subsystems and the optimum number of additional measurements are prescribed for unobservable subsystems to make them observable. In this paper, an industrial case study is considered: the copper production process at Glencore Nikkelverk, Kristiansand, Norway. The copper production process is a large-scale complex system. It is shown how to implement various state estimators, in Python, to estimate parameters and disturbances, in addition to states, based on available measurements.

Efficient channel estimation in massive MIMO systems - a distributed approach

KAUST Repository

Al-Naffouri, Tareq Y.

2016-01-01

We present two efficient algorithms for distributed estimation of channels in massive MIMO systems. The two cases of 1) generic, and 2) sparse channels is considered. The algorithms estimate the impulse response for each channel observed

State estimation and synchronization of pendula systems over digital communication channels

Science.gov (United States)

Fradkov, A. L.; Andrievsky, B.; Ananyevskiy, M.

2014-04-01

The recent results on nonlinear systems synchronization and control under communication constraints are applied to the remote state estimation and synchronization for a class of exogenously excited nonlinear Lurie systems. State estimation of the chain of diffusively coupled pendulums over the digital communication channel with limited capacity is experimentally studied. Advantage of the adaptive coding procedure under the conditions of the plant model uncertainty and irregular disturbances is shown. Quality of the estimation is evaluated by means of the experiments with the multi-pendulum set-up. Experimental study of master-slave synchronization over network (local network, wireless network) for the system with two cart-pendulums is presented.

Earthquake loss estimation for a gas lifeline transportation system in Colombia

Energy Technology Data Exchange (ETDEWEB)

Yamin, L.E.; Arambula, S.; Reyes, J.C. [Universidad de los Andes, Bogota (Colombia). Centro de Innovacion y Desarrollo Tecnologico; Belage, S.; Vega, A.; Gil, W. [TransGas de Occidente S.A., Bogota (Colombia)

2004-07-01

Methodologies are needed to estimate the seismic risk facing natural gas distribution systems in Colombia in order to establish insurance strategies, risk assessments and emergency plans. This study estimated the maximum probable losses associated with Colombia's 770 km long gas transportation system which stretches from Mariquita to Cali. The pipeline is vulnerable to seismic events, volcanic eruptions, extreme hydrological conditions, and their associated effects such as landslides, liquefaction and avalanches. A geographic information system (GIS) which includes seismic, volcanic, landslide and liquefaction hazards was used to estimate earthquake loss estimates for the natural gas distribution system. Elastic and inelastic finite element methods were used to evaluate the vulnerability of pipelines, bridges, underground crossings and valves. The results were incorporated into the GIS and were used to quantify the probable maximum losses for the system, the most critical associated event, the system's critical zones and the probable damage scenarios. The information was used to define insurance strategies, emergency and contingency plans. It was concluded that due to natural hazards, the natural gas distribution system is at moderate risk despite the low vulnerability of its components. Volcanic eruptions and large earthquakes could produce indirect phenomena such as landslides and liquefaction which could greatly influence the system and which would require adequate risk management. 14 refs., 1 tab., 8 figs.

Estimation of Boreal Forest Biomass Using Spaceborne SAR Systems

Science.gov (United States)

Saatchi, Sassan; Moghaddam, Mahta

1995-01-01

In this paper, we report on the use of a semiempirical algorithm derived from a two layer radar backscatter model for forest canopies. The model stratifies the forest canopy into crown and stem layers, separates the structural and biometric attributes of the canopy. The structural parameters are estimated by training the model with polarimetric SAR (synthetic aperture radar) data acquired over homogeneous stands with known above ground biomass. Given the structural parameters, the semi-empirical algorithm has four remaining parameters, crown biomass, stem biomass, surface soil moisture, and surface rms height that can be estimated by at least four independent SAR measurements. The algorithm has been used to generate biomass maps over the entire images acquired by JPL AIRSAR and SIR-C SAR systems. The semi-empirical algorithms are then modified to be used by single frequency radar systems such as ERS-1, JERS-1, and Radarsat. The accuracy. of biomass estimation from single channel radars is compared with the case when the channels are used together in synergism or in a polarimetric system.

Computer software to estimate timber harvesting system production, cost, and revenue

Science.gov (United States)

Dr. John E. Baumgras; Dr. Chris B. LeDoux

1992-01-01

Large variations in timber harvesting cost and revenue can result from the differences between harvesting systems, the variable attributes of harvesting sites and timber stands, or changing product markets. Consequently, system and site specific estimates of production rates and costs are required to improve estimates of harvesting revenue. This paper describes...

Distributed weighted least-squares estimation with fast convergence for large-scale systems.

Science.gov (United States)

Marelli, Damián Edgardo; Fu, Minyue

2015-01-01

In this paper we study a distributed weighted least-squares estimation problem for a large-scale system consisting of a network of interconnected sub-systems. Each sub-system is concerned with a subset of the unknown parameters and has a measurement linear in the unknown parameters with additive noise. The distributed estimation task is for each sub-system to compute the globally optimal estimate of its own parameters using its own measurement and information shared with the network through neighborhood communication. We first provide a fully distributed iterative algorithm to asymptotically compute the global optimal estimate. The convergence rate of the algorithm will be maximized using a scaling parameter and a preconditioning method. This algorithm works for a general network. For a network without loops, we also provide a different iterative algorithm to compute the global optimal estimate which converges in a finite number of steps. We include numerical experiments to illustrate the performances of the proposed methods.

A Parameter Estimation Method for Nonlinear Systems Based on Improved Boundary Chicken Swarm Optimization

Directory of Open Access Journals (Sweden)

Shaolong Chen

2016-01-01

Full Text Available Parameter estimation is an important problem in nonlinear system modeling and control. Through constructing an appropriate fitness function, parameter estimation of system could be converted to a multidimensional parameter optimization problem. As a novel swarm intelligence algorithm, chicken swarm optimization (CSO has attracted much attention owing to its good global convergence and robustness. In this paper, a method based on improved boundary chicken swarm optimization (IBCSO is proposed for parameter estimation of nonlinear systems, demonstrated and tested by Lorenz system and a coupling motor system. Furthermore, we have analyzed the influence of time series on the estimation accuracy. Computer simulation results show it is feasible and with desirable performance for parameter estimation of nonlinear systems.

SNR Estimation in Linear Systems with Gaussian Matrices

KAUST Repository

Suliman, Mohamed Abdalla Elhag; Alrashdi, Ayed; Ballal, Tarig; Al-Naffouri, Tareq Y.

2017-01-01

This letter proposes a highly accurate algorithm to estimate the signal-to-noise ratio (SNR) for a linear system from a single realization of the received signal. We assume that the linear system has a Gaussian matrix with one sided left correlation. The unknown entries of the signal and the noise are assumed to be independent and identically distributed with zero mean and can be drawn from any distribution. We use the ridge regression function of this linear model in company with tools and techniques adapted from random matrix theory to achieve, in closed form, accurate estimation of the SNR without prior statistical knowledge on the signal or the noise. Simulation results show that the proposed method is very accurate.

SNR Estimation in Linear Systems with Gaussian Matrices

KAUST Repository

Suliman, Mohamed Abdalla Elhag

2017-09-27

This letter proposes a highly accurate algorithm to estimate the signal-to-noise ratio (SNR) for a linear system from a single realization of the received signal. We assume that the linear system has a Gaussian matrix with one sided left correlation. The unknown entries of the signal and the noise are assumed to be independent and identically distributed with zero mean and can be drawn from any distribution. We use the ridge regression function of this linear model in company with tools and techniques adapted from random matrix theory to achieve, in closed form, accurate estimation of the SNR without prior statistical knowledge on the signal or the noise. Simulation results show that the proposed method is very accurate.

CFO and channel estimation for MISO-OFDM systems

KAUST Repository

Ladaycia, Abdelhamid

2017-11-02

This study deals with the joint channel and carrier frequency offset (CFO) estimation in a Multiple Input Single Output (MISO) communications system. This problem arises in OFDM (Orthogonal Frequency Division Multiplexing) based multi-relay transmission protocols such that the geo-routing one proposed by A. Bader et al in 2012. Indeed, the outstanding performance of this multi-hop relaying scheme relies heavily on the channel and CFO estimation quality at the PHY layer. In this work, two approaches are considered: The first is based on estimating the overall channel (including the CFO) as a time-varying one using an adaptive scheme under the assumption of small or moderate CFOs while the second one performs separately, the channel and CFO parameters estimation based on the considered data model. The two solutions are analyzed and compared in terms of performance, cost and convergence rate.

Topological estimation of aerodynamic controlled airplane system functionality of quality

Directory of Open Access Journals (Sweden)

С.В. Павлова

2005-01-01

Full Text Available  It is suggested to use topological methods for stage estimation of aerodynamic airplane control in widespread range of its conditions The estimation is based on normalized stage virtual non-isotropy of configurational airplane systems calculation.

Two-Step Time of Arrival Estimation for Pulse-Based Ultra-Wideband Systems

Directory of Open Access Journals (Sweden)

H. Vincent Poor

2008-05-01

Full Text Available In cooperative localization systems, wireless nodes need to exchange accurate position-related information such as time-of-arrival (TOA and angle-of-arrival (AOA, in order to obtain accurate location information. One alternative for providing accurate position-related information is to use ultra-wideband (UWB signals. The high time resolution of UWB signals presents a potential for very accurate positioning based on TOA estimation. However, it is challenging to realize very accurate positioning systems in practical scenarios, due to both complexity/cost constraints and adverse channel conditions such as multipath propagation. In this paper, a two-step TOA estimation algorithm is proposed for UWB systems in order to provide accurate TOA estimation under practical constraints. In order to speed up the estimation process, the first step estimates a coarse TOA of the received signal based on received signal energy. Then, in the second step, the arrival time of the first signal path is estimated by considering a hypothesis testing approach. The proposed scheme uses low-rate correlation outputs and is able to perform accurate TOA estimation in reasonable time intervals. The simulation results are presented to analyze the performance of the estimator.

Markov Jump Linear Systems-Based Position Estimation for Lower Limb Exoskeletons

Directory of Open Access Journals (Sweden)

Samuel L. Nogueira

2014-01-01

Full Text Available In this paper, we deal with Markov Jump Linear Systems-based filtering applied to robotic rehabilitation. The angular positions of an impedance-controlled exoskeleton, designed to help stroke and spinal cord injured patients during walking rehabilitation, are estimated. Standard position estimate approaches adopt Kalman filters (KF to improve the performance of inertial measurement units (IMUs based on individual link configurations. Consequently, for a multi-body system, like a lower limb exoskeleton, the inertial measurements of one link (e.g., the shank are not taken into account in other link position estimation (e.g., the foot. In this paper, we propose a collective modeling of all inertial sensors attached to the exoskeleton, combining them in a Markovian estimation model in order to get the best information from each sensor. In order to demonstrate the effectiveness of our approach, simulation results regarding a set of human footsteps, with four IMUs and three encoders attached to the lower limb exoskeleton, are presented. A comparative study between the Markovian estimation system and the standard one is performed considering a wide range of parametric uncertainties.

Estimating the decomposition of predictive information in multivariate systems

Science.gov (United States)

Faes, Luca; Kugiumtzis, Dimitris; Nollo, Giandomenico; Jurysta, Fabrice; Marinazzo, Daniele

2015-03-01

In the study of complex systems from observed multivariate time series, insight into the evolution of one system may be under investigation, which can be explained by the information storage of the system and the information transfer from other interacting systems. We present a framework for the model-free estimation of information storage and information transfer computed as the terms composing the predictive information about the target of a multivariate dynamical process. The approach tackles the curse of dimensionality employing a nonuniform embedding scheme that selects progressively, among the past components of the multivariate process, only those that contribute most, in terms of conditional mutual information, to the present target process. Moreover, it computes all information-theoretic quantities using a nearest-neighbor technique designed to compensate the bias due to the different dimensionality of individual entropy terms. The resulting estimators of prediction entropy, storage entropy, transfer entropy, and partial transfer entropy are tested on simulations of coupled linear stochastic and nonlinear deterministic dynamic processes, demonstrating the superiority of the proposed approach over the traditional estimators based on uniform embedding. The framework is then applied to multivariate physiologic time series, resulting in physiologically well-interpretable information decompositions of cardiovascular and cardiorespiratory interactions during head-up tilt and of joint brain-heart dynamics during sleep.

The Source Signature Estimator - System Improvements and Applications

Energy Technology Data Exchange (ETDEWEB)

Sabel, Per; Brink, Mundy; Eidsvig, Seija; Jensen, Lars

1998-12-31

This presentation relates briefly to the first part of the joint project on post-survey analysis of shot-by-shot based source signature estimation. The improvements of a Source Signature Estimator system are analysed. The notional source method can give suboptimal results when not inputting the real array geometry, i.e. actual separations between the sub-arrays of an air gun array, to the notional source algorithm. This constraint has been addressed herein and was implemented for the first time in the field in summer 1997. The second part of this study will show the potential advantages for interpretation when the signature estimates are then to be applied in the data processing. 5 refs., 1 fig.

Development of a faulty reactivity detection system applying a digital H∞ estimator

International Nuclear Information System (INIS)

Suzuki, Katsuo; Suzudo, Tomoaki; Nabeshima, Kunihiko

2004-01-01

This paper concerns an application of digital optimal H ∞ estimator to the detection of faulty reactivity in real-time. The detection system, fundamentally based on the reactivity balance method, is composed of three modules, i.e. the net reactivity estimator, the feedback reactivity estimator and the reactivity balance circuit. H ∞ optimal filters are used for these two reactivity estimators, and the nonlinear neutronics are taken into consideration especially for the design of the net reactivity estimator. A series of performance test of the detection system are conducted by using numerical simulations of reactor dynamics with the insertion of a faulty reactivity for an experimental fast breeder reactor JOYO. The system detects the typical artificial reactivity insertions during a few seconds with no stationary offset and the accuracy of 0.1 cent, and is satisfactory for its practical use. (author)

Hybrid fuzzy charged system search algorithm based state estimation in distribution networks

Directory of Open Access Journals (Sweden)

Sachidananda Prasad

2017-06-01

Full Text Available This paper proposes a new hybrid charged system search (CSS algorithm based state estimation in radial distribution networks in fuzzy framework. The objective of the optimization problem is to minimize the weighted square of the difference between the measured and the estimated quantity. The proposed method of state estimation considers bus voltage magnitude and phase angle as state variable along with some equality and inequality constraints for state estimation in distribution networks. A rule based fuzzy inference system has been designed to control the parameters of the CSS algorithm to achieve better balance between the exploration and exploitation capability of the algorithm. The efficiency of the proposed fuzzy adaptive charged system search (FACSS algorithm has been tested on standard IEEE 33-bus system and Indian 85-bus practical radial distribution system. The obtained results have been compared with the conventional CSS algorithm, weighted least square (WLS algorithm and particle swarm optimization (PSO for feasibility of the algorithm.

Sliding-MOMP Based Channel Estimation Scheme for ISDB-T Systems

Directory of Open Access Journals (Sweden)

Ziji Ma

2016-01-01

Full Text Available Compressive sensing based channel estimation has shown its advantage of accurate reconstruction for sparse signal with less pilots for OFDM systems. However, high computational cost requirement of CS method, due to linear programming, significantly restricts its implementation in practical applications. In this paper, we propose a reduced complexity channel estimation scheme of modified orthogonal matching pursuit with sliding windows for ISDB-T (Integrated Services Digital Broadcasting for Terrestrial system. The proposed scheme can reduce the computational cost by limiting the searching region as well as making effective use of the last estimation result. In addition, adaptive tracking strategy with sliding sampling window can improve the robustness of CS based methods to guarantee its accuracy of channel matrix reconstruction, even for fast time-variant channels. The computer simulation demonstrates its impact on improving bit error rate and computational complexity for ISDB-T system.

Improved Sparse Channel Estimation for Cooperative Communication Systems

Directory of Open Access Journals (Sweden)

Guan Gui

2012-01-01

Full Text Available Accurate channel state information (CSI is necessary at receiver for coherent detection in amplify-and-forward (AF cooperative communication systems. To estimate the channel, traditional methods, that is, least squares (LS and least absolute shrinkage and selection operator (LASSO, are based on assumptions of either dense channel or global sparse channel. However, LS-based linear method neglects the inherent sparse structure information while LASSO-based sparse channel method cannot take full advantage of the prior information. Based on the partial sparse assumption of the cooperative channel model, we propose an improved channel estimation method with partial sparse constraint. At first, by using sparse decomposition theory, channel estimation is formulated as a compressive sensing problem. Secondly, the cooperative channel is reconstructed by LASSO with partial sparse constraint. Finally, numerical simulations are carried out to confirm the superiority of proposed methods over global sparse channel estimation methods.

Degenerated-Inverse-Matrix-Based Channel Estimation for OFDM Systems

Directory of Open Access Journals (Sweden)

Makoto Yoshida

2009-01-01

Full Text Available This paper addresses time-domain channel estimation for pilot-symbol-aided orthogonal frequency division multiplexing (OFDM systems. By using a cyclic sinc-function matrix uniquely determined by Nc transmitted subcarriers, the performance of our proposed scheme approaches perfect channel state information (CSI, within a maximum of 0.4 dB degradation, regardless of the delay spread of the channel, Doppler frequency, and subcarrier modulation. Furthermore, reducing the matrix size by splitting the dispersive channel impulse response into clusters means that the degenerated inverse matrix estimator (DIME is feasible for broadband, high-quality OFDM transmission systems. In addition to theoretical analysis on normalized mean squared error (NMSE performance of DIME, computer simulations over realistic nonsample spaced channels also showed that the DIME is robust for intersymbol interference (ISI channels and fast time-invariant channels where a minimum mean squared error (MMSE estimator does not work well.

Nonlinear adaptive control system design with asymptotically stable parameter estimation error

Science.gov (United States)

Mishkov, Rumen; Darmonski, Stanislav

2018-01-01

The paper presents a new general method for nonlinear adaptive system design with asymptotic stability of the parameter estimation error. The advantages of the approach include asymptotic unknown parameter estimation without persistent excitation and capability to directly control the estimates transient response time. The method proposed modifies the basic parameter estimation dynamics designed via a known nonlinear adaptive control approach. The modification is based on the generalised prediction error, a priori constraints with a hierarchical parameter projection algorithm, and the stable data accumulation concepts. The data accumulation principle is the main tool for achieving asymptotic unknown parameter estimation. It relies on the parametric identifiability system property introduced. Necessary and sufficient conditions for exponential stability of the data accumulation dynamics are derived. The approach is applied in a nonlinear adaptive speed tracking vector control of a three-phase induction motor.

An Estimator for Attitude and Heading Reference Systems Based on Virtual Horizontal Reference

DEFF Research Database (Denmark)

Wang, Yunlong; Soltani, Mohsen; Hussain, Dil muhammed Akbar

2016-01-01

makes it possible to correct the output of roll and pitch of the attitude estimator in the situations without accelerometer measurements, which cannot be achieved by the conventional nonlinear attitude estimator. The performance of VHR is tested both in simulation and hardware environment to validate......The output of the attitude determination systems suffers from large errors in case of accelerometer malfunctions. In this paper, an attitude estimator, based on Virtual Horizontal Reference (VHR), is designed for an Attitude Heading and Reference System (AHRS) to cope with this problem. The VHR...... their estimation performance. Moreover, the hardware test results are compared with that of a high-precision commercial AHRS to verify the estimation results. The implemented algorithm has shown high accuracy of attitude estimation that makes the system suitable for many applications....

The Impacts of Changes to Nevada’s Net Metering Policy on the Financial Performance and Adoption of Distributed Photovoltaics

Energy Technology Data Exchange (ETDEWEB)

Gagnon, Pieter [National Renewable Energy Lab. (NREL), Golden, CO (United States); Sigrin, Ben [National Renewable Energy Lab. (NREL), Golden, CO (United States); Gleason, Mike [National Renewable Energy Lab. (NREL), Golden, CO (United States)

2017-01-01

Net energy metering (NEM) is a billing mechanism that has historically compensated owners of distributed generation systems at retail rates for any electricity that they export back to the grid rather than consume on-site. NEM can significantly enhance the financial performance of distributed generation systems from the owner’s perspective. The following analysis was designed to illustrate the potential impact of NEM policy and tariff changes implemented in early 2016 in Nevada.

A Robust Threshold for Iterative Channel Estimation in OFDM Systems

Directory of Open Access Journals (Sweden)

A. Kalaycioglu

2010-04-01

Full Text Available A novel threshold computation method for pilot symbol assisted iterative channel estimation in OFDM systems is considered. As the bits are transmitted in packets, the proposed technique is based on calculating a particular threshold for each data packet in order to select the reliable decoder output symbols to improve the channel estimation performance. Iteratively, additional pilot symbols are established according to the threshold and the channel is re-estimated with the new pilots inserted to the known channel estimation pilot set. The proposed threshold calculation method for selecting additional pilots performs better than non-iterative channel estimation, no threshold and fixed threshold techniques in poor HF channel simulations.

Distributive estimation of frequency selective channels for massive MIMO systems

KAUST Repository

Zaib, Alam

2015-12-28

We consider frequency selective channel estimation in the uplink of massive MIMO-OFDM systems, where our major concern is complexity. A low complexity distributed LMMSE algorithm is proposed that attains near optimal channel impulse response (CIR) estimates from noisy observations at receive antenna array. In proposed method, every antenna estimates the CIRs of its neighborhood followed by recursive sharing of estimates with immediate neighbors. At each step, every antenna calculates the weighted average of shared estimates which converges to near optimal LMMSE solution. The simulation results validate the near optimal performance of proposed algorithm in terms of mean square error (MSE). © 2015 EURASIP.

A distributed approach for parameters estimation in System Biology models

International Nuclear Information System (INIS)

Mosca, E.; Merelli, I.; Alfieri, R.; Milanesi, L.

2009-01-01

Due to the lack of experimental measurements, biological variability and experimental errors, the value of many parameters of the systems biology mathematical models is yet unknown or uncertain. A possible computational solution is the parameter estimation, that is the identification of the parameter values that determine the best model fitting respect to experimental data. We have developed an environment to distribute each run of the parameter estimation algorithm on a different computational resource. The key feature of the implementation is a relational database that allows the user to swap the candidate solutions among the working nodes during the computations. The comparison of the distributed implementation with the parallel one showed that the presented approach enables a faster and better parameter estimation of systems biology models.

Advanced digital PWR plant protection system based on optimal estimation theory

International Nuclear Information System (INIS)

Tylee, J.L.

1981-04-01

An advanced plant protection system for the Loss-of-Fluid Test (LOFT) reactor plant is described and evaluated. The system, based on a Kalman filter estimator, is capable of providing on-line estimates of such critical variables as fuel and cladding temperature, departure from nucleate boiling ratio, and maximum linear heat generation rate. The Kalman filter equations are presented, as is a description of the LOFT plant dynamic model inherent in the filter. Simulation results demonstrate the performance of the advanced system

Channel Estimation for Filter Bank Multicarrier Systems in Low SNR Environments

Energy Technology Data Exchange (ETDEWEB)

Driggs, Jonathan; Sibbett, Taylor; Moradiy, Hussein; Farhang-Boroujeny, Behrouz

2017-05-01

Channel estimation techniques are crucial for reliable communications. This paper is concerned with channel estimation in a filter bank multicarrier spread spectrum (FBMCSS) system. We explore two channel estimator options: (i) a method that makes use of a periodic preamble and mimics the channel estimation techniques that are widely used in OFDM-based systems; and (ii) a method that stays within the traditional realm of filter bank signal processing. For the case where the channel noise is white, both methods are analyzed in detail and their performance is compared against their respective Cramer-Rao Lower Bounds (CRLB). Advantages and disadvantages of the two methods under different channel conditions are given to provide insight to the reader as to when one will outperform the other.

Optimal estimation of entanglement in optical qubit systems

International Nuclear Information System (INIS)

Brida, Giorgio; Degiovanni, Ivo P.; Florio, Angela; Genovese, Marco; Meda, Alice; Shurupov, Alexander P.; Giorda, Paolo; Paris, Matteo G. A.

2011-01-01

We address the experimental determination of entanglement for systems made of a pair of polarization qubits. We exploit quantum estimation theory to derive optimal estimators, which are then implemented to achieve ultimate bound to precision. In particular, we present a set of experiments aimed at measuring the amount of entanglement for states belonging to different families of pure and mixed two-qubit two-photon states. Our scheme is based on visibility measurements of quantum correlations and achieves the ultimate precision allowed by quantum mechanics in the limit of Poissonian distribution of coincidence counts. Although optimal estimation of entanglement does not require the full tomography of the states we have also performed state reconstruction using two different sets of tomographic projectors and explicitly shown that they provide a less precise determination of entanglement. The use of optimal estimators also allows us to compare and statistically assess the different noise models used to describe decoherence effects occurring in the generation of entanglement.

Policy Report for NEMS Enhancement

NARCIS (Netherlands)

de Theije, M.E.M.

2010-01-01

This policy report discusses aspects of health, safety, environment and pollution related to small scale gold mining, the social and economic sustainability of the mining activities, and the role of Environmental Management Systems in reaching better results in these terrains. Specifically it will

Observer-Based Fault Estimation and Accomodation for Dynamic Systems

CERN Document Server

Zhang, Ke; Shi, Peng

2013-01-01

Due to the increasing security and reliability demand of actual industrial process control systems, the study on fault diagnosis and fault tolerant control of dynamic systems has received considerable attention. Fault accommodation (FA) is one of effective methods that can be used to enhance system stability and reliability, so it has been widely and in-depth investigated and become a hot topic in recent years. Fault detection is used to monitor whether a fault occurs, which is the first step in FA. On the basis of fault detection, fault estimation (FE) is utilized to determine online the magnitude of the fault, which is a very important step because the additional controller is designed using the fault estimate. Compared with fault detection, the design difficulties of FE would increase a lot, so research on FE and accommodation is very challenging. Although there have been advancements reported on FE and accommodation for dynamic systems, the common methods at the present stage have design difficulties, whi...

An approach of parameter estimation for non-synchronous systems

International Nuclear Information System (INIS)

Xu Daolin; Lu Fangfang

2005-01-01

Synchronization-based parameter estimation is simple and effective but only available to synchronous systems. To come over this limitation, we propose a technique that the parameters of an unknown physical process (possibly a non-synchronous system) can be identified from a time series via a minimization procedure based on a synchronization control. The feasibility of this approach is illustrated in several chaotic systems

Maxwell-Stefan diffusion coefficient estimation for ternary systems: an ideal ternary alcohol system.

Science.gov (United States)

Allie-Ebrahim, Tariq; Zhu, Qingyu; Bräuer, Pierre; Moggridge, Geoff D; D'Agostino, Carmine

2017-06-21

The Maxwell-Stefan model is a popular diffusion model originally developed to model diffusion of gases, which can be considered thermodynamically ideal mixtures, although its application has been extended to model diffusion in non-ideal liquid mixtures as well. A drawback of the model is that it requires the Maxwell-Stefan diffusion coefficients, which are not based on measurable quantities but they have to be estimated. As a result, numerous estimation methods, such as the Darken model, have been proposed to estimate these diffusion coefficients. However, the Darken model was derived, and is only well defined, for binary systems. This model has been extended to ternary systems according to two proposed forms, one by R. Krishna and J. M. van Baten, Ind. Eng. Chem. Res., 2005, 44, 6939-6947 and the other by X. Liu, T. J. H. Vlugt and A. Bardow, Ind. Eng. Chem. Res., 2011, 50, 10350-10358. In this paper, the two forms have been analysed against the ideal ternary system of methanol/butan-1-ol/propan-1-ol and using experimental values of self-diffusion coefficients. In particular, using pulsed gradient stimulated echo nuclear magnetic resonance (PGSTE-NMR) we have measured the self-diffusion coefficients in various methanol/butan-1-ol/propan-1-ol mixtures. The experimental values of self-diffusion coefficients were then used as the input data required for the Darken model. The predictions of the two proposed multicomponent forms of this model were then compared to experimental values of mutual diffusion coefficients for the ideal alcohol ternary system. This experimental-based approach showed that the Liu's model gives better predictions compared to that of Krishna and van Baten, although it was only accurate to within 26%. Nonetheless, the multicomponent Darken model in conjunction with self-diffusion measurements from PGSTE-NMR represents an attractive method for a rapid estimation of mutual diffusion in multicomponent systems, especially when compared to exhaustive

Parameter estimation in space systems using recurrent neural networks

Science.gov (United States)

Parlos, Alexander G.; Atiya, Amir F.; Sunkel, John W.

1991-01-01

The identification of time-varying parameters encountered in space systems is addressed, using artificial neural systems. A hybrid feedforward/feedback neural network, namely a recurrent multilayer perception, is used as the model structure in the nonlinear system identification. The feedforward portion of the network architecture provides its well-known interpolation property, while through recurrency and cross-talk, the local information feedback enables representation of temporal variations in the system nonlinearities. The standard back-propagation-learning algorithm is modified and it is used for both the off-line and on-line supervised training of the proposed hybrid network. The performance of recurrent multilayer perceptron networks in identifying parameters of nonlinear dynamic systems is investigated by estimating the mass properties of a representative large spacecraft. The changes in the spacecraft inertia are predicted using a trained neural network, during two configurations corresponding to the early and late stages of the spacecraft on-orbit assembly sequence. The proposed on-line mass properties estimation capability offers encouraging results, though, further research is warranted for training and testing the predictive capabilities of these networks beyond nominal spacecraft operations.

Estimation of Parameters in Mean-Reverting Stochastic Systems

Directory of Open Access Journals (Sweden)

Tianhai Tian

2014-01-01

Full Text Available Stochastic differential equation (SDE is a very important mathematical tool to describe complex systems in which noise plays an important role. SDE models have been widely used to study the dynamic properties of various nonlinear systems in biology, engineering, finance, and economics, as well as physical sciences. Since a SDE can generate unlimited numbers of trajectories, it is difficult to estimate model parameters based on experimental observations which may represent only one trajectory of the stochastic model. Although substantial research efforts have been made to develop effective methods, it is still a challenge to infer unknown parameters in SDE models from observations that may have large variations. Using an interest rate model as a test problem, in this work we use the Bayesian inference and Markov Chain Monte Carlo method to estimate unknown parameters in SDE models.

A Human Work Interaction Design (HWID) Case Study in E-Government and Public Information Systems

DEFF Research Database (Denmark)

Clemmensen, Torkil

2011-01-01

This paper first outlines a revised version of the general HWID framework, with a focus on what connects empirical work analysis and interaction design, and then presents a case study of the Danish government one-for-all authentication system NemID. The case is briefly analyzed, using ethnomethod...... in studying how human work analysis and interaction design in concrete cases are related and connected.......This paper first outlines a revised version of the general HWID framework, with a focus on what connects empirical work analysis and interaction design, and then presents a case study of the Danish government one-for-all authentication system NemID. The case is briefly analyzed, using...... ethnomethodology, work domain/task analysis, and the HWID approach, and comparing the results. Compared to the traditional approaches, the HWID focus on case-specific connections between human work and interaction design, gives different and supplementary answers. The conclusion is that there are benefits...

Proof of Concept of an Irradiance Estimation System for Reconfigurable Photovoltaic Arrays

Directory of Open Access Journals (Sweden)

Vincenzo Li Vigni

2015-06-01

Full Text Available In order to reduce the mismatch effect caused by non-uniform shadows in PV arrays, reconfigurable interconnections approaches have been recently proposed in the literature. These systems usually require the knowledge of the solar radiation affecting every solar module. The aim of this work is to evaluate the effectiveness of three irradiance estimation approaches in order to define which can be well suited for reconfigurable PV arrays. It is presented a real-time solar irradiance estimation device (IrradEst, implementing the three different estimation methods. The proposed system is based on mathematical models of PV modules enabling to estimate irradiation values by sensing a combination of temperature, voltage and current of a PV module. Experimental results showed generally good agreement between the estimated irradiances and the measurements performed by a standard pyranometer taken as reference. Finally one of the three methods was selected as possible solution for a reconfigurable PV system.

A Study of an Iterative Channel Estimation Scheme of FS-FBMC System

Directory of Open Access Journals (Sweden)

YongJu Won

2017-01-01

Full Text Available A filter bank multicarrier on offset-quadrature amplitude modulation (FBMC/OQAM system is an alternative multicarrier modulation scheme that does not need cyclic prefix (CP even in the presence of a multipath fading channel by the properties of prototype filter. The FBMC/OQAM system can be implemented either by using the poly-phase network with fast fourier transform (PPN-FFT or by using the extended FFT on a frequency-spreading (FS domain. In this paper, we propose an iterative channel estimation scheme for each sub channel of a FBMC/OQAM system over a frequency-spreading domain. The proposed scheme first estimates the channel using the received pilot signal in the subchannel domain and interpolates the estimated channel to fine frequency-spreading domain. Then the channel compensated FS domain pilot is despread again to modify the channel state information (CSI estimation. Computer simulation shows that the proposed method outperforms the conventional FBMC/OQAM channel estimator in a frequency selective channel.

Distributed State Estimation Using a Modified Partitioned Moving Horizon Strategy for Power Systems.

Science.gov (United States)

Chen, Tengpeng; Foo, Yi Shyh Eddy; Ling, K V; Chen, Xuebing

2017-10-11

In this paper, a distributed state estimation method based on moving horizon estimation (MHE) is proposed for the large-scale power system state estimation. The proposed method partitions the power systems into several local areas with non-overlapping states. Unlike the centralized approach where all measurements are sent to a processing center, the proposed method distributes the state estimation task to the local processing centers where local measurements are collected. Inspired by the partitioned moving horizon estimation (PMHE) algorithm, each local area solves a smaller optimization problem to estimate its own local states by using local measurements and estimated results from its neighboring areas. In contrast with PMHE, the error from the process model is ignored in our method. The proposed modified PMHE (mPMHE) approach can also take constraints on states into account during the optimization process such that the influence of the outliers can be further mitigated. Simulation results on the IEEE 14-bus and 118-bus systems verify that our method achieves comparable state estimation accuracy but with a significant reduction in the overall computation load.

Estimation of second primary cancers risk based on the treatment planning system

International Nuclear Information System (INIS)

Jin Chufeng; Sun Guangyao; Liu Hui; Zheng Huaqing; Cheng Mengyun; Li Gui; Wu Yican; FDS Team

2011-01-01

Estimates of second primary cancers risk after radiotherapy has become increasingly important for comparative treatment planning. A new method based on the treatment planning system to estimate the risk of second primary cancers was introduced in this paper. Using the Advanced/Accurate Radiotherapy Treatment System(ARTS), a treatment planning system developed by the FDS team,the risk of second primary cancer was estimated over two treatment plans for a patient with pancreatic cancer. Based on the second primary cancer risk, the two plans were compared. It was found that,kidney and gall-bladder had higher risk to develop second primary cancer. A better plan was chosen by the analysis of second primary cancer risk. The results showed that this risk estimation method we developed could be used to evaluate treatment plans. (authors)

A Compact VLSI System for Bio-Inspired Visual Motion Estimation.

Science.gov (United States)

Shi, Cong; Luo, Gang

2018-04-01

This paper proposes a bio-inspired visual motion estimation algorithm based on motion energy, along with its compact very-large-scale integration (VLSI) architecture using low-cost embedded systems. The algorithm mimics motion perception functions of retina, V1, and MT neurons in a primate visual system. It involves operations of ternary edge extraction, spatiotemporal filtering, motion energy extraction, and velocity integration. Moreover, we propose the concept of confidence map to indicate the reliability of estimation results on each probing location. Our algorithm involves only additions and multiplications during runtime, which is suitable for low-cost hardware implementation. The proposed VLSI architecture employs multiple (frame, pixel, and operation) levels of pipeline and massively parallel processing arrays to boost the system performance. The array unit circuits are optimized to minimize hardware resource consumption. We have prototyped the proposed architecture on a low-cost field-programmable gate array platform (Zynq 7020) running at 53-MHz clock frequency. It achieved 30-frame/s real-time performance for velocity estimation on 160 × 120 probing locations. A comprehensive evaluation experiment showed that the estimated velocity by our prototype has relatively small errors (average endpoint error < 0.5 pixel and angular error < 10°) for most motion cases.

A multi-camera system for real-time pose estimation

Science.gov (United States)

Savakis, Andreas; Erhard, Matthew; Schimmel, James; Hnatow, Justin

2007-04-01

This paper presents a multi-camera system that performs face detection and pose estimation in real-time and may be used for intelligent computing within a visual sensor network for surveillance or human-computer interaction. The system consists of a Scene View Camera (SVC), which operates at a fixed zoom level, and an Object View Camera (OVC), which continuously adjusts its zoom level to match objects of interest. The SVC is set to survey the whole filed of view. Once a region has been identified by the SVC as a potential object of interest, e.g. a face, the OVC zooms in to locate specific features. In this system, face candidate regions are selected based on skin color and face detection is accomplished using a Support Vector Machine classifier. The locations of the eyes and mouth are detected inside the face region using neural network feature detectors. Pose estimation is performed based on a geometrical model, where the head is modeled as a spherical object that rotates upon the vertical axis. The triangle formed by the mouth and eyes defines a vertical plane that intersects the head sphere. By projecting the eyes-mouth triangle onto a two dimensional viewing plane, equations were obtained that describe the change in its angles as the yaw pose angle increases. These equations are then combined and used for efficient pose estimation. The system achieves real-time performance for live video input. Testing results assessing system performance are presented for both still images and video.

A Nonlinear Attitude Estimator for Attitude and Heading Reference Systems Based on MEMS Sensors

DEFF Research Database (Denmark)

Wang, Yunlong; Soltani, Mohsen; Hussain, Dil muhammed Akbar

2016-01-01

In this paper, a nonlinear attitude estimator is designed for an Attitude Heading and Reference System (AHRS) based on Micro Electro-Mechanical Systems (MEMS) sensors. The design process of the attitude estimator is stated with detail, and the equilibrium point of the estimator error model...... the problems in previous research works. Moreover, the estimation of MEMS gyroscope bias is also inclueded in this estimator. The designed nonlinear attitude estimator is firstly tested in simulation environment and then implemented in an AHRS hardware for further experiments. Finally, the attitude estimation...

Optimal State Estimation for Discrete-Time Markov Jump Systems with Missing Observations

Directory of Open Access Journals (Sweden)

Qing Sun

2014-01-01

Full Text Available This paper is concerned with the optimal linear estimation for a class of direct-time Markov jump systems with missing observations. An observer-based approach of fault detection and isolation (FDI is investigated as a detection mechanic of fault case. For systems with known information, a conditional prediction of observations is applied and fault observations are replaced and isolated; then, an FDI linear minimum mean square error estimation (LMMSE can be developed by comprehensive utilizing of the correct information offered by systems. A recursive equation of filtering based on the geometric arguments can be obtained. Meanwhile, a stability of the state estimator will be guaranteed under appropriate assumption.

A virtually blind spectrum efficient channel estimation technique for mimo-ofdm system

International Nuclear Information System (INIS)

Ullah, M.O.

2015-01-01

Multiple-Input Multiple-Output antennas in conjunction with Orthogonal Frequency-Division Multiplexing is a dominant air interface for 4G and 5G cellular communication systems. Additionally, MIMO- OFDM based air interface is the foundation for latest wireless Local Area Networks, wireless Personal Area Networks, and digital multimedia broadcasting. Whether it is a single antenna or a multi-antenna OFDM system, accurate channel estimation is required for coherent reception. Training-based channel estimation methods require multiple pilot symbols and therefore waste a significant portion of channel bandwidth. This paper describes a virtually blind spectrum efficient channel estimation scheme for MIMO-OFDM systems which operates well below the Nyquist criterion. (author)

Two-Dimensional DOA Estimation Using Arbitrary Arrays for Massive MIMO Systems

Directory of Open Access Journals (Sweden)

Alban Doumtsop Lonkeng

2017-01-01

Full Text Available With the quick advancement of wireless communication networks, the need for massive multiple-input-multiple-output (MIMO to offer adequate network capacity has turned out to be apparent. As a portion of array signal processing, direction-of-arrival (DOA estimation is of indispensable significance to acquire directional data of sources and to empower the 3D beamforming. In this paper, the performance of DOA estimation for massive MIMO systems is analyzed and compared using a low-complexity algorithm. To be exact, the 2D Fourier domain line search (FDLS MUSIC algorithm is studied to mutually estimate elevation and azimuth angle, and arbitrary array geometry is utilized to represent massive MIMO systems. To avoid the computational burden in estimating the data covariance matrix and its eigenvalue decomposition (EVD due to the large-scale sensors involved in massive MIMO systems, the reduced-dimension data matrix is applied on the signals received by the array. The performance is examined and contrasted with the 2D MUSIC algorithm for different types of antenna configuration. Finally, the array resolution is selected to investigate the performance of elevation and azimuth estimation. The effectiveness and advantage of the proposed technique have been proven by detailed simulations for different types of MIMO array configuration.

Channel Estimation and Optimal Power Allocation for a Multiple-Antenna OFDM System

Directory of Open Access Journals (Sweden)

Yao Kung

2002-01-01

Full Text Available We propose combining channel estimation and optimal power allocation approaches for a multiple-antenna orthogonal frequency division multiplexing (OFDM system in high-speed transmission applications. We develop a least-square channel estimation approach, derive the performance bound of the estimator, and investigate the optimal training sequences for initial channel acquisition. Based on the channel estimates, the optimal power allocation solution which maximizes the bandwidth efficiency is derived under power and quality of service (Qos (symbol error rate constraints. It is shown that combining channel tracking and adaptive power allocation can dramatically enhance the outage capacity of an OFDM multiple-antenna system when severing fading occurs.

Estimating the Economic Benefits of Regional Ocean Observing Systems

National Research Council Canada - National Science Library

Kite-Powell, Hauke L; Colgan, Charles S; Wellman, Katharine F; Pelsoci, Thomas; Wieand, Kenneth; Pendleton, Linwood; Kaiser, Mark J; Pulsipher, Allan G; Luger, Michael

2005-01-01

We develop a methodology to estimate the potential economic benefits from new investments in regional coastal ocean observing systems in US waters, and apply this methodology to generate preliminary...

Distributed Channel Estimation and Pilot Contamination Analysis for Massive MIMO-OFDM Systems

KAUST Repository

Zaib, Alam

2016-07-22

By virtue of large antenna arrays, massive MIMO systems have a potential to yield higher spectral and energy efficiency in comparison with the conventional MIMO systems. This paper addresses uplink channel estimation in massive MIMO-OFDM systems with frequency selective channels. We propose an efficient distributed minimum mean square error (MMSE) algorithm that can achieve near optimal channel estimates at low complexity by exploiting the strong spatial correlation among antenna array elements. The proposed method involves solving a reduced dimensional MMSE problem at each antenna followed by a repetitive sharing of information through collaboration among neighboring array elements. To further enhance the channel estimates and/or reduce the number of reserved pilot tones, we propose a data-aided estimation technique that relies on finding a set of most reliable data carriers. Furthermore, we use stochastic geometry to quantify the pilot contamination, and in turn use this information to analyze the effect of pilot contamination on channel MSE. The simulation results validate our analysis and show near optimal performance of the proposed estimation algorithms.

Estimating model parameters in nonautonomous chaotic systems using synchronization

International Nuclear Information System (INIS)

Yang, Xiaoli; Xu, Wei; Sun, Zhongkui

2007-01-01

In this Letter, a technique is addressed for estimating unknown model parameters of multivariate, in particular, nonautonomous chaotic systems from time series of state variables. This technique uses an adaptive strategy for tracking unknown parameters in addition to a linear feedback coupling for synchronizing systems, and then some general conditions, by means of the periodic version of the LaSalle invariance principle for differential equations, are analytically derived to ensure precise evaluation of unknown parameters and identical synchronization between the concerned experimental system and its corresponding receiver one. Exemplifies are presented by employing a parametrically excited 4D new oscillator and an additionally excited Ueda oscillator. The results of computer simulations reveal that the technique not only can quickly track the desired parameter values but also can rapidly respond to changes in operating parameters. In addition, the technique can be favorably robust against the effect of noise when the experimental system is corrupted by bounded disturbance and the normalized absolute error of parameter estimation grows almost linearly with the cutoff value of noise strength in simulation

Preliminary Cost Estimates for Nuclear Hydrogen Production: HTSE System

International Nuclear Information System (INIS)

Yang, K. J.; Lee, K. Y.; Lee, T. H.

2008-01-01

KAERI is now focusing on the research and development of the key technologies required for the design and realization of a nuclear hydrogen production system. As a preliminary study of cost estimates for nuclear hydrogen systems, the hydrogen production costs of the nuclear energy sources benchmarking GTMHR and PBMR are estimated in the necessary input data on a Korean specific basis. G4-ECONS was appropriately modified to calculate the cost for hydrogen production of HTSE (High Temperature Steam Electrolysis) process with VHTR (Very High Temperature nuclear Reactor) as a thermal energy source. The estimated costs presented in this paper show that hydrogen production by the VHTR could be competitive with current techniques of hydrogen production from fossil fuels if CO 2 capture and sequestration is required. Nuclear production of hydrogen would allow large-scale production of hydrogen at economic prices while avoiding the release of CO 2 . Nuclear production of hydrogen could thus become the enabling technology for the hydrogen economy. The major factors that would affect the cost of hydrogen were also discussed

Estimation of system parameters in discrete dynamical systems from time series

International Nuclear Information System (INIS)

Palaniyandi, P.; Lakshmanan, M.

2005-01-01

We propose a simple method to estimate the parameters involved in discrete dynamical systems from time series. The method is based on the concept of controlling chaos by constant feedback. The major advantages of the method are that it needs a minimal number of time series data (either vector or scalar) and is applicable to dynamical systems of any dimension. The method also works extremely well even in the presence of noise in the time series. The method is specifically illustrated by means of logistic and Henon maps

Methods of multicriterion estimations in system total quality management

Directory of Open Access Journals (Sweden)

Nikolay V. Diligenskiy

2011-05-01

Full Text Available In this article the method of multicriterion comparative estimation of efficiency (Data Envelopment Analysis and possibility of its application in system of total quality management is considered.

Estimating parameters of chaotic systems synchronized by external driving signal

International Nuclear Information System (INIS)

Wu Xiaogang; Wang Zuxi

2007-01-01

Noise-induced synchronization (NIS) has evoked great research interests recently. Two uncoupled identical chaotic systems can achieve complete synchronization (CS) by feeding a common noise with appropriate intensity. Actually, NIS belongs to the category of external feedback control (EFC). The significance of applying EFC in secure communication lies in fact that the trajectory of chaotic systems is disturbed so strongly by external driving signal that phase space reconstruction attack fails. In this paper, however, we propose an approach that can accurately estimate the parameters of the chaotic systems synchronized by external driving signal through chaotic transmitted signal, driving signal and their derivatives. Numerical simulation indicates that this approach can estimate system parameters and external coupling strength under two driving modes in a very rapid manner, which implies that EFC is not superior to other methods in secure communication

An adaptive state of charge estimation approach for lithium-ion series-connected battery system

Science.gov (United States)

Peng, Simin; Zhu, Xuelai; Xing, Yinjiao; Shi, Hongbing; Cai, Xu; Pecht, Michael

2018-07-01

Due to the incorrect or unknown noise statistics of a battery system and its cell-to-cell variations, state of charge (SOC) estimation of a lithium-ion series-connected battery system is usually inaccurate or even divergent using model-based methods, such as extended Kalman filter (EKF) and unscented Kalman filter (UKF). To resolve this problem, an adaptive unscented Kalman filter (AUKF) based on a noise statistics estimator and a model parameter regulator is developed to accurately estimate the SOC of a series-connected battery system. An equivalent circuit model is first built based on the model parameter regulator that illustrates the influence of cell-to-cell variation on the battery system. A noise statistics estimator is then used to attain adaptively the estimated noise statistics for the AUKF when its prior noise statistics are not accurate or exactly Gaussian. The accuracy and effectiveness of the SOC estimation method is validated by comparing the developed AUKF and UKF when model and measurement statistics noises are inaccurate, respectively. Compared with the UKF and EKF, the developed method shows the highest SOC estimation accuracy.

Maintenance Management Support Systems for component aging estimation at nuclear power plants

International Nuclear Information System (INIS)

Shimizu, Shunichi; Ando, Yasumasa; Morioka, Toshihiko; Okuzumi, Naoaki

1991-01-01

Maintenance Management Support Systems (MMSSs) for nuclear power plants have been developed using component aging estimation methods and decision tree analysis for maintenance planning. The former evaluates actual component reliability through statistical analysis on field maintenance data. The latter provides preventive maintenance (PM) planning guidance using heuristic expert knowledge and estimated reliability parameters. The following aspects have been investigated: (1) A systematic and effective method of managing components/parts design information and field maintenance data (2) A method for estimating component aging based on a statistical analysis of field maintenance data (3) A method for providing PM planning guidance using estimated component reliability/performance parameters and decision tree analysis. Based on these investigations, two MMSSs were developed. One deals with 'general maintenance data', which are common to all component types and are amenable to common data handling. The other system deals with 'specific maintenance data', which are specific to an individual component type. Both systems provide PM planning guidance for PM cycles propriety and the PM work priority. The function of these systems were verified using simulated maintenance data. (author)

Exact dimension estimation of interacting qubit systems assisted by a single quantum probe

Science.gov (United States)

Sone, Akira; Cappellaro, Paola

2017-12-01

Estimating the dimension of an Hilbert space is an important component of quantum system identification. In quantum technologies, the dimension of a quantum system (or its corresponding accessible Hilbert space) is an important resource, as larger dimensions determine, e.g., the performance of quantum computation protocols or the sensitivity of quantum sensors. Despite being a critical task in quantum system identification, estimating the Hilbert space dimension is experimentally challenging. While there have been proposals for various dimension witnesses capable of putting a lower bound on the dimension from measuring collective observables that encode correlations, in many practical scenarios, especially for multiqubit systems, the experimental control might not be able to engineer the required initialization, dynamics, and observables. Here we propose a more practical strategy that relies not on directly measuring an unknown multiqubit target system, but on the indirect interaction with a local quantum probe under the experimenter's control. Assuming only that the interaction model is given and the evolution correlates all the qubits with the probe, we combine a graph-theoretical approach and realization theory to demonstrate that the system dimension can be exactly estimated from the model order of the system. We further analyze the robustness in the presence of background noise of the proposed estimation method based on realization theory, finding that despite stringent constrains on the allowed noise level, exact dimension estimation can still be achieved.

The evolution of energy-transducing systems. Studies with archaebacteria

Science.gov (United States)

Stan-Lotter, Helga

1994-01-01

N-ethylmaleimide (NEM) inhibits the ATPase of H. saccharovorum in a nucleotide protectable manner. The bulk of C-14 NEM is incorporated into subunit one. Cyanogen bromide cleavage of labeled subunit one indicated that NEM bound to a peptide of a Mr of about 8,900. Thus, Cys 262 (H. salinarium numbering) may be the NEM binding site. Cyanogen bromide fragments have been submitted for sequencing. To prove the presence of three Cys residues in subunit one, alkaline cleavage following treatment with NTCB was carried out. Thiol reagents such as p-chloro mercuri phenyl sulfonate also inhibited the ATPase. However, this inhibition was not nucleotide-protectable, suggesting a different location and role for the PCMS-sensitive Cys. The proteolipid which was extracted with chloroform/methanol from the membranes of H. saccharovorum cross-reacted with an antiserum against subunit c (the DCCD-binding protein) of Escherichia coli. Following labeling of membranes from H. saccharovorum with C-14 DCCD under conditions, which inhibited ATP synthesis, the isotope was incorporated into one protein of Mr of about 6,500. Thus, the proteolipid of H. saccharovorum and the DCCD-labeled peptide may be identical. If so, these results suggest that the proteolipid is a component of the membrane sector of an archaeal F-type ATP synthase.

Frequency offset estimation in OFDM systems using Bayesian filtering

Science.gov (United States)

Yu, Yihua

2011-10-01

Orthogonal frequency division multiplexing (OFDM) is sensitive to carrier frequency offset (CFO) that causes inter-carrier interference (ICI). In this paper, we present two schemes for the CFO estimation, which are based on rejection sampling (RS) and a form of particle filtering (PF) called kernel smoothing technique, respectively. The first scheme is offline estimation, where the observations contained in the OFDM training symbol are treated in the batch mode. The second scheme is online estimation, where the observations in the OFDM training symbol are treated in the sequential manner. Simulations are provided to illustrate the performances of the schemes. Performance comparisons of the two schemes and with other Bayesian methods are provided. Simulation results show that the two schemes are effective when estimating the CFO and can effectively combat the effect of ICI in OFDM systems.

Discrete-time state estimation for stochastic polynomial systems over polynomial observations

Science.gov (United States)

Hernandez-Gonzalez, M.; Basin, M.; Stepanov, O.

2018-07-01

This paper presents a solution to the mean-square state estimation problem for stochastic nonlinear polynomial systems over polynomial observations confused with additive white Gaussian noises. The solution is given in two steps: (a) computing the time-update equations and (b) computing the measurement-update equations for the state estimate and error covariance matrix. A closed form of this filter is obtained by expressing conditional expectations of polynomial terms as functions of the state estimate and error covariance. As a particular case, the mean-square filtering equations are derived for a third-degree polynomial system with second-degree polynomial measurements. Numerical simulations show effectiveness of the proposed filter compared to the extended Kalman filter.

An improved fuzzy Kalman filter for state estimation of nonlinear systems

International Nuclear Information System (INIS)

Zhou, Z-J; Hu, C-H; Chen, L; Zhang, B-C

2008-01-01

The extended fuzzy Kalman filter (EFKF) is developed recently and used for state estimation of the nonlinear systems with uncertainty. Based on extension of the orthogonality principle and the extended fuzzy Kalman filter, an improved fuzzy Kalman filters (IFKF) is proposed in this paper, which is more applicable and can deal with the state estimation of the nonlinear systems better than the EFKF. A simulation study is provided to verify the efficiency of the proposed method

48 CFR 252.215-7002 - Cost estimating system requirements.

Science.gov (United States)

2010-10-01

... contract awards. Estimating system includes the Contractor's— (1) Organizational structure; (2) Established... (e) of this clause apply if the Contractor is a large business and either— (1) In its fiscal year...

Demonstration Integrated Knowledge-Based System for Estimating Human Error Probabilities

Energy Technology Data Exchange (ETDEWEB)

Auflick, Jack L.

1999-04-21

Human Reliability Analysis (HRA) is currently comprised of at least 40 different methods that are used to analyze, predict, and evaluate human performance in probabilistic terms. Systematic HRAs allow analysts to examine human-machine relationships, identify error-likely situations, and provide estimates of relative frequencies for human errors on critical tasks, highlighting the most beneficial areas for system improvements. Unfortunately, each of HRA's methods has a different philosophical approach, thereby producing estimates of human error probabilities (HEPs) that area better or worse match to the error likely situation of interest. Poor selection of methodology, or the improper application of techniques can produce invalid HEP estimates, where that erroneous estimation of potential human failure could have potentially severe consequences in terms of the estimated occurrence of injury, death, and/or property damage.

Study of the Convergence in State Estimators for LTI Systems with Event Detection

Directory of Open Access Journals (Sweden)

Juan C. Posada

2016-01-01

Full Text Available The methods frequently used to estimate the state of an LTI system require that the precise value of the output variable is known at all times, or at equidistant sampling times. In LTI systems, in which the output signal is measured through binary sensors (detectors, the traditional way of state observers design is not applicable even though the system has a complete observability matrix. This type of state observers design is known as passive. It is necessary, then, to introduce a new state estimation technique, which allows reckoning the state from the information of the variable’s crossing through a detector’s action threshold (switch. This paper seeks, therefore, to study the convergence in this type of estimators in finite time, allowing establishing, theoretically, whether some family of the proposed models can be estimated in a convergent way through the use of the estimation technique based on events.

INTERVAL STATE ESTIMATION FOR SINGULAR DIFFERENTIAL EQUATION SYSTEMS WITH DELAYS

Directory of Open Access Journals (Sweden)

T. A. Kharkovskaia

2016-07-01

Full Text Available The paper deals with linear differential equation systems with algebraic restrictions (singular systems and a method of interval observer design for this kind of systems. The systems contain constant time delay, measurement noise and disturbances. Interval observer synthesis is based on monotone and cooperative systems technique, linear matrix inequations, Lyapunov function theory and interval arithmetic. The set of conditions that gives the possibility for interval observer synthesis is proposed. Results of synthesized observer operation are shown on the example of dynamical interindustry balance model. The advantages of proposed method are that it is adapted to observer design for uncertain systems, if the intervals of admissible values for uncertain parameters are given. The designed observer is capable to provide asymptotically definite limits on the estimation accuracy, since the interval of admissible values for the object state is defined at every instant. The obtained result provides an opportunity to develop the interval estimation theory for complex systems that contain parametric uncertainty, varying delay and nonlinear elements. Interval observers increasingly find applications in economics, electrical engineering, mechanical systems with constraints and optimal flow control.

Determination of power system component parameters using nonlinear dead beat estimation method

Science.gov (United States)

Kolluru, Lakshmi

Power systems are considered the most complex man-made wonders in existence today. In order to effectively supply the ever increasing demands of the consumers, power systems are required to remain stable at all times. Stability and monitoring of these complex systems are achieved by strategically placed computerized control centers. State and parameter estimation is an integral part of these facilities, as they deal with identifying the unknown states and/or parameters of the systems. Advancements in measurement technologies and the introduction of phasor measurement units (PMU) provide detailed and dynamic information of all measurements. Accurate availability of dynamic measurements provides engineers the opportunity to expand and explore various possibilities in power system dynamic analysis/control. This thesis discusses the development of a parameter determination algorithm for nonlinear power systems, using dynamic data obtained from local measurements. The proposed algorithm was developed by observing the dead beat estimator used in state space estimation of linear systems. The dead beat estimator is considered to be very effective as it is capable of obtaining the required results in a fixed number of steps. The number of steps required is related to the order of the system and the number of parameters to be estimated. The proposed algorithm uses the idea of dead beat estimator and nonlinear finite difference methods to create an algorithm which is user friendly and can determine the parameters fairly accurately and effectively. The proposed algorithm is based on a deterministic approach, which uses dynamic data and mathematical models of power system components to determine the unknown parameters. The effectiveness of the algorithm is tested by implementing it to identify the unknown parameters of a synchronous machine. MATLAB environment is used to create three test cases for dynamic analysis of the system with assumed known parameters. Faults are

Body composition and net energy requirements of Brazilian Somali lambs

Directory of Open Access Journals (Sweden)

Elzânia S. Pereira

2014-12-01

Full Text Available The aim of this study was to determine the energy requirements for maintenance (NEm and growth of 48 Brazilian Somali ram lambs with an average initial body weight of 13.47±1.76 kg. Eight animals were slaughtered at the trials beginning as a reference group to estimate the initial empty body weight (EBW and body composition. The remaining animals were assigned to a randomised block design with eight replications per block and five diets with increasing metabolisable energy content (4.93, 8.65, 9.41, 10.12 and 11.24 MJ/kg dry matter. The logarithm of heat production was regressed against metabolisable energy intake (MEI, and the NEm (kJ/kg0.75 EBW/day were estimated by extrapolation, when MEI was set at zero. The NEm was 239.77 kJ/kg0.75 EBW/day. The animal’s energy and EBW fat contents increased from 11.20 MJ/kg and 208.54 g/kg to 13.54 MJ/kg and 274.95 g/kg of EBW, respectively, as the BW increased from 13 to 28.70 kg. The net energy requirements for EBW gain increased from 13.79 to 16.72 MJ/kg EBW gain for body weights of 13 and 28.70 kg. Our study indicated the net energy requirements for maintenance in Brazilian Somali lambs were similar to the values commonly recommended by the United States’ nutritional system, but lower than the values recommended by Agricultural Research Council and Commonwealth Scientific and Industrial Research Organization. Net requirements for weight gain were less compared to the values commonly recommended by nutritional system of the United States.

Distributed Generation potential of the U.S. commercial sector

International Nuclear Information System (INIS)

Hamachi LaCommare, Kristina; Edwards, Jennifer L.; Gumerman, Etan; Marnay, Chris

2005-01-01

Small-scale (100 kW - 5 MW) on-site distributed generation (DG) economically driven by combined heat and power (CHP) applications and, in some cases, reliability concerns will likely emerge as a common feature of commercial building energy systems in developed countries over the next two decades. In the U.S., private and public expectations for this technology are heavily influenced by forecasts published by the Energy Information Administration (EIA), most notably the Annual Energy Outlook (AEO). EIA's forecasts are typically made using the National Energy Modeling System (NEMS), which has a forecasting module that predicts the penetration of several possible commercial building DG technologies over the period 2005-2025. Annual penetration is forecast by estimating the payback period for each technology, for each of a limited number of representative building types, for each of nine regions. This process results in an AEO2004 forecast deployment of about a total 3 GW of DG electrical generating capacity by 2025, which is only 0.25% of total forecast U.S. capacity. Analyses conducted using both the AEO2003 and AEO2004 versions of NEMS changes the baseline costs and performance characteristics of DG to reflect a world without U.S. Dept. of Energy (DOE) research into several thermal DG technologies, which is then compared to a case with enhanced technology representative of the successful achievement of DOE research goals. The net difference in 2025 DG penetration is dramatic using the AEO2003 version of NEMS, but much smaller in the AEO2004 version. The significance and validity of these contradictory results are discussed, and possibilities for improving estimates of commercial U.S. DG potential are explored

Estimation of regulated term of technical systems further operation

International Nuclear Information System (INIS)

Strel'nikov, V.P.

2008-01-01

The technique of estimating the regulated term of technical systems further operation on the basis of data on failures during operation and use of probabilistic-physical model of failures (DN-distribution) is proposed

Online Parameter Estimation for a Centrifugal Decanter System

DEFF Research Database (Denmark)

Larsen, Jesper Abildgaard; Alstrøm, Preben

2014-01-01

In many processing plants decanter systems are used for separation of heterogenious mixtures, and even though they account for a large fraction of the energy consumption, most decanters just runs at a fixed setpoint. Here, multi model estimation is applied to a waste water treatment plant, and it...

Um olhar sobre o diabetes na infância e na juventude: nem todos são Tipo 1

Directory of Open Access Journals (Sweden)

Mauren Isfer ANGHEBEM-OLIVEIRA

2013-12-01

Full Text Available O Diabetes mellitus (DM é caracterizado por um quadro de hiperglicemia crônica, que com os anos pode causar disfunção endotelial e sérias complicações vasculares, como a retinopatia, nefropatia e o infarto agudo do miocárdio. À medida que a ciência avança na compreensão da fisiopatologia e das características clínico-laboratoriais do diabetes, sua classificação tem sido adaptada, justamente porque a correta classificação do diabetes impacta no prognóstico e tratamento do paciente. Atualmente, o diabetes é classificado em DM tipo 1, DM tipo 2, DM gestacional e Outros Tipos Específicos, que inclui a categoria MODY (do inglês, Maturity Onset Diabetes of the Young ou diabetes da maturidade com início na juventude. O que esta revisão pretende mostrar é quem nem todo diabetes diagnosticado na infância e na juventude é DM tipo 1. O correto diagnóstico e classificação do DM são fundamentais, uma vez que o prognóstico e o tratamento podem diferir dependendo da causa que predispôs a criança ou adolescente à doença.

Parameter and state estimation in nonlinear dynamical systems

Science.gov (United States)

Creveling, Daniel R.

This thesis is concerned with the problem of state and parameter estimation in nonlinear systems. The need to evaluate unknown parameters in models of nonlinear physical, biophysical and engineering systems occurs throughout the development of phenomenological or reduced models of dynamics. When verifying and validating these models, it is important to incorporate information from observations in an efficient manner. Using the idea of synchronization of nonlinear dynamical systems, this thesis develops a framework for presenting data to a candidate model of a physical process in a way that makes efficient use of the measured data while allowing for estimation of the unknown parameters in the model. The approach presented here builds on existing work that uses synchronization as a tool for parameter estimation. Some critical issues of stability in that work are addressed and a practical framework is developed for overcoming these difficulties. The central issue is the choice of coupling strength between the model and data. If the coupling is too strong, the model will reproduce the measured data regardless of the adequacy of the model or correctness of the parameters. If the coupling is too weak, nonlinearities in the dynamics could lead to complex dynamics rendering any cost function comparing the model to the data inadequate for the determination of model parameters. Two methods are introduced which seek to balance the need for coupling with the desire to allow the model to evolve in its natural manner without coupling. One method, 'balanced' synchronization, adds to the synchronization cost function a requirement that the conditional Lyapunov exponents of the model system, conditioned on being driven by the data, remain negative but small in magnitude. Another method allows the coupling between the data and the model to vary in time according to a specific form of differential equation. The coupling dynamics is damped to allow for a tendency toward zero coupling

Parameter estimation for stiff deterministic dynamical systems via ensemble Kalman filter

International Nuclear Information System (INIS)

Arnold, Andrea; Calvetti, Daniela; Somersalo, Erkki

2014-01-01

A commonly encountered problem in numerous areas of applications is to estimate the unknown coefficients of a dynamical system from direct or indirect observations at discrete times of some of the components of the state vector. A related problem is to estimate unobserved components of the state. An egregious example of such a problem is provided by metabolic models, in which the numerous model parameters and the concentrations of the metabolites in tissue are to be estimated from concentration data in the blood. A popular method for addressing similar questions in stochastic and turbulent dynamics is the ensemble Kalman filter (EnKF), a particle-based filtering method that generalizes classical Kalman filtering. In this work, we adapt the EnKF algorithm for deterministic systems in which the numerical approximation error is interpreted as a stochastic drift with variance based on classical error estimates of numerical integrators. This approach, which is particularly suitable for stiff systems where the stiffness may depend on the parameters, allows us to effectively exploit the parallel nature of particle methods. Moreover, we demonstrate how spatial prior information about the state vector, which helps the stability of the computed solution, can be incorporated into the filter. The viability of the approach is shown by computed examples, including a metabolic system modeling an ischemic episode in skeletal muscle, with a high number of unknown parameters. (paper)

Estimated effects on radiation doses from alternatives in a spent fuel transportation system

International Nuclear Information System (INIS)

Schneider, K.J.; Ross, W.A.; Smith, R.I.

1988-07-01

This paper contains the results of a study of estimated radiation doses to the public and workers from the transport of spent fuel from commercial nuclear power reactors to a geologic repository. A postulated reference rail/legal-weight truck transportation system is defined that would use current transportation technology, and provide a breakdown of activities and time/distance/dose-rate estimates for each activity within the system. Collective doses are estimated for each of the major activities at the reactor site, in transit, and at the repository receiving facility. Annual individual doses to the maximally exposed individuals or groups of individuals are also estimated. The dose-reduction potentials and costs are estimated for a total of 17 conceptual alternatives and subalternatives to the postulated reference system. Most of the alternatives evaluated are estimated to provide both cost and dose reductions. The major conclusion is that the potential exists for significant future reductions in radiation doses to the public and workers and for reductions in costs compared to those based on a continuation of past practices in the US

Estimated effects on radiation doses from alternatives in a spent fuel transportation system

International Nuclear Information System (INIS)

Schneider, K.J.; Ross, W.A.; Smith, R.I.

1988-01-01

This paper contains the results of a study of estimated radiation doses to the public and workers from the transport of spent fuel from commercial nuclear power reactors to a geologic repository. A postulated reference rail/legal-weight truck transportation system is defined that would use current transportation technology, and provide a breakdown of activities and time/distance/dose-rate estimates for each activity within the system. Collective doses are estimated for each of the major activities at the reactor site, in transit, and at the repository receiving facility. Annual individual doses to the maximally exposed individuals or groups of individuals also estimated. The dose-reduction potentials and costs are estimated for a total of 17 conceptual alternatives and subalternatives to the postulated reference system. Most of the alternatives evaluated are estimated to provide both cost and dose reductions. The major conclusion is that the potential exists for significant future reductions in radiation doses to the public and workers and for reductions in costs compared to those based on a continuation of past practices in the U.S

Uncertainty analysis methods for estimation of reliability of passive system of VHTR

International Nuclear Information System (INIS)

Han, S.J.

2012-01-01

An estimation of reliability of passive system for the probabilistic safety assessment (PSA) of a very high temperature reactor (VHTR) is under development in Korea. The essential approach of this estimation is to measure the uncertainty of the system performance under a specific accident condition. The uncertainty propagation approach according to the simulation of phenomenological models (computer codes) is adopted as a typical method to estimate the uncertainty for this purpose. This presentation introduced the uncertainty propagation and discussed the related issues focusing on the propagation object and its surrogates. To achieve a sufficient level of depth of uncertainty results, the applicability of the propagation should be carefully reviewed. For an example study, Latin-hypercube sampling (LHS) method as a direct propagation was tested for a specific accident sequence of VHTR. The reactor cavity cooling system (RCCS) developed by KAERI was considered for this example study. This is an air-cooled type passive system that has no active components for its operation. The accident sequence is a low pressure conduction cooling (LPCC) accident that is considered as a design basis accident for the safety design of VHTR. This sequence is due to a large failure of the pressure boundary of the reactor system such as a guillotine break of coolant pipe lines. The presentation discussed the obtained insights (benefit and weakness) to apply an estimation of reliability of passive system

Joint Symbol Timing and CFO Estimation for OFDM/OQAM Systems in Multipath Channels

Directory of Open Access Journals (Sweden)

Petrella Angelo

2010-01-01

Full Text Available The problem of data-aided synchronization for orthogonal frequency division multiplexing (OFDM systems based on offset quadrature amplitude modulation (OQAM in multipath channels is considered. In particular, the joint maximum-likelihood (ML estimator for carrier-frequency offset (CFO, amplitudes, phases, and delays, exploiting a short known preamble, is derived. The ML estimators for phases and amplitudes are in closed form. Moreover, under the assumption that the CFO is sufficiently small, a closed form approximate ML (AML CFO estimator is obtained. By exploiting the obtained closed form solutions a cost function whose peaks provide an estimate of the delays is derived. In particular, the symbol timing (i.e., the delay of the first multipath component is obtained by considering the smallest estimated delay. The performance of the proposed joint AML estimator is assessed via computer simulations and compared with that achieved by the joint AML estimator designed for AWGN channel and that achieved by a previously derived joint estimator for OFDM systems.

A Fast LMMSE Channel Estimation Method for OFDM Systems

Directory of Open Access Journals (Sweden)

Zhou Wen

2009-01-01

Full Text Available A fast linear minimum mean square error (LMMSE channel estimation method has been proposed for Orthogonal Frequency Division Multiplexing (OFDM systems. In comparison with the conventional LMMSE channel estimation, the proposed channel estimation method does not require the statistic knowledge of the channel in advance and avoids the inverse operation of a large dimension matrix by using the fast Fourier transform (FFT operation. Therefore, the computational complexity can be reduced significantly. The normalized mean square errors (NMSEs of the proposed method and the conventional LMMSE estimation have been derived. Numerical results show that the NMSE of the proposed method is very close to that of the conventional LMMSE method, which is also verified by computer simulation. In addition, computer simulation shows that the performance of the proposed method is almost the same with that of the conventional LMMSE method in terms of bit error rate (BER.

Time of Arrival Estimation in Probability-Controlled Generalized CDMA Systems

Directory of Open Access Journals (Sweden)

Hagit Messer

2007-11-01

Full Text Available In recent years, more and more wireless communications systems are required to provide also a positioning measurement. In code division multiple access (CDMA communication systems, the positioning accuracy is significantly degraded by the multiple access interference (MAI caused by other users in the system. This MAI is commonly managed by a power control mechanism, and yet, MAI has a major effect on positioning accuracy. Probability control is a recently introduced interference management mechanism. In this mechanism, a user with excess power chooses not to transmit some of its symbols. The information in the nontransmitted symbols is recovered by an error-correcting code (ECC, while all other users receive a more reliable data during these quiet periods. Previous research had shown that the implementation of a probability control mechanism can significantly reduce the MAI. In this paper, we show that probability control also improves the positioning accuracy. We focus on time-of-arrival (TOA based positioning systems. We analyze the TOA estimation performance in a generalized CDMA system, in which the probability control mechanism is employed, where the transmitted signal is noncontinuous with a symbol transmission probability smaller than 1. The accuracy of the TOA estimation is determined using appropriate modifications of the Cramer-Rao bound on the delay estimation. Keeping the average transmission power constant, we show that the TOA accuracy of each user does not depend on its transmission probability, while being a nondecreasing function of the transmission probability of any other user. Therefore, a generalized, noncontinuous CDMA system with a probability control mechanism can always achieve better positioning performance, for all users in the network, than a conventional, continuous, CDMA system.

A Model of U.S. Commercial Distributed Generation Adoption

Energy Technology Data Exchange (ETDEWEB)

LaCommare, Kristina Hamachi; Ryan Firestone; Zhou, Nan; Maribu,Karl; Marnay, Chris

2006-01-10

Small-scale (100 kW-5 MW) on-site distributed generation (DG) economically driven by combined heat and power (CHP) applications and, in some cases, reliability concerns will likely emerge as a common feature of commercial building energy systems over the next two decades. Forecasts of DG adoption published by the Energy Information Administration (EIA) in the Annual Energy Outlook (AEO) are made using the National Energy Modeling System (NEMS), which has a forecasting module that predicts the penetration of several possible commercial building DG technologies over the period 2005-2025. NEMS is also used for estimating the future benefits of Department of Energy research and development used in support of budget requests and management decisionmaking. The NEMS approach to modeling DG has some limitations, including constraints on the amount of DG allowed for retrofits to existing buildings and a small number of possible sizes for each DG technology. An alternative approach called Commercial Sector Model (ComSeM) is developed to improve the way in which DG adoption is modeled. The approach incorporates load shapes for specific end uses in specific building types in specific regions, e.g., cooling in hospitals in Atlanta or space heating in Chicago offices. The Distributed Energy Resources Customer Adoption Model (DER-CAM) uses these load profiles together with input cost and performance DG technology assumptions to model the potential DG adoption for four selected cities and two sizes of five building types in selected forecast years to 2022. The Distributed Energy Resources Market Diffusion Model (DER-MaDiM) is then used to then tailor the DER-CAM results to adoption projections for the entire U.S. commercial sector for all forecast years from 2007-2025. This process is conducted such that the structure of results are consistent with the structure of NEMS, and can be re-injected into NEMS that can then be used to integrate adoption results into a full forecast.

Performance Estimation for Embedded Systems with Data and Control Dependencies

DEFF Research Database (Denmark)

Pop, Paul; Eles, Petru; Peng, Zebo

2000-01-01

In this paper we present an approach to performance estimation for hard real-time systems. We consider architectures consisting of multiple processors. The scheduling policy is based on a preemptive strategy with static priorities. Our model of the system captures both data and control dependencies...

Case Study: Zutphen : Estimates of levee system reliability

NARCIS (Netherlands)

Roscoe, K.; Kothuis, Baukje; Kok, Matthijs

2017-01-01

Estimates of levee system reliability can conflict with experience and intuition. For example, a very high failure probability may be computed while no evidence of failure has been observed, or a very low failure probability when signs of failure have been detected.

A new system for seismic yield estimation of underground explosions

International Nuclear Information System (INIS)

Murphy, J.R.

1991-01-01

Research conducted over the past decade has led to the development of a number of innovative procedures for estimating the yields of underground nuclear explosions based on systematic analyses of digital seismic data recorded from these tests. In addition, a wide variety of new data regarding the geophysical environments at Soviet test locations have now become available as a result of the Joint Verification Experiment (JVE) and associated data exchanges. The system described in this paper represents an attempt to integrate all these new capabilities and data into a comprehensive operational prototype which can be used to obtain optimum seismic estimates of explosion yield together with quantitative measures of the uncertainty in those estimates. The implementation of this system has involved a wide variety of technical tasks, including the development of a comprehensive seismic database and related database access software, formulation of a graphical test site information interface for accessing available information on explosion source conditions, design of an interactive seismic analyst station for use in processing the observed data to extract the required magnitude measures and the incorporation of formal statistical analysis modules for use in yield estimation and assessment

A BIM-based system for demolition and renovation waste estimation and planning

International Nuclear Information System (INIS)

Cheng, Jack C.P.; Ma, Lauren Y.H.

2013-01-01

Highlights: ► We developed a waste estimation system leveraging the BIM technology. ► The system can calculate waste disposal charging fee and pick-up truck demand. ► We presented an example scenario demonstrating this system. ► Automatic, time-saving and wide applicability are the features of the system. - Abstract: Due to the rising worldwide awareness of green environment, both government and contractors have to consider effective construction and demolition (C and D) waste management practices. The last two decades have witnessed the growing importance of demolition and renovation (D and R) works and the growing amount of D and R waste disposed to landfills every day, especially in developed cities like Hong Kong. Quantitative waste prediction is crucial for waste management. It can enable contractors to pinpoint critical waste generation processes and to plan waste control strategies. In addition, waste estimation could also facilitate some government waste management policies, such as the waste disposal charging scheme in Hong Kong. Currently, tools that can accurately and conveniently estimate the amount of waste from construction, renovation, and demolition projects are lacking. In the light of this research gap, this paper presents a building information modeling (BIM) based system that we have developed for estimation and planning of D and R waste. BIM allows multi-disciplinary information to be superimposed within one digital building model. Our system can extract material and volume information through the BIM model and integrate the information for detailed waste estimation and planning. Waste recycling and reuse are also considered in our system. Extracted material information can be provided to recyclers before demolition or renovation to make recycling stage more cooperative and more efficient. Pick-up truck requirements and waste disposal charging fee for different waste facilities will also be predicted through our system. The results

A BIM-based system for demolition and renovation waste estimation and planning

Energy Technology Data Exchange (ETDEWEB)

Cheng, Jack C.P., E-mail: cejcheng@ust.hk [Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology (Hong Kong); Ma, Lauren Y.H., E-mail: yingzi@ust.hk [Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology (Hong Kong)

2013-06-15

Highlights: ► We developed a waste estimation system leveraging the BIM technology. ► The system can calculate waste disposal charging fee and pick-up truck demand. ► We presented an example scenario demonstrating this system. ► Automatic, time-saving and wide applicability are the features of the system. - Abstract: Due to the rising worldwide awareness of green environment, both government and contractors have to consider effective construction and demolition (C and D) waste management practices. The last two decades have witnessed the growing importance of demolition and renovation (D and R) works and the growing amount of D and R waste disposed to landfills every day, especially in developed cities like Hong Kong. Quantitative waste prediction is crucial for waste management. It can enable contractors to pinpoint critical waste generation processes and to plan waste control strategies. In addition, waste estimation could also facilitate some government waste management policies, such as the waste disposal charging scheme in Hong Kong. Currently, tools that can accurately and conveniently estimate the amount of waste from construction, renovation, and demolition projects are lacking. In the light of this research gap, this paper presents a building information modeling (BIM) based system that we have developed for estimation and planning of D and R waste. BIM allows multi-disciplinary information to be superimposed within one digital building model. Our system can extract material and volume information through the BIM model and integrate the information for detailed waste estimation and planning. Waste recycling and reuse are also considered in our system. Extracted material information can be provided to recyclers before demolition or renovation to make recycling stage more cooperative and more efficient. Pick-up truck requirements and waste disposal charging fee for different waste facilities will also be predicted through our system. The results

H∞ Channel Estimation for DS-CDMA Systems: A Partial Difference Equation Approach

Directory of Open Access Journals (Sweden)

Wei Wang

2013-01-01

Full Text Available In the communications literature, a number of different algorithms have been proposed for channel estimation problems with the statistics of the channel noise and observation noise exactly known. In practical systems, however, the channel parameters are often estimated using training sequences which lead to the statistics of the channel noise difficult to obtain. Moreover, the received signals are corrupted not only by the ambient noises but also by multiple-access interferences, so the statistics of observation noises is also difficult to obtain. In this paper, we will investigate the H∞ channel estimation problem for direct-sequence code-division multiple-access (DS-CDMA communication systems with time-varying multipath fading channels. The channel estimator is designed by applying a partial difference equation approach together with the innovation analysis theory. This method can give a sufficient and necessary condition for the existence of an H∞ channel estimator.

Estimating ionospheric delay using kriging: 2. Impact on satellite-based augmentation system availability

Science.gov (United States)

Sparks, Lawrence; Blanch, Juan; Pandya, Nitin

2011-12-01

An augmentation of the Global Positioning System, the Wide Area Augmentation System (WAAS) broadcasts, at each node of an ionospheric grid, an estimate of the vertical ionospheric delay and an integrity bound on the vertical delay error. To date, these quantities have been determined from a planar fit of slant delay measurements, projected to vertical using an obliquity factor specified by the standard thin shell model of the ionosphere. In a future WAAS upgrade (WAAS Follow-On Release 3), however, they will be calculated using an established, geo-statistical estimation technique known as kriging that generally provides higher estimate accuracy than planar fit estimation. This paper analyzes the impact of kriging on system availability. In a preliminary assessment, kriging is found to produce improvements in availability of up to 15%.

The Development of Multi-Agent System of State Estimation of Electric Power Systems Using Event Models

Directory of Open Access Journals (Sweden)

L. V. Massel

2015-01-01

Full Text Available The work objective is to offer a methodological approach to the development of multiagent systems (MAS in the energy sector. The agent approach is declared as an integral part of the Smart Grid concept (intelligent energy systems, but so far there is really neither methodological development and nor implementation in this area. The problem to estimate the states of electric power systems (EPS is one of the most important in the energy sector. Decentralization of calculations, when estimating the EPS states, allows reducing the host control center load and the amount of data transferred through the network.To achieve this aim were used the theory and methods for estimating the EPS state, artificial intelligence techniques, methods of object design and programming, multi-agent technologies, and algebraic Joiner-net network.The work analyses existing agent-based solutions, reveals their weaknesses, and proposes author's approach to MAS development in the energy sector, which includes 5 steps: 1 description of the future system, 2 construction and description of the agent-based scenarios, 3 MAS architecture development 4 MAS engineering design 5 MAS implementation.A novelty of the proposed approach lies in introduction of the agent interaction scenarios and application of Joiner-networks for scripting of scenarios. Agent-based scenarios allow nonprogrammers-experts to change the programme algorithm. A Joiner-network of the scenario consists of the functioning processes of agents (nodes, and the events that trigger or end the process. Output event of one process can be the input event for another.The operation algorithm of the EPS estimation system is developed. The first step is to provide decomposition of a nodalization diagram into the areas corresponding to the levels of node voltages. Then diagrams resulting from decomposition are distributed between the agents of EPS estimation and calculated in parallel. At the next stage, all diagrams are

Estimation and Control for Linear Systems with Additive Cauchy Noise

Science.gov (United States)

2013-12-17

man & Hall, New York, 1994. [11] J. L. Speyer and W. H. Chung, Stochastic Processes, Estimation, and Control, SIAM, 2008. [12] Nassim N. Taleb ...Gaussian control algorithms. 18 4 References [1] N. N. Taleb . The Black Swan: The Impact of the Highly Improbable...the multivariable system. The estimator was then evaluated numerically for a third-order example. REFERENCES [1] N. N. Taleb , The Black Swan: The

Simulation of embedded systems for energy consumption estimation

Energy Technology Data Exchange (ETDEWEB)

Lafond, S.

2009-07-01

Technology developments in semiconductor fabrication along with a rapid expansion of the market for portable devices, such as PDAs and mobile phones, make the energy consumption of embedded systems a major problem. Indeed the need to provide an increasing number of computational intensive applications and at the same time to maximize the battery life of portable devices can be seen as incompatible trends. System simulation is a flexible and convenient method for analyzinging and exploring the performance of a system or sub-system. At the same time, the increasing use of computational intensive applications strengthens the need to maximize the battery life of portable devices. As a consequence, the simulation of embedded systems for energy consumption estimation is becoming essential in order to study and explore the influence of system design choices on the system energy consumption. The original publications presented in the second part of this thesis propose several frameworks for evaluating the effects of particular system and software architectures on the system energy consumption. From a software point of view Java and C based applications are studied, and from a hardware perspective systems using general purpose processor and heterogeneous platforms with dedicated hardware accelerators are analyzed. Papers 1 and 2 present a framework for estimating the energy consumption of an embedded Java Virtual Machine and show how an accurate energy consumption model of Java opcodes can be obtained. Paper 3 evaluates the cost-effectiveness of Forward Error Correction algorithms in terms of energy consumption and demonstrates that a substantial energy saving is achievable in a DVB-H receiver when a FEC algorithm is used for file downloading scenarios. Paper 4 and 5 present the simulation of heterogeneous platforms and point out the drawback of different mechanisms used to synchronize a hardware accelerator used as a peripheral device. Paper 6 shows that the use of a multi

System of estimations and prognostications of bodily condition of skilled sportsmen in track-and-field

Directory of Open Access Journals (Sweden)

V.I. Bobrovnyk

2013-01-01

Full Text Available The system of estimation and prognostication of bodily condition of skilled athletes is presented. The system includes the complex of pedagogical tests, evaluation tables, estimation of the functional state vegetative, nervous, cardiovascular systems, system of the external breathing. 436 sportsmen took part in research (212 women and 224 men. The analysis of electrocardiography is conducted, variability of cardiac rhythm, determination of vegetative balance, state of myocardium, violations of rhythm of heart, spirometric researches. The estimation of efficiency of activity of sportsman in extreme terms on the basis of type and properties of temperament, level of personality anxiety and estimation of psychological reliability of sportsmen is presented. The criteria of estimation of physical preparedness are certain, functional state of the basic systems of organism, influencing in a greater degree on achievement of high sporting results, psychological state of sportsmen.

Modulation transfer function estimation of optical lens system by adaptive neuro-fuzzy methodology

Science.gov (United States)

Petković, Dalibor; Shamshirband, Shahaboddin; Pavlović, Nenad T.; Anuar, Nor Badrul; Kiah, Miss Laiha Mat

2014-07-01

The quantitative assessment of image quality is an important consideration in any type of imaging system. The modulation transfer function (MTF) is a graphical description of the sharpness and contrast of an imaging system or of its individual components. The MTF is also known and spatial frequency response. The MTF curve has different meanings according to the corresponding frequency. The MTF of an optical system specifies the contrast transmitted by the system as a function of image size, and is determined by the inherent optical properties of the system. In this study, the adaptive neuro-fuzzy (ANFIS) estimator is designed and adapted to estimate MTF value of the actual optical system. Neural network in ANFIS adjusts parameters of membership function in the fuzzy logic of the fuzzy inference system. The back propagation learning algorithm is used for training this network. This intelligent estimator is implemented using Matlab/Simulink and the performances are investigated. The simulation results presented in this paper show the effectiveness of the developed method.

Distributed Fusion Estimation for Multisensor Multirate Systems with Stochastic Observation Multiplicative Noises

Directory of Open Access Journals (Sweden)

Peng Fangfang

2014-01-01

Full Text Available This paper studies the fusion estimation problem of a class of multisensor multirate systems with observation multiplicative noises. The dynamic system is sampled uniformly. Sampling period of each sensor is uniform and the integer multiple of the state update period. Moreover, different sensors have the different sampling rates and observations of sensors are subject to the stochastic uncertainties of multiplicative noises. At first, local filters at the observation sampling points are obtained based on the observations of each sensor. Further, local estimators at the state update points are obtained by predictions of local filters at the observation sampling points. They have the reduced computational cost and a good real-time property. Then, the cross-covariance matrices between any two local estimators are derived at the state update points. At last, using the matrix weighted optimal fusion estimation algorithm in the linear minimum variance sense, the distributed optimal fusion estimator is obtained based on the local estimators and the cross-covariance matrices. An example shows the effectiveness of the proposed algorithms.

Forecasting overhaul or replacement intervals based on estimated system failure intensity

Science.gov (United States)

Gannon, James M.

1994-12-01

System reliability can be expressed in terms of the pattern of failure events over time. Assuming a nonhomogeneous Poisson process and Weibull intensity function for complex repairable system failures, the degree of system deterioration can be approximated. Maximum likelihood estimators (MLE's) for the system Rate of Occurrence of Failure (ROCOF) function are presented. Evaluating the integral of the ROCOF over annual usage intervals yields the expected number of annual system failures. By associating a cost of failure with the expected number of failures, budget and program policy decisions can be made based on expected future maintenance costs. Monte Carlo simulation is used to estimate the range and the distribution of the net present value and internal rate of return of alternative cash flows based on the distributions of the cost inputs and confidence intervals of the MLE's.

Estimation of thermophysical properties in the system Li-Pb

International Nuclear Information System (INIS)

Jauch, U.; Schulz, B.

1986-01-01

Based on the phase diagram and the knowledge of thermophysical properties data of alloys and intermetallic compounds in the Li-Pb system, quantitative relationships between several properties and between the properties in solid and liquid state are used: to interpret the results on thermophysical properties in the quasibinary system LiPb-Pb and to estimate unknown properties in the concentration range 100 > Li (at.%) > 50. (orig.)

Estimation of component failure probability from masked binomial system testing data

International Nuclear Information System (INIS)

Tan Zhibin

2005-01-01

The component failure probability estimates from analysis of binomial system testing data are very useful because they reflect the operational failure probability of components in the field which is similar to the test environment. In practice, this type of analysis is often confounded by the problem of data masking: the status of tested components is unknown. Methods in considering this type of uncertainty are usually computationally intensive and not practical to solve the problem for complex systems. In this paper, we consider masked binomial system testing data and develop a probabilistic model to efficiently estimate component failure probabilities. In the model, all system tests are classified into test categories based on component coverage. Component coverage of test categories is modeled by a bipartite graph. Test category failure probabilities conditional on the status of covered components are defined. An EM algorithm to estimate component failure probabilities is developed based on a simple but powerful concept: equivalent failures and tests. By simulation we not only demonstrate the convergence and accuracy of the algorithm but also show that the probabilistic model is capable of analyzing systems in series, parallel and any other user defined structures. A case study illustrates an application in test case prioritization

Implementation of a Simplified State Estimator for Wind Turbine Monitoring on an Embedded System

DEFF Research Database (Denmark)

Rasmussen, Theis Bo; Yang, Guangya; Nielsen, Arne Hejde

2017-01-01

system, including individual DER, is time consuming and numerically challenging. This paper presents the approach and results of implementing a simplified state estimator onto an embedded system for improving DER monitoring. The implemented state estimator is based on numerically robust orthogonal......The transition towards a cyber-physical energy system (CPES) entails an increased dependency on valid data. Simultaneously, an increasing implementation of renewable generation leads to possible control actions at individual distributed energy resources (DERs). A state estimation covering the whole...

Implicit Particle Filter for Power System State Estimation with Large Scale Renewable Power Integration.

Science.gov (United States)

Uzunoglu, B.; Hussaini, Y.

2017-12-01

Implicit Particle Filter is a sequential Monte Carlo method for data assimilation that guides the particles to the high-probability by an implicit step . It optimizes a nonlinear cost function which can be inherited from legacy assimilation routines . Dynamic state estimation for almost real-time applications in power systems are becomingly increasingly more important with integration of variable wind and solar power generation. New advanced state estimation tools that will replace the old generation state estimation in addition to having a general framework of complexities should be able to address the legacy software and able to integrate the old software in a mathematical framework while allowing the power industry need for a cautious and evolutionary change in comparison to a complete revolutionary approach while addressing nonlinearity and non-normal behaviour. This work implements implicit particle filter as a state estimation tool for the estimation of the states of a power system and presents the first implicit particle filter application study on a power system state estimation. The implicit particle filter is introduced into power systems and the simulations are presented for a three-node benchmark power system . The performance of the filter on the presented problem is analyzed and the results are presented.

Delay Estimation in Long-Code Asynchronous DS/CDMA Systems Using Multiple Antennas

Directory of Open Access Journals (Sweden)

Sirbu Marius

2004-01-01

Full Text Available The problem of propagation delay estimation in asynchronous long-code DS-CDMA multiuser systems is addressed. Almost all the methods proposed so far in the literature for propagation delay estimation are derived for short codes and the knowledge of the codes is exploited by the estimators. In long-code CDMA, the spreading code is aperiodic and the methods developed for short codes may not be used or may increase the complexity significantly. For example, in the subspace-based estimators, the aperiodic nature of the code may require subspace tracking. In this paper we propose a novel method for simultaneous estimation of the propagation delays of several active users. A specific multiple-input multiple-output (MIMO system model is constructed in a multiuser scenario. In such model the channel matrix contains information about both the users propagation delays and channel impulse responses. Consequently, estimates of the delays are obtained as a by-product of the channel estimation task. The channel matrix has a special structure that is exploited in estimating the delays. The proposed delay estimation method lends itself to an adaptive implementation. Thus, it may be applied to joint channel and delay estimation in uplink DS-CDMA analogously to the method presented by the authors in 2003. The performance of the proposed method is studied in simulation using realistic time-varying channel model and different SNR levels in the face of near-far effects, and using low spreading factor (high data rates.

Action-reaction based parameters identification and states estimation of flexible systems

OpenAIRE

Khalil, Islam; Kunt, Emrah Deniz; Şabanoviç, Asif; Sabanovic, Asif

2012-01-01

This work attempts to identify and estimate flexible system's parameters and states by a simple utilization of the Action-Reaction law of dynamical systems. Attached actuator to a dynamical system or environmental interaction imposes an action that is instantaneously followed by a dynamical system reaction. The dynamical system's reaction carries full information about the dynamical system including system parameters, dynamics and externally applied forces that arise due to system interaction...

PERFORMANCE ANALYSIS OF PILOT BASED CHANNEL ESTIMATION TECHNIQUES IN MB OFDM SYSTEMS

Directory of Open Access Journals (Sweden)

M. Madheswaran

2011-12-01

Full Text Available Ultra wideband (UWB communication is mainly used for short range of communication in wireless personal area networks. Orthogonal Frequency Division Multiplexing (OFDM is being used as a key physical layer technology for Fourth Generation (4G wireless communication. OFDM based communication gives high spectral efficiency and mitigates Inter-symbol Interference (ISI in a wireless medium. In this paper the IEEE 802.15.3a based Multiband OFDM (MB OFDM system is considered. The pilot based channel estimation techniques are considered to analyze the performance of MB OFDM systems over Liner Time Invariant (LTI Channel models. In this paper, pilot based Least Square (LS and Least Minimum Mean Square Error (LMMSE channel estimation technique has been considered for UWB OFDM system. In the proposed method, the estimated Channel Impulse Responses (CIRs are filtered in the time domain for the consideration of the channel delay spread. Also the performance of proposed system has been analyzed for different modulation techniques for various pilot density patterns.

Hybrid NEMS-CMOS Architectures for Ultra Low Power Smart Systems : Architectures for Ultra Low Power Smart Systems

NARCIS (Netherlands)

Enachescu, M.

2016-01-01

The availability of inexpensive and powerful processors provides the means for the computation ecosystem to change its fundamental paradigm towards the Internet of Things (IoT) where ubiquitous nanosystems add intelligence to every object that surrounds us. The new trend for most of those systems is

Efficient channel estimation in massive MIMO systems - a distributed approach

KAUST Repository

Al-Naffouri, Tareq Y.

2016-01-21

We present two efficient algorithms for distributed estimation of channels in massive MIMO systems. The two cases of 1) generic, and 2) sparse channels is considered. The algorithms estimate the impulse response for each channel observed by the antennas at the receiver (base station) in a coordinated manner by sharing minimal information among neighboring antennas. Simulations demonstrate the superior performance of the proposed methods as compared to other methods.

An Efficient Code-Timing Estimator for DS-CDMA Systems over Resolvable Multipath Channels

Directory of Open Access Journals (Sweden)

Jian Li

2005-04-01

Full Text Available We consider the problem of training-based code-timing estimation for the asynchronous direct-sequence code-division multiple-access (DS-CDMA system. We propose a modified large-sample maximum-likelihood (MLSML estimator that can be used for the code-timing estimation for the DS-CDMA systems over the resolvable multipath channels in closed form. Simulation results show that MLSML can be used to provide a high correct acquisition probability and a high estimation accuracy. Simulation results also show that MLSML can have very good near-far resistant capability due to employing a data model similar to that for adaptive array processing where strong interferences can be suppressed.

A Practical Scheme for Frequency Offset Estimation in MIMO-OFDM Systems

Directory of Open Access Journals (Sweden)

Morelli Michele

2009-01-01

Full Text Available This paper deals with training-assisted carrier frequency offset (CFO estimation in multiple-input multiple-output (MIMO orthogonal frequency-division multiplexing (OFDM systems. The exact maximum likelihood (ML solution to this problem is computationally demanding as it involves a line search over the CFO uncertainty range. To reduce the system complexity, we divide the CFO into an integer part plus a fractional part and select the pilot subcarriers such that the training sequences have a repetitive structure in the time domain. In this way, the fractional CFO is efficiently computed through a correlation-based approach, while ML methods are employed to estimate the integer CFO. Simulations indicate that the proposed scheme is superior to the existing alternatives in terms of both estimation accuracy and processing load.

A Practical Scheme for Frequency Offset Estimation in MIMO-OFDM Systems

Directory of Open Access Journals (Sweden)

2009-03-01

Full Text Available This paper deals with training-assisted carrier frequency offset (CFO estimation in multiple-input multiple-output (MIMO orthogonal frequency-division multiplexing (OFDM systems. The exact maximum likelihood (ML solution to this problem is computationally demanding as it involves a line search over the CFO uncertainty range. To reduce the system complexity, we divide the CFO into an integer part plus a fractional part and select the pilot subcarriers such that the training sequences have a repetitive structure in the time domain. In this way, the fractional CFO is efficiently computed through a correlation-based approach, while ML methods are employed to estimate the integer CFO. Simulations indicate that the proposed scheme is superior to the existing alternatives in terms of both estimation accuracy and processing load.

Asymptotic scaling laws for precision of parameter estimates in dynamical systems

International Nuclear Information System (INIS)

Horbelt, W.; Timmer, J.

2003-01-01

When parameters are estimated from noisy data, the uncertainty of the estimates in terms of their standard deviation typically scales like the inverse square root of the number of data points. In the case of deterministic dynamical systems with added observation noise, superior scaling laws can be achieved. This is demonstrated numerically for the logistic map, the van der Pol oscillator and the Lorenz system, where exponential scaling laws and power laws have been found, depending on the number of degrees of freedom. For some special cases, analytical expressions are derived

Method of estimation of scanning system quality

Science.gov (United States)

Larkin, Eugene; Kotov, Vladislav; Kotova, Natalya; Privalov, Alexander

2018-04-01

Estimation of scanner parameters is an important part in developing electronic document management system. This paper suggests considering the scanner as a system that contains two main channels: a photoelectric conversion channel and a channel for measuring spatial coordinates of objects. Although both of channels consist of the same elements, the testing of their parameters should be executed separately. The special structure of the two-dimensional reference signal is offered for this purpose. In this structure, the fields for testing various parameters of the scanner are sp atially separated. Characteristics of the scanner are associated with the loss of information when a document is digitized. The methods to test grayscale transmitting ability, resolution and aberrations level are offered.

Estimating Rates of Fault Insertion and Test Effectiveness in Software Systems

Science.gov (United States)

Nikora, A.; Munson, J.

1998-01-01

In developing a software system, we would like to estimate the total number of faults inserted into a software system, the residual fault content of that system at any given time, and the efficacy of the testing activity in executing the code containing the newly inserted faults.

Economical efficiency estimation of the power system with an accelerator breeder

International Nuclear Information System (INIS)

Rublev, O.V.; Komin, A.V.

1990-01-01

The review deals with economical indices of nuclear power system with an accelerator breeder producing secondary nuclear fuel. Electric power cost was estimated by the method of discounted cost. Power system with accelerator breeder compares unfavourably with traditional nuclear power systems with respect to its capitalized cost

Forecasting US renewables in the national energy modelling system

International Nuclear Information System (INIS)

Diedrich, R.; Petersik, T.W.

2001-01-01

The Energy information Administration (EIA) of the US Department of Energy (DOE) forecasts US renewable energy supply and demand in the context of overall energy markets using the National Energy Modelling System (NEMS). Renewables compete with other supply and demand options within the residential, commercial, industrial, transportation, and electricity sectors of the US economy. NEMS forecasts renewable energy for grid-connected electricity production within the Electricity Market Module (EM), and characterizes central station biomass, geothermal, conventional hydroelectric, municipal solid waste, solar thermal, solar photovoltaic, and wind-powered electricity generating technologies. EIA's Annual Energy Outlook 1998, projecting US energy markets, forecasts marketed renewables to remain a minor part of US energy production and consumption through to 2020. The USA is expected to remain primarily a fossil energy producer and consumer throughout the period. An alternative case indicates that biomass, wind, and to some extent geothermal power would likely increase most rapidly if the US were to require greater use of renewables for power supply, though electricity prices would increase somewhat. (author)

Using field feedback to estimate failure rates of safety-related systems

International Nuclear Information System (INIS)

Brissaud, Florent

2017-01-01

The IEC 61508 and IEC 61511 functional safety standards encourage the use of field feedback to estimate the failure rates of safety-related systems, which is preferred than generic data. In some cases (if “Route 2_H” is adopted for the 'hardware safety integrity constraints”), this is even a requirement. This paper presents how to estimate the failure rates from field feedback with confidence intervals, depending if the failures are detected on-line (called 'detected failures', e.g. by automatic diagnostic tests) or only revealed by proof tests (called 'undetected failures'). Examples show that for the same duration and number of failures observed, the estimated failure rates are basically higher for “undetected failures” because, in this case, the duration observed includes intervals of time where it is unknown that the elements have failed. This points out the need of using a proper approach for failure rates estimation, especially for failures that are not detected on-line. Then, this paper proposes an approach to use the estimated failure rates, with their uncertainties, for PFDavg and PFH assessment with upper confidence bounds, in accordance with IEC 61508 and IEC 61511 requirements. Examples finally show that the highest SIL that can be claimed for a safety function can be limited by the 90% upper confidence bound of PFDavg or PFH. The requirements of the IEC 61508 and IEC 61511 relating to the data collection and analysis should therefore be properly considered for the study of all safety-related systems. - Highlights: • This paper deals with requirements of the IEC 61508 and IEC 61511 for using field feedback to estimate failure rates of safety-related systems. • This paper presents how to estimate the failure rates from field feedback with confidence intervals for failures that are detected on-line. • This paper presents how to estimate the failure rates from field feedback with confidence intervals for failures that are only revealed by

Increasing to Accuracy Estimation of Latent Parameters in Human Resource Management Systems

Directory of Open Access Journals (Sweden)

O.N. Gustun

2011-09-01

Full Text Available An approach to build an adaptive testing system, in which initial estimates of test items are obtained through calibration testing, is considered. The maximum likehood method is used to obtain these estimates. Optimization of the objective function is carried out using the method of Hooke—Jeeves. The influence of various factors on the accuracy of the estimates obtained is investigated.

BOES: Building Occupancy Estimation System using sparse ambient vibration monitoring

Science.gov (United States)

Pan, Shijia; Bonde, Amelie; Jing, Jie; Zhang, Lin; Zhang, Pei; Noh, Hae Young

2014-04-01

In this paper, we present a room-level building occupancy estimation system (BOES) utilizing low-resolution vibration sensors that are sparsely distributed. Many ubiquitous computing and building maintenance systems require fine-grained occupancy knowledge to enable occupant centric services and optimize space and energy utilization. The sensing infrastructure support for current occupancy estimation systems often requires multiple intrusive sensors per room, resulting in systems that are both costly to deploy and difficult to maintain. To address these shortcomings, we developed BOES. BOES utilizes sparse vibration sensors to track occupancy levels and activities. Our system has three major components. 1) It extracts features that distinguish occupant activities from noise prone ambient vibrations and detects human footsteps. 2) Using a sequence of footsteps, the system localizes and tracks individuals by observing changes in the sequences. It uses this tracking information to identify when an occupant leaves or enters a room. 3) The entering and leaving room information are combined with detected individual location information to update the room-level occupancy state of the building. Through validation experiments in two different buildings, our system was able to achieve 99.55% accuracy for event detection, less than three feet average error for localization, and 85% accuracy in occupancy counting.

A practical model for pressure probe system response estimation (with review of existing models)

Science.gov (United States)

Hall, B. F.; Povey, T.

2018-04-01

The accurate estimation of the unsteady response (bandwidth) of pneumatic pressure probe systems (probe, line and transducer volume) is a common practical problem encountered in the design of aerodynamic experiments. Understanding the bandwidth of the probe system is necessary to capture unsteady flow features accurately. Where traversing probes are used, the desired traverse speed and spatial gradients in the flow dictate the minimum probe system bandwidth required to resolve the flow. Existing approaches for bandwidth estimation are either complex or inaccurate in implementation, so probes are often designed based on experience. Where probe system bandwidth is characterized, it is often done experimentally, requiring careful experimental set-up and analysis. There is a need for a relatively simple but accurate model for estimation of probe system bandwidth. A new model is presented for the accurate estimation of pressure probe bandwidth for simple probes commonly used in wind tunnel environments; experimental validation is provided. An additional, simple graphical method for air is included for convenience.

Cooperative Fault Tolerant Tracking Control for Multiagent Systems: An Intermediate Estimator-Based Approach.

Science.gov (United States)

Zhu, Jun-Wei; Yang, Guang-Hong; Zhang, Wen-An; Yu, Li

2017-10-17

This paper studies the observer based fault tolerant tracking control problem for linear multiagent systems with multiple faults and mismatched disturbances. A novel distributed intermediate estimator based fault tolerant tracking protocol is presented. The leader's input is nonzero and unavailable to the followers. By applying a projection technique, the mismatched disturbances are separated into matched and unmatched components. For each node, a tracking error system is established, for which an intermediate estimator driven by the relative output measurements is constructed to estimate the sensor faults and a combined signal of the leader's input, process faults, and matched disturbance component. Based on the estimation, a fault tolerant tracking protocol is designed to eliminate the effects of the combined signal. Besides, the effect of unmatched disturbance component can be attenuated by directly adjusting some specified parameters. Finally, a simulation example of aircraft demonstrates the effectiveness of the designed tracking protocol.This paper studies the observer based fault tolerant tracking control problem for linear multiagent systems with multiple faults and mismatched disturbances. A novel distributed intermediate estimator based fault tolerant tracking protocol is presented. The leader's input is nonzero and unavailable to the followers. By applying a projection technique, the mismatched disturbances are separated into matched and unmatched components. For each node, a tracking error system is established, for which an intermediate estimator driven by the relative output measurements is constructed to estimate the sensor faults and a combined signal of the leader's input, process faults, and matched disturbance component. Based on the estimation, a fault tolerant tracking protocol is designed to eliminate the effects of the combined signal. Besides, the effect of unmatched disturbance component can be attenuated by directly adjusting some

State estimation for networked control systems using fixed data rates

Science.gov (United States)

Liu, Qing-Quan; Jin, Fang

2017-07-01

This paper investigates state estimation for linear time-invariant systems where sensors and controllers are geographically separated and connected via a bandwidth-limited and errorless communication channel with the fixed data rate. All plant states are quantised, coded and converted together into a codeword in our quantisation and coding scheme. We present necessary and sufficient conditions on the fixed data rate for observability of such systems, and further develop the data-rate theorem. It is shown in our results that there exists a quantisation and coding scheme to ensure observability of the system if the fixed data rate is larger than the lower bound given, which is less conservative than the one in the literature. Furthermore, we also examine the role that the disturbances have on the state estimation problem in the case with data-rate limitations. Illustrative examples are given to demonstrate the effectiveness of the proposed method.

Development of an integrated system for estimating human error probabilities

Energy Technology Data Exchange (ETDEWEB)

Auflick, J.L.; Hahn, H.A.; Morzinski, J.A.

1998-12-01

This is the final report of a three-year, Laboratory Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). This project had as its main objective the development of a Human Reliability Analysis (HRA), knowledge-based expert system that would provide probabilistic estimates for potential human errors within various risk assessments, safety analysis reports, and hazard assessments. HRA identifies where human errors are most likely, estimates the error rate for individual tasks, and highlights the most beneficial areas for system improvements. This project accomplished three major tasks. First, several prominent HRA techniques and associated databases were collected and translated into an electronic format. Next, the project started a knowledge engineering phase where the expertise, i.e., the procedural rules and data, were extracted from those techniques and compiled into various modules. Finally, these modules, rules, and data were combined into a nearly complete HRA expert system.

Estimation of the Coefficient of Restitution of Rocking Systems by the Random Decrement Technique

DEFF Research Database (Denmark)

Brincker, Rune; Demosthenous, M.; Manos, G. C.

The aim of this paper is to investigate the possibility of estimating an average damping parameter for a rocking system due to impact, the so-called coefficient of restitution, from the random response, i.e. when the loads are random and unknown, and the response is measured. The objective is to ...... of freedom system loaded by white noise, estimating the coefficient of restitution as explained, and comparing the estimates with the value used in the simulations. Several estimates for the coefficient of restitution are considered, and reasonable results are achieved....

Model calibration and parameter estimation for environmental and water resource systems

CERN Document Server

Sun, Ne-Zheng

2015-01-01

This three-part book provides a comprehensive and systematic introduction to the development of useful models for complex systems. Part 1 covers the classical inverse problem for parameter estimation in both deterministic and statistical frameworks, Part 2 is dedicated to system identification, hyperparameter estimation, and model dimension reduction, and Part 3 considers how to collect data and construct reliable models for prediction and decision-making. For the first time, topics such as multiscale inversion, stochastic field parameterization, level set method, machine learning, global sensitivity analysis, data assimilation, model uncertainty quantification, robust design, and goal-oriented modeling, are systematically described and summarized in a single book from the perspective of model inversion, and elucidated with numerical examples from environmental and water resources modeling. Readers of this book will not only learn basic concepts and methods for simple parameter estimation, but also get famili...

Automatic Regionalization Algorithm for Distributed State Estimation in Power Systems: Preprint

Energy Technology Data Exchange (ETDEWEB)

Wang, Dexin; Yang, Liuqing; Florita, Anthony; Alam, S.M. Shafiul; Elgindy, Tarek; Hodge, Bri-Mathias

2016-08-01

The deregulation of the power system and the incorporation of generation from renewable energy sources recessitates faster state estimation in the smart grid. Distributed state estimation (DSE) has become a promising and scalable solution to this urgent demand. In this paper, we investigate the regionalization algorithms for the power system, a necessary step before distributed state estimation can be performed. To the best of the authors' knowledge, this is the first investigation on automatic regionalization (AR). We propose three spectral clustering based AR algorithms. Simulations show that our proposed algorithms outperform the two investigated manual regionalization cases. With the help of AR algorithms, we also show how the number of regions impacts the accuracy and convergence speed of the DSE and conclude that the number of regions needs to be chosen carefully to improve the convergence speed of DSEs.

Organic carbon balance and net ecosystem metabolism in Chesapeake Bay

Science.gov (United States)

Kemp, W.M.; Smith, E.M.; Marvin-DiPasquale, M.; Boynton, W.R.

1997-01-01

The major fluxes of organic carbon associated with physical transport and biological metabolism were compiled, analyzed and compared for the mainstem portion of Chesapeake Bay (USA). In addition, 5 independent methods were used to calculate the annual mean net ecosystem metabolism (NEM = production - respiration) for the integrated Bay. These methods, which employed biogeochemical models, nutrient mass-balances anti summation of individual organic carbon fluxes, yielded remarkably similar estimates, with a mean NEM of +50 g C m-2 yr-1 (?? SE = 751, which is approximately 8% of the estimated annual average gross primary production. These calculations suggest a strong cross-sectional pattern in NEM throughout the Bay, wherein net heterotrophic metabolism prevails in the pelagic zones of the main channel, while net autotrophy occurs in the littoral zones which flank the deeper central area. For computational purposes, the estuary was separated into 3 regions along the land-sea gradient: (1) the oligohaline Upper Bay (11% of total area); (2) the mesohaline Mid Bay (36% of area); and (3) the polyhaline Lower Bay (53% of area). A distinct regional trend in NEM was observed along this salinity gradient, with net here(atrophy (NEM = 87 g C m-2 yr-1) in the Upper Bay, balanced metabolism in the Mid Bay and net autotrophy (NEM = +92 g C m-2 yr-1) in the Lower Bay. As a consequence of overall net autotrophy, the ratio of dissolved inorganic nitrogen (DIN) to total organic nitrogen (TON) changed from DIN:TON = 5.1 for riverine inputs to DIN:TON = 0.04 for water exported to the ocean. A striking feature of this organic C mass-balance was the relative dominance of biologically mediated metabolic fluxes compared to physical transport fluxes. The overall ratio of physical TOC inputs (1) to biotic primary production (P) was 0.08 for the whole estuary, but varied dramatically from 2.3 in the Upper Bay to 0.03 in the Mid and Lower Bay regions. Similarly, ecosystem respiration was

Lead zirconate titanate nanoscale patterning by ultraviolet-based lithography lift-off technique for nano-electromechanical system applications.

Science.gov (United States)

Guillon, Samuel; Saya, Daisuke; Mazenq, Laurent; Costecalde, Jean; Rèmiens, Denis; Soyer, Caroline; Nicu, Liviu

2012-09-01

The advantage of using lead zirconate titanate (PbZr(0.54)Ti(0.46)O(3)) ceramics as an active material in nanoelectromechanical systems (NEMS) comes from its relatively high piezoelectric coefficients. However, its integration within a technological process is limited by the difficulty of structuring this material with submicrometer resolution at the wafer scale. In this work, we develop a specific patterning method based on optical lithography coupled with a dual-layer resist process. The main objective is to obtain sub-micrometer features by lifting off a 100-nm-thick PZT layer while preserving the material's piezoelectric properties. A subsequent result of the developed method is the ability to stack several layers with a lateral resolution of few tens of nanometers, which is mandatory for the fabrication of NEMS with integrated actuation and read-out capabilities.

Parameter Estimation of a Closed Loop Coupled Tank Time Varying System using Recursive Methods

International Nuclear Information System (INIS)

Basir, Siti Nora; Yussof, Hanafiah; Shamsuddin, Syamimi; Selamat, Hazlina; Zahari, Nur Ismarrubie

2013-01-01

This project investigates the direct identification of closed loop plant using discrete-time approach. The uses of Recursive Least Squares (RLS), Recursive Instrumental Variable (RIV) and Recursive Instrumental Variable with Centre-Of-Triangle (RIV + COT) in the parameter estimation of closed loop time varying system have been considered. The algorithms were applied in a coupled tank system that employs covariance resetting technique where the time of parameter changes occur is unknown. The performances of all the parameter estimation methods, RLS, RIV and RIV + COT were compared. The estimation of the system whose output was corrupted with white and coloured noises were investigated. Covariance resetting technique successfully executed when the parameters change. RIV + COT gives better estimates than RLS and RIV in terms of convergence and maximum overshoot

Optimal power allocation for SM-OFDM systems with imperfect channel estimation

International Nuclear Information System (INIS)

Yu, Feng; Song, Lijun; Lei, Xia; Xiao, Yue; Jiang, Zhao Xiang; Jin, Maozhu

2016-01-01

This paper analyses the bit error rate (BER) of the spatial modulation orthogonal frequency division multiplex (SM-OFDM) system and derives the optimal power allocation between the data and the pilot symbols by minimizing the upper bound for the BER operating with imperfect channel estimation. Furthermore, we prove the proposed optimal power allocation scheme applies to all generalized linear interpolation techniques with the minimum mean square error (MMSE) channel estimation . Simulation results show that employing the proposed optimal power allocation provides a substantial gain in terms of the average BER performance for the SM-OFDM system compared to its equal-power-allocation counterpart.

Control and Estimation of Distributed Parameter Systems

CERN Document Server

Kappel, F; Kunisch, K

1998-01-01

Consisting of 23 refereed contributions, this volume offers a broad and diverse view of current research in control and estimation of partial differential equations. Topics addressed include, but are not limited to - control and stability of hyperbolic systems related to elasticity, linear and nonlinear; - control and identification of nonlinear parabolic systems; - exact and approximate controllability, and observability; - Pontryagin's maximum principle and dynamic programming in PDE; and - numerics pertinent to optimal and suboptimal control problems. This volume is primarily geared toward control theorists seeking information on the latest developments in their area of expertise. It may also serve as a stimulating reader to any researcher who wants to gain an impression of activities at the forefront of a vigorously expanding area in applied mathematics.

Synchronization and parameter estimations of an uncertain Rikitake system

International Nuclear Information System (INIS)

Aguilar-Ibanez, Carlos; Martinez-Guerra, Rafael; Aguilar-Lopez, Ricardo; Mata-Machuca, Juan L.

2010-01-01

In this Letter we address the synchronization and parameter estimation of the uncertain Rikitake system, under the assumption the state is partially known. To this end we use the master/slave scheme in conjunction with the adaptive control technique. Our control approach consists of proposing a slave system which has to follow asymptotically the uncertain Rikitake system, refereed as the master system. The gains of the slave system are adjusted continually according to a convenient adaptation control law, until the measurable output errors converge to zero. The convergence analysis is carried out by using the Barbalat's Lemma. Under this context, uncertainty means that although the system structure is known, only a partial knowledge of the corresponding parameter values is available.

Simultaneous Robust Fault and State Estimation for Linear Discrete-Time Uncertain Systems

Directory of Open Access Journals (Sweden)

Feten Gannouni

2017-01-01

Full Text Available We consider the problem of robust simultaneous fault and state estimation for linear uncertain discrete-time systems with unknown faults which affect both the state and the observation matrices. Using transformation of the original system, a new robust proportional integral filter (RPIF having an error variance with an optimized guaranteed upper bound for any allowed uncertainty is proposed to improve robust estimation of unknown time-varying faults and to improve robustness against uncertainties. In this study, the minimization problem of the upper bound of the estimation error variance is formulated as a convex optimization problem subject to linear matrix inequalities (LMI for all admissible uncertainties. The proportional and the integral gains are optimally chosen by solving the convex optimization problem. Simulation results are given in order to illustrate the performance of the proposed filter, in particular to solve the problem of joint fault and state estimation.

Action-reaction based parameters identification and states estimation of flexible systems

OpenAIRE

Khalil, Islam Shoukry Mohammed; Şabanoviç, Asif; Sabanovic, Asif

2010-01-01

This work attempts to identify and estimate flexible system’s parameters and states by a simple utilization of the Action-Reaction law of dynamical systems. Attached actuator to a dynamical system or environmental interaction imposes an action that is instantaneously followed by a dynamical system reaction. The dynamical system’s reaction carries full information about the dynamical system including system parameters, dynamics and externally applied forces that arise due to system interaction...

Fault Estimation for Fuzzy Delay Systems: A Minimum Norm Least Squares Solution Approach.

Science.gov (United States)

Huang, Sheng-Juan; Yang, Guang-Hong

2017-09-01

This paper mainly focuses on the problem of fault estimation for a class of Takagi-Sugeno fuzzy systems with state delays. A minimum norm least squares solution (MNLSS) approach is first introduced to establish a fault estimation compensator, which is able to optimize the fault estimator. Compared with most of the existing fault estimation methods, the MNLSS-based fault estimation method can effectively decrease the effect of state errors on the accuracy of fault estimation. Finally, three examples are given to illustrate the effectiveness and merits of the proposed method.

Augmented switching linear dynamical system model for gas concentration estimation with MOX sensors in an open sampling system.

Science.gov (United States)

Di Lello, Enrico; Trincavelli, Marco; Bruyninckx, Herman; De Laet, Tinne

2014-07-11

In this paper, we introduce a Bayesian time series model approach for gas concentration estimation using Metal Oxide (MOX) sensors in Open Sampling System (OSS). Our approach focuses on the compensation of the slow response of MOX sensors, while concurrently solving the problem of estimating the gas concentration in OSS. The proposed Augmented Switching Linear System model allows to include all the sources of uncertainty arising at each step of the problem in a single coherent probabilistic formulation. In particular, the problem of detecting on-line the current sensor dynamical regime and estimating the underlying gas concentration under environmental disturbances and noisy measurements is formulated and solved as a statistical inference problem. Our model improves, with respect to the state of the art, where system modeling approaches have been already introduced, but only provided an indirect relative measures proportional to the gas concentration and the problem of modeling uncertainty was ignored. Our approach is validated experimentally and the performances in terms of speed of and quality of the gas concentration estimation are compared with the ones obtained using a photo-ionization detector.

Velocity-Aided Attitude Estimation for Helicopter Aircraft Using Microelectromechanical System Inertial-Measurement Units

Directory of Open Access Journals (Sweden)

Sang Cheol Lee

2016-12-01

Full Text Available This paper presents an algorithm for velocity-aided attitude estimation for helicopter aircraft using a microelectromechanical system inertial-measurement unit. In general, high- performance gyroscopes are used for estimating the attitude of a helicopter, but this type of sensor is very expensive. When designing a cost-effective attitude system, attitude can be estimated by fusing a low cost accelerometer and a gyro, but the disadvantage of this method is its relatively low accuracy. The accelerometer output includes a component that occurs primarily as the aircraft turns, as well as the gravitational acceleration. When estimating attitude, the accelerometer measurement terms other than gravitational ones can be considered as disturbances. Therefore, errors increase in accordance with the flight dynamics. The proposed algorithm is designed for using velocity as an aid for high accuracy at low cost. It effectively eliminates the disturbances of accelerometer measurements using the airspeed. The algorithm was verified using helicopter experimental data. The algorithm performance was confirmed through a comparison with an attitude estimate obtained from an attitude heading reference system based on a high accuracy optic gyro, which was employed as core attitude equipment in the helicopter.

Velocity-Aided Attitude Estimation for Helicopter Aircraft Using Microelectromechanical System Inertial-Measurement Units

Science.gov (United States)

Lee, Sang Cheol; Hong, Sung Kyung

2016-01-01

This paper presents an algorithm for velocity-aided attitude estimation for helicopter aircraft using a microelectromechanical system inertial-measurement unit. In general, high- performance gyroscopes are used for estimating the attitude of a helicopter, but this type of sensor is very expensive. When designing a cost-effective attitude system, attitude can be estimated by fusing a low cost accelerometer and a gyro, but the disadvantage of this method is its relatively low accuracy. The accelerometer output includes a component that occurs primarily as the aircraft turns, as well as the gravitational acceleration. When estimating attitude, the accelerometer measurement terms other than gravitational ones can be considered as disturbances. Therefore, errors increase in accordance with the flight dynamics. The proposed algorithm is designed for using velocity as an aid for high accuracy at low cost. It effectively eliminates the disturbances of accelerometer measurements using the airspeed. The algorithm was verified using helicopter experimental data. The algorithm performance was confirmed through a comparison with an attitude estimate obtained from an attitude heading reference system based on a high accuracy optic gyro, which was employed as core attitude equipment in the helicopter. PMID:27973429

Method and system to estimate variables in an integrated gasification combined cycle (IGCC) plant

Science.gov (United States)

Kumar, Aditya; Shi, Ruijie; Dokucu, Mustafa

2013-09-17

System and method to estimate variables in an integrated gasification combined cycle (IGCC) plant are provided. The system includes a sensor suite to measure respective plant input and output variables. An extended Kalman filter (EKF) receives sensed plant input variables and includes a dynamic model to generate a plurality of plant state estimates and a covariance matrix for the state estimates. A preemptive-constraining processor is configured to preemptively constrain the state estimates and covariance matrix to be free of constraint violations. A measurement-correction processor may be configured to correct constrained state estimates and a constrained covariance matrix based on processing of sensed plant output variables. The measurement-correction processor is coupled to update the dynamic model with corrected state estimates and a corrected covariance matrix. The updated dynamic model may be configured to estimate values for at least one plant variable not originally sensed by the sensor suite.

Input Forces Estimation for Nonlinear Systems by Applying a Square-Root Cubature Kalman Filter.

Science.gov (United States)

Song, Xuegang; Zhang, Yuexin; Liang, Dakai

2017-10-10

This work presents a novel inverse algorithm to estimate time-varying input forces in nonlinear beam systems. With the system parameters determined, the input forces can be estimated in real-time from dynamic responses, which can be used for structural health monitoring. In the process of input forces estimation, the Runge-Kutta fourth-order algorithm was employed to discretize the state equations; a square-root cubature Kalman filter (SRCKF) was employed to suppress white noise; the residual innovation sequences, a priori state estimate, gain matrix, and innovation covariance generated by SRCKF were employed to estimate the magnitude and location of input forces by using a nonlinear estimator. The nonlinear estimator was based on the least squares method. Numerical simulations of a large deflection beam and an experiment of a linear beam constrained by a nonlinear spring were employed. The results demonstrated accuracy of the nonlinear algorithm.

Input Forces Estimation for Nonlinear Systems by Applying a Square-Root Cubature Kalman Filter

Directory of Open Access Journals (Sweden)

Xuegang Song

2017-10-01

Full Text Available This work presents a novel inverse algorithm to estimate time-varying input forces in nonlinear beam systems. With the system parameters determined, the input forces can be estimated in real-time from dynamic responses, which can be used for structural health monitoring. In the process of input forces estimation, the Runge-Kutta fourth-order algorithm was employed to discretize the state equations; a square-root cubature Kalman filter (SRCKF was employed to suppress white noise; the residual innovation sequences, a priori state estimate, gain matrix, and innovation covariance generated by SRCKF were employed to estimate the magnitude and location of input forces by using a nonlinear estimator. The nonlinear estimator was based on the least squares method. Numerical simulations of a large deflection beam and an experiment of a linear beam constrained by a nonlinear spring were employed. The results demonstrated accuracy of the nonlinear algorithm.

A BIM-based system for demolition and renovation waste estimation and planning.

Science.gov (United States)

Cheng, Jack C P; Ma, Lauren Y H

2013-06-01

Due to the rising worldwide awareness of green environment, both government and contractors have to consider effective construction and demolition (C&D) waste management practices. The last two decades have witnessed the growing importance of demolition and renovation (D&R) works and the growing amount of D&R waste disposed to landfills every day, especially in developed cities like Hong Kong. Quantitative waste prediction is crucial for waste management. It can enable contractors to pinpoint critical waste generation processes and to plan waste control strategies. In addition, waste estimation could also facilitate some government waste management policies, such as the waste disposal charging scheme in Hong Kong. Currently, tools that can accurately and conveniently estimate the amount of waste from construction, renovation, and demolition projects are lacking. In the light of this research gap, this paper presents a building information modeling (BIM) based system that we have developed for estimation and planning of D&R waste. BIM allows multi-disciplinary information to be superimposed within one digital building model. Our system can extract material and volume information through the BIM model and integrate the information for detailed waste estimation and planning. Waste recycling and reuse are also considered in our system. Extracted material information can be provided to recyclers before demolition or renovation to make recycling stage more cooperative and more efficient. Pick-up truck requirements and waste disposal charging fee for different waste facilities will also be predicted through our system. The results could provide alerts to contractors ahead of time at project planning stage. This paper also presents an example scenario with a 47-floor residential building in Hong Kong to demonstrate our D&R waste estimation and planning system. As the BIM technology has been increasingly adopted in the architectural, engineering and construction industry

An Application of UAV Attitude Estimation Using a Low-Cost Inertial Navigation System

Science.gov (United States)

Eure, Kenneth W.; Quach, Cuong Chi; Vazquez, Sixto L.; Hogge, Edward F.; Hill, Boyd L.

2013-01-01

Unmanned Aerial Vehicles (UAV) are playing an increasing role in aviation. Various methods exist for the computation of UAV attitude based on low cost microelectromechanical systems (MEMS) and Global Positioning System (GPS) receivers. There has been a recent increase in UAV autonomy as sensors are becoming more compact and onboard processing power has increased significantly. Correct UAV attitude estimation will play a critical role in navigation and separation assurance as UAVs share airspace with civil air traffic. This paper describes attitude estimation derived by post-processing data from a small low cost Inertial Navigation System (INS) recorded during the flight of a subscale commercial off the shelf (COTS) UAV. Two discrete time attitude estimation schemes are presented here in detail. The first is an adaptation of the Kalman Filter to accommodate nonlinear systems, the Extended Kalman Filter (EKF). The EKF returns quaternion estimates of the UAV attitude based on MEMS gyro, magnetometer, accelerometer, and pitot tube inputs. The second scheme is the complementary filter which is a simpler algorithm that splits the sensor frequency spectrum based on noise characteristics. The necessity to correct both filters for gravity measurement errors during turning maneuvers is demonstrated. It is shown that the proposed algorithms may be used to estimate UAV attitude. The effects of vibration on sensor measurements are discussed. Heuristic tuning comments pertaining to sensor filtering and gain selection to achieve acceptable performance during flight are given. Comparisons of attitude estimation performance are made between the EKF and the complementary filter.

Kargo Kullanıcılarının Önem Verdikleri Faktörlerin, Kargo Firmaları Tarafından Başarım Düzeylerinin İncelenmesi / The Achievement Level of Factors which Cargo Users Care about by Cargo Companies

Directory of Open Access Journals (Sweden)

Ali Çağlar Çakmak

2017-10-01

Full Text Available Abstract The service which is provided by courier companies that we often use in our daily life has a great importance for their customers. To deliver a received or sent cargo on time without having damage is one of the most effective factors that comprise this importance. From this point of view, the main purpose of this study is to determine the services that the customers set great care about and to find out to what extent can the courier companies fulfill these demands. For this purpose, in this study the evaluation of the companies by the customers are assessed by using importance-performance analysis. According to the obtained results, the factors which the customers set care the most are; “delivering the post without any deficiency”, “not to open” and “delivering to designated address”. The least important factors are; “to ask help while carrying the cargo”, “the physical conditions of the company” and “applying existing campaigns”. When we look at the courier companies, through the most preferred three companies: Yurtiçi Cargo, Aras Cargo and PTT Cargo, “PTT Cargo” has the highest performance average while “Yurtiçi Cargo” has the lowest.   Öz Günlük hayatımızda sıklıkla kullandığımız kargo firmalarının verdikleri hizmet, bu hizmeti alan kullanıcıları için büyük önem arz etmektedir. Gönderilen veya alınan kargonun zamanında teslim edilmesi, herhangi bir hasar görmemesi de bu önemin oluşmasındaki en etkili unsurlardandır. Buradan hareketle bu çalışmanın ana amacı, kullanıcıların en çok önem verdikleri hizmetlerin belirlenmesi ve çalıştıkları kargo firmalarının bu hizmetleri ne ölçüde yerine getirebildiklerinin ortaya çıkarılmasıdır. Bu amaçla, bu çalışmada kullanıcıların kargo firmalarını değerlendirmeleri önem-başarım analizi kullanılarak ölçülmüştür. Elde edilen sonuçlara göre kullanıcıların en çok önem verdiği unsurlar; g

Estimating cell capacity for multi-cell electrical energy system

Science.gov (United States)

Hashemi, Iman Ahari

A Multi-Cell Electrical Energy System is a set of batteries that are connected in series. The series batteries provide the required voltage necessary for the contraption. After using the energy that is provided by the batteries, some cells within the system tend to have a lower voltage than the other cells. Also, other factors, such as the number of times a battery has been charged or discharged, how long it has been within the system and many other factors, result in some cells having a lesser capacity compared to the other cells within the system. The outcome is that it lowers the required capacity that the electrical energy system is required to provide. By having an unknown cell capacity within the system, it is unknown how much of a charge can be provided to the system so that the cells are not overcharged or undercharged. Therefore, it is necessary to know the cells capacity within the system. Hence, if we were dealing with a single cell, the capacity could be obtained by a full charge and discharge of the cell. In a series system that contains multiple cells a full charging or discharging cannot happen as it might result in deteriorating the structure of some cells within the system. Hence, to find the capacity of a single cell within an electrical energy system it is required to obtain a method that can estimate the value of each cell within the electrical energy system. To approach this method an electrical energy system is required. The electrical energy system consists of rechargeable non-equal capacity batteries to provide the required energy to the system, a battery management system (BMS) board to monitor the cells voltages, an Arduino board that provides the required communication to BMS board, and the PC, and a software that is able to deliver the required data obtained from the Arduino board to the PC. The outcome, estimating the capacity of a cell within a multi-cell system, can be used in many battery related technologies to obtain unknown

Adaptive estimation for control of uncertain nonlinear systems with applications to target tracking

Science.gov (United States)

Madyastha, Venkatesh Kattigari

2005-08-01

Design of nonlinear observers has received considerable attention since the early development of methods for linear state estimation. The most popular approach is the extended Kalman filter (EKF), that goes through significant degradation in the presence of nonlinearities, particularly if unmodeled dynamics are coupled to the process and the measurement. For uncertain nonlinear systems, adaptive observers have been introduced to estimate the unknown state variables where no priori information about the unknown parameters is available. While establishing global results, these approaches are applicable only to systems transformable to output feedback form. Over the recent years, neural network (NN) based identification and estimation schemes have been proposed that relax the assumptions on the system at the price of sacrificing on the global nature of the results. However, most of the NN based adaptive observer approaches in the literature require knowledge of the full dimension of the system, therefore may not be suitable for systems with unmodeled dynamics. We first propose a novel approach to nonlinear state estimation from the perspective of augmenting a linear time invariant observer with an adaptive element. The class of nonlinear systems treated here are finite but of otherwise unknown dimension. The objective is to improve the performance of the linear observer when applied to a nonlinear system. The approach relies on the ability of the NNs to approximate the unknown dynamics from finite time histories of available measurements. Next we investigate nonlinear state estimation from the perspective of adaptively augmenting an existing time varying observer, such as an EKF. EKFs find their applications mostly in target tracking problems. The proposed approaches are robust to unmodeled dynamics, including unmodeled disturbances. Lastly, we consider the problem of adaptive estimation in the presence of feedback control for a class of uncertain nonlinear systems

A model-based initial guess for estimating parameters in systems of ordinary differential equations.

Science.gov (United States)

Dattner, Itai

2015-12-01

The inverse problem of parameter estimation from noisy observations is a major challenge in statistical inference for dynamical systems. Parameter estimation is usually carried out by optimizing some criterion function over the parameter space. Unless the optimization process starts with a good initial guess, the estimation may take an unreasonable amount of time, and may converge to local solutions, if at all. In this article, we introduce a novel technique for generating good initial guesses that can be used by any estimation method. We focus on the fairly general and often applied class of systems linear in the parameters. The new methodology bypasses numerical integration and can handle partially observed systems. We illustrate the performance of the method using simulations and apply it to real data. © 2015, The International Biometric Society.

Effective Scheme of Channel Tracking and Estimation for Mobile WiMAX DL-PUSC System

Directory of Open Access Journals (Sweden)

Phuong Thi Thu Pham

2010-01-01

Full Text Available This paper introduces an effective joint scheme of channel estimation and tracking for downlink partial usage of subchannel (DL-PUSC mode of mobile WiMAX system. Based on the pilot pattern of this particular system, some channel estimation methods including conventional interpolations and a more favorable least-squares line fitting (LSLF technique are comparatively studied. Besides, channel estimation performance can be remarkably improved by taking advantage of channel tracking derived from the preamble symbol. System performances in terms of packet error rate (PER and user link throughput are investigated in various channels adopted from the well-known ITU models for mobile environments. Simulation results show a significant performance enhancement when the proposed joint scheme is utilized, at least 5 dB, compared to only commonly used channel estimation approaches.

Power System Real-Time Monitoring by Using PMU-Based Robust State Estimation Method

DEFF Research Database (Denmark)

Zhao, Junbo; Zhang, Gexiang; Das, Kaushik

2016-01-01

Accurate real-time states provided by the state estimator are critical for power system reliable operation and control. This paper proposes a novel phasor measurement unit (PMU)-based robust state estimation method (PRSEM) to real-time monitor a power system under different operation conditions...... the system real-time states with good robustness and can address several kinds of BD.......-based bad data (BD) detection method, which can handle the smearing effect and critical measurement errors, is presented. We evaluate PRSEM by using IEEE benchmark test systems and a realistic utility system. The numerical results indicate that, in short computation time, PRSEM can effectively track...

Parameter estimation of a delay dynamical system using synchronization in presence of noise

International Nuclear Information System (INIS)

Rakshit, Biswambhar; Chowdhury, A. Roy; Saha, Papri

2007-01-01

A method of parameter estimation of a time delay chaotic system through synchronization is discussed. It is assumed that the observed data can always be effected with some white Gaussian noise. A least square approach is used to derive a system of differential equations which governs the temporal evolution of the parameters. These system of equations together with the coupled delay dynamical systems, when integrated, leads to asymptotic convergence to the value of the parameter along with synchronization of the two system variables. This method is quite effective for estimating the delay time which is an important characteristic feature of a delay dynamical system. The procedure is quite robust in the presence of noise

Estimation of Multiple Point Sources for Linear Fractional Order Systems Using Modulating Functions

KAUST Repository

Belkhatir, Zehor

2017-06-28

This paper proposes an estimation algorithm for the characterization of multiple point inputs for linear fractional order systems. First, using polynomial modulating functions method and a suitable change of variables the problem of estimating the locations and the amplitudes of a multi-pointwise input is decoupled into two algebraic systems of equations. The first system is nonlinear and solves for the time locations iteratively, whereas the second system is linear and solves for the input’s amplitudes. Second, closed form formulas for both the time location and the amplitude are provided in the particular case of single point input. Finally, numerical examples are given to illustrate the performance of the proposed technique in both noise-free and noisy cases. The joint estimation of pointwise input and fractional differentiation orders is also presented. Furthermore, a discussion on the performance of the proposed algorithm is provided.

Receiver IQ mismatch estimation in PDM CO-OFDM system using training symbol

Science.gov (United States)

Peng, Dandan; Ma, Xiurong; Yao, Xin; Zhang, Haoyuan

2017-07-01

Receiver in-phase/quadrature (IQ) mismatch is hard to mitigate at the receiver via using conventional method in polarization division multiplexed (PDM) coherent optical orthogonal frequency division multiplexing (CO-OFDM) system. In this paper, a novel training symbol structure is proposed to estimate IQ mismatch and channel distortion. Combined this structure with Gram Schmidt orthogonalization procedure (GSOP) algorithm, we can get lower bit error rate (BER). Meanwhile, based on this structure one estimation method is deduced in frequency domain which can achieve the estimation of IQ mismatch and channel distortion independently and improve the system performance obviously. Numerical simulation shows that the proposed two methods have better performance than compared method at 100 Gb/s after 480 km fiber transmission. Besides, the calculation complexity is also analyzed.

Moving Horizon Control and Estimation of Livestock Ventilation Systems and Indoor Climate

DEFF Research Database (Denmark)

Wu, Z.; Stoustrup, Jakob; Jørgensen, John Bagterp

2008-01-01

In this paper, a new control strategy involves exploiting actuator redundancy in a multivariable system is developed for rejecting the covariance of the fast frequency disturbances and pursuing optimum energy solution. This strategy enhances the resilience of the control system to disturbances...... beyond its bandwidth and reduce energy consumption through on-line optimization computation. The moving horizon estimation and control (also called predictive control) technology is applied and simulated. The design is based on a coupled mathematical model which combines the hybrid ventilation system...... and the associated indoor climate for poultry in barns. The comparative simulation results illustrate the significant potential and advancement of the moving horizon methodologies in estimation and control for nonlinear Multiple Input and Multiple Output system with unknown noise covariance and actuator saturation....

Estimation and prediction of convection-diffusion-reaction systems from point measurement

NARCIS (Netherlands)

Vries, D.

2008-01-01

Different procedures with respect to estimation and prediction of systems characterized by convection, diffusion and reactions on the basis of point measurement data, have been studied. Two applications of these convection-diffusion-reaction (CDR) systems have been used as a case study of the

Ensinar capacidades gerais de resolução de problemas não é uma substituição, nem um complemento viável, a ensinar matemática [Teaching general problem-solving skills is not a substitute for, or a viable addition to, teaching mathematics

NARCIS (Netherlands)

Sweller, John; Clark, Richard; Kirschner, Paul A.

2012-01-01

Sweller, J., Clark, R. E., & Kirschner, P. A. (2012). Ensinar capacidades gerais de resolução de problemas não é uma substituição, nem um complemento viável, a ensinar matemática [Teaching general problem-solving skills is not a substitute for, or a viable addition to, teaching mathematics]. Gazeta

Reliability estimation of safety-critical software-based systems using Bayesian networks

International Nuclear Information System (INIS)

Helminen, A.

2001-06-01

Due to the nature of software faults and the way they cause system failures new methods are needed for the safety and reliability evaluation of software-based safety-critical automation systems in nuclear power plants. In the research project 'Programmable automation system safety integrity assessment (PASSI)', belonging to the Finnish Nuclear Safety Research Programme (FINNUS, 1999-2002), various safety assessment methods and tools for software based systems are developed and evaluated. The project is financed together by the Radiation and Nuclear Safety Authority (STUK), the Ministry of Trade and Industry (KTM) and the Technical Research Centre of Finland (VTT). In this report the applicability of Bayesian networks to the reliability estimation of software-based systems is studied. The applicability is evaluated by building Bayesian network models for the systems of interest and performing simulations for these models. In the simulations hypothetical evidence is used for defining the parameter relations and for determining the ability to compensate disparate evidence in the models. Based on the experiences from modelling and simulations we are able to conclude that Bayesian networks provide a good method for the reliability estimation of software-based systems. (orig.)

Parameter Estimation

DEFF Research Database (Denmark)

Sales-Cruz, Mauricio; Heitzig, Martina; Cameron, Ian

2011-01-01

of optimisation techniques coupled with dynamic solution of the underlying model. Linear and nonlinear approaches to parameter estimation are investigated. There is also the application of maximum likelihood principles in the estimation of parameters, as well as the use of orthogonal collocation to generate a set......In this chapter the importance of parameter estimation in model development is illustrated through various applications related to reaction systems. In particular, rate constants in a reaction system are obtained through parameter estimation methods. These approaches often require the application...... of algebraic equations as the basis for parameter estimation.These approaches are illustrated using estimations of kinetic constants from reaction system models....

Dynamic State Estimation for Multi-Machine Power System by Unscented Kalman Filter With Enhanced Numerical Stability

Energy Technology Data Exchange (ETDEWEB)

Qi, Junjian; Sun, Kai; Wang, Jianhui; Liu, Hui

2018-03-01

In this paper, in order to enhance the numerical stability of the unscented Kalman filter (UKF) used for power system dynamic state estimation, a new UKF with guaranteed positive semidifinite estimation error covariance (UKFGPS) is proposed and compared with five existing approaches, including UKFschol, UKF-kappa, UKFmodified, UKF-Delta Q, and the squareroot UKF (SRUKF). These methods and the extended Kalman filter (EKF) are tested by performing dynamic state estimation on WSCC 3-machine 9-bus system and NPCC 48-machine 140-bus system. For WSCC system, all methods obtain good estimates. However, for NPCC system, both EKF and the classic UKF fail. It is found that UKFschol, UKF-kappa, and UKF-Delta Q do not work well in some estimations while UKFGPS works well in most cases. UKFmodified and SRUKF can always work well, indicating their better scalability mainly due to the enhanced numerical stability.

Alternative Transportation System Demand Estimation for Federal Land Management Agencies.

Science.gov (United States)

2011-09-30

Estimating travel demand for alternative transportation systems (ATS) is challenging in any context, but is even more daunting for Federal Land Management Agencies (FLMAs). Federal public land sites vary widely in their characteristics. Moreover, tra...

Development of Flight-Test Performance Estimation Techniques for Small Unmanned Aerial Systems

Science.gov (United States)

McCrink, Matthew Henry

This dissertation provides a flight-testing framework for assessing the performance of fixed-wing, small-scale unmanned aerial systems (sUAS) by leveraging sub-system models of components unique to these vehicles. The development of the sub-system models, and their links to broader impacts on sUAS performance, is the key contribution of this work. The sub-system modeling and analysis focuses on the vehicle's propulsion, navigation and guidance, and airframe components. Quantification of the uncertainty in the vehicle's power available and control states is essential for assessing the validity of both the methods and results obtained from flight-tests. Therefore, detailed propulsion and navigation system analyses are presented to validate the flight testing methodology. Propulsion system analysis required the development of an analytic model of the propeller in order to predict the power available over a range of flight conditions. The model is based on the blade element momentum (BEM) method. Additional corrections are added to the basic model in order to capture the Reynolds-dependent scale effects unique to sUAS. The model was experimentally validated using a ground based testing apparatus. The BEM predictions and experimental analysis allow for a parameterized model relating the electrical power, measurable during flight, to the power available required for vehicle performance analysis. Navigation system details are presented with a specific focus on the sensors used for state estimation, and the resulting uncertainty in vehicle state. Uncertainty quantification is provided by detailed calibration techniques validated using quasi-static and hardware-in-the-loop (HIL) ground based testing. The HIL methods introduced use a soft real-time flight simulator to provide inertial quality data for assessing overall system performance. Using this tool, the uncertainty in vehicle state estimation based on a range of sensors, and vehicle operational environments is

Estimation of Multiple Point Sources for Linear Fractional Order Systems Using Modulating Functions

KAUST Repository

Belkhatir, Zehor; Laleg-Kirati, Taous-Meriem

2017-01-01

This paper proposes an estimation algorithm for the characterization of multiple point inputs for linear fractional order systems. First, using polynomial modulating functions method and a suitable change of variables the problem of estimating

Nonparametric Estimation of Interval Reliability for Discrete-Time Semi-Markov Systems

DEFF Research Database (Denmark)

Georgiadis, Stylianos; Limnios, Nikolaos

2016-01-01

In this article, we consider a repairable discrete-time semi-Markov system with finite state space. The measure of the interval reliability is given as the probability of the system being operational over a given finite-length time interval. A nonparametric estimator is proposed for the interval...

Estimation of Nonlinear Functions of State Vector for Linear Systems with Time-Delays and Uncertainties

Directory of Open Access Journals (Sweden)

Il Young Song

2015-01-01

Full Text Available This paper focuses on estimation of a nonlinear function of state vector (NFS in discrete-time linear systems with time-delays and model uncertainties. The NFS represents a multivariate nonlinear function of state variables, which can indicate useful information of a target system for control. The optimal nonlinear estimator of an NFS (in mean square sense represents a function of the receding horizon estimate and its error covariance. The proposed receding horizon filter represents the standard Kalman filter with time-delays and special initial horizon conditions described by the Lyapunov-like equations. In general case to calculate an optimal estimator of an NFS we propose using the unscented transformation. Important class of polynomial NFS is considered in detail. In the case of polynomial NFS an optimal estimator has a closed-form computational procedure. The subsequent application of the proposed receding horizon filter and nonlinear estimator to a linear stochastic system with time-delays and uncertainties demonstrates their effectiveness.

FOREWORD: Focus on Novel Nanoelectromechanical 3D Structures: Fabrication and Properties Focus on Novel Nanoelectromechanical 3D Structures: Fabrication and Properties

Science.gov (United States)

Yamada, Shooji; Yamaguchi, Hiroshi; Ishihara, Sunao

2009-06-01

Microelectromechanical systems (MEMS) are widely used small electromechanical systems made of micrometre-sized components. Presently, we are witnessing a transition from MEMS to nanoelectromechanical systems (NEMS), which comprise devices integrating electrical and mechanical functionality on the nanoscale and offer new exciting applications. Similarly to MEMS, NEMS typically include a central transistor-like nanoelectronic unit for data processing, as well as mechanical actuators, pumps, and motors; and they may combine with physical, biological and chemical sensors. In the transition from MEMS to NEMS, component sizes need to be reduced. Therefore, many fabrication methods previously developed for MEMS are unsuitable for the production of high-precision NEMS components. The key challenge in NEMS is therefore the development of new methods for routine and reproducible nanofabrication. Two complementary types of method for NEMS fabrication are available: 'top-down' and 'bottom-up'. The top-down approach uses traditional lithography technologies, whereas bottom-up techniques include molecular self-organization, self-assembly and nanodeposition. The NT2008 conference, held at Ishikawa High-Tech Conference Center, Ishikawa, Japan, between 23-25 October 2008, focused on novel NEMS fabricated from new materials and on process technologies. The topics included compound semiconductors, small mechanical structures, nanostructures for micro-fluid and bio-sensors, bio-hybrid micro-machines, as well as their design and simulation. This focus issue compiles seven articles selected from 13 submitted manuscripts. The articles by Prinz et al and Kehrbusch et al introduce the frontiers of the top-down production of various operational NEMS devices, and Kometani et al present an example of the bottom-up approach, namely ion-beam induced deposition of MEMS and NEMS. The remaining articles report novel technologies for biological sensors. Taira et al have used manganese nanoparticles

Focus on Novel Nanoelectromechanical 3D Structures: Fabrication and Properties

Directory of Open Access Journals (Sweden)

Shooji Yamada, Hiroshi Yamaguchi and Sunao Ishihara

2009-01-01

Full Text Available Microelectromechanical systems (MEMS are widely used small electromechanical systems made of micrometre-sized components. Presently, we are witnessing a transition from MEMS to nanoelectromechanical systems (NEMS, which comprise devices integrating electrical and mechanical functionality on the nanoscale and offer new exciting applications. Similarly to MEMS, NEMS typically include a central transistor-like nanoelectronic unit for data processing, as well as mechanical actuators, pumps, and motors; and they may combine with physical, biological and chemical sensors. In the transition from MEMS to NEMS, component sizes need to be reduced. Therefore, many fabrication methods previously developed for MEMS are unsuitable for the production of high-precision NEMS components. The key challenge in NEMS is therefore the development of new methods for routine and reproducible nanofabrication. Two complementary types of method for NEMS fabrication are available: 'top-down' and 'bottom-up'. The top-down approach uses traditional lithography technologies, whereas bottom-up techniques include molecular self-organization, self-assembly and nanodeposition.The NT2008 conference, held at Ishikawa High-Tech Conference Center, Ishikawa, Japan, between 23–25 October 2008, focused on novel NEMS fabricated from new materials and on process technologies. The topics included compound semiconductors, small mechanical structures, nanostructures for micro-fluid and bio-sensors, bio-hybrid micro-machines, as well as their design and simulation.This focus issue compiles seven articles selected from 13 submitted manuscripts. The articles by Prinz et al and Kehrbusch et al introduce the frontiers of the top-down production of various operational NEMS devices, and Kometani et al present an example of the bottom-up approach, namely ion-beam induced deposition of MEMS and NEMS. The remaining articles report novel technologies for biological sensors. Taira et al have used

Iterative Pilot-Layer Aided Channel Estimation with Emphasis on Interleave-Division Multiple Access Systems

Directory of Open Access Journals (Sweden)

Schoeneich Hendrik

2006-01-01

Full Text Available Channel estimation schemes suitable for interleave-division multiple access (IDMA systems are presented. Training and data are superimposed. Training-based and semiblind linear channel estimators are derived and their performance is discussed and compared. Monte Carlo simulation results are presented showing that the derived channel estimators in conjunction with a superimposed pilot sequence and chip-by-chip processing are able to track fast-fading frequency-selective channels. As opposed to conventional channel estimation techniques, the BER performance even improves with increasing Doppler spread for typical system parameters. An error performance close to the case of perfect channel knowledge can be achieved with high power efficiency.

Micro and nano fabrication tools and processes

CERN Document Server

Gatzen, Hans H; Leuthold, Jürg

2015-01-01

For Microelectromechanical Systems (MEMS) and Nanoelectromechanical Systems (NEMS) production, each product requires a unique process technology. This book provides a comprehensive insight into the tools necessary for fabricating MEMS/NEMS and the process technologies applied. Besides, it describes enabling technologies which are necessary for a successful production, i.e., wafer planarization and bonding, as well as contamination control.

Development of an Advanced Grid-Connected PV-ECS System Considering Solar Energy Estimation

Science.gov (United States)

Rahman, Md. Habibur; Yamashiro, Susumu; Nakamura, Koichi

In this paper, the development and the performance of a viable distributed grid-connected power generation system of Photovoltaic-Energy Capacitor System (PV-ECS) considering solar energy estimation have been described. Instead of conventional battery Electric Double Layer Capacitors (EDLC) are used as storage device and Photovoltaic (PV) panel to generate power from solar energy. The system can generate power by PV, store energy when the demand of load is low and finally supply the stored energy to load during the period of peak demand. To realize the load leveling function properly the system will also buy power from grid line when load demand is high. Since, the power taken from grid line depends on the PV output power, a procedure has been suggested to estimate the PV output power by calculating solar radiation. In order to set the optimum value of the buy power, a simulation program has also been developed. Performance of the system has been studied for different load patterns in different weather conditions by using the estimated PV output power with the help of the simulation program.

Model documentation: Natural Gas Transmission and Distribution Model of the National Energy Modeling System; Volume 1

Energy Technology Data Exchange (ETDEWEB)

NONE

1994-02-24

The Natural Gas Transmission and Distribution Model (NGTDM) is a component of the National Energy Modeling System (NEMS) used to represent the domestic natural gas transmission and distribution system. NEMS is the third in a series of computer-based, midterm energy modeling systems used since 1974 by the Energy Information Administration (EIA) and its predecessor, the Federal Energy Administration, to analyze domestic energy-economy markets and develop projections. This report documents the archived version of NGTDM that was used to produce the natural gas forecasts used in support of the Annual Energy Outlook 1994, DOE/EIA-0383(94). The purpose of this report is to provide a reference document for model analysts, users, and the public that defines the objectives of the model, describes its basic design, provides detail on the methodology employed, and describes the model inputs, outputs, and key assumptions. It is intended to fulfill the legal obligation of the EIA to provide adequate documentation in support of its models (Public Law 94-385, Section 57.b.2). This report represents Volume 1 of a two-volume set. (Volume 2 will report on model performance, detailing convergence criteria and properties, results of sensitivity testing, comparison of model outputs with the literature and/or other model results, and major unresolved issues.) Subsequent chapters of this report provide: (1) an overview of the NGTDM (Chapter 2); (2) a description of the interface between the National Energy Modeling System (NEMS) and the NGTDM (Chapter 3); (3) an overview of the solution methodology of the NGTDM (Chapter 4); (4) the solution methodology for the Annual Flow Module (Chapter 5); (5) the solution methodology for the Distributor Tariff Module (Chapter 6); (6) the solution methodology for the Capacity Expansion Module (Chapter 7); (7) the solution methodology for the Pipeline Tariff Module (Chapter 8); and (8) a description of model assumptions, inputs, and outputs (Chapter 9).

H infinity Integrated Fault Estimation and Fault Tolerant Control of Discrete-time Piecewise Linear Systems

DEFF Research Database (Denmark)

Tabatabaeipour, Seyed Mojtaba; Bak, Thomas

2012-01-01

In this paper we consider the problem of fault estimation and accommodation for discrete time piecewise linear systems. A robust fault estimator is designed to estimate the fault such that the estimation error converges to zero and H∞ performance of the fault estimation is minimized. Then, the es...

A 2D eye gaze estimation system with low-resolution webcam images

Directory of Open Access Journals (Sweden)

Kim Jin

2011-01-01

Full Text Available Abstract In this article, a low-cost system for 2D eye gaze estimation with low-resolution webcam images is presented. Two algorithms are proposed for this purpose, one for the eye-ball detection with stable approximate pupil-center and the other one for the eye movements' direction detection. Eyeball is detected using deformable angular integral search by minimum intensity (DAISMI algorithm. Deformable template-based 2D gaze estimation (DTBGE algorithm is employed as a noise filter for deciding the stable movement decisions. While DTBGE employs binary images, DAISMI employs gray-scale images. Right and left eye estimates are evaluated separately. DAISMI finds the stable approximate pupil-center location by calculating the mass-center of eyeball border vertices to be employed for initial deformable template alignment. DTBGE starts running with initial alignment and updates the template alignment with resulting eye movements and eyeball size frame by frame. The horizontal and vertical deviation of eye movements through eyeball size is considered as if it is directly proportional with the deviation of cursor movements in a certain screen size and resolution. The core advantage of the system is that it does not employ the real pupil-center as a reference point for gaze estimation which is more reliable against corneal reflection. Visual angle accuracy is used for the evaluation and benchmarking of the system. Effectiveness of the proposed system is presented and experimental results are shown.

State and actuator fault estimation observer design integrated in a riderless bicycle stabilization system.

Science.gov (United States)

Brizuela Mendoza, Jorge Aurelio; Astorga Zaragoza, Carlos Manuel; Zavala Río, Arturo; Pattalochi, Leo; Canales Abarca, Francisco

2016-03-01

This paper deals with an observer design for Linear Parameter Varying (LPV) systems with high-order time-varying parameter dependency. The proposed design, considered as the main contribution of this paper, corresponds to an observer for the estimation of the actuator fault and the system state, considering measurement noise at the system outputs. The observer gains are computed by considering the extension of linear systems theory to polynomial LPV systems, in such a way that the observer reaches the characteristics of LPV systems. As a result, the actuator fault estimation is ready to be used in a Fault Tolerant Control scheme, where the estimated state with reduced noise should be used to generate the control law. The effectiveness of the proposed methodology has been tested using a riderless bicycle model with dependency on the translational velocity v, where the control objective corresponds to the system stabilization towards the upright position despite the variation of v along the closed-loop system trajectories. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

An Estimation Method of System Voltage Sag Profile using Recorded Sag Data

Science.gov (United States)

Tanaka, Kazuyuki; Sakashita, Tadashi

The influence of voltage sag to electric equipment has become big issues because of wider utilization of voltage sensitive devices. In order to reduce the influence of voltage sag appearing at each customer side, it is necessary to recognize the level of receiving voltage drop due to lightning faults for transmission line. However it is hard to measure directly those sag level at every load node. In this report, a new method of efficiently estimating system voltage sag profile is proposed based on symmetrical coordinate. In the proposed method, limited recorded sag data is used as the estimation condition which is recorded at each substation in power systems. From the point of view that the number of the recorded node is generally far less than those of the transmission route, a fast solution method is developed to calculate only recorder faulted voltage by applying reciprocity theorem for Y matrix. Furthermore, effective screening process is incorporated, in which the limited candidate of faulted transmission line can be chosen. Demonstrative results are presented using the IEEJ East10 standard system and actual 1700 bus system. The results show that estimation accuracy is sufficiently acceptable under less computation labor.

MATHEMATICAL MODEL FOR ESTIMATION OF MECHANICAL SYSTEM CONDITION IN DYNAMICS

Directory of Open Access Journals (Sweden)

D. N. Mironov

2011-01-01

Full Text Available The paper considers an estimation of a complicated mechanical system condition in dynamics with due account of material degradation and accumulation of micro-damages. An element of continuous medium has been simulated and described with the help of a discrete element. The paper contains description of a model for determination of mechanical system longevity in accordance with number of cycles and operational period.

Online payload estimation for the control of underactuated mechanical systems

International Nuclear Information System (INIS)

Lu, Yu Sheng; Chiu, Hua Hsu

2014-01-01

This paper presents a payload estimation scheme for underactuated robotic manipulators with passive joints that are not driven by actuators. In the proposed scheme, only the payload, which can be quite uncertain when a robot performs various tasks, is estimated, because the manipulator's electrical and other mechanical parameters are generally known in advance. In comparison to other adaptive schemes for underactuated robotic manipulators, the proposed scheme produces satisfactory transient performance and also reduces the computational burden in real-time implementation. The proposed estimation law is also based on the theory of Variable Structure Systems. In contrast to existing adaptation laws that have an integral form, the proposed law estimates uncertain payload using lowpass filtering of a switching signal that is always bounded, which avoids the parameter-drifting problem that is often encountered when using the previous integral laws. Real-time experiments are conducted using an inverted pendulum and the experimental results demonstrate the feasibility and effectiveness of the proposed scheme.

Chapter 16 - Predictive Analytics for Comprehensive Energy Systems State Estimation

Energy Technology Data Exchange (ETDEWEB)

Zhang, Yingchen [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Yang, Rui [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Hodge, Brian S [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhang, Jie [University of Texas at Dallas; Weng, Yang [Arizona State University

2017-12-01

Energy sustainability is a subject of concern to many nations in the modern world. It is critical for electric power systems to diversify energy supply to include systems with different physical characteristics, such as wind energy, solar energy, electrochemical energy storage, thermal storage, bio-energy systems, geothermal, and ocean energy. Each system has its own range of control variables and targets. To be able to operate such a complex energy system, big-data analytics become critical to achieve the goal of predicting energy supplies and consumption patterns, assessing system operation conditions, and estimating system states - all providing situational awareness to power system operators. This chapter presents data analytics and machine learning-based approaches to enable predictive situational awareness of the power systems.

FUNCTIONS OF THE HEAD OF SPECIAL (CORRECTIONAL) EDUCATIONAL INSTITUTION ON PERFECTION OF ESTIMATION OF EDUCATIONAL SYSTEM

OpenAIRE

Voynelenko Natalya Vaselyevna

2012-01-01

In article the maintenance of activity of the head of special (correctional) educational institution on the organization of estimation of quality of educational system is discussed. The model of joint activity of participants of educational process on estimation of educational objects, as component of system of quality management in Educational institution is presented. Functions of estimation of educational system in activity of the head of educational institution are formulated.

A note on reliability estimation of functionally diverse systems

International Nuclear Information System (INIS)

Littlewood, B.; Popov, P.; Strigini, L.

1999-01-01

It has been argued that functional diversity might be a plausible means of claiming independence of failures between two versions of a system. We present a model of functional diversity, in the spirit of earlier models of diversity such as those of Eckhardt and Lee, and Hughes. In terms of the model, we show that the claims for independence between functionally diverse systems seem rather unrealistic. Instead, it seems likely that functionally diverse systems will exhibit positively correlated failures, and thus will be less reliable than an assumption of independence would suggest. The result does not, of course, suggest that functional diversity is not worthwhile; instead, it places upon the evaluator of such a system the onus to estimate the degree of dependence so as to evaluate the reliability of the system

Power system observability and dynamic state estimation for stability monitoring using synchrophasor measurements

Energy Technology Data Exchange (ETDEWEB)

Sun, Kai; Qi, Junjian; Kang, Wei

2016-08-01

Growing penetration of intermittent resources such as renewable generations increases the risk of instability in a power grid. This paper introduces the concept of observability and its computational algorithms for a power grid monitored by the wide-area measurement system (WAMS) based on synchrophasors, e.g. phasor measurement units (PMUs). The goal is to estimate real-time states of generators, especially for potentially unstable trajectories, the information that is critical for the detection of rotor angle instability of the grid. The paper studies the number and siting of synchrophasors in a power grid so that the state of the system can be accurately estimated in the presence of instability. An unscented Kalman filter (UKF) is adopted as a tool to estimate the dynamic states that are not directly measured by synchrophasors. The theory and its computational algorithms are illustrated in detail by using a 9-bus 3-generator power system model and then tested on a 140-bus 48-generator Northeast Power Coordinating Council power grid model. Case studies on those two systems demonstrate the performance of the proposed approach using a limited number of synchrophasors for dynamic state estimation for stability assessment and its robustness against moderate inaccuracies in model parameters.

CMOS compatible thin-film ALD tungsten nanoelectromechanical devices

Science.gov (United States)

Davidson, Bradley Darren

This research focuses on the development of a novel, low-temperature, CMOS compatible, atomic-layer-deposition (ALD) enabled NEMS fabrication process for the development of ALD Tungsten (WALD) NEMS devices. The devices are intended for use in CMOS/NEMS hybrid systems, and NEMS based micro-processors/controllers capable of reliable operation in harsh environments not accessible to standard CMOS technologies. The majority of NEMS switches/devices to date have been based on carbon-nano-tube (CNT) designs. The devices consume little power during actuation, and as expected, have demonstrated actuation voltages much smaller than MEMS switches. Unfortunately, NEMS CNT switches are not typically CMOS integrable due to the high temperatures required for their growth, and their fabrication typically results in extremely low and unpredictable yields. Thin-film NEMS devices offer great advantages over reported CNT devices for several reasons, including: higher fabrication yields, low-temperature (CMOS compatible) deposition techniques like ALD, and increased control over design parameters/device performance metrics, i.e., device geometry. Furthermore, top-down, thin-film, nano-fabrication techniques are better capable of producing complicated device geometries than CNT based processes, enabling the design and development of multi-terminal switches well-suited for low-power hybrid NEMS/CMOS systems as well as electromechanical transistors and logic devices for use in temperature/radiation hard computing architectures. In this work several novel, low-temperature, CMOS compatible fabrication technologies, employing WALD as a structural layer for MEMS or NEMS devices, were developed. The technologies developed are top-down nano-scale fabrication processes based on traditional micro-machining techniques commonly used in the fabrication of MEMS devices. Using these processes a variety of novel WALD NEMS devices have been successfully fabricated and characterized. Using two different

OGRODJE POSLOVNEGA INFORMACIJSKEGA SISTEMA "MOONLIGHT BUSINESS SYSTEM" Z UPORABO TEHNOLOGIJE WPF

OpenAIRE

Drajzibner, Denis

2011-01-01

Diplomska naloga zajema raziskavo med že obstoječima poslovno informacijskima sistemoma IBM - Lotus Notes in Microsoft - Navision. Zanimivosti teh poslovno informacijskih sistemov so na kratko opisane. V diplomski nalogi je predstavljena idejna zasnova in implementacija lastnega poslovno informacijskega sistema »MoonLight Business System«. Implementacija je izvedena v WPF tehnologiji, ki je predstavljena v teoretičnem delu kakor tudi ostale tehnologije, ki se uporabljajo v »MoonLight Business...

Cost Engineering Techniques and Their Applicability for Cost Estimation of Organic Rankine Cycle Systems

Directory of Open Access Journals (Sweden)

Sanne Lemmens

2016-06-01

Full Text Available The potential of organic Rankine cycle (ORC systems is acknowledged by both considerable research and development efforts and an increasing number of applications. Most research aims at improving ORC systems through technical performance optimization of various cycle architectures and working fluids. The assessment and optimization of technical feasibility is at the core of ORC development. Nonetheless, economic feasibility is often decisive when it comes down to considering practical instalments, and therefore an increasing number of publications include an estimate of the costs of the designed ORC system. Various methods are used to estimate ORC costs but the resulting values are rarely discussed with respect to accuracy and validity. The aim of this paper is to provide insight into the methods used to estimate these costs and open the discussion about the interpretation of these results. A review of cost engineering practices shows there has been a long tradition of industrial cost estimation. Several techniques have been developed, but the expected accuracy range of the best techniques used in research varies between 10% and 30%. The quality of the estimates could be improved by establishing up-to-date correlations for the ORC industry in particular. Secondly, the rapidly growing ORC cost literature is briefly reviewed. A graph summarizing the estimated ORC investment costs displays a pattern of decreasing costs for increasing power output. Knowledge on the actual costs of real ORC modules and projects remains scarce. Finally, the investment costs of a known heat recovery ORC system are discussed and the methodologies and accuracies of several approaches are demonstrated using this case as benchmark. The best results are obtained with factorial estimation techniques such as the module costing technique, but the accuracies may diverge by up to +30%. Development of correlations and multiplication factors for ORC technology in particular is

Estimating the monthly discharge of a photovoltaic water pumping system: Model verification

International Nuclear Information System (INIS)

Amer, E.H.; Younes, M.A.

2006-01-01

A simple algorithm has been adopted for estimating the long term performance of a photovoltaic water pumping system without battery storage. The method uses the standard solar utilizability correlation equation to calculate the flow rate of the system, knowing an insolation threshold value. The method uses the monthly average solar radiation as the only input. The nonlinear relation between flow rate and solar insolation has been obtained experimentally in a first step and then used for performance prediction. The meteorological data collected instantaneously at the site of the pumping system has been used to obtain the monthly average values for solar radiation that are needed by the method. The method has been validated by predicting the performance of two PV pumping systems. The average output of the systems predicted by the method has been compared with experimental measurements. The estimated discharge differs by about 5% from the experimental measurements

Estimation of free-hydrocarbon recovery from dual-pump systems

International Nuclear Information System (INIS)

Charbeneau, R.J.

1995-01-01

Free-product hydrocarbon which floats on the water table may be recovered using single-pump and dual-pump systems. The factors that affect the long-term free-product recovery using dual-pump systems include the free-product thickness as measured in monitoring wells, the ground-water pumping rate, hydrocarbon density and viscosity, and the soil permeability. This paper presents a simple model for prediction of free-product recovery using dual-pump systems. The model predicts the long-term rather than short-term recovery rates, and lends itself to spreadsheet calculations on microcomputers. A particularly simple form arises for cases where the drawdown is small. An application for estimating recovery from a dual-pump system is presented, and limitations of the model are summarized

Estimation of 3D reconstruction errors in a stereo-vision system

Science.gov (United States)

Belhaoua, A.; Kohler, S.; Hirsch, E.

2009-06-01

The paper presents an approach for error estimation for the various steps of an automated 3D vision-based reconstruction procedure of manufactured workpieces. The process is based on a priori planning of the task and built around a cognitive intelligent sensory system using so-called Situation Graph Trees (SGT) as a planning tool. Such an automated quality control system requires the coordination of a set of complex processes performing sequentially data acquisition, its quantitative evaluation and the comparison with a reference model (e.g., CAD object model) in order to evaluate quantitatively the object. To ensure efficient quality control, the aim is to be able to state if reconstruction results fulfill tolerance rules or not. Thus, the goal is to evaluate independently the error for each step of the stereo-vision based 3D reconstruction (e.g., for calibration, contour segmentation, matching and reconstruction) and then to estimate the error for the whole system. In this contribution, we analyze particularly the segmentation error due to localization errors for extracted edge points supposed to belong to lines and curves composing the outline of the workpiece under evaluation. The fitting parameters describing these geometric features are used as quality measure to determine confidence intervals and finally to estimate the segmentation errors. These errors are then propagated through the whole reconstruction procedure, enabling to evaluate their effect on the final 3D reconstruction result, specifically on position uncertainties. Lastly, analysis of these error estimates enables to evaluate the quality of the 3D reconstruction, as illustrated by the shown experimental results.

Computer Model to Estimate Reliability Engineering for Air Conditioning Systems

International Nuclear Information System (INIS)

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

2012-01-01

Reliability engineering is used to predict the performance and optimize design and maintenance of air conditioning systems. Air conditioning systems are expose to a number of failures. The failures of an air conditioner such as turn on, loss of air conditioner cooling capacity, reduced air conditioning output temperatures, loss of cool air supply and loss of air flow entirely can be due to a variety of problems with one or more components of an air conditioner or air conditioning system. Forecasting for system failure rates are very important for maintenance. This paper focused on the reliability of the air conditioning systems. Statistical distributions that were commonly applied in reliability settings: the standard (2 parameter) Weibull and Gamma distributions. After distributions parameters had been estimated, reliability estimations and predictions were used for evaluations. To evaluate good operating condition in a building, the reliability of the air conditioning system that supplies conditioned air to the several The company's departments. This air conditioning system is divided into two, namely the main chilled water system and the ten air handling systems that serves the ten departments. In a chilled-water system the air conditioner cools water down to 40-45 degree F (4-7 degree C). The chilled water is distributed throughout the building in a piping system and connected to air condition cooling units wherever needed. Data analysis has been done with support a computer aided reliability software, this is due to the Weibull and Gamma distributions indicated that the reliability for the systems equal to 86.012% and 77.7% respectively. A comparison between the two important families of distribution functions, namely, the Weibull and Gamma families was studied. It was found that Weibull method performed for decision making.

Reliability/Cost Evaluation on Power System connected with Wind Power for the Reserve Estimation

DEFF Research Database (Denmark)

Lee, Go-Eun; Cha, Seung-Tae; Shin, Je-Seok

2012-01-01

Wind power is ideally a renewable energy with no fuel cost, but has a risk to reduce reliability of the whole system because of uncertainty of the output. If the reserve of the system is increased, the reliability of the system may be improved. However, the cost would be increased. Therefore...... the reserve needs to be estimated considering the trade-off between reliability and economic aspects. This paper suggests a methodology to estimate the appropriate reserve, when wind power is connected to the power system. As a case study, when wind power is connected to power system of Korea, the effects...

Optimal Superimposed Training Sequences for Channel Estimation in MIMO-OFDM Systems

Directory of Open Access Journals (Sweden)

Ratnam V. Raja Kumar

2010-01-01

Full Text Available In this work an iterative time domain Least Squares (LS based channel estimation method using superimposed training (ST for a Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM system over time varying frequency selective fading channels is proposed. The performance of the channel estimator is analyzed in terms of the Mean Square Estimation Error (MSEE and its impact on the uncoded Bit Error Rate (BER of the MIMO-OFDM system is studied. A new selection criterion for the training sequences that jointly optimizes the MSEE and the BER of the OFDM system is proposed. Chirp based sequences are proposed and shown to satisfy the same. These are compared with the other sequences proposed in the literature and are found to yield a superior performance. The sequences, one for each transmitting antenna, offers fairness through providing equal interference in all the data carriers unlike earlier proposals. The effectiveness of the mathematical analysis presented is demonstrated through a comparison with the simulation studies. Experimental studies are carried out to study and validate the improved performance of the proposed scheme. The scheme is applied to the IEEE 802.16e OFDM standard and a case is made with the required design of the sequence.

Estimating rare events in biochemical systems using conditional sampling

Science.gov (United States)

Sundar, V. S.

2017-01-01

The paper focuses on development of variance reduction strategies to estimate rare events in biochemical systems. Obtaining this probability using brute force Monte Carlo simulations in conjunction with the stochastic simulation algorithm (Gillespie's method) is computationally prohibitive. To circumvent this, important sampling tools such as the weighted stochastic simulation algorithm and the doubly weighted stochastic simulation algorithm have been proposed. However, these strategies require an additional step of determining the important region to sample from, which is not straightforward for most of the problems. In this paper, we apply the subset simulation method, developed as a variance reduction tool in the context of structural engineering, to the problem of rare event estimation in biochemical systems. The main idea is that the rare event probability is expressed as a product of more frequent conditional probabilities. These conditional probabilities are estimated with high accuracy using Monte Carlo simulations, specifically the Markov chain Monte Carlo method with the modified Metropolis-Hastings algorithm. Generating sample realizations of the state vector using the stochastic simulation algorithm is viewed as mapping the discrete-state continuous-time random process to the standard normal random variable vector. This viewpoint opens up the possibility of applying more sophisticated and efficient sampling schemes developed elsewhere to problems in stochastic chemical kinetics. The results obtained using the subset simulation method are compared with existing variance reduction strategies for a few benchmark problems, and a satisfactory improvement in computational time is demonstrated.

A priori estimates of global solutions of superlinear parabolic systems

Directory of Open Access Journals (Sweden)

Julius Pacuta

2016-04-01

Full Text Available We consider the parabolic system $ u_{t}-\\Delta u = u^{r}v^{p}$, $v_{t}-\\Delta v = u^{q}v^{s}$ in $\\Omega\\times(0,\\infty$, complemented by the homogeneous Dirichlet boundary conditions and the initial conditions $(u,v(\\cdot,0 = (u_{0},v_{0}$ in $\\Omega$, where $\\Omega $ is a smooth bounded domain in $ \\mathbb{R}^{N} $ and $ u_{0},v_{0}\\in L^{\\infty}(\\Omega$ are nonnegative functions. We find conditions on $ p,q,r,s $ guaranteeing a priori estimates of nonnegative classical global solutions. More precisely every such solution is bounded by a constant depending on suitable norm of the initial data. Our proofs are based on bootstrap in weighted Lebesgue spaces, universal estimates of auxiliary functions and estimates of the Dirichlet heat kernel.

COMPUTER SUPPORT SYSTEMS FOR ESTIMATING CHEMICAL TOXICITY: PRESENT CAPABILITIES AND FUTURE TRENDS

Science.gov (United States)

Computer Support Systems for Estimating Chemical Toxicity: Present Capabilities and Future Trends A wide variety of computer-based artificial intelligence (AI) and decision support systems exist currently to aid in the assessment of toxicity for environmental chemicals. T...

Measurement Model Nonlinearity in Estimation of Dynamical Systems

Science.gov (United States)

Majji, Manoranjan; Junkins, J. L.; Turner, J. D.

2012-06-01

The role of nonlinearity of the measurement model and its interactions with the uncertainty of measurements and geometry of the problem is studied in this paper. An examination of the transformations of the probability density function in various coordinate systems is presented for several astrodynamics applications. Smooth and analytic nonlinear functions are considered for the studies on the exact transformation of uncertainty. Special emphasis is given to understanding the role of change of variables in the calculus of random variables. The transformation of probability density functions through mappings is shown to provide insight in to understanding the evolution of uncertainty in nonlinear systems. Examples are presented to highlight salient aspects of the discussion. A sequential orbit determination problem is analyzed, where the transformation formula provides useful insights for making the choice of coordinates for estimation of dynamic systems.

Simple robust technique using time delay estimation for the control and synchronization of Lorenz systems

International Nuclear Information System (INIS)

Jin, Maolin; Chang, Pyung Hun

2009-01-01

This work presents two simple and robust techniques based on time delay estimation for the respective control and synchronization of chaos systems. First, one of these techniques is applied to the control of a chaotic Lorenz system with both matched and mismatched uncertainties. The nonlinearities in the Lorenz system is cancelled by time delay estimation and desired error dynamics is inserted. Second, the other technique is applied to the synchronization of the Lue system and the Lorenz system with uncertainties. The synchronization input consists of three elements that have transparent and clear meanings. Since time delay estimation enables a very effective and efficient cancellation of disturbances and nonlinearities, the techniques turn out to be simple and robust. Numerical simulation results show fast, accurate and robust performance of the proposed techniques, thereby demonstrating their effectiveness for the control and synchronization of Lorenz systems.

An adaptive neuro fuzzy model for estimating the reliability of component-based software systems

Directory of Open Access Journals (Sweden)

Kirti Tyagi

2014-01-01

Full Text Available Although many algorithms and techniques have been developed for estimating the reliability of component-based software systems (CBSSs, much more research is needed. Accurate estimation of the reliability of a CBSS is difficult because it depends on two factors: component reliability and glue code reliability. Moreover, reliability is a real-world phenomenon with many associated real-time problems. Soft computing techniques can help to solve problems whose solutions are uncertain or unpredictable. A number of soft computing approaches for estimating CBSS reliability have been proposed. These techniques learn from the past and capture existing patterns in data. The two basic elements of soft computing are neural networks and fuzzy logic. In this paper, we propose a model for estimating CBSS reliability, known as an adaptive neuro fuzzy inference system (ANFIS, that is based on these two basic elements of soft computing, and we compare its performance with that of a plain FIS (fuzzy inference system for different data sets.

Artificial Neural Network-Based Clutter Reduction Systems for Ship Size Estimation in Maritime Radars

Directory of Open Access Journals (Sweden)

M. P. Jarabo-Amores

2010-01-01

Full Text Available The existence of clutter in maritime radars deteriorates the estimation of some physical parameters of the objects detected over the sea surface. For that reason, maritime radars should incorporate efficient clutter reduction techniques. Due to the intrinsic nonlinear dynamic of sea clutter, nonlinear signal processing is needed, what can be achieved by artificial neural networks (ANNs. In this paper, an estimation of the ship size using an ANN-based clutter reduction system followed by a fixed threshold is proposed. High clutter reduction rates are achieved using 1-dimensional (horizontal or vertical integration modes, although inaccurate ship width estimations are achieved. These estimations are improved using a 2-dimensional (rhombus integration mode. The proposed system is compared with a CA-CFAR system, denoting a great performance improvement and a great robustness against changes in sea clutter conditions and ship parameters, independently of the direction of movement of the ocean waves and ships.

Hierarchical parameter estimation of DFIG and drive train system in a wind turbine generator

Institute of Scientific and Technical Information of China (English)

Xueping PAN; Ping JU; Feng WU; Yuqing JIN

2017-01-01

A new hierarchical parameter estimation method for doubly fed induction generator (DFIG) and drive train system in a wind turbine generator (WTG) is proposed in this paper.Firstly,the parameters of the DFIG and the drive train are estimated locally under different types of disturbances.Secondly,a coordination estimation method is further applied to identify the parameters of the DFIG and the drive train simultaneously with the purpose of attaining the global optimal estimation results.The main benefit of the proposed scheme is the improved estimation accuracy.Estimation results confirm the applicability of the proposed estimation technique.

Errors in the estimation method for the rejection of vibrations in adaptive optics systems

Science.gov (United States)

Kania, Dariusz

2017-06-01

In recent years the problem of the mechanical vibrations impact in adaptive optics (AO) systems has been renewed. These signals are damped sinusoidal signals and have deleterious effect on the system. One of software solutions to reject the vibrations is an adaptive method called AVC (Adaptive Vibration Cancellation) where the procedure has three steps: estimation of perturbation parameters, estimation of the frequency response of the plant, update the reference signal to reject/minimalize the vibration. In the first step a very important problem is the estimation method. A very accurate and fast (below 10 ms) estimation method of these three parameters has been presented in several publications in recent years. The method is based on using the spectrum interpolation and MSD time windows and it can be used to estimate multifrequency signals. In this paper the estimation method is used in the AVC method to increase the system performance. There are several parameters that affect the accuracy of obtained results, e.g. CiR - number of signal periods in a measurement window, N - number of samples in the FFT procedure, H - time window order, SNR, b - number of ADC bits, γ - damping ratio of the tested signal. Systematic errors increase when N, CiR, H decrease and when γ increases. The value for systematic error is approximately 10^-10 Hz/Hz for N = 2048 and CiR = 0.1. This paper presents equations that can used to estimate maximum systematic errors for given values of H, CiR and N before the start of the estimation process.

Characterization of low temperature deposited atomic layer deposition TiO2 for MEMS applications

NARCIS (Netherlands)

Huang, Y.; Pandraud, G.; Sarro, P.M.

2012-01-01

TiO2 is an interesting and promising material for micro-/nanoelectromechanical systems (MEMS/NEMS). For high performance and reliable MEMS/NEMS, optimization of the optical characteristics, mechanical stress, and especially surface smoothness of TiO2 is required. To overcome the roughness issue of

A continuous wave fan beam tomography system having a best estimating filter

International Nuclear Information System (INIS)

Gordon, B.M.

1982-01-01

A continuous wave fan beam tomographic system is described which continuously samples X-ray absorption values and a means of providing a best-estimate of the X-ray absorption values at discrete points in time determined by sampling signal s(t). The means to provide the best-estimate include a continuous filter having a frequency range defined by the geometry of the mechanical system. Errors due to the statistical variation in photon emissions of the X-ray source are thereby minimized and the effective signal-to-noise ratio of signals is enhanced, which in turn allows a significant reduction in radiation dosage. (author)

Performance of Cross-layer Design with Multiple Outdated Estimates in Multiuser MIMO System

Directory of Open Access Journals (Sweden)

X. Yu

2014-09-01

Full Text Available By combining adaptive modulation (AM and automatic repeat request (ARQ protocol as well as user scheduling, the cross-layer design scheme of multiuser MIMO system with imperfect feedback is presented, and multiple outdated estimates method is proposed to improve the system performance. Based on this method and imperfect feedback information, the closed-form expressions of spectral efficiency (SE and packet error rate (PER of the system subject to the target PER constraint are respectively derived. With these expressions, the system performance can be effectively evaluated. To mitigate the effect of delayed feedback, the variable thresholds (VTs are also derived by means of the maximum a posteriori method, and these VTs include the conventional fixed thresholds (FTs as special cases. Simulation results show that the theoretical SE and PER are in good agreement with the corresponding simulation. The proposed CLD scheme with multiple estimates can obtain higher SE than the existing CLD scheme with single estimate, especially for large delay. Moreover, the CLD scheme with VTs outperforms that with conventional FTs.

A Robust Localization, Slip Estimation, and Compensation System for WMR in the Indoor Environments

Directory of Open Access Journals (Sweden)

Zakir Ullah

2018-05-01

Full Text Available A novel approach is proposed for the path tracking of a Wheeled Mobile Robot (WMR in the presence of an unknown lateral slip. Much of the existing work has assumed pure rolling conditions between the wheel and ground. Under the pure rolling conditions, the wheels of a WMR are supposed to roll without slipping. Complex wheel-ground interactions, acceleration and steering system noise are the factors which cause WMR wheel slip. A basic research problem in this context is localization and slip estimation of WMR from a stream of noisy sensors data when the robot is moving on a slippery surface, or moving at a high speed. DecaWave based ranging system and Particle Filter (PF are good candidates to estimate the location of WMR indoors and outdoors. Unfortunately, wheel-slip of WMR limits the ultimate performance that can be achieved by real-world implementation of the PF, because location estimation systems typically partially rely on the robot heading. A small error in the WMR heading leads to a large error in location estimation of the PF because of its cumulative nature. In order to enhance the tracking and localization performance of the PF in the environments where the main reason for an error in the PF location estimation is angular noise, two methods were used for heading estimation of the WMR (1: Reinforcement Learning (RL and (2: Location-based Heading Estimation (LHE. Trilateration is applied to DecaWave based ranging system for calculating the probable location of WMR, this noisy location along with PF current mean is used to estimate the WMR heading by using the above two methods. Beside the WMR location calculation, DecaWave based ranging system is also used to update the PF weights. The localization and tracking performance of the PF is significantly improved through incorporating heading error in localization by applying RL and LHE. Desired trajectory information is then used to develop an algorithm for extracting the lateral slip along

Linear regressive model structures for estimation and prediction of compartmental diffusive systems

NARCIS (Netherlands)

Vries, D; Keesman, K.J.; Zwart, Heiko J.

In input-output relations of (compartmental) diffusive systems, physical parameters appear non-linearly, resulting in the use of (constrained) non-linear parameter estimation techniques with its short-comings regarding global optimality and computational effort. Given a LTI system in state space

Linear regressive model structures for estimation and prediction of compartmental diffusive systems

NARCIS (Netherlands)

Vries, D.; Keesman, K.J.; Zwart, H.

2006-01-01

Abstract In input-output relations of (compartmental) diffusive systems, physical parameters appear non-linearly, resulting in the use of (constrained) non-linear parameter estimation techniques with its short-comings regarding global optimality and computational effort. Given a LTI system in state

Life cycle cost estimation and systems analysis of Waste Management Facilities

International Nuclear Information System (INIS)

Shropshire, D.; Feizollahi, F.

1995-01-01

This paper presents general conclusions from application of a system cost analysis method developed by the United States Department of Energy (DOE), Waste Management Division (WM), Waste Management Facilities Costs Information (WMFCI) program. The WMFCI method has been used to assess the DOE complex-wide management of radioactive, hazardous, and mixed wastes. The Idaho Engineering Laboratory, along with its subcontractor Morrison Knudsen Corporation, has been responsible for developing and applying the WMFCI cost analysis method. The cost analyses are based on system planning level life-cycle costs. The costs for life-cycle waste management activities estimated by WMFCI range from bench-scale testing and developmental work needed to design and construct a facility, facility permitting and startup, operation and maintenance, to the final decontamination, decommissioning, and closure of the facility. For DOE complex-wide assessments, cost estimates have been developed at the treatment, storage, and disposal module level and rolled up for each DOE installation. Discussions include conclusions reached by studies covering complex-wide consolidation of treatment, storage, and disposal facilities, system cost modeling, system costs sensitivity, system cost optimization, and the integration of WM waste with the environmental restoration and decontamination and decommissioning secondary wastes

Joint state and parameter estimation for a class of cascade systems: Application to a hemodynamic model

KAUST Repository

Zayane, Chadia

2014-06-01

In this paper, we address a special case of state and parameter estimation, where the system can be put on a cascade form allowing to estimate the state components and the set of unknown parameters separately. Inspired by the nonlinear Balloon hemodynamic model for functional Magnetic Resonance Imaging problem, we propose a hierarchical approach. The system is divided into two subsystems in cascade. The state and input are first estimated from a noisy measured signal using an adaptive observer. The obtained input is then used to estimate the parameters of a linear system using the modulating functions method. Some numerical results are presented to illustrate the efficiency of the proposed method.

Simultaneous Event-Triggered Fault Detection and Estimation for Stochastic Systems Subject to Deception Attacks.

Science.gov (United States)

Li, Yunji; Wu, QingE; Peng, Li

2018-01-23

In this paper, a synthesized design of fault-detection filter and fault estimator is considered for a class of discrete-time stochastic systems in the framework of event-triggered transmission scheme subject to unknown disturbances and deception attacks. A random variable obeying the Bernoulli distribution is employed to characterize the phenomena of the randomly occurring deception attacks. To achieve a fault-detection residual is only sensitive to faults while robust to disturbances, a coordinate transformation approach is exploited. This approach can transform the considered system into two subsystems and the unknown disturbances are removed from one of the subsystems. The gain of fault-detection filter is derived by minimizing an upper bound of filter error covariance. Meanwhile, system faults can be reconstructed by the remote fault estimator. An recursive approach is developed to obtain fault estimator gains as well as guarantee the fault estimator performance. Furthermore, the corresponding event-triggered sensor data transmission scheme is also presented for improving working-life of the wireless sensor node when measurement information are aperiodically transmitted. Finally, a scaled version of an industrial system consisting of local PC, remote estimator and wireless sensor node is used to experimentally evaluate the proposed theoretical results. In particular, a novel fault-alarming strategy is proposed so that the real-time capacity of fault-detection is guaranteed when the event condition is triggered.

Dynamic range of atomically thin vibrating nanomechanical resonators

International Nuclear Information System (INIS)

Wang, Zenghui; Feng, Philip X.-L.

2014-01-01

Atomically thin two-dimensional (2D) crystals offer attractive properties for making resonant nanoelectromechanical systems (NEMS) operating at high frequencies. While the fundamental limits of linear operation in such systems are important, currently there is very little quantitative knowledge of the linear dynamic range (DR) and onset of nonlinearity in these devices, which are different than in conventional 1D NEMS such as nanotubes and nanowires. Here, we present theoretical analysis and quantitative models that can be directly used to predict the DR of vibrating 2D circular drumhead NEMS resonators. We show that DR has a strong dependence ∝10log(E Y 3/2 ρ 3D -1/2 rtε 5/2 ) on device parameters, in which strain ε plays a particularly important role in these 2D systems, dominating over dimensions (radius r, thickness t). This study formulizes the effects from device physical parameters upon DR and sheds light on device design rules toward achieving high DR in 2D NEMS vibrating at radio and microwave frequencies

Dependability estimation for non-Markov consecutive-k-out-of-n: F repairable systems by fast simulation

International Nuclear Information System (INIS)

Xiao Gang; Li Zhizhong; Li Ting

2007-01-01

A model of consecutive-k-out-of-n: F repairable system with non-exponential repair time distribution and (k-1)-step Markov dependence is introduced in this paper along with algorithms of three Monte Carlo methods, i.e. importance sampling, conditional expectation estimation and combination of the two methods, to estimate dependability of the non-Markov model including reliability, transient unavailability, MTTF, and MTBF. A numerical example is presented to demonstrate the efficiencies of above methods. The results show that combinational method has the highest efficiency for estimation of unreliability and unavailability, while conditional expectation estimation is the most efficient method for estimation of MTTF and MTBF. Conditional expectation estimation seems to have overall higher speedups in estimating dependability of such systems

Adjudication Decision Support (ADS) System Automated Approval Estimates for NACLC Investigations

National Research Council Canada - National Science Library

Lang, Eric L; Youpa, Daniel G; Berman, Sandi; Leggitt, John S

2007-01-01

The present research is the second in a series of studies to test preliminary decision rules and provide automated approval estimates for a Department of Defense Adjudication Decision Support (ADS) system...

Robust and efficient parameter estimation in dynamic models of biological systems.

Science.gov (United States)

Gábor, Attila; Banga, Julio R

2015-10-29

Dynamic modelling provides a systematic framework to understand function in biological systems. Parameter estimation in nonlinear dynamic models remains a very challenging inverse problem due to its nonconvexity and ill-conditioning. Associated issues like overfitting and local solutions are usually not properly addressed in the systems biology literature despite their importance. Here we present a method for robust and efficient parameter estimation which uses two main strategies to surmount the aforementioned difficulties: (i) efficient global optimization to deal with nonconvexity, and (ii) proper regularization methods to handle ill-conditioning. In the case of regularization, we present a detailed critical comparison of methods and guidelines for properly tuning them. Further, we show how regularized estimations ensure the best trade-offs between bias and variance, reducing overfitting, and allowing the incorporation of prior knowledge in a systematic way. We illustrate the performance of the presented method with seven case studies of different nature and increasing complexity, considering several scenarios of data availability, measurement noise and prior knowledge. We show how our method ensures improved estimations with faster and more stable convergence. We also show how the calibrated models are more generalizable. Finally, we give a set of simple guidelines to apply this strategy to a wide variety of calibration problems. Here we provide a parameter estimation strategy which combines efficient global optimization with a regularization scheme. This method is able to calibrate dynamic models in an efficient and robust way, effectively fighting overfitting and allowing the incorporation of prior information.

Model documentation, Renewable Fuels Module of the National Energy Modeling System

Energy Technology Data Exchange (ETDEWEB)

NONE

1998-01-01

This report documents the objectives, analytical approach, and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the Annual Energy Outlook 1998 (AEO98) forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs, and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described. For AEO98, the RFM was modified in three principal ways, introducing capital cost elasticities of supply for new renewable energy technologies, modifying biomass supply curves, and revising assumptions for use of landfill gas from municipal solid waste (MSW). In addition, the RFM was modified in general to accommodate projections beyond 2015 through 2020. Two supply elasticities were introduced, the first reflecting short-term (annual) cost increases from manufacturing, siting, and installation bottlenecks incurred under conditions of rapid growth, and the second reflecting longer term natural resource, transmission and distribution upgrade, and market limitations increasing costs as more and more of the overall resource is used. Biomass supply curves were also modified, basing forest products supplies on production rather than on inventory, and expanding energy crop estimates to include states west of the Mississippi River using information developed by the Oak Ridge National Laboratory. Finally, for MSW, several assumptions for the use of landfill gas were revised and extended.

Capacity Estimation and Near-Capacity Achieving Techniques for Digitally Modulated Communication Systems

DEFF Research Database (Denmark)

Yankov, Metodi Plamenov

investigation will include linear interference channels of high dimensionality (such as multiple-input multiple-output), and the non-linear optical fiber channel, which has been gathering more and more attention from the information theory community in recent years. In both cases novel CCC estimates and lower......This thesis studies potential improvements that can be made to the current data rates of digital communication systems. The physical layer of the system will be investigated in band-limited scenarios, where high spectral efficiency is necessary in order to meet the ever-growing data rate demand....... Several issues are tackled, both with theoretical and more practical aspects. The theoretical part is mainly concerned with estimating the constellation constrained capacity (CCC) of channels with discrete input, which is an inherent property of digital communication systems. The channels under...

Nem só de pão vive o homem Man shall not live by bread alone

Directory of Open Access Journals (Sweden)

Rodrigo da Cunha Pereira

2006-12-01

Full Text Available Este artigo pretende contribuir com a discussão sobre as prerrogativas da paternidade sob o prisma da valorização das funções paternas, das limitações de direitos e da afirmação de deveres do pai. Uma polêmica instigante se instalou a partir da eclosão de demandas judiciais em que filhos denunciam o abandono afetivo, psíquico e moral de seus pais, pedindo reparação pelos danos causados, em processos que chegaram aos tribunais, Alguns entendem que o abandono afetivo deve ser reparado por meio de indenização pecuniária. Outros, com o argumento de que não se pode obrigar um pai a amar e a conviver com seu filho, se opõem à exigência de reparação por abandono. Argumentam que, uma vez cumprido o dever de prestar alimentos, o pai se desincumbiria de suas obrigações perante o filho. Entretanto, nem só de pão vive o homem...The present article contributes to the discussions regarding the prerrogatives of paternity, under the aspect of valueing paternal functions, the limitation of rights and the affirmation of the paternal duties. A provocative polemic has been installed stemming from the eclosion of judicial demands in which children denounce the affective, psychic and moral abandon suffered from their fathers, claiming reparations for damages caused, all in court. Some of the children demand financial remunerations to compensate affective abandon. Others, claiming that a father can’t be forced to love or live with a child, oppose claiming for financial compensations. They state that, once living up to the function of providing alimony, a father would be exempt from his obligations towards the child. However, a person needs more than bread to survive...

Channel Equalization and Phase Estimation for Reduced-Guard-Interval CO-OFDM Systems

Science.gov (United States)

Zhuge, Qunbi

Reduced-guard-interval (RGI) coherent optical (CO) orthogonal frequency-division multiplexing (OFDM) is a potential candidate for next generation 100G beyond optical transports, attributed to its advantages such as high spectral efficiency and high tolerance to optical channel impairments. First of all, we review the coherent optical systems with an emphasis on CO-OFDM systems as well as the optical channel impairments and the general digital signal processing techniques to combat them. This work focuses on the channel equalization and phase estimation of RGI CO-OFDM systems. We first propose a novel equalization scheme based on the equalization structure of RGI CO-OFDM to reduce the cyclic prefix overhead to zero. Then we show that intra-channel nonlinearities should be considered when designing the training symbols for channel estimation. Afterwards, we propose and analyze the phenomenon of dispersion-enhanced phase noise (DEPN) caused by the interaction between the laser phase noise and the chromatic dispersion in RGI CO-OFDM transmissions. DEPN induces a non-negligible performance degradation and limits the tolerant laser linewidth. However, it can be compensated by the grouped maximum-likelihood phase estimation proposed in this work.

On H∞ Fault Estimator Design for Linear Discrete Time-Varying Systems under Unreliable Communication Link

Directory of Open Access Journals (Sweden)

Yueyang Li

2014-01-01

Full Text Available This paper investigates the H∞ fixed-lag fault estimator design for linear discrete time-varying (LDTV systems with intermittent measurements, which is described by a Bernoulli distributed random variable. Through constructing a novel partially equivalent dynamic system, the fault estimator design is converted into a deterministic quadratic minimization problem. By applying the innovation reorganization technique and the projection formula in Krein space, a necessary and sufficient condition is obtained for the existence of the estimator. The parameter matrices of the estimator are derived by recursively solving two standard Riccati equations. An illustrative example is provided to show the effectiveness and applicability of the proposed algorithm.

State Estimation for Linear Systems Driven Simultaneously by Wiener and Poisson Processes.

Science.gov (United States)

1978-12-01

The state estimation problem of linear stochastic systems driven simultaneously by Wiener and Poisson processes is considered, especially the case...where the incident intensities of the Poisson processes are low and the system is observed in an additive white Gaussian noise. The minimum mean squared

Six types Monte Carlo for estimating the current unavailability of Markov system with dependent repair

International Nuclear Information System (INIS)

Xiao Gang; Li Zhizhong

2004-01-01

Based on integral equaiton describing the life-history of Markov system, six types of estimators of the current unavailability of Markov system with dependent repair are propounded. Combining with the biased sampling of state transition time of system, six types of Monte Carlo for estimating the current unavailability are given. Two numerical examples are given to deal with the variances and efficiencies of the six types of Monte Carlo methods. (authors)

Dynamical System and Nonlinear Regression for Estimate Host-Parasitoid Relationship

Directory of Open Access Journals (Sweden)

Ileana Miranda Cabrera

2010-01-01

Full Text Available The complex relationships of a crop with the pest, its natural enemies, and the climate factors exist in all the ecosystems, but the mathematic models has studied only some components to know the relation cause-effect. The most studied system has been concerned with the relationship pest-natural enemies such as prey-predator or host-parasitoid. The present paper shows a dynamical system for studying the relationship host-parasitoid (Diaphorina citri, Tamarixia radiata and shows that a nonlinear model permits the estimation of the parasite nymphs using nymphs healthy as the known variable. The model showed the functional answer of the parasitoid, in which a point arrives that its density is not augmented although the number host increases, and it becomes necessary to intervene in the ecosystem. A simple algorithm is used to estimate the parasitoids level using the priori relationship between the host and the climate factors and then the nonlinear model.

Carrier Frequency Offset Estimation and I/Q Imbalance Compensation for OFDM Systems

Directory of Open Access Journals (Sweden)

M. Omair Ahmad

2007-01-01

Full Text Available Two types of radio-frequency front-end imperfections, that is, carrier frequency offset and the inphase/quadrature (I/Q imbalance are considered for orthogonal frequency division multiplexing (OFDM communication systems. A preamble-assisted carrier frequency estimator is proposed along with an I/Q imbalance compensation scheme. The new frequency estimator reveals the relationship between the inphase and the quadrature components of the received preamble and extracts the frequency offset from the phase shift caused by the frequency offset and the cross-talk interference due to the I/Q imbalance. The proposed frequency estimation algorithm is fast, efficient, and robust to I/Q imbalance. An I/Q imbalance estimation/compensation algorithm is also presented by solving a least-square problem formulated using the same preamble as employed for the frequency offset estimation. The computational complexity of the I/Q estimation scheme is further reduced by using part of the short symbols with a little sacrifice in the estimation accuracy. Computer simulation and comparison with some of the existing algorithms are conducted, showing the effectiveness of the proposed method.

Nonlinear systems time-varying parameter estimation: Application to induction motors

Energy Technology Data Exchange (ETDEWEB)

Kenne, Godpromesse [Laboratoire d' Automatique et d' Informatique Appliquee (LAIA), Departement de Genie Electrique, IUT FOTSO Victor, Universite de Dschang, B.P. 134 Bandjoun (Cameroon); Ahmed-Ali, Tarek [Ecole Nationale Superieure des Ingenieurs des Etudes et Techniques d' Armement (ENSIETA), 2 Rue Francois Verny, 29806 Brest Cedex 9 (France); Lamnabhi-Lagarrigue, F. [Laboratoire des Signaux et Systemes (L2S), C.N.R.S-SUPELEC, Universite Paris XI, 3 Rue Joliot Curie, 91192 Gif-sur-Yvette (France); Arzande, Amir [Departement Energie, Ecole Superieure d' Electricite-SUPELEC, 3 Rue Joliot Curie, 91192 Gif-sur-Yvette (France)

2008-11-15

In this paper, an algorithm for time-varying parameter estimation for a large class of nonlinear systems is presented. The proof of the convergence of the estimates to their true values is achieved using Lyapunov theories and does not require that the classical persistent excitation condition be satisfied by the input signal. Since the induction motor (IM) is widely used in several industrial sectors, the algorithm developed is potentially useful for adjusting the controller parameters of variable speed drives. The method proposed is simple and easily implementable in real-time. The application of this approach to on-line estimation of the rotor resistance of IM shows a rapidly converging estimate in spite of measurement noise, discretization effects, parameter uncertainties (e.g. inaccuracies on motor inductance values) and modeling inaccuracies. The robustness analysis for this IM application also revealed that the proposed scheme is insensitive to the stator resistance variations within a wide range. The merits of the proposed algorithm in the case of on-line time-varying rotor resistance estimation are demonstrated via experimental results in various operating conditions of the induction motor. The experimental results obtained demonstrate that the application of the proposed algorithm to update on-line the parameters of an adaptive controller (e.g. IM and synchronous machines adaptive control) can improve the efficiency of the industrial process. The other interesting features of the proposed method include fault detection/estimation and adaptive control of IM and synchronous machines. (author)

An expert system for diagnostics and estimation of steam turbine components condition

Science.gov (United States)

Murmansky, B. E.; Aronson, K. E.; Brodov, Yu. M.

2017-11-01

The report describes an expert system of probability type for diagnostics and state estimation of steam turbine technological subsystems components. The expert system is based on Bayes’ theorem and permits to troubleshoot the equipment components, using expert experience, when there is a lack of baseline information on the indicators of turbine operation. Within a unified approach the expert system solves the problems of diagnosing the flow steam path of the turbine, bearings, thermal expansion system, regulatory system, condensing unit, the systems of regenerative feed-water and hot water heating. The knowledge base of the expert system for turbine unit rotors and bearings contains a description of 34 defects and of 104 related diagnostic features that cause a change in its vibration state. The knowledge base for the condensing unit contains 12 hypotheses and 15 evidence (indications); the procedures are also designated for 20 state parameters estimation. Similar knowledge base containing the diagnostic features and faults hypotheses are formulated for other technological subsystems of turbine unit. With the necessary initial information available a number of problems can be solved within the expert system for various technological subsystems of steam turbine unit: for steam flow path it is the correlation and regression analysis of multifactor relationship between the vibration parameters variations and the regime parameters; for system of thermal expansions it is the evaluation of force acting on the longitudinal keys depending on the temperature state of the turbine cylinder; for condensing unit it is the evaluation of separate effect of the heat exchange surface contamination and of the presence of air in condenser steam space on condenser thermal efficiency performance, as well as the evaluation of term for condenser cleaning and for tube system replacement and so forth. With a lack of initial information the expert system enables to formulate a diagnosis

Secure Fusion Estimation for Bandwidth Constrained Cyber-Physical Systems Under Replay Attacks.

Science.gov (United States)

Chen, Bo; Ho, Daniel W C; Hu, Guoqiang; Yu, Li; Bo Chen; Ho, Daniel W C; Guoqiang Hu; Li Yu; Chen, Bo; Ho, Daniel W C; Hu, Guoqiang; Yu, Li

2018-06-01

State estimation plays an essential role in the monitoring and supervision of cyber-physical systems (CPSs), and its importance has made the security and estimation performance a major concern. In this case, multisensor information fusion estimation (MIFE) provides an attractive alternative to study secure estimation problems because MIFE can potentially improve estimation accuracy and enhance reliability and robustness against attacks. From the perspective of the defender, the secure distributed Kalman fusion estimation problem is investigated in this paper for a class of CPSs under replay attacks, where each local estimate obtained by the sink node is transmitted to a remote fusion center through bandwidth constrained communication channels. A new mathematical model with compensation strategy is proposed to characterize the replay attacks and bandwidth constrains, and then a recursive distributed Kalman fusion estimator (DKFE) is designed in the linear minimum variance sense. According to different communication frameworks, two classes of data compression and compensation algorithms are developed such that the DKFEs can achieve the desired performance. Several attack-dependent and bandwidth-dependent conditions are derived such that the DKFEs are secure under replay attacks. An illustrative example is given to demonstrate the effectiveness of the proposed methods.

A Study of Ship Acquisition Cost Estimating in the Naval Sea Systems Command. Appendices

Science.gov (United States)

1977-10-01

acquisition pro- cess, the recommendations are linked to form a structure that is applicable for acquisition progress of all agencies...and impact on cost. CAIG considers GFM estimates to be the weakest link in the estimating process and suggests making it mandatory that the PARMs...tor- pedo and missile orders; and for providing display data to fire control systems and tactical data system operators. The AN/UYK-7 is installed