MEMS- and NEMS-based smart devices and systems
Varadan, Vijay K.
2001-11-01
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 sized now don 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 an 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 sensing and control of a variety functions in automobile, aerospace, marine and civil
International Nuclear Information System (INIS)
Wilkerson, Jordan T.; Cullenward, Danny; Davidian, Danielle; Weyant, John P.
2013-01-01
The National Energy Modeling System (NEMS) is arguably the most influential energy model in the United States. The U.S. Energy Information Administration uses NEMS to generate the federal government's annual long-term forecast of national energy consumption and to evaluate prospective federal energy policies. NEMS is considered such a standard tool that other models are calibrated to its forecasts, in both government and academic practice. As a result, NEMS has a significant influence over expert opinions of plausible energy futures. NEMS is a massively detailed model whose inner workings, despite its prominence, receive relatively scant critical attention. This paper analyzes how NEMS projects energy demand in the residential and commercial sectors. In particular, we focus on the role of consumers' preferences and financial constraints, investigating how consumers choose appliances and other end-use technologies. We identify conceptual issues in the approach the model takes to the same question across both sectors. Running the model with a range of consumer preferences, we estimate the extent to which this issue impacts projected consumption relative to the baseline model forecast for final energy demand in the year 2035. In the residential sector, the impact ranges from a decrease of 0.73 quads (− 6.0%) to an increase of 0.24 quads (+ 2.0%). In the commercial sector, the impact ranges from a decrease of 1.0 quads (− 9.0%) to an increase of 0.99 quads (+ 9.0%). - Highlights: • This paper examines the impact of consumer preferences on final energy in the Commercial and Residential sectors of the National Energy Modeling System (NEMS). • We describe the conceptual and empirical basis for modeling consumer technology choice in NEMS. • We offer a range of alternative parameters to show the energy demand sensitivity to technology choice. • We show there are significant potential savings available in both building sectors. • Because the model uses its own
Vibrations of Elastic Systems With Applications to MEMS and NEMS
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.
NEMS integrating module documentation report
Energy Technology Data Exchange (ETDEWEB)
NONE
1997-05-01
The National Energy Modeling System (NEMS) is a computer-based, energy-economy modeling system of U.S. energy markets for the midterm period. NEMS projects the production, imports, conversion, consumption, and prices of energy, subject to a variety of assumptions. The assumptions encompass macroeconomic and financial factors, world energy markets, resource availability and costs, behavioral and technological choice criteria, technology characteristics, and demographics. NEMS produces a general equilibrium solution for energy supply and demand in the U.S. energy markets on an annual basis through 2015. Baseline forecasts from NEMS are published in the Annual Energy Outlook. Analyses are also prepared in response to requests by the U.S. Congress, the DOE Office of Policy, and others. NEMS was first used for forecasts presented in the Annual Energy Outlook 1994.
NEMS integrating module documentation report
International Nuclear Information System (INIS)
1997-05-01
The National Energy Modeling System (NEMS) is a computer-based, energy-economy modeling system of U.S. energy markets for the midterm period. NEMS projects the production, imports, conversion, consumption, and prices of energy, subject to a variety of assumptions. The assumptions encompass macroeconomic and financial factors, world energy markets, resource availability and costs, behavioral and technological choice criteria, technology characteristics, and demographics. NEMS produces a general equilibrium solution for energy supply and demand in the U.S. energy markets on an annual basis through 2015. Baseline forecasts from NEMS are published in the Annual Energy Outlook. Analyses are also prepared in response to requests by the U.S. Congress, the DOE Office of Policy, and others. NEMS was first used for forecasts presented in the Annual Energy Outlook 1994
Nanotechnology: MEMS and NEMS and their applications to smart systems and devices
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
NEMS integrating module documentation report
Energy Technology Data Exchange (ETDEWEB)
1993-12-14
The National Energy Modeling System (NEMS) is a computer modeling system that produces a general equilibrium solution for energy supply and demand in the US energy markets. The model achieves a supply and demand balance in the end-use demand regions, defined as the nine Census Divisions, by solving for the prices of each energy type such that the quantities producers are willing to supply equal the quantities consumers wish to consume. The system reflects market economics, industry structure, and energy policies and regulations that influence market behavior. The NEMS Integrating Module is the central integrating component of a complex modeling system. As such, a thorough understanding of its role in the modeling process can only be achieved by placing it in the proper context with respect to the other modules. To that end, this document provides an overview of the complete NEMS model, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.
MEMS- and NEMS-based complex adaptive smart devices and systems
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.
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.
Nanorobotics for creating NEMS from 3D helical nanostructures
International Nuclear Information System (INIS)
Dong, Lixin; Zhang, Li; Bell, Dominik J; Gruetzmacher, Detlev; Nelson, Bradley J
2007-01-01
Robotic manipulation at the nanometer scale is a promising technology for structuring, characterizing and assembling nano building blocks into nanoelectromechanical systems (NEMS). Combined with recently developed nanofabrication processes, a hybrid approach to building NEMS from 3D SiGe/Si/Cr and Si/Cr nanostructures is presented. Nanosensors and nanoactuators are investigated from experimental, theoretical, and design perspectives
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
Highly tunable NEMS shallow arches
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.
Integrated NEMS and optoelectronics for sensor applications.
Energy Technology Data Exchange (ETDEWEB)
Czaplewski, David A.; Serkland, Darwin Keith; Olsson, Roy H., III; Bogart, Gregory R. (Symphony Acoustics, Rio Rancho, NM); Krishnamoorthy, Uma; Warren, Mial E.; Carr, Dustin Wade (Symphony Acoustics, Rio Rancho, NM); Okandan, Murat; Peterson, Kenneth Allen
2008-01-01
This work utilized advanced engineering in several fields to find solutions to the challenges presented by the integration of MEMS/NEMS with optoelectronics to realize a compact sensor system, comprised of a microfabricated sensor, VCSEL, and photodiode. By utilizing microfabrication techniques in the realization of the MEMS/NEMS component, the VCSEL and the photodiode, the system would be small in size and require less power than a macro-sized component. The work focused on two technologies, accelerometers and microphones, leveraged from other LDRD programs. The first technology was the nano-g accelerometer using a nanophotonic motion detection system (67023). This accelerometer had measured sensitivity of approximately 10 nano-g. The Integrated NEMS and optoelectronics LDRD supported the nano-g accelerometer LDRD by providing advanced designs for the accelerometers, packaging, and a detection scheme to encapsulate the accelerometer, furthering the testing capabilities beyond bench-top tests. A fully packaged and tested die was never realized, but significant packaging issues were addressed and many resolved. The second technology supported by this work was the ultrasensitive directional microphone arrays for military operations in urban terrain and future combat systems (93518). This application utilized a diffraction-based sensing technique with different optical component placement and a different detection scheme from the nano-g accelerometer. The Integrated NEMS LDRD supported the microphone array LDRD by providing custom designs, VCSELs, and measurement techniques to accelerometers that were fabricated from the same operational principles as the microphones, but contain proof masses for acceleration transduction. These devices were packaged at the end of the work.
Kim, Seong H; Mittal, Kash L
2012-01-01
Phenomena associated with the adhesion interaction of surfaces have been a critical aspect of micro- and nanosystem development and performance since the first MicroElectroMechanicalSystems(MEMS) were fabricated. These phenomena are ubiquitous in nature and are present in all systems, however MEMS devices are particularly sensitive to their effects owing to their small size and limited actuation force that can be generated. Extension of MEMS technology concepts to the nanoscale and development of NanoElectroMechanicalSystems(NEMS) will result in systems even more strongly influenced by surface
Optomechanical transduction applied to M/NEMS devices
Leoncino , Luca
2017-01-01
During several last years, technological advances in the field of silicon micromachininghave initiated the industrial growth of Micro/Nano Electro Mechanical Systems(M/NEMS) for fabricating sensors or actuators.In the field of NEMS with sub-micron sizes, the properties allow for targeting applicationsin biomedical or biochemical analyses. It has been demonstrated that thesenano mass (or force) sensors achieve resolutions of the order of zeptogram (10−21 g)or picoNewton, hence allowing early d...
Wikswo, J P; Prokop, A; Baudenbacher, F; Cliffel, D; Csukas, B; Velkovsky, M
2006-08-01
Systems biology, i.e. quantitative, postgenomic, postproteomic, dynamic, multiscale physiology, addresses in an integrative, quantitative manner the shockwave of genetic and proteomic information using computer models that may eventually have 10(6) dynamic variables with non-linear interactions. Historically, single biological measurements are made over minutes, suggesting the challenge of specifying 10(6) model parameters. Except for fluorescence and micro-electrode recordings, most cellular measurements have inadequate bandwidth to discern the time course of critical intracellular biochemical events. Micro-array expression profiles of thousands of genes cannot determine quantitative dynamic cellular signalling and metabolic variables. Major gaps must be bridged between the computational vision and experimental reality. The analysis of cellular signalling dynamics and control requires, first, micro- and nano-instruments that measure simultaneously multiple extracellular and intracellular variables with sufficient bandwidth; secondly, the ability to open existing internal control and signalling loops; thirdly, external BioMEMS micro-actuators that provide high bandwidth feedback and externally addressable intracellular nano-actuators; and, fourthly, real-time, closed-loop, single-cell control algorithms. The unravelling of the nested and coupled nature of cellular control loops requires simultaneous recording of multiple single-cell signatures. Externally controlled nano-actuators, needed to effect changes in the biochemical, mechanical and electrical environment both outside and inside the cell, will provide a major impetus for nanoscience.
Attosecond nanotechnology: NEMS of energy storage and nanostructural transformations in materials
Energy Technology Data Exchange (ETDEWEB)
Beznosyuk, Sergey A., E-mail: bsa1953@mail.ru; Maslova, Olga A., E-mail: maslova-o.a@mail.ru [Altai State University, Barnaul, 656049 (Russian Federation); Zhukovsky, Mark S., E-mail: zhukovsky@list.ru [Altai State Technical University, Barnaul, 656038 (Russian Federation)
2015-10-27
The attosecond technology of the nanoelectromechanical system (NEMS) energy storage as active center fast transformation of nanostructures in materials is considered. The self-organizing relaxation of the NEMS active center containing nanocube of 256-atoms limited by planes (100) in the FCC lattice matrix of 4d-transition metals (Ru, Rh, Pd) is described by the quantum NEMS-kinetics (NK) method. Typical for these metals change of the NEMS active center physicochemical characteristics during the time of relaxation is presented. There are three types of intermediate quasistationary states of the NEMS active center. Their forms are plainly distinguishable. The full relaxed NEMS active centers (Ru{sub 256}, Rh{sub 256}, Pd{sub 256}) accumulate next storage energies: E{sub Ru} = 2.27 eV/at, E{sub Rh} = 1.67 eV/at, E{sub Pd} = 3.02 eV/at.
Radiation Effects in M and NEMS
2016-03-31
electrical basis of operation of M&NEM structures? In particular, cumulative damage by non - ionizing energy loss can, in principle, alter the... Radiation Effects in M&NEMS Michael Alles, Kirill Bolotin, Alex Zettl, Brian Homeijer, Jim Davidson, Ronald Schrimpf, Robert Reed, Dan Fleetwood...understanding radiation effects on the relevant properties of the constituent materials and structures, particularly advanced 2D materials, and the
Self-Biased 215MHz Magnetoelectric NEMS Resonator for Ultra-Sensitive DC Magnetic Field Detection
Nan, Tianxiang; Hui, Yu; Rinaldi, Matteo; Sun, Nian X.
2013-06-01
High sensitivity magnetoelectric sensors with their electromechanical resonance frequencies electromechanical systems (NEMS) resonator with an electromechanical resonance frequency of 215 MHz based on an AlN/(FeGaB/Al2O3) × 10 magnetoelectric heterostructure for detecting DC magnetic fields. This magnetoelectric NEMS resonator showed a high quality factor of 735, and strong magnetoelectric coupling with a large voltage tunable sensitivity. The admittance of the magnetoelectric NEMS resonator was very sensitive to DC magnetic fields at its electromechanical resonance, which led to a new detection mechanism for ultra-sensitive self-biased RF NEMS magnetoelectric sensor with a low limit of detection of DC magnetic fields of ~300 picoTelsa. The magnetic/piezoelectric heterostructure based RF NEMS magnetoelectric sensor is compact, power efficient and readily integrated with CMOS technology, which represents a new class of ultra-sensitive magnetometers for DC and low frequency AC magnetic fields.
Technology and Greenhouse Gas Emissions: An Integrated Scenario Analysis using the LBNL-NEMS model
International Nuclear Information System (INIS)
Koomey, J.G.; Latiner, S.; Markel, R.J.; Marnay, C.; Richey, R.C.
1998-01-01
This report describes an analysis of possible technology-based scenarios for the U.S. energy system that would result in both carbon savings and net economic benefits. We use a modified version of the Energy Information Administration's National Energy Modeling System (LBNL-NEMS) to assess the potential energy, carbon, and bill savings from a portfolio of carbon saving options. This analysis is based on technology resource potentials estimated in previous bottom-up studies, but it uses the integrated LBNL-NEMS framework to assess interactions and synergies among these options. The analysis in this paper builds on previous estimates of possible ''technology paths'' to investigate four major components of an aggressive greenhouse gas reduction strategy: (1) the large scale implementation of demand-side efficiency, comparable in scale to that presented in two recent policy studies on this topic; (2) a variety of ''alternative'' electricity supply-side options, including biomass cofiring, extension of the renewable production tax credit for wind, increased industrial cogeneration, and hydropower refurbishment. (3) the economic retirement of older and less efficient existing fossil-find power plants; and (4) a permit charge of $23 per metric ton of carbon (1996 $/t),l assuming that carbon trading is implemented in the US, and that the carbon permit charge equilibrates at this level. This level of carbon permit charge, as discussed later in the report, is in the likely range for the Clinton Administration's position on this topic
Policy Report for NEMS Enhancement
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
Influence of surface effects on the pull-in instability of NEMS electrostatic switches
Energy Technology Data Exchange (ETDEWEB)
Ma, Jianming Bryan; Jiang Liying; Asokanthan, Samuel F, E-mail: lyjiang@eng.uwo.ca, E-mail: sasokanthan@eng.uwo.ca [Department of Mechanical and Materials Engineering, University of Western Ontario, London, ON, N6A 5B9 (Canada)
2010-12-17
The influence of surface effects, including residual surface stress and surface elasticity, on the pull-in instability of electrostatic switches in nanoelectromechanical systems (NEMS) is studied using an Euler-Bernoulli beam model. This model is inherently nonlinear due to the driving electrostatic force and Casimir force which become dominant at the nanoscale. Since no exact solutions are available for the resulting nonlinear differential equation, He's homotopy perturbation method (HPM) is used to get the approximate analytical solutions to the static bending of NEMS switches, which are validated by numerical solutions of the finite difference method (FDM). The results demonstrate that surface effects play a significant role in the selection of basic design parameters of NEMS switches, such as static deflection, pull-in voltage and detachment length. Surface effects on low-voltage actuation windows are also characterized for these switches. The present study is envisaged to provide useful insights for the design of NEMS switches.
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...
State estimation in networked systems
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
Impact of scaling on the performance and reliability degradation of metal-contacts in NEMS devices
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.
Early Training Estimation System
1980-08-01
first year efforts in CTES development were Cecil Wakelin, Gavin Livingstone, Ray Walsh« Peter Weddle, David Herlihy, Laurel Brown, Drs. Paul Ronco...and Society, 1980, pp. 1067-1974. David , J., Price, J. Successful communication in full scale engineering development statements of work. Air Force...1980, U.S. Army Engineering Laboratory. Shrier , S. Algorithms for system design. Proceedings of the International Conference on Cybernetics and
Fundamental issues in the manufacturing of nanoelectromechanical (NEMS) and related nanosystems
International Nuclear Information System (INIS)
Singh, R.; Alapatt, G.F.; Gupta, N.; Poole, K.F.
2011-01-01
Nanostructures in dimension below about 10 nm show interesting properties because of the effect of low-dimension physics. However, to utilize these properties in practice to commercialize NEMS and related nano-systems require an extremely precise manufacturing process. This paper briefly evaluates the fundamental issues involved in manufacturing the nano-scale systems.
Graphitization in Carbon MEMS and Carbon NEMS
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
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
VHF NEMS-CMOS piezoresistive resonators for advanced sensing applications
Arcamone, Julien; Dupré, Cécilia; Arndt, Grégory; Colinet, Eric; Hentz, Sébastien; Ollier, Eric; Duraffourg, Laurent
2014-10-01
This work reports on top-down nanoelectromechanical resonators, which are among the smallest resonators listed in the literature. To overcome the fact that their electromechanical transduction is intrinsically very challenging due to their very high frequency (100 MHz) and ultimate size (each resonator is a 1.2 μm long, 100 nm wide, 20 nm thick silicon beam with 100 nm long and 30 nm wide piezoresistive lateral nanowire gauges), they have been monolithically integrated with an advanced fully depleted SOI CMOS technology. By advantageously combining the unique benefits of nanomechanics and nanoelectronics, this hybrid NEMS-CMOS device paves the way for novel breakthrough applications, such as NEMS-based mass spectrometry or hybrid NEMS/CMOS logic, which cannot be fully implemented without this association.
Analiza poslovnega okolja Nemčije in ZDA
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...
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.
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
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
Modeling and estimating system availability
International Nuclear Information System (INIS)
Gaver, D.P.; Chu, B.B.
1976-11-01
Mathematical models to infer the availability of various types of more or less complicated systems are described. The analyses presented are probabilistic in nature and consist of three parts: a presentation of various analytic models for availability; a means of deriving approximate probability limits on system availability; and a means of statistical inference of system availability from sparse data, using a jackknife procedure. Various low-order redundant systems are used as examples, but extension to more complex systems is not difficult
Control and estimation of piecewise affine systems
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
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.
Back End of Line Nanorelays for Ultra-low Power Monolithic Integrated NEMS-CMOS Circuits
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
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...
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.
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.
Cost Estimation and Control for Flight Systems
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.
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 tree biomass and carbon estimation system
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 Mississippiâs State inventory system with bioenergy economic...
Biocontrol (Formulation of Bacillus firmus (BioNem)) of Root-knot ...
African Journals Online (AJOL)
pathogens and viruses and 6 economically important insect and mite pests attacking ... biological control have been tried with different levels of successes in tomato .... At Dire Dawa, the soil application of BioNem at the rates 200 and 400 ... hatching of M. incognita and BioNem at 2.5 % and 3% concentrations caused 100 ...
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
Attitude Estimation in Fractionated Spacecraft Cluster Systems
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.
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.
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
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.
Nanostructured 2D cellular materials in silicon by sidewall transfer lithography NEMS
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.
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.
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.
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.
View Estimation Based on Value System
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.
Nodal kinetics model upgrade in the Penn State coupled TRAC/NEM codes
International Nuclear Information System (INIS)
Beam, Tara M.; Ivanov, Kostadin N.; Baratta, Anthony J.; Finnemann, Herbert
1999-01-01
The Pennsylvania State University currently maintains and does development and verification work for its own versions of the coupled three-dimensional kinetics/thermal-hydraulics codes TRAC-PF1/NEM and TRAC-BF1/NEM. The subject of this paper is nodal model enhancements in the above mentioned codes. Because of the numerous validation studies that have been performed on almost every aspect of these codes, this upgrade is done without a major code rewrite. The upgrade consists of four steps. The first two steps are designed to improve the accuracy of the kinetics model, based on the nodal expansion method. The polynomial expansion solution of 1D transverse integrated diffusion equation is replaced with a solution, which uses a semi-analytic expansion. Further the standard parabolic polynomial representation of the transverse leakage in the above 1D equations is replaced with an improved approximation. The last two steps of the upgrade address the code efficiency by improving the solution of the time-dependent NEM equations and implementing a multi-grid solver. These four improvements are implemented into the standalone NEM kinetics code. Verification of this code was accomplished based on the original verification studies. The results show that the new methods improve the accuracy and efficiency of the code. The verification of the upgraded NEM model in the TRAC-PF1/NEM and TRAC-BF1/NEM coupled codes is underway
Impact of scaling on the performance and reliability degradation of metal-contacts in NEMS devices
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
Nanogenerators for self-powering nanosystems and piezotronics for smart MEMS/NEMS
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
Method of estimation of scanning system quality
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.
Control and Estimation of Distributed Parameter Systems
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.
Estimation and control of dynamical systems
Bensoussan, Alain
2018-01-01
This book provides a comprehensive presentation of classical and advanced topics in estimation and control of dynamical systems with an emphasis on stochastic control. Many aspects which are not easily found in a single text are provided, such as connections between control theory and mathematical finance, as well as differential games. The book is self-contained and prioritizes concepts rather than full rigor, targeting scientists who want to use control theory in their research in applied mathematics, engineering, economics, and management science. Examples and exercises are included throughout, which will be useful for PhD courses and graduate courses in general. Dr. Alain Bensoussan is Lars Magnus Ericsson Chair at UT Dallas and Director of the International Center for Decision and Risk Analysis which develops risk management research as it pertains to large-investment industrial projects that involve new technologies, applications and markets. He is also Chair Professor at City University Hong Kong.
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....
Velocity Estimate Following Air Data System Failure
National Research Council Canada - National Science Library
McLaren, Scott A
2008-01-01
.... A velocity estimator (VEST) algorithm was developed to combine the inertial and wind velocities to provide an estimate of the aircraft's current true velocity to be used for command path gain scheduling and for display in the cockpit...
Parameter estimation techniques for LTP system identification
Nofrarias Serra, Miquel
LISA Pathfinder (LPF) is the precursor mission of LISA (Laser Interferometer Space Antenna) and the first step towards gravitational waves detection in space. The main instrument onboard the mission is the LTP (LISA Technology Package) whose scientific goal is to test LISA's drag-free control loop by reaching a differential acceleration noise level between two masses in √ geodesic motion of 3 × 10-14 ms-2 / Hz in the milliHertz band. The mission is not only challenging in terms of technology readiness but also in terms of data analysis. As with any gravitational wave detector, attaining the instrument performance goals will require an extensive noise hunting campaign to measure all contributions with high accuracy. But, opposite to on-ground experiments, LTP characterisation will be only possible by setting parameters via telecommands and getting a selected amount of information through the available telemetry downlink. These two conditions, high accuracy and high reliability, are the main restrictions that the LTP data analysis must overcome. A dedicated object oriented Matlab Toolbox (LTPDA) has been set up by the LTP analysis team for this purpose. Among the different toolbox methods, an essential part for the mission are the parameter estimation tools that will be used for system identification during operations: Linear Least Squares, Non-linear Least Squares and Monte Carlo Markov Chain methods have been implemented as LTPDA methods. The data analysis team has been testing those methods with a series of mock data exercises with the following objectives: to cross-check parameter estimation methods and compare the achievable accuracy for each of them, and to develop the best strategies to describe the physics underlying a complex controlled experiment as the LTP. In this contribution we describe how these methods were tested with simulated LTP-like data to recover the parameters of the model and we report on the latest results of these mock data exercises.
AES, Automated Construction Cost Estimation System
International Nuclear Information System (INIS)
Holder, D.A.
1995-01-01
A - Description of program or function: AES (Automated Estimating System) enters and updates the detailed cost, schedule, contingency, and escalation information contained in a typical construction or other project cost estimates. It combines this information to calculate both un-escalated and escalated and cash flow values for the project. These costs can be reported at varying levels of detail. AES differs from previous versions in at least the following ways: The schedule is entered at the WBS-Participant, Activity level - multiple activities can be assigned to each WBS-Participant combination; the spending curve is defined at the schedule activity level and a weighing factor is defined which determines percentage of cost for the WBS-Participant applied to the schedule activity; Schedule by days instead of Fiscal Year/Quarter; Sales Tax is applied at the Line Item Level- a sales tax codes is selected to indicate Material, Large Single Item, or Professional Services; a 'data filter' has been added to allow user to define data the report is to be generated for. B - Method of solution: Average Escalation Rate: The average escalation for a Bill of is calculated in three steps. 1. A table of quarterly escalation factors is calculated based on the base fiscal year and quarter of the project entered in the estimate record and the annual escalation rates entered in the Standard Value File. 2. The percentage distribution of costs by quarter for the Bill of Material is calculated based on the schedule entered and the curve type. 3. The percent in each fiscal year and quarter in the distribution is multiplied by the escalation factor for the fiscal year and quarter. The sum of these results is the average escalation rate for that Bill of Material. Schedule by curve: The allocation of costs to specific time periods is dependent on three inputs, starting schedule date, ending schedule date, and the percentage of costs allocated to each quarter. Contingency Analysis: The
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)
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)
System and method for traffic signal timing estimation
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
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.
System and method for correcting attitude estimation
Josselson, Robert H. (Inventor)
2010-01-01
A system includes an angular rate sensor disposed in a vehicle for providing angular rates of the vehicle, and an instrument disposed in the vehicle for providing line-of-sight control with respect to a line-of-sight reference. The instrument includes an integrator which is configured to integrate the angular rates of the vehicle to form non-compensated attitudes. Also included is a compensator coupled across the integrator, in a feed-forward loop, for receiving the angular rates of the vehicle and outputting compensated angular rates of the vehicle. A summer combines the non-compensated attitudes and the compensated angular rates of the to vehicle to form estimated vehicle attitudes for controlling the instrument with respect to the line-of-sight reference. The compensator is configured to provide error compensation to the instrument free-of any feedback loop that uses an error signal. The compensator may include a transfer function providing a fixed gain to the received angular rates of the vehicle. The compensator may, alternatively, include a is transfer function providing a variable gain as a function of frequency to operate on the received angular rates of the vehicle.
MC EMiNEM maps the interaction landscape of the Mediator.
Directory of Open Access Journals (Sweden)
Theresa Niederberger
Full Text Available 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 proteins that have pleiotropic effects on mRNA transcription. MC EMiNEM is based on Nested Effects Models (NEMs, a class of probabilistic graphical models that extends the idea of hierarchical clustering. It combines mode-hopping Monte Carlo (MC sampling with an Expectation-Maximization (EM algorithm for NEMs to increase sensitivity compared to existing methods. A meta-analysis of four Mediator perturbation studies in Saccharomyces cerevisiae, three of which are unpublished, provides new insight into the Mediator signaling network. In addition to the known modular organization of the Mediator subunits, MC EMiNEM reveals a hierarchical ordering of its internal information flow, which is putatively transmitted through structural changes within the complex. We identify the N-terminus of Med7 as a peripheral entity, entailing only local structural changes upon perturbation, while the C-terminus of Med7 and Med19 appear to play a central role. MC EMiNEM associates Mediator subunits to most directly affected genes, which, in conjunction with gene set enrichment analysis, allows us to construct an interaction map of Mediator subunits and transcription factors.
MC EMiNEM maps the interaction landscape of the Mediator.
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 proteins that have pleiotropic effects on mRNA transcription. MC EMiNEM is based on Nested Effects Models (NEMs), a class of probabilistic graphical models that extends the idea of hierarchical clustering. It combines mode-hopping Monte Carlo (MC) sampling with an Expectation-Maximization (EM) algorithm for NEMs to increase sensitivity compared to existing methods. A meta-analysis of four Mediator perturbation studies in Saccharomyces cerevisiae, three of which are unpublished, provides new insight into the Mediator signaling network. In addition to the known modular organization of the Mediator subunits, MC EMiNEM reveals a hierarchical ordering of its internal information flow, which is putatively transmitted through structural changes within the complex. We identify the N-terminus of Med7 as a peripheral entity, entailing only local structural changes upon perturbation, while the C-terminus of Med7 and Med19 appear to play a central role. MC EMiNEM associates Mediator subunits to most directly affected genes, which, in conjunction with gene set enrichment analysis, allows us to construct an interaction map of Mediator subunits and transcription factors.
Effect of intermolecular force on the static/dynamic behaviour of M/NEM devices
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 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.
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...
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;
2016-01-01
The NOAA National Centers for Environmental Prediction (NCEP) implemented the NOAA Environmental Modeling System (NEMS) Global Forecast System (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 1deg x 1deg 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.
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.
Efficient channel estimation in massive MIMO systems - a distributed approach
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
Efecto del hidróxido de calcio sobre comunidades de nemátodos marinos
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.
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.
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
Logistic Vehicle System Replacement Cost Estimate
National Research Council Canada - National Science Library
Stinson, Margaret
1998-01-01
The Logistics Vehicle System (LVS) was originally fielded from 1985-1989. Most of the LVS fleet will reach end-of-service life in 2005, therefore the goal of the Logistics Vehicle System Replacement (LVSR...
Entsorgungswirtschaft zwischen Grünem Punkt und Dosenpfand
Johann Wackerbauer
2003-01-01
Die Zeiten der hohen Wachstumsraten in der Abfallentsorgung dürften vorbei sein. Die Nachfrage nach Entsorgungsleistungen wird stärker von der Umweltpolitik als von der allgemeinen Konjunkturentwicklung beeinflusst. Die Turbulenzen im Zusammenhang mit der Einführung der Pfandpflicht auf Einweggetränkeverpackungen und die Diskussion um die Monopolstellung der Gesellschaft Â»Der Grüne Punkt - Duales System Deutschland AGÂ« im Bereich der Entsorgung von Verkaufsverpackungen haben die Entsorgungs...
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.
Expert system for estimating LWR plutonium production
International Nuclear Information System (INIS)
Sandquist, G.M.
1988-01-01
An Artificial Intelligence-Expert System called APES (Analysis of Proliferation by Expert System) has been developed and tested to permit a non proliferation expert to evaluate the capability and capacity of a specified LWR reactor and PUREX reprocessing system for producing and separating plutonium even when system information may be limited and uncertain. APES employs an expert system coded in LISP and based upon an HP-RL (Hewlett Packard-Representational Language) Expert System Shell. The user I/O interface communicates with a blackboard and the knowledge base which contains the quantitative models required to describe the reactor, selected fission product production and radioactive decay processes, Purex reprocessing and ancillary knowledge
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.
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.
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.
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
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.
Prispevek h konceptualizaciji skupnega v biolingvističnem kapitalizmu
Directory of Open Access Journals (Sweden)
Jernej Prodnik
2011-06-01
which cannot be conceived without the social relations that constitute an inseparable part of it. The narrow or limited approach mentioned above, which is particularly characteristic of a political economy perspective on the common, may of course provide one of the keys to understanding the diversity of the common and the techniques used to exploit it in the age of bio-linguistic capitalism; however, an exclusive focus on this meaning reduces the complexity of both the concept itself and the society in which it emerges, and thus presents a risk of naturalising certain parts of the social. The first part of the text is therefore dedicated to a clarification of the wide range of faces and approaches through which it is possible to observe the common; only in the second part is this followed by a tentative attempt at a political-economic typologisation of the common. In this part, two mostly »intangible« forms of the common which have become »victims« of new processes of enclosure and privatisation are highlighted. In both cases information itself, which is characterised by a non-rival logic and low subtractivity, is privatised, creating new monopolies on knowledge which directly impact the functioning of society as a whole. These processes are enabled through extra-economic interventions, in particular through the enforcement of intellectual property, which is expanding on the global level through new rigid ownership systems (such as the TRIPS system and enabling owners to restrict access and thereby potentially accumulate »profit which is becoming rent«. The author approaches the common from the radical position of alternative modernity and posits the urgency of absolute democracy in the administration, establishment and understanding of the common.
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.
Software Intensive Systems Cost and Schedule Estimation
2013-06-13
of labor counted in or across each activity. The activity data in the SRDR is reported following the [ ISO 12207 ] processes for software development...Release Table 19 ISO /IEC 12207 Development Activities System requirements analysis System architectural design A ct iv iti es in S RD R da ta... 12207 ] ISO /IEC 12207 , International Standard on Information Technology Software Lifecycle Processes, International Organization for Standardization
Ultrasound systems for blood velocity estimation
DEFF Research Database (Denmark)
Jensen, Jørgen Arendt
1998-01-01
Medical ultrasound scanners can be used both for displayinggray-scale images of the anatomy and for visualizing theblood flow dynamically in the body.The systems can interrogate the flow at a single position in the bodyand there find the velocity distribution over time. They can also show adynamic...
Estimating hurricane hazards using a GIS system
Directory of Open Access Journals (Sweden)
A. Taramelli
2008-08-01
Full Text Available This paper develops a GIS-based integrated approach to the Multi-Hazard model method, with reference to hurricanes. This approach has three components: data integration, hazard assessment and score calculation to estimate elements at risk such as affected area and affected population. First, spatial data integration issues within a GIS environment, such as geographical scales and data models, are addressed. Particularly, the integration of physical parameters and population data is achieved linking remotely sensed data with a high resolution population distribution in GIS. In order to assess the number of affected people, involving heterogeneous data sources, the selection of spatial analysis units is basic. Second, specific multi-hazard tasks, such as hazard behaviour simulation and elements at risk assessment, are composed in order to understand complex hazard and provide support for decision making. Finally, the paper concludes that the integrated approach herein presented can be used to assist emergency management of hurricane consequences, in theory and in practice.
Mídia regional: nem menor, nem maior, um elemento integrante do sistema midiático do Brasil
Directory of Open Access Journals (Sweden)
Pâmela Araujo Pinto
2013-12-01
Full Text Available This article ranks the traditional readings of the regional media in asymmetric relational perspective and super local in order to propose a repositioning that includes the role of regional media in the country.The first perspective relates this media in reference to national groups / vehicles (in capitals São Paulo, Rio de Janeiro, and Brasília. The second perspective overestimates, singly, vehicles or groups located outside this axis. They are insufficient to situate medias produced in several regions as heterogeneous regionals subsystems that are part of brazilian media system. Pursue to understand the regional dynamics from suprastate, state and substate levels, exposing their interactions, internal and external, and the diversity of the Brazilian media in its regional dimension.
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.
Virtual Estimator for Piecewise Linear Systems Based on Observability Analysis
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
MC EMiNEM maps the interaction landscape of the Mediator
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...
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
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.
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.
Introduction to State Estimation of High-Rate System Dynamics.
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.
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.
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.
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...
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.
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
Estimating Dynamical Systems: Derivative Estimation Hints from Sir Ronald A. Fisher
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…
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
A Web-Based System for Bayesian Benchmark Dose Estimation.
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.
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)
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...
48 CFR 252.215-7002 - Cost estimating system requirements.
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...
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.
Alternative Transportation System Demand Estimation for Federal Land Management Agencies.
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...
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
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.
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.)
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.
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....
Estimation of Faults in DC Electrical Power System
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.
Novel Material Integration for Reliable and Energy-Efficient NEM Relay Technology
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.
Dynamic state estimation assisted power system monitoring and protection
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
Power system frequency estimation based on an orthogonal decomposition method
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.
Resistencia antihelmíntica en los Nemátodos Gastrointestinales del bovino
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...
Tritium system test assembly control system cost estimate
International Nuclear Information System (INIS)
Stutz, R.A.
1979-01-01
The principal objectives of the Tritium Systems Test Assembly (TSTA), which includes the development, demonstration and interfacing of technologies related to the deuterium--tritium fuel cycle for fusion reactor systems, are concisely stated. The various integrated subsystems comprising TSTA and their functions are discussed. Each of the four major subdivisions of TSTA, including the main process system, the environmental and safety systems, supporting systems and the physical plant are briefly discussed. An overview of the Master Data Acquisition and Control System, which will control all functional operation of TSTA, is provided
Channel estimation for physical layer network coding systems
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
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
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
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.
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...
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...
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...
An expert system to estimate SNM production at LWR systems
International Nuclear Information System (INIS)
Sandquist, G.M.; Allison, J.L.; Rogers, V.C.
1988-01-01
An artificial intelligence expert system, analysis of proliferation by expert system (APES), has been developed and tested to permit a nonexpert to quickly evaluate the capabilities and capacities of a reactor and reprocessing system for producing and separating plutonium [special nuclear material (SNM)] even when system information may be limited and uncertain. The present analysis domain of APES is directed at light water reactors and Purex reprocessing, but extension of the domain is planned
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...
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...
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.
Efficient channel estimation in massive MIMO systems - a distributed approach
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.
Estimation and Control for Linear Systems with Additive Cauchy Noise
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
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.
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
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.
Fuzzy filter for state estimation of a glucoregulatory system.
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.
Nanogenerators for self-powering nanosystems and piezotronics for smart MEMS/NEMS
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.
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...
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....
Time-to-impact estimation in passive missile warning systems
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.
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.
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.
Frequency offset estimation in OFDM systems using Bayesian filtering
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.
CFO and channel estimation for MISO-OFDM systems
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.
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.
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.
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.
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.
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
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)
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
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...
Method of Competence System Estimation for the Ukrainian NPP Personnel
International Nuclear Information System (INIS)
Gushchyna, Maryna
2014-01-01
Conclusions: • During the research the scale allowing assessing the influence of personnel competences and infrastructure on the enterprise safety culture level was developed. • The scale was approved on the statistical data characterizing industrial traumatism on the enterprises of atomic power and atomic industrial complex. • The proposed scale allows receiving system estimation of the safety culture level
Case Study: Zutphen : Estimates of levee system reliability
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.
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.
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.)
System Level Modelling and Performance Estimation of Embedded Systems
DEFF Research Database (Denmark)
Tranberg-Hansen, Anders Sejer
The advances seen in the semiconductor industry within the last decade have brought the possibility of integrating evermore functionality onto a single chip forming functionally highly advanced embedded systems. These integration possibilities also imply that as the design complexity increases, so...... does the design time and eort. This challenge is widely recognized throughout academia and the industry and in order to address this, novel frameworks and methods, which will automate design steps as well as raise the level of abstraction used to design systems, are being called upon. To support...... is carried out in collaboration with the Danish company and DaNES partner, Bang & Olufsen ICEpower. Bang & Olufsen ICEpower provides industrial case studies which will allow the proposed modelling framework to be exercised and assessed in terms of ease of use, production speed, accuracy and efficiency...
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
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...
Modelling, Estimation and Control of Networked Complex Systems
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...
State estimation for networked control systems using fixed data rates
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.
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.
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.
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.
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.
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.
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.
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.
Artificial Neural Network for Location Estimation in Wireless Communication Systems
Directory of Open Access Journals (Sweden)
Chien-Sheng Chen
2012-03-01
Full Text Available In a wireless communication system, wireless location is the technique used to estimate the location of a mobile station (MS. To enhance the accuracy of MS location prediction, we propose a novel algorithm that utilizes time of arrival (TOA measurements and the angle of arrival (AOA information to locate MS when three base stations (BSs are available. Artificial neural networks (ANN are widely used techniques in various areas to overcome the problem of exclusive and nonlinear relationships. When the MS is heard by only three BSs, the proposed algorithm utilizes the intersections of three TOA circles (and the AOA line, based on various neural networks, to estimate the MS location in non-line-of-sight (NLOS environments. Simulations were conducted to evaluate the performance of the algorithm for different NLOS error distributions. The numerical analysis and simulation results show that the proposed algorithms can obtain more precise location estimation under different NLOS environments.
Artificial neural network for location estimation in wireless communication systems.
Chen, Chien-Sheng
2012-01-01
In a wireless communication system, wireless location is the technique used to estimate the location of a mobile station (MS). To enhance the accuracy of MS location prediction, we propose a novel algorithm that utilizes time of arrival (TOA) measurements and the angle of arrival (AOA) information to locate MS when three base stations (BSs) are available. Artificial neural networks (ANN) are widely used techniques in various areas to overcome the problem of exclusive and nonlinear relationships. When the MS is heard by only three BSs, the proposed algorithm utilizes the intersections of three TOA circles (and the AOA line), based on various neural networks, to estimate the MS location in non-line-of-sight (NLOS) environments. Simulations were conducted to evaluate the performance of the algorithm for different NLOS error distributions. The numerical analysis and simulation results show that the proposed algorithms can obtain more precise location estimation under different NLOS environments.
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.
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.
The estimation of energy efficiency for hybrid refrigeration system
International Nuclear Information System (INIS)
Gazda, Wiesław; Kozioł, Joachim
2013-01-01
Highlights: ► We present the experimental setup and the model of the hybrid cooling system. ► We examine impact of the operating parameters of the hybrid cooling system on the energy efficiency indicators. ► A comparison of the final and the primary energy use for a combination of the cooling systems is carried out. ► We explain the relationship between the COP and PER values for the analysed cooling systems. -- Abstract: The concept of the air blast-cryogenic freezing method (ABCF) is based on an innovative hybrid refrigeration system with one common cooling space. The hybrid cooling system consists of a vapor compression refrigeration system and a cryogenic refrigeration system. The prototype experimental setup for this method on the laboratory scale is discussed. The application of the results of experimental investigations and the theoretical–empirical model makes it possible to calculate the cooling capacity as well as the final and primary energy use in the hybrid system. The energetic analysis has been carried out for the operating modes of the refrigerating systems for the required temperatures inside the cooling chamber of −5 °C, −10 °C and −15 °C. For the estimation of the energy efficiency the coefficient of performance COP and the primary energy ratio PER for the hybrid refrigeration system are proposed. A comparison of these coefficients for the vapor compression refrigeration and the cryogenic refrigeration system has also been presented.
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
System health monitoring using multiple-model adaptive estimation techniques
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
BOES: Building Occupancy Estimation System using sparse ambient vibration monitoring
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.
Estimating the decomposition of predictive information in multivariate systems
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.
Fast skin dose estimation system for interventional radiology.
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.
Estimating cell capacity for multi-cell electrical energy system
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
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 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
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.
SNR Estimation in Linear Systems with Gaussian Matrices
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
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.
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
Estimation of Boreal Forest Biomass Using Spaceborne SAR Systems
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.
Micro, nanosystems and systems on chips modeling, control, and estimation
Voda, Alina
2013-01-01
Micro and nanosystems represent a major scientific and technological challenge, with actual and potential applications in almost all fields of the human activity. The aim of the present book is to present how concepts from dynamical control systems (modeling, estimation, observation, identification, feedback control) can be adapted and applied to the development of original very small-scale systems and of their human interfaces. The application fields presented here come from micro and nanorobotics, biochips, near-field microscopy (AFM and STM) and nanosystems networks. Alina Voda has drawn co
Methodologies for Quantitative Systems Pharmacology (QSP) Models: Design and Estimation.
Ribba, B; Grimm, H P; Agoram, B; Davies, M R; Gadkar, K; Niederer, S; van Riel, N; Timmis, J; van der Graaf, P H
2017-08-01
With the increased interest in the application of quantitative systems pharmacology (QSP) models within medicine research and development, there is an increasing need to formalize model development and verification aspects. In February 2016, a workshop was held at Roche Pharma Research and Early Development to focus discussions on two critical methodological aspects of QSP model development: optimal structural granularity and parameter estimation. We here report in a perspective article a summary of presentations and discussions. © 2017 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.
Parameter estimation in space systems using recurrent neural networks
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.
Estimating yield gaps at the cropping system level.
Guilpart, Nicolas; Grassini, Patricio; Sadras, Victor O; Timsina, Jagadish; Cassman, Kenneth G
2017-05-01
Yield gap analyses of individual crops have been used to estimate opportunities for increasing crop production at local to global scales, thus providing information crucial to food security. However, increases in crop production can also be achieved by improving cropping system yield through modification of spatial and temporal arrangement of individual crops. In this paper we define the cropping system yield potential as the output from the combination of crops that gives the highest energy yield per unit of land and time, and the cropping system yield gap as the difference between actual energy yield of an existing cropping system and the cropping system yield potential. Then, we provide a framework to identify alternative cropping systems which can be evaluated against the current ones. A proof-of-concept is provided with irrigated rice-maize systems at four locations in Bangladesh that represent a range of climatic conditions in that country. The proposed framework identified (i) realistic alternative cropping systems at each location, and (ii) two locations where expected improvements in crop production from changes in cropping intensity (number of crops per year) were 43% to 64% higher than from improving the management of individual crops within the current cropping systems. The proposed framework provides a tool to help assess food production capacity of new systems ( e.g. with increased cropping intensity) arising from climate change, and assess resource requirements (water and N) and associated environmental footprint per unit of land and production of these new systems. By expanding yield gap analysis from individual crops to the cropping system level and applying it to new systems, this framework could also be helpful to bridge the gap between yield gap analysis and cropping/farming system design.
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
State Estimation for Sensor Monitoring System with Uncertainty and Disturbance
Directory of Open Access Journals (Sweden)
Jianhong Sun
2014-10-01
Full Text Available This paper considers the state estimation problem for the sensor monitoring system which contains system uncertainty and nonlinear disturbance. In the sensor monitoring system, states of each inner sensor node usually contains system uncertainty, and external noise often works as nonlinear item. Besides, information transmission in the system is also time consuming. All mentioned above may arouse in unstable of the monitoring system. In this case, states of sensors could be wrongly sampled. Under this circumstance, a proper mathematical model is proposed and by the use of Lipschitz condition, the nonlinear item is transformed to linear one. In addition, we suppose that all sensor nodes are distributed arranged, no interface occurs with each other. By establishing proper Lyapunov– Krasovskii functional, sufficient conditions are acquired by solving linear matrix inequality to make the error augmented system stable, and the gains of observers are also derived. Finally, an illustrated example is given to show that system observed value tracks system states well, which fully demonstrate the effectiveness of our result.
Development of dose rate estimation system for FBR maintenance
Energy Technology Data Exchange (ETDEWEB)
Iizawa, Katsuyuki [Japan Nuclear Cycle Development Inst., Tsuruga Head Office, International Cooperation and Technology Development Center, Tsuruga, Fukui (Japan); Takeuchi, Jun; Yoshikawa, Satoru [Hitachi Engineering Company, Ltd., Hitachi, Ibaraki (Japan); Urushihara, Hiroshi [Ibaraki Hitachi Information Service Co., Ltd., Omika, Ibaraki (Japan)
2001-09-01
During maintenance activities on the primary sodium cooling system by an FBR Personnel radiation exposure arises mainly from the presence of radioactive corrosion products (CP). A CP behavior analysis code, PSYCHE, and a radiation shielding calculation code, QAD-CG, have been developed and applied to investigate the possible reduction of radiation exposure of workers. In order to make these evaluation methods more accessible to plant engineers, the user interface of the codes has been improved and an integrated system, including visualization of the calculated gamma-ray radiation dose-rate map, has been developed. The system has been verified by evaluating the distribution of the radiation dose-rate within the Monju primary heat transport system cells from the estimated saturated CP deposition and distribution which would be present following about 20 cycles of full power operation. (author)
Development of dose rate estimation system for FBR maintenance
International Nuclear Information System (INIS)
Iizawa, Katsuyuki; Takeuchi, Jun; Yoshikawa, Satoru; Urushihara, Hiroshi
2001-01-01
During maintenance activities on the primary sodium cooling system by an FBR Personnel radiation exposure arises mainly from the presence of radioactive corrosion products (CP). A CP behavior analysis code, PSYCHE, and a radiation shielding calculation code, QAD-CG, have been developed and applied to investigate the possible reduction of radiation exposure of workers. In order to make these evaluation methods more accessible to plant engineers, the user interface of the codes has been improved and an integrated system, including visualization of the calculated gamma-ray radiation dose-rate map, has been developed. The system has been verified by evaluating the distribution of the radiation dose-rate within the Monju primary heat transport system cells from the estimated saturated CP deposition and distribution which would be present following about 20 cycles of full power operation. (author)
Estimation of temperature in micromaser-type systems
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.
Direct process estimation from tomographic data using artificial neural systems
Mohamad-Saleh, Junita; Hoyle, Brian S.; Podd, Frank J.; Spink, D. M.
2001-07-01
The paper deals with the goal of component fraction estimation in multicomponent flows, a critical measurement in many processes. Electrical capacitance tomography (ECT) is a well-researched sensing technique for this task, due to its low-cost, non-intrusion, and fast response. However, typical systems, which include practicable real-time reconstruction algorithms, give inaccurate results, and existing approaches to direct component fraction measurement are flow-regime dependent. In the investigation described, an artificial neural network approach is used to directly estimate the component fractions in gas-oil, gas-water, and gas-oil-water flows from ECT measurements. A 2D finite- element electric field model of a 12-electrode ECT sensor is used to simulate ECT measurements of various flow conditions. The raw measurements are reduced to a mutually independent set using principal components analysis and used with their corresponding component fractions to train multilayer feed-forward neural networks (MLFFNNs). The trained MLFFNNs are tested with patterns consisting of unlearned ECT simulated and plant measurements. Results included in the paper have a mean absolute error of less than 1% for the estimation of various multicomponent fractions of the permittivity distribution. They are also shown to give improved component fraction estimation compared to a well known direct ECT method.
Reconstruction of financial networks for robust estimation of systemic risk
International Nuclear Information System (INIS)
Mastromatteo, Iacopo; Zarinelli, Elia; Marsili, Matteo
2012-01-01
In this paper we estimate the propagation of liquidity shocks through interbank markets when the information about the underlying credit network is incomplete. We show that techniques such as maximum entropy currently used to reconstruct credit networks severely underestimate the risk of contagion by assuming a trivial (fully connected) topology, a type of network structure which can be very different from the one empirically observed. We propose an efficient message-passing algorithm to explore the space of possible network structures and show that a correct estimation of the network degree of connectedness leads to more reliable estimations for systemic risk. Such an algorithm is also able to produce maximally fragile structures, providing a practical upper bound for the risk of contagion when the actual network structure is unknown. We test our algorithm on ensembles of synthetic data encoding some features of real financial networks (sparsity and heterogeneity), finding that more accurate estimations of risk can be achieved. Finally we find that this algorithm can be used to control the amount of information that regulators need to require from banks in order to sufficiently constrain the reconstruction of financial networks
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.
Reconstruction of financial networks for robust estimation of systemic risk
Mastromatteo, Iacopo; Zarinelli, Elia; Marsili, Matteo
2012-03-01
In this paper we estimate the propagation of liquidity shocks through interbank markets when the information about the underlying credit network is incomplete. We show that techniques such as maximum entropy currently used to reconstruct credit networks severely underestimate the risk of contagion by assuming a trivial (fully connected) topology, a type of network structure which can be very different from the one empirically observed. We propose an efficient message-passing algorithm to explore the space of possible network structures and show that a correct estimation of the network degree of connectedness leads to more reliable estimations for systemic risk. Such an algorithm is also able to produce maximally fragile structures, providing a practical upper bound for the risk of contagion when the actual network structure is unknown. We test our algorithm on ensembles of synthetic data encoding some features of real financial networks (sparsity and heterogeneity), finding that more accurate estimations of risk can be achieved. Finally we find that this algorithm can be used to control the amount of information that regulators need to require from banks in order to sufficiently constrain the reconstruction of financial networks.
Stochastic linear hybrid systems: Modeling, estimation, and application
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
User's guide to the Reliability Estimation System Testbed (REST)
Nicol, David M.; Palumbo, Daniel L.; Rifkin, Adam
1992-01-01
The Reliability Estimation System Testbed is an X-window based reliability modeling tool that was created to explore the use of the Reliability Modeling Language (RML). RML was defined to support several reliability analysis techniques including modularization, graphical representation, Failure Mode Effects Simulation (FMES), and parallel processing. These techniques are most useful in modeling large systems. Using modularization, an analyst can create reliability models for individual system components. The modules can be tested separately and then combined to compute the total system reliability. Because a one-to-one relationship can be established between system components and the reliability modules, a graphical user interface may be used to describe the system model. RML was designed to permit message passing between modules. This feature enables reliability modeling based on a run time simulation of the system wide effects of a component's failure modes. The use of failure modes effects simulation enhances the analyst's ability to correctly express system behavior when using the modularization approach to reliability modeling. To alleviate the computation bottleneck often found in large reliability models, REST was designed to take advantage of parallel processing on hypercube processors.
Estimating rare events in biochemical systems using conditional sampling
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.
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
Observer-Based Fault Estimation and Accomodation for Dynamic Systems
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...
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
Measurement Model Nonlinearity in Estimation of Dynamical Systems
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.
Cost estimation of HVDC transmission system of Bangka's NPP candidates
Liun, Edwaren; Suparman
2014-09-01
Regarding nuclear power plant development in Bangka Island, it can be estimated that produced power will be oversupply for the Bangka Island and needs to transmit to Sumatra or Java Island. The distance between the regions or islands causing considerable loss of power in transmission by alternating current, and a wide range of technical and economical issues. The objective of this paper addresses to economics analysis of direct current transmission system to overcome those technical problem. Direct current transmission has a stable characteristic, so that the power delivery from Bangka to Sumatra or Java in a large scale efficiently and reliably can be done. HVDC system costs depend on the power capacity applied to the system and length of the transmission line in addition to other variables that may be different.
Parameter and state estimation in nonlinear dynamical systems
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
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
Norm estimates of complex symmetric operators applied to quantum systems
International Nuclear Information System (INIS)
Prodan, Emil; Garcia, Stephan R; Putinar, Mihai
2006-01-01
This paper communicates recent results in the theory of complex symmetric operators and shows, through two non-trivial examples, their potential usefulness in the study of Schroedinger operators. In particular, we propose a formula for computing the norm of a compact complex symmetric operator. This observation is applied to two concrete problems related to quantum mechanical systems. First, we give sharp estimates on the exponential decay of the resolvent and the single-particle density matrix for Schroedinger operators with spectral gaps. Second, we provide new ways of evaluating the resolvent norm for Schroedinger operators appearing in the complex scaling theory of resonances
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.
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..
Estimating marginal CO2 emissions rates for national electricity systems
International Nuclear Information System (INIS)
Hawkes, A.D.
2010-01-01
The carbon dioxide (CO 2 ) emissions reduction afforded by a demand-side intervention in the electricity system is typically assessed by means of an assumed grid emissions rate, which measures the CO 2 intensity of electricity not used as a result of the intervention. This emissions rate is called the 'marginal emissions factor' (MEF). Accurate estimation of MEFs is crucial for performance assessment because their application leads to decisions regarding the relative merits of CO 2 reduction strategies. This article contributes to formulating the principles by which MEFs are estimated, highlighting the strengths and weaknesses in existing approaches, and presenting an alternative based on the observed behaviour of power stations. The case of Great Britain is considered, demonstrating an MEF of 0.69 kgCO 2 /kW h for 2002-2009, with error bars at +/-10%. This value could reduce to 0.6 kgCO 2 /kW h over the next decade under planned changes to the underlying generation mix, and could further reduce to approximately 0.51 kgCO 2 /kW h before 2025 if all power stations commissioned pre-1970 are replaced by their modern counterparts. Given that these rates are higher than commonly applied system-average or assumed 'long term marginal' emissions rates, it is concluded that maintenance of an improved understanding of MEFs is valuable to better inform policy decisions.
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...
Development of LLW and VLLW disposal business cost estimation system
International Nuclear Information System (INIS)
Koibuchi, Hiroko; Ishiguro, Hideharu; Matsuda, Kenji
2004-01-01
In order to undertake the LLW and VLLW disposal business, various examinations are carried out in RANDEC. Since it is important in undertaking this business to secure funds, a disposal cost must be calculated by way of trial. However, at present, there are many unknown factors such as the amount of wastes, a disposal schedule, the location of a disposal site, and so on, and the cost cannot be determined. Meanwhile, the cost depends on complicated relations among these factors. Then, a 'LLW and VLLW disposal business cost estimation system' has been developed to calculate the disposal cost easily. This system can calculate an annual balance of payments by using a construction and operation cost of disposal facilities, considering economic parameters of tax, inflation rate, interest rate and so on. And the system can calculate internal reserves to assign to next-stage upkeep of the disposal facilities after the disposal operation. A model of disposal site was designed based on assumption of some preconditions and a study was carried out to make a trial calculation by using the system. Moreover, it will be required to reduce construction cost by rationalizing the facility and to make flat an annual business spending by examining the business schedule. (author)
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.
METAHEURISTIC OPTIMIZATION METHODS FOR PARAMETERS ESTIMATION OF DYNAMIC SYSTEMS
Directory of Open Access Journals (Sweden)
V. Panteleev Andrei
2017-01-01
Full Text Available The article considers the usage of metaheuristic methods of constrained global optimization: “Big Bang - Big Crunch”, “Fireworks Algorithm”, “Grenade Explosion Method” in parameters of dynamic systems estimation, described with algebraic-differential equations. Parameters estimation is based upon the observation results from mathematical model behavior. Their values are derived after criterion minimization, which describes the total squared error of state vector coordinates from the deduced ones with precise values observation at different periods of time. Paral- lelepiped type restriction is imposed on the parameters values. Used for solving problems, metaheuristic methods of constrained global extremum don’t guarantee the result, but allow to get a solution of a rather good quality in accepta- ble amount of time. The algorithm of using metaheuristic methods is given. Alongside with the obvious methods for solving algebraic-differential equation systems, it is convenient to use implicit methods for solving ordinary differen- tial equation systems. Two ways of solving the problem of parameters evaluation are given, those parameters differ in their mathematical model. In the first example, a linear mathematical model describes the chemical action parameters change, and in the second one, a nonlinear mathematical model describes predator-prey dynamics, which characterize the changes in both kinds’ population. For each of the observed examples there are calculation results from all the three methods of optimization, there are also some recommendations for how to choose methods parameters. The obtained numerical results have demonstrated the efficiency of the proposed approach. The deduced parameters ap- proximate points slightly differ from the best known solutions, which were deduced differently. To refine the results one should apply hybrid schemes that combine classical methods of optimization of zero, first and second orders and
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.)
State estimation of chemical engineering systems tending to multiple solutions
Directory of Open Access Journals (Sweden)
N. P. G. Salau
2014-09-01
Full Text Available A well-evaluated state covariance matrix avoids error propagation due to divergence issues and, thereby, it is crucial for a successful state estimator design. In this paper we investigate the performance of the state covariance matrices used in three unconstrained Extended Kalman Filter (EKF formulations and one constrained EKF formulation (CEKF. As benchmark case studies we have chosen: a a batch chemical reactor with reversible reactions whose system model and measurement are such that multiple states satisfy the equilibrium condition and b a CSTR with exothermic irreversible reactions and cooling jacket energy balance whose nonlinear behavior includes multiple steady-states and limit cycles. The results have shown that CEKF is in general the best choice of EKF formulations (even if they are constrained with an ad hoc clipping strategy which avoids undesired states for such case studies. Contrary to a clipped EKF formulation, CEKF incorporates constraints into an optimization problem, which minimizes the noise in a least square sense preventing a bad noise distribution. It is also shown that, although the Moving Horizon Estimation (MHE provides greater robustness to a poor guess of the initial state, converging in less steps to the actual states, it is not justified for our examples due to the high additional computational effort.
Dynamic systems models new methods of parameter and state estimation
2016-01-01
This monograph is an exposition of a novel method for solving inverse problems, a method of parameter estimation for time series data collected from simulations of real experiments. These time series might be generated by measuring the dynamics of aircraft in flight, by the function of a hidden Markov model used in bioinformatics or speech recognition or when analyzing the dynamics of asset pricing provided by the nonlinear models of financial mathematics. Dynamic Systems Models demonstrates the use of algorithms based on polynomial approximation which have weaker requirements than already-popular iterative methods. Specifically, they do not require a first approximation of a root vector and they allow non-differentiable elements in the vector functions being approximated. The text covers all the points necessary for the understanding and use of polynomial approximation from the mathematical fundamentals, through algorithm development to the application of the method in, for instance, aeroplane flight dynamic...
Performance Estimation for Two-Dimensional Brownian Rotary Ratchet Systems
Tutu, Hiroki; Horita, Takehiko; Ouchi, Katsuya
2015-04-01
Within the context of the Brownian ratchet model, a molecular rotary system that can perform unidirectional rotations induced by linearly polarized ac fields and produce positive work under loads was studied. The model is based on the Langevin equation for a particle in a two-dimensional (2D) three-tooth ratchet potential of threefold symmetry. The performance of the system is characterized by the coercive torque, i.e., the strength of the load competing with the torque induced by the ac driving field, and the energy efficiency in force conversion from the driving field to the torque. We propose a master equation for coarse-grained states, which takes into account the boundary motion between states, and develop a kinetic description to estimate the mean angular momentum (MAM) and powers relevant to the energy balance equation. The framework of analysis incorporates several 2D characteristics and is applicable to a wide class of models of smooth 2D ratchet potential. We confirm that the obtained expressions for MAM, power, and efficiency of the model can enable us to predict qualitative behaviors. We also discuss the usefulness of the torque/power relationship for experimental analyses, and propose a characteristic for 2D ratchet systems.
Estimating Spoken Dialog System Quality with User Models
Engelbrecht, Klaus-Peter
2013-01-01
Spoken dialog systems have the potential to offer highly intuitive user interfaces, as they allow systems to be controlled using natural language. However, the complexity inherent in natural language dialogs means that careful testing of the system must be carried out from the very beginning of the design process. This book examines how user models can be used to support such early evaluations in two ways: by running simulations of dialogs, and by estimating the quality judgments of users. First, a design environment supporting the creation of dialog flows, the simulation of dialogs, and the analysis of the simulated data is proposed. How the quality of user simulations may be quantified with respect to their suitability for both formative and summative evaluation is then discussed. The remainder of the book is dedicated to the problem of predicting quality judgments of users based on interaction data. New modeling approaches are presented, which process the dialogs as sequences, and which allow knowl...
Periodic orbits of hybrid systems and parameter estimation via AD
International Nuclear Information System (INIS)
Guckenheimer, John; Phipps, Eric Todd; Casey, Richard
2004-01-01
Rhythmic, periodic processes are ubiquitous in biological systems; for example, the heart beat, walking, circadian rhythms and the menstrual cycle. Modeling these processes with high fidelity as periodic orbits of dynamical systems is challenging because: (1) (most) nonlinear differential equations can only be solved numerically; (2) accurate computation requires solving boundary value problems; (3) many problems and solutions are only piecewise smooth; (4) many problems require solving differential-algebraic equations; (5) sensitivity information for parameter dependence of solutions requires solving variational equations; and (6) truncation errors in numerical integration degrade performance of optimization methods for parameter estimation. In addition, mathematical models of biological processes frequently contain many poorly-known parameters, and the problems associated with this impedes the construction of detailed, high-fidelity models. Modelers are often faced with the difficult problem of using simulations of a nonlinear model, with complex dynamics and many parameters, to match experimental data. Improved computational tools for exploring parameter space and fitting models to data are clearly needed. This paper describes techniques for computing periodic orbits in systems of hybrid differential-algebraic equations and parameter estimation methods for fitting these orbits to data. These techniques make extensive use of automatic differentiation to accurately and efficiently evaluate derivatives for time integration, parameter sensitivities, root finding and optimization. The boundary value problem representing a periodic orbit in a hybrid system of differential algebraic equations is discretized via multiple-shooting using a high-degree Taylor series integration method (GM00, Phi03). Numerical solutions to the shooting equations are then estimated by a Newton process yielding an approximate periodic orbit. A metric is defined for computing the distance
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.
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...
Estimating Biofuel Feedstock Water Footprints Using System Dynamics
Energy Technology Data Exchange (ETDEWEB)
Inman, Daniel; Warner, Ethan; Stright, Dana; Macknick, Jordan; Peck, Corey
2016-07-01
Increased biofuel production has prompted concerns about the environmental tradeoffs of biofuels compared to petroleum-based fuels. Biofuel production in general, and feedstock production in particular, is under increased scrutiny. Water footprinting (measuring direct and indirect water use) has been proposed as one measure to evaluate water use in the context of concerns about depleting rural water supplies through activities such as irrigation for large-scale agriculture. Water footprinting literature has often been limited in one or more key aspects: complete assessment across multiple water stocks (e.g., vadose zone, surface, and ground water stocks), geographical resolution of data, consistent representation of many feedstocks, and flexibility to perform scenario analysis. We developed a model called BioSpatial H2O using a system dynamics modeling and database framework. BioSpatial H2O could be used to consistently evaluate the complete water footprints of multiple biomass feedstocks at high geospatial resolutions. BioSpatial H2O has the flexibility to perform simultaneous scenario analysis of current and potential future crops under alternative yield and climate conditions. In this proof-of-concept paper, we modeled corn grain (Zea mays L.) and soybeans (Glycine max) under current conditions as illustrative results. BioSpatial H2O links to a unique database that houses annual spatially explicit climate, soil, and plant physiological data. Parameters from the database are used as inputs to our system dynamics model for estimating annual crop water requirements using daily time steps. Based on our review of the literature, estimated green water footprints are comparable to other modeled results, suggesting that BioSpatial H2O is computationally sound for future scenario analysis. Our modeling framework builds on previous water use analyses to provide a platform for scenario-based assessment. BioSpatial H2O's system dynamics is a flexible and user
Impulse noise estimation and removal for OFDM systems
Al-Naffouri, Tareq Y.
2014-03-01
Orthogonal Frequency Division Multiplexing (OFDM) is a modulation scheme that is widely used in wired and wireless communication systems. While OFDM is ideally suited to deal with frequency selective channels and AWGN, its performance may be dramatically impacted by the presence of impulse noise. In fact, very strong noise impulses in the time domain might result in the erasure of whole OFDM blocks of symbols at the receiver. Impulse noise can be mitigated by considering it as a sparse signal in time, and using recently developed algorithms for sparse signal reconstruction. We propose an algorithm that utilizes the guard band subcarriers for the impulse noise estimation and cancellation. Instead of relying on ℓ1 minimization as done in some popular general-purpose compressive sensing schemes, the proposed method jointly exploits the specific structure of this problem and the available a priori information for sparse signal recovery. The computational complexity of the proposed algorithm is very competitive with respect to sparse signal reconstruction schemes based on ℓ1 minimization. The proposed method is compared with respect to other state-of-the-art methods in terms of achievable rates for an OFDM system with impulse noise and AWGN. © 2014 IEEE.
Estimating MCC System Dryness Index using the Vineyard Water Indicator
Directory of Open Access Journals (Sweden)
Conceição Marco Antônio Fonseca
2016-01-01
Full Text Available The Dryness Index (DI is one of the three Geoviticulture Multicriteria Climatic Classification System (MCC System indices and its calculation is based on a soil water balance approach. However, other climatic indices can be used for the same purpose. One of them is the Vineyard Water Indicator (VWI that represents the ratio between the total rainfall and the vineyard water requirement during the productive period of the culture. When compared to DI, the VWI presents a simpler calculation methodology. Therefore, the aim of the present study was to establish a model to estimate DI based on VWI values. Climate data of 80 winegrowing regions in 18 countries were used. Four regression models were evaluated: linear, quadratic, logarithmic and the Mitscherlich model. Real and simulated data were compared using the confidence coefficient (c that corresponds to the product of the correlation coefficient (r by the exactness coefficient (d. The best fit was obtained employing the quadratic model and DI can be calculated using the following equation: DI = −363.84 VWI2+ 834.47 VWI – 257.17 (R2 = 0.93, for VHI <0.905. For VHI values equal to or greater than 0.905, DI is constant and equal to 200.
Estimating inhalation hazards for space nuclear power systems
International Nuclear Information System (INIS)
Hoover, M.D.; Cuddihy, R.G.; Seiler, F.Z.
1989-01-01
Minimizing inhalation hazards is a major consideration in the design, development, transportation, handling, testing, storage, launch, use, and ultimate disposition of nuclear space power systems (NSPSs). An accidental dispersion of 238 Pu is of concern for missions involving the radioisotope thermoelectric generators (RTGs) or lightweight radioisotope heater units. Materials of concern for missions involving a nuclear reactor might include other radionuclides, such as uranium, or chemically toxic materials, such as beryllium or lithium. This paper provides an overview of some of the current approaches and uncertainties associated with estimating inhalation hazards from potential NSPS accidents. The question of whether inhalation risks can be acceptable for nuclear space power systems is still open and active. The inherently low toxicity of the uranium fuel of a space nuclear reactor is a desirable feature of that option. The extensive engineering and testing that have contributed to the current generation of plutonium RTGs provide a measure of confidence that dispersion of the RTG fuel would be unlikely in an accident. The use of nuclear reactors or RTGs in space, however, requires society to assume a risk (albeit low) for dispersion of the fuel material. It can be argued that any additional risks from the use of nuclear power in space are far less than the risks we face daily
Impulse noise estimation and removal for OFDM systems
Al-Naffouri, Tareq Y.; Quadeer, Ahmed Abdul; Caire, Giuseppe
2014-01-01
Orthogonal Frequency Division Multiplexing (OFDM) is a modulation scheme that is widely used in wired and wireless communication systems. While OFDM is ideally suited to deal with frequency selective channels and AWGN, its performance may be dramatically impacted by the presence of impulse noise. In fact, very strong noise impulses in the time domain might result in the erasure of whole OFDM blocks of symbols at the receiver. Impulse noise can be mitigated by considering it as a sparse signal in time, and using recently developed algorithms for sparse signal reconstruction. We propose an algorithm that utilizes the guard band subcarriers for the impulse noise estimation and cancellation. Instead of relying on ℓ1 minimization as done in some popular general-purpose compressive sensing schemes, the proposed method jointly exploits the specific structure of this problem and the available a priori information for sparse signal recovery. The computational complexity of the proposed algorithm is very competitive with respect to sparse signal reconstruction schemes based on ℓ1 minimization. The proposed method is compared with respect to other state-of-the-art methods in terms of achievable rates for an OFDM system with impulse noise and AWGN. © 2014 IEEE.
Observing System Simulations for Small Satellite Formations Estimating Bidirectional Reflectance
Nag, Sreeja; Gatebe, Charles K.; de Weck, Olivier
2015-01-01
The bidirectional reflectance distribution function (BRDF) gives the reflectance of a target as a function of illumination geometry and viewing geometry, hence carries information about the anisotropy of the surface. BRDF is needed in remote sensing for the correction of view and illumination angle effects (for example in image standardization and mosaicing), for deriving albedo, for land cover classification, for cloud detection, for atmospheric correction, and other applications. However, current spaceborne instruments provide sparse angular sampling of BRDF and airborne instruments are limited in the spatial and temporal coverage. To fill the gaps in angular coverage within spatial, spectral and temporal requirements, we propose a new measurement technique: Use of small satellites in formation flight, each satellite with a VNIR (visible and near infrared) imaging spectrometer, to make multi-spectral, near-simultaneous measurements of every ground spot in the swath at multiple angles. This paper describes an observing system simulation experiment (OSSE) to evaluate the proposed concept and select the optimal formation architecture that minimizes BRDF uncertainties. The variables of the OSSE are identified; number of satellites, measurement spread in the view zenith and relative azimuth with respect to solar plane, solar zenith angle, BRDF models and wavelength of reflection. Analyzing the sensitivity of BRDF estimation errors to the variables allow simplification of the OSSE, to enable its use to rapidly evaluate formation architectures. A 6-satellite formation is shown to produce lower BRDF estimation errors, purely in terms of angular sampling as evaluated by the OSSE, than a single spacecraft with 9 forward-aft sensors. We demonstrate the ability to use OSSEs to design small satellite formations as complements to flagship mission data. The formations can fill angular sampling gaps and enable better BRDF products than currently possible.
Observing system simulations for small satellite formations estimating bidirectional reflectance
Nag, Sreeja; Gatebe, Charles K.; Weck, Olivier de
2015-12-01
The bidirectional reflectance distribution function (BRDF) gives the reflectance of a target as a function of illumination geometry and viewing geometry, hence carries information about the anisotropy of the surface. BRDF is needed in remote sensing for the correction of view and illumination angle effects (for example in image standardization and mosaicing), for deriving albedo, for land cover classification, for cloud detection, for atmospheric correction, and other applications. However, current spaceborne instruments provide sparse angular sampling of BRDF and airborne instruments are limited in the spatial and temporal coverage. To fill the gaps in angular coverage within spatial, spectral and temporal requirements, we propose a new measurement technique: use of small satellites in formation flight, each satellite with a VNIR (visible and near infrared) imaging spectrometer, to make multi-spectral, near-simultaneous measurements of every ground spot in the swath at multiple angles. This paper describes an observing system simulation experiment (OSSE) to evaluate the proposed concept and select the optimal formation architecture that minimizes BRDF uncertainties. The variables of the OSSE are identified; number of satellites, measurement spread in the view zenith and relative azimuth with respect to solar plane, solar zenith angle, BRDF models and wavelength of reflection. Analyzing the sensitivity of BRDF estimation errors to the variables allow simplification of the OSSE, to enable its use to rapidly evaluate formation architectures. A 6-satellite formation is shown to produce lower BRDF estimation errors, purely in terms of angular sampling as evaluated by the OSSE, than a single spacecraft with 9 forward-aft sensors. We demonstrate the ability to use OSSEs to design small satellite formations as complements to flagship mission data. The formations can fill angular sampling gaps and enable better BRDF products than currently possible.
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
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.
Reducing Inventory System Costs by Using Robust Demand Estimators
Raymond A. Jacobs; Harvey M. Wagner
1989-01-01
Applications of inventory theory typically use historical data to estimate demand distribution parameters. Imprecise knowledge of the demand distribution adds to the usual replenishment costs associated with stochastic demands. Only limited research has been directed at the problem of choosing cost effective statistical procedures for estimating these parameters. Available theoretical findings on estimating the demand parameters for (s, S) inventory replenishment policies are limited by their...
Reliability estimation of semi-Markov systems: a case study
International Nuclear Information System (INIS)
Ouhbi, Brahim; Limnios, Nikolaos
1997-01-01
In this article, we are concerned with the estimation of the reliability and the availability of a turbo-generator rotor using a set of data observed in a real engineering situation provided by Electricite De France (EDF). The rotor is modeled by a semi-Markov process, which is used to estimate the rotor's reliability and availability. To do this, we present a method for estimating the semi-Markov kernel from a censored data
Cost estimating issues in the Russian integrated system planning context
International Nuclear Information System (INIS)
Allentuck, J.
1996-01-01
An important factor in the credibility of an optimal capacity expansion plan is the accuracy of cost estimates given the uncertainty of future economic conditions. This paper examines the problems associated with estimating investment and operating costs in the Russian nuclear power context over the period 1994 to 2010
A Simulation-Based Soft Error Estimation Methodology for Computer Systems
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...
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...
Estimates and sampling schemes for the instrumentation of accountability systems
International Nuclear Information System (INIS)
Jewell, W.S.; Kwiatkowski, J.W.
1976-10-01
The problem of estimation of a physical quantity from a set of measurements is considered, where the measurements are made on samples with a hierarchical error structure, and where within-groups error variances may vary from group to group at each level of the structure; minimum mean squared-error estimators are developed, and the case where the physical quantity is a random variable with known prior mean and variance is included. Estimators for the error variances are also given, and optimization of experimental design is considered
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...
Ženski pari moških poimenovanj v slovenskem knjižnem jeziku 16. stoletja
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.
Estimation of Multiple Point Sources for Linear Fractional Order Systems Using Modulating Functions
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
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
Carleman estimates and applications to inverse problems for hyperbolic systems
Bellassoued, Mourad
2017-01-01
This book is a self-contained account of the method based on Carleman estimates for inverse problems of determining spatially varying functions of differential equations of the hyperbolic type by non-overdetermining data of solutions. The formulation is different from that of Dirichlet-to-Neumann maps and can often prove the global uniqueness and Lipschitz stability even with a single measurement. These types of inverse problems include coefficient inverse problems of determining physical parameters in inhomogeneous media that appear in many applications related to electromagnetism, elasticity, and related phenomena. Although the methodology was created in 1981 by Bukhgeim and Klibanov, its comprehensive development has been accomplished only recently. In spite of the wide applicability of the method, there are few monographs focusing on combined accounts of Carleman estimates and applications to inverse problems. The aim in this book is to fill that gap. The basic tool is Carleman estimates, the theory of wh...
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.
Estimation of Physical Parameters in Linear and Nonlinear Dynamic Systems
DEFF Research Database (Denmark)
Knudsen, Morten
variance and confidence ellipsoid is demonstrated. The relation is based on a new theorem on maxima of an ellipsoid. The procedure for input signal design and physical parameter estimation is tested on a number of examples, linear as well as nonlinear and simulated as well as real processes, and it appears...
CFO and channel estimation for MISO-OFDM systems
Ladaycia, Abdelhamid; Abed-Meraim, Karim; Bader, Ahmed; Alouini, Mohamed-Slim
2017-01-01
-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
Probabilistic fuzzy systems in value-at-risk estimation
Almeida, R.J.; Kaymak, U.
2009-01-01
Value-at-risk (VaR) is a popular measure for quantifying the market risk that a financial institution faces into a single number. Owing to the complexity of financial markets, the risks associated with a portfolio varies over time. Consequently, advanced methods of VaR estimation use parametric
Estimation of failure probabilities of linear dynamic systems by ...
Indian Academy of Sciences (India)
An iterative method for estimating the failure probability for certain time-variant reliability problems has been developed. In the paper, the focus is on the displacement response of a linear oscillator driven by white noise. Failure is then assumed to occur when the displacement response exceeds a critical threshold.
Parameter estimation and prediction of nonlinear biological systems: some examples
Doeswijk, T.G.; Keesman, K.J.
2006-01-01
Rearranging and reparameterizing a discrete-time nonlinear model with polynomial quotient structure in input, output and parameters (xk = f(Z, p)) leads to a model linear in its (new) parameters. As a result, the parameter estimation problem becomes a so-called errors-in-variables problem for which
Energy-efficient power allocation of two-hop cooperative systems with imperfect channel estimation
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.
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
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...
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.
System and Method for Outlier Detection via Estimating Clusters
Iverson, David J. (Inventor)
2016-01-01
An efficient method and system for real-time or offline analysis of multivariate sensor data for use in anomaly detection, fault detection, and system health monitoring is provided. Models automatically derived from training data, typically nominal system data acquired from sensors in normally operating conditions or from detailed simulations, are used to identify unusual, out of family data samples (outliers) that indicate possible system failure or degradation. Outliers are determined through analyzing a degree of deviation of current system behavior from the models formed from the nominal system data. The deviation of current system behavior is presented as an easy to interpret numerical score along with a measure of the relative contribution of each system parameter to any off-nominal deviation. The techniques described herein may also be used to "clean" the training data.
Improving Cyber-Security of Power System State Estimators
Giannini, Martina
2014-01-01
During the last century, technological advances have deeply renewed many critical infrastructures, such as transportation networks and power systems. In fact, the strong interconnection between physical process, communication channels, and control systems have led to the new concept of cyber-physical systems. Next to countless new advantages, these systems unfortunately have also new weaknesses. An example is cyber-attacks: malicious intrusions into the communication channel turned to manipul...
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
Estimation of power system variability due to wind power
Papaefthymiou, G.; Verboomen, J.; Van der Sluis, L.
2007-01-01
The incorporation of wind power generation to the power system leads to an increase in the variability of the system power flows. The assessment of this variability is necessary for the planning of the necessary system reinforcements. For the assessment of this variability, the uncertainty in the
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.
CosmoSIS: A System for MC Parameter Estimation
Energy Technology Data Exchange (ETDEWEB)
Zuntz, Joe [Manchester U.; Paterno, Marc [Fermilab; Jennings, Elise [Chicago U., EFI; Rudd, Douglas [U. Chicago; Manzotti, Alessandro [Chicago U., Astron. Astrophys. Ctr.; Dodelson, Scott [Chicago U., Astron. Astrophys. Ctr.; Bridle, Sarah [Manchester U.; Sehrish, Saba [Fermilab; Kowalkowski, James [Fermilab
2015-01-01
Cosmological parameter estimation is entering a new era. Large collaborations need to coordinate high-stakes analyses using multiple methods; furthermore such analyses have grown in complexity due to sophisticated models of cosmology and systematic uncertainties. In this paper we argue that modularity is the key to addressing these challenges: calculations should be broken up into interchangeable modular units with inputs and outputs clearly defined. We present a new framework for cosmological parameter estimation, CosmoSIS, designed to connect together, share, and advance development of inference tools across the community. We describe the modules already available in Cosmo- SIS, including camb, Planck, cosmic shear calculations, and a suite of samplers. We illustrate it using demonstration code that you can run out-of-the-box with the installer available at http://bitbucket.org/joezuntz/cosmosis.
Cost Estimation Techniques for C3I System Software.
1984-07-01
opment manmonth have been determined for maxi, midi , and mini .1 type computers. Small to median size timeshared developments used 0.2 to 1.5 hours...development schedule 1.23 1.00 1.10 2.1.3 Detailed Model The final codification of the COCOMO regressions was the development of separate effort...regardless of the software structure level being estimated: D8VC -- the expected development computer (maxi. midi . mini, micro) MODE -- the expected
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.
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.
Fault Estimation for Fuzzy Delay Systems: A Minimum Norm Least Squares Solution Approach.
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.
Method of statistical estimation of temperature minimums in binary systems
International Nuclear Information System (INIS)
Mireev, V.A.; Safonov, V.V.
1985-01-01
On the basis of statistical processing of literature data the technique for evaluation of temperature minima on liquidus curves in binary systems with common ion chloride systems being taken as an example, is developed. The systems are formed by 48 chlorides of 45 chemical elements including alkali, alkaline earth, rare earth and transition metals as well as Cd, In, Th. It is shown that calculation error in determining minimum melting points depends on topology of the phase diagram. The comparison of calculated and experimental data for several previously nonstudied systems is given
System for estimation of mean active bone marrow dose
International Nuclear Information System (INIS)
Ellis, R.E.; Healy, M.J.R.; Shleien, B.; Tucker, T.
1975-09-01
The exposure measurements, model and computer program for estimation of mean active bone marrow doses formerly employed in the 1962 British Survey of x-ray doses and proposed for application to x-ray exposure information obtained in the U.S. Public Health Service's X-Ray Exposure Studies (1966 and 1973) are described and evaluated. The method described is feasible for use to determine the mean active bone marrow doses to adults for examinations having a skin to source distance of 80 cm or less. For a greater SSD, as for example in chest x rays, a small correction in the calculation dose can be made
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.
Localization of periodic orbits of polynomial systems by ellipsoidal estimates
International Nuclear Information System (INIS)
Starkov, Konstantin E.; Krishchenko, Alexander P.
2005-01-01
In this paper we study the localization problem of periodic orbits of multidimensional continuous-time systems in the global setting. Our results are based on the solution of the conditional extremum problem and using sign-definite quadratic and quartic forms. As examples, the Rikitake system and the Lamb's equations for a three-mode operating cavity in a laser are considered
Estimators for initial conditions for optimisation in learning hydraulic systems
Post, W.J.A.E.M.; Burrows, C.R.; Edge, K.A.
1998-01-01
In Learning Hydraulic Systems (LHS1. developed at the Eindhoven University of Technology, a specialised optimisation routine is employed In order to reduce energy losses in hydraulic systems. Typical load situations which can be managed by LHS are variable cyclic loads, as can be observed In many
Technical report for effective estimation and improvement of quality system
International Nuclear Information System (INIS)
Kim, Kwan Hyun
2000-06-01
This technical report provides the methods on how to improve the Quality System, in R and D part. This report applies on the quality assurance(QA) programmes of the design, fabrication in nuclear projects. The organization having overall responsibility for the nuclear power item design, preservation, fabrication shall be described in this report in each stage of improvement of QA systems
International Nuclear Information System (INIS)
Jang, Yu Jin
2013-01-01
This paper presents an automatic performance estimation scheme of conceptual temperature control system with multi-heater configuration prior to constructing the physical system for achieving rapid validation of the conceptual design. An appropriate low-order discrete-time model, which will be used in the controller design, is constructed after determining several basic factors including the geometric shape of controlled object and heaters, material properties, heater arrangement, etc. The proposed temperature controller, which adopts the multivariable GPC (generalized predictive control) scheme with scale factors, is then constructed automatically based on the above model. The performance of the conceptual temperature control system is evaluated by using a FEM (finite element method) simulation combined with the controller.
Energy Technology Data Exchange (ETDEWEB)
Jang, Yu Jin [Dongguk University, GyeongJu (Korea, Republic of)
2013-07-15
This paper presents an automatic performance estimation scheme of conceptual temperature control system with multi-heater configuration prior to constructing the physical system for achieving rapid validation of the conceptual design. An appropriate low-order discrete-time model, which will be used in the controller design, is constructed after determining several basic factors including the geometric shape of controlled object and heaters, material properties, heater arrangement, etc. The proposed temperature controller, which adopts the multivariable GPC (generalized predictive control) scheme with scale factors, is then constructed automatically based on the above model. The performance of the conceptual temperature control system is evaluated by using a FEM (finite element method) simulation combined with the controller.
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.
History by history statistical estimators in the BEAM code system
International Nuclear Information System (INIS)
Walters, B.R.B.; Kawrakow, I.; Rogers, D.W.O.
2002-01-01
A history by history method for estimating uncertainties has been implemented in the BEAMnrc and DOSXYZnrc codes replacing the method of statistical batches. This method groups scored quantities (e.g., dose) by primary history. When phase-space sources are used, this method groups incident particles according to the primary histories that generated them. This necessitated adding markers (negative energy) to phase-space files to indicate the first particle generated by a new primary history. The new method greatly reduces the uncertainty in the uncertainty estimate. The new method eliminates one dimension (which kept the results for each batch) from all scoring arrays, resulting in memory requirement being decreased by a factor of 2. Correlations between particles in phase-space sources are taken into account. The only correlations with any significant impact on uncertainty are those introduced by particle recycling. Failure to account for these correlations can result in a significant underestimate of the uncertainty. The previous method of accounting for correlations due to recycling by placing all recycled particles in the same batch did work. Neither the new method nor the batch method take into account correlations between incident particles when a phase-space source is restarted so one must avoid restarts
Performance estimation of photovoltaic–thermoelectric hybrid systems
International Nuclear Information System (INIS)
Zhang, Jin; Xuan, Yimin; Yang, Lili
2014-01-01
A theoretical model for evaluating the efficiency of concentrating PV–TE (photovoltaic–thermoelectric) hybrid system is developed in this paper. Hybrid systems with different photovoltaic cells are studied, including crystalline silicon photovoltaic cell, silicon thin-film photovoltaic cell, polymer photovoltaic cell and copper indium gallium selenide photovoltaic cell. The influence of temperature on the efficiency of photovoltaic cell has been taken into account based on the semiconductor equations, which reveals different efficiency temperature characteristic of polymer photovoltaic cells. It is demonstrated that the polycrystalline silicon thin-film photovoltaic cell is suitable for concentrating PV–TE hybrid system through optimization of the convection heat transfer coefficient and concentrating ratio. The polymer photovoltaic cell is proved to be suitable for non-concentrating PV–TE hybrid system. - Highlights: • Performances of four types of photovoltaic–thermoelectric hybrid systems are studied. • Temperature is one of dominant factors of affecting the conversion efficiency of PV–TE systems. • One can select a proper PV–TE assembly system according to given operating conditions
Systems and economics for the estimation of uranium potential supply
International Nuclear Information System (INIS)
Harris, D.P.; Ortiz-Vertiz, R.; Chavex, M.L.; Agbolosoo, E.K.
1981-07-01
This report consists of four parts, each one reasonably complete unto itself: Part I - Potential Supply Systems Based upon the Simulation of Sequential Exploration and Economic Decisions -- Systems Designed for the Analysis of NURE Endowment; Part II - Crustal Abundance and a Potential Supply System; Part III - An Investigation of Productivity and Technical Change in Exploration for and Production of Uranium; and Part IV - The Use of Solute Transport Models to Generate Geochemical Responses from a Hypothetical Uranium Deposit - An Early Effort in the Exploration Model Design. The bulk of this research was devoted to the design of potential supply systems. However, in that such systems require the modeling of exploration and exploitation, both of these activities were investigated as economic phenomena and as the subjects of models. Part I represents the largest of the research efforts. An attempt was made to design a system in which exploration is modeled in terms of both its efficiency and economics. While the exploration model demonstrated in this report is for roll-type sandstone deposits, this potential supply system, as a system per se, also applies to tabular deposits (San Juan Basin). Part II explores the concept of crustal abundance and existing crustal abundance models. The design of this crustal abundance potential supply system differs from that of any previously constructedcrustal abundance models in that it explicitly considers the third dimension, depth to deposit, and it places great emphasis upon the credible representation of the economics of exploration and exploitation. Part III reports on an attempt to measure the magnitude of technical change and depletion on the productivity of exploration and mining. This research examined these issues from the perspective of the economist, not the engineer. Part IV reports on an investigation of the feasibility of modeling the geochemical exploration for uranium, radon, and helium plumes
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.
COMPUTER SUPPORT SYSTEMS FOR ESTIMATING CHEMICAL TOXICITY: PRESENT CAPABILITIES AND FUTURE TRENDS
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...
Fault Adaptive Control of Overactuated Systems Using Prognostic Estimation
National Aeronautics and Space Administration — Most fault adaptive control research addresses the preservation of system stability or functionality in the presence of a specific failure (fault). This paper...
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
... prediction, offshore energy, power generation, and commercial fishing. Our findings suggest that annual benefits to users from the deployment of ocean observing systems are likely to run in the multiple...
Estimating New Product Success with the Use of Intelligent Systems
Directory of Open Access Journals (Sweden)
Relich Marcin
2014-12-01
Full Text Available The paper presents identifying success factors in new product development and selecting new product portfolio. The critical success factors are identified on the basis of an enterprise system, including the fields of project management, marketing and customer’s comments concerning the previous products. The model of measuring the success of a product includes the indicators such as duration and cost of product development, and net profit from a product. The proposed methodology is based on identification of the relationships between product success and project environment parameters with the use of artificial neural networks and fuzzy neural system that is compared with the results from linear model. The presented method contains the stages of knowledge discovery process such as data selection, data preprocessing, and data mining in the context of an enterprise resource planning system database. The illustrative example enhances a performance comparison of intelligent systems in the context of data preprocessing.
Estimating System-wide Impacts of Smart Grid Demonstrations
Energy Technology Data Exchange (ETDEWEB)
Schneider, Kevin P.; Lightner, Eric M.; Fuller, Jason C.
2015-03-01
Quantifying the impact of a new technology on a single specific distribution feeder is relatively easy, but it does not provide insight into the complexities and variations of a system-wide deployment. It is the inability to extrapolate system-wide impacts that hinders the deployment of many promising new technologies. This paper presents a method of extrapolating technology impacts, either simulated or from a field demonstration, from a limited number of distribution feeders to a system-wide impact. The size of the system can vary from the service territory of a single utility, to a region, or to an entire country. The paper will include an example analysis using the United States Department of Energy (DOE) funded Smart Grid Investment Grant (SGIG) projects, extrapolating their benefits to a national level.
Action-reaction based parameters identification and states estimation of flexible systems
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...
Guidelines and Metrics for Assessing Space System Cost Estimates
2008-01-01
dump momentum from mechanical reaction control systems, and de-orbit at the end of the mission. Various approaches are used to accelerate the...launch vehicle and cargo power system-the necessary generation, storage, and distribution of electrical power and signals, hydraulic power, and any other...service, transport, hoist , repair, overhaul, assemble, disassemble, test, inspect, or otherwise maintain mission equipment any production of
Localization of periodic orbits of polynomial systems by ellipsoidal estimates
Energy Technology Data Exchange (ETDEWEB)
Starkov, Konstantin E. [CITEDI-IPN, Avenue del Parque 1310, Mesa de Otay, Tijuana, BC (Mexico)]. E-mail: konst@citedi.mx; Krishchenko, Alexander P. [Bauman Moscow State Technical University, 2nd Baumanskaya Street, 5, Moscow 105005 (Russian Federation)]. E-mail: apkri@999.ru
2005-02-01
In this paper we study the localization problem of periodic orbits of multidimensional continuous-time systems in the global setting. Our results are based on the solution of the conditional extremum problem and using sign-definite quadratic and quartic forms. As examples, the Rikitake system and the Lamb's equations for a three-mode operating cavity in a laser are considered.
Entropy Evolution and Uncertainty Estimation with Dynamical Systems
Directory of Open Access Journals (Sweden)
X. San Liang
2014-06-01
Full Text Available This paper presents a comprehensive introduction and systematic derivation of the evolutionary equations for absolute entropy H and relative entropy D, some of which exist sporadically in the literature in different forms under different subjects, within the framework of dynamical systems. In general, both H and D are dissipated, and the dissipation bears a form reminiscent of the Fisher information; in the absence of stochasticity, dH/dt is connected to the rate of phase space expansion, and D stays invariant, i.e., the separation of two probability density functions is always conserved. These formulas are validated with linear systems, and put to application with the Lorenz system and a large-dimensional stochastic quasi-geostrophic flow problem. In the Lorenz case, H falls at a constant rate with time, implying that H will eventually become negative, a situation beyond the capability of the commonly used computational technique like coarse-graining and bin counting. For the stochastic flow problem, it is first reduced to a computationally tractable low-dimensional system, using a reduced model approach, and then handled through ensemble prediction. Both the Lorenz system and the stochastic flow system are examples of self-organization in the light of uncertainty reduction. The latter particularly shows that, sometimes stochasticity may actually enhance the self-organization process.
Computer software to estimate timber harvesting system production, cost, and revenue
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...
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.
Visual Estimation of Bacterial Growth Level in Microfluidic Culture Systems
Directory of Open Access Journals (Sweden)
Kyukwang Kim
2018-02-01
Full Text Available Microfluidic devices are an emerging platform for a variety of experiments involving bacterial cell culture, and has advantages including cost and convenience. One inevitable step during bacterial cell culture is the measurement of cell concentration in the channel. The optical density measurement technique is generally used for bacterial growth estimation, but it is not applicable to microfluidic devices due to the small sample volumes in microfluidics. Alternately, cell counting or colony-forming unit methods may be applied, but these do not work in situ; nor do these methods show measurement results immediately. To this end, we present a new vision-based method to estimate the growth level of the bacteria in microfluidic channels. We use Fast Fourier transform (FFT to detect the frequency level change of the microscopic image, focusing on the fact that the microscopic image becomes rough as the number of cells in the field of view increases, adding high frequencies to the spectrum of the image. Two types of microfluidic devices are used to culture bacteria in liquid and agar gel medium, and time-lapsed images are captured. The images obtained are analyzed using FFT, resulting in an increase in high-frequency noise proportional to the time passed. Furthermore, we apply the developed method in the microfluidic antibiotics susceptibility test by recognizing the regional concentration change of the bacteria that are cultured in the antibiotics gradient. Finally, a deep learning-based data regression is performed on the data obtained by the proposed vision-based method for robust reporting of data.
Visual Estimation of Bacterial Growth Level in Microfluidic Culture Systems.
Kim, Kyukwang; Kim, Seunggyu; Jeon, Jessie S
2018-02-03
Microfluidic devices are an emerging platform for a variety of experiments involving bacterial cell culture, and has advantages including cost and convenience. One inevitable step during bacterial cell culture is the measurement of cell concentration in the channel. The optical density measurement technique is generally used for bacterial growth estimation, but it is not applicable to microfluidic devices due to the small sample volumes in microfluidics. Alternately, cell counting or colony-forming unit methods may be applied, but these do not work in situ; nor do these methods show measurement results immediately. To this end, we present a new vision-based method to estimate the growth level of the bacteria in microfluidic channels. We use Fast Fourier transform (FFT) to detect the frequency level change of the microscopic image, focusing on the fact that the microscopic image becomes rough as the number of cells in the field of view increases, adding high frequencies to the spectrum of the image. Two types of microfluidic devices are used to culture bacteria in liquid and agar gel medium, and time-lapsed images are captured. The images obtained are analyzed using FFT, resulting in an increase in high-frequency noise proportional to the time passed. Furthermore, we apply the developed method in the microfluidic antibiotics susceptibility test by recognizing the regional concentration change of the bacteria that are cultured in the antibiotics gradient. Finally, a deep learning-based data regression is performed on the data obtained by the proposed vision-based method for robust reporting of data.
Parameter Estimation for Dynamic Model of the Financial System
Directory of Open Access Journals (Sweden)
Veronika Novotná
2015-01-01
Full Text Available Economy can be considered a large, open system which is influenced by fluctuations, both internal and external. Based on non-linear dynamics theory, the dynamic models of a financial system try to provide a new perspective by explaining the complicated behaviour of the system not as a result of external influences or random behaviour, but as a result of the behaviour and trends of the system’s internal structures. The present article analyses a chaotic financial system from the point of view of determining the time delay of the model variables – the interest rate, investment demand, and price index. The theory is briefly explained in the first chapters of the paper and serves as a basis for formulating the relations. This article aims to determine the appropriate length of time delay variables in a dynamic model of the financial system in order to express the real economic situation and respect the effect of the history of factors under consideration. The determination of the delay length is carried out for the time series representing Euro area. The methodology for the determination of the time delay is illustrated by a concrete example.
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.
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.
Method and system to estimate variables in an integrated gasification combined cycle (IGCC) plant
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.
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.
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)
Wilderness recreation use estimation: a handbook of methods and systems
Alan E. Watson; David N. Cole; David L. Turner; Penny S. Reynolds
2000-01-01
Documented evidence shows that managers of units within the U.S. National Wilderness Preservation System are making decisions without reliable information on the amount, types, and distribution of recreation use occurring at these areas. There are clear legislative mandates and agency policies that direct managers to monitor trends in use and conditions in wilderness....
A review of methods for updating forest monitoring system estimates
Hector Franco-Lopez; Alan R. Ek; Andrew P. Robinson
2000-01-01
Intensifying interest in forests and the development of new monitoring technologies have induced major changes in forest monitoring systems in the last few years, including major revisions in the methods used for updating. This paper describes the methods available for projecting stand- and plot-level information, emphasizing advantages and disadvantages, and the...
Robust Parametric Fault Estimation in a Hopper System
DEFF Research Database (Denmark)
Soltani, Mohsen; Izadi-Zamanabadi, Roozbeh; Wisniewski, Rafal
2012-01-01
The ability of diagnosis of the possible faults is a necessity for satellite launch vehicles during their mission. In this paper, a structural analysis method is employed to divide the complex propulsion system into simpler subsystems for fault diagnosis filter design. A robust fault diagnosis me...
Modeling, Estimation, and Control of Helicopter Slung Load System
DEFF Research Database (Denmark)
Bisgaard, Morten
and simulating different slung load suspension types. It further includes detection and response to wire slacking and tightening, it models the aerodynamic coupling between the helicopter and the load, and can be used for multilift systems with any combination of multiple helicopters and multiple loads...
Methodologies for quantitative systems pharmacology (QSP) models : Design and Estimation
Ribba, B.; Grimm, Hp; Agoram, B.; Davies, M.R.; Gadkar, K.; Niederer, S.; van Riel, N.; Timmis, J.; van der Graaf, Ph.
2017-01-01
With the increased interest in the application of quantitative systems pharmacology (QSP) models within medicine research and development, there is an increasing need to formalize model development and verification aspects. In February 2016, a workshop was held at Roche Pharma Research and Early
Methodologies for Quantitative Systems Pharmacology (QSP) Models: Design and Estimation
Ribba, B.; Grimm, H. P.; Agoram, B.; Davies, M. R.; Gadkar, K.; Niederer, S.; van Riel, N.; Timmis, J.; van der Graaf, P. H.
2017-01-01
With the increased interest in the application of quantitative systems pharmacology (QSP) models within medicine research and development, there is an increasing need to formalize model development and verification aspects. In February 2016, a workshop was held at Roche Pharma Research and Early
The stochastic system approach for estimating dynamic treatments effect.
Commenges, Daniel; Gégout-Petit, Anne
2015-10-01
The problem of assessing the effect of a treatment on a marker in observational studies raises the difficulty that attribution of the treatment may depend on the observed marker values. As an example, we focus on the analysis of the effect of a HAART on CD4 counts, where attribution of the treatment may depend on the observed marker values. This problem has been treated using marginal structural models relying on the counterfactual/potential response formalism. Another approach to causality is based on dynamical models, and causal influence has been formalized in the framework of the Doob-Meyer decomposition of stochastic processes. Causal inference however needs assumptions that we detail in this paper and we call this approach to causality the "stochastic system" approach. First we treat this problem in discrete time, then in continuous time. This approach allows incorporating biological knowledge naturally. When working in continuous time, the mechanistic approach involves distinguishing the model for the system and the model for the observations. Indeed, biological systems live in continuous time, and mechanisms can be expressed in the form of a system of differential equations, while observations are taken at discrete times. Inference in mechanistic models is challenging, particularly from a numerical point of view, but these models can yield much richer and reliable results.
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....
Modern optimization algorithms for fault location estimation in power systems
Directory of Open Access Journals (Sweden)
A. Sanad Ahmed
2017-10-01
Full Text Available This paper presents a fault location estimation approach in two terminal transmission lines using Teaching Learning Based Optimization (TLBO technique, and Harmony Search (HS technique. Also, previous methods were discussed such as Genetic Algorithm (GA, Artificial Bee Colony (ABC, Artificial neural networks (ANN and Cause & effect (C&E with discussing advantages and disadvantages of all methods. Initial data for proposed techniques are post-fault measured voltages and currents from both ends, along with line parameters as initial inputs as well. This paper deals with several types of faults, L-L-L, L-L-L-G, L-L-G and L-G. Simulation of the model was performed on SIMULINK by extracting initial inputs from SIMULINK to MATLAB, where the objective function specifies the fault location with a very high accuracy, precision and within a very short time. Future works are discussed showing the benefit behind using the Differential Learning TLBO (DLTLBO was discussed as well.
Parameter and state estimation of experimental chaotic systems using synchronization
Quinn, John C.; Bryant, Paul H.; Creveling, Daniel R.; Klein, Sallee R.; Abarbanel, Henry D. I.
2009-07-01
We examine the use of synchronization as a mechanism for extracting parameter and state information from experimental systems. We focus on important aspects of this problem that have received little attention previously and we explore them using experiments and simulations with the chaotic Colpitts oscillator as an example system. We explore the impact of model imperfection on the ability to extract valid information from an experimental system. We compare two optimization methods: an initial value method and a constrained method. Each of these involves coupling the model equations to the experimental data in order to regularize the chaotic motions on the synchronization manifold. We explore both time-dependent and time-independent coupling and discuss the use of periodic impulse coupling. We also examine both optimized and fixed (or manually adjusted) coupling. For the case of an optimized time-dependent coupling function u(t) we find a robust structure which includes sharp peaks and intervals where it is zero. This structure shows a strong correlation with the location in phase space and appears to depend on noise, imperfections of the model, and the Lyapunov direction vectors. For time-independent coupling we find the counterintuitive result that often the optimal rms error in fitting the model to the data initially increases with coupling strength. Comparison of this result with that obtained using simulated data may provide one measure of model imperfection. The constrained method with time-dependent coupling appears to have benefits in synchronizing long data sets with minimal impact, while the initial value method with time-independent coupling tends to be substantially faster, more flexible, and easier to use. We also describe a method of coupling which is useful for sparse experimental data sets. Our use of the Colpitts oscillator allows us to explore in detail the case of a system with one positive Lyapunov exponent. The methods we explored are easily
The PARAFAC-MUSIC Algorithm for DOA Estimation with Doppler Frequency in a MIMO Radar System
Directory of Open Access Journals (Sweden)
Nan Wang
2014-01-01
Full Text Available The PARAFAC-MUSIC algorithm is proposed to estimate the direction-of-arrival (DOA of the targets with Doppler frequency in a monostatic MIMO radar system in this paper. To estimate the Doppler frequency, the PARAFAC (parallel factor algorithm is firstly utilized in the proposed algorithm, and after the compensation of Doppler frequency, MUSIC (multiple signal classification algorithm is applied to estimate the DOA. By these two steps, the DOA of moving targets can be estimated successfully. Simulation results show that the proposed PARAFAC-MUSIC algorithm has a higher accuracy than the PARAFAC algorithm and the MUSIC algorithm in DOA estimation.
Neurophysiological Estimates of Human Performance Capabilities in Aerospace Systems
1976-11-30
decreased when the shared activity was within the same hemisphere. We again recall that in our previous dyslexia experiment(l0), good readers had...higher coherence across the hemispheres during reading tasks, whereas the dyslexia poor readers had higher within the hemisphere coherences while...modification of sequential tasks not possible by intervention of the experimenter. Nevertheless, we have not formed a system suited to our needs in a
FUZZY INFERENCE BASED LEAK ESTIMATION IN WATER PIPELINES SYSTEM
N. Lavanya; G. Anand; S. Srinivasan
2015-01-01
Pipeline networks are the most widely used mode for transporting fluids and gases around the world. Leakage in this pipeline causes harmful effects when the flowing fluid/gas is hazardous. Hence the detection of leak becomes essential to avoid/minimize such undesirable effects. This paper presents the leak detection by spectral analysis methods in a laboratory pipeline system. Transient in the pressure signal in the pipeline is created by opening and closing the exit valve. These pressure var...
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.
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.
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.
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....
Distributed weighted least-squares estimation with fast convergence for large-scale systems.
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.
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
Estimating variability in placido-based topographic systems.
Kounis, George A; Tsilimbaris, Miltiadis K; Kymionis, George D; Ginis, Harilaos S; Pallikaris, Ioannis G
2007-10-01
To describe a new software tool for the detailed presentation of corneal topography measurements variability by means of color-coded maps. Software was developed in Visual Basic to analyze and process a series of 10 consecutive measurements obtained by a topographic system on calibration spheres, and individuals with emmetropic, low, high, and irregular astigmatic corneas. Corneal surface was segmented into 1200 segments and the coefficient of variance of each segment's keratometric dioptric power was used as the measure of variability. The results were presented graphically in color-coded maps (Variability Maps). Two topographic systems, the TechnoMed C-Scan and the TOMEY Topographic Modeling System (TMS-2N), were examined to demonstrate our method. Graphic representation of coefficient of variance offered a detailed representation of examination variability both in calibration surfaces and human corneas. It was easy to recognize an increase in variability, as the irregularity of examination surfaces increased. In individuals with high and irregular astigmatism, a variability pattern correlated with the pattern of corneal topography: steeper corneal areas possessed higher variability values compared with flatter areas of the same cornea. Numerical data permitted direct comparisons and statistical analysis. We propose a method that permits a detailed evaluation of the variability of corneal topography measurements. The representation of the results both graphically and quantitatively improves interpretability and facilitates a spatial correlation of variability maps with original topography maps. Given the popularity of topography based custom refractive ablations of the cornea, it is possible that variability maps may assist clinicians in the evaluation of corneal topography maps of patients with very irregular corneas, before custom ablation procedures.
Approximate estimation of system reliability via fault trees
International Nuclear Information System (INIS)
Dutuit, Y.; Rauzy, A.
2005-01-01
In this article, we show how fault tree analysis, carried out by means of binary decision diagrams (BDD), is able to approximate reliability of systems made of independent repairable components with a good accuracy and a good efficiency. We consider four algorithms: the Murchland lower bound, the Barlow-Proschan lower bound, the Vesely full approximation and the Vesely asymptotic approximation. For each of these algorithms, we consider an implementation based on the classical minimal cut sets/rare events approach and another one relying on the BDD technology. We present numerical results obtained with both approaches on various examples
Estimation of the Ideal Binary Mask using Directional Systems
DEFF Research Database (Denmark)
Boldt, Jesper; Kjems, Ulrik; Pedersen, Michael Syskind
2008-01-01
The ideal binary mask is often seen as a goal for time-frequency masking algorithms trying to increase speech intelligibility, but the required availability of the unmixed signals makes it difficult to calculate the ideal binary mask in any real-life applications. In this paper we derive the theory...... and the requirements to enable calculations of the ideal binary mask using a directional system without the availability of the unmixed signals. The proposed method has a low complexity and is verified using computer simulation in both ideal and non-ideal setups showing promising results....
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)
FUZZY INFERENCE BASED LEAK ESTIMATION IN WATER PIPELINES SYSTEM
Directory of Open Access Journals (Sweden)
N. Lavanya
2015-01-01
Full Text Available Pipeline networks are the most widely used mode for transporting fluids and gases around the world. Leakage in this pipeline causes harmful effects when the flowing fluid/gas is hazardous. Hence the detection of leak becomes essential to avoid/minimize such undesirable effects. This paper presents the leak detection by spectral analysis methods in a laboratory pipeline system. Transient in the pressure signal in the pipeline is created by opening and closing the exit valve. These pressure variations are captured and power spectrum is obtained by using Fast Fourier Transform (FFT method and Filter Diagonalization Method (FDM. The leaks at various positions are simulated and located using these methods and the results are compared. In order to determine the quantity of leak a 2 × 1 fuzzy inference system is created using the upstream and downstream pressure as input and the leak size as the output. Thus a complete leak detection, localization and quantification are done by using only the pressure variations in the pipeline.
Using interpolation to estimate system uncertainty in gene expression experiments.
Directory of Open Access Journals (Sweden)
Lee J Falin
Full Text Available The widespread use of high-throughput experimental assays designed to measure the entire complement of a cell's genes or gene products has led to vast stores of data that are extremely plentiful in terms of the number of items they can measure in a single sample, yet often sparse in the number of samples per experiment due to their high cost. This often leads to datasets where the number of treatment levels or time points sampled is limited, or where there are very small numbers of technical and/or biological replicates. Here we introduce a novel algorithm to quantify the uncertainty in the unmeasured intervals between biological measurements taken across a set of quantitative treatments. The algorithm provides a probabilistic distribution of possible gene expression values within unmeasured intervals, based on a plausible biological constraint. We show how quantification of this uncertainty can be used to guide researchers in further data collection by identifying which samples would likely add the most information to the system under study. Although the context for developing the algorithm was gene expression measurements taken over a time series, the approach can be readily applied to any set of quantitative systems biology measurements taken following quantitative (i.e. non-categorical treatments. In principle, the method could also be applied to combinations of treatments, in which case it could greatly simplify the task of exploring the large combinatorial space of future possible measurements.
A NEM diffusion code for fuel management and time average core calculation
International Nuclear Information System (INIS)
Mishra, Surendra; Ray, Sherly; Kumar, A.N.
2005-01-01
A computer code based on Nodal expansion method has been developed for solving two groups three dimensional diffusion equation. This code can be used for fuel management and time average core calculation. Explicit Xenon and fuel temperature estimation are also incorporated in this code. TAPP-4 phase-B physics experimental results were analyzed using this code and a code based on FD method. This paper gives the comparison of the observed data and the results obtained with this code and FD code. (author)
Residual life estimation of electrical insulation system for rotating equipment
International Nuclear Information System (INIS)
Vashishtha, Y.D.; Gupta, A.K.; Bhattacharyya, A.K.; Verma, A.K.
1994-01-01
Residual life assessment gains significance towards the end of designed life for granting plant life extensions and resource planning for costly equipment replacement. A critical review of all the diagnostic techniques presently used to assess either health of insulation system or to infer qualitatively the remaining life for rotating machines is presented. However more emphasis is required on developing quantitative methods. This paper also formulates the experimental plan for progressively censored ageing tests, measurement of partial discharge parameters, micro-structural study for delamination and electrical tree growth and measurement of electrical breakdown strength. Partial discharge (PD) patterns, electrical tree growth and time to failure data shall be taken as training set for the neural network learning which can be useful to predict residual life with only one candidate parameter i.e. PD patterns. (author). 9 refs
High Accuracy Nonlinear Control and Estimation for Machine Tool Systems
DEFF Research Database (Denmark)
Papageorgiou, Dimitrios
Component mass production has been the backbone of industry since the second industrial revolution, and machine tools are producing parts of widely varying size and design complexity. The ever-increasing level of automation in modern manufacturing processes necessitates the use of more...... sophisticated machine tool systems that are adaptable to different workspace conditions, while at the same time being able to maintain very narrow workpiece tolerances. The main topic of this thesis is to suggest control methods that can maintain required manufacturing tolerances, despite moderate wear and tear....... The purpose is to ensure that full accuracy is maintained between service intervals and to advice when overhaul is needed. The thesis argues that quality of manufactured components is directly related to the positioning accuracy of the machine tool axes, and it shows which low level control architectures...
Estimating dependability of programmable systems using bayesian belief nets
International Nuclear Information System (INIS)
Gran, Bjoern Axel; Dahll, Gustav
2000-05-01
The research programme at the Halden Project on software safety assessment is augmented through a joint project with Kongsberg Defence and Aerospace AS and Det Norske Veritas. The objective of this project is to investigate the possibility to combine the Bayesian Belief Net (BBN) methodology with a software safety standard. The report discusses software safety standards in general, with respect to how they can be used to measure software safety. The possibility to transfer the requirements of a software safety standard into a BBN is also investigated. The aim is to utilise the BBN methodology and associated tools, by transferring the software safety measurement into a probabilistic quantity. In this way software can be included in a total probabilistic safety analysis. This project was performed by applying the method for an evaluation of a real, safety related programmable system which was developed according to the avionic standard DO-178B. The test case, the standard, and the BBN methodology are shortly described. This is followed by a description of the construction of the BBN used in this project. This includes the topology of the BBN, the elicitation of probabilities and the making of observations. Based on this a variety of computations are made using the SERENE methodology and the HUGIN tool. Observations and conclusions are made on the basis of the findings from this process. This report should be considered as a progress report in a more long-term activity on the use of BBNs as support for safety assessment of programmable systems. (Author). 23 refs., 9 figs., tabs
Action-reaction based parameters identification and states estimation of flexible systems
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...
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.
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.
State estimation and synchronization of pendula systems over digital communication channels
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.
An Evaluation of the Automated Cost Estimating Integrated Tools (ACEIT) System
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
Schoeneich Hendrik; Hoeher Peter Adam
2006-01-01
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 ...
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.
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)
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.
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.
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.
Developing mechanisms for estimating carbon footprint in farming systems
Anaya-Romero, María; Fernández Luque, José Enrique; Rodríguez Merino, Alejandro; José Moreno Delgado, Juan; Rodado, Concepción Mira; Romero Vicente, Rafael; Perez-Martin, Alfonso; Muñoz-Rojas, Miriam
2015-04-01
Sustainable land management is critical to avoid land degradation and to reclaim degraded land for its productive use and for reaping the benefits of crucial ecosystem services and protecting biodiversity. It also helps in mitigating and adapting to climate change. Land and its various uses are affected severely by climate change too (flooding, droughts, etc.). Existing tools and technologies for efficient land management need to be adapted and their application expanded. A large number of human livelihoods and ecosystems can benefit from these tools and techniques since these yield multiple benefits. Disseminating and scaling up the implementation of sustainable land management approaches will, however, need to be backed up by mobilizing strong political will and financial resources. The challenge is to provide an integral decision support tool that can establish relationships between soil carbon content, climate change and land use and management aspects that allow stakeholders to detect, cope with and intervene into land system change in a sustainable way. In order to achieve this goal an agro-ecological meta-model called CarboLAND will be calibrated in several plots located in Andalusia region, Southern Spain, under different scenarios of climate and agricultural use and management. The output will be the CLIMALAND e-platform, which will also include protocols in order to support stakeholders for an integrated ecosystem approach, taking into account biodiversity, hydrological and soil capability, socio-economic aspects, and regional and environmental policies. This tool will be made available at the European context for a regional level, providing user-friendly interfaces and a scientifically-technical platform for the assessment of sustainable land use and management.
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.
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.
Addressing Single and Multiple Bad Data in the Modern PMU-based Power System State Estimation
DEFF Research Database (Denmark)
Khazraj, Hesam; Silva, Filipe Miguel Faria da; Bak, Claus Leth
2017-01-01
utilization in state estimation can detect and identify single and multiple bad data in redundant and critical measurements. To validate simulations, IEEE 30 bus system are implemented in PowerFactory and Matlab is used to solve proposed state estimation using postprocessing of PMUs and mixed methods. Bad...
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...
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...
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.
Estimates on the minimal period for periodic solutions of nonlinear second order Hamiltonian systems
International Nuclear Information System (INIS)
Yiming Long.
1994-11-01
In this paper, we prove a sharper estimate on the minimal period for periodic solutions of autonomous second order Hamiltonian systems under precisely Rabinowitz' superquadratic condition. (author). 20 refs, 1 fig
Systematic methodology for estimating direct capital costs for blanket tritium processing systems
International Nuclear Information System (INIS)
Finn, P.A.
1985-01-01
This paper describes the methodology developed for estimating the relative capital costs of blanket processing systems. The capital costs of the nine blanket concepts selected in the Blanket Comparison and Selection Study are presented and compared
Estimation of Subdaily Polar Motion with the Global Positioning System During the Spoch '92 Campaign
Ibanez-Meier, R.; Freedman, A. P.; Herring, T. A.; Gross, R. S.; Lichten, S. M.; Lindqwister, U. J.
1994-01-01
Data collected over six days from a worldwide Global Positioning System (GPS) tracking network during the Epoch '92 campaign are used to estimate variations of the Earth's pole position every 30 minutes.
DEFF Research Database (Denmark)
Pittalà, Fabio; Hauske, Fabian N.; Ye, Yabin
2012-01-01
Efficient channel estimation for signal equalization and OPM based on short CAZAC sequences with QPSK and 8PSK constellation formats is demonstrated in a 224-Gb/s PDM 16-QAM optical linear transmission system....
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...
Full information estimations of a system of simultaneous equations with error component structure
Balestra, Pietro; Krishnakumar, Jaya
1987-01-01
In this paper we develop full information methods for estimating the parameters of a system of simultaneous equations with error component struc-ture and establish relationships between the various structural estimat
Application of Joint Parameter Identification and State Estimation to a Fault-Tolerant Robot System
DEFF Research Database (Denmark)
Sun, Zhen; Yang, Zhenyu
2011-01-01
The joint parameter identification and state estimation technique is applied to develop a fault-tolerant space robot system. The potential faults in the considered system are abrupt parametric faults, which indicate that some system parameters will immediately deviate from their nominal values...
Estimating Rates of Fault Insertion and Test Effectiveness in Software Systems
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.
Power monitors: A framework for system-level power estimation using heterogeneous power models
Bansal, N.; Lahiri, K.; Raghunathan, A.; Chakradhar, S.T.
2005-01-01
Paper analysis early in the design cycle is critical for the design of low-power systems. With the move to system-level specifications and design methodologies, there has been significant research interest in system-level power estimation. However, as demonstrated in this paper, the addition of
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
Estimation of the Coefficient of Restitution of Rocking Systems by the Random Decrement Technique
DEFF Research Database (Denmark)
Brincker, Rune; Demosthenous, Milton; Manos, George C.
1994-01-01
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 obtain an estimate of the free rocking response from the measured random response using the Random Decrement (RDD) Technique, and then estimate the coefficient of restitution from this free response estimate. In the paper this approach is investigated by simulating the response of a single degree...
Duan, Chaowei; Zhan, Yafeng
2016-03-01
The output characteristics of a linear monostable system driven with a periodic signal and an additive white Gaussian noise are studied in this paper. Theoretical analysis shows that the output signal-to-noise ratio (SNR) decreases monotonously with the increasing noise intensity but the output SNR-gain is stable. Inspired by this high SNR-gain phenomenon, this paper applies the linear monostable system in the parameters estimation algorithm for phase shift keying (PSK) signals and improves the estimation performance.
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
A Study of Ship Acquisition Cost Estimating in the Naval Sea Systems Command. Appendices
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
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.
International Nuclear Information System (INIS)
Jeon, Woo Soo; Song, Ji Ho
2001-01-01
An expert system for estimation of fatigue properties from simple tensile data of material is developed, considering nearly all important estimation methods proposed so far, i.e., 7 estimation methods. The expert system is developed to utilize for the case of only hardness data available. The knowledge base is constructed with production rules and frames using an expert system shell, UNIK. Forward chaining is employed as a reasoning method. The expert system has three functions including the function to update the knowledge base. The performance of the expert system is tested using the 54 ε-N curves consisting of 381 ε-N data points obtained for 22 materials. It is found that the expert system developed has excellent performance especially for steel materials, and reasonably good for aluminum alloys
Distributed State Estimation Using a Modified Partitioned Moving Horizon Strategy for Power Systems.
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.
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.
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.
Channel estimation in few mode fiber mode division multiplexing transmission system
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.
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.
Nonlinear adaptive control system design with asymptotically stable parameter estimation error
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.
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.
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.
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
An adaptive state of charge estimation approach for lithium-ion series-connected battery system
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.
International Nuclear Information System (INIS)
Zeng, G.L.; Gullberg, G.T.
1995-01-01
It is common practice to estimate kinetic parameters from dynamically acquired tomographic data by first reconstructing a dynamic sequence of three-dimensional reconstructions and then fitting the parameters to time activity curves generated from the time-varying reconstructed images. However, in SPECT, the pharmaceutical distribution can change during the acquisition of a complete tomographic data set, which can bias the estimated kinetic parameters. It is hypothesized that more accurate estimates of the kinetic parameters can be obtained by fitting to the projection measurements instead of the reconstructed time sequence. Estimation from projections requires the knowledge of their relationship between the tissue regions of interest or voxels with particular kinetic parameters and the project measurements, which results in a complicated nonlinear estimation problem with a series of exponential factors with multiplicative coefficients. A technique is presented in this paper where the exponential decay parameters are estimated separately using linear time-invariant system theory. Once the exponential factors are known, the coefficients of the exponentials can be estimated using linear estimation techniques. Computer simulations demonstrate that estimation of the kinetic parameters directly from the projections is more accurate than the estimation from the reconstructed images
Blind Estimation of the Phase and Carrier Frequency Offsets for LDPC-Coded Systems
Directory of Open Access Journals (Sweden)
Houcke Sebastien
2010-01-01
Full Text Available Abstract We consider in this paper the problem of phase offset and Carrier Frequency Offset (CFO estimation for Low-Density Parity-Check (LDPC coded systems. We propose new blind estimation techniques based on the calculation and minimization of functions of the Log-Likelihood Ratios (LLR of the syndrome elements obtained according to the parity check matrix of the error-correcting code. In the first part of this paper, we consider phase offset estimation for a Binary Phase Shift Keying (BPSK modulation and propose a novel estimation technique. Simulation results show that the proposed method is very effective and outperforms many existing algorithms. Then, we modify the estimation criterion so that it can work for higher-order modulations. One interesting feature of the proposed algorithm when applied to high-order modulations is that the phase offset of the channel can be blindly estimated without any ambiguity. In the second part of the paper, we consider the problem of CFO estimation and propose estimation techniques that are based on the same concept as the ones presented for the phase offset estimation. The Mean Squared Error (MSE and Bit Error Rate (BER curves show the efficiency of the proposed estimation techniques.
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.
A model-based initial guess for estimating parameters in systems of ordinary differential equations.
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.
Directory of Open Access Journals (Sweden)
José Eduardo Boffino de Almeida Monteiro
2013-02-01
Full Text Available The objective of this work was to evaluate an estimation system for rice yield in Brazil, based on simple agrometeorological models and on the technological level of production systems. This estimation system incorporates the conceptual basis proposed by Doorenbos & Kassam for potential and attainable yields with empirical adjusts for maximum yield and crop sensitivity to water deficit, considering five categories of rice yield. Rice yield was estimated from 2000/2001 to 2007/2008, and compared to IBGE yield data. Regression analyses between model estimates and data from IBGE surveys resulted in significant coefficients of determination, with less dispersion in the South than in the North and Northeast regions of the country. Index of model efficiency (E1' ranged from 0.01 in the lower yield classes to 0.45 in higher ones, and mean absolute error ranged from 58 to 250 kg ha‑1, respectively.
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)
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.
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
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%.
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.
Organic MEMS/NEMS-based high-efficiency 3D ITO-less flexible photovoltaic cells
International Nuclear Information System (INIS)
Kassegne, Sam; Moon, Kee; Martín-Ramos, Pablo; Majzoub, Mohammad; Őzturk, Gunay; Desai, Krishna; Parikh, Mihir; Nguyen, Bao; Khosla, Ajit; Chamorro-Posada, Pedro
2012-01-01
A novel approach based on three-dimensional (3D) architecture for polymeric photovoltaic cells made up of an array of sub-micron and nano-pillars which not only increase the area of the light absorbing surface, but also improve the carrier collection efficiency of bulk-heterojunction organic solar cells is presented. The approach also introduces coating of 3D anodes with a new solution-processable highly conductive transparent polymer (Orgacon™) that replaces expensive vacuum-deposited ITO (indium tin oxide) as well as the additional hole-collecting layer of conventional PEDOT:PSS (poly(3,4-ethylenedioxythiophene) poly(styrenesulfonate)). In addition, the described procedure is well suited to roll-to-roll high-throughput manufacturing. The high aspect-ratio 3D pillars which form the basis for this new architecture are patterned through micro-electromechanical-system- and nano-electromechanical-system-based processes. For the particular case of P3HT (poly(3-hexylthiophene)) and PCBM (phenyl-C61-butyric acid methyl ester) active material, efficiencies in excess of 6% have been achieved for these photovoltaic cells of 3D architecture using ITO-less flexible PET (polyethylene terephthalate) substrates. This increase in efficiency turns out to be more than twice higher than those achieved for their 2D counterparts. (paper)
International Nuclear Information System (INIS)
Duan, Chaowei; Zhan, Yafeng
2016-01-01
The output characteristics of a linear monostable system driven with a periodic signal and an additive white Gaussian noise are studied in this paper. Theoretical analysis shows that the output signal-to-noise ratio (SNR) decreases monotonously with the increasing noise intensity but the output SNR-gain is stable. Inspired by this high SNR-gain phenomenon, this paper applies the linear monostable system in the parameters estimation algorithm for phase shift keying (PSK) signals and improves the estimation performance. - Highlights: • The response of a linear monostable system driven with a periodic signal and an additive white Gaussian noise is analyzed. • The optimal parameter of this linear monostable system to maximum the output SNR-gain is obtained. • Application of this linear monostable system in parameters estimation algorithm for PSK signals obtains performance improvement.
Generalized synchronization-based multiparameter estimation in modulated time-delayed systems
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.
Buzağılarda Preruminant Dönem Beslenmesinin Rumen Gelişimi Üzerine Etkisi
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...
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
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.
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.
Exact dimension estimation of interacting qubit systems assisted by a single quantum probe
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.
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
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.
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.
Sauer, Ann Goding; Liu, Benmei; Siegel, Rebecca L; Jemal, Ahmedin; Fedewa, Stacey A
2018-01-01
Cancer screening prevalence from the Behavioral Risk Factor Surveillance System (BRFSS), designed to provide state-level estimates, and the National Health Interview Survey (NHIS), designed to provide national estimates, are used to measure progress in cancer control. A detailed description of the extent to which recent cancer screening estimates vary by key demographic characteristics has not been previously described. We examined national prevalence estimates for recommended breast, cervical, and colorectal cancer screening using data from the 2012 and 2014 BRFSS and the 2010 and 2013 NHIS. Treating the NHIS estimates as the reference, direct differences (DD) were calculated by subtracting NHIS estimates from BRFSS estimates. Relative differences were computed by dividing the DD by the NHIS estimates. Two-sample t-tests (2-tails), were performed to test for statistically significant differences. BRFSS screening estimates were higher than those from NHIS for breast (78.4% versus 72.5%; DD=5.9%, pNHIS, each survey has a unique and important role in providing information to track cancer screening utilization among various populations. Awareness of these differences and their potential causes is important when comparing the surveys and determining the best application for each data source. Copyright © 2017 Elsevier Inc. All rights reserved.
An Application of UAV Attitude Estimation Using a Low-Cost Inertial Navigation System
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.
Vilnrotter, V. A.; Rodemich, E. R.
1994-01-01
An algorithm for estimating the optimum combining weights for the Ka-band (33.7-GHz) array feed compensation system was developed and analyzed. The input signal is assumed to be broadband radiation of thermal origin, generated by a distant radio source. Currently, seven video converters operating in conjunction with the real-time correlator are used to obtain these weight estimates. The algorithm described here requires only simple operations that can be implemented on a PC-based combining system, greatly reducing the amount of hardware. Therefore, system reliability and portability will be improved.
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
State Estimation for Linear Systems Driven Simultaneously by Wiener and Poisson Processes.
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
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...
Wheeled vehicle deceleration as estimation parameter of adaptive brake control system state
Directory of Open Access Journals (Sweden)
Turenko A.
2012-06-01
Full Text Available The method of stability estimation of adaptive control system with signal adjustment based on Lyapunov’s direct method that allows to take into account the nonstationarity of the basic system and non-linearity in the form of limitation on control action restriction as well as error control is stated.
ONE OF APPROACHES TO THE ESTIMATION OF FIRMNESS OF TRAFFIC CONTROL SYSTEMS OF MOTOR TRANSPORT
Directory of Open Access Journals (Sweden)
D. Labenko
2009-01-01
Full Text Available The control system of locomotive objects and its description is considered. One of approaches concerning the basic index of control systems estimation – the probability of system’s functioning with the set quality in conditions of various influence on its elements is offered.
Estimation and prediction of convection-diffusion-reaction systems from point measurement
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
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.
Energy Technology Data Exchange (ETDEWEB)
Souza, Andre Nunes de; Silva, Ivan Nunes da; Ulson, Jose Alfredo C.; Zago, Maria Goretti [UNESP, Bauru, SP (Brazil). Dept. de Engenharia Eletrica]. E-mail: andrejau@bauru.unesp.br
2001-07-01
This paper describes a novel approach for mapping characteristics of grounding systems using artificial neural networks. The network acts as identifier of structural features of the grounding processes. So that output parameters can be estimated and generalized from an input parameter set. The results obtained by the network are compared with other approaches also used to model grounding systems concerning lightning. (author)
Perceptual and Acoustic Reliability Estimates for the Speech Disorders Classification System (SDCS)
Shriberg, Lawrence D.; Fourakis, Marios; Hall, Sheryl D.; Karlsson, Heather B.; Lohmeier, Heather L.; McSweeny, Jane L.; Potter, Nancy L.; Scheer-Cohen, Alison R.; Strand, Edythe A.; Tilkens, Christie M.; Wilson, David L.
2010-01-01
A companion paper describes three extensions to a classification system for paediatric speech sound disorders termed the Speech Disorders Classification System (SDCS). The SDCS uses perceptual and acoustic data reduction methods to obtain information on a speaker's speech, prosody, and voice. The present paper provides reliability estimates for…
Linear regressive model structures for estimation and prediction of compartmental diffusive systems
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
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
Estimation of Multiple Point Sources for Linear Fractional Order Systems Using Modulating Functions
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.
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
International Nuclear Information System (INIS)
Zhao, Chao; Vu, Quoc Dong; Li, Pu
2013-01-01
A three-stage computation framework for solving parameter estimation problems for dynamic systems with multiple data profiles is developed. The dynamic parameter estimation problem is transformed into a nonlinear programming (NLP) problem by using collocation on finite elements. The model parameters to be estimated are treated in the upper stage by solving an NLP problem. The middle stage consists of multiple NLP problems nested in the upper stage, representing the data reconciliation step for each data profile. We use the quasi-sequential dynamic optimization approach to solve these problems. In the lower stage, the state variables and their gradients are evaluated through ntegrating the model equations. Since the second-order derivatives are not required in the computation framework this proposed method will be efficient for solving nonlinear dynamic parameter estimation problems. The computational results obtained on a parameter estimation problem for two CSTR models demonstrate the effectiveness of the proposed approach
Joint channel/frequency offset estimation and correction for coherent optical FBMC/OQAM system
Wang, Daobin; Yuan, Lihua; Lei, Jingli; wu, Gang; Li, Suoping; Ding, Runqi; Wang, Dongye
2017-12-01
In this paper, we focus on analysis of the preamble-based joint estimation for channel and laser-frequency offset (LFO) in coherent optical filter bank multicarrier systems with offset quadrature amplitude modulation (CO-FBMC/OQAM). In order to reduce the noise impact on the estimation accuracy, we proposed an estimation method based on inter-frame averaging. This method averages the cross-correlation function of real-valued pilots within multiple FBMC frames. The laser-frequency offset is estimated according to the phase of this average. After correcting LFO, the final channel response is also acquired by averaging channel estimation results within multiple frames. The principle of the proposed method is analyzed theoretically, and the preamble structure is thoroughly designed and optimized to suppress the impact of inherent imaginary interference (IMI). The effectiveness of our method is demonstrated numerically using different fiber and LFO values. The obtained results show that the proposed method can improve transmission performance significantly.
Energy Technology Data Exchange (ETDEWEB)
Zhao, Chao [FuZhou University, FuZhou (China); Vu, Quoc Dong; Li, Pu [Ilmenau University of Technology, Ilmenau (Germany)
2013-02-15
A three-stage computation framework for solving parameter estimation problems for dynamic systems with multiple data profiles is developed. The dynamic parameter estimation problem is transformed into a nonlinear programming (NLP) problem by using collocation on finite elements. The model parameters to be estimated are treated in the upper stage by solving an NLP problem. The middle stage consists of multiple NLP problems nested in the upper stage, representing the data reconciliation step for each data profile. We use the quasi-sequential dynamic optimization approach to solve these problems. In the lower stage, the state variables and their gradients are evaluated through ntegrating the model equations. Since the second-order derivatives are not required in the computation framework this proposed method will be efficient for solving nonlinear dynamic parameter estimation problems. The computational results obtained on a parameter estimation problem for two CSTR models demonstrate the effectiveness of the proposed approach.
2D-DOA and Mutual Coupling Estimation in Vehicle Communication System via Conformal Array
Directory of Open Access Journals (Sweden)
Yan Zou
2015-01-01
Full Text Available Many direction-of-arrival (DOA estimation algorithms have been proposed recently. However, the effect of mutual coupling among antenna elements has not been taken into consideration. In this paper, a novel DOA and mutual coupling coefficient estimation algorithm is proposed in intelligent transportation systems (ITS via conformal array. By constructing the spectial mutual coupling matrix (MCM, the effect of mutual coupling can be eliminated via instrumental element method. Then the DOA of incident signals can be estimated based on parallel factor (PARAFAC theory. The PARAFAC model is constructed in cumulant domain using covariance matrices. The mutual coupling coefficients are estimated based on the former DOA estimation and the matrix transformation between MCM and the steering vector. Finally, due to the drawback of the parameter pairing method in Wan et al., 2014, a novel method is given to improve the performance of parameter pairing. The computer simulation verifies the effectiveness of the proposed algorithm.
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.
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.
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.
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.
Energy Technology Data Exchange (ETDEWEB)
Carranza, O. [Escuela Superior de Computo, Instituto Politecnico Nacional, Av. Juan de Dios Batiz S/N, Col. Lindavista, Del. Gustavo A. Madero 7738, D.F. (Mexico); Figueres, E.; Garcera, G. [Grupo de Sistemas Electronicos Industriales, Departamento de Ingenieria Electronica, Universidad Politecnica de Valencia, Camino de Vera S/N, 7F, 46020 Valencia (Spain); Gonzalez, L.G. [Departamento de Ingenieria Electronica, Universidad de los Andes, Merida (Venezuela)
2011-03-15
This paper presents a comparative study of several speed estimators to implement a sensorless speed control loop in Wind Energy Generation Systems driven by power factor correction three-phase boost rectifiers. This rectifier topology reduces the low frequency harmonics contents of the generator currents and, consequently, the generator power factor approaches unity whereas undesired vibrations of the mechanical system decrease. For implementation of the speed estimators, the compared techniques start from the measurement of electrical variables like currents and voltages, which contain low frequency harmonics of the fundamental frequency of the wind generator, as well as switching frequency components due to the boost rectifier. In this noisy environment it has been analyzed the performance of the following estimation techniques: Synchronous Reference Frame Phase Locked Loop, speed reconstruction by measuring the dc current and voltage of the rectifier and speed estimation by means of both an Extended Kalman Filter and a Linear Kalman Filter. (author)
SBML-PET-MPI: a parallel parameter estimation tool for Systems Biology Markup Language based models.
Zi, Zhike
2011-04-01
Parameter estimation is crucial for the modeling and dynamic analysis of biological systems. However, implementing parameter estimation is time consuming and computationally demanding. Here, we introduced a parallel parameter estimation tool for Systems Biology Markup Language (SBML)-based models (SBML-PET-MPI). SBML-PET-MPI allows the user to perform parameter estimation and parameter uncertainty analysis by collectively fitting multiple experimental datasets. The tool is developed and parallelized using the message passing interface (MPI) protocol, which provides good scalability with the number of processors. SBML-PET-MPI is freely available for non-commercial use at http://www.bioss.uni-freiburg.de/cms/sbml-pet-mpi.html or http://sites.google.com/site/sbmlpetmpi/.
Algorithms of estimation for nonlinear systems a differential and algebraic viewpoint
Martínez-Guerra, Rafael
2017-01-01
This book acquaints readers with recent developments in dynamical systems theory and its applications, with a strong focus on the control and estimation of nonlinear systems. Several algorithms are proposed and worked out for a set of model systems, in particular so-called input-affine or bilinear systems, which can serve to approximate a wide class of nonlinear control systems. These can either take the form of state space models or be represented by an input-output equation. The approach taken here further highlights the role of modern mathematical and conceptual tools, including differential algebraic theory, observer design for nonlinear systems and generalized canonical forms.
Pasma, J.H.; Kordelaar, J. van; Kam, D. de; Weerdesteyn, V.G.M.; Schouten, A.C.; Kooij, H. van der
2017-01-01
BACKGROUND: Closed loop system identification (CLSIT) is a method to disentangle the contribution of underlying systems in standing balance. We investigated whether taking into account lower leg muscle activation in CLSIT could improve the reliability and accuracy of estimated parameters identifying
Pasma, J. H.; Van Kordelaar, J.; de Kam, D.; Weerdesteyn, V.; Schouten, A. C.; Van Der Kooij, H.
2017-01-01
Background: Closed loop system identification (CLSIT) is a method to disentangle the contribution of underlying systems in standing balance. We investigated whether taking into account lower leg muscle activation in CLSIT could improve the reliability and accuracy of estimated parameters identifying
Pasma, J.H.; van Kordelaar, J.; de Kam, D.; Weerdesteyn, V.; Schouten, A.C.; van der Kooij, H.
2017-01-01
Background: Closed loop system identification (CLSIT) is a method to disentangle the contribution of underlying systems in standing balance. We investigated whether taking into account lower leg muscle activation in CLSIT could improve the reliability and accuracy of estimated parameters
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.
Enthalpy estimation for thermal comfort and energy saving in air conditioning system
International Nuclear Information System (INIS)
Chu, C.-M.; Jong, T.-L.
2008-01-01
The thermal comfort control of a room must consider not only the thermal comfort level but also energy saving. This paper proposes an enthalpy estimation that is conducive for thermal comfort control and energy saving. The least enthalpy estimator (LEE) combines the concept of human thermal comfort with the theory of enthalpy to predict the load for a suitable setting pair in order to maintain more precisely the thermal comfort level and save energy in the air conditioning system
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
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
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.
Estimation of presampling MTF in CR systems by using direct fluorescence and its problems
International Nuclear Information System (INIS)
Ono, Kitahei; Inatsu, Hiroshi; Harao, Mototsugu; Itonaga, Haruo; Miyamoto, Hideyuki
2001-01-01
We proposed a method for practical estimation of the presampling modulation transfer function (MTF) of a computed radiography (CR) system by using the MTFs of an imaging plate and the sampling aperture. The MTFs of three imaging plates (GP-25, ST-VN, and RP-1S) with different photostimulable phosphors were measured by using direct fluorescence (the light emitted instantaneously by x-ray exposure), and the presampling MTFs were estimated from these imaging plate MTFs and the sampling aperture MTF. Our results indicated that for imaging plate RP-1S the measured presampling MTF was significantly superior to the estimated presampling MTF at any spatial frequency. This was because the estimated presampling MTF was degraded by the diffusion of direct fluorescence in the protective layer of the imaging plate's surface. Therefore, when the presampling MTF of the imaging plate with a thick protective layer is estimated, correction for the thickness of the protective layer should be carried out. However, the estimated presampling MTF of imaging plates with a thin protective layer were almost the same as the measured presampling MTF, except in the high spatial frequency range. Therefore, we consider this estimation method to be useful and practical, because the spatial resolution property of a CR system can be obtained simply from the imaging plate MTF measured with direct fluorescence. (author)
Directory of Open Access Journals (Sweden)
Dongwoo Jang
2018-03-01
Full Text Available Leaks in a water distribution network (WDS constitute losses of water supply caused by pipeline failure, operational loss, and physical factors. This has raised the need for studies on the factors affecting the leakage ratio and estimation of leakage volume in a water supply system. In this study, principal component analysis (PCA and artificial neural network (ANN were used to estimate the volume of water leakage in a WDS. For the study, six main effective parameters were selected and standardized data obtained through the Z-score method. The PCA-ANN model was devised and the leakage ratio was estimated. An accuracy assessment was performed to compare the measured leakage ratio to that of the simulated model. The results showed that the PCA-ANN method was more accurate for estimating the leakage ratio than a single ANN simulation. In addition, the estimation results differed according to the number of neurons in the ANN model’s hidden layers. In this study, an ANN with multiple hidden layers was found to be the best method for estimating the leakage ratio with 12–12 neurons. This suggested approaches to improve the accuracy of leakage ratio estimation, as well as a scientific approach toward the sustainable management of water distribution systems.
DEFF Research Database (Denmark)
Tranberg-Hansen, Anders Sejer; Madsen, Jan
2009-01-01
This paper presents the application of a compositional simulation based system-level performance estimation framework on a non-trivial industrial case study. The case study is provided by the Danish company Bang & Olufsen ICEpower a/s and focuses on the exploration of a digital mobile audio...... processing platform. A short overview of the compositional performance estimation framework used is given followed by a presentation of how it is used for performance estimation using an iterative refinement process towards the final implementation. Finally, an evaluation in terms of accuracy and speed...
Fractional-order adaptive fault estimation for a class of nonlinear fractional-order systems
N'Doye, Ibrahima; Laleg-Kirati, Taous-Meriem
2015-01-01
This paper studies the problem of fractional-order adaptive fault estimation for a class of fractional-order Lipschitz nonlinear systems using fractional-order adaptive fault observer. Sufficient conditions for the asymptotical convergence of the fractional-order state estimation error, the conventional integer-order and the fractional-order faults estimation error are derived in terms of linear matrix inequalities (LMIs) formulation by introducing a continuous frequency distributed equivalent model and using an indirect Lyapunov approach where the fractional-order α belongs to 0 < α < 1. A numerical example is given to demonstrate the validity of the proposed approach.
Fractional-order adaptive fault estimation for a class of nonlinear fractional-order systems
N'Doye, Ibrahima
2015-07-01
This paper studies the problem of fractional-order adaptive fault estimation for a class of fractional-order Lipschitz nonlinear systems using fractional-order adaptive fault observer. Sufficient conditions for the asymptotical convergence of the fractional-order state estimation error, the conventional integer-order and the fractional-order faults estimation error are derived in terms of linear matrix inequalities (LMIs) formulation by introducing a continuous frequency distributed equivalent model and using an indirect Lyapunov approach where the fractional-order α belongs to 0 < α < 1. A numerical example is given to demonstrate the validity of the proposed approach.
Particle Filtering for Multiple Access DS/CDMA Systems DS/CDMA Channel Estimation
Directory of Open Access Journals (Sweden)
Rafael Oliveira Ribeiro
2013-09-01
Full Text Available This article discusses computational implementation aspects and performance of a Bayesian methodology, namely particle filter (PF. The PF channel estimation technique is directly applied to the channel coefficients estimation of DS/CDMA systems. Simulation results for non-line-of-sight (NLOS Rayleigh fading channel propagation have indicated that the bootstrap PF estimator is capable to provide RMSE in the range of [10-3 ; 10-2] for a wide range of multiple access interference (MAI levels and signal-noise ratio (SNR, and still be able to offer robustness to near-far ratio (NFR effect.
Robust stability and ℋ ∞ -estimation for uncertain discrete systems with state-delay
Directory of Open Access Journals (Sweden)
Mahmoud Magdi S.
2001-01-01
Full Text Available In this paper, we investigate the problems of robust stability and ℋ ∞ -estimation for a class of linear discrete-time systems with time-varying norm-bounded parameter uncertainty and unknown state-delay. We provide complete results for robust stability with prescribed performance measure and establish a version of the discrete Bounded Real Lemma. Then, we design a linear estimator such that the estimation error dynamics is robustly stable with a guaranteed ℋ ∞ -performance irrespective of the parameteric uncertainties and unknown state delays. A numerical example is worked out to illustrate the developed theory.
Zhang, Ke; Jiang, Bin; Shi, Peng
2017-02-01
In this paper, a novel adjustable parameter (AP)-based distributed fault estimation observer (DFEO) is proposed for multiagent systems (MASs) with the directed communication topology. First, a relative output estimation error is defined based on the communication topology of MASs. Then a DFEO with AP is constructed with the purpose of improving the accuracy of fault estimation. Based on H ∞ and H 2 with pole placement, multiconstrained design is given to calculate the gain of DFEO. Finally, simulation results are presented to illustrate the feasibility and effectiveness of the proposed DFEO design with AP.
Savaux, Vincent
2014-01-01
This book presents an algorithm for the detection of an orthogonal frequency division multiplexing (OFDM) signal in a cognitive radio context by means of a joint and iterative channel and noise estimation technique. Based on the minimum mean square criterion, it performs an accurate detection of a user in a frequency band, by achieving a quasi-optimal channel and noise variance estimation if the signal is present, and by estimating the noise level in the band if the signal is absent. Organized into three chapters, the first chapter provides the background against which the system model is pr
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
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
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
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
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.
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
Secure Fusion Estimation for Bandwidth Constrained Cyber-Physical Systems Under Replay Attacks.
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.
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.
Suin Kim; Kyongkwan Ro; Joonbum Bae
2017-01-01
Although various kinds of methodologies have been suggested to estimate individual muscular forces, many of them require a costly measurement system accompanied by complex preprocessing and postprocessing procedures. In this research, a simple wearable sensor system was developed, combined with the inverse dynamics-based static optimization method. The suggested method can be set up easily and can immediately convert motion information into muscular forces. The proposed sensor system consiste...
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)
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.
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...
Estimating the time evolution of NMR systems via a quantum-speed-limit-like expression
Villamizar, D. V.; Duzzioni, E. I.; Leal, A. C. S.; Auccaise, R.
2018-05-01
Finding the solutions of the equations that describe the dynamics of a given physical system is crucial in order to obtain important information about its evolution. However, by using estimation theory, it is possible to obtain, under certain limitations, some information on its dynamics. The quantum-speed-limit (QSL) theory was originally used to estimate the shortest time in which a Hamiltonian drives an initial state to a final one for a given fidelity. Using the QSL theory in a slightly different way, we are able to estimate the running time of a given quantum process. For that purpose, we impose the saturation of the Anandan-Aharonov bound in a rotating frame of reference where the state of the system travels slower than in the original frame (laboratory frame). Through this procedure it is possible to estimate the actual evolution time in the laboratory frame of reference with good accuracy when compared to previous methods. Our method is tested successfully to predict the time spent in the evolution of nuclear spins 1/2 and 3/2 in NMR systems. We find that the estimated time according to our method is better than previous approaches by up to four orders of magnitude. One disadvantage of our method is that we need to solve a number of transcendental equations, which increases with the system dimension and parameter discretization used to solve such equations numerically.
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.
Hughes, J. D.; Metz, P. A.
2014-12-01
Most watershed studies include observation-based water budget analyses to develop first-order estimates of significant flow terms. Surface-water/groundwater (SWGW) exchange is typically assumed to be equal to the residual of the sum of inflows and outflows in a watershed. These estimates of SWGW exchange, however, are highly uncertain as a result of the propagation of uncertainty inherent in the calculation or processing of the other terms of the water budget, such as stage-area-volume relations, and uncertainties associated with land-cover based evapotranspiration (ET) rate estimates. Furthermore, the uncertainty of estimated SWGW exchanges can be magnified in large wetland systems that transition from dry to wet during wet periods. Although it is well understood that observation-based estimates of SWGW exchange are uncertain it is uncommon for the uncertainty of these estimates to be directly quantified. High-level programming languages like Python can greatly reduce the effort required to (1) quantify the uncertainty of estimated SWGW exchange in large wetland systems and (2) evaluate how different approaches for partitioning land-cover data in a watershed may affect the water-budget uncertainty. We have used Python with the Numpy, Scipy.stats, and pyDOE packages to implement an unconstrained Monte Carlo approach with Latin Hypercube sampling to quantify the uncertainty of monthly estimates of SWGW exchange in the Floral City watershed of the Tsala Apopka wetland system in west-central Florida, USA. Possible sources of uncertainty in the water budget analysis include rainfall, ET, canal discharge, and land/bathymetric surface elevations. Each of these input variables was assigned a probability distribution based on observation error or spanning the range of probable values. The Monte Carlo integration process exposes the uncertainties in land-cover based ET rate estimates as the dominant contributor to the uncertainty in SWGW exchange estimates. We will discuss
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
Errors in the estimation method for the rejection of vibrations in adaptive optics systems
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.
International Nuclear Information System (INIS)
1993-01-01
This Working Material provides a review of methodologies for estimating the costs of renewable energy systems and the state of art knowledge on stochastic features and economic evaluation methodologies of renewable energy systems for electricity generation in a grid integrated system. It is expected that this material facilitates the wider access by interested persons to sources for relevant comparative assessment activities which are progressing in the IAEA. Refs, figs, tabs
Parameter estimation for chaotic systems with a Drift Particle Swarm Optimization method
International Nuclear Information System (INIS)
Sun Jun; Zhao Ji; Wu Xiaojun; Fang Wei; Cai Yujie; Xu Wenbo
2010-01-01
Inspired by the motion of electrons in metal conductors in an electric field, we propose a variant of Particle Swarm Optimization (PSO), called Drift Particle Swarm Optimization (DPSO) algorithm, and apply it in estimating the unknown parameters of chaotic dynamic systems. The principle and procedure of DPSO are presented, and the algorithm is used to identify Lorenz system and Chen system. The experiment results show that for the given parameter configurations, DPSO can identify the parameters of the systems accurately and effectively, and it may be a promising tool for chaotic system identification as well as other numerical optimization problems in physics.
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)
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.
International Nuclear Information System (INIS)
Sjoreen, A.L.
1995-01-01
The Hazard Assessment System for Consequence Analysis (HASCAL) is being developed to support the analysis of radiological incidents anywhere in the world for the Defense Nuclear Agency (DNA). HASCAL is a component of the Hazard Prediction and Assessment Capability (HPAC), which is a comprehensive nuclear, biological, and chemical hazard effects planning and forecasting modeling system that is being developed by DNA. HASCAL computes best-guess estimates of the consequences of radiological incidents. HASCAL estimates the amount of radioactivity released, its atmospheric transport and deposition, and the resulting radiological doses
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
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
Forecasting overhaul or replacement intervals based on estimated system failure intensity
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.
Directory of Open Access Journals (Sweden)
A. Elsonbaty
2014-10-01
Full Text Available In this article, the adaptive chaos synchronization technique is implemented by an electronic circuit and applied to the hyperchaotic system proposed by Chen et al. We consider the more realistic and practical case where all the parameters of the master system are unknowns. We propose and implement an electronic circuit that performs the estimation of the unknown parameters and the updating of the parameters of the slave system automatically, and hence it achieves the synchronization. To the best of our knowledge, this is the first attempt to implement a circuit that estimates the values of the unknown parameters of chaotic system and achieves synchronization. The proposed circuit has a variety of suitable real applications related to chaos encryption and cryptography. The outputs of the implemented circuits and numerical simulation results are shown to view the performance of the synchronized system and the proposed circuit.
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.
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.
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.
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.
A practical model for pressure probe system response estimation (with review of existing models)
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.
Guideline for Bayesian Net based Software Fault Estimation Method for Reactor Protection System
International Nuclear Information System (INIS)
Eom, Heung Seop; Park, Gee Yong; Jang, Seung Cheol
2011-01-01
The purpose of this paper is to provide a preliminary guideline for the estimation of software faults in a safety-critical software, for example, reactor protection system's software. As the fault estimation method is based on Bayesian Net which intensively uses subjective probability and informal data, it is necessary to define formal procedure of the method to minimize the variability of the results. The guideline describes assumptions, limitations and uncertainties, and the product of the fault estimation method. The procedure for conducting a software fault-estimation method is then outlined, highlighting the major tasks involved. The contents of the guideline are based on our own experience and a review of research guidelines developed for a PSA
Field Evaluation of the System Identification Approach for Tension Estimation of External Tendons
Directory of Open Access Journals (Sweden)
Myung-Hyun Noh
2015-01-01
Full Text Available Various types of external tendons are considered to verify the applicability of tension estimation method based on the finite element model with system identification technique. The proposed method is applied to estimate the tension of benchmark numerical example, model structure, and field structure. The numerical and experimental results show that the existing methods such as taut string theory and linear regression method show large error in the estimated tension when the condition of external tendon is different with the basic assumption used during the derivation of relationship between tension and natural frequency. However, the proposed method gives reasonable results for all of the considered external tendons in this study. Furthermore, the proposed method can evaluate the accuracy of estimated tension indirectly by comparing the measured and calculated natural frequencies. Therefore, the proposed method can be effectively used for field application of various types of external tendons.
A Novel Comb-Pilot Transform Domain Frequency Diversity Channel Estimation for OFDM System
Directory of Open Access Journals (Sweden)
L. Liu
2009-12-01
Full Text Available Due to implementation complexity, the transform domain channel estimation based on training symbols or comb-type pilots has been paid more attention because of its efficient algorithm FFT/IFFT. However, in a comb-type OFDM system, the length of the channel impulse response is much smaller than the pilot number. In this case, the comb-pilot transform domain channel estimation only works as interpolation like the Least Squares (LS algorithm, but loses the noise suppression function. In this paper, we propose a novel frequency diversity channel estimation method via grouped pilots combining. With this estimator, not only the channel frequency response on non-pilot subcarriers can be interpolated, but also the noise can be better suppressed. Moreover, it does not need prior statistical characteristics of the wireless channel.
PERFORMANCE OF THE ZERO FORCING PRECODING MIMO BROADCAST SYSTEMS WITH CHANNEL ESTIMATION ERRORS
Institute of Scientific and Technical Information of China (English)
Wang Jing; Liu Zhanli; Wang Yan; You Xiaohu
2007-01-01
In this paper, the effect of channel estimation errors upon the Zero Forcing (ZF) precoding Multiple Input Multiple Output Broadcast (MIMO BC) systems was studied. Based on the two kinds of Gaussian estimation error models, the performance analysis is conducted under different power allocation strategies. Analysis and simulation show that if the covariance of channel estimation errors is independent of the received Signal to Noise Ratio (SNR), imperfect channel knowledge deteriorates the sum capacity and the Bit Error Rate (BER) performance severely. However, under the situation of orthogonal training and the Minimum Mean Square Error (MMSE) channel estimation, the sum capacity and BER performance are consistent with those of the perfect Channel State Information (CSI)with only a performance degradation.
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.
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.
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.
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 Channel Estimation and Pilot Contamination Analysis for Massive MIMO-OFDM Systems
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.
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
Determination of power system component parameters using nonlinear dead beat estimation method
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
Modulation transfer function estimation of optical lens system by adaptive neuro-fuzzy methodology
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.
Model calibration and parameter estimation for environmental and water resource systems
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...
Zhu, Xiaoyuan; Zhang, Hui; Yang, Bo; Zhang, Guichen
2018-01-01
In order to improve oscillation damping control performance as well as gear shift quality of electric vehicle equipped with integrated motor-transmission system, a cloud-based shaft torque estimation scheme is proposed in this paper by using measurable motor and wheel speed signals transmitted by wireless network. It can help reduce computational burden of onboard controllers and also relief network bandwidth requirement of individual vehicle. Considering possible delays during signal wireless transmission, delay-dependent full-order observer design is proposed to estimate the shaft torque in cloud server. With these random delays modeled by using homogenous Markov chain, robust H∞ performance is adopted to minimize the effect of wireless network-induced delays, signal measurement noise as well as system modeling uncertainties on shaft torque estimation error. Observer parameters are derived by solving linear matrix inequalities, and simulation results using acceleration test and tip-in, tip-out test demonstrate the effectiveness of proposed shaft torque observer design.
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.
Discrete-time state estimation for stochastic polynomial systems over polynomial observations
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.