Synchronous Machine Steady-State Parameter Estimation Using Neural Networks

2004 ◽  
Vol 19 (2) ◽  
pp. 237-244 ◽  
Author(s):  
M. Calvo ◽  
O.P. Malik
Keyword(s):  
Neural Networks ◽  
Parameter Estimation ◽  
Steady State ◽  
State Parameter ◽  
Synchronous Machine ◽  
Steady State Parameter

Steady-state parameter estimation of an experimental vapour compression refrigeration plant

2016 ◽  
Author(s):  
David Rodriguez ◽  
Jose A. Alfaya ◽  
Guillermo Bejarano ◽  
Manuel G. Ortega ◽  
F. Castano
Keyword(s):  
Parameter Estimation ◽  
Steady State ◽  
State Parameter ◽  
Vapour Compression ◽  
Steady State Parameter

scholarly journals Parameter Selection in the Parameter Estimation of Grade Transitions in a Polyethylene Plant

2015 ◽  
Vol 3 (1) ◽  
pp. 1
Author(s):  
Niklas Andersson ◽  
Per-Ola Larsson ◽  
Johan Åkesson ◽  
Niclas Carlsson ◽  
Staffan Skålén ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
Steady State ◽  
State Parameter ◽  
Parameter Selection ◽  
Selection Algorithm ◽  
Parameter Estimations ◽  
Dynamic Case ◽  
Nominal Parameter ◽  
Best Parameter ◽  
Parameter Values

A polyethylene plant at Borealis AB is modelled in the Modelica language and considered for parameter estimations at grade transitions. Parameters have been estimated for both the steady-state and the dynamic case using the JModelica.org platform, which offers tools for steady-state parameter estimation and supports simulation with parameter sensitivies. The model contains 31 candidate parameters, giving a huge amount of possible parameter combinations. The best parameter sets have been chosen using a parameter-selection algorithm that identified parameter sets with poor numerical properties. The parameter-selection algorithm reduces the number of parameter sets that is necessary to explore. The steady-state differs from the dynamic case with respect to parameter selection. Validations of the parameter estimations in the dynamic case show a significant reduction in an objective value used to evaluate the quality of the solution from that of the nominal reference, where the nominal parameter values are used.

Calculation of Steady State Parameter in Permanent Magnet Linear Synchronous Motors by Analysis Method and FEM

2014 ◽  
Vol 926-930 ◽  
pp. 860-863
Author(s):  
Ming Jie Wang ◽  
Zheng Xiang Ma
Keyword(s):  
Steady State ◽  
Permanent Magnet ◽  
State Parameter ◽  
Synchronous Motor ◽  
Analysis Method ◽  
The Finite Element Method ◽  
Synchronous Motors ◽  
Steady State Operation ◽  
Linear Synchronous Motors ◽  
Steady State Parameter

The steady state parameters of permanent magnet linear synchronous motor (PMLSM) has an important influence on the performance of the motor. Based on a linear permanent magnet horizontal motion synchronous motor, the paper adopts multi-layered model method to give the formulas of the air-gap flux density that the permanent magnet and armature winding act on alone, no-load back electromotive force, the thrust force in steady-state operation and vector control of thrust in the dq model equation, then compute the value of these parameters according to the formulas, and the finite element method (FEM) to each parameter is validated, the simulation curve is given, the experimental value is also done to prove the exactness of the two methods.

scholarly journals Potensi Ekologi Bulu Babi di Pelita Jaya dan Pulau Osi Kabupaten Seram Bagian Barat

2020 ◽  
Vol 13 (1) ◽  
pp. 46
Author(s):  
Yona A. Lewerissa ◽  
Degen E. Kalay
Keyword(s):  
Steady State ◽  
State Parameter ◽  
Steady State Parameter ◽  
Diadema Setosum

Bulu babi (echinoidae) adalah salah satu sumberdaya perikanan bernilai ekonomis penting dengan permintaan pasar yang cukup tinggi di Asia, Eropa dan Amerika.  Permintaan pasar akan sumberdaya ini dari tahun ke tahun semakin meningkat, akibatnya tingkat pemanfaatan dipacu untuk mencukupi kebutuhan tersebut. Metode pemanfaatan yang banyak dilakukan masyarakat adalah pengambilan hasil produksi dari alam. Tujuan dari penelitian ini adalah menganalisa kepadatan, , Potensi/kelimpahan, frekuensi kehadiran, dan indeks ekologi serta mengkaji kondisi kualitas perairan Dusun Pelita Jaya dan Pulau Osi seperti suhu, salinitas, dan kecepatan arus. Untuk pengambilan sampel digunakan metode transek linier kuadrat dengan jarak transek 50 meter dan jarak antara kuadrat pengamatan 10 meter. Dari hasil penelitian ini maka didapatkan hasil yaitu bulu babi di Pelita Jaya terdiri atas tiga spesies, sedangkan di Pulau Osi  lima spesies. Kepadatan dan frekuensi kehadiran tertinggi di Pelita Jaya diwakili oleh spesies Tripeneustes gratilla, sedangkan Pulau Osi diwakili oleh Diadema setosum. Potensi/kelimpahan bulu babi di Pelita Jaya sebesar 33.033 individu, sedangkan di Pulau Osi sebesar 74.240 individu.  Dari nilai indeks ekologi maka dapat dinyatakan bahwa keragaman di kedua lokasi berada pada kategori sedang, dengan dominasi spesies yang rendah , serta  keserasian spesies bulu babi di dalam komunitasnya berada pada keadaan berimbang (Steady State). Parameter kualitas air (suhu, salinitas, dan kecepatan arus) sesuai untuk pertumbuhan bulu babi di Pelita Jaya dan Pulau Osi.

scholarly journals Structural and Kinetic Characterization of an Archaeal β-Class Carbonic Anhydrase

2000 ◽  
Vol 182 (23) ◽  
pp. 6605-6613 ◽  
Author(s):  
Kerry S. Smith ◽  
Nathaniel J. Cosper ◽  
Christina Stalhandske ◽  
Robert A. Scott ◽  
James G. Ferry
Keyword(s):  
Steady State ◽  
Carbonic Anhydrase ◽  
Analytical Ultracentrifugation ◽  
Spinacia Oleracea ◽  
State Parameter ◽  
Intramolecular Proton Transfer ◽  
Zinc Hydroxide ◽  
Carbonic Anhydrases ◽  
Hydrogen Isotope Effect ◽  
Steady State Parameter

ABSTRACT The β-class carbonic anhydrase from the archaeonMethanobacterium thermoautotrophicum (Cab) was structurally and kinetically characterized. Analytical ultracentrifugation experiments show that Cab is a tetramer. Circular dichroism studies of Cab and the Spinacia oleracea (spinach) β-class carbonic anhydrase indicate that the secondary structure of the β-class enzymes is predominantly α-helical, unlike that of the α- or γ-class enzymes. Extended X-ray absorption fine structure results indicate the active zinc site of Cab is coordinated by two sulfur and two O/N ligands, with the possibility that one of the O/N ligands is derived from histidine and the other from water. Both the steady-state parameters k cat andk cat/Km for CO2 hydration are pH dependent. The steady-state parameterk cat is buffer-dependent in a saturable manner at both pH 8.5 and 6.5, and the analysis suggested a ping-pong mechanism in which buffer is the second substrate. At saturating buffer conditions and pH 8.5, k cat is 2.1-fold higher in H2O than in D2O, consistent with an intramolecular proton transfer step being rate contributing. The steady-state parameterk cat/Km is not dependent on buffer, and no solvent hydrogen isotope effect was observed. The results suggest a zinc hydroxide mechanism for Cab. The overall results indicate that prokaryotic β-class carbonic anhydrases have fundamental characteristics similar to the eukaryotic β-class enzymes and firmly establish that the α-, β-, and γ-classes are convergently evolved enzymes that, although structurally distinct, are functionally equivalent.

scholarly journals Coupled Optical and Electronic Modeling of Dye-Sensitized Solar Cells for Steady-State Parameter Extraction

2011 ◽  
Vol 115 (20) ◽  
pp. 10218-10229 ◽  
Author(s):  
Sophie Wenger ◽  
Matthias Schmid ◽  
Guido Rothenberger ◽  
Adrian Gentsch ◽  
Michael Grätzel ◽  
...  
Keyword(s):  
Solar Cells ◽  
Steady State ◽  
Dye Sensitized Solar Cells ◽  
State Parameter ◽  
Parameter Extraction ◽  
Dye Sensitized ◽  
Sensitized Solar Cells ◽  
Steady State Parameter

Operational Determination of the Activated Sludge Process Using Neural Networks

1992 ◽  
Vol 26 (9-11) ◽  
pp. 2461-2464 ◽  
Author(s):  
R. D. Tyagi ◽  
Y. G. Du
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Steady State ◽  
Activated Sludge ◽  
Feedforward Neural Network ◽  
Training Data ◽  
Activated Sludge Process

A steady-statemathematical model of an activated sludgeprocess with a secondary settler was developed. With a limited number of training data samples obtained from the simulation at steady state, a feedforward neural network was established which exhibits an excellent capability for the operational prediction and determination.

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