Thermal system identification using fractional models for high temperature levels around different operating points

2012 ◽  
Vol 70 (2) ◽  
pp. 941-950 ◽  
Author(s):  
Asma Maachou ◽  
Rachid Malti ◽  
Pierre Melchior ◽  
Jean-Luc Battaglia ◽  
Bruno Hay
Keyword(s):  
High Temperature ◽  
System Identification ◽  
Thermal System ◽  
Fractional Models ◽  
Temperature Levels ◽  
Operating Points

Advances in System Identification Using Fractional Models

2008 ◽  
Vol 3 (2) ◽  
Author(s):  
Rachid Malti ◽  
Stephane Victor ◽  
Alain Oustaloup
Keyword(s):  
System Identification ◽  
Least Squares ◽  
Prior Knowledge ◽  
Time Domain ◽  
Simultaneous Estimation ◽  
Thermal System ◽  
Fractional Model ◽  
Output Error ◽  
Equation Error ◽  
Fractional Models

This paper presents an up to date advances in time-domain system identification using fractional models. Both equation-error- and output-error-based models are detailed. In the former models, prior knowledge is generally used to fix differentiation orders; model coefficients are estimated using least squares. The latter models allow simultaneous estimation of model coefficients and differentiation orders using nonlinear programing. As an example, a thermal system is identified using a fractional model and is compared to a rational one.

NIMONIC 80 and 80A

Alloy Digest ◽  
1954 ◽  
Vol 3 (5) ◽  
Keyword(s):  
Corrosion Resistance ◽  
High Temperature ◽  
Physical Properties ◽  
Surface Treatment ◽  
High Strength ◽  
Heat Treating ◽  
Temperature Performance ◽  
Nimonic 80A ◽  
Temperature Levels ◽  
Nickel Base

Abstract Nimonic 80 and Nimonic 80A are nickel-base alloys containing a high percentage of chromium, with aluminum and titanium as hardening agents. They are made to the same compositional specification, but Nimonic 80A is produced to meet a more severe requirement with respect to resistance to creep when stressed at higher temperatures than Nimonic 80. Both alloys show high strength at high temperature levels and are very resistant to scaling, oxidation, heat and corrosion. This datasheet provides information on composition, physical properties, elasticity, and tensile properties as well as creep. It also includes information on high temperature performance and corrosion resistance as well as forming, heat treating, machining, joining, and surface treatment. Filing Code: Ni-10. Producer or source: Henry Wiggin & Company Ltd.

scholarly journals Influence of substitution of Portland cement CP-II-Z32 by refractory cement on residual properties of high-temperature concrete

Cerâmica ◽  
2020 ◽  
Vol 66 (379) ◽  
pp. 330-339
Author(s):  
C. da Silva ◽  
D. S. S. Godinho ◽  
A. Ribeiro ◽  
A. Ferronato ◽  
A. B. S. dos Santos Neto ◽  
...  
Keyword(s):  
Heat Conduction ◽  
High Temperature ◽  
Portland Cement ◽  
Mechanical Strength ◽  
Fire Safety ◽  
Residual Properties ◽  
Refractory Cement ◽  
Lower Heat ◽  
Temperature Levels ◽  
Increasing Temperature

Abstract Concrete structures must be sized to ensure stability over their lifetime. Moreover, there are criteria that must be followed for fire safety verification. Given this context, this study aimed to evaluate the influence of the partial and integral replacement of CPII-Z32 cement by a refractory cement in concrete compositions related to the residual properties after exposure to different temperature levels. For the tests, cylindrical specimens were molded with cement replacement percentages of 0% (reference), 50%, and 100%, and exposed at 450 °C and 900 °C without load. The results showed a change in the color of the specimens and a reduction of the mechanical strength with increasing temperature. The increase in the percentage of refractory cement resulted in lower heat conduction for the concrete made with this material.

scholarly journals Tree-ring based reconstruction of mean maximum temperatures since AD 1829

2013 ◽  
Vol 89 (02) ◽  
pp. 184-191 ◽  
Author(s):  
Zhongjie Shi ◽  
Jixi Gao ◽  
Xiaohui Yang ◽  
Zhiqing Jia ◽  
Hao Guo ◽  
...  
Keyword(s):  
High Temperature ◽  
Tree Ring ◽  
Global Climate ◽  
Northern China ◽  
Warming Trend ◽  
Reconstructed Temperature ◽  
Maximum Temperatures ◽  
Temperature Levels ◽  
June July ◽  
Climate Events

The correlation between tree-ring widths and climate was developed using Pinus sylvestris var. mongolica after which mean maximum temperatures of June–July since 1829 were reconstructed. Results show that the transfer function of temperature explains more than 40% of the variance and that the reconstruction sequence was consistent with several reconstructed temperature variations in the region. Over the past 181 years, climate in the region has undergone eight distinct low temperature and eight high temperature periods. A high temperature period in the 1920s to 1930s is consistent with a drought that occurred in most regions of northern China. Periods of drought in the 1870s were also identified. There was no significant increase or decrease in mean maximum June–July temperatures over the last 181 years, although since the 1950s temperatures have increased gradually. A warming trend has become more pronounced since the early 1990s but temperature levels are not significantly higher than those of the 1850s. A multi-taper spectral analysis shows that there are significant periodicities of 2.4, 2.8, 4.9, 5.1 and 21.3 years in the sequence of reconstructed temperatures. Temperatures were also affected by global climate events and solar activity.

Output error MISO system identification using fractional models

2021 ◽  
Vol 24 (5) ◽  
pp. 1601-1618
Author(s):  
Abir Mayoufi ◽  
Stéphane Victor ◽  
Manel Chetoui ◽  
Rachid Malti ◽  
Mohamed Aoun
Keyword(s):  
System Identification ◽  
Optimization Algorithm ◽  
Simulation Analysis ◽  
Good Efficiency ◽  
Output Error ◽  
Single Output ◽  
Multiple Input ◽  
Fractional Models ◽  
Definition Of ◽  
Initialization Procedure

Abstract This paper deals with system identification for continuous-time multiple-input single-output (MISO) fractional differentiation models. An output error optimization algorithm is proposed for estimating all parameters, namely the coefficients and the differentiation orders. Given the high number of parameters to be estimated, the output error method can converge to a local minimum. Therefore, an initialization procedure is proposed to help the convergence to the optimum by using three variants of the algorithm. Moreover, a new definition of structured-commensurability (or S-commensurability) has been introduced to cope with the differentiation order estimation. First, a global S-commensurate order is estimated for all subsystems. Then, local S-commensurate orders are estimated (one for each subsystem). Finally the S-commensurability constraint being released, all differentiation orders are further adjusted. Estimating a global S-commensurate order greatly reduces the number of parameters and helps initializing the second variant, where local S-commensurate orders are estimated which, in turn, are used as a good initial hit for the last variant. It is known that such an initialization procedure progressively increases the number of parameters and provides good efficiency of the optimization algorithm. Monte Carlo simulation analysis are provided to evaluate the performances of this algorithm.

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