State Primary Standard of Unit of Specific Heat Capacity of Solids (Get 60-2019)

Компан, Т. А.; Kulagin, V. I.; Vlasova, V. V.; Kondratiev, Sergey V.; Lukin, A. Ya.; Pukhov, N. F.

doi:10.1007/s11018-020-01802-3

Cited by 3 publications

(2 citation statements)

References 17 publications

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“…Consider constructing such a model using the example of a precision adiabatic calorimeter [3] designed to measure the specific heat capacity of solids in a wide temperature range. The principle of operation of such a device is to measure the temperature increase when a precisely dosed amount of heat is supplied to the cell containing the test sample.…”

Section: Model Buildingmentioning

confidence: 99%

“…Maintaining a predetermined temperature profile in a sample or process object under study is a very common control task. Thermophysical measurements [1][2][3], in which multiple heaters provide heating with zero temperature gradients throughout the sample, would be a good example. A simple proportional-integral-derivative (PID) controller [4] is not optimal since it does not use information about the main source of changes-the current power of the heaters.…”

Section: Introductionmentioning

confidence: 99%

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Precision Calorimeter Model Development: Generative Design Approach

et al. 2023

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In a wide range of applications, heating or cooling systems provide not only temperature changes, but also small temperature gradients in a sample or industrial facility. Although a conventional proportional-integral-derivative (PID) controller usually solves the problem, it is not optimal because it does not use information about the main sources of change—the current power of the heater or cooler. The quality of control can be significantly improved by including a model of thermal processes in the control algorithm. Although the temperature distribution in the device can be calculated from a full-fledged 3D model based on partial differential equations, this approach has at least two drawbacks: the presence of many difficult-to-determine parameters and excessive complexity for control tasks. The development of a simplified mathematical model, free from these shortcomings, makes it possible to significantly improve the quality of control. The development of such a model using generative design techniques is considered as an example for a precision adiabatic calorimeter designed to measure the specific heat capacity of solids. The proposed approach, which preserves the physical meaning of the equations, allows for not only significantly improving the consistency between the calculation and experimental data, but also improving the understanding of real processes in the installation.

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Section: Model Buildingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Precision Calorimeter Model Development: Generative Design Approach

et al. 2023

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Feasibility analysis and performance characteristic investigation of thermal energy storage system based on organic Rankine cycle for engine exhaust temperature modulation

Dang,

Han,

Liu

et al. 2024

Energy Sources, Part A: Recovery, Utilization, and Environmenta

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Precise measurements of specific heat capacity of beryllium in temperature range 260–870 K

et al. 2021

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The possibility of using beryllium as a means of storing and transferring a unit of specific heat capacity and extending the range of values of heat capacity measures from 1654 to 2900 J/(kg·K) towards the upper limit is estimated. The temperature dependence of the specific heat capacity of beryllium samples of known composition in the temperature range of 260–870 K has been determined. The reproducibility of the thermophysical properties of beryllium over time and under repeated heating in the specified temperature range is analyzed. The results obtained are relevant for the field of metrological support in the field of measurements of thermophysical quantities.

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State Primary Standard of Unit of Specific Heat Capacity of Solids (Get 60-2019)

Cited by 3 publications

References 17 publications

Precision Calorimeter Model Development: Generative Design Approach

Precision Calorimeter Model Development: Generative Design Approach

Feasibility analysis and performance characteristic investigation of thermal energy storage system based on organic Rankine cycle for engine exhaust temperature modulation

Precise measurements of specific heat capacity of beryllium in temperature range 260–870 K

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