Compensation for the Temperature Dependence of the Fog Output Signal

This paper proposes a method for compensating the temperature error in the FOG output signal using neural networks. One of the main advantages of the method lies in possibility for identification of complex dependencies without losing compensation accuracy at the boundaries of the temperature range.

A Real-Time Simulator for an Innovative Hybrid Thermal Management System Based on Experimental Verification

The performance and efficiency of green energy sources in electric vehicles (EVs) are significantly affected by operation temperatures. To maintain the optimal temperatures of a hybrid energy system (HES), an innovative hybrid thermal management system (IHTMS) was designed. The IHTMS contains a coolant pump, a heat exchanger, a proportional valve for hybrid flow rates, five coolant pipes, and three electromagnetic valves to form two mode-switch coolant loops. A Matlab/Simulink-based simulator of the IHTMS was constructed by formulating a set of first-ordered dynamics of temperatures of coolant pipes and energy bodies using the theories of Newton’s law of cooling and the lumped-parameter technique. Parameters were majorly derived by measured performance maps and data from the experimental platform of the IHTMS. To properly manage the optimal temperatures, four control modes were designed for inner-loop form and outer-loop form. For the experimental platform to verify the simulator, two power supplies generated the waste heat of dual energy sources calculated by the driving cycle and vehicle dynamics. Simulation results show that the temperatures were controlled at their optimal ranges by proper mode/loop switch. With the inner-loop mechanism, the rise time of optimal temperature decreased 27.4%. The average simulation-experiment temperature error of the battery was 0.898 °C; the average simulation-experiment temperature error of the PEMFC was 4.839 °C. The IHTMS will be integrated to a real HES in the future.

TEMPERATURE ERROR WHEN DETERMINING THE TIME PARAMETER OF A FIRE DETECTOR WITH A THERMORESISTIVE SENSITIVE ELEMENT

For fire detectors with a thermoresistive sensing element, a mathematical description of the reaction to the thermal action of an electric current pulse flowing through such a sensing element and having the shape of a right triangle is obtained. The mathematical description is constructed using the Laplace integral transformation and is shown to be a superposition of two Heaviside functions. The parameters of these functions are determined by the transmission coefficient and time constant of the thermoresistive sensitive element of the fire detector and the amplitude and duration of the electric current pulse. It is shown that the ratio of the output signals of the thermoresistive sensitive element of the fire detector at two a priori given moments of time can be used to determine the time parameter of the fire detector. The values ​​of a priori set moments of time, in which the temperature of the thermoresistive sensitive element of the fire detector is determined, are selected under the condition of simplicity of technical implementation. If there is a change in ambient temperature, it leads to a temperature error as a function of the time parameter of the fire detector. For such an error, a mathematical description is obtained in the general case, as well as for the case when the thermal influence on the thermoresistive sensitive element of the fire detector is due to the flow of an electric current pulse in the form of a right triangle. It is shown that the value of the temperature error has a minimum at the values ​​of the ratio of the output signals of the thermoresistive sensitive element of the fire detector at two a priori time points belonging to the range The value of this error does not exceed 4.9% with variations in ambient temperature, the value of which does not exceed 2.0%.

Three-Dimensional Transient Finite Element Cooling Simulation For Injection Molding Tools

Plastic injection molding is one of the most popular manufacturing processes for mass production, and optimizing the mold cooling system is critical for reducing the cycle time and improving the final part quality. Conventional cooling simulation uses the boundary element method to perform the cycle-averaged analysis, which is a simplification due to computational resources limitation. This paper develops a three-dimensional transient cooling simulation method based on the finite element method, which can simulate the complex mold system accurately and efficiently. It is shown that this method finishes the transient cooling analysis in 478 seconds on the real-world injection molding mold with more than 6.9 million tetrahedral elements. Its accuracy is compared against the experimental results with the maximum temperature error less than 4%, and the average temperature error less than 1%.

Laboratory characterisation of the radiation temperature error of radiosondes and its application to the GRUAN data processing for the Vaisala RS41

The paper presents the Simulator for Investigation of Solar Temperature Error of Radiosondes (SISTER), a setup that was developed to quantify the solar heating of the temperature sensor of radiosondes under laboratory conditions by recreating as closely as possible the atmospheric and illumination conditions that are encountered during a daytime radiosounding ascent. SISTER controls the pressure (3 hPa to 1020 hPa) and ventilation speed of the air inside the windtunnel-like setup to simulate the conditions between the surface and 35 km altitude, to determine the dependence of the radiation temperature error on the irradiance and the convective cooling. The radiosonde is mounted inside a quartz tube, while the complete sensor boom is illuminated by an external light source to include the conductive heat transfer between sensor and boom. A special feature of SISTER is that the radiosonde is rotated around its axis to imitate the spinning of the radiosonde in flight. The characterisation of the radiation temperature error is performed for various pressures, ventilation speeds and illumination angles, yielding a 2D-parameterisation of the radiation error for each illumination angle, with an uncertainty smaller than 0.2 K (k = 2) for typical ascend speeds. This parameterisation is applied in the GRUAN processing for radiosonde data, which relies on the extensive characterisation of the sensor properties to produce a traceable reference data product which is free of manufacturer dependent effects. The GRUAN radiation correction model combines the laboratory characterisation with model calculations of the actual radiation field during the sounding to estimate the correction profile. In the second part of this paper it is described how this procedure was applied in the development of the GRUAN data product for the Vaisala RS41 radiosonde (version 1, RS41-GDP.1). The magnitude of the averaged correction profile increases gradually from 0.1 K at the surface to approximately 0.8 K at 35 km altitude. Comparison between sounding data (N = 154) that were GRUAN-processed and Vaisala-processed reveal that the daytime differences are smaller than +0.1 K (GRUAN – Vaisala) in the troposphere and increase above the tropopause steadily with altitude to +0.35 K (GRUAN – Vaisala) at 35 km. These differences are just within the limits of the combined uncertainties (with coverage factor k = 2) of both data products, meaning that the GRUAN processing and the Vaisala processing are in agreement.

Experiment to quantify the solar radiative temperature error of radiosondes

<p>One of the main goals of the GCOS Reference Upper Air Network (GRUAN) is to perform reference observations of profiles of atmospheric temperature and humidity for the purpose of monitoring climate change. Two essential criteria for establishing a reference observation are measurement-traceability and the availability of measurement uncertainties. Radiosoundings have proven valuable in providing in-situ profiles of temperature, humidity and pressure at unmatched vertical resolution. Data products from commercial radiosondes often rely on black-box or proprietary algorithms, which are not disclosed to the scientific user. Furthermore, long-term time-series from these products are frequently hampered by changes in the hardware and/or the data processing. GRUAN data products (GDPs) comply with the above-mentioned criteria for a reference product. Correction algorithms are open-source and well-documented and the data include vertically resolved best-estimates of the uncertainties.</p><p>This presentation discusses the quantification and the correction for the temperature error due to solar radiation that is applied in the GRUAN data processing for the Vaisala RS41 radiosonde. Heating of the temperature sensor by solar radiation is the dominant source of error for daytime radiosoundings.</p><p>At Lindenberg Observatory a dedicated laboratory set-up was built to quantify the solar temperature error of radiosondes. The setup allows to create conditions that are similar to those encountered during an actual radiosounding, with special emphasis on parameters such as pressure, air flow (ventilation), and illumination conditions. The radiosonde is placed inside a quartz tube that is integrated in a wind tunnel-like construction that can be operated between ambient pressure and 3 hPa. During the measurements the radiosonde is rotated along its longitudinal axis to mimic the spinning during ascent, and the large quartz window makes it possible to illuminate the temperature sensor together with a considerable part of the sensor boom, allowing to assess the contribution of the heat transfer from the sensor boom to the sensor. A parameterization of the heating of the sensor in terms of flux, pressure, ventilation and solar elevation is presented. This parameterization is the basis of the GRUAN correction algorithm, which in addition includes a radiation model and altitude information. In conclusion the GRUAN data product is compared to the manufacturer-processed data.</p>