Estimation Of Temperature Profiles Research Articles

Technical Note: Recipe for monitoring of total ozone with a precision of around 1 DU applying mid-infrared solar absorption spectra

Abstract. Mid-infrared solar absorption spectra recorded by a state-of-the-art ground-based FTIR system have the potential to provide precise total O3 amounts. The currently best-performing retrieval approaches use a combination of small and broad spectral O3 windows between 780 and 1015 cm−1. We show that for these approaches the uncertainties of the temperature profile are by far the major error sources. We demonstrate that a joint optimal estimation of temperature and O3 profiles widely eliminates this error. The improvements are documented by an extensive theoretical error estimation. Our results suggest that mid-infrared FTIR measurements can provide total O3 amounts with a precision of around 1 DU, placing this method among the most precise ground-based O3 monitoring techniques. We recapitulate the requirements on the instrumental hardware and on the retrieval that are needed to achieve this high precision.

An inverse estimation of initial temperature profile in a polymer process

AbstractSince one of the most important parameter in polymer processing such as injection stretch blow molding is temperature distribution in the thickness direction, an inverse method has been applied to estimate this profile. This process comprises of four steps. In the first step the preform is injection molded, and in the second and third step it is stretched by a rod to its final length and then inflated and in the last step it is discharged from the mold. In such kind of polymer flows viscous dissipation plays a remarkable role in the evolution of temperature profile. Some theoretical temperature profile has been applied to confirm the validation of the inverse algorithm. Different solution techniques are applied in this article to the inverse problem under consideration, namely: the conjugate gradient and Levenberg–Marquardt method. After the preform is injection molded, which is the first step, it is removed from the mold, which corresponds to time t = 0. At this moment an infrared camera is used to record the surface temperature of the preform with a certain time step. With regard to variation of thermal properties with temperature, the inverse problem becomes nonlinear. These experimental data provided by the infrared camera are then used to estimate the temperature profile at the end of injection process before stretching and inflation took place. POLYM. ENG. SCI., 48:133–140, 2008. © 2007 Society of Plastics Engineers

Heat transfer beneath ice-rink floors

This paper presents two models to determine ground-coupled heat gains for ice rinks. The first model is based on an analytical method: the Interzone Temperature Profile Estimation (ITPE) technique while the second model utilized implicit finite difference scheme. Using both models, time-varying heat transfer within the ice medium as well as the ground is investigated. The predictions of both models have been compared and are found to be within good agreement. Moreover, the results from the transient numerical model are compared against measurements obtained for a small-scale ice-rink model operated under laboratory conditions. The measurements provide the time period required to freeze the ice-rink surface as well as the ice temperatures at different locations of the ice-rink floor. The results of the numerical model are then utilized to investigate the impact of various design and operating conditions on the thermal performance of a typical ice rink.

Retrieving soil temperature profile by assimilating MODIS LST products with ensemble Kalman filter

Proper estimation of initial state variables and model parameters are vital importance for determining the accuracy of numerical model prediction. In this work, we develop a one-dimensional land data assimilation scheme based on ensemble Kalman filter and Common Land Model version 3.0 (CoLM). This scheme is used to improve the estimation of soil temperature profile. The leaf area index (LAI) is also updated dynamically by MODIS LAI production and the MODIS land surface temperature (LST) products are assimilated into CoLM. The scheme was tested and validated by observations from four automatic weather stations (BTS, DRS, MGS, and DGS) in Mongolian Reference Site of CEOP during the period of October 1, 2002 to September 30, 2003. Results indicate that data assimilation improves the estimation of soil temperature profile about 1 K. In comparison with simulation, the assimilation results of soil heat fluxes also have much improvement about 13 W m − 2 at BTS and DGS and 2 W m − 2 at DRS and MGS, respectively. In addition, assimilation of MODIS land products into land surface model is a practical and effective way to improve the estimation of land surface variables and fluxes.

Calibration of an integrated land surface process and radiobrightness (LSP/R) model during summertime

In this study, a soil vegetation and atmosphere transfer (SVAT) model was linked with a microwave emission model to simulate microwave signatures for different terrain during summertime, when the energy and moisture fluxes at the land surface are strong. The integrated model, land surface process/radiobrightness (LSP/R), was forced with weather and initial conditions observed during a field experiment. It simulated the fluxes and brightness temperatures for bare soil and brome grass in the Northern Great Plains. The model estimates of soil temperature and moisture profiles and terrain brightness temperatures were compared with the observed values. Overall, the LSP model provides realistic estimates of soil moisture and temperature profiles to be used with a microwave model. The maximum mean differences and standard deviations between the modeled and the observed temperatures (canopy and soil) were 2.6 K and 6.8 K, respectively; those for the volumetric soil moisture were 0.9% and 1.5%, respectively. Brightness temperatures at 19 GHz matched well with the observations for bare soil, when a rough surface model was incorporated indicating reduced dielectric sensitivity to soil moisture by surface roughness. The brightness temperatures of the brome grass matched well with the observations indicating that a simple emission model was sufficient to simulate accurate brightness temperatures for grass typical of that region and surface roughness was not a significant issue for grass-covered soil at 19 GHz. Such integrated SVAT-microwave models allow for direct assimilation of microwave observations and can also be used to understand sensitivity of microwave signatures to changes in weather forcings and soil conditions for different terrain types.

State estimation of a stratified storage tank

Two approaches for the state estimation of the spatial temperature profile in a stratified storage tank, i.e. the state of the art domestic hot water storage system, are presented. There are a distributed parameter observer as a late lumping and an Unscented Kalman filter (UKF) as an early lumping approach which are investigated with respect to applicability and reconstruction convergence. Both, the distributed parameter observer and the UKF are designed based on a hybrid distributed parameter model of the stratified storage tank. The hybrid model is composed of a finite state automaton interacting with an underlying thermal heat conduction–convection system described by a quasi-linear partial differential equation. The performance of the estimation algorithms is illustrated by simulation studies and measurement data, showing excellent convergence results.

Semi-analytical solution for steady-periodic heat transfer of attached underground engineering envelope

The solution for steady-periodic heat transfer of attached underground engineering can be expressed by complex temperature. The solution involves two parts: steady temperature and complex amplitude of the annual temperature fluctuations. Using a mathematical model of heat transfer of attached underground engineering, the calculation area is divided into eight rectangular blocks according to the interzone temperature profile estimation (ITPE) technology, and the solutions are obtained for all the parts using the separation of variables method. During the solution, the Fourier coefficients are determined based on the continuity of the heat flux and boundary conditions; as a result, a system of 14 N linear equations with 14 N unknowns is obtained, where N is the truncation point of the Fourier series. The linear equations can be easily solved with a standard method (e.g. Gauss–Jordan elimination). The semi-analytical solution obtained by the ITPE can provide rapid and accurate solution for calculation of heat transfer as well as the basis for analysis of the influential factors of the heat transfer.

Semi-analytical solution of roof-on-grade attached underground engineering envelope

Using a mathematical model of heat transfer of attached underground Engineering Envelope, the calculation area is divided into 13 rectangular blocks according to the Interzone Temperature Profile Estimation (ITPE) technology, and the solutions are obtained for all the parts using the technique of variable separation. During the solution, the Fourier coefficients are determined based on the continuity of the heat flux and boundary conditions. The influences of the temperature of earth surface and the heat transfer coefficient between air and wall on heat flow through the envelope has been quantitatively analyzed. The results show that the heat flux through the envelope is no longer monotonously increase or decrease with increase of the influencing factors. By analyzing the curve of r-value (the ratio of the flux through the roof to the overall flux through the engineering section including the floor and walls), it can be concluded that the heat flow between the first floor of the building and the engineering is the major reason and the shape of the engineering is another one.

Molecular dynamics calculation of liquid iron properties and adiabatic temperature gradient in the Earth's outer core

SUMMARY The knowledge of the temperature radial distribution in the Earth’s core is important to understand the heat balance and conditions in the Earth’s interior. Molecular dynamics (MD) simulations were applied to study the properties of liquid iron under the pressure-temperature conditions of the Earth’s outer core. It is shown that the model used for the MD simulations can reproduce recent experimentally determined structure factor calculations to the highest pressure of 58 GPa. Applying this model for higher pressures, the calculated densities and diffusion parameters agree well with the results of first-principles. The MD calculations indicate that a reasonable estimate of the adiabatic temperature profile in the Earth’s outer core could be evaluated.

The Use of Condition Maps in the Design and Testing of Power Electronic Circuits and Devices

This paper presents a new technique for analyzing the conditions to which power semiconductor devices are subjected within practical inverters. A representative load cycle, which defines the inverter conditions, is used to estimate the switching conditions of the devices. Condition maps are generated, which allows the design and testing of the system to consider the more likely range of conditions. Estimates of temperature profiles can also be made to further improve the realism of such design. This promises to lead to the development of more realistic optimization procedures.

Effects of urbanization and groundwater flow on the subsurface temperature in Osaka, Japan

Subsurface temperatures were analyzed to evaluate the effects of urbanization and groundwater flow in Osaka, the second largest metropolitan in Japan. The temperature–depth profiles were classified into three (recharge, intermediate and discharge) types based on the thermal gradient, shape of the profiles, and temperature itself. The locations of the three types of profiles represent the places of regional and local groundwater flow systems in Osaka plain. The analyses of subsurface temperature using heat conduction–convection theory under the condition of surface warming showed that the depth of minimum temperature in the profile increased with the groundwater recharge rate and time lapse from the beginning of surface warming due to urbanization. Comparisons between observed and estimated temperature profiles showed that the surface warming due to urbanization is larger and occurred earlier in the middle of the city than those in surrounding area, which agreed with the air temperature records.

Energy Balance on the Laser Drawing Process of Poly (ethylene terephthalate) Fiber

The energy balance on the laser drawing process of poly (ethylene terephthalate) was analyzed by the on-line fiber temperature measurement. The energy converting process from the external work for drawing to the thermal energy was quantitatively investigated by comparing the measured temperature profiles with the estimated temperature profiles using energy balance equations. From the result, it was shown that 9-24% of the applied work was stored as the elastic energy into the system just after the neck drawing point, and that the stored elastic energy was released as the thermal energy with the progress of orientation-induced-crystallization. It was also shown that the ratio of stored energy to the applied work tend to increase with the increase of fiber speed.

Combining Microwave Radiometer and Wind Profiler Radar Measurements for High-Resolution Atmospheric Humidity Profiling

Abstract A self-consistent remote sensing physical method to retrieve atmospheric humidity high-resolution profiles by synergetic use of a microwave radiometer profiler (MWRP) and wind profiler radar (WPR) is illustrated. The proposed technique is based on the processing of WPR data for estimating the potential refractivity gradient profiles and their optimal combination with MWRP estimates of potential temperature profiles in order to fully retrieve humidity gradient profiles. The combined algorithm makes use of recent developments in WPR signal processing, computing the zeroth-, first-, and second-order moments of WPR Doppler spectra via a fuzzy logic method, which provides quality control of radar data in the spectral domain. On the other hand, the application of neural network to brightness temperatures, measured by a multichannel MWRP, can provide continuous estimates of tropospheric temperature and humidity profiles. Performance of the combined algorithm in retrieving humidity profiles is compared with simultaneous in situ radiosonde observations (raob’s). The empirical sets of WPR and MWRP data were collected at the Atmospheric Radiation Measurement (ARM) Program’s Southern Great Plains (SGP) site. Combined microwave radiometer and wind profiler measurements show encouraging results and significantly improve the spatial vertical resolution of atmospheric humidity profiles. Finally, some of the limitations found in the use of this technique and possible future improvements are also discussed.

High‐velocity lid of East Antarctica: Evidence of a depleted continental lithosphere

In broadband seismograms from shallow earthquakes occurring south of New Zealand recorded at the South Pole, we found significant arrivals 40–70 s after the first SH arrivals at distances of 29°–35° and 20–50 s after the first P arrivals at distances of 28°–35°. These waves traversing beneath East Antarctica can be modeled by slightly modifying one‐dimensional P and S wave velocity structures of the Canadian shield. In the obtained velocity models, a velocity reduction below the lithosphere forms a deep low‐velocity zone. S waves turning below the low‐velocity zone explain the SH waveforms observed at 29°–55°. The observed P waveforms, however, suggest that a corresponding reduction in P velocity is smaller. These P and S wave velocity variations are likely to be a manifestation of a depleted continental lithosphere (high concentrations of olivine and magnesium number (Mg # = 100Mg/(Mg + Fe)). For a lithospheric composition more depleted than that of the underlying mantle, the temperature profile estimated from our velocity models is smooth from the lithosphere to the underlying mantle. Lithospheric depletion can also explain that the velocity anomaly in the lithosphere is larger for S than for P waves. Were the composition to be assumed uniform throughout the upper mantle, a large temperature gradient would be required at the bottom of the lithosphere, implying a heat sink which is unlikely to be sustainable. Thus a difference in composition between the lithosphere and underlying mantle leads to a reasonable estimate of temperature profile that is consistent with the observed seismic waveforms.

Modeling of batch reactions with in situ spectroscopic measurements and calorimetry

AbstractThis paper describes kinetic fitting of UV‐visible spectra and energy flow measured as a function of time from a reaction calorimeter, giving a single global model that achieves fusion of spectroscopic and calorimetry data. We demonstrate that a temperature controlled model of a reaction mechanism fitted to in situ spectroscopic measurements can be coupled to an energy balance model, since the amount of energy released by the reaction is proportional to the change in concentration of reactants and products with time. This allows simultaneous determination of the reaction mechanism parameters and the reaction enthalpy by fitting the coupled model to the spectroscopic and temperature data. The resulting model fully characterizes the kinetics and thermochemical properties of reactions that take place during a batch titration reaction of salicylic acid (SA) with acetic anhydride (AA) to form acetylsalicylic acid (ASA). The model comprises a system of ordinary differential equations fit directly to the spectroscopic and calorimetry data. It permits accurate estimates of model parameters producing estimates of concentration and reaction temperature profiles as a function of time, provided a sufficiently accurate description of the reaction mechanism is specified. No standards or pure component spectra were required, giving calibration‐free estimates of concentration and temperature profiles. The parameters estimated in the model include kinetic rate constants and heat of reaction of the reactions observed during the experiment. In addition, heat capacities of reagents flowing into the reactor and thermal transfer coefficients were estimated. Copyright © 2006 John Wiley & Sons, Ltd.

Effect of the thermal conductivity of building materials on the steady-state thermal behaviour of underground building envelopes

Using a mathematical model of heat transfer of basement, the calculation area is divided into eight rectangles according to the interzone temperature profile estimation (ITPE) technology, and the solution obtained for all the parts by the separation of variables technique. During the solution, the Fourier coefficients are determined by the continuity of the heat flux and boundary conditions, as a result, a system of linear equation group including 14 N equations has been obtained. The effect of building materials on the temperature and heat flux for the building envelope has been evaluated by calculating the temperature and heat flux for three buildings built with different building materials. The results show that the highest relative error in heat flux among the three envelopes built with various non-insulation material is 27.8%, which indicates the thermal conductivity of the building materials is an important factor of the heat transfer of the envelope.

Estimation of ocean subsurface thermal structure from surface parameters: A neural network approach

Satellite remote sensing provides diverse and useful ocean surface observations. It is of interest to determine if such surface observations can be used to infer information about the vertical structure of the ocean's interior, like that of temperature profiles. Earlier studies used either sea surface temperature or dynamic height/sea surface height to infer the subsurface temperature profiles. In this study we have used neural network approach to estimate the temperature structure from sea surface temperature, sea surface height, wind stress, net radiation, and net heat flux, available from an Arabian Sea mooring from October 1994 to October 1995, deployed by the Woods Hole Oceanographic Institution. On the average, 50% of the estimations are within an error of ±0.5°C and 90% within ±1.0°C. The average RMS error between the estimated temperature profiles and in situ observations is 0.584°C with a depth‐wise average correlation coefficient of 0.92.

Roles of vertical correlations of background error and T‐S relations in estimation of temperature and salinity profiles from sea surface dynamic height

A data assimilation scheme based on three‐dimensional variational analysis (3DVAR) is proposed to estimate temperature and salinity profiles from surface dynamic height information. The scheme takes into consideration vertical correlations for both temperature and salinity background errors and the nonlinear temperature‐salinity (T‐S) relation. In this study we designed some one‐dimensional test cases to examine the separate and combined impacts of the vertical correlations and the nonlinear T‐S relation on estimations of temperature and salinity profiles in comparison with a simplified scheme that considers neither vertical correlations nor T‐S relations. Results show that the simplified scheme cannot simultaneously improve temperature and salinity profiles over their backgrounds in some cases and could make the correction seriously nonsmooth at different depths. The consideration of vertical correlations helps to balance the magnitude of the profile correction among all depths and produce smoother results. However, consideration of vertical correlations cannot help much in reducing the root‐mean square error of estimation. The consideration of the nonlinear T‐S relation can improve both temperature and salinity estimations in all test cases and can significantly reduce the root‐mean square error of estimations. The combined effects of both vertical correlations and the nonlinear T‐S relation are similar to those of the latter but with vertically smoother results.

Heat and mass transfer in a concentric-annular-tube bed packed with ZrV1.9Fe0.1 particles

Pressure–composition isotherms of the ZrV1.9Fe0.1–hydrogen system were determined by a constant volume method and were correlated to an empirical van’t Hoff equation. The enthalpy change of hydrogen absorption was correlated to a function of the hydrogen-to-alloy atomic molar ratio. The entropy change was independent of it. Heat and mass transfer process in a concentric-annular-tube bed packed with the ZrV1.9Fe0.1 particles was studied experimentally and numerically as a basic study of hydrogen storage at elevated temperature. A one-dimensional concentric-annular-tube bed was charged with hydrogen. The experimental profiles of hydrogen partial pressure and temperature were compared with numerical simulation calculated by the pressure–composition isotherm, a hydrogenating rate equation and two balance equations of hydrogen and heat. Another simplified analysis using three dimensionless lump parameters succeeded in estimating temperature profiles in the hydrogen-absorbing-alloy bed more easily. The simulation was able to make it better to understand contributions of experimental parameters such as the flow rate, surrounding temperature and other physical properties.

Estimating temperature profiles for short-term load forecasting: neural networks compared to linear models

Short-term load profile forecasts (forecasts of the next day's 24 hourly loads, for example) have become vital tools for the efficient operation of power systems. Many new forecasting systems have been proposed in recent years, most based on models that relate the load profile to the temperature profile. Weather services, however, do not usually supply temperature profile forecasts, but only predictions of maximum and minimum values. Some methods to estimate temperature profiles by linearly interpolating between the predicted extreme values have been devised by the utilities. A model that replaces such methods by a multi-output neural network is proposed. In out-of-sample simulations over real data, this model outperformed the more traditional methods we used for comparison. Forecasting systems like this, based on neural networks, may help to deal with the lack of weather-service profile forecasts of temperature (or other weather-related variables), and may ultimately contribute to the reduction of the load forecasting error.