Virtual reference station-based computerized ionospheric tomography

In computerized ionospheric tomography (CIT) with ground-based GNSS, the voxels without satellite-receiver ray traversing cannot be reconstructed directly. We present a CIT algorithm based on virtual reference stations (VRSs), called VRS–CIT, to decrease the number of unilluminated voxels and improve the precision of the estimated ionospheric electron density (IED). The VRSs are set at the nodes of grids with a 0.5° × 0.5° resolution in longitude and latitude. We generate the virtual observations with the observations from nearby six or three stations selected according to azimuths and distances. The generation utilizes multi-quadric surface fitting with six stations and triangular linear interpolation with three stations. With the virtual observations added, the IED distribution is reconstructed by the multiplicative algebraic reconstruction technique with the initial values obtained from IRI-2016. The performance of VRS–CIT is examined by using the data from 127 GNSS stations located in 24–46° N and 122–146° E to derive the IED every 30 min. The study focuses on April 29, 2014, with the adaptability of VRS–CIT analyzed by 12 days, evenly distributed around equinoxes and solstices of 2014. The accuracy of the virtual observation is about 1 TECU. Comparing to that derived from CIT with only real observations, the unsolvability of VRS–CIT declined by 4–12% for the whole region, and for the main area, the improvement can be up to 70%. Taking two IED profiles from radio occultation as reference measurements, the mean absolute error (MAE) of IED by VRS–CIT decreases by 6.88% and 8.43%, respectively. Comparing with slant total electron content (STEC) extracted from five additional GNSS stations, the MAE and the root mean square error of the estimated STEC can be reduced up to 17.24% and 33.81%, respectively.

A study on two-dimensional temperature and concentration distribution of Propane-Air premixed flame using CT-TDLAS

To use supplying gases and energy resources efficiently, accurate measurement of irregular gas is necessary. The TDLAS (Tunable laser absorption spectroscopy) technique can be used to control and monitor the supplying gas conditions and combustion of industrial processes. Recently, CT-TDLAS (Computed tomography-tunable diode laser absorption spectroscopy) has been developed to measure the temperature and concentration field of gases. In this study, the 2-dimensional temperature distribution of the Propane-Air premixed flame in several mixing conditions of fuel has been measured by the constructed CT-TDLAS system. 2-Dimensional temperature distributions are measured by 16 path cells. Further, the third-order polynomial regression analysis was applied to resolve the absorption spectra from the incident and transmitted light for a particular gas. The SMART (simultaneous multiplicative algebraic reconstruction technique) algorithm has been adopted for reconstructing the absorption coefficients on the detecting area. As a result of comparing the temperature for the 2-dimensional detecting area using the thermocouple and CT-TDLAS technique, it has been verified that the relative error for the temperatures measured by the thermocouples and calculated by the CT-TDLAS was up to 8%.

Measurement Enhancement on Two-Dimensional Temperature Distribution of Methane-Air Premixed Flame Using SMART Algorithm in CT-TDLAS

In this study, the temperature distribution of the Methane-Air premixed flame was measured. In order to enhance the measurement accuracy of the CT-TDLAS (Computed tomography-tunable diode laser absorption spectroscopy), the SMART (simultaneous multiplicative algebraic reconstruction technique) algorithm has been adopted. Further, the SLOS (summation of line of sight) and the CSLOS (corrective summation of line of sight) methods have been adopted to increase measurement accuracies. It has been verified that the relative error for the temperatures measured by the thermocouples and calculated by the CT-TDLAS was about 10%.

Evaluation of 3D measurement using CT-TDLAS

In order to satisfy the requirements of high quality and optimal material manufacturing process, it is important to control the environment of the manufacturing process. Depending on these processes, it is possible to improve the quality of the product by adjusting various gases. With the advent of the tunable laser absorption spectroscopy (TDLAS) technique, the temperature and concentration of the gases can be measured simultaneously. Among them, computed tomography-tunable diode laser absorption spectroscopy (CT-TDLAS) is the most important technique for measuring the distributions of temperature and concentration across the two-dimensional planes. This study suggests a three-dimensional measurement to consider the irregular flow of supplying gases. The simultaneous multiplicative algebraic reconstruction technique (SMART) algorithm was used among the CT algorithms. Phantom datasets have been generated by using Gaussian distribution method. It can show expected temperature and concentration distributions. The (HITRAN) database in which the thermo-dynamical properties and the light spectra of H2O are listed were used for the numerical test. The relative average temperature error ratio in the results obtained by the SMART algorithm was about 3.2% for temperature. The maximum error was 86.8 K.

PENCITRAAN DISTRIBUSI VERTIKAL UAP AIR DI KAWASAN BANDUNG MENGGUNAKAN TEKNIK GPS TOMOGRAFI 1D

Global Positioning System (GPS) tidak hanya berguna untuk keperluan navigasi dan penentuan posisi. GPS juga dapat dimanfaatkan untuk keperluan meteorologi seperti pemantauan kondisi atmosfer Bumi. Sinyal GPS yang ditransmisikan dari satelit ke receiver mengalami perlambatan dan pembelokan akibat adanya partikel-partikel pada lapisan troposfer. Salah satu partikel yang memiliki peranan penting terhadap berlangsungnya siklus hidrologi di Bumi adalah uap air. Uap air tersebut bersifat sangat dinamis baik secara spasial maupun temporal. Perbedaan kandungan uap air pada setiap tempat dan ketinggian menyebabkan besarnya refraktivitas pada lapisan troposfer juga bervariasi. Pemantauan uap air dengan ketelitian tinggi masih menjadi tantangan di Indonesia. Informasi yang akurat mengenai uap air tentunya bermanfaat dalam melakukan prediksi cuaca lokal maupun mempelajari iklim global. Salah satu produk dari pengolahan data GPS adalah informasi mengenai estimasi besarnya bias troposfer pada arah zenith atau disebut sebagai Zenith Tropospheric Delay (ZTD). Besarnya hasil estimasi tersebut kemudian dapat dipisahkan menjadi komponen kering atau Zenith Hydrostatic Delay (ZHD) dan uap air atau Zenith Wet Delay (ZWD). Untuk mengetahui besarnya kandungan uap air pada setiap lintasan sinyal, maka ZWD harus dikonversi menjadi Slant Wet Delay (SWD) dengan mengalikan ZWD dan mapping function. Nilai SWD kemudian digunakan untuk melakukan rekonstruksi distribusi vertikal uap air pada troposfer dengan teknik tomografi. Pada penelitian ini digunakan data pengamatan GPS dari stasiun GPS kontinu (CGPS) ITB selama satu hari. Hasil yang didapatkan menyatakan bahwa Multiplicative Algebraic Reconstruction Technique (MART) berhasil diterapkan untuk menyelesaikan persamaan linear dalam menentukan refraktivitas komponen basah dengan GPS tomografi 1D. Penelitian lebih lanjut dengan memanfaatkan jaringan stasiun CGPS dan pengembangan metode numerik dapat memberikan hasil yang lebih optimal dan akurat.