Building performance simulation is being increasingly deployed beyond the building design phase to support efficient building operation. Specifically, the predictive feature of the simulation-assisted building systems control strategy provides distinct advantages in view of building systems with high latency and inertia. Such advantages can be exploited only if model predictions can be relied upon. Hence, it is important to calibrate simulation models based on monitored data. In the present paper, we report on the use of optimization-aided model calibration in the context of an existing university building. Thereby, our main objective is to deploy data obtained via the monitoring system to both populate the initial simulation model and to maintain its fidelity through an ongoing optimization-based calibration process. The results suggest that the calibration can significantly improve the predictive performance of the thermal simulation model.

Background: In this study, measurement of indoor radon and its progeny levels was carried out in Gas Turbine Power Station in Haryana ( India ), where natural gas is used as fuel. For comparison, the results of a study carried out in thermal power plant in Haryana are also presented. Radon being a ubiquitous air pollutant has global impact and its monitoring in the environment at work places is essential from health and hygiene point of view. Materials and Methods: LR-115, Type- II (Kodak Pathe, France), plastic track detectors commonly known as solid state nuclear track detectors (SSNTDs) were used to measure the radon concentration over long integrated times. Alpha particles emitted from radon cause radiation damage tracks, which were subsequently revealed by chemical etching in NaOH. These alpha tracks registered were counted by optical microscope at suitable magnification and converted into radon concentration. Results: The radon levels measured at various locations were moderate to high and thus unsafe from health point of view. The potential alpha energy concentration (PAEC), radon levels (EEC), annual exposure, annual effective dose in the Gas Turbine Power Plant varied from 4.14 mWL to 26.7 mWL, 38.3 Bq m-3 to 247.6 Bq m-3, 0.17 WLM to 1.10 WLM and 0.66 mSv to 4.25 mSv respectively. Conclusion: In gas turbine power plant, the radon levels were found to be lower as compared with thermal power plant. In thermal power plant a lot of coal is being burnt which contains radionuclides. Coal fired plants release more radioactive waste which is hazardous into the air than gas power plants of equivalent capacity

The main purpose of this work is introducing a novel method of temperature monitoring using B-Mode Ultrasound digital images. Thermal dependence of sound speed causes a virtual displacement of scatterer particles. The virtual displacement is computed using speckle tracking methods. Horn-Shunck algorithm was applied to a tissue mimicking phantom to measure the virtual displacement. A heating resistor was used in this phantom to generate temperature elevation. The DICOM ultrasound images were acquired using commercial SIMENES ultrasound imaging system with 10MHz linear probe. The accuracy of noninvasive temperature estimation was measured comparing with invasive temperature measurement. The phantom is warmed up to the 8. The mean error of temperature estimation was found to be 0.4°C and peak error 0.9°C. Fast temperature estimation can be achieved using Optical-Flow methods. This Method is a differential based motion estimation method that estimates displacement by calculating the optical pattern changes caused by movements between two frames. Noise sensitivity is the main infirmity of Horn-Schunck method.