Simple solutions for improving thermal comfort in huts in the highlands of Peru.

In the Peruvian mountains, hundreds of thousands of rural households living in poverty live in cold indoor environments, close to 0 °C. Indoor cold causes thousands of respiratory diseases and excess of winter deaths. In this study, we numerically calculated the impact of simple low-cost refurbishments on discomfort time during a year. Using EnergyPlus and Python, we modelled a typical one-room hut used as bedroom built with a metal-sheet roof, adobe walls, dirt floors, and high infiltration rates. Then, 9 individual solutions were studied, and their combination resulted in 215 different hut designs. The model was calibrated with field measurements to estimate the infiltration. All the numerical calculations included an uncertainty analysis based on Monte Carlo method, and a sensitivity analysis to assess the impact of reducing infiltration on discomfort time. The base case had a discomfort time of 44% of time. The calibration of infiltration resulted in a mean hourly air exchange rate equal to 29.1 h-1 (SD = 17.0 h-1). Five different designs formed the Pareto front that optimized discomfort time and costs. The solution with the lowest discomfort time during a year, 37% of the time, was adding insulation to the roof (U = 0.83 W/m2•K) and the door (U = 1.00 W/m2•K); and its cost was 286USD. In this solution, when infiltrations were reduced to 4.1 h-1 (SD = 4.1 h-1) discomfort time decreased until 16%. These results benefit those households that nowadays invest their limited resources to improve their living conditions but without technical guidance.

Calibration and Uncertainty Quantification for Single-Ended Raman-Based Distributed Temperature Sensing: Case Study in a 800 m Deep Coaxial Borehole Heat Exchanger.

Raman-based distributed temperature sensing (DTS) is a valuable tool for field testing and validating heat transfer models in borehole heat exchanger (BHE) and ground source heat pump (GSHP) applications. However, temperature uncertainty is rarely reported in the literature. In this paper, a new calibration method was proposed for single-ended DTS configurations, along with a method to remove fictitious temperature drifts due to ambient air variations. The methods were implemented for a distributed thermal response test (DTRT) case study in an 800 m deep coaxial BHE. The results show that the calibration method and temperature drift correction are robust and give adequate results, with a temperature uncertainty increasing non-linearly from about 0.4 K near the surface to about 1.7 K at 800 m. The temperature uncertainty is dominated by the uncertainty in the calibrated parameters for depths larger than 200 m. The paper also offers insights into thermal features observed during the DTRT, including a heat flux inversion along the borehole depth and the slow temperature homogenization under circulation.