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  • Thermophysical Properties o...
    Sah, Pawan Kishor; Kumar, Shiv Shankar; Sreedeep, S.

    International journal of thermophysics, 04/2023, Letnik: 44, Številka: 4
    Journal Article

    The surrounding (backfill) materials around the underground power cable systems are essential for dissipating the heat away from it, during the exertion phases. The heat dissipation restrains the thermal instability and risk of progressive drying of the backfill materials, thus reducing the thermal stress on the power cable. Thermal instability indicates the reduction in thermal properties (conductivity or diffusivity) due to the migration of moisture because of heat accumulation. Thus, the backfill materials should have adequate thermal properties and water retention capacity to transfer the heat from the heat source to the surrounding area with minimal moisture migration. The bentonite has high water retention capacity, but low thermal conductivity, whereas sand/fly ash exhibits low water retention and has higher thermal conductivity than bentonite. The addition of bentonite promotes the water holding capacity and thermophysical properties of sand and fly ash. Therefore, this study presents the thermal properties of backfill materials, bentonite–fly ash (B–F) and bentonite–sand (B–S), at varying weight-percent of sand and fly ash with bentonite. Various compositions of the mixtures were compacted to varying dry densities, and water contents and thermal properties variation of backfill materials were measured using a dual thermal needle probe ‘KD2 Pro’ at room temperature. The study deals with the systematic evaluation of the volumetric specific heat capacity, thermal conductivity, and diffusivity of backfill materials against varying dry density and water content. The threshold water content (TWC) has been determined from the thermal diffusivity–water content variation curve, and it has correlated with plastic limit (PL) and optimum moisture content (OMC). Thereafter, the efficacies of two thermal conductivity prediction models have also been evaluated statistically with respect to experimental results.