Abstract: The latent heat thermal energy storage system is a
thrust area of research due to exuberant thermal energy storage
potential. The thermal performance of PCM is significantly
augmented by installation of the high thermal conductivity fins. The
objective of the present study is to obtain optimum size and location
of the fins to enhance diffusion heat transfer without altering overall
melting time. Hence, the constructal theory is employed to eliminate,
resize, and re-position the fins. A numerical code based on conjugate
heat transfer coupled enthalpy porosity approached is developed to
solve Navier-Stoke and energy equation. The numerical results show
that the constructal fin design has enhanced the thermal performance
along with the increase in the overall volume of PCM when
compared to conventional. The overall volume of PCM is found to be
increased by half of total of volume of fins. The elimination and repositioning
the fins at high temperature gradient from low
temperature gradient is found to be vital.
Abstract: River Hindon is an important river catering the
demand of highly populated rural and industrial cluster of western
Uttar Pradesh, India. Water quality of river Hindon is deteriorating at
an alarming rate due to various industrial, municipal and agricultural
activities. The present study aimed at identifying the pollution
sources and quantifying the degree to which these sources are
responsible for the deteriorating water quality of the river. Various
water quality parameters, like pH, temperature, electrical
conductivity, total dissolved solids, total hardness, calcium, chloride,
nitrate, sulphate, biological oxygen demand, chemical oxygen
demand, and total alkalinity were assessed. Water quality data
obtained from eight study sites for one year has been subjected to the
two multivariate techniques, namely, principal component analysis
and cluster analysis. Principal component analysis was applied with
the aim to find out spatial variability and to identify the sources
responsible for the water quality of the river. Three Varifactors were
obtained after varimax rotation of initial principal components using
principal component analysis. Cluster analysis was carried out to
classify sampling stations of certain similarity, which grouped eight
different sites into two clusters. The study reveals that the
anthropogenic influence (municipal, industrial, waste water and
agricultural runoff) was the major source of river water pollution.
Thus, this study illustrates the utility of multivariate statistical
techniques for analysis and elucidation of multifaceted data sets,
recognition of pollution sources/factors and understanding
temporal/spatial variations in water quality for effective river water
quality management.