Factors affecting people’s participation in joint forest management programmes in Kinnaur district of Himachal Pradesh, India

The present investigation examined the various factors affecting people's participation in the planning, implementation and maintenance of JFM programmes in the tribal distrct (Kinnaur) of Himachal Pradesh. In total, 10 factors were identified that influence people’s participation in Joint Forest Management (JFM) activities in the study area, which were independently affecting in all of three development blocks. District as a whole factors affecting in decreasing order were Lack of awareness about participatory forest management (66%), lack of co-ordination with forestry officials (64%), non availability of routine funds (56%), lack of training and visit programme (56%), clash between agriculture and JFM activities (54%), lack of emphasis on quick economic activities (49%), improper usufruct sharing (43%) etc. were some of major factors that influenced people’s participation. Policy and development emphasis on these factors, particularly taking into consideration the geography and need based activity in the various development blocks will increase the people’s participation in similar kind of projects

Simulation of dimensionality effects in thermal transport

The discovery of nanostructures and the development of growth and fabrication techniques of one- and two-dimensional materials provide the possibility to probe experimentally heat transport in low-dimensional systems. Nevertheless measuring the thermal conductivity of these systems is extremely challenging and subject to large uncertainties, thus hindering the chance for a direct comparison between experiments and statistical physics models. Atomistic simulations of realistic nanostructures provide the ideal bridge between abstract models and experiments. After briefly introducing the state of the art of heat transport measurement in nanostructures, and numerical techniques to simulate realistic systems at atomistic level, we review the contribution of lattice dynamics and molecular dynamics simulation to understanding nanoscale thermal transport in systems with reduced dimensionality. We focus on the effect of dimensionality in determining the phononic properties of carbon and semiconducting nanostructures, specifically considering the cases of carbon nanotubes, graphene and of silicon nanowires and ultra-thin membranes, underlying analogies and differences with abstract lattice models.Comment: 30 pages, 21 figures. Review paper, to appear in the Springer Lecture Notes in Physics volume "Thermal transport in low dimensions: from statistical physics to nanoscale heat transfer" (S. Lepri ed.

Self-Assembly for Integration of Microscale Thermoelectric Coolers

Optimum thermoelectric cooling (TEC) solutions often require the integration of component sizes inaccessible by common manufacturing techniques such as thin-film processing and robotic assembly. This work considers an application case in which small elements (100 μm to 300 μm thick) are optimal. A capillary self-assembly process is presented as a potential route to manufacturing TECs in these size ranges. A millimeter-scale demonstration of the assembly concept is presented and Monte Carlo simulation is used to study the scaling of the self-assembly approach to assemblies with more components. While assembly rate and system yield can be a challenge, several approaches are presented for increasing both rate and yield

A Review of Thermal Conductivity Models for Nanofluids

Nanofluids, as new heat transfer fluids, are at the center of attention of researchers, while their measured thermal conductivities are more than for conventional heat transfer fluids. Unfortunately, conventional theoretical and empirical models cannot explain the enhancement of the thermal conductivity of nanofluids. Therefore, it is important to understand the fundamental mechanisms as well as the important parameters that influence the heat transfer in nanofluids. Nanofluids’ thermal conductivity enhancement consists of four major mechanisms: Brownian motion of the nanoparticle, nanolayer, clustering, and the nature of heat transport in the nanoparticles. Important factors that affect the thermal conductivity modeling of nanofluids are particle volume fraction, temperature, particles size, pH, and the size and property of nanolayer. In this paper, each mechanism is explained and proposed models are critically reviewed. It is concluded that there is a lack of a reliable hybrid model that includes all mechanisms and influenced parameters for thermal conductivity of nanofluids. Furthermore, more work needs to be conducted on the nature of heat transfer in nanofluids. A reliable database and experimental data are also needed on the properties of nanoparticles.http://www.tandfonline.com/loi/uhte202016-09-30hb201