Heat transfer enhancement (HTE) is a topic of everlasting importance in thermal engineering research. The latest focuses in this field are on nanosolutions for more efficient thermal transmission fluids (a) and designs of metallic foams (b) Metallic foams provide extended surfaces for HTE and possess advantages such as a high value of Cp, high thermal conductivity (TC) and being light weight. nanosolutions, on the other hand, can be used as an efficient HT medium as they exhibit higher TCs in comparison to base fluids. This review paper summarizes the physical properties of nanosolutions and or within the metal foam, focusing on HT and flow properties of nanosolutions, metal foam and combined NS-metal foam systems. The inspiration novelty for this review is the basic transference identifications for the HT enhancement of nanosolutions in porous media. The aim of the work is to provide insight on how nanosolutions in conjunction with porous media can be useful for HTE.
The Method of Discretization in Time (MDT) is a hybrid numerical technique intended to alleviate upfront the computational procedure of timedependent partial differential equations of parabolic type upfront. The MDT engenders a sequence of adjoint second order ordinary differential equations, wherein the space coordinate is the independent variable and time becomes an embedded parameter. Essentially, the adjoint second order ordinary differential equations are considered of “quasistationary” nature. In this work, the MDT is used for the analysis of unsteady heat conduction in regular bodies (large wall, long cylinder and sphere) accounting for nearly constant thermophysical properties, uniform initial temperature and surface heat flux. In engineering applications, the surface heat flux is customarily provided by electrical heating, radiative heating and pool fire heating. It is demonstrated that the approximate, semianalytical temperature solutions of the first adjoint “quasistationary” heat conduction equations using the first time jump are easily obtainable for each regular body. For enhanced acccuracy, regression analysis is applied to the deviations of the dimensionless surface temperature as a function of the dimensionless time for each regular body.
Bamboo is one of the noble plant species in Ethiopia. Household (HH) income and construction role of highland bamboo (Oldeania alpina (K. Schum.) Stapleto) stands were assessed at Masha district, Southern Ethiopia. Three peasant associations (PAs), Yepo, Yina and Gada, 7–15 key informants and 68, 46, 31 households, respectively were interviewed about the cost and income of bamboo to compare with woody climbers, honey, and mushroom in 2021. Bamboo was one of the main sources of income in all PAs, at least for fencing or house construction. In Yepo, Yina and Gada bamboo accounts 0.7%, 28.1%, 16.3% of the HH NTFP income, respectively. The local people responded that bamboo constructed houses and fences were durable for 15–30 and 2–10 years, respectively. In constructing a 2.44–4.27 m radius local house in Yepo, Yina and Gada 2.4–6 m3, 4.1–5.82 m3 and 3.1–4.3 m3 bamboo culms were harvested at 15, 20, and 30 years interval, respectively by each HH. Bamboo young shoots were also seasonally used for food. Although bamboo provides multiple uses, like substitute for wood and environmental services, it was facing different problems of deforestation. Therefore, policy attention is highly important for bamboo sustainable utilization.
Cartography includes two major tasks: map making and map application, which is inextricably linked to artificial intelligence technology. The cartographic expert system experienced the intelligent expression of symbolism. After the spatial optimization decision of behaviorism intelligent expression, cartography faces the combination of deep learning under connectionism to improve the intelligent level of cartography. This paper discusses three problems about the proposition of “deep learning + cartography”. One is the consistency between the deep learning method and the map space problem solving strategy, based on gradient descent, local correlation, feature reduction and non-linear nature that answer the feasibility of the combination of “deep learning + cartography”; the second is to analyze the challenges faced by the combination of cartography from its unique disciplinary characteristics and technical environment, involving the non-standard organization of map data, professional requirements for sample establishment, the integration of geometric and geographical features, as well as the inherent spatial scale of the map; thirdly, the entry points and specific methods for integrating map making and map application into deep learning are discussed respectively.
Spectrum map is the foundation of spectrum resource management, security governance and spectrum warfare. Aiming at the problem that the traditional spectrum mapping is limited to two-dimensional space, a three-dimensional spectrum data acquisition and mapping system architecture for the integration of space, sky and earth is presented, and a spectrum map reconstruction scheme driven by propagation model is proposed, which can achieve high-precision three-dimensional spectrum map rendering under the condition of sparse sampling. The spectrum map reconstructed by this method in the case of single radiation source and multiple radiation sources is in good agreement with the theoretical results based on ray tracing method. In addition, the measured results of typical scenes further verify the feasibility of this method.
Leisure education has an impact not only on individuals but also on the environment and society. The present study aimed to explore and describe experts’ knowledge and experience about leisure education to develop leadership among youth with physical disabilities. The present study used a qualitative research approach through an exploratory design to answer the research question. Five participants were purposefully recruited and selected based on their expertise in the topic of interest. Participants’ expertise ranged from leisure, recreation, youth and leadership. The participants had experience working in higher education institutions, and community projects, held doctorate qualifications, and have over ten years in this field. Data was collected online using Google Meet software using semi-structured interviews with open-ended questions. Data was analyzed using a thematic analysis framework and guidelines. The findings of this study suggest that youth with physical disabilities can develop personal capacity through leisure education programmes. Leisure education programmes can be meaningful to youth with physical disabilities and have a developmental impact, including leadership. Youth with physical disabilities’ capacities and abilities should be nurtured and protected to allow growth and independence. The implications are that leisure education programmes for leadership development must be intentional to achieve the intended outcome.
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