In recent years, the foundry sector has been showing an increased interest in reclamation of used sands. Grain shape, sieve analysis, chemical and thermal characteristics must be uniform while molding the sand for better casting characteristics. The problem that tackled by every foundry industry is that of processing an adequate supply of sand which has the properties to meet many requirements imposed upon while molding and core making. Recently, fluidized bed combustors are becoming core of ‘clean wastes technology’ due to their efficient and clean burning of sand. For proven energy efficient sand reclamation processing, analysis of heating system in fluidized bed combustor (FBC) is required. The objective of current study is to design heating element and analysis of heating system by calculation of heat losses and thermal analysis offluidized bed combustorfor improving efficiency.

The regulation of compressor extraction and energy storage can improve the performance of gas turbine energy system. In order to make the gas turbine system match the external load more flexibly and efficiently, a gas turbine cogeneration system with solar energy coupling compressor outlet extraction and energy storage is proposed. By establishing the variable condition mathematical model of air turbine, waste heat boiler and solar collector, we use Thermoflex software to establish the variable condition model of gas turbine compressor outlet extraction, and analyze the variable condition of the coupling system to study the changes of thermal parameters of the system in the energy storage, energy release and operation cycle. Taking the hourly load of a hotel in South China as an example, this paper analyzes the case of the cogeneration system of solar energy coupling compressor outlet extraction and energy storage, and compares it with the benchmark cogeneration system. The results show that taking a typical day as a cycle, the primary energy utilization rate of the system designed in this paper is 3.2% higher than that of the traditional cogeneration system, and the efficiency is 2.4% higher.

This paper uses a new cross-country cross-industry dataset on investment in tangible and intangible assets for 18 European countries and the US.  We set out a framework for measuring intangible investment and capital stocks and their effect on output, inputs and total factor productivity. The analysis provides evidence on the diffusion of intangible investment across Europe and the US over the years 2000-2013 and offers growth accounting evidence before and after the Great Recession in 2008-2009. Our major findings are the following. First, tangible investment fell massively during the Great Recession and has hardly recovered, whereas intangible investment has been relatively resilient and recovered fast in the US but lagged behind in the EU. Second, the sources of growth analysis including only national account intangibles (software, R&D, mineral exploration and artistic originals), suggest that capital deepening is the main driver of growth, with tangibles and intangibles accounting for 80% and 20% in the EU while both account for 50% in the US, over 2000-2013. Extending the asset boundary to the intangible assets not included in the national accounts (Corrado, Hulten and Sichel (2005)) makes capital deepening increase. The contribution of tangibles is reduced both in the EU and the US (60% and 40% respectively) while intangibles account for a larger share (40% in EU and 60% in the US). Then, our analysis shows that since the Great Recession, the slowdown in labour productivity growth has been driven by a decline in TFP growth with relatively a minor role for tangible and intangible capital. Finally, we document a significant correlation between stricter employment protection rules and less government investment in R&D, and a lower ratio of intangible to tangible investment.

This study aims to investigate the enhancement in electrical efficiency of a polycrystalline photovoltaic (PV) module. The performance of a PV module primarily depends upon environmental factors like temperature, irradiance, etc. Mainly, the PV module performance depends upon the panel temperature. The performance of the PV module has an inverse relationship with temperature. The open circuit voltage of a module decreases with the increase in temperature, which consequently leads to the reduction in maximum power, efficiency, and fill factor. This study investigates the increase in the efficiency of the PV module by lowering the panel temperature with the help of water channel cooling and water-channel accompanied with forced convection. The two arrangements, namely, multi-inlet outlet and serpentine, are used to decrease the temperature of the polycrystalline PV module. Copper tubes in the form of the above arrangements are employed at the back surface of the panel. The results demonstrate that the combined technique is more efficient than the simple water-channel cooling technique owing to multi-heat dissipation and effective heat transfer, and it is concluded that the multi-inlet outlet cooling technique is more efficient than the serpentine cooling technique, which is attributed to uniform cooling over the surface and lesser pressure losses.

Smallholder paprika farmers in Zimbabwe contribute to local economies and food security but face supply chain challenges like limited market access and poor infrastructure which lead to post harvest losses and unpredictable prices. To survive, these farmers must adopt sustainable value networks to reduce operational costs and improve performance. This study sought to establish the effect of sustainable value networks on the operational performance of smallholder paprika farming in Zimbabwe. This study, using a positivist research philosophy and a quantitative approach, surveyed 288 smallholder paprika farmers in Zimbabwe. Exploratory factor analysis and partial least squares structural equation modelling were used to validate the constructs and test the hypothesised relationships. Results demonstrate a moderate level of implementation of value networks in smallholder paprika farming characterised by successes and challenges. The findings illustrated resource sharing among smallholder farmers, facilitated by initiatives, such as recycled seed exchanges and financial support through village savings and loan associations. However, results show that challenges persist, particularly with market access and financial support. Results indicate that there is a significant awareness and implementation of green supply chain management practices among smallholder paprika farmers even though they do not have access to resources and live in rural areas. The findings demonstrate that value networks significantly influence the adoption of green supply chain management practices, which in turn positively impact operational performance, environmental performance, and social performance. Green supply chain management practices were found to mediate the relationship between value networks and environmental performance, social performance, and operational performance, underlining the critical role of sustainable practices in enhancing performance outcomes. While environmental performance showed a positive effect on operational performance, the direct influence of social performance on operational performance was found to be statistically insignificant, suggesting the need for further exploration of the factors linking social benefits to operational efficiency. The research contributes to both theory and practice by presenting a sustainable value network model for smallholder paprika farmers, integrating value network, green supply chain management practices and environmental performance to enhance operational performance. Practical implications include policy recommendations to strengthen collaboration between smallholder farmers and other stakeholdersand address power imbalances with intermediaries. Future research should extend the study to other agricultural sectors and incorporate more diverse stakeholder perspectives to validate and generalise the proposed sustainable value network model.