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Abstract Dimethyl ether appears to be a better choice among various diesel alternatives due to its high cetane number and sootless combustion. However, the physical and chemical properties of dimethyl ether are very different from those of diesel. The physical properties influence spray formation and atomization characteristics, while chemical properties determine combustion and emission formation characteristics. Thus, fuel's physical and chemical properties significantly determine engine performance and emissions. In the present work, spray combustion and emission formation characteristics of n-heptane, dimethyl ether, and their blends (10, 25, and 50% dimethyl ether in n-heptane) were numerically studied in a constant volume chamber. Results show that the n-heptane spray combustion has the highest heat release rate with an intense premix combustion phase, whereas dimethyl ether spray combustion has the lowest heat release rate and shortest premix combustion phase. The magnitude of the premixed phase and heat release rate decreases with the increase in dimethyl ether mass fraction in the blends. Soot, carbon monoxide (CO), unburned hydrocarbon (UHC), and nitric oxide (NO) emissions decreased with the increase in the dimethyl ether mass fraction in the blends and were lowest for the dimethyl ether.

Abstract Heat pipes and two-phase thermosyphons are highly efficient heat transfer devices utilizing continuous evaporation and condensation of working fluid for two-phase heat transport in closed systems. Because of the nearly isothermal and fully passive phase-change heat transfer mechanism, heat pipes and thermosyphons have found many applications in nuclear engineering, space technologies, and other energy systems. High-temperature heat pipes are used in nuclear microreactors to remove fission power from the primary system and are coupled with power conversion systems or process heat applications. Modeling of the two-phase flow phenomena inside a heat pipe is essential to its design and safety analysis. In this study, a comprehensive one-dimensional two-phase three-field flow model has been developed for the analysis of heat pipes in normal operation conditions and transients. The conservation or field equations of mass, momentum, and energy were developed for the liquid film, vapor, and droplet. In addition, constitutive models or correlations were reviewed thoroughly and provided for the closure of the three-field equations. Specific constitutive equations regarding interfacial mass and heat transfer at two interfaces, namely film-gas interface and gas-droplet interface, were reviewed for droplet entrainment and deposition rates as well as film and droplet evaporation rates. Additionally, mechanistic correlations of annular flow film thickness were recommended for the modeling of the thermosyphons without a wick as a critical constitutive correlation. Furthermore, experimental data needs from new experiments using a prototype working fluid or surrogate fluids for the model validation of high-temperature heat pipes in microreactors were recommended for future research.

Abstract The main hindrances to the large-scale development of renewable-energy projects are the lack of bankability and the inability to align investments and investors with suitable financial instruments or robust policy measures. To illustrate a bankable project, this paper presents a research-based case study on the installation of solar photovoltaic panels on the rooftops of 195 trains of the Indian Railways. Detailed information on the annual running hours, exposure to sunlight, efficiency of solar photovoltaic generation and electrical power demands of each rail coach is considered to conduct a quantitative measure of the tentative amount of fossil fuel savings. The purpose is to provide insight into the types of renewable-energy projects that can be highly attractive to financial institutions and promoters due to their lucrative internal return on investment. As seen in this case study, there are annual savings in diesel of 12 323 088 litres and a CO2 reduction of 32 755 tonnes, with return on investment of 1.3 years. Furthermore, this study conducts a comprehensive analysis of the limitations of existing renewable-energy project financing mechanisms in India. Subsequently, three policy measures are recommended to develop a robust financial mechanism that can effectively meet the needs of investors and investors. These measures include increasing equity injection through a buy-and-hold strategy, providing direct tax benefits to promoters and financing through real-estate investment trusts. The findings are highly relevant to address the challenges associated with bridging the financial gap between access to finance and capital investment in the renewable-energy sector, especially for Asian countries.

Yeast volatiles double starvation survival in Drosophila .

Lithium-ion batteries exhibit a dynamic voltage behaviour depending nonlinearly on current and state of charge. The modelling of lithium-ion batteries is therefore complicated and model parametrisation is often time demanding. Grey-box models combine physical and data-driven modelling to benefit from their respective advantages. Neural ordinary differential equations (NODEs) offer new possibilities for grey-box modelling. Differential equations given by physical laws and NODEs can be combined in a single modelling framework. Here we demonstrate the use of NODEs for grey-box modelling of lithium-ion batteries. A simple equivalent circuit model serves as a basis and represents the physical part of the model. The voltage drop over the resistor–capacitor circuit, including its dependency on current and state of charge, is implemented as a NODE. After training, the grey-box model shows good agreement with experimental full-cycle data and pulse tests on a lithium iron phosphate cell. We test the model against two dynamic load profiles: one consisting of half cycles and one dynamic load profile representing a home-storage system. The dynamic response of the battery is well captured by the model.

The solutions-based design framework of permaculture exhibits transformative potential, working to holistically integrate natural and human systems toward a more just society. The term can be defined and applied in a breadth of ways, contributing to both strengths and weaknesses for its capacity toward change. To explore the tension of breadth as strength and weakness, we interviewed 25 prominent permaculture teachers and practitioners across the United States (US) regarding how they define permaculture as a concept and perceive the term’s utility. We find that permaculture casts a wide net that participants grapple with in their own work. They engaged in a negotiation process of how they associate or disassociate themselves with the term, recognizing that it can be both unifying and polarizing. Further, there was noted concern of permaculture’s failure to cite and acknowledge its rootedness in Indigenous knowledge, as well as distinguish itself from Indigenous alternatives. We contextualize these findings within the resounding call for a decolonization of modern ways of living and the science of sustainability, of which permaculture can be critically part of. We conclude with recommended best practices for how to continuously (re-)define permaculture in an embodied and dynamic way to work toward these goals.

Abstract The present work attempts to devise an efficient method utilizing an on-grid photovoltaic-thermal heat pump water heater (PV-THPWH) integrated with a real-time variable frequency controller to achieve the goal of energy-efficient buildings. The prime focus is to reduce the grid's dependence on the compressor's energy-intensive operation by employing a feedback-controlled variable frequency drive (VFD). Additionally, the possibilities involved with addressing the electrical and thermal energy requirements of an energy-efficient building was investigated utilizing the proposed system. R-32 refrigerant in the photovoltaic-thermal (PV-T) evaporator coils of the heat pump assembly help to cool the photovoltaic (PV) panel while delivering the absorbed heat in the condenser to heat water contained inside the storage tank. Outdoor experiments and theoretical investigations of the combined system were carried out to appraise the dynamic behavior under varying solar irradiation and ambient temperature conditions. The observations conveyed that the PV-THPWH system succeeded in reducing the PV panel operating temperature by 25%, which resulted in a 20% increment in PV power output. Also, the performance indicators, such as the instantaneous energy efficiency and instantaneous PV efficiency, were found to increase by 15% and 34%, respectively, resulting in an average coefficient of performance of 6.4. For a clear sky day, the recorded total PV energy output was 4.67 units, while the VFD compressor consumption was 3.42 units, and the surplus 1.25 units were sent to the grid. Furthermore, the economic analysis reported a payback period of 2.3 years for the developed PV-THPWH system.

Global sensitivity analysis (GSA) of distribution system with respect to stochastic PV and load variations plays an important role in designing optimal voltage control schemes. This paper proposes a data-driven framework for GSA of distribution system. In particular, two representative surrogate modeling-based approaches are developed, including the traditional Gaussian process-based and the analysis of variance (ANOVA) kernel ones. The key idea is to develop a surrogate model that captures the hidden global relationship between voltage and real and reactive power injections from the historical data. With the surrogate model, the Sobol indices can be conveniently calculated through either the sampling-based method or the analytical method to assess the global sensitivity of voltage to variations of load and PV power injections. The sampling-based method estimates the Sobol indices using Monte Carlo simulations while the analytical method calculates them by resorting to the ANOVA expansion framework. Comparison results with other model-based GSA methods on the unbalanced three-phase IEEE 37-bus and 123-bus distribution systems show that the proposed framework can achieve much higher computational efficiency with negligible loss of accuracy. The results on a real 240-bus distribution system using actual smart meter data further validate the feasibility and scalability of the proposed framework.