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Abstract The improvement of thermodynamic efficiency of power plants is of great interest for the whole energy industry. The use of Kalina cycle has a great potential to improve the thermal efficiency of a nuclear power plant. This cycle uses a mixture of ammonia and water as working fluid. In this paper, we discuss the development of an Ammonia-Water mixture Property Code (AWProC). The estimation of the mixture properties are based on the Gibbs free energy functions. The code is verified and validated against experimental data available in the literature and REFPROP code. It is shown that AWProC can accurately estimate the thermodynamic properties of ammonia-water mixtures over a wide range of conditions, including high temperature and pressure regions. The code is then used to investigate the feasibility of applying the Kalina cycle to a typical Pressurizer Water Reactor (PWR) plant as an effective way to improve the plant efficiency. The fundamental of Basic-Kalina (B-K) cycle is described in detail firstly. Then, two modified configurations, Recuperation-Kalina (R-K) and Flash-Kalina (F-K) cycles respectively, are proposed for a typical 1000 MWe PWR. The simulation results indicate that the R-K type cycle can reach about 31.2% efficiency with simple equipment requirements, while the F-K type cycle can reach efficiencies up to about 34.8%, but at the expenses of a slightly more complex design. The present work demonstrates the applicability of the Kalina cycle as a way to improve the thermal efficiency of a nuclear power plant. This concept is meaningful for improving nuclear power plants economic and competitiveness.

In this paper, we compare 2015 satellite-derived natural gas (gas) flaring data with the greenhouse gas reduction targets presented by those countries in their nationally determined contributions (NDC) under the United Nations Framework Convention on Climate Change (UNFCCC) Paris Agreement. Converting from flaring to utilization is an attractive option for reducing emissions. The analysis rates the potential role of reduction of gas flaring in meeting country-specific NDC targets. The analysis includes three categories of flaring: upstream in oil and gas production areas, downstream at refineries and transport facilities, and industrial (e.g., coal mines, landfills, water treatment plants, etc.). Upstream flaring dominates with 90.6% of all flaring. Global flaring represents less than 2% of the NDC reduction target. However, most gas flaring is concentrated in a limited set of countries, leaving the possibility that flaring reduction could contribute a sizeable portion of the NDC targets for specific countries. States that could fully meet their NDC targets through gas flaring reductions include: Yemen (240%), Algeria (197%), and Iraq (136%). Countries which could meet a substantial portion of their NDC targets with gas flaring reductions include: Gabon (94%), Algeria (48%), Venezuela (47%), Iran (34%), and Sudan (33%). On the other hand, several countries with large flared gas volumes could only meet a small portion of their NDC targets from gas flaring reductions, including the Russian Federation (2.4%) and the USA (0.1%). These findings may be useful in guiding national level efforts to meet NDC greenhouse gas reduction targets. Keywords: VIIRS, Gas flaring, Nightfire, Nationally determined contributions, UN climate agreement

Alpine, subalpine and boreal tree species, of low genetic diversity and adapted to low optimal temperatures, are vulnerable to the warming effects of global climate change. The accurate prediction of these species’ distributions in response to climate change is critical for effective planning and management. The goal of this research is to predict climate change effects on the distribution of red spruce (Picea rubens Sarg.) in the Great Smoky Mountains National Park (GSMNP), eastern USA. Climate change is, however, conflated with other environmental factors, making its assessment a complex systems problem in which indirect effects are significant in causality. Predictions were made by linking a tree growth simulation model, red spruce growth model (ARIM.SIM), to a GIS spatial model, red spruce habitat model (ARIM.HAB). ARIM.SIM quantifies direct and indirect interactions between red spruce and its growth factors, revealing the latter to be dominant. ARIM.HAB spatially distributes the ARIM.SIM simulations under the assumption that greater growth reflects higher probabilities of presence. ARIM.HAB predicts the future habitat suitability of red spruce based on growth predictions of ARIM.SIM under climate change and three air pollution scenarios: 10% increase, no change and 10% decrease. Results show that suitable habitats shrink most when air pollution increases. Higher temperatures cause losses of most low-elevation habitats. Increased precipitation and air pollution produce acid rain, which causes loss of both low- and high-elevation habitats. The general prediction is that climate change will cause contraction of red spruce habitats at both lower and higher elevations in GSMNP, and the effects will be exacerbated by increased air pollution. These predictions provide valuable information for understanding potential impacts of global climate change on the spatiotemporal distribution of red spruce habitats in GSMNP.

<p>Increasing renewable energy penetrations bring complex feasibility and stability problems. Data-driven methods are applied in extracting and embedding these feasibility and stability rules in power system operations and planning. This paper presents a method of alternate support vector machine decision trees for rule extraction problems. The method has significant improvements to the classical decision-tree-based algorithms in terms of efficiency, stability and versatility. Finally, we apply the method to several power and energy system scenarios to show its effectiveness.</p>

The Proliferation Assessment (program area - Things Thin) within the Defense Systems and Assessment Investment Area desires high energy density and long-lived power sources with moderate currents (mA) that can be used as building blocks in platforms for the continuous monitoring of chemical, biological, and radiological agents. Fuel cells can be an optimum choice for a power source because of the high energy densities that are possible with liquid fuels. Additionally, power generation and fuel storage can be decoupled in a fuel cell for independent control of energy and power density for customized, application-driven power solutions. Direct methanol fuel cells (DMFC) are explored as a possible concept to develop into ultrathin or two-dimensional power sources. New developments in nanotechnology, advanced fabrication techniques, and materials science are exploited to create a planar DMFC that could be co-located with electronics in a chip format. Carbon nanotubes and pyrolyzed polymers are used as building block electrodes - porous, mechanically compliant current collectors. Directed assembly methods including surface functionalization and layer-by-layer deposition with polyelectrolytes are used to pattern, build, and add functionality to these electrodes. These same techniques are used to incorporate nanoscale selective electrocatalyst into the carbon electrodes to provide a high density more » of active electron transfer sites for the methanol oxidation and oxygen reduction reactions. The resulting electrodes are characterized in terms of their physical properties, electrocatalytic function, and selectivity to better understand how processing impacts their performance attributes. The basic function of a membrane electrode assembly is demonstrated for several prototype devices. « less

Since its invention in 2009, Perovskite solar cells (PSCs) has attracted great attention because of its low cost, numerous options of efficiency enhancement, ease of manufacturing and high-performance. Within a short span of time, the PSC has already outperformed thin-film and multicrystalline silicon solar cells. A current certified efficiency of 25.2% demonstrates that it has the potential to replace its forerunner generations. However, to commercialize PSCs, some problems need to be addressed. The toxic nature of lead which is the major component of light absorbing layer, and inherited stability issues of fabricated devices are the major hurdles in the industrialization of this technology. Therefore, new researching areas focus on the lead-free metal halide perovskites with analogous optical and photovoltaic performances. Tin being nontoxic and as one of group IV(A) elements, is considered as the most suitable alternate for lead because of their similarities in chemical properties. Efficiencies exceeding 13% have been recorded using Tin halide perovskite based devices. This review summarizes progress made so far in this field, mainly focusing on the stability and photovoltaic performances. Role of different cations and their composition on device performances and stability have been involved and discussed. With a considerable room for enhancement of both efficiency and device stability, different optimized strategies reported so far have also been presented. Finally, the future developing trends and prospects of the PSCs are analyzed and forecasted.

The research focus has shifted towards lightweight structures with high energy absorption capabilities due to advancements in automotive safety technology. This study specifically investigates the impact of cross-sectional area on the energy absorption characteristics of hemispherical composite shells. The experimental phase involves characterizing a glass fiber epoxy composite, followed by the manufacture of hemispherical composite shell specimens with varying cross-sectional areas. These specimens undergo quasi-static axial compressive loading, and the energy absorption parameters are analyzed. The results indicate a significant influence of the composite cross-sectional area on the crushing behavior of hemispherical shells, with a observed decrease in specific energy absorption as the cross-sectional area increases. Additionally, a 3D Finite Element (FE) model is created using ABAQUS FE code to numerically simulate the crushing process. The model's predictions are compared and validated against experimentally measured values, demonstrating a satisfactory correlation.

In recent years, the accelerating climate change and intensifying natural disasters have called for more renewable, resilient, and reliable energy from more distributed sources to more diversified consumers, resulting in a pressing need for advanced situational awareness of modern smart distribution systems [...]