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Abstract The promise of redox flow batteries (RFBs) utilizing soluble redox couples, such as all vanadium ions as well as iron and chromium ions, is becoming increasingly recognized for large-scale energy storage of renewables such as wind and solar, owing to their unique advantages including scalability, intrinsic safety, and long cycle life. An ongoing question associated with these two RFBs is determining whether the vanadium redox flow battery (VRFB) or iron-chromium redox flow battery (ICRFB) is more suitable and competitive for large-scale energy storage. To address this concern, a comparative study has been conducted for the two types of battery based on their charge–discharge performance, cycle performance, and capital cost. It is found that: i) the two batteries have similar energy efficiencies at high current densities; ii) the ICRFB exhibits a higher capacity decay rate than does the VRFB; and iii) the ICRFB is much less expensive in capital costs when operated at high power densities or at large capacities.

The offshore wells are subject to hostile environments of such areas as the North Sea, GOM and the high arctic. The strong loop ocean currents and induced eddies can pose significant problems for deep-water well. Broadly divided ocean currents, surface currents, bottom currents and vertical currents, interact with the deep water well structures as one of environmental forces. One of the engineering challenges in deep water drilling is temperature gradient. In the past the temperature in the wellbore was ignored and an isothermal system was assumed because no practical means existed to determine the well bore temperature profile. But the fact is that the negative thermal gradient exists between surface to seafloor and it becomes positive below the seafloor. The extreme values could be as low as 40°F and as high as 150∼200°F. In addition to low temperature condition, the significant heat exchange also occurs for high temperature and geothermal reservoirs. The universal matrix form of implicit finite differential equations is introduced to predict the temperature profile of the fluid in the well and near-wellbore formation. This paper is to combine various factors together to derive a solver for the transient temperature modeling during the dirculation of riserless drilling, which can be the basis to describe the near-wellbore well stability under geo-thermal stress and predict the annular pressure during HPHT injection or production, which can also be used to including but not limited to the dynamic temperature profile and bottom-hole temperature, improving cementing program design, casing thermal stresses to be determined.

Charging lithium–oxygen batteries with redox mediators suppresses singlet oxygen generation at rates orders of magnitude faster than quenchers.

Using an experiment embedded within a representative survey, this study examined the interactive effect of party identification and risk/benefit perception on public opinion about biofuels. Democrats tended to be more supportive of biofuels than Republicans. However, the effect of party identification on opinion about biofuels varied when individuals considered the risk/benefit of biofuels in different domains. Individuals who reported greater affiliation with the Democratic Party were likely to support funding biofuels research when primed with the economic risks or the social/ethical benefits of biofuels. For those who considered the social/ethical benefits of biofuels, more self-identified Democrats were likely to support biofuels production and use. However, more self-identified Democrats were less supportive of biofuels production and use when they considered the political risks of biofuels. Implications are discussed.

Abstract Explosion risk analysis (ERA) is an effective method to investigate potential accidents in hydrogen production facilities. The ERA suffers from significant hydrogen dispersion-explosion scenario-related parametric uncertainty. To better understand the uncertainty in ERA results, thousands of Computational Fluid Dynamics (CFD) scenarios need to be computed. Such a large number of CFD simulations are computationally expensive. This study presents a stochastic procedure by integrating a Bayesian Regularization Artificial Neural Network (BRANN) methodology with ERA to effectively manage the uncertainty as well as reducing the stimulation intensity in hydrogen explosion risk study. This BRANN method randomly generates thousands of non-simulation data presenting the relevant hydrogen dispersion and explosion physics. The generated data is used to develop scenario-based probability models, which are then used to estimate the exceedance frequency of maximum overpressure. The performance of the proposed approach is verified by analyzing the parametric sensitivity on the exceedance frequency curve and comparing the results against the traditional ERA approach.

Abstract The present study is aimed to investigate and compare effects of biodiesel-ethanol (BE) and biodiesel-n-butanol (BBu) blends on combustion, performance and emissions of a direct-injection diesel engine. Experiments were conducted on BE5 (5% ethanol and 95% biodiesel, v/v), BE10, BE15, BBu5, BBu10 and BBu15, at five engine loads and at 1800 rpm. In regard to combustion characteristics, effects on maximum heat release rate, maximum in-cylinder pressure, start of combustion, combustion duration and coefficients of variations (COVs) of IMEP and maximum increase rate of in-cylinder pressure were investigated. In regard to engine performance, effects on BSFC and BTE were investigated. The blended fuels have adverse effects on engine performance especially at low load, with the BE blends having more adverse effects than the BBu blends. Moreover, on average of the five engine loads, the BBu and BE blends increase CO emission by 13.7% and 22.8% and HC emission by 5.6% and 29.2%, respectively; but reduce NOx emission by 6.5% and 28.0%, particle mass concentration by 20.7% and 20.6% and particle number concentration by 22% and 21%, respectively. Overall, the BE blends are more effective in reducing particulate and NOx emissions but the BBu blends would lead to less increase in CO and HC emissions.

Abstract Renewable energy utilisation, latent energy storage, optimal system design, and robust system operation are critical elements for carbon-free buildings and communities. Machine learning methods are effective to assist the energy-efficient renewable systems during multi-criteria design and multi-level uncertainty-based operation periods. However, the current literature provides little knowledge on this topic. In this study, a state-of-the-art-review on phase change materials for cooling applications is presented, in terms of smart ventilations, intelligent PCMs charging/discharging, deterministic parametrical analysis, stochastic uncertainty-based performance prediction and optimisation. Furthermore, technical effectiveness of machine learning methods in single and multi-objective optimisations has been presented, through hybrid PCMs integrated renewable systems. Multivariables involved in the review include thermo-physical, geometrical and operating parameters of PCMs. Multi-criteria employed in the review include heat transfer rate, cooling energy storage density, heat storage and release efficiency, and indoor thermal comfort. The literature review presents technical challenges, such as tradeoff solutions between computational accuracy and efficiency, generic methods for effective selection amongst multi-diversified optimal solutions along the Pareto front, the general methodology for multi-level uncertainty quantification, smart controllers with accurate predictions under high-level parameters’ uncertainty and stochastic occupants’ behaviors. The future outlook and recommendations of machine learning methods in PCMs integrated cooling systems have also been presented as avenues for upcoming research.

Abstract Conventional vanadium redox flow batteries (VRFBs) using Nafion 115 suffered from issues associated with high ohmic resistance and high capital cost. In this work, we report a commercial membrane (VANADion), consisting of a porous layer and a dense Nafion layer, as a promising alternative to Nafion 115. In the dual-layer structure, the porous layer (∼210 μm) can offer a high ionic conductivity and the dense Nafion layer (∼20 μm) can depress the convective flow of electrolyte through the membrane. By comparing with the conventional Nafion 115 in a VRFB, it is found that the change from the conventional Nafion 115 to the composite one results in an increase in the energy efficiency from 71.3% to 76.2% and an increase in the electrolyte utilization from 54.1% to 68.4% at a current density of as high as 240 mA cm−2. In addition, although two batteries show the comparable cycling performance at current densities ranging from 80 mA cm−2 to 240 mA cm−2, the composite membrane is estimated to be significantly cheaper than the conventional Nafion 115 due to the fact that the porous layer is rather cost-effective and the dense Nafion layer is rather thin. The impressive combination of desirable performance and low cost makes this composite membrane highly promising in the VRFB applications.

Abstract Ground source heat pump (GSHP) systems can provide cost effective and sustainable heating and cooling for buildings while using considerably less fossil fuel than conventional heating and cooling systems. This benefit can be further enhanced by adopting hybrid GSHP (HGSHP) systems wherein the GSHP component provides the baseload thermal energy with the balance provided by conventional systems. This study compares the costs of GSHP and HGSHP systems against conventional systems under a variety of climatic conditions, exemplified by those encountered across Australia, but including conditions encountered elsewhere. The results indicate that the comparative performance of GSHP and HGSHP systems depend on many parameters including climatic conditions, ground conditions, drilling prices and prices of electricity and gas in the regions where the systems are installed. Here we show that in general, adopting GSHP or HGSHP systems over conventional systems allow property owners to pay lower lifetime costs under most climatic conditions and gas to electricity energy price ratios. The results also indicate that conventional systems may be preferred in highly heating or cooling dominant climates and at locations with high drilling costs or low energy prices. In contrast, GSHP and HGSHP systems are preferred in locations with a more balanced climate, lower drilling costs and/or higher energy prices. There is no “one size fits all” rule given the many factors that can influence the lifetime costs. The paper shows that climatic conditions, ground conditions, drilling and energy costs must all be carefully considered when assessing the most cost effective sustainable energy technologies for space heating and cooling.