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Abstract Predicting the distribution and resource of gas hydrates and understanding gas hydrate forming mechanisms are critical for assessing natural gas hydrate exploration potential, as well as exploiting hydrates. This study aims to provide a portable solution for evaluating resource of natural gas hydrate and quantifying contribution of methane sources via numerical simulations constrained by site-specific data. To numerically describe the complex process of biogenic methane production, an integrated simulation package, TOUGH + Hydrate + React (TOUGH + HR), was developed by coupling reactive transport, biodegradation and deposition of organic matter with behavior of hydrate-bearing system. Based on observed data from site SH2 in the South China Sea, a growing one-dimensional column model was constructed, and simulated via the developed TOUGH + HR tool. The results showed that when considering biogenic methane was the only source for hydrate, simulated maximum saturation of hydrate reached ~ 0.19, which is much lower than the observed value (~0.46), suggesting that the in-situ biogenic methane is not enough to form the high-saturation hydrate. When the upward flux of methane (considered as thermogenic methane) increased to 1.00 × 10−11 k g · m - 2 · s - 1 , both simulated saturation and distribution of hydrates matched the observed data well, including the profile of remained total organic carbon (TOC), the location of interface between dissolved methane and sulfate (SMI), and the derived chlorinity. Simulation results suggest that the ratio of biogenic methane to thermogenic methane forming hydrates was about 1:3. Predicted amount of methane hydrate using the column model was 3258.33 kg, very close to the estimated based on field observation (3112.82 kg).

Abstract While the use of energy efficient absorption heat pumps has been typically limited to the high capacity commercial and industrial applications, the use of a semi-open absorption heat pump for water heating has been demonstrated to be an energy efficient alternative for residential scale applications. A semi-open absorption system uses ambient water vapor as the refrigerant in the absorber where its heat of phase change is transferred to the process water, cooling the solution in the absorber. The solution is pumped to the desorber, where by adding heat, the water vapor is released from the solution and condensed in the condenser. The heat of phase change of water vapor is transferred to process water again in the condenser. This cycle when implemented with a membrane-based absorber in a plate and frame form of heat exchanger using ionic liquids can overcome the challenges related to the system architecture of conventional absorption heat pumps like the lower efficiency at small scale, crystallization/corrosion issues with the desiccants and the high cost of hermetically sealed components. The cycle COP for such a system was previously demonstrated by Chugh et al. for high humidity conditions. In this experimental study, design improvements were made that expand the system’s applicability to more practical and standardized test conditions. With these improvements, the performance of the system was evaluated. The results presented in this study demonstrate the improved system’s viability as a heat pump water heater conforming to standard water heater test conditions. Performance was measured at a cycle thermal COP of 1.2 with a hot water delivery water temperature of 56 °C and ambient air at 19 °C and 49% RH.

Abstract Although experimental studies have shown that Ga3Ni5 is a promising catalyst for carbon dioxide (CO2) hydrogenation to methanol (CH3OH), the roles that cluster size and support play in the reaction are not clear. This research was set to study the quantitative and qualitative impacts of the size and support of Ga-Ni clusters on CO2 hydrogenation to CH3OH at electronic and molecular levels by using density functional theory (DFT). Ga3Ni5, Ga6Ni10, Ga12Ni20, Ga15Ni25, and Ga24Ni40 nanoclusters, and γ-Al2O3- and SiO2- supported Ga6Ni10 were chosen as the study objects. Results show that adsorption energies of intermediates are highly related to intermediates’ characteristics and clusters’ active sites. Moreover, cluster size has no linear relation with the adsorption strengths of intermediates, while it has significant impact on the activation barrier of the rate-limiting step of hydrogenation process. Ga6Ni10 cluster has the lowest activation barrier of 1.04 eV due to the d-band center location and the exposed active sites of clusters. Compared with unsupported Ga6Ni10 clusters, Ga6Ni10/SiO2 and Ga6Ni10/γ-Al2O3 increase the adsorption energies of the intermediates and the activation barriers of the rate-limiting steps due to the lower electron transfer ability of Ga6Ni10 on SiO2 and γ-Al2O3 supports. Therefore, a support that can increase the electron transfer abilities of catalysts are preferable. The findings will be very beneficial for preparing new Ga-Ni catalysts for CO2 hydrogenation to CH3OH.

Abstract A portable commercial solid-oxide fuel cell that consisted of 56 stacked cells and used an indirect internal reforming strategy with a rhodium catalyst on an yttria-stabilized zirconia structure for its reformer and a nickel anode on an yttria-stabilized zirconia structure electrolyte was tested with propane fuel intentionally blended with 0 to 15 ppmv H2S. The voltages of cell pairs and stack were recorded during 7-h poison and recovery tests. Results indicated that with higher H2S concentrations, the rate of stack voltage decrease could vary from 181.4 mV/h at 3 ppmv to 432.0 mV/h at 15 ppmv. The voltage losses of individual cell pairs showed a consistent trend as well. Results from recovery tests indicated that a longer recovery time may be necessary at higher H2S concentration. Electrochemical impedance spectroscopy was employed to better understand the role of varying phenomena within the solid-oxide fuel cell. An equivalent circuit model was constructed to fit electrochemical impedance spectral data that was taken at the system level. Effects of individual components within the system (fuel cell, battery, and DC/DC converter), determined by using electrochemical impedance spectra, were then used to deduce the behaviour of the SOFC. A clear charge transfer resistance increase was observed due to H2S poisoning, consistent with the blocking of active sites on the catalyst in the anode layer. The effect was found to be completely reversible by a period of operation with sulfide-free fuel.

Geoenergy sources will continue to be mainstays of the world’s energy mix for many years to come, but the technological and business realities behind these energy sources are changing in two fundamental ways. First, with much of the world’s “easy oil” already consumed, the companies behind geoenergy will have to use increasingly sophisticated technologies to find and deliver these energy sources to the market. Second, the expectations placed upon the geoenergy sector by many of its stakeholders have grown considerably with regards to environmental stewardship, safety, and human welfare. In the face of these kinds of challenges, the industry will require an increasing degree of technological and commercial sophistication to continue to be a part of the world’s sustainable energy mix. Blockchain has emerged as a promising innovation that could potentially play an important role in delivering the kinds of technological and commercial capabilities that the geoenergy sector will need to achieve these ends. In spite of the myriad ways that blockchain could potentially improve the efficiency and sustainability of the geoenergy industry, however, the technology is still evolving, and a few barriers stand in the way of its widespread deployment. This paper puts forward case study evidence from the Intel Corporation and the Energistics Consortium showing what the geoenergy sector can learn about blockchain from other industries, and highlights that the absence of data standards and interoperability has contributed to blockchain’s failure to deliver significant value in the geoenergy domain thus far.

Abstract Within residences, normative messaging interventions have encouraged households to engage in various pro-environmental behaviors. In norm-based intervention campaigns, it is hypothesized that more personally relevant reference groups increase norm adherence, thus improving the effectiveness of normative messaging interventions. Advanced energy grid infrastructure, such as smart meters and cloud computing, enables the creation of highly personalized behavioral reference groups in a non-invasive manner by dynamically classifying households into highly similar user groups based on usage patterns. Unfortunately, it remains unclear how readily available data on household energy use and housing characteristics affect the classification performance of dynamic behavioral reference groups. Therefore, this research evaluates the classification performance of dynamic behavioral reference groups using readily available data. An energy-cyber-physical system for personalized normative messaging interventions is trained and tested using one-year of energy use data from 2248 households in Holland, Michigan. Dynamic behavioral reference group classification proved very accurate, 94.7–95.9% for weekly feedback and 89.9–93.1% for monthly feedback using only readily available data. In addition, using more historical energy use data contributes to enhancing classification accuracy. Lastly, high classification performance for each behavioral reference group is achieved at 97.6% of precision, recall and F1-score. With the proposed system, it is possible to dynamically assign highly personalized behavioral reference groups to households every billing cycle even if behavioral patterns are subject to change. Thus, interveners will be able to deploy personalized normative feedback messages on a large scale.