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AbstractMembrane Technology and Research, Inc. has proposed a hybrid system combining amine scrubbing with membrane technology to reduce energy cost. Previous studies of CO2 absorption mainly focused on coal-fired flue gas with 12% CO2. However, in the hybrid process, the CO2 in the flue gas can be enriched to 20%. Natural gas turbines will have flue gas with as little as 3% CO2。 Based on the arrangement, the hybrid amine/membrane system provides a gas to the system that has double the CO2 concentration of normal flue gas, reduces the volume of gas sent to the capture unit, or reduces the removal requirements for the capture unit.The objective of this work is to minimize the total energy use of stripping concentrated piperazine (PZ) at rich loading when treating flue gas from 3 to 20% inlet CO2. The base-case stripping configuration is the advanced flash stripper with warm rich bypass and cold rich exchanger bypass. . This configuration includes two split cross-exchangers in series, a convective steam heater, a smaller stripper column, a low residence time flash tank, and stripping at high temperature to produce CO2 at 5 to 17bar. Rich loading in 5 and 8m PZ was varied from 0.37 to 0.43mol CO2/mol N. For each rich loading, lean loading was optimized to minimize the total equivalent work. The “Independence” model for PZ in Aspen Plus® was used to simulate the stripping performance.Because 5m PZ has a lower viscosity than 8m PZ, it can achieve a reduced approach temperature in the cross exchanger. The total energy performance for 5m PZ is practically the same as 8m PZ, even though the capacity of 5m PZ is lower. Significantly more energy is required to regenerate solvents with lower rich loading. As CO2 rich loading increases, the equivalent work requirement decreases for the same loading difference between rich and lean.Stripping data for 24 cases, including heat duty, equivalent work, CO2 output pressure, and optimal cold and warm rich bypass were used to build a correlation with CO2 rich and lean loading. The Second Law efficiency based on the ratio of stripping minimum work and total ideal work was introduced to make the most of stripping work. The Second Law efficiency has a maximum value at a specific CO2 loading.

Abstract This study sought to quantify and characterize cassava waste as fuel. The wastes from three cultivars were collected to study and were divided into three distinct parts of the cassava plant: seed stem, thick stalks, and thin stalks. Physical and chemical analyzes were carried out to determine the elemental composition of the waste: volatile matter; fixed carbon; ash; moisture; lignin; cellulose; hemicellulose; ash composition and higher heating value were determined. We conducted a thermogravimetric analysis in oxidizing and inert atmospheres to study the behavior of the waste as fuel. The root productivity obtained ranged from 7.7 to 13.0 t ha−1 yr−1 on a dry basis (db), and the ratio between waste and roots varied from 0.36 to 0.91. The physical and chemical properties of cassava waste are analogous to those of woody biomass regarding the elemental composition, the higher heating value, and thermogravimetric analysis. Ash content varied from 2.5% to 3.5%, reaching around 6.0% in samples unwashed. Approximately 60% of the ashes are alkali oxides, especially P2O5, K2O, and CaO, which have low melting points. The alkali index calculated suggests that there is a strong tendency that the combustion process leads to ash fouling and the formation of ash deposits.

Flexible butyl interconnection segments are synthetically incorporated into an electronically conductive poly(pyrene methacrylate) homopolymer and its copolymer. The insertion of butyl segment makes the pyrene polymer more flexible, and can better accommodate deformation. This new class of flexible and conductive polymers can be used as a polymer binder and adhesive to facilitate the electrochemical performance of a silicon/graphene composite anode material for lithium ion battery application. They act like a “spring” to maintain the electrode mechanical and electrical integrity. High mass loading and high areal capacity, which are critical design requirements of high energy batteries, have been achieved in the electrodes composed of the novel binders and silicon/graphene composite material. A remarkable area capacity of over 5 mAh/cm2 and volumetric capacity of over 1700 Ah/L have been reached at a high current rate of 333 mA/g.

The rapid development of advanced metering infrastructure provides a new data source—building electrical load profiles with high temporal resolution. Electric load profile characterization can generate useful information to enhance building energy modeling and provide metrics to represent patterns and variability of load profiles. Such characterizations can be used to identify changes to building electricity demand due to operations or faulty equipment and controls. In this study, we proposed a two-path approach to analyze high temporal resolution building electrical load profiles: (1) time-domain analysis and (2) frequency-domain analysis. The commonly adopted time-domain analysis can extract and quantify the distribution of key parameters characterizing load shape such as peak-base load ratio and morning rise time, while a frequency-domain analysis can identify major periodic fluctuations and quantify load variability. We implemented and evaluated both paths using whole-year 15-minute interval smart meter data of 188 commercial office building in Northern California. The results from these two paths are consistent with each other and complementary to represent full dynamics of load profiles. The time- and frequency-domain analyses can be used to enhance building energy modeling by: (1) providing more realistic assumptions about building operation schedules, and (2) validating the simulated electric load profiles using the developed variability metrics against the real building load data.

ASHRAE Standard 62-1989 (Standard 62-89) Ventilation for Acceptable Indoor Air Quality'' is the new heating, ventilating, and air-conditioning (HVAC) industry consensus for ventilation air in commercial buildings. Bonneville Power Administration (Bonneville) references ASHRAE Standard 62-81 (the predecessor to Standard 62-89) in their current environmental documents for required ventilation rates. Through its use, it had become evident to Bonneville that Standard 62-81 needed interpretation. Now that the revised Standard (Standard 62-89) is available, its usefulness needs to be evaluated. Based on current information and public comment, the American Society of Heating, Refrigeration, and Air-Conditioning Engineers (ASHRAE) revised Standard 62-1981 to Standard 62-89. Bonneville's study estimated the energy and cost implications of ASHRAE Standard 62-89 using simulations based on DOE-2.1D, a computer simulation program which estimates building use hourly as a function of building characteristics and climatic location. Ten types of prototypical commercial buildings used by Bonneville for load forecasting purposes were examined: Large and Small Office, Large and Small Retail, Restaurant, Warehouse, Hospital, Hotel, School, and Grocery. These building characterizations are based on survey and energy metering data and represent average or typical construction and operation practices and mechanical system types. Prototypical building ventilation rates were varied in five steps to estimate the impacts of outside air on building energy use. 11 refs., 14 tabs.

Abstract. Reliable quantification of the sources and sinks of greenhouse gases, together with trends and uncertainties, is essential to monitoring the progress in mitigating anthropogenic emissions under the Paris Agreement. This study provides a consolidated synthesis of CH4 and N2O emissions with consistently derived state-of-the-art bottom-up (BU) and top-down (TD) data sources for the European Union and UK (EU27+UK). We integrate recent emission inventory data, ecosystem process-based model results, and inverse modelling estimates over the period 1990–2018. BU and TD products are compared with European National GHG Inventories (NGHGI) reported to the UN climate convention secretariat UNFCCC in 2019. For uncertainties, we used for NGHGI the standard deviation obtained by varying parameters of inventory calculations, reported by the Member States following the IPCC guidelines recommendations. For atmospheric inversion models (TD) or other inventory datasets (BU), we defined uncertainties from the spread between different model estimates or model specific uncertainties when reported. In comparing NGHGI with other approaches, a key source of bias is the activities included, e.g. anthropogenic versus anthropogenic plus natural fluxes. In inversions, the separation between anthropogenic and natural emissions is sensitive to the geospatial prior distribution of emissions. Over the 2011–2015 period, which is the common denominator of data availability between all sources, the anthropogenic BU approaches are directly comparable, reporting mean emissions of 20.8 Tg CH4 yr−1 (EDGAR v5.0) and 19.0 Tg CH4 yr−1 (GAINS), consistent with the NGHGI estimates of 18.9 ± 1.7 Tg CH4 yr−1. TD total inversions estimates give higher emission estimates, as they also include natural emissions. Over the same period regional TD inversions with higher resolution atmospheric transport models give a mean emission of 28.8 Tg CH4 yr−1. Coarser resolution global TD inversions are consistent with regional TD inversions, for global inversions with GOSAT satellite data (23.3 Tg CH4yr−1) and surface network (24.4 Tg CH4 yr−1). The magnitude of natural peatland emissions from the JSBACH-HIMMELI model, natural rivers and lakes emissions and geological sources together account for the gap between NGHGI and inversions and account for 5.2 Tg CH4 yr−1. For N2O emissions, over the 2011–2015 period, both BU approaches (EDGAR v5.0 and GAINS) give a mean value of anthropogenic emissions of 0.8 and 0.9 Tg N2O yr−1 respectively, agreeing with the NGHGI data (0.9 ± 0.6 Tg N2O yr−1). Over the same period, the average of the three total TD global and regional inversions was 1.3 ± 0.4 and 1.3 ± 0.1 Tg N2O yr−1 respectively, compared to 0.9 Tg N2O yr−1 from the BU data. The TU and BU comparison method defined in this study can be operationalized for future yearly updates for the calculation of CH4 and N2O budgets both at EU+UK scale and at national scale. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.4288969 (Petrescu et al., 2020).

The classical approach to load modeling is to divide the load by customer class and then identify and model the load components corresponding to each customer class. This work explores an alternative way to break down the load using readily available data. Namely, using historical usage data and historical weather data the load can be first divided into temperature-dependent and temperature-independent portions. A simple thermal model of the structure(s) served by the electrical circuit forms the theoretical and mathematical basis of this separation. During summer peaking conditions, the temperature-dependent load is generally composed of air conditioners, which must be modeled properly in order to analyze delayed voltage recovery or other dynamic phenomenon. Once the temperature-dependent fraction of the load has been characterized, the size of compressor, fan, and pump motors can be inferred by the customer class.

The steady-state phase distribution and the structural parameters have been taken as the input for the nuclear physics calculation in the ADS windowless spallation target. The distribution of the extreme large power density of the heat load is imported back as the source term in the energy equation. Then temperature distribution is obtained based on the flow process and heat transfer. The preliminary results show that the temperature distribution reaches the steady-state and its shape is like the broken wings of the butterfly. This is very important for the further design and optimization of the ADS windowless spallation target. So the two-way coupling simulation of the heat transfer process is successfully performed between the computational fluid dynamics and the nuclear physics simulation.