Marine hydrate reservoir has great resource potential, but its accumulation mode is not clear yet. At present, the study of hydrate accumulation mode is mainly carried out by in-situ exploration results and the analysis of hydrate formation conditions. In this study, methane hydrate is generated in the sediments of South China Sea on four modes, and the influence of the initial state and generation mode on the reservoir temperature and pressure change trend and the final temperature and pressure state is obtained, which provides guidance for the exploration of hydrate accumulation mode in South China Sea.
A building or a group of buildings may be considered as a set of thermal zones which exchange energy with the environment through the envelopes and systems: walls, thermal bridges, glazing, HVAC. A thermal model of a building (or group of buildings) may thus be represented by a graph where the vertices stand the capacitive nodes (thermal zones and wall meshes) and the edges carry the heat flows. Therefore, it is possible to convert a BIM representation of a building such as a gbXML file into a graph holding the physical laws of the heat flows and heat balances involved.
The aim of this paper is to introduce a novel methodology to generate building energy models (BEM) from BIM digital mock-ups. This new approach consists in creating a graph model using the Python NetworkX library from the available geometric and physical data extracted in the BIM representation. The graph model is used to generate a set of linear invariant systems for numerical simulation assuming linear or linearizable heat fluxes (such as radiative exchanges). In this contribution, the approach is applied to a test case building and validated by comparison with a reference model generated with an already tested tool chain.
The increase in refrigerated food demand, due to increase on urban population is involving the replacement of conventional diesel-powered transport refrigeration units (TRUs) by electrical-based auxiliary power units APUs, in an imperious. This paper presents a turnkey solution of a hydrogen-based APU for a refrigeration unit integrated in short haul trucks, for its use in the food industry.
The importance of renewable energy sources like solar energy in reducing carbon emissions and other greenhouse gases has contributed to an increase in grid integration. However, the intermittent nature of solar power causes reliability issues and a loss of energy balance in the system, which are barriers to solar energy penetration. This study proposes a unique three-step approach that identifies weather parameters with moderate to strong correlation to solar radiation and uses them to predict solar energy generation. The combination of an on-site weather station and a reliable local weather station produces relevant data that increases the accuracy of the forecasting model irrespective of the machine learning algorithm used. This data source combination is tested, along with two other scenarios, using the exponential Gaussian Process Regression machine learning algorithm in MATLAB. It was found to be the most effective algorithm with a Normalized Root Mean Square Error of 1.1922, and an R2 value of 0.66.
Hydrogen fuel cell vehicles (HFCVs) replacing internal combustion engine vehicles are a viable option to achieve net-zero carbon emission in transportation. Higher hydrogen storage pressure is necessary for increased recharge mileage, necessitating a hydrogen decompression mechanism. A unique pressure-lowering construction (Tesla-type orifice structure) is proposed in this study, in which Tesla-type channels are paralleled and incorporated into a standard orifice plate structure. A complete parametric analysis is used to optimize the Tesla-type orifice construction further. Compared to a standard orifice plate, at low inlet mass flow rates, the Tesla-type secondary orifice construction gives higher pressure drop performance. The presented study may provide a feasible technical structure for achieving high-efficiency hydrogen decompression in HFCVs.
Both effective utilization of renewable energy and multi-generation system are promising ways to reduce greenhouse gas emissions. This paper proposed a combined cooling, heating and power (CCHP) system, which is based on a basic system and consists of a transcritical CO2 cycle, an ejector refrigeration cycle, a domestic water heater and a thermoelectric generator. The parametric and comparative analyses are performed to show the system performance enhancement of the modification system. The multi-objective optimization is also conducted for the involved CCHP systems. Results show that compared to basic system, the novel system owns a higher exergy efficiency (30.75 VS 27.42%) and a lower total product unit cost (27.39 VS 32.28 $/GJ), confirming the obvious performance improvement.
The catalytic mechanism of Cu(111) surface on the pyrolysis of HFO-1234yf has been investigated by Density Functional Theory (DFT). Firstly, search for the most stable adsorption structure of HFO-1234yf and its pyrolysis products on the Cu(1 1 1) surface. Secondly, The most stable co-adsorption structure of the products of Path1-4 on Cu(1 1 1) surfaces was calculated. Finally, the transition state structure of Path1-4 were investigated. The results prove that the copper surface reduces the energy needed for the pyrolysis of HFO-1234yf.
Electric mobility can reduce energy consumption and polluting emissions and is one of the key elements of the current energy transition. Electric vehicles take over is hampered by different problems, above all the scarce diffusion of adequate recharging infrastructures. The objective of this paper is to design a smart system for the shared charging of electric vehicles. Such system minimizes the necessity of additional infrastructure by valorizing the electricity not used by a residential building. The effectiveness of such a system has been demonstrated in two realistic scenarios with a building consisting of 3 apartments and an elevator, a photovoltaic system, and up to 4 electric vehicles.
The upcoming transformation from internal combustion vehicles to electric vehicles in the private transport sector, together with the increasing demand for electricity, leads to challenges such as over-loading for the power grid. This study shows an economic analysis to what extent storage systems can be an alternative to conventional grid reinforcement. Current and predicted costs for storage systems are compared with the costs for cable replacement in the medium-voltage grid and correlations are derived. Accurate co-simulations of storage systems and the distribution grid allow these cost scenarios to be applied to use cases. The results show that the energy related costs for storage systems decrease about 38.5 % from 468 $/kWh to 288 $/kWh from 2020 to 2030. This leads to scenarios, mainly in urban distribution grids, where storage systems are an alternative to conventional grid reinforcement.
The combustion characteristics of a newly developed Clustered Porous Radiant Burner was investigated. Numerical simulations were performed at different equivalence ratios for a power input of 12.56 kW and the flame movement was analyzed by locating the maximum temperature points. Thermal nonequilibrium model was considered for the energy equations and the combustion was modelled by employing eddy-dissipation model. Surface combustion was reported for equivalence ratio 0.6, while the submerged combustion was obtained for equivalence ratios 0.7 to 0.85. Stable partially submerged combustion was obtained for equivalence ratio of 0.9. The burner was observed to be unstable when operated at an equivalence ratio of above 0.95. Numerically predicted result was in good agreement with the experimental data.