Coupling pinch analysis and rigorous process simulation for hydrogen networks with light hydrocarbon recovery

In refineries,some hydrogen-rich streams contain considerable light hydrocarbons that are important raw materials for the chemical industry.Integrating hydrogen networks with light hydrocarbon recovery can enhance the reuse of both hydrogen and light hydrocarbons.This work proposes an automated method for targeting hydrogen networks with light hydrocarbon recovery.A pinch-based algebraic method is improved to determine the minimum fresh hydrogen consumption and hydrogen sources fed into the light hydrocarbon recovery unit automatically.Rigorous process simulation is conducted to determine the mass and energy balances of the light hydrocarbon recovery process.The targeting procedures are developed through combination of the improved pinch method and rigorous process simulation.This hybrid method is realized by coupling the Matlab and Aspen HYSYS platforms.A refinery hydrogen network is analyzed to illustrate application of the proposed method.The integration of hydrogen network with light hydrocarbon recovery further reduces fresh hydrogen requirement by463.0 m^(3)·h^(-1) and recovers liquefied petroleum gas and gasoline of 1711.5 kg·h^(-1) and 643 kg·h^(-1),respectively.A payback period of 9.2 months indicates that investment in light hydrocarbon recovery is economically attractive.

Relationship between Colored Microstructure under Polarized Light and Shape Recovery Characteristics on the Thermomechanical Cycled CuAlNi Single Crystals

The paper studied the relationship between microstructure and shape recovery characteristics by using colored microstructure analysis under polarized light on the thermomechanical cycled CuAlNi single crystals. The two-way shape memory effect in quenched thin bar resulted from the preferential formation/extinction of martensite variant due to the internal quench stress, and the variant was formed at an angle of about 45 deg. with the tension direction ([001] of the βphase). Initial thermomechanical cycling under relatively low stress single variant stress-induced martensite was formed at an angle of 45 deg. with the tension and its morphology was a lath of parallel twins. More than one group of variants were formed after several training cycles and such variants also caused tilting of some thermally formed accommodated martensite. By overheating the trained sample containing stabilized multi-variants of stress-induced martensite, very coarse martensite structure with a strong asymmetry was produced, which caused the reverse two-way shape memory effect.

Automatic detection and removal of static shadows

In case of complex textures,existing static shadow detection and removal algorithms are prone to false detection of the pixels.To solve this problem,a static shadow detection and removal algorithm based on support vector machine(SVM)and region sub-block matching is proposed.Firstly,the original image is segmented into several superpixels,and these superpixels are clustered using mean-shift clustering algorithm in the superpixel sets.Secondly,these features such as color,texture,brightness,intensity and similarity of each area are extracted.These features are used as input of SVM to obtain shadow binary images through training in non-operational state.Thirdly,soft matting is used to smooth the boundary of shadow binary graph.Finally,after finding the best matching sub-block for shadow sub-block in the illumination region based on regional covariance feature and spatial distance,the shadow weighted average factor is introduced to partially correct the sub-block,and the light recovery operator is used to partially light the sub-block.The experimental results show the number of false detection of the pixels is reduced.In addition,it can remove shadows effectively for the image with rich textures and uneven shadows and make a natural transition at the boundary between shadow and light.

The key parameter of shale oil resource evaluation: Oil content

The United States has become the world's largest oil producer of shale oil. China has abundant shale oil resources, but its resource potential has not yet been exploited. The core of the evaluation is the selection of parameters and their reliability. By combining the parameters of the shale oil resource evaluation, we investigated the key parameters in the evaluation model and reviewed the research results. The adsorption and retention of heavy hydrocarbons, loss of light hydrocarbons, and original oil saturation are key in the evaluation of shale oil resources. The adsorption and retention of heavy hydrocarbons can be determined by the pyrolysis, FID curve, and hydrocarbon generation kinetics of shale before and after extraction. The loss of light hydrocarbons mainly occurs in coring(change in temperature and pressure),sample treatment, which can be evaluated using the GC spectrum, rock pyrolysis, crude oil volume coefficient, mass balance, component hydrocarbon generation kinetics, and other methods. The original oil saturation evaluation includes indirect, direct, logging, and simulation methods. The most reliable parameters can be obtained by using the sealed or pressure-maintained coring immediately after thawing(without crushing), and the recovery of light hydrocarbon loss is critical for the resource evaluation of medium to high mature shale. Therefore, the experimental determination of shale oil content and the study of the influencing factors of the parameters should be strengthened.

Fuzzy optimization design of multicomponent refinery hydrogen network

Hydrogen and light hydrocarbon components are essential resources of the refinery.The optimization of the refinery hydrogen system and recovery of the light hydrocarbon components contained in the gas streams are key strategies to reduce the operating costs for sustainable development.Many research efforts have been focused on the optimization of single impurity hydrogen network,and the flowrates of the hydrogen sources and sinks are assumed to be constant.However,their flowrates vary along with the quality of crude oil and refinery processing plans.A general superstructure of multicomponent refinery hydrogen network is proposed,which considers four components,namely H_(2),H_(2)S,CH_(4) and C_(2+),as well as the flowrate variations of hydrogen source and hydrogen sink.The mathematical model based on the superstructure is developed with objective functions,including the minimization of total annualized cost and the maximization of overall satisfaction of the hydrogen network.Moreover,the model considers the removal of hydrogen sulfide and the recovery of light hydrocarbon components(i.e.,C_(2+))in the optimization.To verify the applicability of the proposed mathematical model,a simplified industrial case study with four scenarios is solved.The optimization results show that the economic benefit can be maximized by considering both the direct reuse of gas streams from high-pressure separator(HP gas stream)and from low-pressure separator(LP gas stream)and the recovery of the light hydrocarbon streams.The fuzzy optimization method can be used to guide the optimal design of the refinery hydrogen system with multi-period variable flowrates.