Crude oil cracking in deep reservoirs:A review of the controlling factors and estimation methods

The natural cracking of crude oils in deep reservoirs has gained great interest due to continuously increasing depth of petroleum exploration and exploitation.Complex oil compositions and surroundings as well as complicated geological evolutions make oil cracking in nature much more complex than industrial pyrolysis.So far,numerous studies,focused on this topic,have made considerable progress although there still exist some drawbacks.However,a comprehensive review on crude oil cracking is yet to be conducted.This article systematically reviews the controlling factors of oil cracking from six aspects,namely,oil compositions,temperature and time,pressure,water,minerals and solid organic matter.We compare previous experimental and modelling results and present new field cases.In the following,we evaluate the prevailing estimation methods for the extent of oil cracking,and elucidate other factors that may interfere with the application of these estimation methods.This review will be helpful for further investigations of crude oil cracking and provides a guide for estimation of the cracking extent of crude oils.

Sedimentology and Paleoenvironmental Characteristics of Fine-grained Sediments in Coal-bearing Strata in the Eastern Ordos Basin:A Case Study of the Exploratory Well in the Zizhou Area

The continuously collected cores from the Permo-Carboniferous coal-bearing strata of the eastern Ordos Basin are essential for studying the hydrocarbon potential in this region.This study adopted sedimentological and geochemical methods to analyze the sedimentary environment,material composition,and geochemical characteristics of the coal-bearing strata.The differences in depositional and paleoclimatic conditions were compared;and the factors influencing the organic matter content of fine-grained sediments were explored.The depositional environment of the Benxi and Jinci formations was lagoon to tidal flat with weakly reduced waters with low salinity and dry-hot paleoclimatic conditions;while that of the Taiyuan Formation was a carbonate platform and shallow water delta front,where the water was highly reductive.The xerothermic climate alternated with the warm and humid climate.The period of maximum transgression in the Permo-Carboniferous has the highest water salinity.The Shanxi Formation was deposited in a shallow water delta front with a brackish and fresh water environment and alternative weak reductiveness.And the paleoclimate condition is dry-hot.The TOC content in fine-grained samples was averaging 1.52%.The main controlling mechanism of organic matter in this area was the input conditions according to the analysis on input and preservation of organic matter.

Finite Element Numerical Simulation and PIV Measurement of Flow Field inside Metering-in Spool Valve

The finite element method （FEM） and particle image velocimetry （PIV） technique are utilized to get the flow field along the inlet passage, the chamber, the metering port and the outlet passage of spool valve at three different valve openings. For FEM numerical simulation, the stream function ψ-vorticity ω forms of continuity and Navier-Stokes equations are employed and FEM is applied to discrete the equations. Homemade simulation codes are executed to compute the values of stream function and vorticity at each node in the flow domain, then according to the correlation between stream function and velocity components, the velocity vectors of the whole field are calculated. For PIV experiment, pulse Nd： YAG laser is exploited to generate laser beam, cylindrical and spherical lenses are combined each other to produce 1.0 mm thickness laser sheet to illuminate the object plane, Polystyrene spherical particle with diameter of 30-50 μm is seeded in the fluid as a tracing particles, Kodak ES 1.0 CCD camera is employed to capture the images of interested, the images are processed with fast Fourier transform （FFT） cross-correlation algorithm and the processing results is displayed. Both results of numerical simulation and PIV experimental show that there are three main areas in the spool valve where vortex is formed. Numerical results also indicate that the valve opening have some effects on the flow structure of the valve. The investigation is helpful for qualitatively analyzing the energy loss, noise generating, steady state flow forces and even designing the geometry structure and flow passage.

Self-sustained catalytic combustion of CO enhanced by micro fluidized bed: stability operation, fluidization state and CFD simulation

A micro fluidized bed reactor was used to study the self-sustaining catalytic combustion of carbon monoxide(CO).The Cu_(1−x)Ce_(x)O_(y) catalyst,as well as the pure CuO and CeO_(2),are used to investigate the contributing mechanism of different active sites including dispersed CuO and Cu–Ce solid solutions.The ignition temperature(Ti)of CO over these catalysts at a flow rate of 2000 mL/min followed the order:74℃(Cu_(0.5)Ce_(0.5)O_(y))<75℃(Cu_(0.25)Ce_(0.75)O_(y))<84℃(Cu_(0.75)Ce_(0.25)O_(y))<105℃(CuO)<500℃(CeO_(2)).Furthermore,the lean combustion limits(equivalence ratioϕ)over these catalysts under the flow rates of 750–3000 mL/min(through fixed,bubbling,and fluidized bed)were also measured,which are Cu_(0.5)Ce_(0.5)O_(y)<Cu_(0.25)Ce_(0.75)Oy<Cu_(0.75)Ce_(0.25)O_(y)<CuO<CeO_(2).The fluidized bed was simulated using the Eulerian two-fluid model(TFM)coupled with a diffusion/kinetic-limited reaction model to evaluate the influence of operation conditions on the self-sustained combustion of CO.The predicted maximum temperature agreed with the experimental measurements,demonstrating the validity of the kinetic model and simulation parameters.The results of catalytic combustion with increasing CO concentrations suggest that the catalytic combustion reaction could co-exist with the flamed combustion.When a high concentration of CO is used,a blue-purple flame caused by CO combustion appears in the upper part of the fluidized bed,indicating that the range of CO-containing exhaust gas purification could be expanded to a larger range using the fluidized-bed catalytic combustion technique.

CONDENSATION HEAT TRANSFER OF R-134A IN HORIZONTAL STRAIGHT AND HELICALLY COILED TUBE-IN-TUBE HEAT EXCHANGERS

This article presents an experimental investigation on condensation heat transfer of R-134a in horizontal straight and helically coiled tube-in-tube heat exchangers. The experiments were carried out at three saturation temperatures（35 ℃ , 40 ℃ and 45 ℃ ） with the refrigerant mass flux varying from 100 kg/m2 s to 400 kg/m2 s and the vapor quality ranging from 0.1 to 0.8. The effects of vapor quality and mass flux of R-134a on the condensation heat transfer coefficient were investigated. The results indicate that the condensation heat transfer coefficients of the helical section are 4%-13.8% higher than that of the straight section. The experimental results were compared with the data available in literature for helical and straight pipes.

Hierarchical predictive energy management strategy for fuel cell buses entering bus stops scenario

This paper aims to answer how to use traffic information to design energy management strategies for fuel cell buses in a networked environment.For the buses entering the bus stops scenario,this paper proposes a hierarchical energy management strategy for fuel cell buses,which considers the traffic information near the bus stops.In the upper-level trajectory planning stage,the optimal SOC trajectory under various historical traffic conditions is solved through dynamic planning.The traffic information and the best SOC trajectory are mapped through BiLSTM,which can achieve fast,real-time long-term SOC reference.In the lower-level real-time predictive energy management strategy,the optimal SOC is used as the state reference to guide the predictive energy management of fuel cell buses when entering the bus stops.Simulation results show that compared with the strategy without SOC trajectory reference,the life cost of the proposed strategy is reduced by 13.8%,and the total cost is reduced by 3.61%.The SOC of the proposed strategy is closer to the DP optimal solution.

Rollover prevention control for a four in-wheel motors drive electric vehicle on an uneven road

When a four in-wheel motors drive electric vehicle with a specific wheels mass is running on an uneven road and transient steering occurs in the meantime, the joint action of the large unsprung dynamic load and the centrifugal force may cause the vehicle to rollover. To avoid the above accident, a rollover prevention control method based on active distribution of the in-wheel motors driving torques is investigated. First, the rollover evolution process of the four in-wheel motors drive electric vehicle under the described operating condition is analyzed. Next, a multiple degrees of freedom vehicle dynamics model including an uneven road tyre model is established, and the rollover warning threshold is determined according to the load transfer ratio. Then, the hypothesis of the effects of unsprung mass on the vehicle roll stability on a plat road and on an uneven road is verified respectively. Finally, a rollover prevention controller is designed based on the distribution of the four wheels driving torques with sliding mode control,and the control effect is verified by simulations. The conclusion shows that, once the wheels mass does not match road conditions,the large unsprung mass may play a detrimental role on the vehicle roll stability on an uneven road, which is different from the beneficial role of large unsprung mass on the vehicle roll stability on a plat road. With the aforementioned rollover prevention controller, the vehicle rollover, which is caused by the coupling effect between large unsprung dynamic load and suspension potential energy on an uneven road, can be avoided effectively.

Adaptive Fault-Tolerant Control During the Mode Switching for Electric Vehicle Dual-Mode Coupling Drive System

As a new drive system for electric vehicles,the dual-mode coupling drive system can automatically switch between centralized and distributed drive modes and realize two-speed gear shifting.Because the actuator’s displacement signal affects the mode-switching control,when failure occurs at the angle-displacement sensor,the mode-shifting quality is likely to drop greatly,even possibly leading to shift failure.To address the angle-displacement sensor failure and improve the reliability of the shift control,an adaptive fault-tolerant control method is proposed and verified.First,the effect of the output signal of the angle-displacement sensor in the mode-switching control process is analyzed.Then,an adaptive mode-switching fault-tolerant control method is designed based on the Kalman filter and fuzzy theory.Finally,the feasibility of the control effect is verified through simulations and vehicle experiments.The results indicate that the proposed method can effectively eliminate the signal noise of the angle-displacement sensor and successfully switch the modes when the sensor fails.It provides a reference for ensuring the working quality of similar electric drive systems under sensor failures.

Density‑Based Road Segmentation Algorithm for Point Cloud Collected by Roadside LiDAR

This paper proposes a novel density-based real-time segmentation algorithm,to extract ground point cloud in real time from point cloud data collected by roadside LiDAR.The algorithm solves the problems such as the large amount of original point cloud data collected by LiDAR,which leads to heavy computational burden in ground point search.First,point cloud data is filtered by straight-through filtering method and rasterized to improve the real-time performance of the algorithm.Then,the density of the point cloud in horizontal plane is calculated,and the threshold of the density is selected to extract the low-density regional point cloud according to the density statistical histogram and 95%loci.Finally,the low-density regional point cloud is used as the initial ground seeds for iterative optimization of ground parameters,and the ground point cloud is extracted by the fitted ground model to realize road point cloud extraction.The experimental results on 1055 frames of continuous data collected on real scenes show that the average time consumption of the proposed method is 0.11 s,and the average segmentation precision is 92.48%.This shows that the density-based road segmentation algorithm can reduce the time of point cloud traversal in the process of ground parameter fitting and improve the real-time performance of the algorithm while maintaining the accuracy of ground extraction.