Flow Test Data Research Articles

Aerodynamic design of two-stage centrifugal compressor for vehicle hydrogen fuel cell

Abstract The on-board hydrogen fuel cell is a power generation device that converts the chemical energy of hydrogen and oxygen directly into electrical energy. The centrifugal compressor mainly provides oxygen for the cathode of the fuel cell system. With the rapid development of the hydrogen fuel cell industry, the key components of the air compressor field are also developing rapidly. In the technical route, most companies launched two-stage compression centrifugal air compressors in response to the increasing power of the product development trend. The newly developed hydrogen fuel cell system power has reached above 120kW to meet the needs of heavy trucks and other applications. Both the flow rate and pressure ratio of the air compressor are required to increase accordingly. Based on the reduction of parasitic power, the optimal efficiency at the working point of the two-stage centrifugal air compressor is taken as the design goal, from one-dimensional aerodynamic calculation to two-dimensional flow channel design. Finally, the feasibility and accuracy of the aerodynamic design are verified based on key parameters such as pressure ratio, flow rate, and efficiency of the final stage through CFD flow field simulation and test data comparison. The results show that the flow rate is consistent with the calculated flow field, and the maximum error of pressure ratio and efficiency is less than 2%, which meets the target requirements. The research results can provide a research and development basis for designing high-performance centrifugal air compressors for fuel cell vehicles.

Experiment and simulation study on energy flow characteristics of a battery electric vehicle throughout the entire driving range in low-temperature conditions

To comprehensively investigate the energy distribution and performance of a battery electric vehicle (BEV), an integrated simulation model based on energy flow test data was developed and validated, and the energy flow characteristics of the BEV throughout the entire driving range in low-temperature conditions were studied. The results show that the battery heat loss and motor energy loss first increase and then decrease with an increment in cycle number, while the transmission loss first decreases and then remains constant. The energy recovery efficiency demonstrates an incremental trend with the number of cycles post-battery charging, while the energy utilization efficiency experiences a decline due to escalating energy losses within the power distribution unit (PDU). The energy flow characteristics of the BEV exhibit a pronounced connection with the speed properties inherent in the driving cycle. The battery charge energy is maximal under Urban Dynamometer Driving Schedule (UDDS), whereas the electricity consumption per 100 km is minimized under China light-duty vehicle test cycle-passenger (CLTC-P). Conversely, the energy utilization and recovery efficiency are the highest under Worldwide Light-duty Test Cycle (WLTC). These findings provide directional insights, theoretical support and data basis for rational performance evaluation and optimal energy distribution of BEVs.

Many-objective optimization of BEV design parameters based on gradient boosting decision tree models and the NSGA-III algorithm considering the ambient temperature

In this study, extensive efforts have been devoted to optimizing the energy distribution and performance of a battery electric vehicle (BEV). An integrated simulation model based on energy flow test data is built and validated, and a parallel framework to implement automatic batch simulations is developed. On this basis, eXtreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM) and Categorical Boosting (CatBoost) models of the BEV are established and compared, and many-objective optimization is carried out based on the Non-dominated Sorting Genetic Algorithm-III (NSGA-III) algorithm. The results indicate that the developed parallel framework can efficiently perform automatic batch computations of the integrated simulation model for the BEV, and the CatBoost model demonstrates superior prediction performance on both the train and test sets. A uniformly distributed non-dominated set approximating the Pareto Front (PF) is obtained by the many-objective optimization, with the fourth non-dominated solution exhibiting a favorable optimization effect. The electricity consumption per 100 km, half-axis effective work, electricity recovered by battery, energy utilization and recovery efficiency are improved by 9.4 %, 12.2 %, 6.4 %, 96.3 % and 16.0 %, respectively. These findings can provide the theoretical basis, directional guidance and data support for the accurate modeling, batch simulation and many-objective optimization of BEVs.

Effect of inlet gas and liquid velocity profiles on one-group interfacial area transport equation in a vertical large rectangular channel

Bubbly flows appear in many heat and mass transfer equipment. The interfacial area concentration is a critical parameter in determining the performance of the heat and mass transfer systems. The one-dimensional one-group interfacial area transport equation (IATE) was developed based on area-averaged bubbly flow data collected under uniform inlet flow boundary conditions. The applicability of the IATE to the flow systems with non-uniform inlet flow boundary conditions was not comprehensively examined. This study investigated the effect of inlet liquid and gas velocity profiles on measured interfacial area concentration changes along the flow direction. The data used in this study were collected for vertical upward air-water two-phase flow in a rectangular channel with a gap length of 10 mm and width of 200 mm. The test conditions were the superficial gas velocity ranging from 0.0870 to 0.288 m/s and the superficial liquid velocity ranging from 0.515 to 2.53 m/s. The interfacial area concentrations with uniform and non-uniform inlet flow boundary conditions measured in a large vertical rectangular channel were compared under the same area-averaged flow rate conditions. Then, the predictive capability of the IATE to the bubbly flow test data with uniform and non-uniform inlet flow boundary conditions was assessed. Some non-uniform inlet flow boundary conditions, including channel-center peaking of liquid flow (CPF), channel-center peaking of gas flow (CPG), single-side-wall peaking of liquid flow (SPF), and single-side-wall peaking of gas flow (SPG), significantly affected the interfacial area concentration changes along the axial location at relatively high superficial gas or liquid velocity conditions. The IATE's predictive capability deteriorated for several non-uniform inlet flow boundary conditions, including double-side-wall peaking of gas flow (DPG) and single-side-wall peaking of liquid flow (SPF), specifically at relatively high superficial liquid velocity conditions. The maximum percentage error of the interfacial area concentration prediction by the IATE for these non-uniform inlet flow boundary conditions reached 75%.

Flow calibration method for gas-liquid two-phase flow of Coriolis flowmeter based on LSTM

Measuring with Coriolis flowmeter under the condition of gas-liquid two-phase flow, the vibration signal frequency, phase and amplitude of the measuring pipe fluctuate randomly. The traditional phase difference extraction algorithm is difficult to ensure the measurement accuracy of mass flow. In order to improve the extraction accuracy of mass flow, this paper presents a dynamic error correction method of mass flow based on LSTM (Long Short-Term Memory). The water flow test platform and data acquisition system are built, and the mass flow corrected by this method is compared with the mass flow corrected by ARMA (Autoregressive moving average) model and the mass flow obtained by flow meter. The experimental results show that the mean error of mass flow corrected by this method is 0.0357, and the variance is 0.0453, which is far less than the static error correction of 0.0988 and 0.1068, and far less than the mass flow meter of 0.3816 and 0.4045.

Fish habitat restoration on the basis of water morphology simulation.

The hydrodynamic conditions of rivers affect fish habitats by influencing parameters such as river bottom topography. Ecological restoration projects change the water morphological characteristics of rivers. Here, water flow characteristics of the upper Yangtze River before and after the construction of a restoration project were analyzed using the computational fluid dynamics simulation method. The longitudinal diversion dam could divide the river into two flow velocity zones, and the outer flow is similar to the original river with a flow velocity of 0.75 m/s. However, flow velocity on the inner side of the river was about 0.25 m/s, forming a larger buffer area. The eddy became more diversified and stable, with a high eddy viscosity coefficient and less fluctuations, at 9 Pa·s; this was conducive to fish aggregation and spawning. At different depths, large gradient differences were observed between the inner and outer sides of the longitudinal diversion dam, and the turbulent current and upward flow of the inner side were obvious; this was more favorable to the aggregation of different fish species. The longitudinal dam body was under a pressure of about 200.2 Pa at the same flow rate; this was significantly lower than the pressure on the transverse dam body. The field flow test and fish survey data showed that the error rate of the simulation using the RNG turbulent model was less than 10% compared with actual mapping. After the restoration of fish habitats by the longitudinal diversion dam, the number of fish species in the area increased from 40 to 49; The density of fish in the water increased from 71.40 fish per 1,000 m2 before the project to 315.70 fish per 1,000 m2 after the project. These results can provide a reference for the rapid assessment of water morphology and fish habitat restoration in the future.

E&P Notes (August 2022)

E&P Notes (August 2022)

Fuzzy Logic As A Tool For Estimating Production Potential Of A Sand Layer

In production management, a prior knowledge over production potential of a candidate sand layer (geological complexity in Indonesia has led to existence of stratified reservoirs with a set of layers) to be opened is always desirable. The common practice performed during drilling and completion activities of a production well is through the use of well testing and fluid sampling. From the test, fluid dynamic data such as total liquid rate, water cut, and gas cut are produced. A similar set of data is also required for more mature fields for the purpose of monitoring through the running of routine production and/or swab tests.Although the tests, especially flow tests during drilling and completion, are always regarded as the only source of proof about productive layer(s) production potential, an alternative means that can be used to provide estimates is always desired. The main reason is that flow tests are costly so that only layer(s) considered as the most potential are to be assigned for testing. Layer(s) that are considered less potential are left untested, eventhough in some cases they are also set on production during the well's production phase.The idea of establishing a method that can provide illustration over production potentials of all layer(s) always exists. Certainly, there are approaches to serve the purpose such as productivity index (PI) analogy and petrophysical through fractional flow measurement in a core laboratory. However, those approaches are often considered inadequate in accommodating various factors that may influence production potential.To materialize the idea stated above, the pattern recognition approach was taken. This approach was taken in order to model the relationships between various fac- tors in wellbore and production potential without being trapped by the certain complexity that occurs in any mathematical expressions trying to explain the relationships. For the purpose, fuzzy logie (a branch in ArtificialIntelligence) has been used. The choice is actually based on its ability to accommodate both numeric and non-numeric data. Some non-numeric data such as lithology and pore system also have some degrees of influence on production potential. With a tool that enables us to have production potential estimates of reservoir layers, from which layers with the most promising potential are taken to undergo flow tests. Furthermore, as flow test data has been acquired and used as feedback and calibration by the fuzzy model, production potential of layer(s) with less promising or ambiguous prospect can also be predicted.

Injection molding and shear‐induced stress simulation of poly (styrene‐ethylene‐butylene‐styrene) and polypropylene blends

AbstractIn this article, the structure and rheological properties of poly (styrene‐ethylene‐butylene‐styrene) (SEBS) triblock copolymer blends are analyzed. The influence of polypropylene content on the three SEBS blends was discussed, the viscoelastic response and phase structure evolution during injection molding were studied. According to the capillary flow test data, the least square method is used to fit the viscosity parameters of the cross‐WLF model. The filling length of the spline was tested by adjusting the injection molding process parameters, and its accuracy was verified by comparing the filling simulation with the experimental results. Numerical simulation is used to predict the shear rate distribution of injection‐molded samples, and the shear sensitivity and residual stress of SEBS blends with different phase structures are analyzed. Based on the phase structure analysis and rheological properties, this article predicts the filling properties of triblock copolymer composites, which can be used to construct the flow‐induced structure–property relationship of complex polymer blends.

Fast Equivalent Micro-Scale Pipe Network Representation of Rock Fractures Obtained by Computed Tomography for Fluid Flow Simulations

Fractures in rocks often provide preferential fluid migration pathways and their geometrical properties are the main factors influencing the permeability of the rock mass. By taking into account the complex geometries of rock fractures, including tortuous features, highly variable fracture apertures, rough fracture wall surfaces and complex fracture intersections, a highly effective approach is proposed in this work to investigate the behaviour of fluid flows in laboratory-scale fractured rocks. The computed tomography (CT) scanning was used to capture the micro-structures of non-planar fractures in a sandstone specimen. An image processing method was then developed to extract the three-dimensional fracture network. The fractures and fracture network were represented using an equivalent pipe network model, taking into consideration the complex geometries mentioned above. The nonlinear flow is incorporated into the model through the consideration of a friction factor in the pipe flow method (PFM). The absolute difference of the derived permeability between PFM and finite volume method (FVM) is 3.45%, but the FVM needs 15 times more CPU computation time. Therefore, the proposed approach is better than FVM in terms of computational efficiency. In addition, the use of the friction factor was demonstrated to be effective and efficient to model nonlinear flow within the fracture network, where the flow nonlinearity is caused by high flow velocity and the formation of eddies in certain parts of the fracture network, leading to a decrease in the overall apparent permeability and an increase in the flow tortuosity. The proposed method was further validated against flow test data covering a wide range of linear and nonlinear flow regimes.

Adaptive neuro-fuzzy algorithm applied to predict and control multi-phase flow rates through wellhead chokes

A Takagi-Sugeno adaptive neuro-fuzzy inference system (TSFIS) model is developed and applied to a dataset of wellhead flow-test data for the Resalat oil field located offshore southern Iran, the objective is to assist in the prediction and control of multi-phase flow rates of oil and gas through the wellhead chokes. For this purpose, 182 test data points (Appendix 1) related to the Resalat field are evaluated. In order to predict production flow rate (QL) expressed as stock-tank barrels per day (STB/D), this dataset includes four selected input variables: upstream pressure (Pwh); wellhead choke sizes (D64); gas to liquid ratio (GLR); and, base solids and water including some water-soluble oil emulsion (BS&W). The test data points evaluated include a wide range of oil flow rate conditions and values for the four input variables recorded. The TSFIS algorithm applied involves five data processing steps: a) pre-processing, b) fuzzification, c) rules base and adaptive neuro-fuzzy inference engine, d) defuzzification, and e) post-processing of the fuzzy model. The developed TSFIS model for the Resalat oil field database predicted oil flow rate to a high degree of accuracy (root mean square error = 247 STB/D, correlation coefficient = 0.9987), which improves substantially on the commonly used empirical algorithms used for such predictions. TSFIS can potentially be applied in wellhead choke fuzzy controllers to stabilize flow in specific wells based on real-time input data records.

Impact of facies and diagenetic variability on permeability and fluid flow in an oolitic grainstone—Pleistocene Miami Oolite

AbstractThe Miami Oolite of South Florida is representative of a grainstone‐rich carbonate unit that has been surficially karsted, and therefore may be considered as an analogue for subsurface reservoirs/aquifers with ‘high’ permeability extremes. The deposit can potentially serve to improve a conceptual understanding of heterogeneity as imparted by shallow‐marine facies changes and early meteoric diagenetic modification. Reviewed here are recent studies of the Miami Oolite with the intent to emphasize those key aspects of the facies and early diagenesis that most impact permeability and fluid flow. The Miami Oolite displays the preserved morphology of a fossilized ooid sandbody, even though it has been subaerially exposed in a tropical climate since its deposition approximately 120 kyr bp during the last interglacial highstand. The depositional motif is one of a dip‐oriented, tidal bar belt of shoals and shallow channels fronted by a strike‐oriented barrier bar. The barrier bar comprises cross‐stratified grainstones and locally burrowed grain/packstones, while the tidal shoals and channels are more commonly burrowed pack/grainstones. Surficial karst features (dolines and stratiform caves) have been added during the ca 120 kyr of subaerial exposure, but of more significance is the associated solution‐enhancement of the widespread burrowed facies. Since the Miami Oolite is the uppermost portion of the Biscayne Aquifer, there is also an understanding of fluid flow through the deposit that sheds valuable insight on the larger scale, shallow subsurface plumbing. The pore system comprises matrix pores (interparticle and separate vugs) and touching‐vug macropores that are commonly associated with burrowed [Ophiomorpha] intervals. Ground‐penetrating radar, well and flow test data indicate that matrix porosity provides most of the groundwater storage, whereas the touching vug macropores account for the majority of flow. The dolines and shallow caves seem to be sufficiently spaced as to generally not be in direct connection, with the result that they are less important in terms of regional flow than the prevailing pore system.

Mitigating Allocation and Hydrocarbon Accounting Uncertainty Using More Frequent Flow Test Data

Abstract Although the application of multi-phase flow meters has recently increased, the production of individual wells in many fields is still monitored by occasional flow tests using test separators. In the absence of flow measurement data during the time interval between two consecutive flow tests, the flow rates of wells are typically estimated using allocation techniques. As the flow rates, however, do not remain the same over the time between the tests, there is typically a large uncertainty associated with the allocated values. In this research, the effect of the frequency of flow tests on the estimated total production of wells, allocation, and hydrocarbon accounting has been investigated. Allocation calculations have been undertaken for three different cases using actual and simulated production data based on one to four flow tests per month. Allocation errors for each case have subsequently been obtained. The results show that for all the investigated cases, the average allocation error decreased when the number of flow tests per month increased. The sharpest error reduction has been observed when the frequency of the tests increased from one to two times per month. It reduced the allocation error for the three investigated cases by 0.43%, 0.45%, and 1.11% which are equivalent to $18.2M (million), $18.9M, and $46.8M reduction in the yearly cost of the allocation error for the respective cases. The reductions in the allocation error cost for the three cases were $27M, $29M, and $80M, respectively, when the flow tests have been undertaken weekly instead of monthly.

Prediction of the in-piston-bowl swirl ratio of diesel engines

Steady flow tests are widely used to evaluate the performance of intake ports in generating swirl flow in diesel engines. Such test data, however, may deviate largely from the real in-piston-bowl swirl ratio due to the complex unsteady air motion in the compression stroke. In this study, a new method is proposed to predict the unsteady in-piston-bowl swirl ratio of diesel engines from steady flow test data by focusing on three key steps, including the swirl field at intake valve close timing, swirl enhancement due to squish flow, and swirl decay during the compression stroke. Experimental results on an optically accessible diesel engine under non-firing conditions show that, at intake valve close, the relationship between the swirl ratio and the vertical location was approximately linear and the mean swirl ratio could be fitted by a Bessel function; the correlation between the swirl decay coefficient and surface-to-volume ratio was built by fitting the experiment data. Furthermore, the in-piston-bowl swirl ratio during the compression stroke could then be derived according to the conservation of angular momentum.

A theoretical model for the single-phase natural circulation flow rate and its assessment against the ATLAS test data

A theoretical model for the single-phase natural circulation flow rate has been derived on the assumption of the quasi-steady state flow. The unique feature of this model is that it is just a simple function of the heat source power rate and the system flow resistance number with a power of one third, enabling it very convenient for use and application. The derived model has also been assessed against available single-phase NC flow test data from the ATLAS facility, an integral effect test facility with respect to the APR1400. The test data used for the assessment include those from the SBO-01 test, a kind of (Station Blackout) scenario test, and those from the FLB-EC-01R test, a FLB (Feedwater Line Break) test. Different from conventional treatment where the power and mass pair is plot, the NC flow rate transient is correlated with the proposed model by a single constant flow resistance number Nr. The predicted NC flow rate with the proposed model agree very well with the test data, inferring that the change of the NC flow rate with time can be well correlated with the proposed model by a single constant flow resistance number Nr. In addition, the flow resistance number was also varied to see its effect on the NC flow rate.

Ambipolar zinc-polyiodide electrolyte for a high-energy density aqueous redox flow battery.

Redox flow batteries are receiving wide attention for electrochemical energy storage due to their unique architecture and advantages, but progress has so far been limited by their low energy density (~25 Wh l−1). Here we report a high-energy density aqueous zinc-polyiodide flow battery. Using the highly soluble iodide/triiodide redox couple, a discharge energy density of 167 Wh l−1 is demonstrated with a near-neutral 5.0 M ZnI2 electrolyte. Nuclear magnetic resonance study and density functional theory-based simulation along with flow test data indicate that the addition of an alcohol (ethanol) induces ligand formation between oxygen on the hydroxyl group and the zinc ions, which expands the stable electrolyte temperature window to from −20 to 50 °C, while ameliorating the zinc dendrite. With the high-energy density and its benign nature free from strong acids and corrosive components, zinc-polyiodide flow battery is a promising candidate for various energy storage applications.

Rheological Properties of Cement-Based Grouts Determined by Different Techniques

The rheological properties of cement-based grouts containing talc or palygorskite were investigated for optimizing fluidity and quick strengthening at injection. The fluidity controls the ability of grout to penetrate fractures and can be determined by pipe flow tests, Marsh funnel tests, mini-slump cone tests and rheometer tests. The grouts were 1) Talc for fluidity and strength by reacting with cement, 2) Palygorskite (attapulgite) for early gelation by being thixotropic, and 3) Powdered quartz for chemical integrity. The freshly prepared grouts behaved as Bingham fluids with viscosities from 0.151 to 0.464 Pas and yield stresses 5.2 Pa to 36.7 Pa. Statistical analysis of the flow test data converted Marsh flow time into viscosity. The pipe flow tests gave 26.5% higher values than the viscometer for grout with Portland cement and talc, and about 13.7% lower than the viscometer data for the grout with low-pH cement and talc. The big Marsh funnel gave values differing by 5.2% - 5.3% from those of the viscometer for grout with talc and Portland, and Merit 5000 cements. For grout with palygorskite the viscosity was at least twice that of the other grouts. Grout fluidity was positively affected by talc and negatively by palygorskite and early cement hydration.

Case study on combined CO2 sequestration and low-salinity water production potential in a shallow saline aquifer in Qatar

CO2 is one of the byproducts of natural gas production in Qatar. The high rate of natural gas production from Qatar's North Field (world's largest non-associated gas field) has led to the production of significant amounts of CO2. The release of CO2 into the atmosphere may be harmful from the perspective of global warming. In this work, we study the CO2 sequestration potential in Qatar's Aruma aquifer. The Aruma aquifer is a saline aquifer in the southwest of Qatar. It occupies an area of approximately 1985 km2 on land (16% of Qatar's total area). We have developed a compositional model for CO2 sequestration in the Aruma aquifer on the basis of available log and flow test data. We suggest water production at some distance from the CO2 injection wells as a possible way to control the pore pressure. This method increases the potential for safe sequestration of CO2 in the aquifer without losing integrity of the caprock and without any CO2 leakage. The water produced from this aquifer is considerably less saline than seawater and could be a good water source for the desalination process, which is currently the main source of water in Qatar. The outcome of the desalination process is water with higher salinity than the seawater that is currently discharged into the sea. This discharge can have negative long-term environmental effects. The water produced from the Aruma aquifer is considerably less saline than seawater and can be a partial solution to this problem.

Validation of CFD predictions using process data obtained from flow through an industrial control valve

This study uses the experimental flow test data to validate CFD simulations for a complex control valve trim. In both the simulation and the experimental flow test the capacity of the trim (Cv) is calculated in order to test the ability of CFD software to provide a design tool for these trims. While CFD tests produced results for the capacity which were consistent across a series of five different simulations, it differed from the experimental flow data by nearly 25%. This indicates that CFD simulations need to be properly calibrated before being used in designing complex valve trims.

Field appraisal and accurate resource estimation from 3D quantitative interpretation of seismic and CSEM data

The key questions in field appraisal are: What is the hydrocarbon volume, and how are the hydrocarbons distributed in the field? The ability to answer these questions accurately is critical for deciding whether to produce a field and for developing a production plan. Wells drilled during the appraisal phase provide well and flow-test data, which are combined with structural knowledge from seismic surveys to map the extent of the field and generate a reservoir model. The cost for appraising an offshore field can exceed US $100 million, and it is desirable to obtain the information required with fewer wells if possible. Quantitative interpretation of surface geophysical data provides reservoir properties between well locations and can, therefore, significantly reduce appraisal costs. A quantitative analysis of seismic data using well-log information will typically determine reservoir rock porosity. Other important parameters are hydrocarbon saturation, permeability, and net-to-gross ratio. Quantitative interpretation of several reservoir properties using only the seismic data is associated with significant ambiguity. To determine several of these parameters accurately, complementary geophysical data sets with different sensitivity characteristics are needed. Controlled-source electromagnetic (CSEM) data are sensitive to the fluid type and can provide additional information to determine the hydrocarbon saturation more accurately. We have developed a new quantitative interpretation workflow integrating seismic and marine 3D CSEM data for estimating the hydrocarbon volume and obtaining 3D distributions of the hydrocarbon pore volume. A performance test of the workflow has been carried out on the Troll West Oil Province (TWOP) in the Norwegian North Sea (Figures 1 and 2). This article describes our methodology and presents encouraging results.