Experimental validation of an adsorbent-agnostic artificial neural network (ANN) framework for the design and optimization of cyclic adsorption processes

The efficacy of an adsorbent agnostic machine-learning surrogate model for rapid design and optimization of a Skarstrom cycle vacuum swing adsorption (VSA) process is experimentally validated. The surrogate model is trained to predict the process performance using adsorbent features that include hypothetical Langmuir adsorption isotherm parameters, particle density, porosity and bed voidage, and process variables such as pressure, step duration and feed velocity. The training data was generated from a detailed process model for 20,000 unique combinations of the training variables. The model shows high accuracy of R2adj>0.99 for predicting key performance parameters such as product purity, recovery and productivity. The ability of this surrogate to predict the experimental performance for the purification of O2 from the air on two adsorbents, namely 13X and LiX zeolites, was studied. Two separate multi-objective optimization studies, to maximize purity and recovery, and to maximize productivity and purity were performed. For these optimization studies, the volumetrically measured isotherms of N2 and O2 were used as inputs to the surrogate model. Note that these isotherms were not a part of the dataset used to train the model. Nine points were chosen from the Parteo curves and the corresponding decision variables were used as set-points in a two-column lab-scale rig. The average difference between the calculated and experimentally measured purity, recovery and productivity was 3%, 5% and 9%, respectively. This study provides the necessary confidence to use surrogate-based process models for adsorbent screening and adsorption process optimization.

Accurate Live Interfacial Tension for Improved Reservoir Engineering Practices

Current reservoir simulators use interfacial tension (IFT) values derived from dead oil measurements at ambient conditions or predicted from literature correlations. IFT is highly dependent on temperature, pressure and fluid composition. Therefore, knowledge of the IFT value at reservoir conditions is essential for accurate reservoir fluid characterization. This study compares IFT values from dead and live oil measurements and the results of literature predicted values, thereby clearly showing the weakness of existing correlations when trying to predict crude oil IFT. A total of ten live oils was sampled for this study. Using the pendent drop technique, IFT was measured for each oil at different conditions: in the under-saturated region at reservoir pressure and temperature, in the saturated region at reservoir temperature, and for dead oil at ambient conditions. Basic PVT properties such as gas to oil ratio (GOR), gas and liquid composition, density, viscosity and molecular weight were also measured. The bubble point for each oil was identified to define the pressure step in the saturated region for extra IFT measurement. The equilibrium IFT values for the live oils were generally higher than for the corresponding dead oils. For oils where this general trend was not observed, contaminations were found in the crude samples. The use of current literature correlations does not allow to predict correct reservoir IFT. Therefore, this study provides accurate live IFT values for a variety of reservoir fluids and conditions in combination with live oil properties, highly beneficial to reservoir engineers, allowing better oil production planning.

Membranes for the Gas/Liquid Phase Separation at Elevated Temperatures: Characterization of the Liquid Entry Pressure

Hydrophobic membranes were characterized at elevated temperatures. Pressure was applied at the feed and permeate side to ensure liquid phase conditions. Within this scope, the applicability of different polymeric and ceramic membranes in terms of liquid entry pressure was studied using water. The Visual Method and the Pressure Step Method were applied for the experimental investigation. The results show the Pressure Step Method to be an early detection method. The tests at higher pressure and temperature conditions using the Pressure Step Method revealed the temperature as being the main factor affecting the liquid entry pressure. Novel LEP data up to 120 °C and 2.5 bar were obtained, which broadens the application range of hydrophobic membranes.

Research and Control of Underground Pressure Law of Coal Mining Face in Soft Rock Strata Based on Neural Network under the Background of Wireless Network Communication

Our country has a vast territory and rich resources, but it is a country with more coal, less oil, and poor gas. With the increase of our population, the development of society, and the more severe international situation, coal has become more important for our country’s economic development and energy. Security plays an irreplaceable role. Based on the neural network, this paper studies and controls the underground pressure law of the coal mine’s soft rock heading face, aiming at the safe and efficient mining of the first face and providing an experience for the next face. This paper mainly uses BP neural network learning algorithm and support pressure algorithm to measure and study the ground pressure law of coal mine soft rock heading face and establishes the ground pressure online monitoring system, which is used to analyze and summarize the ground pressure abnormal area during the mining of the working face, so as to provide the basis for safe mining of the working face. Through the field measured data, the initial pressure step and periodic pressure step at the upper, middle, and lower parts of the working face, the average working resistance of the support at the working face during pressure, and the dynamic load coefficient of the support are obtained. It is analyzed that the support in the middle of the working face has a large load and the pressure is obvious. The experimental results show that the initial support force of the whole working face is approximately normally distributed, the proportion of the initial support force in the range of 10–30 MPa accounts for more than 85% of the total statistics, and the frequency of the initial support force in the upper, middle, and lower stations at 10–25 MPa is 55%–65%.

Optimizing Sour Qualification Testing – Determination and Verification of H₂S Solubility from H₂S/N₂ Gas Mixtures up to 20,000 psig at 70 °F

Traditionally, the H<sub>2</sub>S partial pressure (P<sub>H2S</sub>) of the gas/hydrocarbon phase has been used as the primary sour severity metric for material qualification and selection under ANSI/NACE MR0175/ISO 15156 guidelines. While the P<sub>H2S</sub> is appropriate for characterizing low total pressure systems, the strict, or ideal, Henry’s Law approach leads to over estimation of the dissolved H<sub>2</sub>S concentration (C<sub>H2S</sub>) for high-pressure, high-temperature (HPHT) wells by up to ~20 times at 70 °F (21 °C). Alternatively, the Ensemble Henry’s Law equation corrects for the non-ideal phase behavior of H<sub>2</sub>S at HPHT conditions and avoids over-estimation of C<sub>H2S</sub>. Given the industry’s reliance on using thermodynamic models to evaluate sour HPHT systems, an investigation was initiated to determine the accuracy of these model calculations. An empirical program was undertaken to verify C<sub>H2S </sub>predictions for the H<sub>2</sub>S-N<sub>2</sub>-H<sub>2</sub>O system. Multiple 2.7-L C-276 lined autoclaves were charged with a fixed inventory of H<sub>2</sub>S in N<sub>2</sub> at multiple total pressure steps, with increasing N<sub>2</sub> pressure, between 30 and 20,000 psig (3 and 1,380 bar) at 70 ± 5 °F (21 ± 3 °C). Per total pressure step, H<sub>2</sub>S levels in both the liquid and gas phases were measured using common H<sub>2</sub>S sampling techniques (H<sub>2</sub>S-specific colorimetric tubes and iodometric titration, respectively), following ANSI/NACE TM0177-2016 guidelines. The results were used to calculate total pressure corrected (apparent) H<sub>2</sub>S solubility coefficients (<sup>A</sup>k<sub>H2S</sub>). Very good agreement was observed between empirically and computationally derived <sup>A</sup>k<sub>H2S</sub> values. Key words: ANSI/NACE TM0177-2016, ANSI/NACE TM0284-2016, Sour testing, Ensemble Henry’s Law, Ionic-equation of state (EOS) frameworks, H2S solubility, Iodometric titration.

THE DYNAMIC CALIBRATION UNCERTAINTY OF FAST RESPONSE PRESSURE PROBES

In this paper, error sources affecting the dynamic calibration of fast response pressure probes in shock tubes are examined. In particular, the sensors uncertainty, the uncertainty in the rising point of the pressure step and the nonideality of the step are treated. The latter refers to the presence of pressure oscillations past the shock front, which are particularly important in the case of low-pressure shock tubes, typically used for the calibration of pressure probes for turbomachinery applications. The nonideality effect is investigated using a Linear Time Invariant (LTI) second order model for the transfer function of the probe's line-cavity system and an existing analytical model for the post-shock oscillations. The effect of these uncertainty sources to the experimentally determined transfer function of a fast response probe calibrated in the von Karman Institute (VKI) shock tube are finally presented.

Grain scale investigation of shear reactivation by fluid pressurization

<p>Fluid pressurization of critically stressed sheared zones can trigger slip mechanisms at the origin of many geological rupture processes such as earthquakes and landslides. It is now well assumed that the reduction of effective stress induced by fluid pressurization can lead to the reactivation of shear zones. However, the micromechanisms that govern this reactivation remain poorly understood. By using discrete element modeling, we simulate pore-pressure-step creep test experiments on a sheared granular layer at a sub-critical stress state in order to investigate the micromechanical processes at stake during fluid induced reactivation. The simulated responses are consistent with both laboratory and in situ experiments, confirming the scale independent nature of fluid induced slip. The progressive increase of pore pressure promotes slow steady slip at sub-critical stress states and fast accelerated dynamic slip once the critical strength is overcome. The analyses of both global and local quantities show that these two emergent slip behaviors correlate to characteristic deformation modes: diffuse deformation for slow slip and highly localized deformation for fast slip. Our results suggest that, besides the control of the fabric of shear zones on their emergent slip behavior, failure is associated to grain rotations resulting from unlocking of interparticle contacts mostly located within the shear band, which, as a consequence, acts as a roller bearing for the surrounding bulk.</p>

Diaphragmless shock tube for primary dynamic calibration of pressure meters

In conventional shock tubes with a diaphragm many effects related to the burst of the diaphragm can influence the shock formation and thus prevent an ideal pressure step change predicted by the shock tube measurement model being generated. This paper presents a newly developed diaphragmless shock tube, in which a diaphragm is replaced with a quick-acting pneumatic valve. The developed shock tube has a capability to generate pressure steps calculable from its measurement model with a relative expanded uncertainty of less than 0.025, which can be used as the input signal in primary calibrations of pressure meters.

Hyperemic hemodynamic characteristics of serial coronary lesions assessed by pressure pullbacks gradients (PPG) index

Introduction The evaluation of functional significance in serial coronary lesions is crucial for achieving optimal clinical outcomes. In this setting, fractional flow reserve (FFR) measurements with pullback pressure recording can be helpful in assessing lesion functional significance. Purpose To describe the functional characteristics of angiography-defined serial coronary lesions using FFR-derived motorised pullback tracings, and to describe the Pullback Pressure Gradients (PPG) index - in these lesions. Methods Prospective, multicentre study with independent core laboratory analysis. Patients undergoing coronary angiography due to stable angina were enrolled. Serial lesions were defined angiographically as the presence of 2 or more narrowings with visual diameter stenosis >50% separated at least by 3 times the reference vessel diameter in the same coronary vessel. Continuous IV adenosine-FFR measurements were obtained using a motorised device at a speed of 1 mm/s. Pullback curves were assessed to determine the presence of focal step-ups (FFR >0.05 units over 20 mm). In addition, the PPGindex was computed for all vessels. PPGindex values close to 0 define functional diffuse disease whereas values close to 1 define focal disease. Results From a total of 159 vessels (117 patients), 25 vessels were adjudicated as presenting serial lesions (mean PPGindex 0.48±0.17, range 0.26–0.87). Two focal pressure step-ups were observed in 40% of the cases (n=10; mean PPGindex 0.59±0.17), whereas 8% of the vessels presented a progressive pressure losses (n=2; mean PPGindex 0.27±0.01). In the remaining 52% of the cases, a single pressure step-up was recorded (n=13; mean PPGindex 0.44±0.12; ANOVA p-value = 0.01). The PPGindex independently predicted the presence of two focal pressure step ups. Conclusion Hyperemic FFR curves in tandem stenoses revealed high prevalence of functional diffuse CAD. Two pressure step-ups occurred in less than half of the vessels. High PPG-Index identified vessels with two focal pressure drops. FFR tracings and the PPGindex provide a more objective CAD evaluation, which can lead to changes in the therapeutic approach. Funding Acknowledgement Type of funding source: None