Steady-state Model Research Articles

One-dimensional, multi-fluid model of the plasma wall transition. I. Hot electrons

The plasma-wall transition in a plasma containing singly charged positive ions and two groups of electrons is studied with a one-dimensional steady-state multifluid model, which is presented in some detail. When the temperature and the initial density ratio between the two groups of electrons are varied, a transition between the two types of solutions to the model equations is observed. When the density and temperature of the hot electrons are above certain critical values, a high solution is observed. If the ion mass is decreased, these critical values increase. However, this effect only occurs with artificially small ion masses, which are significantly lower than the proton mass. In the high solution, the potential drop is determined by the hot electrons and is greater in absolute terms than in the low solution, where it is determined by the base electron population. The transition between the low and high solutions is very sharp if a neutrality condition is imposed. However, if the neutrality condition is replaced by the Poisson equation, the transition becomes blurred and the solutions exhibit oscillations. The temperature profiles of the ions are analyzed, and it is confirmed that the ion sound and the ion fluid velocity become equal at the breaking point of the plasma neutrality. It is shown how the ion source term, the initial ion velocity, and the initial electric field are found to be self-consistent. The density profiles of the negatively biased particles resulting from the fluid equations deviate very little those of from the Boltzmann-distributed particles, even if the corresponding source terms are quite large.

Prevalence of HIV, HBV and HCV among livestock merchants and slaughterhouse workers in Ibadan, Nigeria.

Most studies on viral infections among livestock handlers have focused on occupational exposure from inadvertent contact with infected animals. Consequently, little emphasis is given to the effect of their lifestyle on the acquisition of other blood-borne viruses. To determine the prevalence and assess risk factors for HIV, HBV and HCV infections among livestock handlers in Ibadan, Nigeria. Blood samples were collected from 265 livestock handlers between October 2016 to April 2017 in Ibadan. The samples were tested for the presence of antibodies to HIV and HCV; and surface antigen to HBV using ELISA. Structured questionnaire was administered to collect information on risk factors associated with the transmission of these viruses. Data analysis was carried out using Chi-square test and logistic regression to determine the association between risk factors and predictors of infection (p < 0.05). Of 265 participants, 11 (4.2%), 29 (10.9%) and 13 (4.9%) individuals tested positive for HIV, HBV and HCV infections respectively. Two (0.8%) of the participants were coinfected with HIV and HBV while 1(0.4%) was coinfected with both HBV and HCV. Individuals who travelled frequently in the course of Livestock trades had a higher rate of HIV infection. A high Infection with HIV, HBV and HCV is common among the study participants. There is a need for continued surveillance and awareness creation on preventive measures against these viruses.

Numerical Analysis of Altered Parallel Flow Heat Exchanger with Promoted Geometry at Multifarious Baffle Prolongs

This study investigated the influence of BFFSP on the thermohydraulic performance of a SATHEC(s) using a novel computational approach. The novelty lies in the detailed exploration of the interplay between BFFSP, MFRT, and key performance parameters. Unlike prior studies, which often focus on a limited range of operating conditions, this work employs a comprehensive parametric analysis encompassing two BFFSPs (95 mm and 125 mm) and four MFRTs (0.1, 0.3, 0.5, and 0.7 kg/h). This extensive analysis provides a deeper understanding of the trade-off between the HTRFR enhancement and PDP associated with the BFFSP across a wider range of operating conditions. This investigation leverages the power of computational fluid dynamics (CFD) simulations for high-fidelity analysis. ANSYS Fluent, a widely recognized commercial CFD software package, was used as a computational platform. A three-dimensional steady-state model of HEXR geometry was established. The cold fluid was modeled as water, and the hot fluid was modeled as water. The selection of appropriate turbulence models is crucial for accurate flow simulations within the complex geometry of HEXR. This study incorporates a well-established two-equation turbulence model to effectively capture turbulent flow behavior. The governing equations for mass, momentum, and energy conservation were solved numerically within the CFD framework. Convergence criteria were meticulously established to ensure the accuracy and reliability of the simulation results. BFFs are crucial components in HEXRs as they promote fluid mixing and turbulence on the HTRFR surface, thereby enhancing HTRFR. This study explores the interplay between BFFSP and HTRFR effectiveness. It is hypothesized that a larger BFFSP (125 mm) might lead to a higher HTC owing to the increased fluid mixing. However, the potential drawbacks of the increased PDP due to the flow restriction also need to be considered. The PDP across the HEXR is a critical parameter that affects pumping costs and overall system yield. This study investigates the impact of BFFSP on the PDP. It is expected that a larger BFFSP (125 mm) will result in a higher PDP, owing to the increased resistance to fluid flow. Here, we aim to quantify the trade-off between enhanced HTRFR and increased PDP associated with different BFFSPs. The optimal design of an HEXR seeks a balance between achieving a high HTRFR rate and minimizing pressure losses. HTRPD, a metric combining both HTC and PDP, was employed to evaluate the thermohydraulic performance. We hypothesized that a specific BFFSP might offer a superior HTRPD, indicating an optimal balance between HTRFR effectiveness and PDP for the investigated HEXR geometry and operating conditions. CFD simulations were conducted using ANSYS Fluent to analyze the effects of BFFSP and MFRT on the HTC, PDP, and HTRPD. The simulations employed a commercially available HEXR geometry with water as the cold and hot fluid. The results are presented and discussed to elucidate the relationships between the BFFSP, MFRT, and key performance parameters of the HEXR. This study provides valuable insights into the influence of BFFSP on the thermohydraulic performance of HEXRs. The findings can aid in optimizing the HEXR design by identifying the BFFSP that offers the best compromise between HTRFR enhancement and PDP for specific operating conditions. The results contribute to the knowledge base of HEXR design and optimization, potentially leading to improved yield in various industrial applications. The results indicate that a larger BFFSP (125 mm) leads to higher outlet temperatures but also results in a higher PDP compared to the 95 mm design. Conversely, the 95 mm BFFSP exhibits a lower PDP but achieves a lower HTC. In terms of thermohydraulic performance, as indicated by HTRPD, the 95 mm BFFSP with the lowest MFRT (0.1 kg/h) achieved the highest value, surpassing the 125 mm design by 19.81%. This suggests that a 95 mm BFFSP offers a better trade-off between HTRFR effectiveness and pressure loss, potentially improving the overall HEXR performance.

Research on optimal power flow of AC/DC hybrid system for civil more electric aircraft

Modern civil more electric aircraft often use AC/DC systems instead of AC systems to reduce the weight of the power system. Compared with the AC/DC system of the land power grid, the aircraft power system needs to pursue economic operation mode under more complex security constraints. This paper establishes the optimal power flow model of the AC/DC hybrid system of more electric aircraft, which takes minimizing the active power loss of the line as the optimization objective, including the steady-state operation constraints and security constraints of the AC/DC system. The interior point method and prediction correction interior point method are used to solve the model. Then, based on the simplified steady-state model of the B787 power system, the model and algorithm are verified by experiments. The experimental results show that by optimizing the power flow distribution of the power system, the power utilization efficiency of the system has been significantly improved, and its stability and reliability can also be better guaranteed.

Discovery and characterization of l-DOPA 2,3-dioxygenase from Streptomyces hygroscopicus jingganensis

The largest natural reservoir of untapped carbon can be found in the cell-wall strengthening, plant woody-tissue polymer, lignin - a polymer of catechols or 1,2-dihydroxybenzene monomers. The catecholic carbon of lignin could be valorized into feedstocks and natural products by way of catabolic and biosynthetic transformations, including the oxygen-dependent cleavage reaction of extradiol dioxygenase (EDX) enzymes. The EDX l-DOPA 2,3-dioxygenase was first discovered as part of a biosynthetic gene cluster to the natural product antibiotic, lincomycin, and also contributes to the biosyntheses of anthramycin, sibiromycin, tomaymycin, porothramycin and hormaomycin. Using these l-DOPA 2,3-dioxygenases as a starting point, we searched sequence space in order to identify new sources of dioxygenase driven natural product diversity. A “vicinal-oxygen-chelate (VOC) family protein” from Streptomyces hygroscopicus jingganensis was identified using bioinformatic methods and biochemically investigated for dioxygenase activity against a suite of natural and synthetic catechols. Steady-state oxygen consumption assays were used to screen and identify substrates, and a steady-state kinetic model of oxygen consumption was developed to evaluate activity of the S. hygroscopicus jingganensis VOC-family-protein with respect to activity of l-DOPA 2,3-dioxygenases from Streptomyces lincolnensis and Streptomyces sclerotialus. Lastly, these data were integrated with steady-state kinetic methods to observe the formation of the EDX cleavage product with UV–visible spectroscopy. The genomic context and enzymatic activity of the S. hygroscopicus jingganensis VOC family protein are consistent with a l-DOPA 2,3-dioxygenase contained within a cryptic biosynthetic pathway.

Prediction of Production-Inflow Profile of a Well Producing Single-Phase Flow of Slightly Compressible Fluid from Multilayer Systems by Temperature and/or Pressure Transient Data

Summary This study focuses on the prediction of the production-inflow profile of a well producing a single-phase flow of slightly compressible fluid (water or oil flow) in a multilayered system using the layer permeability and skin values estimated by history matching spatial and temporal temperature and/or pressure data sets along the completion interval. Such data may be acquired by wireline formation testing, production-logging-tool (PLT), or distributed temperature sensing (DTS) fiber-optic cables. We use an in-house thermal, transient coupled reservoir/wellbore simulator developed during this study. It solves transient mass, momentum, and energy conservation equations simultaneously for both reservoir and wellbore. The effects of the Joule-Thomson (J-T), adiabatic expansion, conduction, and convection are all included for predicting the flow profiles across the wellbore. The results from our in-house simulator are verified with the results from a commercial simulator for the single-phase fluid flow of a vertical well producing geothermal brine and oil in a two-zone multilayer system. We also compare the results from our rigorous transient coupled wellbore/reservoir model with the results from a model assuming steady-state thermal wellbore model used in the previous studies. We find that the steady-state thermal wellbore model used in the previous studies that ignore accumulation terms in mass, momentum, and thermal energy balances is a reasonably accurate model for predicting wellbore pressures and temperatures when it is coupled with a nonisothermal reservoir model for slightly compressible fluid because the transient effect in the wellbore is less important with the slightly compressible fluid. We investigate the nonlinear parameter estimation problem based on the use of single or multiple observed temperature and/or pressure (if available) profiles recorded spatially inside the wellbore and at the sandface. The purpose is to identify if the wellbore or sandface data profiles are more useful to accurately estimate the permeability and skin information and predict a production-inflow profile of the well depending on the representation of an actual multilayer system by a reduced-layered or fine-layered model. We show that using an upscaled-layered model (e.g., representing each heterogeneous layer with a lumped single layer with uniform permeability and skin) provides estimates that are more toward the thickness-average permeability and skin factors of the layers and may not provide a good prediction of the well’s production-inflow profile. We show that including the sandface temperature data in regression worsens, while the use of wellbore temperature data sets improves the quality of parameter estimation if an upscaled multilayered model is used. We also show that regressing on multiple temperature profiles, preferably at the sandface, alone could be used to predict the production-inflow profile accurately if a “fine” multilayered heterogeneous model is used. We also investigate if including or excluding the temperature and/or pressure measurements at the nonperforated sections along the completion interval could help enhance the parameter estimation problem. The results show that when multiple profiles of temperatures including the data at nonperforated zones at different production rates are regressed, reliable estimates of the individual layer properties that predict the production-inflow profile accurately can be obtained, though layer permeability and skin factors may often exhibit wide 95% confidence intervals and high correlations among them. Adding sandface or wellbore pressure data, if available, into observed data sets in history matching always improves the quality of parameter estimation.

An intelligent fault detection and diagnosis monitoring system for reactor operational resilience: Unknown fault detection

Multiple advanced reactor designs envision deployment scenarios that feature reactor operations with significantly reduced operating staff compared to present reactors, or even feature fully autonomous operations. Since many of these new reactor designs, like small modular reactors (SMRs) and microreactors, also include extended fuel cycles which limit inspection intervals, load-following capabilities, and reduced access to critical components, safe and reliable semi- or fully autonomous operations must be enabled through an on-line monitoring (OLM) system that effectively detects and diagnoses any faults in the reactor. This paper presents the development of the Fault Detection Module of the previously proposed intelligent OLM system: the Fault Detection and Diagnosis Monitoring System (FDDMS). The Fault Detection Module monitors various plant parameters from 86 sensors throughout the nuclear power plant and accurately defines operations as nominal or abnormal. The methodology leverages the advantages of unsupervised learning and semi-supervised optimization data-driven techniques to successfully detect any fault in the system in real-time without fault information a priori. This allows the Fault Detection Module to identify any unknown fault that may affect the system. When integrated with the rest of the FDDMS architecture, the Fault Detection Module provides power transient dependent fault detection by using a separate model for steady state, ramping up in power, and ramping down in power operations. This makes the FDDMS especially applicable for load-following reactor systems. The Fault Detection Module architecture features a dimensionality reduction algorithm followed by an anomaly detection method. Three dimensionality reduction techniques: 1) Principal Component Analysis (PCA), 2) Deep Neural Network Autoencoder (DNNAE), and 3) Convolutional Neural Network Autoencoder (CNNAE); and three anomaly detection methods: 1) One-Class Support Vector Machine (OC-SVM), 2) Clustering (DBSCAN), and 3) Reconstruction Error (RecErr) thresholding were compared to find the best model for each power transient dataset. Precision rates, recall rates, F1-scores, and accuracies were used to compare model performance. The best models produced total accuracies of 94.50%, 93.63%, and 91.76% for the steady state, ramp up, and ramp down datasets, respectively, or 99.19%, 98.97%, and 97.09% when omitting 1%-severe fault cases. Specifically, the best performing models for the steady state, ramp up, and ramp down cases were the CNNAE-RecErr, DNNAE-DBSCAN, and CNNAE-RecErr, respectively. Recall rates were calculated for various fault types at multiple severity levels. The results show that the Fault Detection Module can identify any type of fault in the system with a delay of a few seconds on average. Additionally, robustness against noisy sensor data was tested, with models maintaining 100% accuracy at various levels of noise, and an illustrative real-time application of the methodology is provided.

Energy Consumption Optimization Analysis of LNG Receiving Station Based on Genetic Algorithm

In response to the problem of high energy consumption in LNG receiving stations, based on literature research, numerical simulation combined with genetic algorithm optimization methods were used to establish a calculation model and ASPEN HYSYS steady-state simulation model for the LNG receiving station equipment, each unit process and the overall receiving station process. The various parameters in the LNG receiving station will have a certain impact on the overall energy consumption of the LNG receiving station. Combined with the operating requirements of the LNG receiving station site under different working conditions, and considering the coupling effect of multiple factors, the technology of optimizing the operating parameters of the LNG receiving station to reduce energy consumption is selected, and the adjustable decision-making parameters and their range of changes are selected, and the constraints are set according to the actual situation and Establish the energy optimization objective function of the LNG receiving station process system, and evaluate and analyze the energy consumption indicators of the optimized process system.

Dynamic wind farm flow control using free-vortex wake models

Abstract. A novel dynamic economic model-predictive control strategy is presented that improves wind farm power production and reduces the additional demands of wake steering on yaw actuation when compared to an industry state-of-the-art reference controller. The novel controller takes a distributed approach to yaw control optimisation using a free-vortex wake model. An actuator-disc representation of the wind turbine is employed and adapted to the wind farm scale by modelling secondary effects of wake steering and connecting individual turbines through a directed graph network. The economic model-predictive control problem is solved on a receding horizon using gradient-based optimisation, demonstrating sufficient performance for realising real-time control. The novel controller is tested in a large-eddy simulation environment and compared against a state-of-the-art look-up table approach based on steady-state model optimisation and an extension with wind direction preview. Under realistic variations in wind direction and wind speed, the preview-enabled look-up table controller yielded the largest gains in power production. The novel controller based on the free-vortex wake produced smaller gains in these conditions while yielding more power under large changes in wind direction. Additionally, the novel controller demonstrated potential for a substantial reduction in yaw actuator usage.

Dynamic modeling of a centrifugal chiller with hybrid falling film evaporator including pressure drop computation

Over the last decade, the introduction of new technologies such as falling film evaporators and advanced control techniques has significantly enhanced chiller efficiency while reducing refrigerant charges. However, the complexity of the involved transport phenomena poses significant challenges in simulating the behavior of these devices, resulting in very few validated models that encompass such advances. This study introduces a novel dynamic model for centrifugal liquid chillers with a hybrid evaporator (one that combines features of falling film and flooded designs). Employing the moving boundary method, the model incorporates the intricacies of the transport phenomena, including the pressure drop across the tube bank, with relatively low computational requirements. Implemented in OpenModelica, the model was validated using performance data from a 550 TR centrifugal chiller, yielding normalized residual errors of less than 0.5% for values of supply water temperature and power consumption. This provides a comprehensive tool suitable for analyzing chiller performance as a function of the evaporator geometric characteristics and enabling optimal dynamic control of central cooling systems incorporating this kind of chillers, as long as contributes to the development of dynamic and steady state models of vapor compression centrifugal chillers with falling film evaporators.

Multicomponent steady-state modeling, performance optimization and prediction of cleaning frequency for treatment of cellulosic manmade fibre industry stream using polysodium 4- styrenesulfonate (PSS) incorporated nanofiltration membrane

Effect of polysodium 4-styrenesulfonate (PSS) in the skin layer on performance of nanofiltration (NF) membrane was analyzed for treatment of saline stream from manmade fiber industry. The NF membrane with 0.05 % (w/w) PSS concentration in aqueous phase had better hydrophilicity (contact angle: 330) and water flux of 27 L.m−2.h−1 along with significant salt rejection (Na2SO4: 90 %, CaSO4: 85 % and NaCl: 80 %) at transmembrane pressure 8.3 bar and crossflow rate 100 L.h−1. A long-term study with the wastewater showed that the intermittent cleaning of the membrane every 6 h led to 16 L.m−2.h−1 average permeate flux and sulfate rejection above 95 %.A two-component, steady-state model was used to quantify the performance of the selected membrane. Based on the fouling study, a semi-empirical theory was proposed to identify the cleaning frequency. The theory developed is useful for the operation, maintenance and recovery of the divalent salts from reject stream of such industry.

A data-driven approach for simplifying the estimation of time for contaminant plumes to reach their maximum extent

Globally there exist a very large number of contaminated or possibly contaminated sites where a basic preliminary assessment has not been completed. This is largely, among others, due to limited simple methods/models available for estimating key site quantities such as the maximum plume length, further denoted as Lmax and the corresponding time T=TLmax, at which the plume reaches its maximum extent L=Lmax. An approach to easily obtain an estimate of TLmax in particular is presented in this work. Limited availability of high-quality field data, particularly of TLmax, necessitates the use of synthetic data, which constrains the overall model development works. Taking BIOSCREEN-AT (transient 3D model) as a base model, this work proposes second-order polynomial models, with only two parameters, for estimating Lmax and TLmax. This reformulation of the well established solution significantly reduces data requirement and workload for initial site assessment purposes. A global sensitivity analysis (Morris, 1991), using a large number of random synthetic data, identifies the first-order decay rate constants in the plume λEFF and at the source γ as dominantly most influential for TLmax. For Lmax, the first-order decay rate constant λEFF and groundwater velocity v are the two important parameters. The sensitivity analysis also identifies that these parameters non-linearly impact TLmax or Lmax. With this information, the proposed polynomial models (each for Lmax and TLmax) were trained to obtain model coefficients, using a large amount of synthetic data. For verification, the developed models were tested using four datasets comprising over 100 sample sets against the results obtained from BIOSCREEN-AT and the developed BIOSCREEN-AT-based steady-state model. Additionally, the developed models were evaluated against two well documented field sites. The proposed models largely simplify estimation, particularly, of TLmax, for which only very limited field or literature information is available.

Experimental and Numerical Simulation Study of Oxygen Transport in Proton Exchange Membrane Fuel Cells at Intermediate Temperatures (80 °C-120 °C).

Investigating the oxygen transport law within the Membrane Electrode Assembly at intermediate temperatures (80-120 °C) is crucial for enhancing fuel cell efficiency. This study analyzed the resistance to oxygen transport within the Membrane Electrode Assembly at intermediate temperatures using limiting current density and electrochemical impedance spectroscopy. The study findings reveal that, as temperature progressively increases, the Ostwald ripening effect leads to a 34% rise in the local oxygen transport resistance (Rlocal) in relation to the pressure-independent resistance (Rnp) within the cathode catalytic layer. Concurrently, the total transport resistance (Rtotal) decreases from 27.8% to 37.5% due to an increase in the gas diffusion coefficient and molecular reactivity; additionally, there is a decrease in the amount of liquid water inside the membrane electrode. A three-dimensional multiphysics field steady-state model was also established. The model demonstrates that the decrease in oxygen partial pressure can be mitigated effectively by increasing the back pressure at intermediate temperatures to ensure the cell's performance.

Non-steady-state stomatal conductance modeling and its implications: from leaf to ecosystem

Abstract. Accurate and efficient modeling of stomatal conductance (gs) has been a key challenge in vegetation models across scales. Current practice of most land surface models (LSMs) assumes steady-state gs and predicts stomatal responses to environmental cues as immediate jumps between stationary regimes. However, the response of stomata can be orders of magnitude slower than that of photosynthesis and often cannot reach a steady state before the next model time step, even on half-hourly timescales. Here, we implemented a simple dynamic gs model in the vegetation module of an LSM developed within the Climate Modeling Alliance and investigated the potential biases caused by the steady-state assumption from leaf to canopy scales. In comparison with steady-state models, the dynamic model better predicted the coupled temporal response of photosynthesis and stomatal conductance to changes in light intensity using leaf measurements. In ecosystem flux simulations, while the impact of gs hysteresis response may not be substantial in terms of monthly integrated fluxes, our results highlight the importance of considering this effect when quantifying fluxes in the mornings and evenings, as well as interpreting diurnal hysteresis patterns observed in ecosystem fluxes. Simulations also indicate that the biases in the integrated fluxes are more significant when stomata exhibit different speeds for opening and closure. Furthermore, prognostic modeling can bypass the A-Ci iterations required for steady-state simulations and can be robustly run with comparable computational costs. Overall, our study demonstrates the implications of dynamic gs modeling for improving the accuracy and efficiency of LSMs and for advancing our understanding of plant–environment interactions.

Modelling the impact of deep fractures on groundwater flow and slope stability in post-glacial marine clays (Quebec, Canada)

It is usually assumed that post-glacial marine clay deposits, such as those found in Quebec, are generally intact below a shallow fractured crust (3–5 m depth). However, recent work has shown the presence of hydraulically-active fractures to depths of down to 16 m. In light of this finding, the potential impacts of these fractures on groundwater flow dynamics and slope stability are explored by comparing field data with the results of transient and steady-state groundwater models with and without fractures. Two slope geometries that exhibit contrasting groundwater flow directions and different fracture scenarios were considered. The results of the hydrogeological modelling were then imported into a slope stability model to determine how the hydraulic effects of these fractures impact slope stability. Results show that fractures increase hydraulic head when they act as preferential pathways for infiltration, but can also reduce hydraulic head by acting as pathways for water to more quickly exit the formation within the slope face. Therefore, from a hydrogeological perspective, fractures could improve or reduce slope stability depending on the groundwater flow system. As this study only addressed the hydrogeological impact of the fractures, future work should focus on the coupled hydromechanical impacts of these features.

Co-Fe bimetallic oxides derived from Prussian blue analogs to activate peracetic acid for eliminating sulfamethazine: Contribution and identification of radical species

Peracetic acid (PAA), as a disinfectant with powerful oxidation and exceptional antimicrobial efficiency, has gained considerable attention for its application in advanced oxidation processes (AOPs). However, leaching of metal ions and low recovery efficiency limited the application of heterogeneous AOPs. Herein, we synthesized a CoFe bimetallic oxide (Co-Fe-O) derived from Prussian blue analogs to serve as an activator for PAA, efficiently eliminating sulfamethazine (SMZ) in a wide pH range (5–9). Electron paramagnetic resonance and quenching test revealed the coexistence of radical species in the system, and R-O· were the main factors of SMZ elimination. The steady-state model evaluation showed that 3.1 × 10−14 M R-O· and 2.05 × 10−14 M ·OH existed in the system. CoFe bimetallic synergies expedite the generation of radical species. Based on density functional theory, the aniline ring and heterocyclic ring of SMZ were regarded as the susceptible sites for radical attack and electron transfer. Furthermore, the elimination pathway of SMZ was proposed by combining the results of intermediate products. Additionally, the toxicity of SMZ and intermediates as well as the reaction conditions, water matrices, stability, and oxidation capacity of Co-Fe-O/PAA were subjected to evaluation. Results indicate that the Co-Fe-O/PAA system has significant application potential in the elimination of micropollutants.

Evaluation of Recovery of Tight Sandstone Gas Reservoirs Based on a Seepage Steady-State Model

As an important indicator for measuring the effectiveness and level of oil and gas field development, recovery rate has always been a focus in the research of oil and gas fields. Reservoirs of tight sandstone gas formations have significant characteristics of low porosity, high permeability, and high water content, which leads to greater difficulty in their development and makes it challenging to evaluate the recovery rate. Newtonian mechanics, as an important component of the mechanical system, is an innovative application of classical mechanics in the field of seepage mechanics when applied to the two-phase flow of gas and water. Firstly, starting from the perspective of mechanics analysis, we derive a steady-state model for gas–water two-phase infiltration and obtain the productivity equation based on this model. Then, according to the steady-state model, we establish a method to calculate the effective control radius of gas reservoirs under different production conditions and reservoir physical properties. Finally, using Matlab 2018a programming based on the productivity equation, we calculate the gas recovery under different conditions during constant pressure drop production and constant production rate production. The results indicate that the effective control radius of the reservoir decreases with an increase in the economic ultimate daily gas production, increases with an increase in production pressure difference, slightly decreases with an increase in startup pressure gradient, and correspondingly increases with an increase in microtube radius and quantity. Regardless of whether it is production with a fixed pressure drop or production with a fixed production rate, the gas recovery decreases as the production pressure drop and bottomhole abandonment pressure increase, but it increases as the proportion of the single-well control radius increases. In production with a fixed pressure drop, the gas recovery remains consistent across different reservoir quality indices. However, in production with a fixed production rate, the gas recovery initially increases rapidly and then gradually slows down as the reservoir quality index increases, and there is an obvious critical permeability (0.1 mD). The research findings are based on the mechanical analysis of porous media, delving into the laws governing fluid flow during infiltration. The derived infiltration model can be used to calculate the effective control radius and evaluate recovery rates, providing practical guidance for reservoir development.

Advancements in Iso-Diameter seeded growth of CdZnTe crystals: A numerical modeling approach and applications in liquid phase Epitaxy

CdZnTe (CZT) is the preferred material for HgCdTe (MCT) infrared detectors and room temperature nuclear-radiation detector applications. However, their widespread application is hindered by the low yield, attributed to intrinsic thermophysical properties like extremely low thermal conductivity and stacking fault energy, complicating the growth of large-volume crystals. Based on steady-state computer numerical modeling simulation, this paper examines the impact of seed size variations (from 15 mm to 90 mm) in the crystal growth process on the initial growth surface morphology, simulations indicate that larger seed crystals are predisposed to developing more convex interfaces, which are conducive to enhanced crystal growth. An optimized Vertical Gradient Freeze (VGF) method employing iso-diameter seed (having the same diameter as the grown crystals) of approximately 90 mm has been developed to grow single crystals with reduced defect density in a VGF furnace, and the applications in liquid phase epitaxy (LPE) are also discussed.

Electrical-thermal modeling and electrical design optimization of fuses in a nickel bus-plate for a Li-ion battery pack

This paper presents a two-dimensional thermal-electrical coupled steady-state physics-based finite-element model developed to analyze Nickel 201 (Ni201) bus-plates for a novel 134P battery pack design, where a 1.4C current was applied per cell. Two modeling approaches were used: one with an out-of-plane current density boundary condition inserted in the charge conservation equation and a second one with a constant voltage boundary condition calculated at each battery tab. Both positive and negative-bus plate designs were analyzed. Electric resistance measurements were used to validate the model and the two modeling approaches. This study demonstrated that a nickel bus plate design can be optimized, without the addition of extra material or substantive geometry changes, by clocking the fuses and weld tab connections towards the direction of the closest terminal connection point. The resulting geometry, mimicking a sunflower formation, can reduce the internal resistance of the bus plate by at least 15 %, regardless of the modeling approach used.

Scalar-potential mapping of the steady-state magnetosheath model

Abstract. The steady-state magnetosheath model has various applications for studying the plasma and magnetic field profile around the planetary magnetospheres. In particular, the magnetosheath model is analytically obtained by solving the Laplace equation for parabolic boundaries (bow shock and magnetopause). We address the question, how can we utilize the magnetosheath model by transforming into a more general, empirical, non-parabolic magnetosheath geometry? To achieve the goal, we develop the scalar-potential mapping method which provides a semi-analytic estimate of steady-state flow velocity and magnetic field in the empirical magnetosheath domain. The method makes use of a coordinate transformation from the empirical magnetosheath domain into the parabolic magnetosheath domain and evaluates a set of variables (shell variable and connector variable) to utilize the solutions of the Laplace equation obtained for the parabolic magnetosheath domain. Our model uses two invariants of transformation: the zenith angle within the magnetosheath with respect to the direction to the Sun and the ratio of the distance to the magnetopause and the thickness of magnetosheath along the magnetopause-normal direction. The use of magnetopause-normal direction makes a marked difference from the earlier model construction using the radial direction as reference. The plasma flow and magnetic field can be determined as a function of the upstream condition (flow velocity or magnetic field) in a wide range of zenith angles. The scalar-potential mapping method is computationally inexpensive, using analytic expressions as much as possible, and is applicable to various planetary magnetosheath domains.