Characteristics of proppant transport and placement within rough hydraulic fractures

A three-dimensional reconstruction of rough fracture surfaces of hydraulically fractured rock outcrops is carried out by casting process,a large-scale experimental setup for visualizing rough fractures is built to perform proppant transport experiments.The typical characteristics of proppant transport and placement in rough fractures and its intrinsic mechanisms are investigated,and the influences of fracture inclination,fracture width and fracturing fluid viscosity on proppant transport and placement in rough fractures are analyzed.The results show that the rough fractures cause variations in the shape of the flow channel and the fluid flow pattern,resulting in the bridging buildup during proppant transport to form unfilled zone,the emergence of multiple complex flow patterns such as channeling,reverse flow and bypassing of sand-carrying fluid,and the influence on the stability of the sand dune.The proppant has a higher placement rate in inclined rough fractures,with a maximum increase of 22.16 percentage points in the experiments compared to vertical fractures,but exhibits poor stability of the sand dune.Reduced fracture width aggravates the bridging of proppant and induces higher pumping pressure.Increasing the viscosity of the fracturing fluid can weaken the proppant bridging phenomenon caused by the rough fractures.

Experiment of non-vascularized iliac bone grafts with the simultaneous placement of titanium nnplants

AIM:To investigate the osseointegration process of titanium implant and non-vascularized iliac bone grafts.METHODS:12 mongrel were divided into 4 groups randomly.Bone grafts were resected from iliac crest and then transplanted to the other side.Animals were skilled in different time after surgery,X-ray pictures were taken,then histological observation were done.RESULTS:At 3rd week,bone grafts dissolved,resorbed or necrosis partly;At 6th week,new bone began to regenerated;At 9th week,the amount of new bone increased;At 12nd week,bone interface around implant formed,without soft tissue interrupt.CONCLUSION:Osseointegration can formed between non-vascularized iliac bone grafts and titanium implant.

Extended finite element-based cohesive zone method for modeling simultaneous hydraulic fracture height growth in layered reservoirs

In this study,a fully coupled hydromechanical model within the extended finite element method(XFEM)-based cohesive zone method(CZM)is employed to investigate the simultaneous height growth behavior of multi-cluster hydraulic fractures in layered porous reservoirs with modulus contrast.The coupled hydromechanical model is first verified against an analytical solution and a laboratory experiment.Then,the fracture geometry(e.g.height,aperture,and area)and fluid pressure evolutions of multiple hydraulic fractures placed in a porous reservoir interbedded with alternating stiff and soft layers are investigated using the model.The stress and pore pressure distributions within the layered reservoir during fluid injection are also presented.The simulation results reveal that stress umbrellas are easily to form among multiple hydraulic fractures’tips when propagating in soft layers,which impedes the simultaneous height growth.It is also observed that the impediment effect of soft layer is much more significant in the fractures suppressed by the preferential growth of adjoining fractures.After that,the combined effect of in situ stress ratio and fracturing spacing on the multi-fracture height growth is presented,and the results elucidate the influence of in situ stress ratio on the height growth behavior depending on the fracture spacing.Finally,it is found that the inclusion of soft layers changes the aperture distribution of outmost and interior hydraulic fractures.The results obtained from this study may provide some insights on the understanding of hydraulic fracture height containment observed in filed.

Hybrid Approach for Cost Efficient Application Placement in Fog-Cloud Computing Environments

Fog computing has recently developed as a new paradigm with the aim of addressing time-sensitive applications better than with cloud computing by placing and processing tasks in close proximity to the data sources.However,the majority of the fog nodes in this environment are geographically scattered with resources that are limited in terms of capabilities compared to cloud nodes,thus making the application placement problem more complex than that in cloud computing.An approach for cost-efficient application placement in fog-cloud computing environments that combines the benefits of both fog and cloud computing to optimize the placement of applications and services while minimizing costs.This approach is particularly relevant in scenarios where latency,resource constraints,and cost considerations are crucial factors for the deployment of applications.In this study,we propose a hybrid approach that combines a genetic algorithm(GA)with the Flamingo Search Algorithm(FSA)to place application modules while minimizing cost.We consider four cost-types for application deployment:Computation,communication,energy consumption,and violations.The proposed hybrid approach is called GA-FSA and is designed to place the application modules considering the deadline of the application and deploy them appropriately to fog or cloud nodes to curtail the overall cost of the system.An extensive simulation is conducted to assess the performance of the proposed approach compared to other state-of-the-art approaches.The results demonstrate that GA-FSA approach is superior to the other approaches with respect to task guarantee ratio(TGR)and total cost.

An approximate analytical model for unconventional reservoir considering variable matrix blocks and simultaneous matrix depletion

In regard to unconventional oil reservoirs,the transient dual-porosity and triple-porosity models have been adopted to describe the fluid flow in the complex fracture network.It has been proven to cause inaccurate production evaluations because of the absence of matrix-macrofracture communication.In addition,most of the existing models are solved analytically based on Laplace transform and numerical inversion.Hence,an approximate analytical solution is derived directly in real-time space considering variable matrix blocks and simultaneous matrix depletion.To simplify the derivation,the simultaneous matrix depletion is divided into two parts:one part feeding the macrofractures and the other part feeding the microfractures.Then,a series of partial differential equations(PDEs)describing the transient flow and boundary conditions are constructed and solved analytically by integration.Finally,a relationship between oil rate and production time in real-time space is obtained.The new model is verified against classical analytical models.When the microfracture system and matrix-macrofracture communication is neglected,the result of the new model agrees with those obtained with the dual-porosity and triple-porosity model,respectively.Certainly,the new model also has an excellent agreement with the numerical model.The model is then applied to two actual tight oil wells completed in western Canada sedimentary basin.After identifying the flow regime,the solution suitably matches the field production data,and the model parameters are determined.Through these output parameters,we can accurately forecast the production and even estimate the petrophysical properties.

Effective Controller Placement in Software-Defined Internet-of-Things Leveraging Deep Q-Learning (DQL)

The controller is a main component in the Software-Defined Networking(SDN)framework,which plays a significant role in enabling programmability and orchestration for 5G and next-generation networks.In SDN,frequent communication occurs between network switches and the controller,which manages and directs traffic flows.If the controller is not strategically placed within the network,this communication can experience increased delays,negatively affecting network performance.Specifically,an improperly placed controller can lead to higher end-to-end(E2E)delay,as switches must traverse more hops or encounter greater propagation delays when communicating with the controller.This paper introduces a novel approach using Deep Q-Learning(DQL)to dynamically place controllers in Software-Defined Internet of Things(SD-IoT)environments,with the goal of minimizing E2E delay between switches and controllers.E2E delay,a crucial metric for network performance,is influenced by two key factors:hop count,which measures the number of network nodes data must traverse,and propagation delay,which accounts for the physical distance between nodes.Our approach models the controller placement problem as a Markov Decision Process(MDP).In this model,the network configuration at any given time is represented as a“state,”while“actions”correspond to potential decisions regarding the placement of controllers or the reassignment of switches to controllers.Using a Deep Q-Network(DQN)to approximate the Q-function,the system learns the optimal controller placement by maximizing the cumulative reward,which is defined as the negative of the E2E delay.Essentially,the lower the delay,the higher the reward the system receives,enabling it to continuously improve its controller placement strategy.The experimental results show that our DQL-based method significantly reduces E2E delay when compared to traditional benchmark placement strategies.By dynamically learning from the network’s real-time conditions,the proposed method ensures that controller placement remains efficient and responsive,reducing communication delays and enhancing overall network performance.

Layered Coded Cache Placement and Cooperative Delivery with Sharing Links in Satellite-Terrestrial Integrated Networks

Cooperative utilization of multidimensional resources including cache, power and spectrum in satellite-terrestrial integrated networks(STINs) can provide a feasible approach for massive streaming media content delivery over the seamless global coverage area. However, the on-board supportable resources of a single satellite are extremely limited and lack of interaction with others. In this paper, we design a network model with two-layered cache deployment, i.e., satellite layer and ground base station layer, and two types of sharing links, i.e., terrestrial-satellite sharing(TSS) links and inter-satellite sharing(ISS) links, to enhance the capability of cooperative delivery over STINs. Thus, we use rateless codes for the content divided-packet transmission, and derive the total energy efficiency(EE) in the whole transmission procedure, which is defined as the ratio of traffic offloading and energy consumption. We formulate two optimization problems about maximizing EE in different sharing scenarios(only TSS and TSS-ISS),and propose two optimized algorithms to obtain the optimal content placement matrixes, respectively.Simulation results demonstrate that, enabling sharing links with optimized cache placement have more than 2 times improvement of EE performance than other traditional placement schemes. Particularly, TSS-ISS schemes have the higher EE performance than only TSS schemes under the conditions of enough number of satellites and smaller inter-satellite distances.

Analysis and Verification on Buckling Mechanism of Spatial Tow Steering in Automated Fiber Placement

Automated fiber placement(AFP)enables the efficient and precise fabrication of complex-shaped aerospace composite structures with lightweight and high-performance properties.However,due to the excessive compression on the inner edge of the tow placed along the curved trajectory,the resulting defects represented by buckling and wrinkles in spatial tow steering can induce poor manufacturing accuracy and quality degradation of products.In this paper,a theoretical model of tow buckling based on the first-order shear deformation laminate theory,linear elastic adhesion interface and Hertz compaction contact theory is proposed to analyze the formation mechanism of the wrinkles and predict the formation of defects by solving the critical radius of the trajectory,and finite element analysis involving the cohesive zone modeling(CZM)is innovated to simulate the local buckling state of the steered tow in AFP.Additionally,numerical parametric studies and experimental results indicate that mechanical properties and geometric parameters of the prepreg,the curvature of the placement trajectory and critical process parameters have a significant impact on buckling formation,and optimization of process parameters can achieve effective suppression of placement defects.This research proposes a theoretical modeling method for tow buckling,and conducts in-depth research on defect formation and suppression methods based on finite element simulation and placement experiments.

Efficient placement technology of proppants based on structural stabilizers

Fiber is highly escapable in conventional slickwater,making it difficult to form fiber-proppant agglomerate with proppant and exhibit limited effectiveness.To solve these problems,a novel structure stabilizer(SS)is developed.Through microscopic structural observations and performance evaluations in indoor experiments,the mechanism of proppant placement under the action of the SS and the effects of the SS on proppant placement dimensions and fracture conductivity were elucidated.The SS facilitates the formation of robust fiber-proppant agglomerates by polymer,fiber,and quartz sand.Compared to bare proppants,these agglomerates exhibit reduced density,increased volume,and enlarged contact area with the fluid during settlement,leading to heightened buoyancy and drag forces,ultimately resulting in slower settling velocities and enhanced transportability into deeper regions of the fracture.Co-injecting the fiber and the SS alongside the proppant into the reservoir effectively reduces the fiber escape rate,increases the proppant volume in the slickwater,and boosts the proppant placement height,conveyance distance and fracture conductivity,while also decreasing the proppant backflow.Experimental results indicate an optimal SS mass fraction of 0.3%.The application of this SS in over 80 wells targeting tight gas,shale oil,and shale gas reservoirs has substantiated its strong adaptability and general suitability for meeting the production enhancement,cost reduction,and sand control requirements of such wells.

Efficient Digital Twin Placement for Blockchain-Empowered Wireless Computing Power Network

As an open network architecture,Wireless Computing PowerNetworks(WCPN)pose newchallenges for achieving efficient and secure resource management in networks,because of issues such as insecure communication channels and untrusted device terminals.Blockchain,as a shared,immutable distributed ledger,provides a secure resource management solution for WCPN.However,integrating blockchain into WCPN faces challenges like device heterogeneity,monitoring communication states,and dynamic network nature.Whereas Digital Twins(DT)can accurately maintain digital models of physical entities through real-time data updates and self-learning,enabling continuous optimization of WCPN,improving synchronization performance,ensuring real-time accuracy,and supporting smooth operation of WCPN services.In this paper,we propose a DT for blockchain-empowered WCPN architecture that guarantees real-time data transmission between physical entities and digital models.We adopt an enumeration-based optimal placement algorithm(EOPA)and an improved simulated annealing-based near-optimal placement algorithm(ISAPA)to achieve minimum average DT synchronization latency under the constraint of DT error.Numerical results show that the proposed solution in this paper outperforms benchmarks in terms of average synchronization latency.

AI-Driven Resource and Communication-Aware Virtual Machine Placement Using Multi-Objective Swarm Optimization for Enhanced Efficiency in Cloud-Based Smart Manufacturing

Cloud computing has emerged as a vital platform for processing resource-intensive workloads in smart manu-facturing environments,enabling scalable and flexible access to remote data centers over the internet.In these environments,Virtual Machines(VMs)are employed to manage workloads,with their optimal placement on Physical Machines(PMs)being crucial for maximizing resource utilization.However,achieving high resource utilization in cloud data centers remains a challenge due to multiple conflicting objectives,particularly in scenarios involving inter-VM communication dependencies,which are common in smart manufacturing applications.This manuscript presents an AI-driven approach utilizing a modified Multi-Objective Particle Swarm Optimization(MOPSO)algorithm,enhanced with improved mutation and crossover operators,to efficiently place VMs.This approach aims to minimize the impact on networking devices during inter-VM communication while enhancing resource utilization.The proposed algorithm is benchmarked against other multi-objective algorithms,such as Multi-Objective Evolutionary Algorithm with Decomposition(MOEA/D),demonstrating its superiority in optimizing resource allocation in cloud-based environments for smart manufacturing.

Right ventricular diverticulum following a pulmonary valve placement for correction of tetralogy of Fallot:A case report

BACKGROUND Ventricular diverticula are a rare congenital cardiac disorder presenting with an extremely low incidence.The presence of an apical diverticulum of the right ventricle has been associated with other congenital heart diseases such as tetralogy of Fallot.An important defining characteristic of ventricular diverticula that separates them from aneurysms through imaging techniques,is that they possess myocardial contraction synchronous to the adjacent walls,contributing to the ventricular stroke volume,so they do not usually require surgical treatment.CASE SUMMARY A 15-year-old male,currently asymptomatic,in follow up due to a pulmonary valve prosthesis placement and a history of corrected tetralogy of Fallot at 18 months old,underwent a cardiac magnetic resonance imaging in February 2024.A diverticulum was detected in the apical inferolateral wall of the right ventricle,which was not documented in the cardiac magnetic resonance imaging prior to valve prosthesis placement.CONCLUSION Right ventricular diverticula are a rare entity.To this date we could not find another case of a pulmonary valve placement,followed by a right ventricular diverticulum appearance.

Simultaneous Identification of Thermophysical Properties of Semitransparent Media Using a Hybrid Model Based on Artificial Neural Network and Evolutionary Algorithm

A hybrid identification model based on multilayer artificial neural networks(ANNs) and particle swarm optimization(PSO) algorithm is developed to improve the simultaneous identification efficiency of thermal conductivity and effective absorption coefficient of semitransparent materials.For the direct model,the spherical harmonic method and the finite volume method are used to solve the coupled conduction-radiation heat transfer problem in an absorbing,emitting,and non-scattering 2D axisymmetric gray medium in the background of laser flash method.For the identification part,firstly,the temperature field and the incident radiation field in different positions are chosen as observables.Then,a traditional identification model based on PSO algorithm is established.Finally,multilayer ANNs are built to fit and replace the direct model in the traditional identification model to speed up the identification process.The results show that compared with the traditional identification model,the time cost of the hybrid identification model is reduced by about 1 000 times.Besides,the hybrid identification model remains a high level of accuracy even with measurement errors.

Sci-tech Simultaneous Interpreter Education Based on Translation Universals Research

The rapid evolution of scientific and technological advancements and industrial changes has profoundly interconnected countries and regions in the digital information era,creating a globalized environment where effective communication is paramount.Consequently,the demand for proficient interpreting skills within the scientific and technology sectors has surged,making effective language communication increasingly crucial.This paper explores the potential impact of translation universals on enhancing sci-tech simultaneous interpreter education.By examining the selection of teaching materials,methods,and activities through the lens of translation universals,this study aims to improve the quality of teaching content,innovate instructional approaches,and ultimately,enhance the effectiveness of interpreter education.The findings of this research are expected to provide valuable insights for curriculum development and pedagogical strategies in interpreter education.

Simultaneous Waveform Inverse Modelling for Litho-Fluid Prediction in an Old Marginal, “Agbbo”Field, Onshore Niger Delta, Nigeria

Simultaneous waveform inversion was used to predict lithofacies and fluid type across the field. Very often, characterizing reservoirs in terms of lithology and fluid type using conventional methods is replete with uncertainties, especially in marginal fields. An approach is employed in this study that integrated rock physics and waveform inverse modelling for lithology and fluid-type characterization to appropriately identify potential hydrocarbon saturated zones and their corresponding lithology. Seismic and well-log data were analyzed using Hampson Russel software. The method adopted includes lithofacies and fluid content analysis using rock physics parameters and seismic simultaneous inverse modelling. Rock physics analysis identified 2 broad reservoirs namely: HDZ1 and HDZ2 reservoirs. Results from the inverse modelling showed that low values of acoustic impedance from 19,743 to 20,487 (ft/s)(g/cc) reflect hydrocarbon-bearing reservoirs while medium to high values shows brine and shale respectively, with brine zone ranging from 20,487 to 22,531 (ft/s)(g/cc) and shale above 22,531 (ft/s)(g/cc). Two lithofacies were identified from inversion analysis of Vp/Vs and Mu-Rho, namely: sand and shale with VpVs 1.95 values respectively. Mu-Rho > 12.29 (GPa)(g/cc) and <12.29 (GPa) (g/cc) represent sand and shale respectively. From 3D volume, it was observed that a high accumulation of hydrocarbon was observed to be saturated at the north to the eastern part of the field forming a meandering channel. Sands were mainly distributed around the northeastern to the southwestern part of the field, that tends to be away from Well 029. This was also validated by the volume of rigidity modulus (Mu-Rho) showing high values indicating sands fall within the northeastern part of the field.

Analysis of the Application Effect of Tracheal Stent Placement in the Nutritional Support Treatment of Tracheoesophageal Fistula

Objective:To evaluate and analyze the application effect of tracheal stent placement in nutritional support therapy for tracheoesophageal fistula.Methods:Clinical data of 32 patients who underwent nutritional support therapy for tracheoesophageal fistula in our hospital from September 2021 to September 2022 were collected,and all patients underwent tracheal silicone stenting,comparing dyspnea classification and Karnofsky score before and after stenting,and conducting post-treatment follow-up.Results:In 32 patients with tracheoesophageal fistula,dyspnea grading improved from grades III and IV to grades 0 to II.Before treatment,10 patients(31.06%)were in grade IV,17 patients(53.12%)were in grade III,and five patients(15.62)were in grade II;after treatment,13 patients(40.63%)were in grade I,12 patients(37.50%)were in grade I,and seven patients(21.87%)were in grade 0(P<0.05);Karnofsky score(37.52±4.86 before treatment)improved significantly to 71.39±8.24 one week after treatment(P<0.05).Nine patients with tracheoesophageal fistula were placed with silicone Y14-10-10 stent,11 with silicone 18-14-14 stent,three with silicone Y15-12-12,and seven with silicone stent 16-13-13.Conclusion:Silicone tracheobronchial stent placement for the treatment of tracheoesophageal fistula is technically feasible,simple,and safe,with reliable near-term efficacy,and is worthy of popularization and application.

Clinical Study on Improving Articulation Clarity in Spastic Cerebral Palsy with 120 Cases of Oral-Facial Acupressure Combined with Oral Placement Therapy

Objective:To observe the efficacy of oral-facial acupressure combined with oral placement therapy(OPT)in improving articulation clarity in 120 children with spastic cerebral palsy,and to explore effective therapeutic solutions for speech disorders associated with spastic cerebral palsy.Methods:A total of 120 children with spastic cerebral palsy and speech disorders,meeting the inclusion criteria,were randomly assigned into two groups:60 cases in the treatment group and 60 cases in the control group.The treatment group received orofacial acupressure combined with OPT,while the control group received only OPT.The Oral Motor Function Assessment Scale(OMFAS),developed by the China Rehabilitation Research Centre(CRRC),was used to evaluate the treatment outcomes before and after the intervention.Results:After the treatment,both the treatment and control groups showed improved mobility of the mandible,lips,and tongue.However,the treatment group exhibited significantly better improvement than the control group,with the difference between the two groups being statistically significant(P<0.05).Conclusion:Oral-facial acupressure combined with OPT can effectively improve articulation clarity in children with spastic cerebral palsy.This combined therapy is recommended for clinical promotion and application.

Simultaneous inversion of petrophysical parameters based on geostatistical a priori information

The high-resolution nonlinear simultaneous inversion of petrophysical parameters is based on Bayesian statistics and combines petrophysics with geostatistical a priori information. We used the fast Fourier transform–moving average（FFT–MA） and gradual deformation method（GDM） to obtain a reasonable variogram by using structural analysis and geostatistical a priori information of petrophysical parameters. Subsequently, we constructed the likelihood function according to the statistical petrophysical model. Finally, we used the Metropolis algorithm to sample the posteriori probability density and complete the inversion of the petrophysical parameters. We used the proposed method to process data from an oil fi eld in China and found good match between inversion and real data with high-resolution. In addition, the direct inversion of petrophysical parameters avoids the error accumulation and decreases the uncertainty, and increases the computational effi ciency.

Placement distance of freeway exit advance guide sign and its safety impacts

To remedy the empirical pitfalls of current chinese specifications and MUTCD 2009 guidelines in determining the placement distance of freeway exit advance guide signs,the driving maneuver of exiting traffic is analyzed and the factors influencing placement distance are explored.Variables including the number of lanes,lane width,lane-changing time,driver＇s visual characteristics,sign installation methods and operating speeds on both freeway mainlines and exit ramps are found significant in explaining exit safety.Three different installation methods,namely ground installation,overhead installation and median installation,are introduced and their applicable conditions are given.Models,with the same structure among the three installation methods,are developed to compute the placement distance under different roadway geometric and traffic conditions.Taking overhead installation as an example,simulation results in TSIS-CORSIM show that the proposed distance reduces the number of lane changes in the area from the ramp nose to 500 m upstream by 58.93% compared with current Chinese specifications and 27.35% compared with MUTCD 2009 guidelines.Thus,the distances recommended in this paper have a better safety performance.

Fame:A Fast Detailed Placement Algorithm for Standard\| Cell Layout Based on Mixed Mincut and Enumeration

Rapid progress in manufacturing greatly challenges to the VLSI physical design in both speed and performance. A fast detailed placement algorithm, FAME is presented in this paper, according to these demands. It inherits the optimal positions of cells given by a global placer and exact position to each cell by local optimization. FM Mincut heuristic and local enumeration are used to optimize the total wirelength in y and x directions respectively, and a two way mixed optimizing flow is adopted to combine the two methods for a better performance. Furthermore, a better enumeration strategy is introduced to speed up the algorithm. An extension dealing with blockages in placement has also been discussed. Experimental results show that FAME runs 4 times faster than RITUAL and achieves a 5% short in total wirelength on average.