Effect of Penetration Rates on the Piezocone Penetration Test in the Yellow River Delta Silt

Partial drainage often occurs during piezocone penetration testing on Yellow River Delta silt because of its intermediate physical and mechanical properties between those of sand and clay.Yet,there is no accurate understanding for the range of penetra-tion rates to trigger the partial drainage of silt soils.In order to fully investigate cone penetration rate effects under partial drainage condi-tions,indoor 1 g penetration model tests and numerical simulations of cavity expansion at variable penetration rates were carried out on the Yellow River Delta silt.The boundary effect of the model tests and the variation of key parameters at the different cavity ex-pansion rates were analyzed.The 1 g penetration model test results and numerical simulations results consistently indicated that the penetration rate to trigger the partially drainage of typical silt varied at least three orders of magnitude.The numerical simulations also provide the reference values for the penetration resistance corresponding to zero dilation and zero viscosity at any given normalized penetration rate for silt in Yellow River Delta.These geotechnical properties can be used for the design of offshore platforms in Yel-low River Delta,and the understanding of cone penetration rate effects under the partially drained conditions would provide some technical support for geohazard evaluation of offshore platforms.

Interpretation and characterization of rate of penetration intelligent prediction model

Accurate prediction of the rate of penetration(ROP)is significant for drilling optimization.While the intelligent ROP prediction model based on fully connected neural networks(FNN)outperforms traditional ROP equations and machine learning algorithms,its lack of interpretability undermines its credibility.This study proposes a novel interpretation and characterization method for the FNN ROP prediction model using the Rectified Linear Unit(ReLU)activation function.By leveraging the derivative of the ReLU function,the FNN function calculation process is transformed into vector operations.The FNN model is linearly characterized through further simplification,enabling its interpretation and analysis.The proposed method is applied in ROP prediction scenarios using drilling data from three vertical wells in the Tarim Oilfield.The results demonstrate that the FNN ROP prediction model with ReLU as the activation function performs exceptionally well.The relative activation frequency curve of hidden layer neurons aids in analyzing the overfitting of the FNN ROP model and determining drilling data similarity.In the well sections with similar drilling data,averaging the weight parameters enables linear characterization of the FNN ROP prediction model,leading to the establishment of a corresponding linear representation equation.Furthermore,the quantitative analysis of each feature's influence on ROP facilitates the proposal of drilling parameter optimization schemes for the current well section.The established linear characterization equation exhibits high precision,strong stability,and adaptability through the application and validation across multiple well sections.

Enhancing Accumulation and Penetration Efficiency of Next-Generation Antibiotics to Mitigate Antibiotic Resistance in Pseudomonas aeruginosa PAO1

This study explores the efficacy of advanced antibiotic compounds against P. aeruginosa, focusing on Antibiotic B, an enhanced derivative of Ceftriaxone. The study measured the intracellular uptake of Antibiotic B and introduced a novel adjuvant, Influximax, which augmented its antibacterial activity. Results showed a diminished potential for resistance emergence with Antibiotic B, particularly when used in combination with Influximax. The study suggests that optimizing antibiotic delivery into bacterial cells and leveraging syner-gistic adjuvant combinations can enhance drug resistance combat. .

Investigating the effects of gradual deployment of market penetration rates(MPR)of connected vehicles on delay time and fuel consumption

Purpose–This research paper aims to investigate the effects of gradual deployment of market penetration rates(MPR)of connected vehicles(MPR of CVs)on delay time and fuel consumption.Design/methodology/approach–A real-world origin-destination demand matrix survey was conducted in Boston,MA to identify the number of peak hour passing vehicles in the case study.Findings–The results showed that as the number of CVs(MPR)in the network increases,the total delay time decreases by an average of 14%and the fuel consumption decreases by an average of 56%,respectively,from scenarios 3 to 15 compared to scenario 2.Research limitations/implications–The first limitation of this study was considering a small network.The considered network shows a small part of the case study.Originality/value–This study can be a milestone for future research regarding gradual deployment of CVs’effects on transport networks.Efficient policy(s)may define based on the results of this network for Brockton transport network.

Effects of data smoothing and recurrent neural network(RNN)algorithms for real-time forecasting of tunnel boring machine(TBM)performance

Tunnel boring machines(TBMs)have been widely utilised in tunnel construction due to their high efficiency and reliability.Accurately predicting TBM performance can improve project time management,cost control,and risk management.This study aims to use deep learning to develop real-time models for predicting the penetration rate(PR).The models are built using data from the Changsha metro project,and their performances are evaluated using unseen data from the Zhengzhou Metro project.In one-step forecast,the predicted penetration rate follows the trend of the measured penetration rate in both training and testing.The autoregressive integrated moving average(ARIMA)model is compared with the recurrent neural network(RNN)model.The results show that univariate models,which only consider historical penetration rate itself,perform better than multivariate models that take into account multiple geological and operational parameters(GEO and OP).Next,an RNN variant combining time series of penetration rate with the last-step geological and operational parameters is developed,and it performs better than other models.A sensitivity analysis shows that the penetration rate is the most important parameter,while other parameters have a smaller impact on time series forecasting.It is also found that smoothed data are easier to predict with high accuracy.Nevertheless,over-simplified data can lose real characteristics in time series.In conclusion,the RNN variant can accurately predict the next-step penetration rate,and data smoothing is crucial in time series forecasting.This study provides practical guidance for TBM performance forecasting in practical engineering.

Predicting TBM penetration rate in hard rock condition:A comparative study among six XGB-based metaheuristic techniques

A reliable and accurate prediction of the tunnel boring machine(TBM)performance can assist in minimizing the relevant risks of high capital costs and in scheduling tunneling projects.This research aims to develop six hybrid models of extreme gradient boosting(XGB)which are optimized by gray wolf optimization(GWO),particle swarm optimization(PSO),social spider optimization(SSO),sine cosine algorithm(SCA),multi verse optimization(MVO)and moth flame optimization(MFO),for estimation of the TBM penetration rate(PR).To do this,a comprehensive database with 1286 data samples was established where seven parameters including the rock quality designation,the rock mass rating,Brazilian tensile strength(BTS),rock mass weathering,the uniaxial compressive strength(UCS),revolution per minute and trust force per cutter(TFC),were set as inputs and TBM PR was selected as model output.Together with the mentioned six hybrid models,four single models i.e.,artificial neural network,random forest regression,XGB and support vector regression were also built to estimate TBM PR for comparison purposes.These models were designed conducting several parametric studies on their most important parameters and then,their performance capacities were assessed through the use of root mean square error,coefficient of determination,mean absolute percentage error,and a10-index.Results of this study confirmed that the best predictive model of PR goes to the PSO-XGB technique with system error of(0.1453,and 0.1325),R^(2) of(0.951,and 0.951),mean absolute percentage error(4.0689,and 3.8115),and a10-index of(0.9348,and 0.9496)in training and testing phases,respectively.The developed hybrid PSO-XGB can be introduced as an accurate,powerful and applicable technique in the field of TBM performance prediction.By conducting sensitivity analysis,it was found that UCS,BTS and TFC have the deepest impacts on the TBM PR.

Hard rock tunnel boring machine penetration test as an indicator of chipping process efficiency

The transition from grinding to chipping can be observed in tunnel boring machine(TBM) penetration test data by plotting the penetration rate(distance/revolution) against the net cutter thrust(force per cutter) over the full range of penetration rates in the test.Correlating penetration test data to the geological and geomechanical characteristics of rock masses through which a penetration test is conducted provides the ability to reveal the efficiency of the chipping process in response to changing geological conditions.Penetration test data can also be used to identify stress-induced tunnel face instability.This research shows that the strength of the rock is an important parameter for controlling how much net cutter thrust is required to transition from grinding to chipping.It also shows that the geological characteristics of a rock will determine how efficient chipping occurs once it has begun.In particular,geological characteristics that lead to efficient fracture propagation,such as fabric and mica contents,will lead to efficient chipping.These findings will enable a better correlation between TBM performance and geological conditions for use in TBM design,as a basis for contractual payments where penetration rate dominates the excavation cycle and in further academic investigations into the TBM excavation process.

Relationship between Formation Water Rate,Equivalent Penetration Rate and Volume Flow Rate of Air in Air Drilling

Formation water invasion is the most troublesome problem associated with air drilling. However, it is not economical to apply mist drilling when only a small amount of water flows into wellbore from formation during air drilling. Formation water could be circulated out of the wellbore through increasing the gas injection rate. In this paper, the Angel model was modified by introducing Nikurade friction factor for the flow in coarse open holes and translating formation water rate into equivalent penetration rate. Thus the distribution of annular pressure and the relationship between minimum air injection rate and formation water rate were obtained. Real data verification indicated that the modified model is more accurate than the Angel model and can provide useful information for air drilling.

Drillability prediction in some metamorphic rocks using composite penetration rate index(CPRI)–An approach

Assessment of drillability of rocks is vital in the selection,operation,and performance evaluation of cutting tools used in various excavation machinery deployed in mining and tunneling.The commonly used rock drillability prediction methods,namely,drilling rate index(DRI)and Cerchar hardness index(CHI)have limitations in predicting the penetration rate due to differential wear of the cutting tool in rocks with varied hardness and abrasivity.Since cutting tools get blunt differently in different rocks,the stress beneath the tip of the bit decreases until it reaches a threshold value beyond which the penetration rate becomes constant.In this research,a new composite penetration rate index(CPRI)is suggested based on the investigations on four metamorphic rocks viz.quartzite,gneiss,schist and phyllite with varied hardness-abrasivity values.The penetration-time behavior was classified into active,moderate,passive,and dormant phases based on the reduction in penetration rate at different stages of drilling.A comparison of predicted penetration rate values using DRI and CPRI with actual penetration rate values clearly establishes the supremacy of CPRI.Micro-structure and hardness-based index was also developed and correlated with CPRI.The new indices can help predict cutting tool penetration and its consumption more accurately.

Hybrid ensemble soft computing approach for predicting penetration rate of tunnel boring machine in a rock environment

This study implements a hybrid ensemble machine learning method for forecasting the rate of penetration(ROP) of tunnel boring machine(TBM),which is becoming a prerequisite for reliable cost assessment and project scheduling in tunnelling and underground projects in a rock environment.For this purpose,a sum of 185 datasets was collected from the literature and used to predict the ROP of TBM.Initially,the main dataset was utilised to construct and validate four conventional soft computing(CSC)models,i.e.minimax probability machine regression,relevance vector machine,extreme learning machine,and functional network.Consequently,the estimated outputs of CSC models were united and trained using an artificial neural network(ANN) to construct a hybrid ensemble model(HENSM).The outcomes of the proposed HENSM are superior to other CSC models employed in this study.Based on the experimental results(training RMSE=0.0283 and testing RMSE=0.0418),the newly proposed HENSM is potential to assist engineers in predicting ROP of TBM in the design phase of tunnelling and underground projects.

PENETRATION RATE MEASUREMENT AND ITS INSTRUMENT DESIGN

The practical method for precise penetration rate measurement in a short time and the instrument design have been specially discussed in this paper.Considering the defects of the penetration rate meters available,via the balanced design in consideration of service life,costs,accuracy and reliability,a kind of penetration rate meter has been put forward.The meter consists of a magnetic clutch,a gear box and a raster disk system to pick up the signal.The meter has the following advantages-it might measure a low speed with higher accura-cy,it could disengage automatically without being divorced from the driving device during tripping rods at high speed,it has a circuit of rotary direction discrimination and of repeated counting prevention so as to eU-minate error caused by rod vibration.

Observation on Sperm Penetration Rate of Infertile Men with Varicocele at 1.5 to 2 Years after Varicolectomy

Objective To observe the sperm penetration rate among treated but 'unsuccessful' infertile men with varicocele Material & Methods Twenty nine infertile males with II°(n=17) or III°(n=12) varicocele were enrolled into this study. They underwent a varicolectomy, but their spouses had not achieved a pregnancy after 1.5~2 years of treatment. The sperm zona-free hamster oocyte penetration assay (SPA) was used to compare the sperm penetration rate (PR) before treatment and 1.5~2 years after treatment. Results After varicolectomy, enhanced PR were observed in 7 cases of the II°group and in 1 case of the III°group. However, the PR values of these 8 cases were still below 20% PR-level. Conclusion Among the treated but 'unsuccessful' men, some patients could obtain improvements on PR after varicolectomy. But PRs of men with III°grade varicele would still remain a low PR-level which indicate varicolectomy is ineffective in increasing PR among part of sever varicocele patients. SPA is a useful test for evaluating the fertilizing potential of treated infertile males with varicocele.

Discussion of reasonable drilling parameters in impregnated diamond bit drilling

The impregnated diamond(ID)bit drilling is one of the main rotary drilling methods in hard rock drilling and it is widely used in mineral exploration,oil and gas exploration,mining,and construction industries.In this study,the quadratic polynomial model in ID bit drilling process was proposed as a function of controllable mechanical operating parameters,such as weight on bit(WOB)and revolutions per minute(RPM).Also,artificial neural networks(ANN)model for predicting the rate of penetration(ROP)was developed using datasets acquired during the drilling operation.The relationships among mechanical operating parameters(WOB and RPM)and ROP in ID bit drilling were analyzed using estimated quadratic polynomial model and trained ANN model.The results show that ROP has an exponential relationship with WOB,whereas ROP has linear relationship with RPM.Finally,the optimal regime of mechanical drilling parameters to achieve high ROP was confirmed using proposed model in combination with rock breaking principal.

Multi-objective optimization of oil well drilling using elitist non-dominated sorting genetic algorithm

A multi-objective optimization of oil well drilling has been carried out using a binary coded elitist non-dominated sorting genetic algorithm.A Louisiana offshore field with abnormal formation pressure is considered for optimization.Several multi-objective optimization problems involving twoand three-objective functions were formulated and solved to fix optimal drilling variables.The important objectives are：（i） maximizing drilling depth,（ii） minimizing drilling time and （iii） minimizing drilling cost with fractional drill bit tooth wear as a constraint.Important time dependent decision variables are：（i） equivalent circulation mud density,（ii） drill bit rotation,（iii） weight on bit and （iv） Reynolds number function of circulating mud through drill bit nozzles.A set of non-dominated optimal Pareto frontier is obtained for the two-objective optimization problem whereas a non-dominated optimal Pareto surface is obtained for the three-objective optimization problem.Depending on the trade-offs involved,decision makers may select any point from the optimal Pareto frontier or optimal Pareto surface and hence corresponding values of the decision variables that may be selected for optimal drilling operation.For minimizing drilling time and drilling cost,the optimum values of the decision variables are needed to be kept at the higher values whereas the optimum values of decision variables are at the lower values for the maximization of drilling depth.

Experimental study of rock-breaking with an offset single cone bit

An experimental study of rock-breaking with an offset single cone bit was completed on the bit bench test equipment. Data such as transmission ratio, weight on bit （WOB）, rate of penetration （ROP） and torque on bit were acquired in the experiments. Based on analyzing the experimental results, several conclusions were drawn as follows. The transmission ratio of the offset single-cone bit changed slightly with rotary speed of bit, weight on bit and offset distance. The rate of penetration of the offset singlecone bit increased with increase of WOB and off＇set distance. The torque on bit increased with increase of offset distance under the same WOB and bit rotary speed, decreased with increase of bit rotary speed under the same WOB. The rock-breaking mechanism of the offset single-cone bit was a scraping action. This indicates that the offset single-cone bit is a chipping type bit.

Investigations into the coiled tubing partial underbalanced drilling (CT-PUBD)technique for drilling hard formations

To improve the rate of penetration(ROP) in drilling deep and hard formations, this paper proposes a new drilling method called coiled tubing partial underbalanced drilling(CT-PUBD). As a preliminary investigation into the new drilling method, this paper presents predictions of hole cleaning efficiency, drilling speed, cuttings migration and pressure loss in the drilling process with CT-PUBD. Based on numerical simulation and full-scale experimental studies, we conclude that using CT-PUBD, an underbalanced drilling condition can be achieved near the bit while maintaining wellbore safety at the same time. This condition can be achieved using a cuttings discharge device, a rotary packer and a backflow controller.According to the numerical simulations performed in this study, CT-PUBD can achieve high efficiency of hole cleaning.Along the cuttings migration process, the fluid velocities can reach the maximum values in the backflow holes. A full-scale laboratory experimental system was used to test the hydraulic characteristics and obtain the drilling performance of the new technology. The result shows that CT-PUBD significantly improves the ROP compared to the conventional drilling method.

Drilling cost optimization in a hydrocarbon field by combination of comparative and mathematical methods

In drilling operation, a large saving in time and money would be achieved by reducing the drilling time, since some of the costs are time-dependent. Drilling time could be minimized by raising the penetration rate. In the comparative optimization method, by using the records of the first drilled wells and comparing the criteria like penetration rate, cost per foot and specific energy, the drilling parameters of the next wells being drilled can be optimized in each depth interval. In the mathematical optimization technique, some numerical equations to model the penetration rate, bit wear rate and hydraulics would be used to minimize the drilling cost and time as much as possible and improve the results of the primary comparative optimization. In this research, as a case study the Iranian Khangiran gas field has been evaluated to optimize the drilling costs. A combination of the mentioned optimization techniques resulted in an optimal well which reduced the drilling time and cost considerably in comparison with the wells already drilled.

Heterogeneous traffic flow modeling with drivers’ timid and aggressive characteristics

The driver’s characteristics(e.g.,timid and aggressive)has been proven to greatly affect the traffic flow performance,whereas the underlying assumption in most of the existing studies is that all drivers are homogeneous.In the real traffic environment,the drivers are distinct due to a variety of factors such as personality characteristics.To better reflect the reality,we introduce the penetration rate to describe the degree of drivers’heterogeneity(i.e.,timid and aggressive),and proceed to propose a generalized heterogeneous car-following model with different driver’s characteristics.Through the linear stability analysis,the stability conditions of the proposed heterogeneous traffic flow model are obtained based on the perturbation method.The impacts of the penetration rate of drivers with low intensity,the average value and standard deviation of intensity parameters characterizing two types of drivers on the stability of traffic flow are analyzed by simulation.Results show that higher penetration of aggressive drivers contributes to traffic flow stability.The average value has a great impact on the stability of traffic flow,whereas the impact of the standard deviation is trivial.

Evaluation of boring machine performance with special reference to geomechanical characteristics

The duration of tunneling projects mostly depends on the performance of boring machines. The performance of boring machines is a function of advance rate, which depends on the machine characterizations and geomechanical properties of rock mass. There were various theoretical and empirical models for estimating the advance rate. In this paper, after determining the geomechanical properties of rock mass encountered in the Isfahan metro tunnel, the performance of the roadheader and tunnel boring machine （TBM） were then evaluated using various models. The calculation results show that the average instantaneous cutting rate of the roadheader in sandstone and shale are 42.8 and 74.5 m^3/h respectively. However the actual values in practice are 34.2 and 51.3 m^3/h. The operational cutting rate of the roadheader in sandstone and shale are 8.2 and 9.7 m^3/h respectively, but the actual values are 6.5 and 6.7 m^3/h. The penetration rate of the TBM in shale is predicted to be 50-60 mm/round.

Properties and testing of a hydraulic pulse jet and its application in offshore drilling

Offshore drilling has attracted more attention than ever before due to the increasing worldwide energy demand especially in China. High cost, long drilling cycles, and low rate of penetration （ROP） represent critical challenges for offshore drilling operations. The hydraulic pulse generator was specifically designed, based on China offshore drilling technologies and parameters, to overcome problems encountered during offshore drilling. Both laboratory and field tests were conducted to collect the characteristics of the hydraulic pulse generator. The relationships between flow rate and pressure amplitude, pressure loss and pulse frequency were obtained, which can be used to optimize operation parameters for hydraulic pulse jet drilling. Meanwhile a bottom hole assembly （BHA） for pulse jet drilling has been designed, combining the hydraulic pulse generator with the conventional BHA, positive displacement motor, and rotary steerable system （RSS） etc. Furthermore, the hydraulic pulse jet technique has been successfully applied in more than 10 offshore wells in China. The depth of the applied wells ranged from 2,000 m to 4,100 m with drilling bit diameters of 311 mm and 216 mm. The field application results showed that hydraulic pulse jet technique was feasible for various bit types and formations, and that ROP could be significantly increased, by more than 25%.