Influence Of Multiple Parameters Research Articles

Study on the aerodynamic characteristics and ventilation effects of ultra-high-speed elevator car-counterweight system under the influence of multiple parameters

When the ultra-high-speed elevator car-counterweight system runs opposite each other, significant piston effects are caused, seriously affecting the elevator operation's stability. In order to explore the aerodynamic characteristics of the whole operation process of a car-counterweight system under multi-parameters, this study first establishes a three-dimensional transient model of the car-counterweight system and a multi-region dynamic layering numerical simulation method based on this model is proposed. Then, the actual elevator experiment validates the correctness of the model and the method. Finally, the influence rules of key parameters on the car's aerodynamic characteristics and ventilation effect are analyzed, and the car's aerodynamic characteristics at intersection time are analyzed emphatically. The results show that with the increase in the blocking ratio, the pressure drag and viscous drag have similar change trends at each stage, but the influence of pressure drag is more significant. The air displacement ratio increases by 34.1%, 75.8%, and 117.3%, respectively. With the increase in the hoistway height, the air displacement ratio decreases by 0.9%, 2.4%, and 2.9%, respectively. The spacing significantly affects the car's aerodynamic characteristics at the intersection time. The drag peak increases by 6.8%, 13.6%, and 20.5% and the lift peak by 21.2%, 47.8%, and 82.5%, respectively.

Modeling and prediction of tribological properties of copper/aluminum-graphite self-lubricating composites using machine learning algorithms

The tribological properties of self-lubricating composites are influenced by many variables and complex mechanisms. Data-driven methods, including machine learning (ML) algorithms, can yield a better comprehensive understanding of complex problems under the influence of multiple parameters, typically for how tribological performances and material properties correlate. Correlation of friction coefficients and wear rates of copper/aluminum-graphite (Cu/Al-graphite) self-lubricating composites with their inherent material properties (composition, lubricant content, particle size, processing process, and interfacial bonding strength) and the variables related to the testing method (normal load, sliding speed, and sliding distance) were analyzed using traditional approaches, followed by modeling and prediction of tribological properties through five different ML algorithms, namely support vector machine (SVM), K-Nearest neighbor (KNN), random forest (RF), eXtreme gradient boosting (XGBoost), and least-squares boosting (LSBoost), based on the tribology experimental data. Results demonstrated that ML models could satisfactorily predict friction coefficient and wear rate from the material properties and testing method variables data. Herein, the LSBoost model based on the integrated learning algorithm presented the best prediction performance for friction coefficients and wear rates, with R2 of 0.9219 and 0.9243, respectively. Feature importance analysis also revealed that the content of graphite and the hardness of the matrix have the greatest influence on the friction coefficients, and the normal load, the content of graphite, and the hardness of the matrix influence the wear rates the most.

Research on quantitative inversion characterization of high-definition electrical imaging logging in oil-based mud based on backpropagation neural network and multiple population genetic algorithm-Levenberg-Marquardt algorithm

Electrical imaging logging in oil-based mud (OBM) has been developed for some time and is gradually playing an important role in the description of deep carbonate and shale reservoirs. Quantitative characterization of reservoir rock parameters such as resistivity is one of the most innovative developments in this field. The development of this technology needs to address and resolve four core issues: a wide range of parameter variations, removal of mud-cake influence in low-resistivity formations, dielectric rollover in high-resistivity formations, and multifrequency dielectric dispersion effects. To address the aforementioned issues, the joint use of a backpropagation neural network (BPNN) and the multiple population genetic algorithm (MPGA)-Levenberg-Marquardt (LM) algorithm for high-resolution quantitative imaging is developed. First, the numerical simulation is used to calculate the well-logging response data under the influence of multiple parameters, thereby establishing a forward response database. Then, within the forward response database, the instrument response function is fitted using BPNN, to compress the data volume. Next, based on the fitted response function, an inversion method for three parameters, including reservoir rock resistivity, permittivity, and plate standoff, is established using the LM algorithm optimized with MPGA. The results indicate that the use of a three-layer BPNN enables rapid and accurate calculation of the electrical imaging logging response in OBM. The calculation of a single point only requires 0.1 ms with an accuracy of more than 99%. The MPGA-LM algorithm exhibits stronger stability and improved inversion accuracy, with a single point inversion time of only 2 ms, and contributes to the high-definition quantitative description of electrical imaging logging in OBM, which is important in characterizing formation structures, distinguishing formation fractures, etc.

Coupled piezo-pyro-photocatalysis of oxygen vacancies and Bi quantum dots co-modified BaTiO3 for highly efficient removal of ciprofloxacin

Understanding the synergistic promotion of photocarrier separation by multiple parameters is crucial to developing superior photocatalysts in environmental remediation. In this study, we have engineered BaTiO3 photocatalyst by creating oxygen vacancies (OVs) and decorating Bi quantum dots (QDs) on its surface, and then elucidated its piezo-pyro-photocatalysis and mechanism for ciprofloxacin (CIP) elimination. The optimal OVs-/Bi QDs-engineered sample (labeled as 7 %Bi@BTO-325 °C) exhibits a photodegradation activity, under simulated-sunlight irradiation, that is improved by 3.8 times over that of pristine BTO. This phenomenon can be explained due to the improved visible-light absorption and photocarrier separation by OVs and Bi QDs. Moreover, when the simulated-sunlight illumination (photocatalysis) was companied with ultrasonic irradiation (piezocatalysis) and cold-hot alternation (pyrocatalysis), the coupling of piezo-pyro-photocatalysis shows a further improvement in the CIP removal with a synergistic enhancement factor SF = 1.77. The enhanced piezo-pyro-photocatalysis is ascribed to the fact that the piezoelectric/pyroelectric polarization field facilitates the separation of photocarriers (particularly the bulk photocarriers). Experiment and theory were combined to deeply study the catalysis mechanism. Moreover, the influence of multiple parameters on the CIP elimination was investigated and analyzed by machine learning to establish the best prediction model.

Damping performance and its influencing factors of wind turbine towers with constrained layer damping treatment

Constrained layer damping (CLD) is proposed as an energy dissipation measure for vibration control of offshore monopile wind turbine towers (OMWTT). The damping performance and influencing factors of OMWTT with CLD treatment are studied in this paper. First, a theory for calculating the first-order modal loss factor provided by CLD for composite structures is derived using the modal strain energy (MSE) method; second, the error of the theoretical formulation is analyzed using the finite element method; and finally, the influence of each parameter of the CLD on the first-order modal loss factor is discussed. The modal loss factor’s temperature dependence is described with the theory’s aid. The modal damping calculation theory proposed in this paper can rapidly determine the optimal design of CLD, considering the influence of multiple parameters and a complex environment, which could be helpful in the efficient vibration reduction of OMWTT.

Heat exchange mechanism analysis and structural parameter optimization for series-combined microchannel heat sinks

This study presents a heat exchange mechanism analysis and an optimization of structural parameters of a built-in series combined microchannel heat dissipation platform, aiming to address the problems of low heat exchange and high pumping power caused by the mismatch in the selection of the structural parameters of the microchannel heat sink (MHS). A numerical calculation model was built in Fluent, and the temperature difference, pressure difference, and their ratio between the inlet and outlet of the MHS were used as the evaluation indicators. Using an orthogonal test, the influence of multiple parameters on the heat exchange effect was investigated. It is found that the shape of the microchannel is the main factor affecting the heat exchange phenomena, and the optimal combination of parameters such as the height, width, and length of the rectangular microchannel is obtained by a genetic algorithm. Physical transformation and heat exchange experiments were carried out. It was highlighted that the comprehensive performance of the optimized cooling system has been improved to varying degrees under different inlet flow conditions. At an inlet flow rate of 2.0 m3 h−1, the pressure difference and pumping power consumption are reduced by 24.9%, and the maximum temperature difference and heat dissipation power are increased by 21.0%. An experimental study on the heat exchange effect of MHSs with different numbers of serial pieces was carried out. With a number of MHSs of 15, the heat exchange is found to be sufficient, and the maximum heat exchange estimated was 9289.52 W.

Nanomaterials as a Sustainable Choice for Treating Wastewater: A Review

The removal of dyes from textile effluents utilizing advanced wastewater treatment methods with high efficiency and low cost has received substantial attention due to the rise in pollutants in water. The purpose of this work is to give a comprehensive analysis of the different treatments for removing chemical dyes from textile effluents. The capability and potential of conventional treatments for the degradation of dyeing compounds in aqueous media, as well as the influence of multiple parameters, such as the pH solution, initial dye concentration, and adsorbent dose, are presented in this study. This study is an overview of the scientific research literature on this topic, including nanoreductive and nanophotocatalyst processes, as well as nanoadsorbents and nanomembranes. For the purpose of treating sewage, the special properties of nanoparticles are currently being carefully researched. The ability of nanomaterials to remove organic matter, fungus, and viruses from wastewater is another benefit. Nanomaterials are employed in advanced oxidation techniques to clean wastewater. Additionally, because of their small dimensions, nanoparticles have a wide effective area of contact. Due to this, nanoparticles' adsorption and reactivity are powerful. The improvement of nanomaterial technology will be beneficial for the treatment of wastewater. This report also offers a thorough review of the distinctive properties of nanomaterials used in wastewater treatment, as well as their appropriate application and future possibilities. Since only a few types of nanomaterials have been produced, it is also important to focus on their technological feasibility in addition to their economic feasibility. According to this study, nanoparticles (NPs) have a significant adsorption area, efficient chemical reactions, and electrical conductivity that help treat wastewater effectively.

Comprehensive Performance Assessment of Dual Loop Organic Rankine Cycle (DORC) for CNG Engine: Energy, Thermoeconomic and Environment

The improvement of the overall utilization rate of compressed natural gas (CNG) engine fuel is the basis of efficient energy utilization. On the foundation of heat balance theory of internal combustion engines, this study fully considers the operation characteristics of CNG engines and systematically analyzes the distribution characteristics of different waste heat under variable working conditions. The nonlinear relationship between speed and intercooler heat source becomes evident with the increasing of intake mass flow rate. In accordance with the structural characteristics, the thermodynamic model, heat transfer model and environmental model of dual-loop organic Rankine cycle (DORC) are constructed. The system potential in full working environments is systematically evaluated. Compared with the speed, airmass flow has a significant effect on comprehensive performance of loop. The maximum power, heat transfer area and power output of per unit heat transfer area (POPA) of DORC are 36.42 kW, 23.34 m2, and 1.75 kW/m2, respectively. According to the operating characteristics of different loops, the variation laws of loop performance under the influence of multiple parameters are analyzed. The synergistic influence laws of multiple variables on system performance are also analyzed.

Polarization analysis and optimization of negative electrode nickel foam structure of zinc-nickel single-flow battery

The polarization of zinc‑nickel single-flow battery (ZNB) seriously affects the power density of the battery. In this paper, the polarization of ZNB is studied by establishing a three-dimensional polarization model and using the numerical simulation method. Nickel foam (NF) is used to replace conventional nickel-plated steel strip (NS) as the anode, and the polarization of the battery with nickel foam as the negative electrode is studied by the response surface method for the first time. The reliability of the numerical model is proved by experimental comparison, and the effectiveness of the response surface method is also proved by analysis of variance. In this paper, the influence of multiple parameters (thickness of nickel foam, porosity, and flow rate of inlet electrolyte) on the negative polarization degree of the battery is discussed. The coupling function of the negative polarization to each parameter is fitted, and the optimal structure is given. The results show that the optimal nickel foam structure is compared with the traditional nickel-plated steel strip structure, negative activation polarization overpotential and concentration polarization overpotential decrease by 90.28 % and 88.12 % respectively when a state of charge is 0.5. In addition, the negative polarization of the optimal nickel foam structure is discussed with time and space.

Research on the Influence of Multiple Parameters on the Responses of a B-type Subway Train

To obtain improved comprehensive crashworthiness criteria for a B-type subway train, the influence laws of the vehicle design collision weight M and empty stroke D on the train’s collision responses were investigated, and multi-objective optimization and decision-making were performed to minimize TS (total compression displacement along the moving train) and TAMA (the overall mean acceleration along the moving train). Firstly, a one-dimensional train collision dynamics model was established and verified by comparing with the results of the finite element model. Secondly, based on the dynamics model, the influence laws of M and D on the collision responses, such as the energy-absorbing devices’ displacements and absorbed energy, vehicles’ velocity and acceleration, TS, TAMA and the coupling correlation effect were investigated. Then, surrogate models for TS and TAMA were developed using the optimal Latin hypercube method (OLHD) and response surface method (RSM), and multi-objective optimization was conducted using the particle swarm optimization algorithm method (MPOSO). Finally, the entropy method was used to obtain the weight coefficients for TS and TAMA, and multi-objective decision-making was performed. The results indicate that D and M significantly affect the compression displacements and energy absorption of the first three collision interfaces, but have limited impact on the last three collision interfaces. The velocity versus time curves of vehicle M1 and M2 are shifted and parallel with different D. However, the velocity versus time curves of all the vehicles are shifted but gradually divergent with different M. The maximum collision instantaneous accelerations of the vehicles are directly determined by M, but are only slightly affected by D. Under the coupling effect, all concerned collision responses are strongly correlated with M; however, the responses are weakly correlated with D except for the compression displacement at the M2-M3 collision interface and the maximum collision instantaneous acceleration of vehicle M2. The comprehensive crashworthiness criteria of the B-type subway train were significantly improved after multi-objective optimization and decision-making. The research provides more theoretical and engineering application references for the subway train crashworthiness design.

Model for analyzing the energy efficiency of hydrogen liquefaction process considering the variation of hydrogen liquefaction ratio and precooling temperature

The energy efficiency of the hydrogen liquefaction process is studied, and a general model of the hydrogen liquefaction process is built for analyzing the energy efficiency and the influence of multiple parameters. Energy and exergy analysis models of the typical single-pass cycle and multiple-pass cycle are developed. The specific relationships among the parameters and energy efficiency of the total liquefaction system are deduced. A hydrogen liquefaction process with precooling nitrogen and cryogenic helium cycles is studied. For the precooling and cryogenic cycles, the SEC and net power consumption of the cryogenic helium cycle have different variation trends along with the precooling temperature and hydrogen liquefaction ratio. Their optimal values are identified to be −194 °C and 0.9453, and the corresponding SEC, exergy efficiency, total capital expense, and total annual cost are 3.619 kWh/kgLH2, 33.44%, 82.58%, 8.263 M$, and 531.62 M$/yr, respectively. The proposed model can be used in the design and operation stages to analyze the variation of energy efficiency along with multiple parameters of the hydrogen liquefaction process.

Dynamic analysis of composite rod fastening rotor system considering multiple parameter influence

Dynamic performances of composite rod fastening rotor system are analyzed considering the integration of multiple parameters. A dynamic modeling method of multi-disk rod fastening rotor system is proposed based on the composite rotor structure and the influences of multiple parameters. The interaction of system parameters and fault features are revealed in the composite rod fastening rotor system. The dynamic analysis discloses the influence of fault degree and multiple parameters on the nonlinear behaviors. The results show that the dynamic characteristics of the rod fastening rotor system alter under the crack fault. The evolution of nonlinear performances is displayed in the analysis of multiple parameters. The analysis results contribute to the identification of dynamic characteristics for rod fastening rotor system and fault detection of gas turbine rotor system.

Modeling and Analysis Variable Cross Section Pile Driven in Sandy Soil using Finite Element

This study focuses on the finite element simulation of piles with different models in sandy soils using the software PLAXIS 3D V20. The parametric study has conducted to investigate the influence of multiple parameters on the axial capacity of steel piles in sandy soil, including the cross-section variables in two cases: open and close-ended piles. The typical circular and square cross-section open and close-ended piles were selected as the reference for comparison with variables cross-section piles. The open-ended tapered pile 3b showed an increase in the maximum load capacity about 210% more than the open-ended circular section, while the close-ended tapered pile 3b showed an increase of about 176% in the axial load capacity more than the solid close-ended circular section. In terms of the effect of pile’s type, all of the close-ended sections outperformed the open-ended sections, with the circular section showing a 146% increase in its close-ended section, while the tapered 3b section showed the lowest difference between the close-ended and the open-ended sections with just 120% increase. These results showed that the tapering pile is much more efficient than any straight-sided pile or even circular pile. The results also showed that a short open-ended pile's capacity is smaller than the corresponding closed-ended pile.

Numerical investigation on the tensile fracturing behavior of rock-shotcrete interface based on discrete element method

Four groups of numerical models of Brazilian tests on rock-shotcrete interfaces were successfully conducted by PFC2D. The tensile strength and Young’s modulus of shotcrete were considered. Six different undulations of rock-shotcrete interface were set up. The influences of multiple parameters on the bearing characteristics of the rock-shotcrete interface were studied. The results showed that a better support performance can be obtained by increasing the Young’s modulus of shotcrete rather than the tensile strength of shotcrete. For different tensile strength and Young’s modulus, the increase of sawtooth height has different effects on the support performance. The failure mechanism of the rock-shotcrete interfaces was analysed in detail. The stress shielding effect and stress concentration effect caused by the shape characteristics of rock-shotcrete interface were observed. The influence of these parameters on the overall support performance should be fully considered in a reasonable support design.

Research on a non-linear calibration method for dynamometer

Purpose The purpose of this paper is to solve the problem that the relationship between loading forces, which were applied at different positions on a plane, and output values of load-sharing dynamometer is non-linear. Design/methodology/approach First, the analytical model of ISPM (isodynamic surface proportional mapping method) method, which is used to calibrate dynamometer, was established. Then, a series of axial force calibration tests were performed on a load-sharing dynamometer at different loading positions. Finally, according to output values, calibration forces at different loading positions were calculated by ISPM method, and corresponding distribution histogram of calibration force error was generated. Findings The largest error between calculated force and standard force is 2.92 per cent, and the probability of calculated force error within 1 per cent is 91.03 per cent, which verify that the ISPM method is reliable for non-linear calibration of dynamometers. Originality/value The proposed ISPM method can achieve non-linear calibration between measured force and output signal of load-sharing dynamometer at different positions. In addition, ISPM method can also solve some complex non-linear problems, such as prediction of plane cutting force under the influence of multiple parameters, the force measurement of multi-degree-of-freedom platform and so on.

A new electrical imaging logging method in oil-based mud for low-resistivity formation based on concave electrode couples

Electrical imaging logging can provide high-resolution information and occupies a pivotal position in reservoir exploration and evaluation. To realize clear electrical imaging in high-resistivity oil-based mud (OBM), researchers have tried various methods. In the existing methods, there are some worrisome issues such as the challenge in clear imaging in low-resistivity formation, the complication and robustness in the inversion of quantitative interpretation and few obtained parameters etc. In this paper, a gratifying way with the help of concave electrode couple is presented and analyzed particularly to focus on the quantitative evaluation in low-resistivity formation. The imaging pad structure and its work principle are first introduced. Then, a systematical and mathematical statement is carried out to obtain desired formation resistivity and standoff between imaging pad and borehole wall. Furthermore, sensitivity analysis is implemented to make clear the performances of measured values including equivalent formation resistance, tool factor and calculated standoff under the influence of multiple parameters. Finally, several imaging tests are shown to demonstrate the effectiveness of this new method presented in this paper. The results shown that profiting from the change of traditional electrode array to concave electrode couples, the formation resistivity and standoff between the pad and borehole wall in low-resistivity formation can be measured simultaneously. Another major advantage of this new method is that the unknown OBM parameters are unnecessarily mastered, and the entire process is free from complicated iterative computation. This study provides another new choice for the electrical imaging logging in OBM.

Interactions between Organic Model Compounds and Ion Exchange Resins.

Ion exchange (IEX) can successfully remove natural organic matter (NOM) from surface water. However, the removal mechanism is not well understood due to the complexity and variability of NOM in real source waters as well as the influence of multiple parameters on the removal behavior. For example, this includes the physicochemical properties of the NOM and IEX resin, and the presence of competing anions. Model compounds with a range of physical and chemical characteristics were therefore used to determine the mechanisms of NOM removal by IEX resins. Fifteen model compounds were selected to evaluate the influence of hydrophobicity, size, and charge of organic molecules on the removal by ion exchange, both individually and in mixtures. Three different resins, comprising polystyrene and polyacrylic resin of macroporous and gellular structure, showed that charge density (CD) was the most important characteristic that controlled the removal, with CD of >5 mequiv mgDOC-1 resulting in high removal (≥89%). Size exclusion of compounds with high MW (≥8 kDa) was evident. The hydrophobicity of the resin and model compound was particularly important for removal of neutral molecules such as resorcinol, which was best removed by the more hydrophobic polystyrene resin. Relationships were identified that provided explanations of the interactions observed between NOM and IEX resin in real waters.

A preliminary optimization of borehole microseismic array design with a multiple criteria decision analysis

Economic development of unconventional reservoirs requires a combination of different techniques such as horizontal drilling and hydraulic fracturing. To obtain valuable information about the effectiveness of a hydraulic fracturing operation, it is a common practice to use borehole microseismic monitoring by deploying arrays of geophones in wells nearby. Microseismic monitoring provides important data about fracture parameters including: half-length, geometry, orientation and complexity of the fracture network. Based on this information, stimulation programs can be improved to increase production volumes. However, inaccurate microseismic acquisition design can result in poor quality raw microseismic data that undermines the success of this important operation.In this study, we developed a comprehensive workflow using Multiple Criteria Decision Analysis (MCDA) to optimize microseismic acquisition design in order to improve borehole microseismic data quality. The influence of multiple parameters, such as average distance to microseismic events, receiver and event aperture, and wave-field complexity, is considered. A computer code is developed to resolve the conflicting parameters to achieve the best possible data quality. The program output is used recommend an optimum depth and location for deploying the borehole geophone array(s). The algorithm is then applied to a case study that utilizes synthetic microseismic data and real well trajectories from several vertical and horizontal wells in Williston Basin, North Dakota.

Friction performance and optimisation of diamond‐like texture on hydraulic cylinder surface

For the ring surface of a hydraulic cylinder, grid and striped textures have been demonstrated in many previous works to easily provide a conductive oil path, which increases the difficulty of generating converging wedges and are harmful to the formation of dynamic pressure lubrication, especially for full lubrication. Moreover, these studies used an orthogonal design method to study the hydrodynamic lubrication effect and friction performance of the surface without considering the comprehensive effect of multiple parameters with simultaneous changes, which may introduce errors into the simulation analysis. In this work, a diamond-like, non-conductive texture, which mimics shark skin, is developed and optimised to determine the optimal texture morphology while simultaneously considering the influence of multiple parameters, including the diamond angle, axial length ratio, and area occupancy, to optimise the surface of the friction pair. The results show that under the same working conditions, the lift of the diamond texture is nine times greater than that of the striped texture, while its friction coefficient is only one-quarter of that of the striped texture, which will greatly improve the friction and responsiveness of the hydraulic cylinder.

Global Sensitivity Analysis for the Elastic Properties of Unidirectional Carbon Fibre Reinforced Composites Based on Metamodels

A fast and effective numerical method to predict mechanical properties of carbon fibre reinforced polymer (CFRP) composites, even elastic properties, is complicated due to the mismatch of mechanical properties among the constituents. Furthermore, it is not possible to completely characterise the influence of multiple parameters including mechanical and structural parameters on the bulk properties of CFRP by experiments. In this study, a three-phase finite-element model consisting of matrix, carbon fibre and interface was developed to predict the elastic mechanical behaviour of unidirectional CFRP. The elastic properties in terms of two Young's moduli, two Poisson's ratios and a shear modulus were calculated by means of a homogenisation method. High-accuracy Kriging surrogate models were constructed to fast-calculate the elastic responses for a large number of samples. Combining Kriging and high-dimensional model representation (HDMR) methods, a global sensitivity analysis was performed to study how the microscopic parameters influence the elastic responses to get a deeper understanding of elastic property-structure relationship. Eleven parameters, including mechanical and geometry properties of constituent phases, were chosen as inputs. Independent and cooperative effects of input parameters on the elastic properties of the studied composites were surveyed via first- and second-order sensitivity indices, respectively. An importance ranking of these parameters for each elastic response was derived directly by these indices. The procedure proposed in this work could serve as a theoretical guide for further design optimisation of CFRP.