Interference Degree Research Articles

A quantum probability theory-based method for heterogeneous multi-criteria group decision making with incomplete probabilistic linguistic preference relations considering the interference effect among decision makers

Quantum probability theory (QPT) reveals that decision makers (DMs) can interfere with each other and thus affect the decision result. However, existing methods of heterogeneous multi-criteria group decision making (HMCGDM) seldom consider the interference effect among DMs. This paper defines an interference degree based on the phase angle difference obtained by QPT to address HMCGDM problems in which the alternative and criteria sets provided by DMs may be different. In addition, the incomplete probabilistic linguistic preference relations (InPLPRs) are introduced to express the evaluation information of DMs. Considering that the same linguistic term may has different meanings for DMs, we construct a consistency-driven optimization model based on the personalized individual semantics (PISs) to estimate the missing information in InPLPR on each criterion provided by DMs and the corresponding complete PLPR (CPLPR). Then, for each DM, the individual weights of criteria and the comprehensive CPLPR on all criteria in the individual criteria set can be obtained by an optimization model. Subsequently, a novel QPT-based model is erected to derive the weights of DMs and the ranking order of alternatives. Finally, an example of tourism evaluation and several sensitivity and comparative analyses are offered to examine the applicability of the proposed method.

Key factors affecting project delivery system selection in the Chinese construction industry

This study aims to investigate the key factors owners consider when selecting a PDS, the importance degree of these factors, and the perception differences among owners, consultants, and contractors regarding these factors. Interviews and questionnaire surveys were used to determine the importance degree of each influencing factor. And perception differences of the influencing factors on PDS among the three subjects were calculated through SPSS 15.0. The findings show that the three subjects' perceptions of the importance degree of the economic attributes of the engineering project, engineering project complexity, sub-project construction interference degree, and delivery system preference were significantly different, while the perceptions of engineering project scale, investment control requirements, schedule requirements, quality requirements, risk preference, construction management capability, land acquisition, demolition and migration, construction site conditions, local policies and regulations, and construction market development level were insignificantly different. This research can help owners understand influencing factors on PDS selection from different dimensions. Valuable information was provided for owners to select an accurate and reasonable PDS, ultimately reducing project costs and facilitating project management. Additionally, this research complements previous research on PDS selection and proposes a new influencing factors framework by exploring the key factors affecting PDS selection and the perception differences between the three subjects.

Spectral-based estimation of chlorophyll content and determination of background interference mechanisms in low-coverage rice

The chlorophyll content is a vital indicator of rice growth and nutritional status. However, estimating the rice chlorophyll content using spectral-based techniques at the early tillering stage is challenging because of background interference. Using the energy conservation principle, this study explained the spectral variation and background interference mechanisms of clear, muddy, and green algae-covered backgrounds. We developed mathematical interference models for the three types of backgrounds and determined their interference degree and influence mode. We developed rice chlorophyll content estimation models for unclassified and classified (clear, muddy, and green algae-covered) backgrounds using 12 preprocessing, four wavelength selection, and three modeling methods, and we explored the importance of background classification. Moreover, we found that the optimal chlorophyll content estimation model for the clear background was SS+UVE+CNN, with R2 and RMSE values of 0.786 and 13.191 in the training set and 0.741 and 15.327 in the test set, respectively; that for the muddy background was MSC+GA+CNN, with R2 and RMSE values of 0.914 and 10.425 in the training set and 0.660 and 16.844 in the test set, respectively; and that for the green algae-covered background was DC+GA+CNN, with R2 and RMSE values of 0.904 and 9.111 in the training set and 0.688 and 17.694 in the test set, respectively. Our study could provide valuable insights into reducing and correcting background interference during proximal remote sensing data collection.

Feasibility analysis of commingle production of multi-layer reservoirs in the high water cut stage of oilfield development

Multi-layer commingle production is a common development technique to improve the overall oil recovery of multi-layer reservoirs. However, this technique is mainly used at low water cut stage. Research on this technique at high water cut stage is comparatively few. Therefore, in order to improve productivity and recovery of wells, feasibility analysis of commingle production of multi-layer reservoirs in the high water cut stage is analyzed. To achieve a good commingle production result, the production layers must be optimized and inter-layer interference must be analyzed and reduced as much as possible. Factors, such as permeability, porosity, viscosity, capillary pressure, gravity, pressure difference, and water cut difference, have impact on commingle production. But it is difficult to consider all these factors. Therefore, according to the geological reservoir characteristics of X Oilfield, a model is established to simulate commingle production process, and the results are compared and analyzed. The interference degree is characterized by seepage resistance. The commingle production effect is evaluated by dimensionless oil increase coefficient, production index, and production index interference coefficient. The results show that the larger the difference of permeability ratio and water cut between multi-layers, the more severe the interlayer interference; dimensionless oil increase coefficients are all positive, it means that commingle production can achieve good oil increase effect even in the high water cut stage; the recommended technical limits for commingle production are that: permeability ratio is less than 5; commingle production timing is that water cut of low permeability layer is higher than 80%. This technique has been applied to X Oilfield, and the oil recovery increased about 2.8%, which confirmed this method feasibility.

Analysis method of explosive electromagnetic radiation energy

AbstractThe energy of electromagnetic radiation from explosions is coupled to electronic equipment circuits, disrupting the initiation sequence or causing failure in an increasing number of cases, which seriously affects the stability of weapon systems. There is a significant difference between the characteristics of the explosive electromagnetic radiation signals and modulated electromagnetic signals. The electric field intensity and signal power cannot directly represent the magnitude of the explosive electromagnetic radiation energy, and traditional electromagnetic signal analysis methods are unsuitable for explosion electromagnetic signal analysis. To solve this problem, the mechanism of explosive electromagnetic radiation was first analyzed. Through verification experiments of the explosion electromagnetic intensity and temperature, it was concluded that there is a strong correlation between the explosion plasma temperature and electromagnetic intensity. The temperature of the explosive plasma is derived based on the measured surface temperature of the explosive fireball, a functional relationship is established between the energy of the explosive plasma and the temperature of the plasma, and plasma energy is introduced as a parameter for electric field intensity correction. The interference signal analysis method based on eye diagram is used to calibrate the electromagnetic radiation damage ability, achieving quantitative analysis of the interference degree of electromagnetic radiation energy on the signal, and providing a new approach for the analysis of explosive electromagnetic radiation energy.

Online detection and assessment of cable insulation fault based on time–frequency domain reflectometry

The insulation performance of cables plays an important role in the safe and stable operation of aircraft. Time–frequency domain reflectometry (TFDR) is an effective method to detect the local insulation faults of cables. Usually, Wigner–Ville distribution (WVD) is used to analyze the energy distribution of reflected signals in TFDR. However, WVD can easily introduce cross-term interference to the detection results. In addition, most of the current studies have used TFDR to perform offline detection of cable insulation fault, and the performance of TFDR for online operation is unclear. In order to solve the above problems, first, this paper eliminates the interference of cross-term based on smoothed pseudo-Wigner–Ville distribution. Then, an online cable insulation fault detection platform based on non-contact signal injection is built. According to the requirements of the standard GJB181A, the interference degree of the incident signal of TFDR to the original signal of cable is analyzed, and the feasibility of using TFDR method to perform online detection is proved. Finally, the correlation between different features of reflected signals under different fault degrees of cable is analyzed. It is proved that time-domain correlation has a better correlation with the fault degree of cable compared to other four features.

Accurately evaluate anti-magnetic field interference ability: A study on magnetic field interference degree analysis method for magnetic sensors

One of the problems faced in magnetic sensors is how to evaluate their ability to anti-magnetic field interference (AMFI). External magnetic fields can easily affect the accuracy of magnetic sensor measurements. In the worst-case scenario, the measured magnetic field will be masked entirely, and the magnetic sensor will lose its measurement function. Existing research usually uses measurement errors to reflect the AMFI ability of magnetic sensors, but measurement errors can vary with changes in interference current. Therefore, measurement error cannot be used as an indicator to evaluate the ability of magnetic sensors to AMFI. This article proposes a magnetic field interference degree (MFID) analysis method in response to this issue. By establishing an MFID mathematical model, the influence of parameters such as current interference angle and distance ratio on the MFID distribution characteristics of magnetic sensors is studied. In order to guide the AMFI design of magnetic sensors, the MFID mathematical model is solved to calculate the magnetic field interference zero point (MFIZP). An optimization plan is also proposed to improve the AMFI capability of magnetic sensors. The single-axis TMR sensor is used in this article for experiments to verify the feasibility of the proposed method and optimization scheme. Analysis and experimental results indicate that the method proposed in this paper can reasonably evaluate the magnetic sensor's AMFI ability, and the optimization scheme is superior in improving the magnetic sensor's AMFI ability.

An improved prediction model for COD measurements using UV-Vis spectroscopy.

In the 21st century, although water quality has been improved in the last two decades, water pollution by organic contaminants has remained a non-negligible issue in China, so Chemical-Oxygen Demand (abbreviated as COD, unit: mg L-1) is often used as the main index to measure the degree of surface water pollution. UV-Vis spectroscopy, as a sensitive and rapid analytical technique, is a green detection technology suitable for automatic online COD detection equipment. However, due to the complex composition of surface water, the interference degree of the UV-Vis spectrum caused by turbidity is strongly correlated with the size, type and color of particulate matter in the solution, which results in noise sensitivity and poor generalization of the current detection model. Therefore, the main purpose of this research is to improve the traditional detection model performance by using deep learning and a spectrum preprocessing algorithm. Firstly, we used an improved noise filter based on discrete wavelet transforms to solve the noise sensitivity. Secondly, we proposed a novel COD detection network to address poor generalization. Thirdly, we collected a total of 2259 water samples' UV-Vis absorption spectra and corresponding COD as a dataset. Then, we pipelined the improved noise removal algorithm and proposed COD detection network, as a complete COD prediction model. Finally, the experiment on the dataset shows that the COD prediction model has a good performance in terms of both noise tolerance and accuracy.

Controlled Sequential Assembly of DNA Nanoparticles Inside Cells Enabling Mitochondrial Interference

AbstractDeveloping artificial material systems to rationally interfere with organelles is emerging as a promising route to regulate the behaviors and fate of cells, thus providing new therapeutic strategies. Herein, a DNA nanoparticles (DNPs)‐based material system is reported, which achieves controlled sequential assembly inside cells, and realizes specific interference toward mitochondria. Two types of DNPs are synthesized via radical polymerization, followed with cascade hybridization chain reaction of hairpin DNA with Cyanine5 (Cy5) for mitochondrial targeting, and with complementary sequences for base pairing, respectively. DNPs with Cy5 (Cy5‐DNPs) first entered cells to target mitochondria, and the other DNPs with complementary sequences entered cells after an interval to sequentially assemble with Cy5‐DNPs into aggregates via base pairing. Mitochondrial interference is achieved, including increased reactive oxygen species, decreased membrane potential, abnormal elevation of Ca2+ level, decreased adenosine triphosphate, and attenuated cellular migration rate. In particular, by regulating the intervals of two types of DNPs entering cells, the mitochondrial interference degree is controllably modulated. This work achieves regulated organelles interference via the precise controlled self‐assembly of DNA nanostructures inside cells, which is envisioned to have great potential in precision biomedicine.

Polarization control and enhanced magnetic field sensitivity utilizing surface plasmon polaritons-assisted dual-V-type four-level system

We propose a kind of surface plasmon polaritons (SPPs)-assisted dual-V-type four-level composite system used for high-sensitivity weak magnetic field measurement. The SPPs are excited by a D-shaped photonic crystal fiber (PCF) deposited with gold nanowires, and are interacted with the above quantum emitter from the rubidium atomic vapor. In the presence of the external magnetic field, Faraday rotation symmetry is broken due to Zeeman effect, resulting in the polarization plane rotation when a linearly polarized probe field goes through the above quantum emitter. With the help of the coupled field and SPPs, Faraday magneto-optical rotation (MOR) are effectively regulated. The Rabi frequency of the coupled field (Ω c ), quantum interference degree (q), and phase difference (φ) between the applied fields show strong dependence on the MOR angle and magnetic field measurement sensitivity. The simulated results reveal that the maximum MOR angle and magnetic field sensitivity both damp with Ω c expanding and q reducing. The maximum dichroism-independent MOR angle of 89.97° is realized for φ = 0° (180°), and the magnetic field sensitivity of 10.88°/Oe is obtained in the sweeping range of −8.88–8.88 Oe for q = 0.99, being 2.66°/Oe higher than that in the absence of SPPs (q = 0). Most importantly, the output probe field with different polarization forms can be realized by adjusting the φ value. Hence, the proposed device exhibits the potential in the fields of weak magnetic field measurement and polarization control.

Energy-Aware Mode Selection for D2D Resource Allocation in 5G Networks

This paper proposes an energy-aware mode-selection mechanism for device-to-device (D2D) resource allocation in the coexisting 5G network environment of D2D users and traditional cellular users by taking into consideration the mechanisms of mode selection, transmit power, and spectrum resource allocation simultaneously. In the proposed approach, all spectrum resources are fully shared by traditional cellular users and D2D users. We first determine the communication mode of all users after considering the transmission opportunity of traditional cellular users and analyzing the interference degree of different D2D communication modes. Next, we divide all users into three tiers according to the distances between users and the base station to solve the interference problem generated by excessing transmit power in uplink transmission. Afterward, based on the different communication modes, corresponding spectrum resource allocation mechanisms using the Hungarian algorithm are developed. We simulate a single cell environment using Python language and perform several simulations for different pairs of traditional cellular users and D2D users. The simulation results reveal that the proposed approach outperforms the proposed approach by Hou et al. in system throughput. With power control, the energy efficiency of the proposed approach could be enhanced by 20%.

Low-frequency FBG vibration sensors for micro-seismic monitoring

Vibration sensors are key components in low-frequency micro-seismic monitoring, and their performance directly determines the accuracy of monitoring results. In response to the current problem that fiber Bragg grating (FBG) vibration sensors are difficult to effectively monitor micro-seismic low-frequency vibration signals, a rigid L-shaped beam FBG vibration sensor based on bearings is proposed. Firstly, a sensor model is established and theoretically analyzed; secondly, key parameters are optimized using differential evolution algorithm and imported into COMSOL simulation software for static stress analysis and dynamic characteristic analysis; finally, the sensor prototype is developed and a low-frequency vibration test system is set up to verify the sensor performance. The results reveal that the inherent frequency of the sensor is 57 Hz, with a flat response band of 0.3–35 Hz, a frequency lower limit of 0.05 Hz, a transverse interference degree of 4.5%, an average sensitivity of over 800 pm g−1, a dynamic range of 67.75 dB, favorable linearity, and the ability to achieve temperature self-compensation. Research findings provide new insights into low-frequency micro-seismic monitoring.

A dataset of monthly light pollution indexes of rivers in China

This paper provides a dataset of monthly river pollution index from April 2012 to October 2021 in China based on the published HydroSHEDS dataset and the monthly composite data of NPP-VIIRS night light. Firstly, we extracted the river sections in China from HydroSHEDS, and corrected unreasonable river sections in accordance with the authoritative river data. Secondly, we overlyed the river sections layer and NPP-VIIRS grid to identify the pixels flowing through the water system, and extracted the value of each pixel from the NPP-VIIRS grid. Then, taking the 10 × 10 km grid as the unit, comprehensively considering the flow, brightness and river length of each unit, we designed the river light pollution indexes, and calculated the monthly river light pollution index of each unit. Finally, we obtained a dataset of monthly light pollution index of rivers with the resolution of 10 × 10 km. As the first dataset of river light pollution, this dataset reflects the temporal and spatial distribution and evolution pattern of river light pollution in China, and it can provide reference for river development degree and interference degree evaluation, light pollution analysis and other research.

Channel modeling and achievable data rate for 1-D molecular communication in bounded environments

In this paper, we propose the analytical propagation model for diffusive molecular communication in an one-dimensional bounded environment, and determine the available data rate for a given limit of interference. Molecular communication is a promising solution for applications when the typical electromagnetic communication is not available. However, due to the randomness of the molecule movement, it is challenging to analyze the channel in molecular communication. Taking into account the impact of an absorbing boundary to the one-dimensional vessel-like channel, we model the time-varying distribution of the releasing molecules. Accordingly, we derive the hitting probabilities for an information molecule to separately reach the receiver or the boundary, and present the impulse response of the channel at a given time t. Moreover, under the same environment, we consider the time duration between transmissions of a binary modulation system for a given level of inter-symbol interference. Our analysis shows that, for a certain degree of interference, the available data rate of the system can be expressed as 2Dαth2S2, where S is the distance between the receiver and the boundary, and D is the diffusion coefficient of the channel, and αth2 is the corresponding index to the interference degree. The authenticity of our analysis are verified via simulations.

Spatio-temporal dynamics and sensitive distance of nighttime light environment in Pearl River Delta Protected Areas, China.

Protected areas (PAs) are important barriers to ensure the ecological security of territory. Light pollution is a threat to PAs, which is particularly obvious in the urban agglomeration environment. We used multi-source big data (satellite remote sensing light data, land cover types and points of interest) to quantitatively analyze the temporal and spatial dynamics of nighttime light in the PAs of the Pearl River Delta (PRD) urban agglomeration from 2000 to 2018, the correlation between the night light environment within the PAs and human activity intensity outside, as well as the sensitive distance of the PAs to artificial light interference. The results showed that the total value of nighttime light data of PAs in the PRD increased from 71107 nanoW·cm-2·sr-1 to 127682 nanoW·cm-2·sr-1 from 2000 to 2018, the mean value per pixel increased from 15.3 nanoW·cm-2·sr-1 to 23.7 nanoW·cm-2·sr-1, and the lighted ratio increased from 73.3% to 86.4%, indicating that the nighttime light environment of PAs in the region were facing cumulative deterioration risks and serious challenges. The nighttime light intensity of the PAs in the core area of the PRD was much higher than that in the peripheral areas such as Zhaoqing and Huizhou, whereas the expansion degree of the PAs in the peripheral areas was higher than that in the core area. The nighttime light environment inside the PAs was positively correlated with the intensity of human activities around it. The most sensitive distance of the PAs to the artificial light interference around it was 10 km, and the interference degree tended to be stable after 30 km. We proposed that 0-10 km area outside the boundary of the PAs should be the light control core zone and 10-20 km area as the control buffer zone.

Human-exoskeleton oscillation model and qualitative analysis of interaction and functional practicality of exoskeletons

In the previous exoskeleton research, the development method of the exoskeleton-function-expectation prediction in the initial design stage is lacking, which is not conducive to reviewing the system-parameter influences on exoskeleton performances, nor to exploring the exoskeleton optimization direction. In this paper, a human-exoskeleton oscillation model is designed by integrating the main functions of one load-supporting exoskeleton in the gravity direction into the double-mass coupled oscillator model. The model simplifies the human-exoskeleton coupling motion into the human-exoskeleton oscillation motion in the gravity direction, and in the oscillation process qualitatively calculates the multiple functional expectations of the exoskeleton, such as the load-supporting capability, the human-exoskeleton interaction force, the oscillation response of the backpack and the power-assistance ability. By comparing the test results of the model with previous research, the model performance was analyzed. And further, the reasons for the unsatisfying load-supporting efficiency of previous exoskeletons were explained and the influences of system parameters for the system expectations were evaluated, which helps to provide a theoretical basis for improving the exoskeleton load-supporting efficiency and human-body comfort. In addition, the combination of the exoskeleton supporting static load and the suspension system buffering dynamic load is a new direction, and the model of the paper is also beneficial to evaluate the interference degree of the exoskeleton to the suspension system.

Quantifying Resource Contention of Co-located Workloads with the System-level Entropy

The workload co-location, such as deploying offline analysis workloads with online service workloads on the same node, has become common for modern data centers. Workload co-location deployment improves data center resource utilization significantly. Still, it also introduces resource contention, resulting in the online service’s quality of service fluctuation, which we call performance interference. As the online service is a tail-latency-sensitive workload, the tail-latency metric can reflect the performance interference degree of the co-location workloads at the application level. However, to guide system design and evaluation, quantitatively evaluating the resource contention of the co-located workloads at the system level is also essential. This article proposes a novel metric called System-Level Entropy (SLE). As a system-level metric, SLE can measure quantitatively resource contention of the co-location systems and perform the apples-to-apples comparison between systems. The experimental results show that SLE can accurately reflect the performance interference of workloads and then evaluate the system resource contention. We also demonstrate two case studies of the SLE. We quantify the affinity of different co-location combinations, including three online services and five offline workloads. Furthermore, we evaluate the effects of state-of-the-art isolated mechanisms (the container and the CPU–affinity binding) with these co-location combinations.

Well interference evaluation considering complex fracture networks through pressure and rate transient analysis in unconventional reservoirs

Severe well interference through complex fracture networks (CFNs) can be observed among multi-well pads in low permeability reservoirs. The well interference analysis between multi-fractured horizontal wells (MFHWs) is vitally important for reservoir effective development. Well interference has been historically investigated by pressure transient analysis, while it has shown that rate transient analysis has great potential in well interference diagnosis. However, the impact of complex fracture networks (CFNs) on rate transient behavior of parent well and child well in unconventional reservoirs is still not clear. To further investigate, this paper develops an integrated approach combining pressure and rate transient analysis for well interference diagnosis considering CFNs. To perform multi-well simulation considering CFNs, non-intrusive embedded discrete fracture model approach was applied for coupling fracture with reservoir models. The impact of CFN including natural fractures and frac-hits on pressure and rate transient behavior in multi-well system was investigated. On a log–log plot, interference flow and compound linear flow are two new flow regimes caused by nearby producers. When both NFs and frac-hits are present in the reservoir, frac-hits have a greater impact on well #1 which contains frac-hits, and NFs have greater impact on well #3 which does not have frac-hits. For all well producing circumstances, it might be challenging to see divergence during pseudosteady state flow brought on by frac-hits on the log–log plot. Besides, when NFs occur, reservoir depletion becomes noticeable in comparison to frac-hits in pressure distribution. Application of this integrated approach demonstrates that it works well to characterize the well interference among different multi-fractured horizontal wells in a well pad. Better reservoir evaluation can be acquired based on the new features observed in the novel model, demonstrating the practicability of the proposed approach. The findings of this study can help for better evaluating well interference degree in multi-well systems combing PTA and RTA, which can reduce the uncertainty and improve the accuracy of the well interference analysis based on both field pressure and rate data.

A multi-fracture balanced extension control method for horizontal wells in anisotropic shale

Shale has anisotropy in elastic parameters and permeability coefficient in parallel and perpendicular directions to the bedding plane. In the study of fracture propagation during hydraulic fracturing, it is necessary to consider the influence of shale anisotropy. Through the development of fluid pipe element, fluid pipe connector element, cohesive damage element, and rock matrix element with pore pressure, a fluid–structure coupling numerical model with comprehensive consideration of dynamic flow distribution, dynamic fracture propagation and extension, and stress interference are established. The anisotropic characteristic parameters of shale reservoirs are given to study the balanced propagation control method of multi-fracture in horizontal shale Wells. The results show that under anisotropic conditions, hydraulic fractures are easy to expand in the direction parallel to the bedding plane but not in the direction perpendicular to the bedding plane. Finally, It forms a long extension in the length direction and a short extension in the height direction. The stress interference along the direction of the minimum horizontal principal stress is gradually intense with the increase of the degree of anisotropy. During multi-fracture propagation in horizontal shale wells, the stress interference generated in the direction of minimum horizontal principal stress can be balanced by effectively controlling the perforation friction so as to promote the balanced extension of multiple fractures. At the same time, with the increase of injection flow and the decrease of the distance between clusters, the stress interference degree gradually becomes serious. Therefore, it is necessary to strictly design how to control the perforation friction in the multi-fracture fracturing process of shale horizontal Wells with large flow rates and small cluster distances. The research conclusions provide a theoretical reference for the efficient development of shale petroleum resources.

The Interference of Pre-Processing Software for the Numerical Simulation of Groundwater on the Cognition of Environmental Students: Model Mesh Construction as an Example.

(1) Background: Software for the numerical simulation of groundwater plays an important role in studying environmental problems. However, it is still unclear whether the pre-processing software of the numerical simulation of groundwater has a negative effect on the cognition of undergraduates in the environmental field who only have basic groundwater flow and solute transport knowledge and software operation skills. (2) Methods: To explore this issue, we used software meshing as an example and selected undergraduates in the environmental field to conduct the questionnaire surveys. A total of 345 undergraduate answer sheets were received, and data analysis was carried out. The students were divided into two groups, one with and another without certain basic groundwater flow and solute transport knowledge or software operation skills. (3) Results: For undergraduate students with some basic knowledge or software operation ability, the proportion of students whose cognition was adversely interfered with by the pre-processing software was 64.3%, and the ratio of students not interfered with was 35.7%. For undergraduates without groundwater flow and solute transport knowledge and relevant software operation skills, the ratios were 63.2% and 36.8%, respectively. (4) Conclusions: Pre-processing software numerical simulation of groundwater could negatively interfere with students' cognition. The basic groundwater flow and solute transport knowledge and software operation skills did not observably reduce the interference degree (p = 0.259) but had significant influences on the undergraduates' thinking modes on the numerical simulation problems (p = 0.009). The interference was mainly caused by the significant difference between the level of knowledge possessed by the students and that represented by the pre-processing software. This paper provides basic scientific data for the optimization of students' knowledge structures and the improvement of teaching methods.