EFAST Method Research Articles

Sensitivity analysis and compensation for tooth surface deviation of spiral bevel gear machine tool

To analyze the quantitative mapping relationship between the geometric errors of the five-axis CNC machine tool and the tooth surface deviation of spiral bevel gears, and identify the key geometric errors that affect the machining deviation of the spiral bevel gear tooth surface, a sensitivity analysis method for tooth surface machining deviation of spiral bevel gear based on screw theory and EFAST method is proposed. Firstly, the machining model of the spiral bevel gear tooth surface based on the five-axis CNC machine tool is established. Then, the geometric error transfer model of the machine tool is established based on the screw theory. Combined with the EFAST global sensitivity analysis method, the key geometric errors that affect tooth surface deviation are identified. Finally, the reliability and effectiveness tests are performed by comparing the results to the local sensitivity analysis method and simulating compensation for the key geometric errors. The result of compensation shows that the tooth surface deviation is reduced significantly according to global sensitivity analysis. The feasibility of applying sensitivity analysis to control the tooth surface deviation of spiral bevel gears has been demonstrated.

Deformation Analysis of Existing Buildings Affected by Shield Tunnels Based on Intelligent Inversion and Measured Data

In the construction of urban underground shield tunnels, uneven deformation can easily occur when the shield passes through soft soil and other poor strata. Such deformation has a significant impact on surface settlement and may cause potential safety hazards to the surrounding existing buildings, directly affecting the safety of urban operation. When simulating and predicting surface settlements, the small-strain soil hardening model can more accurately characterize the mechanical parameters of soil. Nevertheless, its parameters are numerous and complicated to determine accurately, so parameter inversion is needed to determine the accurate parameters of the soft soil layer in order to more accurately predict the surface settlement. This study uses the EFAST method to analyse the sensitivity of the HSS model parameters of soft soil strata. It is determined that the parameters that have the most significant impact on the surface settlement are the reference tangent modulus, rebound modulus, and effective cohesion. Then, XGBoost’s fast calculation speed and high precision of SSA inversion are used to inverse and optimize the parameters with high sensitivity. Finally, according to the parameters of the soft soil layer obtained from inversion and measured data, the settlement deformation and safety behaviour of existing buildings are analysed. Combined with the actual shield tunnel project in a city along a river, the inversion calculation shows that the overall average error of the transverse monitoring section is 1.04 mm, and the average maximum error of each monitoring point in the overall shield process is 2.87 mm. The prediction effect is significantly improved compared with the original parameters. The accuracy of the inversion of soil layer parameters is verified from the perspective of time and space. The average settlement of the river embankment foundation is 2.5 mm. Compared with the original parameter data, the prediction results have been greatly improved, and the settlement deformation results are more consistent with the measured data.

An Interwell Connectivity Assessment Model for Polymer Flooding Short-Term Development Data Based on A-LSTM and EFAST Methods

Interwell connectivity assessment in polymer-driven reservoirs is critical for setting appropriate injection rates and improving oil recovery. Traditional deep learning techniques often lack accuracy and reliability when applied to short-term oilfield production data. In response, the A-LSTM algorithm is proposed, which integrates the attention mechanism with a long- and short-term memory network (LSTM). The predictive accuracy of A-LSTM is assessed and juxtaposed with LSTM and support vector regression (SVR) algorithms for short-term single-well daily oil production analysis. The Huber loss function was utilized to quantify the difference between predicted and actual results, resulting in a dynamic production prediction model. An interwell connectivity (IWC) assessment model is then obtained by fusing the dynamic production prediction model with the EFAST method, thus demonstrating the superior prediction accuracy of A-LSTM in oil production prediction and connectivity assessment. Moreover, the credibility of the assessment is further corroborated through numerical simulations and interwell tracer tests. The study results showed that the interwell connectivity evaluation model based on the A-LSTM algorithm and EFAST method is not only capable of accurately predicting the single-well daily oil production using a small sample dataset but also a highly reliable method for interwell connectivity evaluation, and the application of the interwell connectivity assessment model can further guide polymer flooding work in oilfields.

Safe Operating Conditions of isoperiodic Homogeneous Semi-Batch Reaction Based on Parameter Uncertainties Analysis

Proper operating conditions have a significant impact on the process state of semi-batch reaction. However, various error and bias lead to the uncertainties of parameter, which affect process safety of the semi-batch reaction. In this work, the effect of dimensionless parameters dimensionless adiabatic temperature rise (), Westerterp number (Wt), , dimensionless activation energy (γ), volumetric heat capacity ratio (RH) and relative volume increase (ε) on the temperature of the isoperiodic homogeneous semi-batch reaction are investigated by local sensitivity analysis. The sensitivity of the dimensionless maximum temperature to global parameters is analyzed using the scatter plot method based on Monte-Carlo sampling. Parameter sensitivity results are further quantitatively calculated by the eFAST method. The results indicate that there is a strong linear relationship between the maximum reaction temperature and △τad,0, which exhibits the highest sensitivity index compared to the other parameters. The safety boundary diagram and adiabatic temperature diagram are constructed by considering parameter uncertainty and the effect of parameter uncertainty on the critical criteria is analyzed.

Sensitivity analysis of effective parameters on bone drilling force by using E-fast method

Sensitivity analysis of effective parameters on bone drilling force by using E-fast method

Sensitivity Analysis of Biome-BGC for Gross Primary Production of a Rubber Plantation Ecosystem: A Case Study of Hainan Island, China.

Accurate monitoring of forest carbon flux and its long-term response to meteorological factors is important. To accomplish this task, the model parameters need to be optimized with respect to in situ observations. In the present study, the extended Fourier amplitude sensitivity test (eFAST) method was used to optimize the sensitive ecophysiological parameters of the Biome BioGeochemical Cycles model. The model simulation was integrated from 2010 to 2020. The results showed that using the eFAST method quantitatively improved the model output. For instance, the R2 increased from 0.53 to 0.72. Moreover, the root-mean-square error was reduced from 1.62 to 1.14 gC·m-2·d-1. In addition, it was reported that the carbon flux outputs of the model were highly sensitive to various parameters, such as the canopy average specific leaf area and canopy light extinction coefficient. Moreover, long-term meteorological factor analysis showed that rainfall dominated the trend of gross primary production (GPP) of the study area, while extreme temperatures restricted the GPP. In conclusion, the eFAST method can be used in future studies. Furthermore, eFAST could be applied to other biomes in response to different climatic conditions.

Comprehensive evaluation on water resources carrying capacity based on water-economy-ecology concept framework and EFAST-cloud model: A case study of Henan Province, China

Water is the basic need for human survival and the development of economy and ecology. Water resources carrying capacity (WRCC) modelling is a fundamental task to explore the interaction mechanism between economy-ecology development and water resources carrying system. To reasonably quantify the regional WRCC, an evaluation method based on Water-economy-ecology (WEE) concept framework and EFAST-Cloud model is proposed in this study, and Henan Province of China is selected as a typical study area. It can both identify the inter-feeding relationships between sub-systems and evaluate the proportion of each grade in detail by reflecting the randomness and fuzziness of the evaluation. A total of 15 indicators including water system, economy system, and ecology system are constructed. The study analyzes the sensitivity of indicators by using Simlab software and then calculates the weight of indicators by using EFAST method. Compared with other traditional methods, EFAST algorithm is a special method for model sensitivity analysis, which can fully consider the coupling effect between indicators. According to the statistical data of 2010, 2015, and 2020, the WRCC at the watershed scale and municipal scale in Henan Province are evaluated through the EFAST-Cloud model. At the watershed scale, the ecology system criterion layer performs best over the multiple years, the Huaihe and Yangtze River basin have better WRCC at the target layer. At the municipal scale, Xuchang, Luohe, and Zhumadian have better WRCC, Puyang, Zhoukou, and Jiaozuo are slightly worse. The results show that WRCC of the study area has shown an overall improvement, but there is still much space for its development. Therefore, targeted recommendations are made for the water, economy, and ecology system respectively. The conclusion of this paper can provide a reference for the government in making water resources management policies.

Sensitivity and stability analysis of a Kaplan turbine system considering synergistic regulation

Kaplan turbines, also known as movable propeller turbines, are attractive for power generation from water currents. They are controlled by guide vanes and runner blades, whose synergistic relationship plays an essential role in maintaining the stable operation of Kaplan turbine systems during transient process. Here we introduce a novel nonlinear dynamic model of a Kaplan turbine system with synergistic regulation by coupling the turbine, generator and governor. Sensitivity and stability analysis of the Kaplan turbine system are carried out based on EFAST method and stability theory. Effects of synergistic regulation on transient characteristic and stability of the Kaplan turbine system are investigated during transient process. Dynamics characteristic and stability region of the Kaplan turbine system suggest that transient performance improvement can be obtained by adjusting the synergistic relationship between the guide vanes and turning angle.

A comprehensive probabilistic approach for integrating and separating natural variability and parametric uncertainty in the prediction of distribution coefficient of radionuclides in rivers

A geochemical speciation model was developed to predict Distribution coefficients (Kds) of radionuclides (RNs) in rivers. The model takes into account complexation of RNs with inorganic ligands, sorption of RNs with hydrous ferric oxides, complexation of RNs with dissolved and particulate organic carbon (DOC and POC) and sorption and/or co-precipitation of RNs to carbonates. A sorption model of Cs onto clay was also integrated. The tool is also designed to conduct uncertainty and sensitivity analysis. Sensitivity analysis follows a stepwise structured approach, starting from computationally ‘inexpensive’ Morris method to most costly variance-based EFAST method. A nested Monte Carlo approach was also implemented to separate natural variability and lack of knowledge in global uncertainty assessment. As case studies, Kd distributions were estimated for Co, Mn, Ag and Cs in seven French rivers. Uncertainty analysis allowed to quantify Kd ranges that can be expected when considering all the sensitive parameters together.

Development of a behaviour-pattern based global sensitivity analysis procedure for coupled socioeconomic and environmental models

Dynamically Coupled Socioeconomic system dynamics models integrated with physically-based Environmental Models (DCSEM) can capture relationships between complex environmental and socioeconomic systems, and are promising tools for participatory environmental management involving the integration of various viewpoints, disciplines and processes for sustainable water resources management. However, the application of DCSEMs has been limited for many reasons, including the complexity of the model coupling process (i.e., the lack of a flexible model coupling approach), issues of over-parameterization, high parameter uncertainty, intensive computational requirements (due to many interacting parameters), and the possibility of eliciting behaviour-pattern oriented model outputs. As such, most conventional (numerical) procedures for model evaluation (i.e., analysis of point values of modelled results) that have been implemented for physically-based models are not applicable to DCSEMs. In order to address these challenges, this study developed a novel automatic behaviour-pattern global sensitivity analysis (GSA) procedure to determine the influence of input parameters on the general behaviour trends (rather than numerical point values) of coupled model outputs. The developed behaviour-pattern GSA procedure was implemented in an existing software (Tinamït), developed previously by the authors, to ensure ease-of-use. This study investigates the suitability of the proposed behaviour-pattern GSA procedure for the analysis of DCSEMs by comparing the proposed procedure with the conventional numerical procedure. The numerical and proposed behaviour-pattern procedures, coupled with the Morris (qualitative) and EFAST (quantitative) GSA methods, were applied to a DCSEM to rank and screen parameters in a water table depth simulation in Pakistan. The determination of important parameters facilitates subsequent model calibration and groundwater management. It was found that the Morris and EFAST methods achieved similar parameter ranking results in the numerical and behavioural procedures, respectively. The results also indicated that the behaviour-pattern GSA procedure offers more information about several important parameters, and a variety of parameter ranking orders, compared to the numerical GSA procedure, regardless of which GSA method (Morris or EFAST) was used. The increased information obtained through the application of the developed behaviour-pattern procedure confirms that the DCSEM model outputs are behaviour-oriented. It is recommended that the proposed behaviour-pattern GSA procedure be used with the Morris method, which has a higher computational efficiency (>150 times) than the EFAST method, to detect important parameters in DCSEMs.

A comprehensive probabilistic approach for integrating natural variability and parametric uncertainty in the prediction of trace metals speciation in surface waters

The main objectives of this study were to evaluate global uncertainty in the prediction of Distribution coefficients (Kds) for several Trace Metals (TM) (Cd, Cu, Pb, Zn) through the probabilistic use of a geochemical speciation model, and to conduct sensitivity analysis in speciation modeling in order to identify the main sources of uncertainty in Kd prediction. As a case study, data from the Loire river (France) were considered. The geochemical speciation model takes into account complexation of TM with inorganic ligands, sorption of TM with hydrous ferric oxides, complexation of TM with dissolved and particulate organic matter (i.e. dissolved and particulate humic acids and fulvic acids) and sorption and/or co-precipitation of TM to carbonates. Probability Density Functions (PDFs) were derived for physico-chemical conditions of the Loire river from a comprehensive collection of monitoring data. PDFs for model parameters were derived from literature review. Once all the parameters were assigned PDFs that describe natural variability and/or knowledge uncertainty, a stepwise structured sensitivity analysis (SA) was performed, by starting from computationally ‘inexpensive’ Morris method to most costly variance-based EFAST method. The most sensitive parameters on Kd predictions were thus ranked and their contribution to Kd variance was quantified. Uncertainty analysis was finally performed, allowing quantifying Kd ranges that can be expected when considering all the sensitive parameters together.

Experimental and theoretical analysis of the DMASP cantilever vibration behavior based on the MCS theory in moist environment

A micro cantilever (MC) and a probe are two main components of the atomic force microscope (AFM). The dimensions of these components are in micro scales while their oscillation amplitude is on a nanometer scale. The present study intended to not only increase the accuracy of the simulation with regard to geometric discontinuities based on the Timoshenko beam model using the modified couple stress (MCS) theory but also increase the accuracy of the prediction of a system behavior by considering the hysteresis effect into the system vibration equations based on Bouc–Wen model. Since, the classical theory disregarded the molecular structure of matter and neglected the microstructure size dependency, which raise its physical breakdowns in micro and nanoscale applications. Therefore, some micro continuum theories are developed to account for the microstructure effects by introducing additional material constants to the conventional ones. Due to the lack of the experimental results for this kind of MCs, this paper is focused on the both experimental and simulation results by utilizing the DMASP MC. The roughness of the surfaces affects the MC vibration behavior in the air medium. Therefore, surface roughness affecting van der Waals force has been considered in the air medium. Furthermore, the simulation results are compared with experimental results in the air medium with different moisture content during the surface topography. Due to the results, the best surface topography is achieved in the third vibration mode. Since the piezoelectric MC can tolerate the limited voltage, for this AFM MC type, the best surface topography is achieved in the third mode. Hence, this paper highly recommends using the third vibration mode during the surface topography. Finally, based on the EFAST method the most effective parameters on the AFM MC performance are the piezoelectric layer length, thickness and the probe length.

Study of the Population Dynamics of Busseola fusca, Maize Pest.

Busseola fusca is a maize and sorghum pest that can cause significant damage to both crops. Given that maize is one of the main cereals grown in the worldwide, this pest is a major challenge for maize production and therefore for the economies of several countries . In this paper , based on the life cycle of B. fusca, we propose a mathematical model to study the population dynamics of this insect pest . A sensitivity analysis using the eFast method was performed to show the most important parameters of the model. We present the theoretical analysis of the model. More precisely, we derive a threshold parameter [Formula: see text], called basic offspring number and show that the trivial equilibrium is globally asymptotically stable whenever [Formula: see text], while if [Formula: see text], the non trivial equilibrium is globally asymptotically stable. The theoretical results are supported by numerical simulations.

Theoretical Assessment of the Impact of Climatic Factors in a Vibrio Cholerae Model.

A mathematical model for Vibrio Cholerae (V. Cholerae) in a closed environment is considered, with the aim of investigating the impact of climatic factors which exerts a direct influence on the bacterial metabolism and on the bacterial reservoir capacity. We first propose a V. Cholerae mathematical model in a closed environment. A sensitivity analysis using the eFast method was performed to show the most important parameters of the model. After, we extend this V. cholerae model by taking account climatic factors that influence the bacterial reservoir capacity. We present the theoretical analysis of the model. More precisely, we compute equilibria and study their stabilities. The stability of equilibria was investigated using the theory of periodic cooperative systems with a concave nonlinearity. Theoretical results are supported by numerical simulations which further suggest the necessity to implement sanitation campaigns of aquatic environments by using suitable products against the bacteria during the periods of growth of aquatic reservoirs.

Managing too little and too much water: Robust mine-water management strategies under variable climate and mine conditions

Mine-water managers need tools to guide robust management strategies that can address the challenges of climate-influenced water scarcity and unregulated discharge. We aimed to identify those factors driving the risks of insufficient water supply for mine production and unpermitted discharge of mine-affected water in a way that is robust to heterogeneity between extreme climatic variability and mine sites. Using 16 coal mines in the Bowen Basin of Queensland, Australia, as a case study, we combined a model of complex mine-water management systems (C-HSM) with global sensitivity analysis (eFAST) to identify influential mine-water management factors. Comprehensive model diagnostics for the 16 mine-water systems under three climate conditions revealed that the uncertainty of key mine-water management indicators, and the contributions of model input parameters differed substantially between climate conditions and mine sites. We then applied four criteria from decision theory into the total sensitivity effects produced by the eFAST method, and developed sensitivity indicators that were robust to heterogeneity between climates and mine sites. These sensitivity indicators provide mine-water managers with options to guide the development of effective management strategies and the collection of additional information based on their own risk preference. While our results indicate some general management strategies that will be robust under multiple conditions, we caution that mine-water managers’ experience in dealing with challenges caused by too little and too much water cannot be blindly transplanted from one mine to another, or from one climate condition to another.

Incorporating deep uncertainty into the elementary effects method for robust global sensitivity analysis

Internally-consistent scenarios are increasingly used in social–ecological systems modelling to explore how a complex system might be influenced by deeply uncertain future conditions such as climate, population, and demand and supply of resources and energy. The presence of deep uncertainty requires model diagnostic techniques such as global sensitivity analysis to provide reliable diagnostic insights that are robust to highly uncertain future conditions. We extended the elementary effects method of Morris, which is widely used to screen important model input factors at low computational cost, by incorporating deep uncertainty via the use of scenarios, and evaluated its potential as a robust global sensitivity analysis approach. We applied this robust elementary effects (rEE) method to the highly-parameterised Australian continental Land Use Trade-Offs (LUTO) model—a complex, non-linear model with strong interactions between parameters. We compared rEE sensitivity indicators with robust global sensitivity analysis (RGSA) indicators based on the variance-based eFAST method that imposes relatively high computational demand. We found that the rEE method provided a good approximation of the main effects and was effective in screening the most influential model parameters under deep uncertainty at a greatly reduced computational cost. However, the rEE method was not able to match the accuracy of the eFAST-based method in identifying the most influential parameters in the complex LUTO model based on their total effects. We conclude that the rEE method is well-suited for screening complex models, and possibly for efficient RGSA of models with weak interaction effects, but not for RGSA of complex models. Despite its limitations, rEE is a valuable addition to the robust global sensitivity analysis toolbox, helping to provide insights into model performance under deep uncertainty.

Is pneumoperitoneum the terra ignota in ultrasonography?

In most cases, pneumoperitoneum is caused by gastrointestinal perforation, which usually requires surgical treatment. Many authors believe that ultrasound imaging of pneumoperitoneum is at least as effective as conventional radiography, or even that its efficacy is superior. In such a situation, it is imperative to make this modality one of the main tools in the diagnostic arsenal of emergency medicine. This is the main aim of this paper. First, ultrasound anatomy of so-called thoracic-abdominal border is discussed. The equipment requirements emphasize that the diagnostic process can be conducted with the simplest portable US scanner, even without the Doppler mode. The technique of a US examination, the aim of which is to detect, free air in the peritoneal cavity is also simple and conducted with the patients lying down, either in the supine or lateral position. A convex transducer with the frequency of 3.5–5 MHz is applied above the lower intercostal spaces on the right and left side, to the epigastric region below the xiphoid process and in various sites of the abdominal wall. The most effective examination, however, is conducted in the left lateral position via the right intercostal spaces. The differential diagnosis on the right side under the diaphragm should include the presence of a subdiaphragmatic abscess with gas and a hepatic abscess with a similar content as well as transposition of the colon in between the diaphragm and the liver (Chilaiditi syndrome). It seems that the inclusion of a US examination to the E-FAST method in order to detect free gas in the peritoneal cavity is justified since it is a sign of gastrointestinal perforation in numerous cases, and is clinically as relevant as the presence of free fluid.

Enhance Derivative Design Considering Global Sensitivity of Design Parameters

An engineering product design considers derivatives to reduce the life cycle cost and to increase the efficiency on operation when it has new demands. The proposed design process in this study obtains derivative designs based on sensitivity of design variable. The efficiency and accuracy of the derivative design process can be enhanced by implementing global sensitivity analysis. Sensitivity analysis sensors the design variables accordingly and variables with low sensitivity for objective function can be neglected, since computational effort and time is not necessary for a design with less priority. In this research, e-FAST method code for global sensitivity analysis module was developed and implemented on Multidisciplinary Design Optimization (MDO) problem. The wing design was considered for MDO problem that used aerodynamics and structural disciplines. The global sensitivity analysis method was applied to reduce the number of design variables and Collaborative Optimization (CO) was used as MDO method. This research shows the efficiency of reduction of dimensionality of complex MDO problem by using global sensitivity analysis. In addition, this result shows important design variables for design requirement to student when they solving design problem.

EFAST analysis applied to a PA model for a generic HLW repository in clay

This paper contributes to the investigation whether sophisticated methods, i.e., the EFAST method are suitable for use in long-term safety assessments of geological repositories for radioactive wastes and also whether they provide deeper insight into a repository system than less sophisticated methods such as rank-based regression or correlation or non-parametric methods, scatterplots or CSM plots. A generic test case for a HLW repository in a clay formation was selected. Despite the skewed and heavily tailed distribution of the model output, the EFAST results were surprisingly good compared to results previously obtained for a repository in rock salt. The important difference between the PA models in clay and salt is that the former produces a less skewed and less scattered distribution of the annual dose than the latter. As a result, the variance of the model output and the sensitivity indices are more stable. For the considered model, the EFAST method yields quantitative information about the parameter importance that cannot be obtained using linear regression, correlation or graphical methods. It is therefore a valuable tool, especially in combination with other sensitivity analysis methods.

EFAST Analysis Applied to a PA Model for a Generic HLW Repository in Clay

In this paper we investigate whether the EFAST method is suitable for use in long-term safety assessments of geological repositories for radioactive wastes. A generic test case for a HLW repository in a clay formation was selected. Despite the skewed and heavily tailed distribution of the model output, the EFAST results were surprisingly good compared to results previously obtained for a repository in rock salt. The important difference between the PA models in clay and salt is that the former produces a less skewed and less scattered distribution of the annual dose than the latter. As a result, the variance of the model output and the sensitivity indexes are more stable.