Method For Determination Of Parameters Research Articles

A Study of Measurement Modeling of Decision Trees in Machine Learning Processes

Abstract Accompanied by the rapid development of economy and science and technology, the ordinary measurement model with a single method of parameter determination and accuracy is not guaranteed, which has made it difficult to adapt to the measurement needs of complex data in industrial engineering and other systems. This study proposes a measurement model for complex data through the optimization of decision trees in the process of machine learning. Firstly, the gradient-boosting-based decision tree measurement model (GBDT) is constructed by analyzing the decision tree model, and then the model is solved. At the same time, latent variables were included in the model, SEM described the reflection relationship of explicit variables to latent variables, and the GBDT optimization model, including latent variables, was constructed by using the results of the model measurement, including latent variables. Then, for the measurement of multivariate data, the fusion convolutional network was used for image data feature extraction, and the combined measurement model with multi-source data fusion (MDF-DTFEE) was constructed on the basis of the decision tree measurement model. In the empirical analysis of the measurement model, the predicted and actual values of the model training were fitted between 4~60 mg/L and 5~45 ml/L, respectively, and its R² on the training set and test set were 0.948 and 0.886, respectively, with the RMSE lower than 1.2, and none of the MAPE exceeded 0.2. The practical application always had an error range of 1 mg/L, which is in line with the requirements. It fulfills the practical application requirements, demonstrates the practical value of the measurement model in this paper, and provides a useful solution for measuring complex data.

Multiple Parameters Determination Method of Hardening Soil Model Based on Particle Swarm Optimization

The utilization of numerical analytic techniques has become essential in evaluating the environmental consequences of excavation in foundation pits. The careful selection of suitable soil constitutive models has significant importance in this regard. The Hardening Soil (HS) model has become widely utilized in the numerical analysis of foundation pits among the several models considered. The essence of a constitutive model is in the identification and determination of its calculation parameters. The stress–strain curve is derived by conducting triaxial testing, utilizing the inherent properties of the particle swarm optimization (PSO) technique. The objective function entails quantifying the disparity between stress–strain curves obtained from various parameters and experimental curves while iteratively searching for five crucial parameters of soil‐hardening models: effective internal friction angle φ, effective cohesion, failure ratio Rf, stiffness level‐dependent power exponent, and standard triaxial‐drained test secant stiffness . The objective of this research is to create a computational software utilizing the Python programming language to execute PSO with the purpose of determining sets of five fundamental soil constitutive parameters. This research employs optimized parameters acquired from PSO to construct a numerical model for foundation pits and performs numerical computations. Accurate findings may be reached by comparing the measured deformation in the numerical simulation with that seen in actual foundation pits. The results demonstrate a high degree of consistency between the experimental curves and the five parameter combinations obtained through the PSO algorithm, with an error rate not exceeding 8.2%. Moreover, the optimized curves exhibit closer alignment with theoretical expectations. The settlement values calculated using a numerical model based on optimized parameters show only a 6.12% deviation from actual measurements while closely following the trend of the observed curve. This outcome has the potential to greatly alleviate the burden of conducting indoor tests and holds considerable practical value in engineering applications. The observable optimization impact of PSO also serves as evidence of its viability in improving soil constitutive parameters, providing new perspectives and sources of information for future progress in this domain.

Performance Study of an Autotriggered Anticollapse Fusing Hardware and Its Application on Transmission Lines Subjected to Conductor Breakage

Conductor breakage with ice load is one of the major threats to the safe operation of transmission lines. The ice load increases the unbalanced longitudinal tension, leading to failure of tower members and even progressive collapse of the transmission line. This paper proposes an autotriggered anticollapse fusing hardware (AAFH), designed to reduce the unbalanced longitudinal tension caused by conductor breakage. When the longitudinal unbalanced tension of the transmission line exceeds the threshold of the AAFH, the fused part is destroyed, and the AAFH is elongated to reduce the longitudinal unbalanced tension. First, the construction and working mechanism of the device are introduced, and a numerical model of the transmission line–AAFH system is established to verify its effectiveness. Then, a parameter determination method for unbalanced tension in the tower‐line system subjected to conductor breakage is proposed. In addition, the control performance of the device is studied. The results show that AAFH can effectively reduce the unbalanced tension induced by conductor breakage. The proposed method can predict the unbalanced tension of transmission lines, with an error within 10%. The greater the length of vertical/horizontal elongation, the better the protective effect. From a safety perspective, the AAFH should be designed according to the actual transmission line parameters to achieve an ideal control effect.

Fault detection and diagnosis for chemical processes using dynamic global–local preserving projections

AbstractMost traditional multivariate statistical monitoring methods require an assumption that the observation values at a certain moment and a past moment are statistically independent. However, in actual chemical and biological processes, the sample at a certain moment is often affected by the previous moment. Therefore, given the problem of more false alarms and poor detection ability based on the traditional principal component analysis, this article proposes a dynamic global–local preserving projections (DGLPP) algorithm. Unlike dynamic local preserving projections (DLPP) and dynamic principal component analysis (DPCA), DGLPP controls the global and local information retained in the dimensionality reduction data by introducing weight coefficients, which makes the algorithm applicable to more types of industrial processes. Moreover, new parameter determination methods are also proposed for improved detection and diagnosis. Through the improved contribution graph method, we can see the influence degree of each variable on the fault, to monitor and isolate the fault. Finally, by verifying the operation of the multivariable process and two practical cases, the results show that compared with DPCA, DLPP, and global local retained projection (GLPP) methods, the performance under this method has been significantly improved.

Parameter Determination Method in Analysis of Stratum Deformation Caused by Tunnel Excavation

Based on the analytical method of formation deformation caused by tunnel excavation proposed by Verruijt and Sagaseta, combined with the basic principles of soil mechanics and elastic mechanics, a method for determining the pending parameters required in the analysis process is proposed. This method does not require the actual measurement of deformation values in the field, and the required parameters can be determined from geological data, so as to obtain the deformation values of any points of the whole stratum. According to engineering examples, when the pending parameters are obtained by this method, the difference between the resolved value of maximum surface settlement and the measured value can be controlled within 5.0%, and the analytical results can splendidly reflect the formation deformation law caused by tunnel excavation. Further combined with the analysis of the numerical simulation results, the proposed approximation method has certain shortcomings and deficiencies, mainly in the lack of lateral constraints on the displacement. When the measured data in the field are insufficient, this method can be used to estimate the deformation, and the analysis results are slightly larger than the measured values, which is safer.

Microresonator Effective Thermal Parameters Definition via Thermal Modes Decomposition

High-Q optical microresonators are particularly efficient practical tools of modern applied optics and photonics. Using them, one inevitably faces the problem of thermal effects. Accurate determination of effective thermal parameters of high-Q microresonators (effective thermal relaxation rate and optical absorption rate) is of particular importance for developing microresonator-based devices. Our investigation looks into diverse methodologies to estimate these effective parameters for such systems, ultimately revealing a divergence between the commonly employed simplified model, the direct numerical approach, and classical analytical formulas. We introduce a novel approach to calculate effective parameters based on the decomposition of the thermal field into microresonator thermal modes, which inherently considers the intricate geometry and material anisotropy inherent in microresonators, as well as the influence of external conditions. The method for the accurate determination of the effective thermal parameters of the microresonator for corresponding thermal modes is developed. As a result of applying this method, we modified the classical approach for the simulation of thermal effects in optical microresonators for better agreement with the numerical simulations. By accounting for the complexities of microresonator shapes, material properties, and external factors, our proposed method contributes to a more accurate understanding of thermal dynamics and enhances the predictive capabilities of simulations for these systems. We demonstrated the application of this method on the example of integrated microring resonators, but it can be used to analyze thermal effects in other microresonator platforms.

Reliability of Methods for Determination of Stress History Parameters in Soils

Abstract Stress history acquired by any cohesive soil influences, to a large extent, three groups of fundamental properties indispensable in geotechnical design i.e. state of soil, shear strength, and stiffness characteristics. The basic stress history parameter (from which other parameters are derived) determined directly from laboratory tests is a preconsolidation stress σ′ p. Since the first method proposed by Casagrande in 1936, value σ′ p is determined in the oedometer test as a border between overconsolidated (OC) and normally consolidated (NC) zones. Approach based on division between predominantly elastic, (recoverable) strain, and plastic (irrecoverable) strain is a main principle of several methods of σ′ p determination, which have been proposed over the past eighty-six years. Accumulated experiences have revealed that any laboratory procedure based on the oedometer test does not provide realistic value of preconsolidation stress, especially in heavy preconsolidated soils. The major reason for that results from the fact that the mechanism responsible for natural overconsolidation is more complicated than mechanical preloading. Therefore, there is a necessity to reevaluate effectiveness of standard methods and look for another solution of evaluation yield stress σ′ Y in natural soils. This article presents the comparison between σ′ Y determined for various soils with use of standard methods based on conventional oedometer test and yield stress determined on the basis of alternative procedures. The latter are represented by various approaches as e.g. based on SHANSEP procedure or initial shear modulus and others. The most promising among these alternative methods is a new concept based on dilatancy phenomenon that takes place during shearing of a dense soil. The parameter reflecting stress history is derived from pore pressure response and is based on characteristic values of Skempton's parameter A record. Consistency of data concerning stress history parameters profile obtained for deep subsoil on the basis of various methods is shown for comparison.

Damage-coupled unified constitutive modeling of 316LN stainless steel including dynamic strain aging under various tension dwell time: A macroscopic phenomenological study

A damage-coupled unified constitutive model is developed for 316LN stainless steel based on the framework of the Abdel-Karim and Ohno model. In the modified model, a kinematic hardening coefficient related to accumulated plastic strain is introduced in the linear hardening term, and a damage coefficient is incorporated in the static recovery term. Meanwhile, the parameters of isotropic hardening and kinematic hardening are associated with the maximum plastic strain rate and plastic strain memory to describe the effects of dynamic strain aging and plastic strain memory. Additionally, the kinematic hardening coefficients and static recovery coefficients correlate with dwell time to simulate stress relaxation throughout the whole-life time. The comparison between the simulation and experimental results indicates the validity of the modified model under the conditions of low-cycle fatigue and creep-fatigue interaction. After identifying the material parameters using a combination of classic parameter determination methods and optimization algorithms, the cyclic stress response and hysteresis loops can be accurately simulated throughout the whole-life time.

The modification of Mohr-Coulomb criteria based on shape function and determination method of undetermined parameters

Rock strength criteria is a key step to estimate the stability of rock engineering, especially, the effect of intermediate principal stress on rock failure should be considered in formation at great depth. However, the mostly used Mohr-Coulomb criterion don't consider the effect of intermediate principal stress, besides, most rock mechanics laboratories do not have the ability to do true triaxial strength, the strength parameters in poly-axial strength criteria are difficult to be determined. In order to solve these problems, based on the least absolute deviation method, the square of the correlation coefficient, absolute difference and mean difference are adopted to verify the fitting effect of 10 strength criteria on 32 groups of true triaxial strength data. On this basis, the elliptical Lode angle shape function, hyperbolic Lode angle shape function, and the Lode angle shape function based on spatial slip plane are used to establish the modified MC strength criteria, which not only meets the requirements of smoothness and convexness, but also can be used widely in many geomaterials. Besides, strength parameters of the established criteria can be decided by conventional triaxial strength experiment, and the prediction accuracy of the modified MC strength criteria for the 32 groups of true triaxial strength data is better than or close to the lowest fitting error of the existing poly-axial strength criteria.

Investigation of anisotropic strength criteria for layered rock mass

Layered rock mass is a type of engineering rock mass with sound mechanical anisotropy, which is generally unfavorable to the stability of underground works. To investigate the strength anisotropy of layered rock, the Mohr-Coulomb and Hoek-Brown criteria are introduced to establish the two transverse isotropic strength criteria based on Jaeger's single weak plane theory and maximum axial strain theory, and parameter determination methods. Furthermore, the sensitivity of strength parameters (K1, K2, and K3) that are used to characterize the anisotropy strength of non-sliding failure involved in the strength criteria and confining pressure are investigated. The results demonstrate that strength parameters K1 and K2 affect the strength of layered rock samples at all bedding angles except for the bedding angle of 90° and the angle range that can cause the shear sliding failure along the bedding plane. The strength of samples at any bedding angle decreases with increasing K1, whereas the opposite is for K2. Except for bedding angles of 0° and 90° and the bedding angle range that can cause the shear sliding along the bedding plane, K3 has an impact on the strength of rock samples with other bedding angles that the specimens' strength increases with increase of K3. In addition, the strength of the rock sample increases as confining pressure rises. Furthermore, the uniaxial and triaxial tests of chlorite schist samples were carried out to verify and evaluate the strength criteria proposed in the paper. It shows that the predicted strength is in good agreement with the experimental results. To test the applicability of the strength criterion, the strength data of several types of rock in the literature are compared. Finally, a comparison is made between the fitting effects of the two strength criteria and other available criteria for layered rocks.

Improvement of DBSCAN Algorithm Based on K-Dist Graph for Adaptive Determining Parameters

For the shortcomings of an unstable clustering effect and low accuracy caused by the manual setting of the two parameters Eps and MinPts of the DBSCAN (density-based spatial clustering of applications with noise) algorithm, this paper proposes an adaptive determination method for DBSCAN algorithm parameters based on the K-dist graph, noted as X-DBSCAN. The algorithm uses the least squares polynomial curve fitting method to fit the curve in the K-dist graph to generate a list of candidate Eps parameters and uses the mathematical expectation method and noise reduction threshold to generate the corresponding MinPts parameter list. According to the clustering results of each group of parameters in the Eps and MinPts parameter lists, a stable range of cluster number changes is found, and the MinPts and Eps corresponding to the maximum K value in the stable range are selected as the optimal algorithm parameters. The optimality of this parameter was verified using silhouette coefficients. A variety of experiments were designed from multiple angles on the artificial dataset and the UCI real dataset. The experimental results show that the clustering accuracy of X-DBSCAN was 21.83% and 15.52% higher than that of DBSCAN on the artificial and real datasets, respectively. The X-DBSCAN algorithm was also superior to other algorithms through comprehensive evaluation and analysis of various clustering indicators. In addition, experiments on four synthetic Gaussian datasets of different dimensions showed that the average clustering indices of the proposed algorithm were above 0.999. The X-DBSCAN algorithm can select parameters adaptively in combination with the characteristics of the dataset; the clustering effect is better, and clustering process automation is realized.

ARTIFICIAL INTELLIGENCE APPLICATION IN PHOTOACOUSTIC OF GASES

Photoacoustic spectroscopy is a powerful, non-destructive, ultrasensitive technique that covers a wide range of applications including atmospheric monitoring, industrial, environmental, and biomedical practice. In this paper, our attention is focused on the area of artificial intelligence implementation in photoacoustic spectroscopy of gases. Artificial intelligence has been proven as a very successful, effective, and promising method for the accurate and real-time determination of photoacoustic signal parameters, related to relaxation, thermal and other physical properties of various media (i.e., for solving the inverse photoacoustic problem). To improve the sensitivity and selectivity of the photoacoustic method feedforward multilayer perceptron network is applied for real-time simultaneous determination of photoacoustic signal parameters: vibrational-to-translational relaxation time, and radius of the laser beam. Also, to solve the problem of finding optimal values of these photoacoustic parameters, metaheuristic algorithms, genetic algorithms and simulated annealing are used. The performance of artificial intelligence methods has been tested on a set of experimental signals generated in the (SF6+Ar) gas. The potential advantages and disadvantages of those methods are discussed.

A novel anisotropic deterioration mechanical model for rock ductile–brittle failure under 3D high-stress and its application

After the excavation of deep underground engineering, the three-dimensional (3D) stress state redistributes, leading to a significant change in the mechanical properties of the surrounding rock; however, the mechanical properties and parameter evolutions of rock under true triaxial stress are not clear, and theoretical mechanical models characterizing the above rock properties for surrounding rock stability analysis are very deficient. Therefore, in this research, a series of true triaxial compression tests and cyclic loading and unloading tests were carried out to investigate 3D stress-induced anisotropic behaviours, ductile–brittle characteristics and mechanical parameter evolutions. The determination methods of the mechanical parameters of Young’s modulus Ei, cohesion c, internal friction angle φ and dilation angle ψ in the rock failure process under true triaxial stresses were established, and the evolution functions of the mechanical parameters were proposed. A 3D degradation mechanical model for rock ductile–brittle and anisotropic behaviours under true triaxial stress was established. A numerical calculation program of the proposed model was implemented, and the simulation results agreed with the experimental results. The engineering application of the proposed model was further investigated with an improved index of rock fracture degree for the localized asymmetric failure of deep surrounding rock after excavation.

Softening/Hardening Damage Model and Numerical Implementation of Seabed Silt-Steel Interface in Yellow River Underwater Delta

The interaction between soil and structure is a research hotspot in ocean engineering, and the shear performance of interfaces is an essential factor affecting the bearing capacity of offshore structures. Taking the Yellow River Underwater Delta as the research area, the Softening/Hardening damage model of the silt–steel interface and the determination method of model parameters are proposed based on the statistical damage theory. Through the interface monotonic shear test under the conditions of different normal stress, roughness and water content, the shear mechanical properties and volumetric deformation laws on the silt–steel interface are analyzed, and the damage model parameters are obtained. Finally, a FRIC subroutine for the damage model was developed based on ABAQUS. The research results indicate the following: (1) The interface between silt and steel exhibits two characteristics, softening/hardening and shear shrinkage/expansion, under different conditions. Roughness significantly impacts interfacial cohesion, while water content mainly affects the internal friction angle. (2) The softening model based on the classic rock damage model can better simulate the stress–strain relationship of the silt–steel interface under high normal stress and low water content. In contrast, the hardening model based on the classic hyperbola model can better simulate the stress–strain relationship under low normal stress and high water content. The calculated results of the softening/hardening model agree with the experimental results, and the model has 7 parameters. (3) The developed FRIC subroutine can effectively simulate the nonlinear mechanical behavior of the interface between silt and steel. The research results provide a reference for exploring the stability analysis of offshore structures considering interface weakening effects.

Operational Control of Substrates and Epitaxial Layers of Silicon Carbide and Diamond by IR Spectroscopy

A set of efficient operational methods for post-growth determination of the kinetic parameters of charge carriers and impurity concentration in silicon carbide and diamond substrates and epitaxial layers, as well as layer thicknesses, by analyzing infrared (IR) reflection and absorption spectra, is presented.

Inertial Sensor-Based Estimation of Temporal Events in Skating Sub-Techniques While In-Field Roller Skiing.

The aim of this study was to test and adapt a treadmill-developed method for determination of inner-cycle parameters and sub-technique in cross-country roller ski skating for a field application. The method is based on detecting initial and final ground contact of poles and skis during cyclic movements. Eleven athletes skied 4 laps of 2.5km at low- and high-endurance intensities, using 2 types of skis with different rolling coefficients. Participants were equipped with inertial measurement units attached to their wrists and skis, and insoles with pressure sensors and poles with force measurements were used as reference systems. The method based on inertial measurement units was able to detect >97% of the temporal events detected with the reference system. The inner-cycle temporal parameters had a precision ranging from 49 to 59milliseconds, corresponding to 3.9% to 13.7% of the corresponding inner-cycle duration. Overall, this study showed good reliability of using inertial measurement units on athletes' wrists and skis to determine temporal events, inner-cycle parameters, and the performed sub-techniques in cross-country roller ski skating in field conditions.

Calibration and Sensitivity Analysis of Macro and Meso Parameters of Discrete Element Model for Coal Measure Soil

The orthogonal test sequence of the meso parameters of the discrete element model was designed by using the orthogonal test method. The calculation method of directly determining the meso parameters from the macro mechanical parameters was established by using the test simulation calculation results and the multi factor nonlinear joint inversion method. The proposed method was applied to the discrete element numerical simulation of triaxial test of coal measure soil. The results show that the numerical simulation results are in good agreement with the stress-strain curves of the triaxial test of coal bearing soil. Through error analysis, it is found that the maximum error of the partial stress peak is 5.4%, the error of the cohesion is 2%, the error of the internal friction angle is 7%, and the error is all within 10%. It verifies that the method for rapid determination of the meso parameters proposed in this paper is feasible, and provides a new idea for the calibration of the meso parameters in the discrete element numerical simulation method.

Acoustic Radiation of a Beam Subjected to Transverse Load

In this paper, the dynamic response of a Euler–Bernoulli beam subjected to transverse harmonic forces is calculated. The method of separation of variables combined with the mode shape superposition method, which includes the determination of eigenvalues, is used to define the velocity field of the beam surface. The Rayleigh integral was used to calculate the sound radiation and the beam was placed in an infinite baffle. Additional actuators are introduced in order to minimize the sound radiation, or, more specifically, the total sound power level of the vibrating beam, and their optimal position and force amplitude are determined; the conclusions were drawn from the optimization results. This paper proposes a method for faster determination of the optimal actuator parameters in order to achieve the minimum total sound power level. The validity of the obtained results is demonstrated with examples, whose solutions are compared to the results in the published literature.

Reconstructing Primary Voltages Across Inductive VTs — Part I: Methodology

Inductive voltage transformers (VTs) are the most widely used instrument transformers in power grids operating at 35 kV and below. Frequently, however, during disturbances, the secondary signals are not replicas of the primary voltages because of eddy current effects, capacitive effects, and nonlinearities. In this two-part paper, a new inverse method considering the frequency-dependent characteristics and nonlinearities is proposed to reconstruct the primary voltage from a distorted secondary signal. In Part I, the framework of the method is presented and then realized with two inverse models. An inverse black-box model is used to compensate the eddy currents and capacitive effects, and an inverse duality-derived model is used to consider the nonlinearities. Methods for model parameter determination are described. Experimental validation and analysis of the proposed method are afforded in Part II. The inverse method effectively improves the primary voltage measurement of VTs without any auxiliary high-voltage equipment. The proposed method provides accurate primary voltage waveforms of VTs during disturbances.

Design of highway pavement earthquake damage prediction method considering horizontal earthquake force

Due to the influence of geographical environment and horizontal seismic force, it is difficult to predict the seismic damage of urban highway pavement. In addition, poor engineering characteristics will cause damage to the stability of the subgrade and extremely easy to deformation. The above situation has become an important problem in highway construction. To improve the accuracy of earthquake damage prediction of highway pavement, a method of earthquake damage prediction considering horizontal seismic force is proposed. This method is based on the fuzzy comprehensive evaluation, taking the highway bridge, subgrade and pavement, roadside environment and highway tunnel as the main factors, and establishing the post-earthquake damage evaluation model of the highway system. Based on the analysis of the relevant data, the power polynomial prediction model is proposed, and the feasibility and parameter determination method of the power polynomial are analyzed. The stability of highway pavement under earthquake is predicted. The results show that the design method can predict the seismic damage of highway pavement. In addition, the proposed surface model can also simulate the settlement value and predict the settlement law.