Method For Determination Of Parameters Research Articles

Advanced Bayesian-Inspired Multilayer Effective Parameter Determination Method for Automated ANN Model Generation of Microwave Components

Advanced Bayesian-Inspired Multilayer Effective Parameter Determination Method for Automated ANN Model Generation of Microwave Components

Solutions of crack constraint parameter in 3D models −− II: Through T-stress

To more accurately analyze the crack front fields, especially under the low constraint conditions which are more common in practical engineering structures, two-parameter approaches (e.g. J-A(A2), J-Q, etc.) are proposed. Currently, no theoretical solutions of the constraint parameters (e.g. A(A2), Q, etc.) in two-parameter approaches are available. Meanwhile, numerical methods for constraint parameter determination are not practical because of significant resource and time consumption, especially for 3D solid models or engineering structures. Therefore, theory and formulae for the estimation of constraint parameter A in 3D solid models are developed in the current work based on T-stress, so as to make it possible to apply two-parameter approaches in practical engineering structures under normal working condition. Two actual structures are used to validate the engineering application of the developed estimate method and formulae.

Micro-scale crystallization thermodynamics study of typical energetic compounds integrating optofluidics and machine learning

With the aim of investigating the changing law of crystallization driving force of typical energetic compounds under micro-scale crystallization conditions, a thermodynamic parameter determination method based on optofluidics was proposed. Aimed at nitro, nitramine and nitrate explosives in energetic compounds, hexanitrostilbene (HNS), cyclotetramethylene tetranitramine (HMX) and pentaerythritol tetranitrate (PETN) were selected as representatives, the solubility of the three kinds of energetic compounds in their respective commonly used solvents (HNS: in DMF, DMSO, NMP; HMX: in DMF, DMSO, CYC; PETN: in DMF, DMSO, EAc) at different temperatures were determined. Furthermore, microfluidics and machine learning were combined, the solubility data of the explosives were processed using BP neural network. Moreover, the metastable zone widths of HNS, HMX and PETN in each solvent were determined using on-line Raman technique. Additionally, crystalline thermodynamic parameters such as solid–liquid interfacial tension, crystal surface entropy factor, enthalpy of dissolution and etc. were calculated for each system.

Multi-criteria group emergency decision-making method considering knowledge granularity

Emergencies are typically characterized by abruptness, time urgency, and complexity, which give rise to challenges such as incomplete information, compromised information effectiveness, and reduced efficiency. To address these issues, this study proposes a novel multi-criteria group emergency decision-making (MCGEDM) method considering knowledge granularity. Within the framework of a hierarchical criterion system (HCS), decision makers' (DMs') judgment information is extracted using belief distributions (BDs) on knowledge chunks, based on the conceptualization of knowledge granularity. This enables DMs to make judgments as effectively as possible, thereby improving efficiency in terms of time and enhancing the effectiveness of information. The generalized combination (GC) rule is applied for individual information fusion within basic nests, demonstrating internal revision and complementation of information. Automatic parameter determination methods are proposed to enhance the effectiveness of information and the efficiency of MCGEDM. Finally, the proposed method is demonstrated through a simulative case of an oil spill emergency, and the subsequent sensitivity analysis and comparisons verify its feasibility and effectiveness.

UAV-based LiDAR Bathymetry at an Alpine Mountain Lake

Abstract. LiDAR bathymetry provides an efficient and comprehensive way to capture the topography of water bodies in shallow water areas. However, the penetration depth of this measurement method into the water column is limited by the medium water and water turbidity, resulting in a limited detectability of the bottom topography in deeper waters. An increase of the analyzable water depth is possible by the use of extended evaluation methods, in detail full-waveform stacking methods. So far, however, this has only been investigated for water depths of up to 3.50 m due to water turbidity. In this article, the potential of these extended data processing methods is investigated on an alpine mountain lake with low water turbidity and thus high analyzable water depth. Compared to the standard data processing, the penetration depth could be significantly increased by 58%. In addition, methods for depth-resolved water turbidity parameter determination on the basis of LiDAR bathymetry data were successfully tested.

Initial structure parameters determination and aberration optimization method for ultra-wide angle optical system with large aperture

Initial structure parameters determination and aberration optimization method for ultra-wide angle optical system with large aperture

Rapid analysis method for process parameter determination of transient thermal tensioning during welding buckling distortion mitigation

The effect of transient thermal tensioning (TTT) on mitigating buckling distortion is significantly influenced by the process parameters. TTT and conventional welding (CW) experiments were both performed on butt welded joints using induction heating as an additional heat source. The thermal elastic plastic (TEP) FE simulation was then carried out with consideration of material nonlinearity and geometrical nonlinearity to investigate the temperature, buckling distortion fields of the butt welded joints. A good agreement between computational results and the measurement was represented, and the buckling distortion of the butt welded joints with TTT was much smaller than that with CW. Based on the validated FE simulation, the sensitivity of process parameters (amount, sizes, tensioning temperature Ttmax, locations of induction heating) for TTT was examined in detail. The results show that amount and sizes exerted an evident impact on buckling distortion mitigation, which were determined by equipment. Tensioning temperature Ttmax and the offset from weld centerline d1 are more important parameters on effectively mitigating welding buckling distortion of thin plate structures than the offset from welding arc d2. Through optimizing Ttmax and d1, buckling distortion of examined butt welded joint can be reduced by more than 80 %. Moreover, a method for determining the process parameters of TTT towards engineering applications was proposed. Firstly, the amount and sizes of additional heat sources are maximized per the available equipment. Secondly, Ttmax is recommended as yield temperature to implement TTT and d1 is optimized through an experiment or TEP FE simulation. Eventually, the offset from welding arc d2 is further optimized when the manufacturing precisions are not reached.

Regional features of camel milk composition and properties in the Republic of Kazakhstan

Camel milk, renowned for its distinctive nutritional qualities, has captured the interest of scientific researchers due to its potential health benefits. This study aims to compare the biochemical composition of camel milk sourced from two distinct regions of Kazakhstan: Jetisu and Mangystou. Analytical methods were employed to achieve this objective, including gas chromatography for fatty acid analysis, chemical methods for physicochemical parameter determination, and assessment of amino acid, fatty acid, mineral, and vitamin content. In samples from the Jetisu region, protein content ranged from 3.61% to 3.70%, fat from 3.85% to 4.64%, and lactose from 4.80% to 4.85%. In comparison, samples from the Mangystou region exhibited protein content ranging from 3.65% to 3.81%, fat from 4.72% to 5.75%, and lactose from 4.21% to 4.28%. Regarding amino acid composition, Mangystou region samples contained more essential amino acids per 100 g of protein than Jetisu region samples: 41.29 g versus 38.20 g, respectively. Additionally, the Jetisu region sample contained 64.291% saturated fatty acids, while the Mangystou region sample had 62.135%, indicating differences in fatty acid composition based on geographical origin. In terms of mineral composition, camel milk from the Mangystou region exhibited higher calcium and zinc content compared to Jetisu region samples, with calcium and zinc content measured at 124.50 mg/100 g and 490.15 μg/100 g, respectively, for Mangystou samples, and 112.50 mg/100 g and 321.24 μg/100 g, respectively, for Jetisu samples. Overall, the study underscores regional variances in camel milk's biochemical composition, which can impact its nutritional and biological value. These findings provide dairy product producers in Kazakhstan with enhanced opportunities to create healthy, high-quality dairy products.

Biophysical phenotyping of single-cell based on impedance and application for individualized precision medicine

Single-cell biophysical characterization based on impedance measurement is an advantageous approach due to its label-free, high-efficiency, cost-effective and real-time capability. Biophysical phenotyping can yield timely and rich information on physiological and pathological state of cells for disease diagnosis, drug screening, precision medicine, etc. However, precise measurement on single-cell impedance is challenging, particularly hard to figure out the detailed biophysical parameters of single cell due to coupling and complexity of impedance model. Here, we propose an analytic determination method to decode single-cell electrophysiological parameters (including cell-substrate interface capacitance, cell membrane capacitance, cell membrane conductivity, and cytoplasm conductivity) from the impedances measured at optimized frequencies by using analytic solution rather than spectrum fitting. With this simple and fast analytic solution method, the physiological parameters of single cell in natural adhesion state can be accurately determined in real time. We validate this cell parameter determination method in monitoring the change of cell adhesion under hydraulic effects and exploring electrophysiological differences among MCF-7, HeLa, Huh7, and MDA-MB-231 cell lines. Particularly, we apply the approach to optimize tumor treating fields (TTFields) therapy, realizing individualized precision medicine. Our work provides an accurate and efficient approach for characterizing single-cell biophysical properties with real-time, in-situ, label-free, and less invasive advantages.

Characterization of a filamentary discharge ignited in a gliding arc plasmatron operated in nitrogen flow

A gliding arc plasmatron (GAP) is a promising warm plasma source for the use in gas conversion applications but lacks an understanding of the plasma dynamics. In this paper, the gliding arc plasma conditions of a GAP operated with nitrogen flow (10 slm) are characterized using optical emission spectroscopy (OES) and numerical simulation. A simultaneously two-wavelength OES method and Abel inversion of the measured images with a spatial resolution of 19.6 μm are applied. The collisional radiative model used in this study includes Coulomb collisions of electrons. An iterative method of plasma parameter determination is applied. The determined values of the electric field up to 49 Td and electron density up to 2.5∙1015 cm−3 fit well to the plasma parameters received with different diagnostics methods in comparable plasma sources. Additionally, the electric current, which is calculated using the determined reduced electric field and electron density, is compared with the measured one.

Modeling and free vibration analysis of bolted composite flanged cylindrical-cylindrical shells under partial bolt loosening conditions

The bolted composite coupled cylindrical shell is a common substructure in modern engineering, which may encounter the issue of local loosening conditions during service. Meanwhile, the influence of flanges on the structural vibration characteristics is often overlooked in dynamic numerical analysis. In this paper, a semi-analytical dynamic model for the bolted composite flanged cylindrical-cylindrical shell structure under arbitrary connection conditions is established, and the free vibration characteristics of locally loose structures are emphatically studied. In the model, the annular plate modeling method is developed to achieve the simulation of the flange part. To fully reflect the connection characteristics of the bolted joint, a spring surface model and the corresponding parameter determination method based on fractal contact theory are developed. The equations of motion of the structure are obtained utilizing the Lagrange equations. The accuracy of the model and its predictive ability for the vibration characteristics of the bolted composite flanged cylindrical-cylindrical shell under local loosening conditions are fully demonstrated through numerous comparisons with experimental results from other literature and modal test results obtained under various working conditions. Furthermore, the influence of the number and degree of loosening bolts on the free vibration characteristics of the structure and the coupling phenomenon between different modes are discussed. The research in this paper is expected to provide references for the design of bolted composite flanged cylindrical shell structures and the monitoring of bolt connection defects.

A parameter determination method of powder burn model based on Levenberg-Marquardt optimization

ABSTRACT The powder burn model is a mathematical model used to characterize the combustion behavior of energetic materials. In this paper, a parameter determination method for the powder burn model is proposed based on the Levenberg-Marquardt (L-M) optimization algorithm, establishing connections between internal ballistics parameters and powder burn model parameters. Taking a 4/1 single-base propellant as an example, the detailed fitting process is presented, and error analysis is conducted. The fittings of the gas state equation and reaction rate equation of powder burn model converge at the 15th and 22nd iterations, respectively. Both fittings displayed a high level of accuracy, with an R-squared value of 0.999. The comparison with the results of the closed bomb experiments demonstrates excellent agreement between pressure-time curves calculated by the powder burn model and the internal ballistics model, confirming their suitability for describing the combustion behavior of propellants. This method provides a foundation for numerically simulating the internal ballistics combustion behavior of energetic materials.

Investigation on damage creep constitutive model of rock under the coupled effect of freeze–thaw cycles and loading

AbstractThe investigation on damage creep properties of rock under freeze–thaw conditions are essential for assessing the long‐term stability of rock mass engineering in cold regions. This research analyzed the damage characteristics of rock under the coupled effect of freeze–thaw cycles and loading; the damage variable under the coupled effect of freeze–thaw cycles and loading was proposed. A damage creep constitutive model was developed, and the determination method for the model parameters was proposed. The rationality of the model was calibrated using test data, and the calculation results of the proposed model were compared with classical Nishihara model. Additionally, the research analyzed the variation of model parameters with the number of freeze–thaw cycles and discussed the damage creep mechanisms of rock under the coupled effect of freeze–thaw cycles and loading.

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.

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.