Initial Input Values Research Articles

Improved General Polarimetric Model-Based Decomposition for Coherency Matrix

A representative general polarimetric model-based decomposition framework was proposed by Chen et al., which implements a simultaneous full-parameter inversion by using complete polarimetric information and solves several limitations in previous decomposition methods. However, there are still shortcomings in Chen’s work. Firstly, only the real part of the parameter β in the generalized surface scattering model is considered. Secondly, inappropriate initial input values may lead to local optima in the nonlinear least squares optimization algorithm. Thirdly, the volume scattering component is underestimated in the volume scattering-dominated scene, but overestimated in buildings with large orientation (LOB) areas. Finally, nonlinear optimization is time-consuming computationally. To overcome those issues, an improved generalized polarimetric model-based decomposition method is proposed in this paper. The imaginary part of the parameter β is incorporated into the decomposition framework of the proposed method. Ingeniously utilizing the internal relationship in the generic equations composed of coherent matrix elements, the model parameters can be inversed by simplifying the nonlinear equations to linear equations. Therefore, compared with Chen’s method, the proposed method does not rely on the initial input values, and improves the computational efficiency. In addition, a hierarchical decomposition scheme is presented to solve the problem of underestimation or overestimation of volume scattering component mentioned above. The performance and advantages of this method are evaluated with L-band and C-band polarimetric synthetic aperture radar (PolSAR) data sets. Comparison studies are carried out with other model-based decomposition methods, demonstrating that the proposed method can further improve decomposition performance, especially in LOB areas.

Modeling HTS non-insulated coils: A comparison between finite-element and distributed network models

High-temperature superconducting (HTS) non-insulated (NI) coils have the unique capability to bypass current through conductive turn-to-turn contacts, mitigating the possibility of a catastrophic failure in the event of a quench. However, this turn-to-turn conductivity leads to a significant increase in the coil decay/charging time constant. To understand this phenomenon, several modeling techniques have been proposed, including the lumped and distributed network (DN) circuit models, and more recently the finite-element (FE) models. In this paper, the decay results obtained from modeling HTS NI pancake coils using both a DN model and a 2D FE model approach are evaluated and compared. Steady-state fields, and transient charging and decay behaviors are calculated with each model and the results compared. Key differences are highlighted, including the computation speed and the capturing of various physical phenomena. Both models exhibit non-exponential decay during initial coil discharge due to current redistribution between the inner and outer turns. In addition, the FE model exhibits other effects arising from current redistribution in both the radial and axial directions, including remanent magnetization, and variation of the “apparent total inductance” during charging. Simulations of sudden discharge have also been analyzed using the common “lumped circuit” formula. This shows that extracted values for the apparent surface contact resistance between coil windings can differ by more than a factor of 5 from the initial input value. Our results confirms the optimal choice of architecture for future NI coil models and emphasize that caution should be exercised when interpreting experimental results using the lumped circuit approach.

Fast Derivation of Contact Binary Parameters for Large Photometric Surveys

Thanks to an enormous release of light curves of contact binaries, it is a challenge to derive the parameters of contact binaries using the Phoebe program and the Wilson–Devinney program with the Markov chain Monte Carlo (MCMC) algorithm. In this paper, we use neural network (NN) and MCMC algorithm to derive the parameters of contact binaries. The fitting of models is still done with the MCMC algorithm, but that the neural network is used to establish the mapping relationship between the parameters and the light curves generated beforehand by Phoebe. The NN model is trained with a set of Phoebe-generated light curves with known input parameters, and then combined with the MCMC algorithm to quickly obtain the posterior distribution of the parameters. Two NN models without and with the influence of third light are established, which can generate light curves with 100 points faster than Phoebe by about four orders of magnitude under the same running condition. In addition, the two models can generate the light curves with an error of less than a millimagnitude. The feasibility of NN and MCMC algorithm is also verified by the synthetic light curves generated by Phoebe and the light curves from Kepler survey data. NN and MCMC algorithms can quickly derive the parameters and the corresponding parameter errors of contact binaries from sky survey. These parameters can also be used as more precise initial input values for the objectives of individual detailed studies.

An accelerated approach for mechanistic model based prediction of linear gradient elution ion-exchange chromatography of proteins

With growing demands for therapeutic monoclonal antibodies, in silico downstream process development based on mechanistic modeling of chromatography separation process is being increasingly used for process optimization and process characterization. Application of mechanistic modeling in biopharmaceutical industry has been sparse due to the significant investment of time and resources that are required for performing model calibration. Mechanistic modeling of the chromatography process involves a large number of mass transport and binding parameters and their initial input values are required for simulations. These input values of column parameters can be easily obtained either from experiments or from empirical correlations available in literature. On the other hand, obtaining the model input valves for binding kinetic parameters is usually a cumbersome process as it involves performing batch experiments which are not only tedious but also require significant quantities of purely isolated main product and its related impurities, which is challenging as the product related impurities are typically present in smaller quantities and hence are difficult to obtain as pure species. In the present work, a mechanistic model that is based on the general rate model coupled with extended Langmuir binding model has been used for prediction of linear gradient elution peaks of monoclonal antibody on cation exchanger chromatography. The present work describes an accelerated approach for obtaining the input values for binding kinetic parameters in the extended Langmuir binding model from the two Yamamoto coefficient A and B values obtained by Yamamoto method directly from the model calibration linear gradient elution runs of different gradient slopes and at low to moderate protein loadings. The equations that can relate the two coefficients to the extended Langmuir model equation binding kinetic parameters were derived. Therefore, once A and B are determined, the binding kinetic parameter values were determined straightforward, thereby avoiding the problem of multiple solutions for the model parameters. The estimated binding parameters were successfully validated from isocratic elution experiments performed at low loading. What we demonstrate is that the proposed approach allows us to estimate binding kinetic parameters in a significantly more efficient and accelerated manner than presently used approaches, thereby accelerating development and implementation of mechanistic modeling for process chromatography.

A Two-Step Projected Iterative Algorithm for Tropospheric Water Vapor Tomography

The tropospheric tomography is an ill-posed inversion problem due to the sparsity of Global Navigation Satellite Systems (GNSS) stations and the limitation on the projection angles of GNSS signals, which in turn affects the stability and robustness of the tomographic solution. To address this, a new tomographic algorithm, named two-step projected iterative algorithm (TSPIA), is proposed. The wet refractivity (WR) field was constructed in two steps: first, an iterative preprocessing for the initial input values was performed, then its resultant solution was input into the projected iterative method, in which a hypothesis convex set was constructed to constrain the reconstruction based on the classical algebraic iterative reconstruction (AIR) methods. In addition, a two-dimensional normalized cumulative periodogram (2D-NCP) termination criterion was investigated since the traditional criteria for judging the convergence of iterations use pre-fixed empirical thresholds, which may lead to excessive iterations and need complicated work. The TSPIA was tested using GNSS data in Hong Kong over a wet period and a dry period. Statistical results showed that, compared to the classical AIR methods, the accuracy of the reconstructed WR field of the TSPIA were improved by about 10% and 15% when radiosonde and ECMWF data were used as the reference, respectively. Moreover, experiments for the proposed 2D-NCP criterion demonstrated noticeable computational efficiency. These results suggest that the new approaches proposed in this study can improve the performance of the iterative methods for GNSS tropospheric tomography.

Robust integral of sign of error‐based distributed flocking control of double‐integrator multi‐agent systems with a varying virtual leader

AbstractThis article investigates the flocking control problem of double‐integrator multi‐agent systems with a virtual leader subject to unknown external disturbances. A robust integral of sign of error (RISE) based control method is leveraged to design a distributed flocking controller with advantages of zero initial input value and continuous control input. By means of a new second‐order differential virtual potential field function, and the navigational feedback from a virtual leader, the proposed flocking controller assures agents of velocity consensus with the virtual leader and a quasi‐lattice formation within a circular neighborhood centered on the virtual leader. Moreover, this algorithm guarantees collision avoidance and connectivity preservation of a proximity‐induced communication topology. Numerical simulations of the algorithm are provided to illustrate the effectiveness of the proposed flocking algorithm.

Analysis on the stiffness iteration of segmental joints in segmental linings: Method and sensitivity analysis

In current structural analyses on segmental linings, the bending stiffness of segmental joints is usually treated as a constant, which results in a deviation in the calculated internal forces and deformation. In view of this, a finite element model of segmental linings is established using one ring and two half rings. An iterative algorithm is designed with a 3D curved surface of bending stiffness for the segmental joint, obtained from a series of full-scale tests under different axial force and bending moment cases. The rational convergence criteria for the iterative algorithm are recommended by evaluating the convergence efficiency of the iterative algorithm. Moreover, the influence of load magnitude and initial value of bending stiffness, as well as the changing laws of structural internal forces and deformation with the assembly angles, are presented and analyzed. The results show that with the same load, the convergence of the iterative algorithm in staggered-jointed assembly structures (STGS) is better than that of straight-jointed assembly structures (STRS), owing to its greater overall stiffness. The initial input value of bending stiffness has no effect on the convergence of the proposed iterative algorithm, and generally the convergence performance in STGS is better than that in STRS. In STRS, the bending moment is most sensitive to the changes of assembly angles, while in STGS the assembly angles have great influence on both the bending moment and structural displacement. Without the stiffness iteration, the maximum differences for maximum axial force, bending moment, and displacement under different assembly angle in STRS are 11.7%, 31.9% and 22.3%, respectively, and that differences in STGS are 10.4%, 59.3% and 35.1%, respectively. With the stiffness iterative method, the increase amplitude of the maximum axial force, the maximum bending moment, and the maximum displacement in STRS and STGS are 50.0%, 317.4%, 77.1% and 41.9%, 459.3%, 156.5%, respectively, indicating that changing the assembly angles is a rational way to control the internal structural forces and deformations.

Elastic properties assessment in the multiferroic BiFeO3 by pump and probe method

We have performed elasticity measurements in the bulk multiferroic BiFeO3 (BFO) using acoustical pump and probe spectroscopy. The sound velocities of the (quasi)-longitudinal and two (quasi)-transverse acoustic waves along three independent directions of the (110) surface have been measured. Moreover, one surface wave and one longitudinal wave propagating perpendicular to the surface have been detected. Based on initial input values of the six independent Cij elastic constants determined by our density functional theory calculations and our eleven experimental velocities, the numerical resolution of the acoustic equations allows us to determine all the Cij elastic constants of BFO. The propagation direction dependence of volume and surface waves phase velocities allows the unambiguous assignment of the waves and, hence, the polarization of phonons.

Use of Remote Sensing Tools to Measure a Fluvial Geomorphic Design-Input Parameter for Land Reclamation

Fluvial geomorphic approaches for reclamation landform design have been applied since 2000, mostly in mined lands, as an alternative to conventional landform design methods. Those approaches aim to reconstruct mature landforms and drainage networks that would develop within a natural catchment, after thousands of years of work performed by geomorphic processes. Some fluvial geomorphic design methods take specific measurements from natural and stable reference areas for initial input values for reclamation design. Valid reference areas can be difficult to find, can be in highly anthropized environments, or may be difficult to access. This paper evaluates the use of remote sensing tools to measure morphometric parameters in upper sections of agricultural land catchments considered for use as reference areas. The ridge to head of channel distance (Xrh) was the parameter of interest. We used land surface profiles developed from LiDAR (Laser Imaging Detection and Ranging) data and planimetric measurements from orthoimages to estimate Xrh. The results obtained by the two methods were encouraging but showed a significant difference. Ground truthing showed that ploughing obliterated between 19.5 and 22.4 m (on average) of the headwater section of first-order channels, reducing the channel length by 15.1 to 32.4%. Using a greater Xrh value than appropriate for near steady-state conditions as a design input for a geomorphic reclamation project would be expected to result in active erosion processes in the constructed reclamation to regain their missing channel length. We recognize the advantages and limitations of remote sensing methods for measuring the morphometric parameters of the landform relief design inputs. We show how these tools may be used to help select and prioritize reference areas, and warn about the use of disturbed landscapes as reference areas to assure the geomorphic stability of the constructed reclamation designs.

Proving expected sensitivity of probabilistic programs with randomized variable-dependent termination time

The notion of program sensitivity (aka Lipschitz continuity) specifies that changes in the program input result in proportional changes to the program output. For probabilistic programs the notion is naturally extended to expected sensitivity. A previous approach develops a relational program logic framework for proving expected sensitivity of probabilistic while loops, where the number of iterations is fixed and bounded. In this work, we consider probabilistic while loops where the number of iterations is not fixed, but randomized and depends on the initial input values. We present a sound approach for proving expected sensitivity of such programs. Our sound approach is martingale-based and can be automated through existing martingale-synthesis algorithms. Furthermore, our approach is compositional for sequential composition of while loops under a mild side condition. We demonstrate the effectiveness of our approach on several classical examples from Gambler's Ruin, stochastic hybrid systems and stochastic gradient descent. We also present experimental results showing that our automated approach can handle various probabilistic programs in the literature.

Effectiveness assessment of ship navigation safety countermeasures using fuzzy cognitive maps

The fuzzy cognitive map method is adopted to construct the systematic mapping relationship between ship navigational risk factors and safety level for assessing the effectiveness of ship navigation safety countermeasures. The proposed approach integrates fuzzy inference system and evidential reasoning to convert initial input values of variables and obtain the strength of interconnections, respectively. Non-linear Hebbian learning algorithm is employed to refine the model. The constructed model is then applied with an illustrative case study associated with the middle stream region of the Yangtze river, where the current safety situation and several scenarios for improving navigational safety in the future are evaluated. The logicality and robustness constructed model and the assessing results are validated by applying sensitivity analysis. Through this research, it is found that the proposed method has the characteristics of high efficiency, lightweight and stability, which simulates the safety dynamics of the ship navigational system intuitively like the mode of natural thinking. This work provides an alternative for the shipping safety decision maker to understand the navigation safety status and control the evolving trend of it for a foreseeable period.

Evaluation of retrieval methods of daytime convective boundary layer height based on lidar data

AbstractThe atmospheric boundary layer height is a basic parameter in describing the structure of the lower atmosphere. Because of their high temporal resolution, ground‐based lidar data are widely used to determine the daytime convective boundary layer height (CBLH), but the currently available retrieval methods have their advantages and drawbacks. In this paper, four methods of retrieving the CBLH (i.e., the gradient method, the idealized backscatter method, and two forms of the wavelet covariance transform method) from lidar normalized relative backscatter are evaluated, using two artificial cases (an idealized profile and a case similar to real profile), to test their stability and accuracy. The results show that the gradient method is suitable for high signal‐to‐noise ratio conditions. The idealized backscatter method is less sensitive to the first estimate of the CBLH; however, it is computationally expensive. The results obtained from the two forms of the wavelet covariance transform method are influenced by the selection of the initial input value of the wavelet amplitude. Further sensitivity analysis using real profiles under different orders of magnitude of background counts show that when different initial input values are set, the idealized backscatter method always obtains consistent CBLH. For two wavelet methods, the different CBLH are always obtained with the increase in the wavelet amplitude when noise is significant. Finally, the CBLHs as measured by three lidar‐based methods are evaluated by as measured from L‐band soundings. The boundary layer heights from two instruments coincide with ±200 m in most situations.

Prediction of Welded Joint Strength in Plasma Arc Welding: A Comparative Study Using Back-Propagation and Radial Basis Neural Networks

Welding input parameters such as current, gas flow rate and torch angle play a significant role in determination of qualitative mechanical properties of weld joint. Traditionally, it is necessary to determine the weld input parameters for every new welded product to obtain a quality weld joint which is time consuming. In the present work, the effect of plasma arc welding parameters on mild steel was studied using a neural network approach. To obtain a response equation that governs the input-output relationships, conventional regression analysis was also performed. The experimental data was constructed based on Taguchi design and the training data required for neural networks were randomly generated, by varying the input variables within their respective ranges. The responses were calculated for each combination of input variables by using the response equations obtained through the conventional regression analysis. The performances in Levenberg-Marquardt back propagation neural network and radial basis neural network (RBNN) were compared on various randomly generated test cases, which are different from the training cases. From the results, it is interesting to note that for the above said test cases RBNN analysis gave improved training results compared to that of feed forward back propagation neural network analysis. Also, RBNN analysis proved a pattern of increasing performance as the data points moved away from the initial input values.

유한요소해석을 이용한 차대차 측면충돌에 대한 연구

The deformed degree of car body varies largely with the collision part from side collision of car-to-car. In case of deformation of car body caused by collision, the movement is different as speed energy changes to strain energy. Generally, in the analysis of traffic accident, the movement of car after the collision is analyzed by law of conservation of motion and the error of energy absorption rate along the deformation of car body can be calibrated by inputting coefficient of restitution, but it is current situation that coefficient of restitution applied by referring to the research results of forward collision and backward collision because the research results of side collision is rare. Vehicle model of finite element method applied by structure of car body and materials of each component was analyzed by explicit finite element method, and coefficient of restitution and collision detection time along contact part of side collision was drawn by analyzing the results. Analysis result acquired through the law of conservation momentum by applying finally-computed coefficient of restitution and crash detection time compared to collision result of actual vehicle. As a result, the reliability of analysis was higher than the existing analysis method were acquired when applying the drawn initial input value that used finite element method analysis model.

2D CPITD method for extracting attenuation constant of longitudinally invariant lossy transmission lines

Owing to the fact that the conventional compact two-dimensional (2D) precise integration time-domain (CPITD) method ignores the attenuation along the propagation direction for lossy invariant transmission lines, the calculation results are unsatisfactory. To extract the exact attenuation constant, a novel CPITD method that considers the attenuation constant along the propagation direction and describes an iterative process to seek out the attenuation constant is proposed. Compared with previous research related to the compact 2D finite-difference time-domain (CFDTD) method, the analytical or approximate analytical solution of the attenuation constant as the initial input value is used followed by the golden division method to find the interval of the exact attenuation constant in the iterative process. Numerical experimentations validate that the results of the novel method are much more accurate than those of the conventional CPITD method. Furthermore, the proposed method is of higher computational efficiency than the CFDTD method.

Influence of stone column installation on settlement reduction

The paper presents numerical simulations investigating the settlement reduction caused by stone columns in a natural soft clay. The focus is on the influence of the soft soil alteration caused by column installation. A uniform mesh of end-bearing columns under a distributed load was considered. Therefore, the columns were modelled using the “unit cell” concept, i.e. only one column and the corresponding surrounding soil in axial symmetry. The properties of the soft clay correspond to Bothkennar clay, which is modelled using S-CLAY1 and S-CLAY1S, which are Cam clay type models that account for anisotropy and destructuration. The Modified Cam clay model is also used for comparison. Column installation was modelled independently to avoid mesh distortions, and soft soil alteration was directly considered in the initial input values. The results show that the changes in the stress field, such as the increase of radial stresses and mean stresses and the loss of overconsolidation, are beneficial for high loads and closely spaced columns but, on the contrary, may be negative for low loads, widely spaced columns and overconsolidated soils. Moreover, whilst the rotation of the soil fabric reduces the settlement, in contrast the soil destructuration during column installation reduces the improvement.

Prediction of Methyl Bromide Flux from Area Sources Using the ISCST Model

AbstractGrowing concern about atmospheric exposure of humans to pesticides has led to increased air monitoring in California. Air monitoring data typically consist of measurements made downwind from point or area sources. The utility of monitoring at fixed stations is limited for establishing buffer zones to protect neighboring populations from pesticide exposure. A modeling approach designed to use these data would provide the flexibility needed to establish buffer zones. The Industrial Source Complex Short Term (ISCST) model is a gaussian plume dispersion model that predicts air concentrations around point or area sources using emission rates (flux) and meteorological conditions as model inputs. The flux data, however, are typically not collected in the field nor available in the literature. In order to use the field data currently available, we developed a procedure using methyl bromide (MeBr) concentrations around two area sources and the ISCST model, to back‐calculate flux. In addition, MeBr flux was measured concurrently by cooperators conducting an independent study. Air concentrations, together with actual meteorological data, were used as inputs to the ISCST model. Flux of MeBr was then back‐calculated using a two step process: (i) an arbitrary flux value of 100 µg m−2 s−1 was used as an initial input value. Resultant air concentrations predicted by the model were then regressed on air concentrations measured offsite and (ii) the resultant regression coefficient was then used to adjust the arbitrary flux to a back‐calculated flux. Using another regression analysis, back‐calculated and measured flux rates were found to be significantly correlated, indicating this approach may be suitable for indirect estimation of flux. Implications for the use of this method in establishing buffer zones designed to protect human health are discussed.

The application of fuzzy logic to JPEG

To achieve the efficiency and automatic control, a fuzzy controller to incorporate with the JPEG lossy model is proposed. The simulation results based on USC 15 pictures indicate that this JPEG model equipped with the designed fuzzy controller is insensitive to the given initial input values, that is, (with the help of fuzzy controller) this JPEG can always find the proper values of inputs for desired distortion ratio even though the relation of input parameters and the output distortion ratio is not known. In addition, the effect of different defuzzification techniques to accuracy and convergence speed is studied as well. >