Conventional Inverse Method Research Articles

Estimation of cable safety factors of suspension bridges using artificial neural network‐based inverse reliability method

AbstractThe design of the main cables of suspension bridges is based on the verification of the rules defined by standard specifications, where cable safety factors are introduced to ensure safety. However, the current bridge design standards have been developed to ensure structural safety by defining a target reliability index. In other words, the structural reliability level is specified as a target to be satisfied by the designer. Thus, calibration of cable safety factors is needed to guarantee the specified reliability of main cables. This study proposes an efficient and accurate algorithm to solve the calibration problem of cable safety factors of suspension bridges. Uncertainties of the structure and load parameters are incorporated in the calculation model. The proposed algorithm integrates the concepts of the inverse reliability method, non‐linear finite element method, and artificial neural networks method. The accuracy and efficiency of this method with reference to an example long‐span suspension bridge are studied and numerical results have validated its superiority over the conventional deterministic method or inverse reliability method with Gimsing's simplified approach. Finally, some important parameters in the proposed method are also discussed. Copyright © 2006 John Wiley & Sons, Ltd.

Determination of near surface refractive index of graded-index waveguides based on surface plasmon resonance

Near surface refractive index of a graded-index waveguide, which is greater than the effective index of the fundamental mode and cannot be evaluated in conventional m-line technique, is experimentally determined by employing the surface plasmon resonance technique. This nondestructive approach avoids the high degree of freedom in selecting the surface index of the profile. Subsequently, the index profile predicted in this paper are more accurate than that obtained by the conventional inverse WKB method.

A method to improve spatial resolution and smoothness of intensity profiles in IMRT treatment planning

In IMRT optimization, the size of beamlets used for optimizing the beam intensity distributions is a planner-selected parameter. The appropriate setting for the beamlet size is critical to the outcome of IMRT planning. With too small beamlets the dose calculation can be inaccurate, and the resulting intensity profiles can be unnecessarily complex and difficult to generate. Relatively simple intensity profiles can be obtained using large beamlets. However, this may compromise the conformity of the dose distribution. In this paper we present a method, in which multiple beamlet matrices displaced from each other by a shift in MLC leaf travel direction are used instead of the single beamlet matrix per beam in a conventional method, to achieve finer spatial resolution for the intensity distribution than the given beamlet size. Two test cases were used to assess the method by the resultant DVHs and dose distributions and characteristic indices of the intensity profiles. The results show that this method can produce optimized dose distributions that are similar to those produced by the conventional inverse planning method with the benefit of smoother intensity profiles that are easier to deliver with a computer controlled MLC.

A Concise Description of an Old Problem: Application of Matrices to Obtain the Balancing Coefficients of Chemical Equations

It is not difficult to balance chemical equations and thus it is hardly given more thoughts. However, there is a mathematical principle for the balancing of chemical equations and this principle may be used for automation. The balancing of chemical equation is carried out, by formulating a reaction matrix and the latter is used in a matrix equation. The matrix equation is then solved to obtain the balancing coefficients. The conventional matrix inverse method cannot always be used and hence the solution is obtained by row reduced operations. These operations and any matrix manipulation are carried out with Matlab. Further this novel method can be used to classify chemical equations as nonfeasible, unique and nonunique.

Determination of strength parameters for landslide slope stability analysis by laboratory test and inverse calculation engagement.

A practical method of determining strength parameters for stability calculation of landslide slope is proposed in which the strength parameters are given by combining the conventional inverse calculation method, which has been frequently used in engineering practice, with the laboratory shear test results. In addition, the authors have newly developed a fully automated reversal direct box shear (RDBS) test apparatus using a high-precision digital servomotor. Test results on ten kinds of clay samples using the new apparatus are presented. Case studies for three sites of landslide which prove the suitability of design strength parameters determined by using the proposed method based on the test data obtained by newly developed RDBS test apparatus are also presented.

Are the solutions of stress inversion correct? Visualization of their reliability and the separation of stresses from heterogeneous fault-slip data

It is now a conventional technique to determine the optimal stress from fault-slip data by inversion. However, the method is weak when applied to heterogeneous data. A new technique is presented here to visualize the reliability of the solution. It is also shown that the technique allows us to separate stresses from those data. The technique is simple: it is the visualization of the object function of the inversion. The present method is compared with the conventional inverse method and the multi-inverse method using artificial and natural heterogeneous data sets. The conventional method can determine one of the stresses, if the orientation of the faults has a large variation. It is shown that the solutions of the method are non-unique and unstable for some data sets, indicating that they are not reliable. The present graphical method and multi-inverse method are more robust than the conventional one for heterogeneity. The multi-inverse method seems to have better resolution than the present method. However, unlike the multi-inverse method, the time of computation of the present method does not increase with the number of faults, so that the method becomes favorable for processing hundreds of faults.

Characterization of preferential flow in undisturbed, structured soil columns using a vertical TDR probe

Rapid movement of agricultural chemicals through soil to groundwater via preferential flow pathways is one cause of water contamination. Previous studies have shown that time domain reflectometry (TDR) could be used to characterize solute transport in soil. However, previous studies have only scarcely addressed preferential flow. This study presents an extended application of TDR for determining preferential flow properties. A TDR method was tested in carefully controlled laboratory experiments using 20-cm long and 12-cm diameter undisturbed, structured soil columns. The method used a vertically installed TDR probe and a short pulse of tracer application to obtain residual mass (RM) breakthrough curves (BTC). The RM BTC obtained from TDR were used to estimate mobile/immobile model (MIM) parameters that were compared to the parameter estimates from effluent data. A conventional inverse curve fitting method (CXTFIT) was used to estimate parameters. The TDR-determined parameters were then used to generate calculated effluent BTC for comparison with observed effluent BTC for the same soil columns. Time moments of the calculated and observed BTC were calculated to quantitatively evaluate the calculated BTC. Overall, the RM BTC obtained from TDR were similar to the RM BTC obtained from effluent data. The TDR-determined parameters corresponded well to the parameters obtained from the effluent data, although they were not within the 95% confidence intervals. Correlation coefficients between the parameters obtained from TDR and from effluent data for the immobile water fraction ( θ im/ θ), mass exchange coefficient ( α), and dispersion coefficient ( D m) were 0.95, 0.95, and 0.99, respectively. For three of the four soil cores, θ im/ θ ranged from 0.42 to 0.82, indicating considerable preferential flow. The TDR-calculated effluent BTC also were similar to the observed effluent BTC having an average coefficient of determination of 0.94. Time moments obtained from calculated BTC were representative of those obtained from observed BTC. The vertical TDR probe method was simple and minimally destructive and provided representative preferential flow properties that enabled the characterization of solute transport in soil.

Application of an optimal estimation inverse method to GPS/MET bending angle observations

Palmer et al. [2000] describes an optimal estimation inverse method for radio occultation (RO) bending angle measurements to retrieve simultaneously temperature, humidity, and surface pressure; outlines quality control procedures for retrieved profiles; and investigates the results from numerical simulations. Here we present retrievals that use bending angle observations from the Global Positioning System Meteorology (GPS/MET) satellite instrument and a priori information from the European Centre for Medium‐Range Weather Forecasts analyses. Retrieved profiles are compared with correlative radiosondes, United Kingdom Meterological Office (UKMO) model analyses, and retrievals from the conventional inverse method. Retrieved temperature profiles are generally colder than analyses but agree with the conventional inverse method to within 1 K. Water vapor retrievals are generally drier than the UKMO analyses and wetter than the radiosonde profiles. Quality of retrieved surface pressure values are related to the extent to which RO observations reach into the troposphere. Low‐latitude retrievals make large adjustments to surface pressure and tropospheric temperatures, which are directly linked to the lack of water vapor above 300 hPa in the inverse model, consistent with previous studies. A study of individual occultations at low and high latitude shows that the optimal retrievals are able to resolve small‐scale atmospheric structure exhibited by the conventional inverse method and collocated radiosondes, not shown by analyses.

Information Content of Data for Identifying Soil Hydraulic Parameters from Outflow Experiments

Process-oriented models of open systems often contain parameters that cannot be measured directly but can only be obtained by inverse modeling. A conventional inverse method is typically based on the minimization of an objective function that lumps the discrepancies in time series of observed values and predicted model response. However, problems are often encountered with the non-uniqueness of the parameter estimates. Non-unique parameter estimates result in case of low parameter sensitivity, mutual parameter dependency, and high measurement noise. These problems can be solved partly if we do not use the entire data set but focus on subsets where the model is most sensitive to changes in the unknown parameters. Therefore we propose PIMLI (Parameter Identification Method based on the Localization of Information), that uses the variability in time of the model sensitivity for the various parameters to split the total set of measurements into disjunctive subsets that each contain the most information on one of the model parameters. Thereupon, each distinguished subset is used to constrain its corresponding parameter. To illustrate PIMLI we chose a simulated multi-step outflow (MSO) experiment in which only cumulative outflow is measured because of its well-known problems with the uniqueness of the identified soil hydraulic properties. The results show that PIMLI not only leads to unique parameter sets of soil hydraulic properties for a range of soils but also significantly improves the understanding of uniqueness problems related to parameter identification.

A Time Domain Reflectometry Method to Measure Immobile Water Content and Mass Exchange Coefficient

Physical nonequilibrium of water and solute transport in soil has been reported. One of the most common mechanistic models used to describe physical nonequilibrium transport phenomena is the mobile–immobile model (MIM). Two significant parameters in the MIM are immobile water content (θim) and mass exchange coefficient (α). Previously, a method for determining θim and α using sequential tracers (ST) has been used to characterize solute transport. In this work, we present and evaluate a method to estimate θim and α using time domain reflectometry (TDR). The TDR method was tested in laboratory experiments using three 20 cm long by 12 cm diameter undisturbed saturated soil columns. The method used TDR with an application of CaCl2 to obtain resident concentrations as a function of time. The data obtained from TDR were analyzed using a log‐linear equation developed based on the ST method to estimate θim and α. The θim and α estimates from the TDR method were compared with the estimates from the ST method and from effluent data. A conventional inverse curve fitting method (CXTFIT) was used to estimate parameters from effluent data. The means of θim/θ from the TDR method, ST method, and effluent data were 0.31, 0.30, and 0.26, respectively. The means of α from the TDR method, ST method, and effluent data were 0.03, 0.03, and 0.04 h−1, respectively. The values of θim/θ and α from the TDR method were very similar to the estimates from the ST method. In all three columns, the θim estimates from the TDR method were within the 95% confidence intervals (CI) of the estimates from the effluent data. In two of three columns, the α estimates from the TDR method were within the 95% CI of the estimates from the effluent data. The TDR method is relatively simple, rapid, and had advantages over the ST method and conventional methods for measuring solute transport properties.

Inverse Neural Networks Control for Nonlinear Flexible Structure

For the attitude control of nonlinear flexible structure, a special control method is proposed that combines inverse neural networks feed-forward control with output feedback control. The conventional inverse system method requests all states feedback. Being aimed at immeasurable characteristics of flexible structure modes, the recurrent neural network is introduced to approach the inverse system of controlled plant The inverse neural network forms the feed-forward controller. The output feedback constitutes the feedback loop in order to guarantee the stability of system. The simulation results are presented based on a flexible satellite model

Performance improvement of active noise control using on-line estimation of secondary path transfer function

In the conventional inverse modeling method for on-line modeling of the secondary path transfer function, the signal to noise ratio between the arbitrary random signal and the plant noise have to keep at -10 - -20 dB. For these reasons, the modeling can't be exactly implemented by the conventional method alone and the convergence time for modeling becomes too long. In this study, by combining the conventional inverse modeling method with an adaptive line enhancer, or with an adaptive noise canceller, a rigorous transfer functions of secondary path modeling and the control of a primary noise have been implemented simultaneously.