Novel thick-target inverse kinematics method for the astrophysical ^(12)C+^(12)C fusion reaction

The ^(12)C+^(12)C fusion is one of the most important reactions in modern nuclear astrophysics.The trend and magnitude of the reaction rate within the Gamow window strongly influence various astrophysical processes.However,direct measurement of this reaction is extremely difficult,which makes it necessary to develop indirect methods.In this study,the ^(23)Na+p reaction system was used to study the compound nucleus ^(24)Mg.We employed a thick-target inverse kinematics method combined with theγ-charged-particle coincidence technique to measure the proton andα exit channels of ^(24)Mg.Technical details of the ^(23)Na+p thick-target inverse kinematics experiment and analysis are presented herein.

Inversion method of deflection of the vertical based on SWOT wide-swath altimeter data

The deflection of the vertical(DOV)is the key information in the study of ocean gravity field.However,in most areas,the precision of the prime component of DoV is significantly lower than that of the meridian component.To obtain higher accuracy and resolution of ocean gravity information,researchers have proposed a novel altimeter called the wide-swath altimeter.This altimeter allows for the simultaneous acquisition of high-precision and high-resolution two-dimensional measurements of sea surface height(SSH).In this paper,the Surface Water and Ocean Topography(SWOT)mission with a wide-swath altimeter on board is selected for research.One cycle of swoT sea surface height data is simulated to inverse the DOV in the Arabian Sea(45°E—80°E,0°-30°N),and the inversion results are compared with those of conventional altimeter data.The results demonstrate that the difference between the meridian and prime components derived from the inversion of swoT wide-swath data is minimal,significantly outperforming the inversion results of conventional nadir altimeter data.The advantage of swoT wide-swath altimeter lies in its ability to use the multi-directional geoid slope at any sea surface measurement point to invert the components in the meridian and prime directions.To investigate the impact of this advantage on inversion precision,this paper employs a method to calculate the gradient of the geoid in multiple directions to invert DoV components.The improvement effect of calculating the gradient of the geoid in multiple directions on the precision of DoV component is analyzed.It is found that the accuracy of DoV inversion has significantly improved with the increase of geodetic gradient calculation direction.In addition,the effects of various errors and grid spacing in SwoT wide sea surface height data on the precision of Dov inversion are also analyzed.

An empirical method for joint inversion of wave and wind parameters based on SAR and wave spectrometer data

Synthetic aperture radar(SAR)and wave spectrometers,crucial in microwave remote sensing,play an essential role in monitoring sea surface wind and wave conditions.However,they face inherent limitations in observing sea surface phenomena.SAR systems,for instance,are hindered by an azimuth cut-off phenomenon in sea surface wind field observation.Wave spectrometers,while unaffected by the azimuth cutoff phenomenon,struggle with low azimuth resolution,impacting the capture of detailed wave and wind field data.This study utilizes SAR and surface wave investigation and monitoring(SWIM)data to initially extract key feature parameters,which are then prioritized using the extreme gradient boosting(XGBoost)algorithm.The research further addresses feature collinearity through a combined analysis of feature importance and correlation,leading to the development of an inversion model for wave and wind parameters based on XGBoost.A comparative analysis of this model with ERA5 reanalysis and buoy data for of significant wave height,mean wave period,wind direction,and wind speed reveals root mean square errors of 0.212 m,0.525 s,27.446°,and 1.092 m/s,compared to 0.314 m,0.888 s,27.698°,and 1.315 m/s from buoy data,respectively.These results demonstrate the model’s effective retrieval of wave and wind parameters.Finally,the model,incorporating altimeter and scatterometer data,is evaluated against SAR/SWIM single and dual payload inversion methods across different wind speeds.This comparison highlights the model’s superior inversion accuracy over other methods.

A Two-step Inverse Method for Quantitative Damage Evaluation of Plate-like Structures Using Vibration Approach

This study presents a novel two-step approach to assess plate-like structural laminar damages,particularly for delamination damage detection of composite structures.Firstly,a 2-D continuous wavelet transform is employed to identify the damage location and sizes from vibration curvature data.An inverse method is subsequently then used to determine the bending stiffness reduction ratio along a specified direction,enabling the quantification of the delamination severity.The method employed in this study is an extension of the one-dimensional inverse method developed in a previous work of the authors.The applicability of the two-step inverse approach is demonstrated in a simulation analysis and by an experimental study on a cantilever composite plate containing a single delamination.The inverse method is shown to have the capacity to reveal the detailed damage information of delamination within a constrained searching space and can be used to determine the effective flexural stiffness of composite plate structures,even in cases of complex delamination damage.

Inverse Method of Centrifugal Pump Impeller Based on Proper Orthogonal Decomposition (POD) Method

To improve the accuracy and reduce the calcu- lation cost for the inverse problem of centrifugal pump impeller, the new inverse method based on proper orthog- onal decomposition （POD） is proposed. The pump blade shape is parameterized by quartic Bezier curve, and the initial snapshots is generated by introducing the perturbation of the blade shape control parameters. The internal flow field and its hydraulic performance is predicted by CFD method. The snapshots vector includes the blade shape parameter and the distribution of blade load. The POD basis for the snap- shots set are deduced by proper orthogonal decomposition. The sample vector set is expressed in terms of the linear combination of the orthogonal basis. The objective blade shape corresponding to the objective distribution of blade load is obtained by least square fit. The Iterative correction algorithm for the centrifugal pump blade inverse method based on POD is proposed. The objective blade load dis- tributions are corrected according to the difference of the CFD result and the POD result. The two dimensional and three dimensional blade calculation cases show that the proposed centrifugal pump blade inverse method based on POD have good convergence and high accuracy, and thecalculation cost is greatly reduced. After two iterations, the deviation of the blade load and the pump hydraulic perfor- mance are limited within 4.0% and 6.0% individually for most of the flow rate range. This paper provides a promising inverse method for centrifugal pump impeller, which will benefit the hydraulic optimization of centrifugal pump.

Application of inverse method to estimation of boundary conditions during investment casting simulation

Inverse method was used in single crystal superalloy DD6 processing simulation during solidification. Numerical modeling coupled with experiments has been used to estimate the interface heat transfer coefficient （IHTC） between the surface of slab casting and inner mold. Calculated temperature dependent values of IHTC were obtained from a numerical solution. The calculated temperatures agreed well with the measurement of cooling profile.

Calculation of circulation in the South China Sea during summer of 2000 by the modified inverse method

On the basis of hydrographic data obtained in August 2000 cruise, the circulation in the South China Sea (SCS) is computed by the modified inverse method in combination with SSH data from TOPEX/ERS-2 analysis. For study of the dynamical mechanism, which causes the pattern of summer circulation in the SCS, the diagnostic model (Yuan et al. 1982. Acta Oceanologica Sinica,4(1):1-11; Yuan and Su. 1992. Numerical Computation of Physical Oceanography.474-542) is used to simulate numerically the summer circulation in the SCS. The following results have been obtained. (1) The central and southwestern SCSs are dominated mainly by anticy-clonic circulation systems. They are mainly as follows. 1) There is strong anticyclonic eddy southeast of Vietnam (W1). Its horizontal scale is about 300 km, and it extends vertically from the surface to the about 1 000 m level. 2) There are a warm eddy W2 southeast of Zhongsha Islands and the anticyclonic circulation system W3 west off the Luzon Island. 3) There is a stronger cyclonic eddy C1 between the anticyclonic eddies W1 and W2.4) A strong northward coastal jet is present near the coast of Vietnam, and separates from the coast of Vietnam at about 12° N to the northeast.(2)The northern SCS is dominated mainly by a cyclonic circulation system. There is a cyclonic circulation system near and north of Section N2. (3) The southeastern SCS is dominated mainly by the cyclonic circulation system. (4) Comparing the results of circulation in the SCS during the summer of 2000 with those during the summer of 1998, it is found that they agree qualitatively, but there is the some difference between them in quantity.This shows that the circulation in the SCS has obviously seasonal feature. (5) The dynamical mechanism which products the basic pattern of summer circulation is because the following two reasons: 1) the joint effect of the baroclinity and relief (JEBAR) is essential dynamical cause; and 2) it is next important dynamical cause that the interaction between the wind stress and bottom topography under the southerly monsoon. (6) Comparing the hydrographic structure and distribution of stream functions with the SSH data from TOPEX/ERS-2 analysis in the SCS during August of 2000, they agree qualitatively.

Application of the Modified nverse Design Method in the Optimization of the Runner Blade of a Mixed-Flow Pump

To improve the design speed and reduce the design cost for the previous blade design method, a modified inverse design method is presented. In the new method, after a series of physical and mathematical simplifications, a sail?like constrained area is proposed, which can be used to configure di erent runner blade shapes. Then, the new method is applied to redesign and optimize the runner blade of the scale core component of the 1400?MW canned nuclear coolant pump in an established multi?optimization system compromising the Computational Fluid Dynamics(CFD) analysis, the Response Surface Methodology(RSM) and the Non?dominated Sorting Genetic Algorithm?II(NSGA?II). After the execution of the optimization procedure, three optimal samples were ultimately obtained. Then, through comparative analysis using the target runner blade, it was found that the maximum e ciency improvement reached 1.6%, while the head improvement was about 10%. Overall, a promising runner blade inverse design method which will benefit the hydraulic design of the mixed?flow pump has been proposed.

Bayesian machine learning-based method for prediction of slope failure time

The data-driven phenomenological models based on deformation measurements have been widely utilized to predict the slope failure time(SFT).The observational and model uncertainties could lead the predicted SFT calculated from the phenomenological models to deviate from the actual SFT.Currently,very limited study has been conducted on how to evaluate the effect of such uncertainties on SFT prediction.In this paper,a comprehensive slope failure database was compiled.A Bayesian machine learning(BML)-based method was developed to learn the model and observational uncertainties involved in SFT prediction,through which the probabilistic distribution of the SFT can be obtained.This method was illustrated in detail with an example.Verification studies show that the BML-based method is superior to the traditional inverse velocity method(INVM)and the maximum likelihood method for predicting SFT.The proposed method in this study provides an effective tool for SFT prediction.

A time domain induced polarization relaxation time spectrum inversion method based on a damping factor and residual correction

Relaxation time spectra （RTS） derived from time domain induced polarization data （TDIP） are helpful to assess oil reservoir pore structures. However, due to the sensitivity to the signal-to-noise ratio （SNR）, the inversion accuracy of the traditional singular value decomposition （SVD） inversion method reduces with a decrease of SNR. In order to enhance the inversion accuracy and improve robustness of the inversion method to the SNR, an improved inversion method, based on damping factor and spectrum component residual correction, is proposed in this study. The numerical inversion results show that the oscillation of the RTS derived from the SVD method increased with a decrease of SNR, which makes it impossible to get accurate inversion components. However, the SNR has little influence on inversion components of the improved method, and the RTS has high inversion accuracy and robustness. Moreover, RTS derived from core sample data is basically in accord with the pore-size distribution curve, and the RTS derived from the actual induced polarization logging data is smooth and continuous, which indicates that the improved method is practicable.

An improved data space inversion method to predict reservoir state fields via observed production data

A data-space inversion(DSI)method has been recently proposed and successfully applied to the history matching and production prediction of reservoirs.Based on Bayesian theory,DSI can directly and effectively obtain good posterior flow predictions without inversion of geological parameters of reservoir model.This paper presents an improved DSI method to fast predict reservoir state fields(e.g.saturation and pressure profiles)via observed production data.Firstly,a large number of production curves and state data are generated by reservoir model simulation to expand the data space of original DSI.Then,efficient history matching only on the observed production data is carried out via the original DSI to obtain related parameters which reflects the weight of the real reservoir model relative to prior reservoir models.Finally,those parameters are used to predict the oil saturation and pressure profiles of the real reservoir model by combining large amounts of state data of prior reservoir models.Two examples including conventional heterogeneous and unconventional fractured reservoir are implemented to test the performances of predicting saturation and pressure profiles of this improved DSI method.Besides,this method is also tested in a real field and the obtained results show the high computational efficiency and high accuracy of the practical application of this method.

Comparison of different inversion methods of D-T_(2)two-dimensional nuclear magnetic resonance logging and applicability analysis

D-T_(2)two-dimensional nuclear magnetic resonance(2D NMR)logging technology can distinguish pore fluid types intuitively,and it is widely used in oil and gas exploration.Many 2D NMR inversion methods(e.g.,truncated singular value decomposition(TSVD),Butler-Reds-Dawson(BRD),LM-norm smoothing,and TIST-L1 regularization methods)have been proposed successively,but most are limited to numerical simulations.This study focused on the applicability of different inversion methods for NMR logging data of various acquisition sequences,from which the optimal inversion method was selected based on the comparative analysis.First,the two-dimensional NMR logging principle was studied.Then,these inversion methods were studied in detail,and the precision and computational efficiency of CPMG and diffusion editing(DE)sequences obtained from oil-water and gas-water models were compared,respectively.The inversion results and calculation time of truncated singular value decomposition(TSVD),Butler-Reds-Dawson(BRD),LM-norm smoothing,and TIST-L1 regularization were compared and analyzed through numerical simulations.The inversion method was optimized to process SP mode logging data from the MR Scanner instrument.The results showed that the TIST-regularization and LM-norm smoothing methods were more accurate for the CPMG and DE sequence echo trains of the oil-water and gas-water models.However,the LM-norm smoothing method was less time-consuming,making it more suitable for logging data processing.A case study in well A25 showed that the processing results by the LM-norm smoothing method were consistent with GEOLOG software.This demonstrates that the LM-norm smoothing method is applicable in practical NMR logging processing.

Transport properties of a binary mixture of CO_2-N_2 from the pair potential energy functions based on a semi-empirical inversion method

The potential energy snrface of a CO2-N2 mixture is determined by using an inversion method, together with a new collision integral correlation [J. Phys. Chem. R@ Data 19 1179 （1990）]. With the new invert potential, the transport properties of CO2-N2 mixture are presented in a temperature range front 273.15 K to 3273.15 K at low density by employing the Chapman-Enskog scheme and the Wang Chang-Uhlenbeck de Boer theory, consisting of a viscosity coefficient, a thermal conductivity coefficient, a binary diffusion coefficient, and a thermal diffusion factor. The accuracy of the predicted results is estimated to be 2% for viscosity, 5% for thermal conductivity, and 10% for binary diffusion coefficient.

Modeling of Diffusion Transport through Oral Biofilms with the Inverse Problem Method

Aim The purpose of this study was to develop a mathe-matical model to quantitatively describe the passive trans-port of macromolecules within dental biofilms. Methodology Fluorescently labeled dextrans with different molecular mass （3 kD,10 kD,40 kD,70 kD,2 000 kD） were used as a series of diffusion probes. Streptococcus mutans,Streptococcus sanguinis,Actinomyces naeslundii and Fusobacterium nucleatum were used as inocula for biofilm formation. The diffusion processes of different probes through the in vitro biofilm were recorded with a confocal laser microscope. Results Mathematical function of biofilm penetration was constructed on the basis of the inverse problem method. Based on this function,not only the relationship between average concentration of steady-state and molecule weights can be analyzed,but also that between penetrative time and molecule weights. Conclusion This can be used to predict the effective concentration and the penetrative time of anti-biofilm medicines that can diffuse through oral biofilm. Further-more,an improved model for large molecule is proposed by considering the exchange time at the upper boundary of the dental biofilm.

Inverse Construction Methods of Heterogeneous NURBS Object Based on Additive Manufacturing

According to the requirement of heterogeneous object modeling in additive manufacturing(AM),the Non-Uniform Rational B-Spline(NURBS)method has been applied to the digital representation of heterogeneous object in this paper.By putting forward the NURBS material data structure and establishing heterogeneous NURBS object model,the accurate mathematical unified representation of analytical and free heterogeneous objects have been realized.With the inverse modeling of heterogeneous NURBS objects,the geometry and material distribution can be better designed to meet the actual needs.Radical Basis Function(RBF)method based on global surface reconstruction and the tensor product surface interpolation method are combined to RBF-NURBS inverse construction method.The geometric and/or material information of regular mesh points is obtained by RBF interpolation of scattered data,and the heterogeneous NURBS surface or object model is obtained by tensor product interpolation.The examples have shown that the heterogeneous objects fitting to scattered data points can be generated effectively by the inverse construction methods in this paper and 3D CAD models for additive manufacturing can be provided.

Nonlinear system compound inverse control method

A compound neural network is utilized to identify the dynamic nonlinear system. This network is composed of two parts： one is a linear neural network, and the other is a recurrent neural network. Based on the inverse theory a compound inverse control method is proposed. The controller has also two parts： a linear controller and a nonlinear neural network controller. The stability condition of the closed-loop neural network-based compound inverse control system is demonstrated .based on the Lyapunov theory. Simulation studies have shown that this scheme is simple and has good control accuracy and robustness.

Shape Sensing of Thin Shell Structure Based on Inverse Finite Element Method

Shape sensing as a crucial component of structural health monitoring plays a vital role in real-time actuation and control of smart structures,and monitoring of structural integrity.As a model-based method,the inverse finite element method(iFEM)has been proved to be a valuable shape sensing tool that is suitable for complex structures.In this paper,we propose a novel approach for the shape sensing of thin shell structures with iFEM.Considering the structural form and stress characteristics of thin-walled structure,the error function consists of membrane and bending section strains only which is consistent with the Kirchhoff–Love shell theory.For numerical implementation,a new four-node quadrilateral inverse-shell element,iDKQ4,is developed by utilizing the kinematics of the classical shell theory.This new element includes hierarchical drilling rotation degrees-of-freedom(DOF)which enhance applicability to complex structures.Firstly,the reconstruction performance is examined numerically using a cantilever plate model.Following the validation cases,the applicability of the iDKQ4 element to more complex structures is demonstrated by the analysis of a thin wallpanel.Finally,the deformation of a typical aerospace thin-wall structure(the composite tank)is reconstructed with sparse strain data with the help of iDKQ4 element.

Gas emission source term estimation with 1-step nonlinear partial swarm optimization-Tikhonov regularization hybrid method

Source term identification is very important for the contaminant gas emission event. Thus, it is necessary to study the source parameter estimation method with high computation efficiency, high estimation accuracy and reasonable confidence interval. Tikhonov regularization method is a potential good tool to identify the source parameters. However, it is invalid for nonlinear inverse problem like gas emission process. 2-step nonlinear and linear PSO （partial swarm optimization）-Tikhonov regularization method proposed previously have estimated the emission source parameters successfully. But there are still some problems in computation efficiency and confidence interval. Hence, a new 1-step nonlinear method combined Tikhonov regularizafion and PSO algorithm with nonlinear forward dispersion model was proposed. First, the method was tested with simulation and experiment cases. The test results showed that 1-step nonlinear hybrid method is able to estimate multiple source parameters with reasonable confidence interval. Then, the estimation performances of different methods were compared with different cases. The estimation values with 1-step nonlinear method were close to that with 2-step nonlinear and linear PSO-Tikhonov regularization method, 1-step nonlinear method even performs better than other two methods in some cases, especially for source strength and downwind distance estimation. Compared with 2-step nonlinear method, 1-step method has higher computation efficiency. On the other hand, the confidence intervals with the method proposed in this paper seem more reasonable than that with other two methods. Finally, single PSO algorithm was compared with 1-step nonlinear PSO-Tikhonov hybrid regularization method. The results showed that the skill scores of 1-step nonlinear hybrid method to estimate source parameters were close to that of single PSO method and even better in some cases. One more important property of 1-step nonlinear PSO-Tikhonov regularization method is its reasonable confidence interval, which is not obtained by single PSO algorithm. Therefore, 1-step nonlinear hybrid regularization method proposed in this paper is a potential good method to estimate contaminant gas emission source term.

Seismic fluid identification using a nonlinear elastic impedance inversion method based on a fast Markov chain Monte Carlo method

Elastic impedance inversion with high efficiency and high stability has become one of the main directions of seismic pre-stack inversion. The nonlinear elastic impedance inversion method based on a fast Markov chain Monte Carlo （MCMC） method is proposed in this paper, combining conventional MCMC method based on global optimization with a preconditioned conjugate gradient （PCG） algorithm based on local optimization, so this method does not depend strongly on the initial model. It converges to the global optimum quickly and efficiently on the condition that effi- ciency and stability of inversion are both taken into consid- eration at the same time. The test data verify the feasibility and robustness of the method, and based on this method, we extract the effective pore-fluid bulk modulus, which is applied to reservoir fluid identification and detection, and consequently, a better result has been achieved.

Investigation on heat-transfer-coefficient between aluminum alloy and organic/inorganic sand mold based on inverse method

A kind of cylinder sand mold was designed to investigate the heat-transfer-coefficients（HTCs） between aluminum alloy and organic/inorganic binder bonded sand mold during the solidification processes. Temperature during the solidification process was recorded and input into the simulation software. The inverse model of MAGMA was used to calculate the HTC based on the actual temperature. Results show that the temperature of the inorganic sand mold increased faster than the organic sand mold; while the temperature of the casting part with the inorganic sand mold decreased faster. The optimal HTCs between Al and the organic/inorganic sand mold are confirmed to be 300 to 700 and 1000 to 1800 W·m-2·K-1, respectively, along with the change of solid-liquid phase line. The simulated temperature curves show the same trend as the measured ones. The maximum deviation between the two temperature curves are 17.32 °C and 18.77 °C for castings by inorganic and organic sand molds.