A Novel Method for the Reconstruction of Road Profiles from Measured Vehicle Responses Based on the Kalman Filter Method

The estimation of the disturbance input acting on a vehicle from its given responses is an inverse problem.To overcome some of the issues related to ill-posed inverse problems,this work proposes a method of reconstructing the road roughness based on the Kalman filter method.A half-car model that considers both the vehicle and equipment is established,and the joint input-state estimation method is used to identify the road profile.The capabilities of this methodology in the presence of noise are numerically demonstrated.Moreover,to reduce the influence of the driving speed on the estimation results,a method of choosing the calculation frequency is proposed.A road vibration test is conducted to benchmark the proposed method.

Reconstruction of hollow areas in density profiles from frequency swept reflectometry

The standard density profile reconstruction techniques are based on the WKB approximation of the probing wave’s phase,making them unable to properly reconstruct blind areas in the cut-off frequency profile.The reconstruction suffers a significant immediate error that is not rapidly damped.It is demonstrated that even though no reflections occur inside the hollow region causing the blind area,the higher probing frequencies that propagate through it carry information that can be used to estimate its properties.The usually ignored full-wave effects were investigated with the use of full-wave simulations in 1 D,with special attention paid to the frequency band where they are dominant.A database of perturbation signals was simulated onfive-dimensions of parameters and an application of the database inversion was demonstrated for a magnetic island in a Tore Supra discharge.The new adapted reconstruction scheme improved the description of the density profile inside the hollow region and also along 10 cm after it.

A Portable Noncontact Profile Scanning System for Aircraft Assembly

Three-dimensional(3D)profile scanning plays a crucial role in the inspection of assembled large aircraft.In this paper,to achieve noncontact automatic measurements of the high-reflective profiles of large-scale curved parts and components,an automated noncontact system and method with high accuracy and high efficiency are presented.First,a hybrid 3D coordinate measurement system based on proximity sensors and cameras is proposed to obtain noncontact measurements while avoiding the influence of high reflection on the measurement accuracy.A hybrid measurement model that combines the one-dimensional distances measured by the proximity sensors and the 3D information obtained by cameras is proposed to determine high-accuracy 3D coordinates of the measured points.Then,a profile-driven 3D automated scanning method and strategy are designed to rapidly scan and reconstruct the profile within the effective range without scratching the profile or exceeding the measurement range of the proposed system.Finally,experiments and accuracy analyses are performed in situ on an assembled tailplane panel(approximately 1760 mm×460 mm).The automated scanning process is completed in a timeframe of 208s with an average error of less than 0.121 mm for profile reconstruction.Therefore,the proposed method is promising considering both the high accuracy and high efficiency requirements of profile inspections for large aircraft.

Reconstructing bubble profiles from gas-liquid two-phase flow data using agglomerative hierarchical clustering method

The knowledge of bubble profiles in gas-liquid two-phase flows is crucial for analyzing the kinetic processes such as heat and mass transfer, and this knowledge is contained in field data obtained by surface-resolved computational fluid dynamics (CFD) simulations. To obtain this information, an efficient bubble profile reconstruction method based on an improved agglomerative hierarchical clustering (AHC) algorithm is proposed in this paper. The reconstruction method is featured by the implementations of a binary space division preprocessing, which aims to reduce the computational complexity, an adaptive linkage criterion, which guarantees the applicability of the AHC algorithm when dealing with datasets involving either non-uniform or distorted grids, and a stepwise execution strategy, which enables the separation of attached bubbles. To illustrate and verify this method, it was applied to dealing with 3 datasets, 2 of them with pre-specified spherical bubbles and the other obtained by a surface-resolved CFD simulation. Application results indicate that the proposed method is effective even when the data include some non-uniform and distortion.

Integrative multi-omics and systems bioinformatics in translational neuroscience:A data mining perspective

Bioinformatic analysis of large and complex omics datasets has become increasingly useful in modern day biology by providing a great depth of information,with its application to neuroscience termed neuroinformatics.Data mining of omics datasets has enabled the generation of new hypotheses based on differentially regulated biological molecules associated with disease mechanisms,which can be tested experimentally for improved diagnostic and therapeutic targeting of neurodegenerative diseases.Importantly,integrating multi-omics data using a systems bioinformatics approach will advance the understanding of the layered and interactive network of biological regulation that exchanges systemic knowledge to facilitate the development of a comprehensive human brain profile.In this review,we first summarize data mining studies utilizing datasets from the individual type of omics analysis,including epigenetics/epigenomics,transcriptomics,proteomics,metabolomics,lipidomics,and spatial omics,pertaining to Alzheimer's disease,Parkinson's disease,and multiple sclerosis.We then discuss multi-omics integration approaches,including independent biological integration and unsupervised integration methods,for more intuitive and informative interpretation of the biological data obtained across different omics layers.We further assess studies that integrate multi-omics in data mining which provide convoluted biological insights and offer proof-of-concept proposition towards systems bioinformatics in the reconstruction of brain networks.Finally,we recommend a combination of high dimensional bioinformatics analysis with experimental validation to achieve translational neuroscience applications including biomarker discovery,therapeutic development,and elucidation of disease mechanisms.We conclude by providing future perspectives and opportunities in applying integrative multi-omics and systems bioinformatics to achieve precision phenotyping of neurodegenerative diseases and towards personalized medicine.

An approach to gas sensors based on tunable diode laser incomplete saturated absorption spectra

A spectral profile reconstruction method that can be applied to incomplete saturated-absorption spectra is proposed and demonstrated. Through simulation and theoretical calculation, it is proved that compared with the traditional wholeprofile fitting method, this new method can increase the concentration detection upper limit of a single absorption line by about 8.7 times. High-concentration water vapor is measured using TDLAS technology, the total water vapor pressure and the self-broadened half-width coefficient of the spectrum were simultaneously measured from incomplete saturatedabsorption spectra and compared with high-precision pressure sensors and the HITRAN databases. Their maximum relative deviations were about 4.63% and 9.10%, respectively. These results show that the spectral profile reconstruction method has great application potential for expanding the dynamic range of single-line measurements to higher concentrations,especially for in-situ online measurements under complex conditions, such as over large temperature and concentration dynamic ranges.

An Optimization Method in Inverse Elastic Scattering for One-Dimensional Grating Profiles

Consider the inverse diffraction problem to determine a two-dimensional periodic structure from scattered elastic waves measured above the structure.We formulate the inverse problem as a least squares optimization problem,following the two-step algorithm by G.Bruckner and J.Elschner[Inverse Probl.,19(2003),315–329]for electromagnetic diffraction gratings.Such a method is based on the Kirsch-Kress optimization scheme and consists of two parts:a linear severely ill-posed problem and a nonlinear well-posed one.We apply this method to both smooth(C2)and piecewise linear gratings for the Dirichlet boundary value problem of the Navier equation.Numerical reconstructions from exact and noisy data illustrate the feasibility of the method.

Minimizing the effects of unmodulated light and uneven intensity profile on the holographic images reconstructed by pixelated spatial light modulators

A simple and effective approach is proposed to minimize the effect of unmodulated light and uneven intensity caused by the pixelated structure of the spatial light modulator in a holographic display. A more uniform image is produced by purposely shifting the holographic images of multiple reconstructed lights with different incident angles from the zero-diffraction-order and overlapping those selected different orders. The simulation and optical experimental results show that the influence of the zero-diffraction-order can be reduced, while keeping the good uniformity of the target images by this new approach.

A Study of the Velocity Field of Liquid Sodium in a Toroidal Channel

The velocity field of liquid sodium in a toroidal channel is studied.Velocity measurements are made using the magnetic induction method.The proposed technique involves two steps:an external alternating magnetic field of certain frequency is induced in the channel;then the measurements of the resulting magnetic field are used to reconstruct the velocity profile.