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Location-based analysis of car-following behavior during braking using naturalistic driving data

CANADIAN JOURNAL OF CIVIL ENGINEERING 2020年第5期47卷 498-505页

作者： Tawfeek, Mostafa H. El-Basyouny, Karim Ain Shams Univ Dept Civil Engn Cairo Egypt Univ Alberta Dept Civil & Environm Engn Edmonton AB Canada

This study investigates the car-following behavior during braking at intersections and segments. Car-following events were extracted from a naturalistic driving dataset, mapped using ArcGIS, and analyzed to differentiate between the intersection-and segment-related events. The intersection-related events were identified according to an intersection influence area, which was estimated based on the stopping sight distance and the speed limit. Five behavioral measures were quantified based on exploring the probability density functions (PDF) for intersection- and segment-related events. The results showed that there were significant differences between the PDFs of the measures for both cases. Moreover, it was indicated that drivers tend to be more aggressive at intersections compared with segments. Thus, it is crucial to consider the driver's location when investigating driver behavior. The quantified behavioral measures are a rich data source that can be used for car-following microscopic modeling, surrogate safety analysis, and driver assistance systems development.

关键词： driver behavior naturalistic driving data car following during braking driving aggressiveness intersection influence area probability density functions

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Precise Reentry Maneuver Estimation Using Radar Trilateration

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2020年第3期43卷 422-437页

作者： Hough, Michael E. Raytheon Co 235 Presidential Way Woburn MA 01801 USA

An iterated recursive filter is formulated for radar trilateration of reentry maneuvers. Using range and range rate measurements from three radars in a regional network, trilateration provides very accurate three-dimensional position and velocity measurements, which improves drag and lift acceleration estimates. A new first-order, nonlinear vector differential equation specifies the rate of change of acceleration (or jerk). Acceleration process noise is determined from dynamic pressure estimates and mean-square area-to-mass covariances, which are derived from probability density functions that statistically characterize a family of expected maneuvers. Trilateration accuracies are demonstrated for demanding reentry maneuvers. Monte Carlo simulations assess accuracy sensitivity to modeling assumptions and to off-nominal reentry trajectories.

关键词： RADAR Dynamic Pressure probability density functions Recursive Filter Monte Carlo Simulation Lift Coefficient Earth Aerodynamic Coefficients Extended Kalman Filter Guidance Algorithms

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Multifidelity Data Fusion: Application to Blended-Wing-Body Multidisciplinary Analysis Under Uncertainty

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AIAA JOURNAL 2020年第2期58卷 889-906页

作者： Feldstein, Alex Lazzara, David Princen, Norman Willcox, Karen Aurora Flight Sci Cambridge MA 02142 USA Boeing Co Huntington Beach CA 92647 USA Univ Texas Austin Oden Inst Computat Engn & Sci Austin TX 78712 USA

This paper presents a methodology to support improved decision making and identification of risks in early stage multidisciplinary design. The approach fuses multifidelity data from disparate information sources available to designers, such as disciplinary simulations, experiments, and operational data from previously deployed systems. The multifidelity data fusion is achieved using a fidelity-weighted combination of Gaussian process surrogate models. This weighting takes into account both the quality of the Gaussian process approximation and the designer's confidence in the underlying information source being approximated. The resulting multifidelity surrogate provides a rapid analysis capability, which in turn enables the high number of evaluations needed to conduct multidisciplinary trade studies and to propagate uncertainty to the overall system level. The methodology is broadly applicable across engineering design problems where multiple information sources are available to support design decisions. In this paper, the approach is demonstrated on the stability and control analysis of a Blended-Wing-Body aircraft's center-of-gravity limits, considering the longitudinal criteria of fly-to-stall, stall recovery, nose-wheel steering, and nose-wheel liftoff. The results show that low-fidelity models are enhanced by the presence of higher-fidelity data in key areas of the design space. The presence of even sparse high-fidelity data is key to reducing the variance in the overall analysis, thereby improving the quality of the predictions needed to inform early stage design decisions.

关键词： Mean Aerodynamic Chord Data Fusion probability density functions Surrogate Model Aircraft Center of Gravity Aerodynamic Coefficients Lift Coefficient Reynolds Averaged Navier Stokes Wind Tunnel Models Control Surfaces

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Trajectory Optimization for Multitarget Tracking Using Joint Probabilistic Data Association Filter

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2020年第1期43卷 170-178页

作者： He, Shaoming Shin, Hyo-Sang Tsourdos, Antonios Cranfield Univ Sch Aerosp Transport & Mfg Coll Rd Cranfield MK43 0AL Beds England

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Efficient Aerodynamic Shape Optimization with Deep-Learning-Based Geometric Filtering

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AIAA JOURNAL 2020年第10期58卷 4243-4259页

作者： Li, Jichao Zhang, Mengqi Martins, Joaquim R. R. A. Shu, Chang Natl Univ Singapore Dept Mech Engn Singapore 117575 Singapore Univ Michigan Dept Aerosp Engn Ann Arbor MI 48109 USA

Surrogate-based optimization has been used in aerodynamic shape optimization, but it has been limited due to the curse of dimensionality. Although a large number of variables are required for the shape parameterization, many of the shapes that the parameterization can produce are abnormal and do not add meaningful information to a surrogate model. To improve the efficiency of surrogate-based optimization, recent machine learning techniques are applied in this study to reduce the abnormality of both initial and infill samples. This paper proposes a new sampling method for airfoils and wings, which is based on a deep convolutional generative adversarial network. This network is trained to learn the underlying features among the existing airfoils and is able to generate sample airfoils that are notably more realistic than those generated by other sampling methods. In addition, a discriminative model is developed based on convolutional neural networks. This model detects the geometric abnormality of airfoils or wing sections quickly without using expensive computational fluid dynamic models. These machine learning models are embedded in a surrogate-based aerodynamic optimization framework and perform aerodynamic shape optimization for airfoils and wings. The results demonstrate that, compared with the conventional methods, our proposed models can double the optimization efficiency.

关键词： Aerodynamic Shape Optimization Generative Adversarial Network Surrogate Model Gaussian Mixture Models Chord Line Supercritical Airfoils CFD Simulation Aerodynamic Performance probability density functions Singular Value Decomposition

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Quantification of Airfoil Aerodynamic Uncertainty due to Pressure-Sensitive Paint Thickness

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AIAA JOURNAL 2020年第4期58卷 1432-1440页

作者： Liu, Siyang Wang, Yibin Qin, Ning Zhao, Ning Nanjing Univ Aeronaut & Astronaut Coll Aerosp Engn Nanjing 210016 Peoples R China Univ Sheffield Dept Mech Engn Aerodynam Sheffield S1 3JD S Yorkshire England

In this paper, uncertainty quantification is used to investigate the propagation of the uncertainty of the pressure-sensitive paint (PSP) thickness distribution to the uncertainty of aerodynamic force measured. Specifically, airfoil surface pressure coefficient (Cp) and aerodynamic lift coefficient (Cl) of a natural laminar flow wing are analyzed with uncertain PSP thickness distribution. The airfoil with PSP applied is parameterized by using a novel parameterization method based on radial basis function interpolation. As a characteristic of wing aerodynamic performance, Cl is determined by surface pressure distribution, which can be affected by uncertainties of PSP binder thickness. A kriging response surface method has been used to develop a surrogate model to represent the Reynolds-averaged Navier-Stokes solution of the flow around the airfoil with PSP. This enables the use of Monte Carlo simulations to obtain stochastic output, including the probability of the occurrence of significantly inaccurate output values affected by the inputs subjecting to Gaussian distributions. An error margin and associated probability for its occurrence are recommended to account for uncertainties for the aerodynamic force occurring in the PSP measurement.

关键词： Airfoil Profiles Pressure Sensitive Paint Reynolds Averaged Navier Stokes Surrogate Model Aerodynamic Performance Monte Carlo Simulation Experimental Aerodynamics Natural Laminar Flow probability density functions Skin Friction Coefficient

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Satellite Instantaneous Collision probability Computation Using Equivalent Volume Cuboids

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2020年第9期43卷 1757-1763页

作者： Zhang, Shuo Fu, Tuo Chen, Defeng Cao, Huawei Beijing Inst Technol Sch Informat & Elect Beijing 100081 Peoples R China

In a study researchers propose an integrated, two-stage approach to effectively compute the satellite instantaneous collision probability. First, it uses the Gaussian mixture model (GMM) o approximate the relative position vector probability density function (PDF) for the two involved resident space objects (RSOs) at a future time, and the GMM is then integrated over the hard body sphere. The core of this integration involves evaluating the integral for a general 3-D Gaussian PDF over a sphere, in which researchers adopt the equivalent volume method to yield an analytic approximation.

关键词： Satellite Collision Numerical Integration Geosynchronous Equatorial Orbit Gaussian Mixture Models Monte Carlo Simulation Space Situational Awareness Position Dilution of Precision Earth Centered Inertial probability density functions Numerical Simulation

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Uncertainty Characterization Methods for Sparsely Sampled Quantity: A Tradeoff Analysis Considering Propagation

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AIAA JOURNAL 2020年第7期58卷 3129-3138页

作者： Yang, Qiang Han, Guokai Xie, Weihua Meng, Songhe Jin, Hua Harbin Inst Technol Natl Key Lab Sci & Technol Adv Composites Special Harbin 150001 Heilongjiang Peoples R China

The reliable characterization of uncertainties is critical for system evaluations and safety designs. However, insufficient samples are frequently encountered especially in composite materials. Four characterization methods for sparsely sampled quantities (SSQs) were discussed in the current study, including extreme value (EV) interval, tolerance interval (TI), optimized kernel density estimation (KDE), and the Dempster-Shafer (D-S) theory. Two different problems, a Sandia challenge function and a constitutive model for C/SiC composites, are considered for method evaluations. Performances of different methods are evaluated regarding reliabilities and errors in the output quantity derived with the uncertainty propagation. A manufactured solution method is employed. Results show that the TI, KDE, and D-S methods converge to the true distribution with increasing samples, whereas the EV method tends to expand the uncertainties. Under small samples (<= 18), the TI method exhibits the highest reliability, and the KDE method exhibits the smallest error. Under extremely small samples (<= 3) the D-S method offers a balance between reliability and error. The TI method can apply well in the constitutive model for the characterization of material uncertainties, where failure is of high consequence and conservatism is emphasized. The obtained results are general and can be employed in the future material characterization with experimental data.

关键词： Composite Materials Residual Thermal Stresses Kernel functions probability density functions Structural Analysis Material Properties Hyperelastic Material Monte Carlo Simulation Sensitivity Analysis Hypersonic Vehicles

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Probabilistic estimation of dynamic impact factor for masonry arch bridges using health monitoring data and new finite element method

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STRUCTURAL CONTROL & HEALTH MONITORING 2020年第12期27卷 e2640-e2640页

作者： Nouri, Mehrdad Mohammadzadeh, Saeed Iran Univ Sci & Technol Sch Railway Engn POB *** Tehran Iran

The presence of uncertainties in the behavior of rolling stock, infrastructure, and the interaction between them undoubtedly generates a probabilistic nature for the structure impact factor. Such an effect becomes more severe in the case of the aged structures, specifically masonry arch bridges. This research initially provides a probabilistic estimation for the impact factor based on the ratio of the dynamic to static loads by using Weigh-In-Motion data. Then, the research is followed by proposing a new finite elements approach for a more precise estimation of the structure response pattern and a more rigorous evaluation of the masonry arch bridges. It uses optimization techniques for updating the model and results in the probabilistic estimation of the impact factor by using field measurements. Through these two methods and by using data from continuous monitoring of an 80-year-old masonry arch bridge with a length of 100 m and a span of 66 m, the impact factor is surveyed. The outputs prove to be 50% more accurate compared with the already established methods. The rate of variations of the impact factor within the first proposed method is 1.6 times more compared with the second approach. This emphasizes the uncertainties in the available approaches and the probabilistic nature of the impact factor. Therefore, the assumption of the absolute certainty for the impact factor becomes questionable. This survey reveals that for the best cases, the available certainty-based methods can only cover 17% of the probabilistic domain of the impact factor.

关键词： dynamic amplification factor long-term health monitoring mortar block element method probability density functions railway masonry arch bridge

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Physical layer security performance analysis of the time reversal transmission system

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IET COMMUNICATIONS 2020年第4期14卷 635-645页

作者： Lei, Weijia Yang, Miaomiao Yao, Li Lei, Hongjiang Chongqing Univ Posts & Telecommun Sch Commun & Informat Engn Chongqing 400065 Peoples R China

Thanks to its characteristics of temporal compression and spatial focusing, the time reversal (TR) transmission system has the intrinsic capability of anti-eavesdropping. This study analyses the physical layer security performance of the TR transmission system. The probability density functions and cumulative distribution functions of the signal-to-noise ratio of the legitimate user and eavesdropper are given. On this basis, the theoretical expressions of the ergodic capacities of the legitimate channel and the wiretap channel, and the achievable ergodic secrecy rate are derived. The bit error rates of the legitimate user and eavesdropper for binary phase-shift keying modulation are given too. The correctness of the theoretical derivation is verified by simulation. For the legitimate user, the signal power increases as the number of paths increases, which indicates a higher diversity gain can be obtained, and the inter-symbol interference power decreases as the up-sampling factor increases. So, the signal-to-interference-plus-noise ratio (SINR) of the received signal can be significantly improved by appropriately reducing the spectral efficiency. However, the received signal's SINR of the eavesdropper cannot be promoted obviously. That is to say, compared with the eavesdropper, the legitimate user can achieve a higher rate and a lower BER, so secure transmission can be realised.

关键词： radio receivers channel capacity wireless channels telecommunication security probability intersymbol interference MIMO communication error statistics time reversal transmission system intrinsic capability anti-eavesdropping TR transmission system probability density functions cumulative distribution functions signal-to-noise ratio legitimate user eavesdropper theoretical expressions ergodic capacities legitimate channel wiretap channel achievable ergodic secrecy rate bit error rates binary phase-shift keying modulation signal power increases inter-symbol interference power up-sampling factor increases signal-to-interference-plus-noise ratio received signal secure transmission physical layer security performance analysis temporal compression spatial focusing

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