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Surrogate-based algorithms are indispensable in the aerospace engineering field for reducing the computational cost of optimization and uncertainty quantification analyses, particularly those involving computationally intensive solvers. This paper presents a novel approach for enhancing the efficiency of surrogate-based algorithms through a new multi-fidelity sampling technique. Unlike existing multi-fidelity methods which are based on a single multiplicative acquisition function, the proposed technique decouples the identification of the new infill sample from the selection of the fidelity level. The location of the infill sample is determined by leveraging the highest fidelity surrogate model, while the fidelity level used for its performance evaluation is chosen as the cheapest one within the "accurate enough" models at the infill location. Moreover, the methodology introduces the application of the Jensen–Shannon divergence to quantify the accuracy of the different fidelity levels. Overall, the resulting technique eliminates some of the drawbacks of existing multiplicative acquisition functions such as the risk of continuous sampling from lower and cheaper fidelity levels. Experimental validation conducted in surrogate-based optimization and uncertainty quantification scenarios demonstrates the efficacy of the proposed approach. In an aerodynamic shape optimization task focused on maximizing the lift-to-drag ratio, the multi-fidelity strategy achieved comparable results to standard single-fidelity sampling but with approximately a five-fold improvement in computational efficiency. Likewise, a similar reduction in computational costs was observed in the uncertainty quantification problem, with the resulting statistical values aligning closely with those obtained using traditional single-fidelity sampling. [ABSTRACT FROM AUTHOR]

Understanding the physical properties and scattering mechanisms contributes to synthetic aperture radar (SAR) image interpretation. For single-polarized SAR data, however, it is difficult to extract the physical scattering mechanisms due to lack of polarimetric information. Time–frequency analysis (TFA) on complex-valued SAR image provides extra information in frequency perspective beyond the “image” domain. Based on TFA theory, we propose to generate the subband scattering pattern for every object in complex-valued SAR image as the physical property representation, which reveals backscattering variations along slant-range and azimuth directions. In order to discover the inherent patterns and generate a scattering classification map from single-polarized SAR image, an unsupervised hierarchical deep embedding clustering (HDEC) algorithm based on TFA (HDEC-TFA) is proposed to learn the embedded features and cluster centers simultaneously and hierarchically. The polarimetric analysis result for quad-pol SAR images is applied as reference data of physical scattering mechanisms. In order to compare the scattering classification map obtained from single-polarized SAR data with the physical scattering mechanism result from full-polarized SAR, and to explore the relationship and similarity between them in a quantitative way, an information theory based evaluation method is proposed. We take Gaofen-3 quad-polarized SAR data for experiments, and the results and discussions demonstrate that the proposed method is able to learn valuable scattering properties from single-polarization complex-valued SAR data, and to extract some specific targets as well as polarimetric analysis. At last, we give a promising prospect to future applications. [ABSTRACT FROM AUTHOR]

Compressible density-based solvers are widely used in OpenFOAM, and the parallel scalability of these solvers is crucial for large-scale simulations. In this paper, we report our experiences with the scalability of OpenFOAM's native rhoCentralFoam solver, and by making a small number of modifications to it, we show the degree to which the scalability of the solver can be improved. The main modification made is to replace the first-order accurate Euler scheme in rhoCentralFoam with a third-order accurate, four-stage Runge-Kutta or RK4 scheme for the time integration. The scaling test we used is the transonic flow over the ONERA M6 wing. This is a common validation test for compressible flows solvers in aerospace and other engineering applications. Numerical experiments show that our modified solver, referred to as rhoCentralRK4Foam, for the same spatial discretization, achieves as much as a 123.2% improvement in scalability over the rhoCentralFoam solver. As expected, the better time resolution of the Runge–Kutta scheme makes it more suitable for unsteady problems such as the Taylor–Green vortex decay where the new solver showed a 50% decrease in the overall time-to-solution compared to rhoCentralFoam to get to the final solution with the same numerical accuracy. Finally, the improved scalability can be traced to the improvement of the computation to communication ratio obtained by substituting the RK4 scheme in place of the Euler scheme. All numerical tests were conducted on a Cray XC40 parallel system, Theta, at Argonne National Laboratory. [ABSTRACT FROM AUTHOR]

Many composite materials are based on 1D fibers being embedded into 3D solid volumes, e.g. carbon‐fiber reinforced plastics in aerospace engineering or fiber‐reinforced concrete in civil engineering to name only two prominent examples. The present contribution highlights the most important numerical methods and algorithmic building blocks for an efficient analysis of such systems based on cutting‐edge finite element formulations for nonlinear beams and a novel beam‐to‐solid volume coupling approach inspired by classical mortar methods. A particular emphasis is put on the efficient parallel implementation for large‐scale simulations, which includes suitable procedures for domain partitioning and geometry‐based search. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new simulation platform called SIM (Simulation Integrated Management) for analyzing parallel and distributed systems in the aerospace domain. This platform aims to test parallel and distributed architectures and applications. The main characteristics of SIM are its flexibility, scalability, and expandability. SIM has five management functions: model, experiment, distribution, operation, and node management functions. To improve the efficiency of project development, new sub-functionalities and assistive tools were designed for aerospace system simulation missions combined with SIM. Finally, a validation process and evaluation tests were developed and conducted, respectively, to evaluate the SIM simulator. SIM will become an excellent simulation platform with intelligence, versatility, and flexibility, laying the foundation for further validations of autonomy technology used in researches in the aerospace systems engineering domain. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to provide a design solution of an engine intake duct suitable for delivering air to the compressor of a gas turbine engine of a general aviation turboprop aircraft, where the initial duct shape suffers a problem of flow distortion due to flow separation at the compressor inlet.Design/methodology/approach Aerodynamic design uses a three-dimensional inverse-by-optimization approach where the deviation from a desirable target pressure distribution is minimized by means of the adjoint method.Findings By virtue of a minimization algorithm, the specified target pressure distribution does not necessarily have to be fully realizable to drive the initial pressure distribution towards one with a favourable pressure gradient. The resulting optimized engine intake duct features a deceleration region, in a diverging channel, followed by an acceleration region, in a contracting channel, inhibiting flow separation on the compressor inlet plane.Practical implications The flow separation at the compressor inlet has been eliminated allowing proper installation of the engine and flight testing of the aircraft.Originality/value Placement and shaping of the intake duct of a turboshaft and turboprop gas turbine engine is a common industrial problem which can be challenging when the available space is limited. The inverse-by-optimization approach based on a reduced flow model, i.e. inviscid flow based on the Euler equations, and a specification of a simple target pressure distribution constitutes an efficient method to overcome the challenge. [ABSTRACT FROM AUTHOR]

Computational aerodynamics, which complement more expensive empirical approaches, are critical for developing aerospace vehicles. During the past three decades, computational aerodynamics capability has improved remarkably, following advances in computer hardware and algorithm development. However, most of the fundamental computational capability realised in recent applications is derived from earlier advances, where specific gaps in solution procedures have been addressed only incrementally. The present article presents our view of the state of the art in computational aerodynamics and assessment of the issues that drive future aerodynamics and aerospace vehicle development. Requisite capabilities for perceived future needs are discussed, and associated grand challenge problems are presented. [ABSTRACT FROM PUBLISHER]

One key issue in the simulation of bare electrodynamic tethers (EDTs) is the accurate and fast computation of the collected current, an ambient dependent operation necessary to determine the Lorentz force for each time step. This paper introduces a novel semianalytical solution that allows researchers to compute the current distribution along the tether efficient and effectively under orbital-motion-limited (OML) and beyond OML conditions, i.e., if tether radius is greater than a certain ambient dependent threshold. The method reduces the original boundary value problem to a couple of nonlinear equations. If certain dimensionless variables are used, the beyond OML effect just makes the tether characteristic length L* larger and it is decoupled from the current determination problem. Avalidation of the results and a comparison of the performance in terms of the time consumed is provided, with respect to a previous ad hoc solution and a conventional shooting method. [ABSTRACT FROM AUTHOR]

Twin pinion gear pumps are used widely in industrial hydraulics and as fuel-delivery pumps for aero engines. The kinematics of the pumping action leads to high-flow rates into and out of the meshing gears, and at the high speeds used with aerospace fuel pumps cavitation can occur. One-dimensional ‘lumped parameter’ models are often used to analyse this type of pump. These methods rely on an accurate description of the volume trapped by the meshing teeth and the flow areas during the meshing cycle. Typically, multiple computer-aided design models have to be created to calculate these values during the meshing cycle. This paper presents a mathematical method for calculating these parameters based on a parametric definition of the gear and inlet and outlet porting. Green's theorem is used to allow line integrals around the periphery of the tooth spaces to be used to calculate the volumes and flow areas. Winding numbers are used to calculate the inflow and outflow areas that are formed by the intersection of the trapped volume and the side area porting. The method is validated against computer-aided design model data. This method is well suited for incorporation in an optimisation algorithm since the geometry is defined parametrically. [ABSTRACT FROM AUTHOR]

Noise radar systems transmitting incoherent signal sequences have been proposed as powerful candidates for implementing compressively sampled detection and imaging systems. This paper presents an analysis of compressively sampled noise radar systems by formulating ultrawideband (UWB) compressive noise radar imaging as a problem of inverting ill-posed linear systems with circulant system matrices. The nonlinear nature of compressive signal recovery presents challenges in characterizing the performance of radar imaging systems. The suitability of noise waveforms for compressive radar is demonstrated using phase transition diagrams and transform point spread functions (TPSFs). The numerical simulations are designed to provide a compelling validation of the system. Nonidealities occurring in practical compressive noise radar systems are addressed by studying the properties of the transmit waveform. The results suggest that waveforms and system matrices that arise in practical noise radar systems are suitable for compressive signal recovery. Field imaging experiments on various target scenarios using a UWB millimeter wave noise radar validate our analytical results and the theoretical guarantees of compressive sensing. [ABSTRACT FROM AUTHOR]

We present low-complexity, quickly converging robust adaptive beamformers, for beamforming large arrays in snapshot deficient scenarios. The proposed algorithms are derived by combining data-dependent Krylov-subspace-based dimensionality reduction, using the Powers-of-R or conjugate gradient (CG) techniques, with ellipsoidal uncertainty set based robust Capon beamformer methods. Further, we provide a detailed computational complexity analysis and consider the efficient implementation of automatic, online dimension-selection rules. We illustrate the benefits of the proposed approaches using simulated data. [ABSTRACT FROM AUTHOR]

SUMMARY One of the major challenges of shape optimisation in practical industrial cases is to generically parametrise the wide range of complex shapes. A novel approach is presented, which takes CAD descriptions as input and produces the optimal shape in CAD form using the control points of the Non-Uniform Rational B-Splines (NURBS) boundary representation as design variables. An implementation of the NURBS equations in source allows to include the CAD-based shape deformation inside the design loop and evaluate its sensitivities efficiently and robustly. In order to maintain or establish the required level of geometric continuity across patch interfaces, geometric constraints are imposed on the control point displacements. The paper discusses the discrete adjoint flow solver used and the computation of the complete sensitivities of the design loop by differentiating all components using automatic differentiation tools. The resulting rich but smooth deformation space is demonstrated on the optimisation of a vehicle climate duct. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

An acceleration model and a jerk model are proposed in this paper for kinematic state estimation of re-entry ballistic targets. The models proposed here use fully coupled equations of the target kinematics, without assuming any model structure for variations of ballistic coefficient and air density as found in the literature. The novelty of the algorithms lies in the bootstrapped computation of the model parameter γ, which is the ratio of air density and ballistic coefficient, at every time step, utilizing the estimated velocity and acceleration. γ and its time derivatives, thus computed, are used for parameterization of DA and DJ models for estimating position, velocity and acceleration. This makes the algorithms inherently adaptive to the variations of the ballistic coefficient and the air density during the re-entry trajectory. It is demonstrated that the proposed models produce unbiased estimates of target acceleration as opposed to biased estimates from the existing models. [ABSTRACT FROM AUTHOR]

For polymer matrix composites subjected to large strain rates, it is important to correctly characterize the nonlinear and strain-rate dependent response of polymers. Viscoplastic constitutive material models have been developed to account for the effects of hydrostatic effects and inelastic strains in polymer materials. The effective implementation of such viscoplastic models is important for development of composite models geared toward practical applications. Goldberg’s polymer model numerical implementation into a commercial finite-element code constitutes the main objective of this paper. Special attention is given to the use of effective algorithms for solving the model nonlinear rate dependent viscoplastic equations. Existent experimental data are used to verify the accuracy and robustness of the computational polymer model. A phenomenological fiber model and a simplified iso-strain mixture theory used to obtain the resultant stresses in the composite by averaging the stresses of the individual constituents are also defined. The validation of the simplified mixture theory for the composite model will be presented later on. [ABSTRACT FROM AUTHOR]

A pressurized gravitational capillary viscometer was developed for subcooled liquefied gases such as oxygen, nitrogen, hydrogen, and methane. It acquires accurate absolute viscosity measurements with an uncertainty of 1% at a 95.5% confidence level, necessary for the demands of aerospace engineering. The viscometer includes a coiled capillary of electroformed nickel that hydraulically connects two reservoirs located at equal heights. Using helium gas to temporarily drive liquid from a third supply reservoir, a level difference is created between the first two reservoirs without the need to tilt or invert the viscometer. Helium gas is then used to pressurize the first two reservoirs equally. Each reservoir holds a capacitive liquid-level sensor that both measure the flow induced by gravity through the capillary more precisely than by visual observations through windows. Viscosity data for liquid oxygen were acquired in the pressure domain from 0.15 to 1.0 MPa and in the temperature domain from the normal boiling point to near the freezing point. Published viscosity data and correlations for subcooled liquid oxygen are not precise nor complete in this density regime. Accordingly, the viscosity data delivered by the viscometer of the present work are superior. [ABSTRACT FROM AUTHOR]

This paper describes a vision-based control system for a tracked mobile robot (an excavator). The system includes several controllers that collaborate to move the mobile vehicle from a starting position to a goal position. First, the path planner designs an optimum path using a predefined elevation map of the work space. Second, a fuzzy logic path-tracking controller estimates the rotational and translational velocities for the vehicle to move along the predesigned path. Third, a cross coupling controller corrects the possible orientation error that may occur when moving along the path. A motor controller then converts the track velocities to the corresponding rotational wheel velocities. Fourth, a vision-based motion tracking system is implemented to find the three-dimensional (3-D) motion of the vehicle as it moves in the work space. Finally, a specially-designed slippage controller detects slippage by comparing the motion through reading of flowmeters and the vision system. If slippage has occurred, the remaining path is corrected within the path tracking controller to stop at the goal position. Experiments are conducted to test and verify the presented control system. An analysis of the results shows that improvement is achieved in both path-tracking accuracy and slippage control problems. [ABSTRACT FROM AUTHOR]

The demand for lightweight structures in aerospace and automotive is on the rise and so are the requirements regarding the vibro‐acoustic behavior. Materials with a high stiffness‐to‐mass ratio are often used in this field, but these materials typically have an unfavorable vibrational behavior regarding structure‐borne noise. Acoustic metamaterials offer a solution for improving the vibro‐acoustic performance of the structure, while the stiffness‐to‐mass ratio remains nearly constant. Such a metamaterial consists of periodic patterns of microstructures placed on the host structure. They modify the vibrational behavior of the host by adding local resonances and thus minimize vibrations at specific frequencies. Distinct resonances can have a major contribution to the acoustic behavior of a structure, so it is of interest to tailor microstructures, that generate stop bands at certain frequencies. This can be computationally expensive, so efficient numerical models are required for the design of acoustic metamaterials. Initial investigations show, that a parametric model order reduction (PMOR) method based on the Loewner framework can generate such models. [ABSTRACT FROM AUTHOR]

A divisible load can be arbitrarily divided into independent small load fractions which are assigned to processors in a parallel or distributed computing system for simultaneous processing. The theory and techniques of divisible load distribution have a wide range of aerospace applications, including satellite signal and image processing, radar and infrared tracking, target identification and searching, and data reporting and aggregation and processing in wireless sensor networks. We make new progress on divisible load distribution on tree and pyramid networks. We revisit the classic method for divisible load distribution on partitionable static interconnection networks (including complete tree and pyramid networks) and derive a closed-form expression of the parallel time and speedup. We propose two new methods which employ pipelined communication techniques to distribute divisible loads on tree and pyramid networks. We derive closed-form expressions of the parallel time and speedup for both methods and show that the asymptotic speedup of both methods is b\beta+1 for a complete b-ary tree network and 4\beta+1 for a pyramid network, where \beta is the ratio of the time for computing a unit load to the time for communicating a unit load. The technique of pipelined communications leads to improved performance of divisible load distribution on tree and pyramid networks. Compared with the classic method, the asymptotic speedup of our new methods is 100% faster on a complete binary tree network and 33% faster on a pyramid network for large \beta. [ABSTRACT FROM PUBLISHER]

This paper is an introduction for the nonpractitioner to the ideas and issues of LISA data analysis, as reflected in the explorations and experiments of the participants in the Mock LISA Data Challenges. In particular, I discuss the methods and codes that have been developed for the detection and parameter estimation of supermassive black-hole binaries, extreme mass-ratio inspirals and galactic binaries. [ABSTRACT FROM AUTHOR]

Due to numerous applications of micro-/nano-sized structures in medical, electrical, mechanical, and aeronautical engineering, etc., mathematical modelling of thermoelastic diffusive responses of these structures has become a hot topic of investigation. The inclusion of fractional-order derivatives in these models brings out more productive results. Thus considering fractional generalized thermoelastic diffusion model with nonlocal elastic effects, transient responses of a transversely isotropic hollow cylinder are analysed. The medium is held at undisturbed state initially and periodically varying thermal and continuous concentration loadings applied at the outer boundary of the cylinder. Assuming the plane strain and axisymmetry in the cylinder, the problem is reduced to one dimension which is solved using Laplace transformation along with inversion technique. The objective of this work is to theoretically investigate the impact of nonlocal and fractional-order parameters on thermophysical quantities of a transversely isotropic hollow cylinder and consideration of diffusion phenomenon along with the said effects augments the novelty of this work. Thus, the graphical representation of the results reveals that displacement is less perturbed with the introduction of the nonlocal elastic parameter. The fractional-order parameter has an increasing impact on thermal and diffusion profiles. Time has varying degrees of influence on all the physical quantities. [ABSTRACT FROM AUTHOR]

In aerospace engineering, the incomplete environment conditions have been realized to be a significant factor affecting the system safety assessment. Considering the hybrid random and fuzzy uncertainties in system inputs, the paper proposes a novel numerical procedure for reliability analysis and reliability-based optimization. Random parameters are adopted to denote the aleatory uncertainties with sufficient sample information; whereas fuzzy parameters are used to quantify the epistemic uncertainties associated with expert opinions. Using the level-cut operation, fuzzy parameters are converted into interval variables, and a satisfaction degree-based interval ranking strategy is utilized to precisely quantify the interval safety possibility. Then the system safety possibility is calculated by the multiple integral, where cut levels of different fuzzy parameters are treated as independent variables. Subsequently based on the given safety index, a hybrid reliability optimization model is established. To avoid the huge computational burden caused by nested-loop optimization, a modified interval Monte Carlo method (MIMC) is proposed for limit state function evaluation. Eventually, a numerical example about the refractory ceramics tile of spacecraft verifies the feasibility of proposed method for hybrid reliability analysis and optimization design in practical aerospace engineering. [ABSTRACT FROM AUTHOR]