bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deep Active Subspaces: A Scalable Method for High-Dimensional Uncertainty Propagation
Authors: Tripathy Rohit , Bilionis Ilias 
Published: November 2019

Abstract
A problem of considerable importance within the field of uncertainty quantification (UQ) is the development of efficient methods for the construction of accurate surrogate models. Such efforts are particularly important to applications constrained by high-dimensional uncertain parameter spaces. The difficulty of accurate surrogate modeling in such systems, is further compounded by data scarcity brought about by the large cost of forward model evaluations. Traditional response surface techniques, such as Gaussian process regression (or Kriging) and polynomial chaos are difficult to scale to high dimensions. To make surrogate modeling tractable in expensive high-dimensional systems, one must resort to dimensionality reduction of the stochastic parameter space. A recent dimensionality reduction technique that has shown great promise is the method of ‘active subspaces’. The classical formulation of active subspaces, unfortunately, requires gradient information from the forward model — often impossible to obtain. In this work, we present a simple, scalable method for recovering active subspaces in high-dimensional stochastic systems, without gradient-information that relies on a reparameterization of the orthogonal active subspace projection matrix, and couple this formulation with deep neural networks. We demonstrate our approach on challenging synthetic datasets and show favorable predictive comparison to classical active subspaces.
Bio-Inspired Modeling Approaches for Human Networks With Link Dissipation
Authors: Panyam Varuneswara , Layton Astrid 
Published: November 2019

Abstract
Structural similarities between human networks and biological ecosystems have inspired biomimetic design of human networks. The approach requires the networks to be represented as graphs, where the actors are nodes and the connections between actors are links. A major oversight in the application of ecosystem-based modeling to human networks thus far has been in the selection of actors and links. Transfers between species in a biological ecosystem are direct, happening when the species are co-located. Human networks often require a physical aid to complete the transaction, such as power transmission lines, pipelines, or vehicles. These exchange methods experience dissipation, which is not captured in current applications of ecosystem-based human network modeling. Human networks modeled as ecosystems thus far simply categorize exchanges as links in the graph, effectively forcing dissipation during material/energy transport to be neglected. This dissipation can sometimes be high relative to the total energy/material exchanged and thus is a potentially large oversight. Three hypothetical power grids and three Italian urban water distribution networks are used to quantify the impact of modeling interaction aids — power lines and water pipelines — as actors (and thus including any dissipation) in an ecosystem model. Ecological structural and flow metrics previously applied to human networks are evaluated between the two modeling methods. The comparison shows that the impact of this overlooked aspect is potentially significant and warrants consideration.
Design and Biological Simulation of 3D Printed Lattices for Biomedical Applications
Authors: Egan Paul F. 
Published: November 2019

Abstract
There is great potential for using 3D printed designs fabricated via additive manufacturing processes for diverse biomedical applications. 3D printing offers capabilities for customizing designs for each new fabrication that could leverage automated design processes for personalized patient care, but there are challenges in developing accurate and efficient assessment methods. Here, we conduct a sensitivity analysis for a biological growth simulation for evaluating 3D printed lattices for regenerating bone and then use these simulations to identify performance trends. Four design topologies were compared by generating varied unit cells. Biological growth was modeled in a voxel environment by simulating the advancement of a tissue front by calculating its local curvature. Designs were generated with properties suitable for bone tissue engineering, namely 50% porosity and microscale pores. The sensitivity analysis determined trade-offs between prediction consistency and computation time, suggesting calculating curvature within a radius of 7.5 voxels is sufficient for most cases. Topologies were compared in bulk with design variations. All topologies had similar tissue growth rates for a given surface-volume ratio, but with differing unit cell sizes. These findings inform future optimization for selecting unit cells based on volume requirements and other criteria, such as mechanical stiffness. A fitted analytical relationship predicted tissue growth rate based on a design’s surface-volume ratio, which enables design evaluation without computationally expensive simulations. Lattices were 3D printed with biocompatible materials as proof-of-concepts, demonstrating the feasibility of the approach for future computational design methods for personalized medicine.
On the Friction Isolator for Precision Motion Control and its Dynamics
Authors: Dong Xin , Okwudire Chinedum , Wang Jiamin , Barry Oumar 
Published: November 2019

Abstract
Motion stages are widely used for precision positioning in manufacturing and metrology applications. However, they suffer from nonlinear pre-motion (i.e., “static”) friction which adversely affects their precision and motion speed. Existing friction compensation methods are not robust enough to handle the highly nonlinear and variable dynamic behavior of pre-motion friction. Therefore, the first two authors have proposed the concept of a friction isolator as a simple and robust solution to mitigate the undesirable effects of pre-motion friction in precision motion stages. They experimentally demonstrated that a motion stage with friction isolator can achieve significantly improved precision, speed and robustness to variations in pre-motion friction. However, a theoretical study was not carried out to fundamentally understand the dynamic phenomena associated with using a friction isolator on a motion stage. This introductory paper investigates the dynamics of a PD-controlled motion stage with friction isolator. The influence of the friction isolator on the response and stability of the system is examined through theoretical and numerical analysis. It is shown, using a case study, that the addition of a friction isolator shrinks the range of P and D gains that can stabilize the motion stage. Several other case studies that include the effects of external excitation and integral controller are carried out to motivate deeper dynamic analyses of the friction isolator for precision motion control.
Reference Governors Based on Online Learning of Maximal Output Admissible Set
Authors: Lanchares Manuel , Kolmanovsky Ilya , Girard Anouck , Rizzo Denise 
Published: November 2019

Abstract
Reference governors are add-on control schemes that modify the reference commands, if it becomes necessary, in order to avoid constraint violations. To implement a reference governor, explicit knowledge of a model of the system and its constraints is typically required. In this paper, a reference governor which does not require an explicit model of the system or constraints is presented. It constructs an approximation of the maximal output admissible set, as the system operates, using online neural network learning. This approximation is used to modify the reference command in order to satisfy the constraints. The potential of the algorithm is demonstrated through simulations for an electric vehicle and an agile positioning system.
Energy Optimization of Lateral Motions for Autonomous Ground Vehicles With Four-Wheel Steering Control
Authors: Wang Fengchen , Xu Peidong , Li Ao , Chen Yan 
Published: November 2019

Abstract
In this paper, a hierarchical optimal four-wheel steering (4WS) controller is proposed to enhance the energy saving for vehicle lateral motions. By the integration of the four-wheel vehicle dynamics, wheel dynamics, and tire model, the vehicle propulsion power consumption is derived with respect to the front and rear wheel steering angles as control inputs. In the high level of the proposed controller, an autonomous path following control is developed to provide virtual control inputs including the lateral forces and yaw moment via the dynamic sliding mode control design. In the low level, the high-level virtual control inputs are distributed to the front and rear steering angles, in which the energy optimization problem is solved. The objective function of the optimization problem aims to minimize the vehicle propulsion power consumption and virtual control tracking error. Furthermore, the requirements of the vehicle stability and the path following accuracy are considered in the constraints. Verified by CarSim® and MATLAB/Simulink® co-simulation, the proposed 4WS hierarchical energy optimization controller can successfully reduce the power loss for vehicle lateral motions.
Gaussian-Based Kernel for Multi-Agent Aerial Chemical-Plume Mapping
Authors: He Xiang , Steiner Jake A. , Bourne Joseph R. , Leang Kam K. 
Published: November 2019

Abstract
This paper presents a multi-vehicle chemical-plume mapping process that incorporates onboard wind speed and direction estimation. A Gaussian plume model is exploited to develop the kernel for extrapolating the measured data. Compared to the uni- or bi-variate kernels, the proposed kernel uses the estimated wind information to refine the chemical concentration prediction downwind of the source. This new approach, compared to previous mapping methods, relies on fewer parameters and provides 30% reduction in the mapping mean-squared error. Simulation and experimental results are presented to validate the approach. Specifically, outdoor flight tests show three aerial robots with chemical sensing capabilities mapping a real propane gas leak to demonstrate feasibility of the approach.
A Preliminary Study on a Physical Model Oriented Learning Algorithm With Application to UAVs
Authors: Zheng Minghui , Chen Zhu , Liang Xiao 
Published: November 2019

Abstract
This paper provides a preliminary study for an efficient learning algorithm by reasoning the error from first principle physics to generate learning signals in near real time. Motivated by iterative learning control (ILC), this learning algorithm is applied to the feedforward control loop of the unmanned aerial vehicles (UAVs), enabling the learning from errors made by other UAVs with different dynamics or flying in different scenarios. This learning framework improves the data utilization efficiency and learning reliability via analytically incorporating the physical model mapping, and enhances the flexibility of the model-based methodology with equipping it with the self-learning capability. Numerical studies are performed to validate the proposed learning algorithm.
Generic On-Board Decision Support System Framework for Marine Operations
Authors: Skjong Stian , Kyllingstad Lars T. , Reite Karl-Johan , Haugen Joakim , Ladstein Jarle , Aarsæther Karl Gunnar 
Published: November 2019

Abstract
In this work, we present a generic framework for designing on-board decision support systems for marine operations. We discuss different technologies and methods for obtaining and analysing data and providing relevant information to on-board personnel. In particular, we focus on combining and integrating simulators with measurements, both live and stored historical data, in on-board systems for both pre-operational planning and live situation observers that might have predictive functionalities. To exemplify, we present four case studies: The first two are concerned with development of an on-board decision support system for offshore crane operations. Here, vessel motion measurements and numerical models are combined for both on-board surveillance applications and on-board pre-operational planning applications, where the latter include historical vessel characteristics. In the third, we combine simulations, measurements and automatic control in an application aimed at triple-trawl fishing operations. Finally, we present a data-driven decision support system for energy-efficient operation of hybrid propulsion systems.
Evaluation of Flow Field in the Layouts of Cross-Shaped Artificial Reefs
Authors: Tang Yanli , Hu Qi , Wang Xinxin , Zhao Fenfang , Huang Liuyi , Xie Tao 
Published: November 2019

Abstract
Artificial reefs (ARs) are purposely submerged in natural aquatic environments to provide additional habitat for fish. The reasonable layout of ARs on the sea floor can effectively enhance and support important marine species. This research involves a three-dimensional numerical simulation to analyze the flow effect of three types of AR layouts based on computational fluid dynamics. Through numerical simulation of the flow past the reefs, we can determine the scale of the upwelling and back-eddy flow. Based on the simulation data, the rational transverse distance between two cross-shaped artificial reefs (CSARs) is 6L (L is the length of the single reef), which is used to design the layouts of CSARs. Five indicators have been used to evaluate the flow field effect of these three layouts. According to the comparison of five indications for different layouts of CSAR, it is more reasonable to divide the AR layouts into two categories: upwelling layout and back eddy layout. Finally, the sphere of influence of the AR layouts on the fisheries resource is also discussed.
Numerical Simulation of Solitary Wave Breaking With Adaptive Mesh Refinement
Authors: Zhang Yunxing , Duan Wenyang , Liao Kangping , Ma Shan , Xia Guihua 
Published: November 2019

Abstract
The numerical simulation of wave breaking problem is still a tough challenge, partly due to the large grid number and CPU time requirement for capturing the multi-scale structures embedded in it. In this paper, a two-dimensional two-phase flow model with Adaptive Mesh Refinement (AMR) is proposed for simulating solitary wave breaking problems. Fractional step method is employed for the velocity-pressure decoupling. The free surface flow is captured with the Volume-of-Fluid (VOF) method combined with Piecewise Linear Interface Calculation (PLIC) for the reconstruction of the interface. Immersed boundary (IB) method is utilized to account for the existence of solid bodies. A geometric multigrid method is adopted for the solution of Pressure Poisson Equation (PPE).
Benchmark case of advection test is considered first to test the VOF method. Then the solitary wave propagation problem is utilized to validate the model on AMR grid as well as analyze the efficiency of AMR. Furthermore, the solitary wave past a submerged stationary stage problem is simulated to validate the combined IB-VOF-AMR model. All the numerical results are compared with analytic solutions, experimental data or other published numerical results, and good agreements are obtained. Finally, the influence of stage height on the occurrence of wave breaking is analyzed. The locations of wave breaking are summarized for different stage heights.
Fluid-Structure-Soil Interaction of a Moored Wave Energy Device
Authors: Tom Joe G. , Rijnsdorp Dirk P. , Ragni Raffaele , White David J. 
Published: November 2019

Abstract
This paper explores the response of a wave energy device during extreme and operational conditions and the effect of this response on the geotechnical stability of the associated taut moorings. The non-hydrostatic wave-flow model SWASH is used to simulate the response of a taut-moored wave energy converter. The predicted forces acting on the mooring system are used to compute the build-up of excess pore pressures in the soil around the mooring anchor and the resulting changes in strength and capacity. An initial loss of strength is followed by a subsequent increase in capacity, associated with long-term cyclic loading and hardening due to consolidation. The analyses show how cyclic loading may actually benefit and reduce anchoring requirements for wave energy devices. It demonstrates the viability of a close interdisciplinary approach towards an optimized and cost-effective design of mooring systems, which form a significant proportion of expected capital expenditures.
Optimal Methods for Estimating the JONSWAP Spectrum Peak Enhancement Factor From Measured and Hindcast Wave Data
Authors: Ewans Kevin , McConochie Jason 
Published: November 2019

Abstract
The specification of design wave spectra is based on spectral parameters estimated from available wave data. Measured data allow high-resolution estimates to be made, but they suffer from sampling variability and often do not contain a sufficient number of measurements in extreme sea states. Hindcast data can be used to examine spectral features associated with extreme sea states, but they can be limited by resolution and are dependent on how the physics are incorporated in the source terms of the wave model. We examine and compare the effects of estimating JONSWAP spectrum peak enhancement factor from measured and hindcast data for a range of sea states but particularly those with large significant wave heights. In the case of measured data, we build on earlier work and review effects associated with different methods for processing measured time series data, including the effect of sampling frequency, record length, and smoothing. These are then contrasted with estimates made from typical hindcast data, including the effect of the spectral shape associated with different source terms — in particular the four-wave interaction term. Finally, we provide recommendations on how best to estimate the peak enhancement factor of the JONSWAP spectrum for design purposes.
Baseline Design of the Deep Turbine Installation-Floating, a New Floating Wind Concept
Authors: Serret Jordi , Tezdogan Tahsin , Stratford Tim , Thies Philipp R. , Venugopal Vengatesan 
Published: November 2019

Abstract
This paper presents the preliminary design of the Deep Turbine Installation-Floating (DTI-F) concept. The DTI-F concept is a hybrid spar buoy-based floating offshore substructure capable of supporting a 7MW wind turbine with the uniqueness of being able to raise and lower the tower and nacelle, which simplifies construction, installation, maintenance, and decommissioning.
A relevant subset of design load cases (DLCs) derived from the International Electrotechnical Commission (ICE) standards is simulated with NREL-FAST software, and the aero-elastic loads are used for the structural assessment.
The paper presents the principal dimensions and crucial hydrostatic and hydrodynamic properties. The floating platform with three different mooring configurations is designed using ANSYS AQWA software, and the design is validated with experiments in laboratory conditions. The paper evaluates the design regarding the natural frequencies and the stability of the platform for a chosen site off the Scottish coast.
Further, a novel construction method, the materials chosen for the construction, and the installation and assembly processes are also outlined.
Big Data Analytics As a Tool to Monitor Hydrodynamic Performance of a Ship
Authors: Gupta Prateek , Steen Sverre , Rasheed Adil 
Published: November 2019

Abstract
A modern ship is fitted with numerous sensors and Data Acquisition Systems (DAQs) each of which can be viewed as a data collection source node. These source nodes transfer data to one another and to one or many centralized systems. The centralized systems or data interpreter nodes can be physically located onboard the vessel or onshore at the shipping data control center. The main purpose of a data interpreter node is to assimilate the collected data and present or relay it in a concise manner. The interpreted data can further be visualized and used as an integral part of a monitoring and decision support system. This paper presents a simple data processing framework based on big data analytics. The framework uses Principal Component Analysis (PCA) as a tool to process data gathered through in-service measurements onboard a ship during various operational conditions. Weather hindcast data is obtained from various sources to account for environmental loads on the ship. The proposed framework reduces the dimensionality of high dimensional data and determines the correlation between data variables. The accuracy of the model is evaluated based on the data recorded during the voyage of a ship.
Axial Resistance of Smooth Polymer Pipelines on Sand
Authors: Milewski Henry , Dietz Matt , Diambra Andrea , de Leeuw Lawrence W. 
Published: November 2019

Abstract
The axial resistance of pipelines is an important design input, influencing a variety of analyses such as buckling and axial walking. As such, accurate assessment of the frictional behaviour of the soil-pipeline interface is necessary to properly model axial behaviour. Smooth polymer coated pipelines are commonly used subsea, yet despite their common application, limited guidance exists in the main governing standards concerning the expected level of axial friction to be used in design. Related guidance that does exist (e.g. BSI, 2016) suggests a minimum friction coefficient of 0.55 for sand-pipeline interfaces. This paper reviews various aspects of sand-polymer direct shear interface testing that must be considered and presents the results of some experimental research TechnipFMC have undertaken in collaboration with the University of Bristol. These results indicate that a sand-pipeline friction coefficient of 0.55 is often unrealistic for smooth polymer coated pipelines and in many design scenarios a lower frictional coefficient is more appropriate.
The experimental test program considered the main factors believed to influence axial friction of smooth polymers on sand including D50 grain size, sand density and a range of stress levels (including the low stresses expected for subsea pipelines). All tests were conducted fully saturated to mimic subsea conditions and the roughness of the pipe coating samples was thoroughly characterised. TechnipFMC project experience has found that use of lower axial friction is sometimes beneficial (e.g. axial feed-in to trigger buckle initiation). In other cases, a higher axial friction may be better for design (e.g. limiting axial walking). Being able to better characterise the friction range is therefore important to ensure a robust design and to assist in avoiding more costly mitigation measures where they may not actually be needed.