bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identification of Dynamic Coefficients of a Five-Pad Tilting Pad Journal Bearing Up to Highest Surface Speeds
Authors: Zemella Philipp , Hagemann Thomas , Pfau Bastian , Schwarze Hubert 
Published: January 2021

Abstract
Tilting-pad journal bearings are widely used in turbomachinery industry due to their positive dynamic properties at high rotor speeds. However, the exact description of this dynamic behavior is still part of current research. This paper presents the measurement results for a five-pad tilting-pad journal bearing in load between pivot configurations. The bearing is characterized by a nominal diameter of 100 mm, a length of 90 mm, and a pivot offset of 0.6. Investigations include the results for surface speeds between 25 and 120 m/s and specific bearing loads ranging from 0.0 to 3.0 MPa. The results of theoretical predictions are commonly derived from perturbation of stationary operation under static load. Therefore, experimental results for stationary operation including pad deflection under static load are presented first to characterize the investigated bearing. Measured results indicate considerable nonlaminar flow in the upper region of the investigated range of rotor speeds. Second, dynamic excitation tests are performed with excitation frequencies up to 400 Hz to evaluate dynamic coefficients of a stiffness (K) and damping (C) KC model, and additionally, a KCM model using additional virtual mass (M) coefficients. KCM coefficients are obtained by fitting frequency dependent KC-characteristics to the KCM model structure using least square approach. The wide range of rotating and excitation frequencies leads to subsynchronous as well as supersynchronous vibrations. Excitation forces are applied with multisinus and single-sinus characteristics. The latter one allows evaluation of KC coefficients at the particular frequency ratio in the time domain. Here, frequency and time domain evaluation algorithms for dynamic coefficients are used in order to assess their special properties and quality. The impact of surface speed, bearing load, and oil flow rate on measured and predicted KCM coefficients is investigated. Measured and predicted results can be well fitted to a KCM model and show a significant influence of the ratio between fluid film and pivot support stiffness on the speed dependent characteristic of bearing stiffness coefficients. However, the impact of this ratio on damping coefficients is considerably lower. Further investigations on the impact of oil flow rates indicate that a significant decrease of direct damping coefficients exists below a certain level of starvation. Above this limit, direct damping coefficients are nearly independent of oil flow rate. Results are analyzed in detail and demands on improvements for predictions are derived.
Failure Modeling and Sensitivity Analysis of Ceramics Under Impact
Authors: Bhattacharjee Amartya , Bhaduri Anindya , Hurley Ryan C. , Graham-Brady Lori 
Published: January 2021

Abstract
A micromechanical multi-physics model for ceramics has been recalibrated and used to simulate impact experiments with boron carbide in abaqus. The dominant physical mechanisms in boron carbide have been identified and simulated in the framework of an integrated constitutive model that combines crack growth, amorphization, and granular flow. The integrative model is able to accurately reproduce some of the key cracking patterns of Sphere Indentation experiments and Edge On Impact experiments. Based on this integrative model, linear regression has been used to study the sensitivity of sphere indentation model predictions to the input parameters. The sensitivities are connected to physical mechanisms, and trends in model outputs have been intuitively explored. These results help suggest material modifications that might improve material performance, prioritize calibration experiments for materials-by-design iterations, and identify model parameters that require more in-depth understanding.
Hemodynamic Assessment of Hollow-Fiber Membrane Oxygenators Using Computational Fluid Dynamics in Heterogeneous Membrane Models
Authors: Dipresa Daniele , Kalozoumis Panagiotis , Pflaum Michael , Peredo Ariana , Wiegmann Bettina , Haverich Axel , Korossis Sotirios 
Published: January 2021

AbstractExtracorporeal membrane oxygenation (ECMO) has been used clinically for more than 40 years as a bridge to transplantation, with hollow-fiber membrane (HFM) oxygenators gaining in popularity due to their high gas transfer and low flow resistance. In spite of the technological advances in ECMO devices, the inevitable contact of the perfused blood with the polymer hollow-fiber gas-exchange membrane, and the subsequent thrombus formation, limits their clinical usage to only 2–4 weeks. In addition, the inhomogeneous flow in the device can further enhance thrombus formation and limit gas-transport efficiency. Endothelialization of the blood contacting surfaces of ECMO devices offers a potential solution to their inherent thrombogenicity. However, abnormal shear stresses and inhomogeneous blood flow might affect the function and activation status of the seeded endothelial cells (ECs). In this study, the blood flow through two HFM oxygenators, including the commercially available iLA® MiniLung Petite Novalung (Xenios AG, Germany) and an experimental one for the rat animal model, was modeled using computational fluid dynamics (CFD), with a view to assessing the magnitude and distribution of the wall shear stress (WSS) on the hollow fibers and flow fields in the oxygenators. This work demonstrated significant inhomogeneity in the flow dynamics of both oxygenators, with regions of high hollow-fiber WSS and regions of stagnant flow, implying a variable flow-induced stimulation on seeded ECs and possible EC activation and damage in a biohybrid oxygenator setting.
Parametric Wave Spectrum Model for Typhoon-Generated Waves Based on Field Measurements in Nearshore Strait Water
Authors: Wei Kai , Imani Hasan , Qin Shunquan 
Published: January 2021

AbstractThe stochastic waves generated by storm landfalls usually determine the design and safety of coastal and offshore structures in typhoon regions. This study developed a parametric wave spectrum model for typhoon-generated stochastic waves that considers the variation in the wave spectrum due to the temporal variation in the typhoon. A field measurement campaign was conducted in nearshore strait water on the east coast of China to measure the wave data for two landfall typhoons: Soudelor and Dujuan. The measured wave data were filtered through a preprocessing framework. The parametric wave spectrum model was then developed based on the measured wave spectra for different stages of the typhoon. The main conclusions include the following: (1) 78% of the measured wave spectra at the example site under a typhoon are double-peaked, and approximately 15% are single-peaked; (2) the parametric model with either the Joint North Sea Wave Project (JONSWAP) or Ochi-Hubble (OH) kernel function is effective in defining the typhoon-generated wave spectra; and (3) the critical parameters of the developed model for typhoon-generated waves are site-specific and depend on the temporal variation of the typhoon.
Control Allocation Application to Automotive Suspension Actuators for Handling Objectives
Authors: Beckerman Alex K. , Abapo Gladys , Clemen Layne 
Published: January 2021

Abstract
Current research within the automotive community suggests an increasing trend in applying mechatronic actuators for improved ride and handling. In particular, there is an increasing trend towards semi-active and active suspension actuators. This research presents various novel suspension control strategies specific to handling by building upon a control allocation type framework. Such a framework is common in the aerospace and marine industries due its multi-objective control properties, suitability for over-actuated systems, the ease in which nonlinear or time-varying properties are included, in addition to many other benefits. Control allocation is becoming increasingly more appropriate for automotive applications due to the increasing trend in applying mechatronic actuators for improved ride and handling.
Specifically, this paper develops methods for improving yaw rate with active suspension actuators. It will be shown that this task is nontrivial within an allocation framework due to properties of the physical system. By using the methods developed in this paper, it becomes trivial to incorporate this and other handling related methods into a larger and more integrated framework with a higher number of control objectives and actuators. The methods in this paper take advantage of the complicated dynamics and inherent nonlinear relationship between suspension actuator forces and resultant tire lateral forces. It is demonstrated through simulation that a vehicle with the proposed allocation framework outperforms a vehicle with no suspension actuation. Different methods are evaluated and compared based on stability and robustness properties.
On the Nonlinear Vibration Analysis of a Hand-Held Impact Machine
Authors: Alabi Oreoluwa , Barry Oumar 
Published: January 2021

Abstract
Prolonged exposure of the human arm to vibrations from hand-held impact (HIM) tools can be hazardous as such, it is important that the level of vibration suppression in HIMs is improved. This paper sought to address this issue by studying a model of the hand-arm system (HAS) coupled to a HIM which is also coupled to a nonlinear tuned vibration absorber inerter (NVAI). The HAS is modelled as a 2-DOF system coupled to the HIM at a single point. The HIM is modelled as an oscillator with linear damping, and both linear and nonlinear stiffnesses. The nonlinear stiffness of the HIM is introduced to represent the nonlinearities introduced by the vibro-impact dynamics of the HIM. After obtaining the equations of motion for the system, an analytical solution is obtained using the harmonic balance method. The analytical solution is validated using direct numerical integration and the results show very good agreement. The performance of the NVAI is compared to those of the classical nonlinear and linear vibration absorbers. Parametric study is carried out to examine the role of key design parameters, such as the damping of the absorber, nonlinear stiffness of the HIM and inertance of the NVAI, on the performance of the NVAI.
Improving Passenger Comfort by Exploiting Hub Motors in Electric Vehicles: Suspension Modeling
Authors: Chen Di , Danielson Claus , Iezawa Masahiro 
Published: January 2021

Abstract
This paper examines using electric vehicles with independently actuated wheels and anti-squat/lift/dive suspensions to improve passenger comfort by reducing the lift, pitch, and roll motion of the vehicle chassis. Anti-squat/lift/dive suspensions use an angled suspension bar to transfer a portion of the longitudinal driving force into a vertical reaction force on the chassis. Using this effect, we derive a control-oriented model of the lift, pitch, and roll of the chassis where the steering angle and the four driving forces of the individual wheels are the control inputs and the road-height is a disturbance. The model is simplified under the assumption that the suspension deflections are small during normal, comfortable driving. Finally, we use steady-state analysis and open-loop simulations to provide intuition about the relationship between the driving forces and the chassis motions.
Galvanic Skin Response As a Measure of Engagement During Play in Virtual Reality
Authors: Ventura Roni Barak , Porfiri Maurizio 
Published: January 2021

Abstract
Competition is a common design strategy used to enhance user engagement and participation. However, it remains unclear how winning or losing might influence player’s engagement. In a recent study, we used behavioral metrics to quantify player engagement during competitive gameplay in virtual reality. To control for players’ status of winning or losing, we programmed a virtual opponent to either under-perform, over-perform, or tie with them. We conducted a series of experiments and found that players’ engagement was higher when they were losing, compared to when they played alone. Nevertheless, players’ engagement did not change during competition with an under-performing or equally-performing opponent. By applying the information-theoretic notion of transfer entropy, we unveiled a causal relationships between relative performance and engagement, whereby players monitored the scores and adapted their behavior accordingly. However, behavioral metrics are not detached from volition and may be influenced by confounding factors. This limitation is addressed by the use of physiological metrics, which offer largely unbiased measurements of cognitive and emotional processes. In the present study, we sought to strengthen our prior findings by measuring engagement with a physiological correlate. We conducted experiments in the same experimental setting and we measured players’ galvanic skin response during competition. We discovered that players’ skin conductance was higher when they were outperformed by their opponent, indicating that they were experiencing less flow. The results inform the design of technology-mediated applications toward sustaining user engagement and participation.
Combining Non-Parametric and Parametric Models for Stable and Computationally Efficient Battery Health Estimation
Authors: Aitio Antti , Howey David 
Published: January 2021

Abstract
Equivalent circuit models for batteries are commonly used in electric vehicle battery management systems to estimate state of charge and other important latent variables. They are computationally inexpensive, but suffer from a loss of accuracy over the full range of conditions that may be experienced in real-life. One reason for this is that the model parameters, such as internal resistance, change over the lifetime of the battery due to degradation. However, estimating long term changes is challenging, because parameters also change with state of charge and other variables. To address this, we modelled the internal resistance parameter as a function of state of charge and degradation using a Gaussian process (GP). This was performed computationally efficiently using an algorithm [1] that interprets a GP to be the solution of a linear time-invariant stochastic differential equation. As a result, inference of the posterior distribution of the GP scales as 𝒪(n) and can be implemented recursively using a Kalman filter.
Autonomous Light Assessment Drone for Dark Skies Studies
Authors: Goodell Matthew N. , Truong Takara E. , Marston Stephanie R. , Smiley Brett J. , Befus Elliot R. , Bingham Alex , Allen Kent , Bourne Joseph R. , Wei Yi , Magargal Kate E. , Ganesan Vellachi , Mendoza Daniel L. , Seth Anil C. , Harwood Stacy A. , Bodson Marc , Hermans Tucker , Leang Kam K. 
Published: January 2021

Abstract
The improper use of artificial light causing skyglow is detrimental to many types of wildlife and can potentially cause irregular human sleeping patterns. Studies have been performed to analyze light pollution on a global scale. However, light pollution data on a local scale is not of ten available and the effects at local scale have rarely been studied. Herein, a new custom-designed autonomous light assessment drone (ALAD) is described for evaluating light pollution at local scale. The ALAD is designed and equipped with a sky quality meter (SQM) to measure skyglow and a low-cost illuminance sensor to measure light from artificial sources. Outdoor field tests are performed at a remote site in central Utah and the measured results are validated against data from lightpollution-map.info. The SQM measurements are in agreement with the estimates from the light pollution map, and the initial results demonstrate feasibility of the ALAD for local-scale skyglow assessment.
Sensor and Actuator Intrusion Detection for Cyber-Physical Systems via Adaptive Estimation Algorithm
Authors: Su Jiayi , Weng Yuqin , Schneider Susan C. , Yaz Edwin E. 
Published: January 2021

Abstract
In this work, a new approach to detect sensor and actuator intrusion for Cyber-Physical Systems using a bank of Kalman filters is presented. The case where the unknown type of the intrusion signal is considered first, using two Kalman filters in a bank to provide the conditional state estimates, then the unknown type of intrusion signal can be detected properly via the adaptive estimation algorithm. The case where the target (either sensor or actuator) of the intrusion signal is unknown is also considered, using four Kalman filters in a bank designed to detect if the intrusion signal is about to affect healthy sensor or actuator signal. To test these methods, a DC motor speed control system subject to attack by different types of sensor and actuator signals is simulated. Simulations show that different types of sensor and actuator intrusion signals can be detected properly without the knowledge of the nature and the type of these signals.
Maximum Correntropy Kalman Filter for Orientation Estimation With Application to LiDAR Inertial Odometry
Authors: Fakoorian Seyed , Palieri Matteo , Santamaria-Navarro Angel , Guaragnella Cataldo , Simon Dan , Agha-mohammadi Ali-akbar 
Published: January 2021

Abstract
Accurate attitude estimation using low-cost sensors is an important capability to enable many robotic applications. In this paper, we present a method based on the concept of correntropy in Kalman filtering to estimate the 3D orientation of a rigid body using a low-cost inertial measurement unit (IMU). We then leverage the proposed attitude estimation framework to develop a LiDAR-Intertial Odometry (LIO) demonstrating improved localization accuracy with respect to traditional methods. This is of particular importance when the robot undergoes high-rate motions that typically exacerbate the issues associated with low-cost sensors. The proposed orientation estimation approach is first validated using the data coming from a low-cost IMU sensor. We further demonstrate the performance of the proposed LIO solution in a simulated robotic cave exploration scenario.
Application of Fuzzy Logic for Developing Sense and Avoid Techniques for UAV Flight Operations in National Airspace
Authors: Lee Zoe , Kumar Rumit , Radmanesh Reza , Kumar Manish , Cohen Kelly 
Published: January 2021

Abstract
In this work, a Fuzzy Inference System (FIS) is proposed to develop a sense and avoid technique for conflict-free Unmanned Aerial Vehicle (UAV) flight operations in the national airspace. The proposed method is implemented alongside the flight control software guiding the UAV towards a predefined goal. The fuzzy system makes decisions for sense and avoid with respect to the state of other intruder aircraft in the airspace. The fuzzy rules are selected under consideration of the heading and position data of the intruder aircraft obtained using ADS-B sensor relative to the controlled UAV. The avoidance controller is implemented alongside a traditional PID-based flight controller to test the effectiveness of the sense-and-avoid technique. The PID controller drives the controlled UAV towards the goal and the fuzzy controller is for conflict avoidance based on an event trigger logic if the controlled UAV is in the intrusion zone of another aircraft. The integration of the dynamic model of the controlled UAV and fuzzy inference system is described. The numerical simulations are shown to evaluate the performance of the proposed method in the presence of moving as well as stationary intruder aircraft.
Fuzzy Logic Controller for Force Feedback Control of Quadcopter via Tether
Authors: Breese Bennett , Scott Drew , Barawkar Shraddha , Kumar Manish 
Published: January 2021

Abstract
Tethered drone systems can be used to perform long-endurance tasks such as area surveillance and relay stations for wireless communication. However, all the existing systems use tethers only for data and power transmission from a stationary point on the ground. This work presents a control strategy that enables a quadcopter to follow a moving tether anchor. A force feedback controller is implemented using Fuzzy Logic. Using force-based strategy provides effective compliance between the tether’s anchor and the drone. The drone can thus be controlled by mere physical movement/manipulation of tether. This enhances the safety of current tethered drone systems and simplifies the flying of drones. Fuzzy Logic provides an intuitive edge to the control of such systems and allows handling noise in force sensors. Extensive simulation results are presented in this paper showing the effectiveness of the proposed control scheme.
Design of a Parallel Elastic Hopper With a Wrapping Cam Mechanism and Template Based Virtually Tunable Damping Control
Authors: Candan Sinan Şahin , Karagöz Osman Kaan , Yazıcıoğlu Yiğit , Saranlı Uluç 
Published: January 2021

Abstract
In this study, mechanical design and control of a novel parallel elastically actuated (PEA) legged robot are presented. Motion under analysis is limited to vertical apex to apex hopping. Robot is composed of a symmetric four link mechanism as the leg, a brushless direct-drive DC motor and a wrapping cam with extension spring. Controller is based on templates (the simplest model) and anchors (more realistic model) scheme, where the template is the Spring Loaded Inverted Pendulum (SLIP) including a viscous damper which is virtually tunable. For a desired apex, required damping constant is calculated to provide necessary energy to SLIP from an approximate analytical map. Template motion is realized in the anchor model by equating its dynamics to the template dynamics through torque control to equate energy inputs and a wrapping cam to equate potential energies. During the motion, a string is wrapped around a cam by relative motion between two links of the four link mechanism. The string pulls the spring and creates a nonlinear elongation function. Desired elongation is obtained from the required template potential energy and the necessary cam profile is calculated analytically. Thus, a linear compression spring is realized with a tension spring with cam. Static force experiments are performed to show that cam works as desired. Overall simulations and details of mechanical design are presented. This novel PEA robot architecture provides an accurate and energy efficient solution with a simple mechanical design.
Including Image-Based Perception in Disturbance Observer for Warehouse Drones
Authors: Chen Zhu , Liang Xiao , Zheng Minghui 
Published: January 2021

Abstract
Grasping and releasing objects would cause oscillations to delivery drones in the warehouse. To reduce such undesired oscillations, this paper treats the to-be-delivered object as an unknown external disturbance and presents an image-based disturbance observer (DOB) to estimate and reject such disturbance. Different from the existing DOB technique that can only compensate for the disturbance after the oscillations happen, the proposed image-based one incorporates image-based disturbance prediction into the control loop to further improve the performance of the DOB. The proposed image-based DOB consists of two parts. The first one is deep-learning-based disturbance prediction. By taking an image of the to-be-delivered object, a sequential disturbance signal is predicted in advance using a connected pre-trained convolutional neural network (CNN) and a long short-term memory (LSTM) network. The second part is a conventional DOB in the feedback loop with a feedforward correction, which utilizes the deep learning prediction to generate a learning signal. Numerical studies are performed to validate the proposed image-based DOB regarding oscillation reduction for delivery drones during the grasping and releasing periods of the objects.