bluuebunny/crossref_metadata_2025_split huggingface dataset:
End-to-End Multi-Task Machine Learning of Vehicle Dynamics for Steering Angle Prediction for Autonomous Driving
Authors: Merrill Nicholas , Eskandarian Azim 
Published: November 2019

Abstract
The traditional approaches to autonomous, vision-based vehicle systems are limited by their dependency on robust algorithms, sensor fusion, detailed scene construction, and high-quality maps. End-to-end models offer a means of circumventing these limitations by directly mapping an image input to a steering angle output for lateral control. Existing end-to-end models, however, either fail to capture temporally dynamic information or rely on computationally expensive Recurrent Neural Networks (RNN), which are prone to error accumulation via feedback. This paper proposes a Multi-Task Learning (MTL) network architecture that leverages available dynamic sensor data as a target for auxiliary tasks. This method improves steering angle prediction by facilitating the extraction of temporal dependencies from sequentially stacked image inputs. Evaluations performed on the publicly available Comma.ai dataset show a 28.6% improvement in steering angle prediction over existing end-to-end methods.
Using Inertial Control to Improve Maneuverability of Propeller-Assisted Flapping Wing Aerial Vehicle
Authors: Holness Alex E. , Solheim Hannah , Bruck Hugh A. , Gupta S. K. 
Published: November 2019

Abstract
Biological creatures demonstrate tremendous feats of maneuverability and dexterity. Some of these feats are achieved by intelligent usage of mass and inertia. For example, lizards use their tail mass and inertia to change body pose during jumping to self-right in mid-air. In a similar fashion, having shown passive mass position effects during flight tests of both flapping only and propeller-assisted flapping platforms, usage of an actuated reaction mass is proposed as a means of improving the maneuverability of a propeller-assisted flapping wing aerial vehicle. A simplified model for equations of motion, utilized successfully for autonomous diving, is presented and adapted to describe the aerodynamic forces on the wings and other surfaces. A model to approximate the change in the center of mass to be used with the equations of motion is also described. A design using a linear actuator in concert with the platform battery as a reaction mass system was prototyped and flight tested. Using the prototype design, flight characteristics for improved maneuverability were demonstrated via both video footage and data gathered by an inertial measurement unit during the same flight.
Stress-Constrained Design of Functionally Graded Lattice Structures With Spline-Based Dimensionality Reduction
Authors: Zhang Jenmy Zimi , Sharpe Conner , Seepersad Carolyn Conner 
Published: November 2019

Abstract
This paper presents a computationally tractable approach for designing lattice structures for stiffness and strength. Yielding in the mesostructure is determined by a worst-case stress analysis of the homogenization simulation data. This provides a physically meaningful, generalizable, and conservative way to estimate structural failure in three-dimensional functionally graded lattice structures composed of any unit cell architectures. Computational efficiency of the design framework is ensured by developing surrogate models for the unit cell stiffness and strength as a function of density. The surrogate models are then used in the coarse-scale analysis and synthesis. The proposed methodology further uses a compact representation of the material distribution via B-splines, which reduces the size of the design parameter space while ensuring a smooth density variation that is desirable for manufacturing. The proposed method is demonstrated in compliance minimization studies using two types of unit cells with distinct mechanical properties. The effects of B-spline mesh refinement and the presence of a stress constraint on the optimization results are also investigated.
An Event Based Machine Learning Framework for Predictive Maintenance in Industry 4.0
Authors: Calabrese Matteo , Cimmino Martin , Manfrin Martina , Fiume Francesca , Kapetis Dimos , Mengoni Maura , Ceccacci Silvia , Frontoni Emanuele , Paolanti Marina , Carrotta Alberto , Toscano Giuseppe 
Published: November 2019

Abstract
Predictive Maintenance concerns the smart monitoring of machine to avoid possible future failures, since because it is better to intervene before the damage occurs, saving time and money. In this paper, a Predictive Maintenance methodology based on Machine learning approach is presented and it is applied to a real cutting machine, a woodworking machinery in a real industrial group, producing accurate estimations. This kind of strategy is important to deal with maintenance problems given the ever increasing need to reduce downtime and associated costs. The Predictive Maintenance methodology implemented allows dynamical decision rules that have to be considered for maintenance prediction using a combined approach on Azure Machine Learning Studio. The Three models (RF, GBM and XGBM) allowed the accurately predict machine down ever gripped bearing thanks to the pre-processing phases.
Vehicle-Terrain Interaction Simulation With Parallelized Multiscale Moving Soil Patch Model
Authors: Yamashita Hiroki , Chen Guanchu , Ruan Yeefeng , Jayakumar Paramsothy , Sugiyama Hiroyuki 
Published: November 2019

Abstract
Although many physics-based off-road mobility simulation models are proposed and utilized for vehicle performance evaluation as well as for understanding of tire-soil interaction problems, full vehicle simulation on deformable terrain requires addressing the computational complexity associated with the large dimensional physics-based terrain dynamics models for practical use. This paper, therefore, presents a hierarchical multiscale tire-soil interaction model that is fully integrated into parallelized off-road mobility simulation framework. In particular, a co-simulation procedure is developed for full vehicle simulation with multiscale terrain dynamics models by exploiting the moving soil patch technique. To this end, a detailed off-road vehicle simulation model is divided into five subsystems: a multibody vehicle subsystem and four tire-soil subsystems composed of nonlinear FE tires and multiscale moving soil patches. The tire-soil subsystems are interfaced with the vehicle subsystem by MPI through force-displacement coupling. It is demonstrated that the proposed framework allows for alleviating computational intensity of a full vehicle simulation that involves complex hierarchical multiscale terrain dynamics models by effectively distributing computational loads with co-simulation techniques.
Computing Robust Inverse Kinematics Under Uncertainty
Authors: Sinha Anirban , Chakraborty Nilanjan 
Published: November 2019

Abstract
Robotic tasks, like reaching a pre-grasp configuration, are specified in the end effector space or task space, whereas, robot motion is controlled in joint space. Because of inherent actuation errors in joint space, robots cannot achieve desired configurations in task space exactly. Furthermore, different inverse kinematics (IK) solutions map joint space error set to task space differently. Thus for a given task with a prescribed error tolerance, all IK solutions will not be guaranteed to successfully execute the task. Any IK solution that is guaranteed to execute a task (possibly with high probability) irrespective of the realization of the joint space error is called a robust IK solution. In this paper we formulate and solve the robust inverse kinematics problem for redundant manipulators with actuation uncertainties (errors). We also present simulation and experimental results on a 7-DoF redundant manipulator for two applications, namely, a pre-grasp positioning and a pre-insertion positioning scenario. Our results show that the robust IK solutions result in higher success rates and also allows the robot to self-evaluate how successful it might be in any application scenario.
Towards an Information Archetypes Framework: Exploring the Types of Information Used in Open Source Design Engagements
Authors: Yi Sue , Lumbard Kevin , Damen Nicole B. , Germonprez Matt , Toh Christine A. 
Published: November 2019

Abstract
Across disciplines such as software engineering to architectural design, it is well acknowledged that the different types of information employed during the design process impacts the potential of the final design. However, a lack of understanding exists about how designers utilize and navigate the abundance of complex information types, making it difficult to develop design methodologies that support the development of competitive products and services. As part of an ongoing effort to develop an Information Archetypes Framework, this study focuses on identifying the emergence of information dimensions and archetypes during decision making. This was accomplished through a detailed analysis of interviews with designers who engage in open source work as part of their employment. The findings of this study provide empirical evidence of the types of information used during the design process, validates existing information archetypes, and identifies new archetypes that emerge from co-occurring information dimensions.
Improved Surgical Robot Design Using a Novel Compliant Rolling-Contact Joint
Authors: Nelson Carl A. , Dempsey Cole A. , Brush Ethan R. , Laribi M. Amine 
Published: November 2019

Abstract
This paper presents an improved design concept for a surgical robot that contributes to improved human-robot interaction and precise positioning of surgical tools. Based on a spherical wrist design, the robot incorporates new human-safe features limiting its ability to apply excessive force and uses a novel adaptation of the compliant rolling-element (CORE) joint suitable for conical rolling surfaces. The proposed safety features aim to provide novel functionality by mechanically disengaging the drive in overload conditions. This approach avoids the necessity of force sensing and control to detect and compensate for unintended device collisions. Further, proof of concept of a novel compliant rolling-element joint is presented as a low-backlash alternative to bevel gear pairs for heightened precision in angular positioning.
Constructing Scissor-Like Structures and Parallelogram Linkages With 4-Crease Single-Vertex Flat-Foldable Rigid Origami and Their Thick-Panel Versions
Authors: Xing David , You Zhong 
Published: November 2019

Abstract
Scissor-like structures are commonly composed of two straight rigid supports in a crisscross pattern connected by a pivot at its point of intersection [1]. Opposite angles formed by the supports are equal regardless of the structure’s folded state. Parallelogram linkages have a similar property. Rigid origami can be used to create these structures by combining two identical copies of a 4-crease single-vertex flat-foldable rigid origami, a single 4C, to form a flat-foldable composite structure, a double 4C. In this paper, we prove mathematically that regardless of the folded state of a single-4C, its even dihedral angles are equal, and odd dihedral angles are equal. As a result, the double 4C consists of 2 scissor-like structures. A past method to prove these dihedral angle equalities requires a more complex approach involving rotation matrices using Denavit and Hartenberg parameters [2,3]. This paper will provide a more intuitive method that proves the same equalities. We will also show that a similar construction of the double 4C using thick-panel versions of the single 4C satisfies the same dihedral angle equalities necessary for the formation of parallelogram linkages. The construction of the double 4C can help design self-folding mechanisms and useful metamaterials.
A Proposal for a Decision Support Framework to Solve Design Problems in the Automotive Industry
Authors: Sissoko Timothé M. , Jankovic Marija , Paredis Christiaan J. J. , Landel Eric 
Published: November 2019

Abstract
Decision-makers often rely on heuristics and experience to make complex decisions in the industrial context. Often, integrating implicit or expert knowledge as well as uncertainties can lead to decisions that are not necessarily the best ones. Moreover, in engineering design, the decision-making approaches focus on the product itself and do not investigate the necessary effort that is needed to gather additional data in order to devise more precise decision-making models. In our research, we propose to integrate this estimation of additional effort needed for data gathering and decision-making refinement in order to support design teams. This research has been conducted in collaboration with a major car manufacturing company, and in particular in the development process through Modeling and Simulation. The objective is to propose a decision-making model that integrates data-gathering estimation, hence integrating also the estimation of postponing one decision. A decision problem model based upon expected utility combined with the value of information theory is proposed to address this issue. The model has been developed and tested on 4 case studies. We define a decision support framework by integrating the model into a tool and by proposing roles in the decision-making process. We finally present its application on a concrete example.
Dynamic Analysis of a Rotating Planar Timoshenko Beam Using an Accurate Global Spatial Discretization Method
Authors: Fan W. , Zhu W. D. , Zhu H. 
Published: November 2019

Abstract
A new formulation is developed for dynamic analysis of a rotating planar Timoshenko beam. The configuration of Timoshenko beam is described using its slope angle and axial and shear strains; hence, the shear locking problem can be naturally avoided. While six boundary conditions are needed for choices of trial functions of three dependent variables, there are only four boundary conditions that can be determined and two boundary conditions are undetermined. An accurate global spatial discretization method is used, where dependent variables are divided into internal and boundary-induced terms. Internal terms only need to satisfy homogeneous boundary conditions, which can be easily chosen as trigonometric functions. Boundary-induced terms are interpolated using dependent variables at boundaries that are taken as generalized coordinates. When the hub rotates at a constant angular velocity, nonlinear governing equations can be linearized for vibration analysis. Frequency veering and mode shift phenomena occur. Nonlinear dynamic responses of the system are then calculated and compared with those from the commercial software ADAMS, and they are in good agreement. Axial and shear strains of the beam and their spatial derivatives are also calculated. Since trial functions in the assumed modes method cannot satisfy undetermined boundary conditions, inaccurate results of strains and their spatial derivatives are obtained using the assumed modes method. Hence, use of the accurate global spatial discretization method in the current formulation is essential.
A Feasibility Study on the Benefits of Feedback Aerator Control in Precision Aquaculture Applications for the Developing World
Authors: Cruz Francis Cedric , Mahmudov Kamran , Marouchos Andreas , Bilton Amy 
Published: November 2019

Abstract
Aquaculture is a growing source of food and income for many in the developing world. In developing countries, where more than 18 million people engage in aquaculture, yields have been low due to lacking infrastructure. Aeration has been shown to improve dissolved oxygen (DO) and increase yields, but its use has been low in many developing world environments due to high operating costs. Even when used, they are operated in an ad-hoc manner, resulting in higher than required costs. A potentially more effective implementation is the use of feedback control to maintain adequate DO and increase energy savings. To demonstrate the potential, a feasibility study was conducted comparing the energy consumption of a diffused aeration system, with and without the use of a feedback control system. The effect of the diffused aeration system was simulated for a 100 m3 pond in Bangladesh for extensive and intensive fish farming. The interaction between the aerators and the pond was simulated on ANSYS FLUENT and was used with a DO model to predict the oxygen dynamics of the pond. Results indicated that the addition of a feedback control system could result in 78.66%, and 52.48% in energy cost savings compared to continuous operation for extensive and intensive fish farming respectively. Further work in smart instrumentation has the potential to decrease the energy requirements of aeration technologies and improve production for farmers in the developing world.
Kinematic Optimization of a 2-DOF U, 2PSS Parallel Wrist Device
Authors: Bajaj Neil M. , Dollar Aaron M. 
Published: November 2019

Abstract
The wrist plays the crucial role of orienting a hand or end effector without significant translational motion, a critical requirement of successful manipulation. In this paper, we present the kinematic design optimization a two degree of freedom universal, two-prismatic-spherical-spherical (U, 2-PSS) parallel wrist mechanism. By varying the geometric parameters of the mechanism, we examine configurations that maximize the Global Conditioning Index, a metric describing the quality of the motion and torque, over the desired workspace, which mimics a healthy human wrist range of motion in circumduction (flexion/extension and abduction/adduction). We further investigate the effects of sizing constraints on the resulting optimized design which satisfies the imposed sizing constraints.
Evaluation of the ISHM Method Applied for Composite Rotors
Authors: Tsuruta Karina M. , Rocha Lucas A. A. , Cavalini Aldemir Ap. , Finzi Neto Roberto M. , Steffen Valder 
Published: November 2019

Abstract
The use of SHM (structural health monitoring) techniques has shown promising results for fault detection in rotating machines, making possible to identify various malfunctions. SHM methods provide maintainability and safe operation for these systems. The objective of the present work is to evaluate the SHM method based on the electromechanical impedance (ISHM) to detect faults in a composite rotor shaft. Composite materials present complex damage mechanisms due to their anisotropy and heterogeneity. Moreover, the process of damage detection in these materials is more challenging than in metallic structures. The ISHM approach uses piezoelectric (PZT – Lead Zirconate Titanate) patches as sensors and actuators coupled to the monitored structure. Variations in their electrical impedance are associated with changes in the mechanical integrity of the system. The electrical impedance of the PZT sensor is directly related to the mechanical impedance of the structure, which changes according to variations in the mass, stiffness, and damping properties of the structure. Damage metrics are used to quantify variations in the electrical impedance (impedance signatures) of the PZT patches. Despite the ISHM approach be able to detect incipient faults, it presents some disadvantages. For instance, the impedance signatures are susceptible to temperature variation. In the present contribution, to detect damages in the considered composite rotor shaft, the ISHM technique was implemented based on a data normalization methodology. Thus, an optimization procedure based on hybrid optimization was used to avoid false diagnostics.
Experimental and Numerical Investigation of Residual Stress Stiffening Influence on Dynamic Response of Welded Structures
Authors: MajidiRad AmirHossein , Yihun Yimesker S. 
Published: November 2019

Abstract
This paper presents the study of welding residual stress-stiffening effect on the dynamic responses and vibrational parameters of welded aluminum parts through an experimental modal analysis and Center Hole Drilling (CHD) residual stress measurement methods. Having a great corrosion resistance, AA5056 was utilized in this research that has been used in aircraft and ship structures; making the welding assesment of crucial. Natural frequencies and damping factors of several specimens are compared before and after the welding along with verification of experimental modal analysis integrity using Euler-Bernoulli relations. Finite element modeling of welding, cutting and modal/stress analysis of samples are also done to compare the experimental results. The results obtained from the precise modal analysis of all samples show that welding made the structure harder leading to 2% increase in natural frequencies and changing damping factors of different mode shapes. Cutting also reduced the level of residual stresses up to 34%. A good agreement is shown between the modal analysis and the experimental results. The technique used in the experiment and finite element simulation along with modeling assumptions are beneficial to other applications where model updating is required or a prediction of residual stress stiffening influence on modal responses is important.
Approximate Force History Estimation in Multi-Point Non-Smooth Collisions
Authors: Chatterjee Abhishek , Bowling Alan , Ghaednia Hamid , Brake Matthew 
Published: November 2019

Abstract
Collisions between hard objects cause abrupt changes in the velocities of the system, which are characterized by very large contact forces over very small time-durations. A common approach in the analysis of such collisions is to describe the system velocities using an impulse-momentum based relationship. The time-duration of impact and the deformations at the contact points are usually assumed to be negligible in such impact models, and the system velocities are evolved in terms of the impulses on the system. This type of impact models are usually relevant for hard (rigid) impacts, where deformations at the contact points can be considered negligible. However, these models cannot determine the forces during the impact process. The main objective of this work is to reformulate the impulse-momentum based model to determine the forces during an impact event, by relaxing the rigidity assumption to allow small deformations at the contact points.
Study of Industry 4.0 and its Impact on Lean Transformation in Aerospace Manufacturing
Authors: James Sagil , Cervantes Alejandro 
Published: November 2019

Abstract
Lean manufacturing practices focus on minimizing all forms of waste from the production system. The applicability of lean manufacturing concepts and principles has often been questioned in sectors including aerospace manufacturing primarily due to their high variety - low volume environments. The key challenges include the difficulty in changing the factory layout, lack of plant-specific manufacturing strategies, lack of benchmarking between manufacturing plants and non-existence of learning through experimentation culture. Consequently, the aerospace manufacturing industries have struggled to implement lean principles over the years successfully. Industry 4.0 is a new paradigm that is significantly influencing several manufacturing industries across the globe. Applying the concepts of Industry 4.0 along with the conventional lean transformation technology could potentially address these challenges. The focus of this research is to study the possibilities of integrating Industry 4.0 tools with existing lean manufacturing philosophies within the aerospace manufacturing sector in order to improve various aspects of manufacturing processes in a cyber-physical environment. A case study is performed considering a quality inspection department in a typical aerospace industry. The case study is simulated using discrete event simulation tool — Arena. The study found that a hybrid approach involving the holistic merger of the lean principles along with the Industry 4.0 tools known as Lean Industry 4.0 is the best way forward for the aerospace manufacturing sector. The outcomes of this research provide an understanding of the role of industry 4.0 paradigm and their implementation in several other high-technology and high-risk manufacturing sectors including life sciences, space, and defense industries.