bluuebunny/crossref_metadata_2025 huggingface dataset:
Frictional Head Loss of Various Bimodal Settling Slurry Flows in Pipe
Authors: Matoušek Václav , Visintainer Robert , Furlan John , Sellgren Anders
Published: November 2019

Pipe flows of bimodal settling slurries exhibit frictional head losses quite different from those determined simply as a sum of loss contributions by the individual fractions. Mechanisms governing flow friction and resulting from an interaction of grains of different fractions in transported slurry are not well understood. This makes a prediction of the frictional head loss in flows of bimodal slurries with Newtonian carrier uncertain. An extensive experimental campaign was conducted in GIW Hydraulic Laboratory in 2016 with slurries of four narrow graded fractions of the virtually same grain densities and very different grain sizes (carrier-liquid fraction, pseudo-homogeneous-, heterogeneous-, and stratified fractions). Besides testing of the individual fractions, different combinations of the fraction mixtures (bimodal, three- and four-component) were tested as well.

In our previous work published in 2018, we employed experimental results for bimodal slurry composed of coarse granite rock (the stratified fraction) and fine sand (the pseudo-homogeneous fraction) to analyze the observed considerable reduction of the frictional head loss caused by an addition of the fine sand to the granite rock slurry.

In this work, we extend our analysis to the other bimodal slurries composed of permutations of the four fractions (in total 3 additional bimodal slurries) with a major objective to identify possible mechanisms leading to a modification of the frictional head loss due to an addition of a finer fraction to a coarser mono-disperse slurry, and to quantify this effect for the purposes of a predictive four-component model (4CM). The investigation shows that the frictional loss of bimodal slurry is always smaller than the theoretical loss obtained as the sum of losses of the fractions, although the massive reduction observed in the slurry composed of the stratified rock and fine sand is not observed in any other bimodal slurry. The investigation also suggests that the friction effect obtained by the finer fraction addition is due to different mechanisms for different bimodal slurries although all mechanisms are associated with altering mechanical friction due to granular contacts.

It is shown that the observed effects can be well reproduced by the friction loss model 4CM, calibrated by the experimental data set from the 203-mm pipe and validated by the data set from the 103-mm pipe.
A Robust Aerodynamic Optimization Design for Airfoil Based on Interval Uncertainty Analysis Method
Authors: Song Xin , Zheng Guannan , Yang Guowei
Published: November 2019

Uncertainties will make aircraft deviate from the designed condition, resulting in the decrease in aerodynamic performance and even destruction. This paper presents a fast nonlinear interval analysis method considering geometric uncertainties. DFFD method is used to parameterize the airfoil shape, and the Kriging model for aerodynamic force and uncertainty variables is optimized by PSO algorithm to find the upper and lower bounds of the objective interval. The effects of geometric uncertainties on NACA0012 airfoil are analyzed using the above method. And then, a robust optimization design method is established based on the interval analysis method. FFD method is used to produce the deterministic design variables and the order relation of interval number is employed to transform the uncertain optimization to deterministic multi-objective optimization which is solved by MOPSO based on Pareto entropy. The robust optimization design is implemented for the symmetrical airfoil with the drag objective under geometric uncertainties and thickness constraint, and the results are compared with the deterministic optimization to validate the effectiveness of the developed method.
Implicit Large-Eddy Simulation of Transition and Turbulence Decay
Authors: Grinstein Fernando F.
Published: November 2019

Accurate predictions with quantifiable uncertainties are essential to many practical turbulent flow applications exhibiting extreme geometrical complexity and broad ranges of length and time scales. Under-resolved computer simulations are typically unavoidable in such applications, and implicit large-eddy simulation (ILES) often becomes the effective strategy. We focus on ILES initialized with well-characterized 2563 homogeneous isotropic turbulence datasets generated with direct numerical simulation (DNS). ILES is based on the LANL xRAGE code, and solutions are examined as function of resolution for 643, 1283, 2563, and 5123 grids. The ILES performance of new directionally-unsplit high-order numerical hydrodynamics algorithms in xRAGE is examined. Compared to the initial 2563 DNS, we find longer inertial subranges and higher turbulence Re for directional-split 2563 & 5123 xRAGE — attributed to having linked DNS (Navier-Stokes based) solutions to nominally inviscid (higher Re) Euler based ILES solutions. Alternatively — for fixed resolution, we find that significantly higher simulated turbulence Re can be achieved with unsplit (vs. split) discretizations.
Formation of Clot Analogs Between Co-Flow Fluid Streams in a Microchannel Device
Authors: Saw Sue-Mae , Ramasubramanian Anand K. , Simon Melinda , Lee Sang-Joon John
Published: November 2019

Hemodynamics plays an important role in the formation of blood clots, for which changes in hydrodynamic stresses and transport phenomena can initiate or inhibit the clotting process. Fibrin, which is converted from fibrinogen in blood plasma, plays a dominant role in structural mechanics of a clot. Clot analogs are conventionally fabricated in a static in vitro environment whereas clot formation in vivo occurs in the presence of dynamic blood flow. In this paper we demonstrate an ability to produce clot analogs at the boundary between active co-flow fluid streams. The time evolution of clot formation in microchannel flow was investigated using fluorescence imaging of fibrin clots at one-minute intervals. Time-tracking of skewness and kurtosis of fluorescence intensity data was conducted to monitor shape and density distribution changes in the clot. Soft lithography and casting techniques were used to fabricate a polydimethylsiloxane (PDMS) microfluidic device which consisted of a Y-shaped microchannel 300 μm wide × 12 μm deep × 10 mm long with two inlets and a single outlet. The first inlet introduced fresh frozen plasma (FFP), which contains fibrinogen and plasma proteins. The second inlet introduced thrombin, which initiated the conversion of fibrinogen to fibrin. Clot analogs were formed at the interface between these two parallel streams. Flow was driven by withdrawal of a syringe pump at flow rates of 50 nL/min and 100 nL/min. Clots that are formed in such an engineered device provide opportunities to recapitulate the flow rates and concentrations of reagents, to mimic in vivo scenarios in which clot density and composition gradients depend on flow conditions.
Modelling and Validation of Tooth Tip Leakages in Gerotor Pumps
Authors: Rituraj Fnu , Vacca Andrea
Published: November 2019

Gerotor pumps are commonly used as charge pumps in hydrostatic transmission systems as well as in fuel injection and automotive lubrication systems. For high pressure applications, Gerotors suffer from internal leakages which are one of the main sources of volumetric loss. The curvature of typical gear profiles for Gerotors prevents the usage of simple analytical relations to describe this leakage flow.

In this paper, a non-dimensional functional relationship is developed between geometric and flow parameters to model this leakage flow. A set of CFD simulations are conducted on the tooth tip geometry to establish this relationship. Then, an experimental setup is designed to reproduce the flow conditions at tooth tip of Gerotor. Experiments are conducted for a range of geometric and flow parameters and results from experiments are used to validate the proposed non-dimensional model.

The tooth tip leakage model developed and validated in this work is valuable for pump designers in determining the impact of gear geometry and clearances on volumetric performance of the pump. Moreover, the model can be readily used in any lumped parameter based simulation tool permitting a fast and accurate prediction of the tooth tip leakage flow and hence the volumetric efficiency of the unit.
A Novel Energy-Conversion Device for Wind and Hydrokinetic Applications
Authors: Houchens Brent C. , Marian David V. , Pol Suhas , Westergaard Carsten H.
Published: November 2019

In its simplest implementation, patent-protected AeroMINE consists of two opposing foils, where a low-pressure zone is generated between them. The low pressure draws fluid through orifices in the foil surfaces from plenums inside the foils. The inner plenums are connected to ambient pressure. If an internal turbine-generator is placed in the path of the flow to the plenums, energy can be extracted. The fluid transports the energy through the plenums, and the turbine-generator can be located at ground level, inside a controlled environment for easy access and to avoid inclement weather conditions or harsh environments. This contained internal turbine-generator has the only moving parts in the system, isolated from people, birds and other wildlife. AeroMINEs could be used in distributed-wind energy settings, where the stationary foil pairs are located on warehouse rooftops, for example. Flow created by several such foil pairs could be combined to drive a common turbine-generator.
Multi-Phase Gearbox Modelling Using GPU-Accelerated Smoothed Particle Hydrodynamics Method
Authors: Menon Muraleekrishnan , Szewc Kamil , Maurya Vishal
Published: November 2019

Developments in automotive design such as electrification of engines and a growing need to improve driveline efficiency requires adaption of old techniques. The ability to make fast and accurate Computational Fluid Dynamics (CFD) assessment is of high importance to the development of novel powertrains. Consequently, innovative numerical techniques and continuous improvements to existing CFD codes is relevant to ensure reliability. This work extends the capabilities of a Smoothed Particle Hydrodynamics (SPH) code to include multiphase modeling, studied using a gearbox model.

A vast majority of CFD codes use grid-based approaches following the Eulerian spatial discretization, which is quite established in engineering applications. Lagrangian based approaches where the moving fluid particles are discretized over time and space present a promising alternative. One of the most common methods of this kind is the Smoothed Particle Hydrodynamics (SPH) method, a fully Lagrangian, particle-based approach for fluid-flow simulations. The main advantage is the absence of numerical grid for computations, which eliminates complexities of interface handling. Nowadays, the SPH approach is more commonly used for hydro-engineering applications involving free-surface flows. New techniques to perform numerical simulations on Graphics Processing Units (GPU) virtually eliminates some of the disadvantages of the method. In this work, we present our multi-GPU solution designed for both GPU-equipped desktops and multi-GPU supercomputers.

Fluid dynamic simulations on a single gearbox model is used to validate the multiphase model, by comparing the results with earlier simulations that use a single-phase model omitting air-lubricant interface in the gearbox. The base case in the study is a single bevel gear placed inside a cuboid case with a lubricant depth equivalent to 25% gear diameter. Simulations are performed at various rotational speeds, and corresponding lubricant distribution and churning losses are obtained. The current study targets a comparison of the single-phase and multiphase models in approximating the lubricant distribution and churning loss values at nominal rotational speeds. This serves to standardize the numerical procedure, which will help in improving the accuracy of churning loss calculations through validations against experimental results in the future.
Unsteady Flow in the Vaned Diffuser of a Low Specific Speed Centrifugal Pump With an Unshrouded Impeller
Authors: Ichinose Asuma , Takeda Tomoki , Miyagawa Kazuyoshi , Ogawa Yohei , Negishi Hideyo , Niiyama Kazuki
Published: November 2019

The unsteady internal flow in a low specific speed centrifugal pump was experimentally and numerically investigated. Unshrouded impellers enable high head designs but on the other hand, they exhibit complicated internal flow and an efficiency decline compared to shrouded impellers. Furthermore, the complicated impeller outlet flow induces unsteady internal flow in the vaned diffuser. Therefore, a detailed investigation of the internal flow is required in order to increase the efficiency of these low specific speed centrifugal pumps. The aims of this paper are to clarify the loss mechanisms in the impeller and to investigate the effect of impeller outlet flow to the diffuser internal flow at the design point. The detailed pump internal flow is investigated using unsteady computation, which enables the computation of the 3D flow pattern. The reversed flow and the secondary flow are induced by the tip leakage flow, and this creates a high loss region in the blade-to-blade region. On the other hand, the mixing effect is remarkable at the impeller outlet, and this affects the creation of the wake. This flow behavior makes the internal flow of the diffuser unsteady and the diffuser performance fluctuates due to the impeller wake at the design point.
Directional Surface Roughness Influence on Turbulent Flow Structure
Authors: Harun Zambri , Abbas Ashraf A. , Nugroho Bagus
Published: November 2019

A series of experiments have been conducted to investigate turbulent flow structures when it is exposed to a highly directional riblet-type surfaces roughness (converging-diverging/herringbone pattern) at a relatively low Reynolds number (Reτ). These experiments show that even at a low Reτ, the surface pattern is able to modify the turbulent boundary layer. Over the diverging region, we observe a decrease in drag penalty, while over the converging region there is an increase of drag penalty, which is indicated by the shift in the mean velocity profiles. The surface roughness also influences the turbulence production, indicated by the elevated turbulence intensities profiles for both the converging and diverging regions. The result seems to deviate from early investigations that show an increase in turbulence intensities above the converging region and a lowered turbulence intensities above the diverging region. The discrepancy may be caused by the lower Reτ Ret in the current report. Other important statistics such as skewness and flatness are also reported.
Effects of Shaft-Bore Water Flow Cooling of High-Speed Spindle Supported With Water-Lubricated Hydrostatic Bearings on Thermal Stability
Authors: Nakao Yohichi , Yaguchi Tsubasa , Fedorynenko Dmytro , Kusuyama Junpei
Published: November 2019

In this paper, the thermal stability of a spindle with water-lubricated hydrostatic bearings was investigated. In order to improve the thermal stability of the spindle, a center bore water cooling structure was designed in the rotor. Influences of the center bore water cooling on not only thermal stability but also temperature control performance of the spindle was studied via simulations and experiments. Power losses due to water flows in the spindle were considered. Based on a derived lumped parameter model, the temperature changes of the water flow and spindle were predicted. As used in many machine tool components, it was verified that the center bore cooling are effective to improve the thermal stability of the spindle. An influence of structural change of the rotor due to the center bore on the heat capacity and time constant was investigated. As a result, the time constant in terms of the thermal characteristics is decreased due to the center bore structure. Because of this feature, the temperature control performance can be improved.
Capturing S-Shape of Pump-Turbines by CFD Simulations Using an Anisotropic Turbulence Model
Authors: Casartelli Ernesto , Mangani Luca , Del Rio Armando , Schmid Angelika
Published: November 2019

Pump-turbines cope very well with modern electricity-market demand, having high operational flexibility and storage capabilities. Nevertheless, dynamic operation of these machines can lead to very challenging transient conditions, depending on the shape of the characteristic. Mechanical integrity can be correspondingly affected. Therefore assessment of the characteristic during the design phase, i.e. before model testing, is of crucial importance.

In the past years different attempts to accurately compute the characteristic under steady (i.e. fix point) and transient conditions have been undertaken using RANS CFD. While the SST turbulence model has become the reference for machine design, it often fails for conditions close to or around instabilities. Its strength to accurately predict separation close to sound conditions (i.e. mild part- and over-load) is no more helpful. Under unstable conditions, which are characterized by continuous unsteady vortex formation, turbulence isotropy as assumed by linear two equation models is no more the right choice.

Accordingly a turbulence model able to capture anisotropy, EARSM (Explicit Algebraic Reynolds Stress Model), has been implemented in an in-house code and used for the computation of the characteristic of various machines, stable and unstable, in order to assess the model performance.

In this paper computations of three different machines in turbine mode are presented. Results using steady boundary conditions (BC) in the unstable region as well as transient BC like load-rejection and runaway are computed with EARSM, showing its superiority compared to linear two equation models.
Towards Scalable Gaussian Process Modeling
Authors: Pandita Piyush , Kristensen Jesper , Wang Liping
Published: November 2019

Numerous engineering problems of interest to the industry are often characterized by expensive black-box objective function evaluations. These objective functions could be physical experiments or computer simulations. Obtaining a comprehensive idea of the problem and/or performing subsequent optimizations generally requires hundreds of thousands of evaluations of the objective function which is most often a practically unachievable task. Gaussian Process (GP) surrogate modeling replaces the expensive function with a cheap-to-evaluate data-driven probabilistic model. While the GP does not assume a functional form of the problem, it is defined by a set of parameters, called hyper-parameters, that need to be learned from the data. The hyperparameters define the characteristics of the objective function, such as smoothness, magnitude, periodicity, etc. Accurately estimating these hyperparameters is a key ingredient in developing a reliable and generalizable surrogate model. Markov chain Monte Carlo (MCMC) is a ubiquitously used Bayesian method to estimate these hyperparameters. At GEs Global Research Center, a customized industry-strength Bayesian hybrid modeling framework utilizing the GP, called GEBHM, has been employed and validated over many years. GEBHM is very effective on problems of small and medium size, typically less than 1000 training points. However, the GP does not scale well in time with a growing dataset and problem dimensionality which can be a major impediment in such problems. For some challenging industry applications, the predictive capability of the GP is required but each second during the training of the GP costs thousands of dollars. In this work, we apply a scalable MCMC-based methodology enabling the modeling of large-scale industry problems. Towards this, we extend and implement in GEBHM an Adaptive Sequential Monte Carlo (ASMC) methodology for training the GP. This implementation saves computational time (especially for large-scale problems) while not sacrificing predictability over the current MCMC implementation. We demonstrate the effectiveness and accuracy of GEBHM with ASMC on four mathematical problems and on two challenging industry applications of varying complexity.
Deep Learning Automatic Inspections of Mushroom Substrate Packaging for PP-Bag Cultivations
Authors: Jou Rong-Yuan , Li Tseng-Wei
Published: November 2019

The mushroom cultivation is an important smart agriculture in Taiwan. This study uses the deep learning object detection method to inspect the cap flaws or positional imperfection in the automatic production of the mushroom PP-bag packaging. This study uses the UR robotic arm and integrated 3D vision module, and uses the extra positioning axis to achieve the purpose of multi-positioning inspections by robot arm. Projecting the structured LED light sources to the object to be inspected has the advantages of a larger identification ranges and complex objects detection. A duallens CMOS industrial camera is used to capture images, and a 3D point cloud image of a basket of PP-bag packages is created by software calculation, which can obtain detailed information on the appearance of the whole basket of PP-bag packages. Deep learning is performed by the training set with labelling, and the image recognition such as the cap flaws in the PP-bag package or positional shift is performed after the training is completed. In this paper, the image data is divided into four sets of datasets, and the same training parameters are used for individual training. With images of dataset1 and the ambient illumination level of 200 lm to 800 lm, the matching score is up to 0.989. The clamping force and the opening degree are adjusted by the variable jaws. The clamping force of the jaws is maintained at 20 N to prevent the clamping force from damaging the dimensions of the PP-bag package and existing holes inside it, making the product unusable. Using the variable jaws and repeating 30 times of clamping experiments, the hole diameter inside the PP-bag package can still be maintained within around 25 mm, which can meet the needs of the mushroom PP-bag packaging.
Lucid Analysis of Periodically Forced Nonlinear Systems via Normal Forms
Authors: Waswa Peter M. B. , Redkar Sangram
Published: November 2019

This paper presents a straightforward methodology to analyze periodically forced nonlinear systems with constant and periodic coefficients via normal forms. We demonstrate how the intuitive system state augmentation facilitates construction of normal forms by avoiding ad-hoc addition of equation variables, book-keeping parameters and detuning parameters. Moreover, this technique directly connects the periodic forcing terms and periodic coefficients of the nonlinearity with the augmented states — making it applicable to all periodically forced nonlinear systems. Accuracy of this approach is successfully verified via fulfilled compliance between analytical and numerical results of forced Duffing’s equation and Mathieu-Duffing equation.
Genetically Modified Soybean Detection Using a Biosensor Electrode With Self-Assembled Gold Nanoparticles on a Micro Hemisphere Array
Authors: Lin Ying-Ting , Kuznetsova Iren , Wang Gou-Jen
Published: November 2019

Gene transfer technology changes some of the characteristics of crops. However, genetically modified foods have been reported to have an impact on human health. We proposed a cost effective and highly sensitive biosensor electrode with self-assembled monolayer of gold nanoparticle on a micro hemisphere array to detect genetically modified soybean. An ordered array of micro hemispherical features was formed on a 6-inch reclaimed silicon wafer using photolithography. Then, a thin gold layer was sputtered onto the hemispheres. The wafer was then immersed into a 5 mM ethanol solution of 1,6-hexanedithiol (1,6-HDT) to enable the attachment of one thio-end of 1,6-HDT to the thin gold layer. Next, a colloidal gold (15 nm) solution was dripped onto the wafer and baked on a hot plate in such a way that the monolayer of gold nanoparticles could self-assemble on the 1,6-HDT surface. Finally, we used electrochemical impedance spectroscopy (EIS) analysis to detect genetically modified soybean. Experimental results demonstrate that our biosensor can successfully distinguish the genetically modified soybeans from the normal ones.
Simulating Compliant Crease Origami With a Bar and Hinge Model
Authors: Zhu Yi , Filipov Evgueni T.
Published: November 2019

Small-scale origami inspired assemblages are usually made with soft compliant plates to serve as creases because it is difficult to fabricate real hinges at those scales. In most conventional origami modeling techniques, these soft and compliant creases are usually neglected and simplified as concentrated rotational springs. Such simplification does not capture the three dimensional geometry correctly and also neglects torsional and extensional deformations of the compliant creases. These deformations could be significant for determining advanced mechanical behaviors of the origami such as bistablity and multistablity. In this paper an improved formulation of a simple bar and hinge model is proposed to capture the geometry and flexibility of compliant creases. Equations for assigning bar areas and spring stiffness are derived based on the theoretical plane stress plate models and the pseudo-rigid model. These equations are next verified against finite element simulations for both infinitesimal stiffness and large deformation stiffness. It is found that the proposed model can predict stiffness characteristics of compliant crease origami relatively well. Furthermore, two examples are used to demonstrate the efficiency and capability of the proposed model.
Analysis of Static and Dynamic Behavior of Thick-Walled PALEO Elements
Authors: Klett Yves , Muhs Fabian , Middendorf Peter
Published: November 2019

Plastically annealed lamina emergent mechanisms have been recently introduced as origami-based structures that can be designed with a tendency to return into arbitrary folding states without additional actuators or external stimuli. The inherent elasticity of the surrogate hinges can realize a large range of elastic deformation. This paper describes the implementation of the PALEO principle for structures made from 2mm thick polycarbonate. The flat sheet is machined to generate the hinge elements and is afterwards folded and thermally annealed in a non-flat state. A FE analysis of the initial folding and behavior after annealing is carried out in parallel, with the goal to determine strains and stresses for different hinge configurations. Finally, a dynamic test is carried out on PALEO unit cells to determine the fatigue behavior of the manufactured samples.
Improvement of a Forward Dynamic Predictive Human Gait Model
Authors: Thayer Jessica B. , Voglewede Philip A.
Published: November 2019

Lack of understanding of human gait is detrimental to the development of gait related treatments and devices. This study improves a dynamic, predictive model of human gait which uses model predictive control (MPC) to replicate the control of the central nervous system (CNS). In this work, improved performance criteria, including metabolic cost and dynamic effort, are developed using an existing optimization framework to better mimic control of the CNS. Consistent with existing literature, incorporating dynamic effort and COM energy into the objective function improved gait simulations. This study also demonstrates COM energy and dynamic effort can both be used to predict metabolic energy consumption, which is likely the primary optimization criteria in normal gait generation.
Vibration Control of Spur Geared Rotor Systems With Transmission Errors by Active Magnetic Bearings
Authors: Majumder Gargi , Tiwari Rajiv
Published: November 2019

Dynamic forces between the mating gears are generated due to the mesh deformation, gear eccentricities, transmission error, and gear run-out, which cause excessive vibration and noise. Study and control of these forced vibrations in gear box are vital to prevent any adverse effects on the gears and its supporting structures. Hence, this work presents a novel concept of active vibration control by introducing Active Magnetic Bearings (AMBs) on the shaft of a spur gearbox having conventional bearings as well. The AMB suppresses the response of the system by generating controlled electromagnetic forces based on the gear shaft vibration measurement. The AMB force is applied without any physical contact as opposed to mechanical forces in conventional bearings. A coupled torsional-lateral vibration analysis has been simulated with the effects of mesh deformation, gear eccentricities, transmission error, and gear run-out. The electromagnetic actuator is designed in such a way that a resultant radial control force can be developed with the help of forces in two mutually perpendicular directions. With a feedforward PID controller, the transverse vibration amplitude is observed to be suppressed to a considerable level. The frequency domain analysis is done using a full spectrum, which shows that multiple harmonics of gear mesh frequency is minimized simultaneously.
Predicting Multi-Disciplinary Design Performance Utilizing Automated Topic Discovery
Authors: Ball Zachary , Lewis Kemper
Published: November 2019

Increasing the complexity of engineering design projects expands of the diversity of required topic knowledge. Multi-disciplinary design processes have the need for expertise from multiple fields of study. In the context of mass collaboration within engineering design, positioning key members within multi-disciplinary teams is of great importance. Determining how each discipline impacts the overall design process requires an understanding of the mapping between competency and performance. This work explores this mapping through the use of predictive models composed of various regression algorithms. Design performance of students working on their capstone design project is analyzed and the relationship between individual competencies is compared against their overall project performance. Each competency and project is represented as a distribution of topic knowledge to produce the performance metrics. Following the automated topic extraction of the textual data, the regression algorithms are applied. Three topic models and five prediction models are compared for their prediction accuracy. From this analysis it was found that representing both input and output variables as a distribution of topics while performing a support vector regression provided the most accurate mapping between ability and performance.
Modeling and Dynamic Characteristics of Planetary Gear Transmission in Non-Inertial System of Aerospace Environment
Authors: Wei Jing , Shi Lei , Zhang Aiqiang , Qin Datong
Published: November 2019

The traditional research on the dynamics of planetary gear transmission system is based on the assumption that the support is on the ground. However, the planetary gear transmission system inside the aircraft is spatially moved along with the airframe, which is not only subject to gravity, but also to convected inertia force and Coriolis inertia force, as well as gyroscopic moment. These loads affect the dynamic characteristics of the planetary gear transmission system. In order to investigate the dynamic behavior of planetary gear transmission system in non-inertial system of aerospace environment, the kinematic equations of the central component and planetary gear in arbitrary spatial motion state of the airframe are deduced with the influence of internal non-inertial system and external non-inertial system. Subsequently, the coupling dynamic model of planetary gear transmission system is established, which is in non-inertial system of aerospace environment. The motion variation law of planetary gear transmission system in the non-inertial system and the dynamic behavior of each component in different non-inertial conditions are researched based on the hovering motion of the airframe. The results indicate that the radial equilibrium position of the planetary gear has great offset due to the influence of non-inertial system inside the planetary gear train when the airframe has no spatial motion. Moreover, the gravity on each component will generate radial force, which and additional inertial force will vary with the external non-inertia conditions when the airframe is in the state of spatial motion. In addition, different non-inertial conditions have significant influence on the motion trajectory, bearing force and acceleration of each component, and have different influence rules on the central component and planetary gear.
The Evaluation of Bending Fatigue Testing of Austempered Ductile Iron Spur Gear
Authors: Zhang Qi , Lv Jianhua , Syed Rizwanulhaque , Zhang Jing , Xu Yang , Liu Baojian
Published: November 2019

An experimental evaluation of bending fatigue strength for austempered ductile iron (ADI) spur gears have been performed using Zwick fatigue tester. The gear material was manufactured by vertically continuous casting, in which the radius of the graphite grains is smaller. The Stress-Number of Cycles curve (S-N curve) for the bending fatigue strength of the ADI spur gears are manufactured without any specific surface treatments, and have been obtained by post-processing software. It was observed that when the reliability was 50%, the fatigue limit was 304.89 MPa. It has provided a reliable basis to rate the reliability design of the small gearboxes in automation later.
Cylindrical Developable Mechanisms for Minimally Invasive Surgical Instruments
Authors: Seymour Kenny , Sheffield Jacob , Magleby Spencer P. , Howell Larry L.
Published: November 2019

Developable mechanisms conform to and emerge from developable, or specially curved, surfaces. The cylindrical developable mechanism can have applications in many industries due to the popularity of cylindrical or tube-based devices. Laparoscopic surgical devices in particular are widely composed of instruments attached at the proximal end of a cylindrical shaft. In this paper, properties of cylindrical developable mechanisms are discussed, including their behaviors, characteristics, and potential functions. One method for designing cylindrical developable mechanisms is discussed. Two example developable surgical devices that exemplify these behaviors, characteristics, and functions, along with the kinematic mechanisms comprising them, are discussed in detail.
Clearance Measurement of 3D Objects Using Accessibility Cone
Authors: Inui Masatomo , Nishimiya Kouhei , Umezu Nobuyuki
Published: November 2019

Clearance is a basic parameter in the design of mechanical products, generally specified as the distance between two shape elements, for example, the width of a slot. This definition is unsuitable for evaluating the clearance during assembly or manufacturing tasks, where the depth information is also critical. In this paper, we propose a novel definition of clearance for the surface of three-dimensional objects. Unlike the typical methods used to define clearance, the proposed method can simultaneously handle the relationship between the width and depth in the clearance, and thus, obtain an intuitive understanding regarding the assembly and manufacturing capability of a product. Our definition is based on the accessibility cone of a point on the object’s surface; further, the peak angle of the accessibility cone corresponds to the clearance at this point. A computation method of the clearance is presented and the results of its application are demonstrated. Our method uses the rendering function of a graphics processing unit to compute the clearance. A large computation time necessary for the analysis is considered as a problem regarding the practical use of this clearance definition.
Independent Asymmetric Period-3 Motions in a Periodically Forced Double-Pendulum
Authors: Luo Albert C. J. , Guo Chuan
Published: November 2019

In this paper, the independent asymmetric period-3 motions of a periodically forced, damped, double-pendulum are predicted through a discrete implicit mapping method. The corresponding stability and bifurcation conditions of the paired asymmetric period-3 motions are determined through eigenvalue analysis. Numerical simulation of the two asymmetric period-3 motions in the double-pendulum system is completed from analytical predictions. The example presented herein can be used for the vibration reduction of the first pendulum through the motions of the second pendulum.
Framed Harvesters for Collecting Energy From Vibrations in Industrial Plants
Authors: Doria Alberto
Published: November 2019

The idea of increasing the number of resonance conditions of a cantilever piezoelectric harvester by coupling the harvester with a frame that surrounds the harvester’s body is presented and discussed. Experimental tests on prototypes show that it is possible to design framed harvesters able to generate significant powers at two frequencies. Since the framed harvesters will be used for harvesting energy from periodic vibrations characterized by multiple harmonics, a tuning method is needed. For this reason a numerical sensitivity analysis is performed to analyze the effect on harvester tuning of small masses mounted on the frame. A prototype tuned to 40 and 80 Hz is developed and tested, its performance is compared with the one of a system of two simple harvesters tuned to the same frequencies.
Period-1 to Period-2 Motions in a Periodically Forced Nonlinear Spring Pendulum
Authors: Luo Albert C. J. , Yuan Yaoguang
Published: November 2019

In this paper, bifurcation trees of period-1 to period-2 motions in a periodically forced, nonlinear spring pendulum system are predicted analytically through the discrete mapping method. The stability and bifurcations of period-1 to period-2 motions on the bifurcation trees are presented as well. From the analytical prediction, numerical illustrations of period-1 and period-2 motions are completed for comparison of numerical and analytical solutions. The results presented in this paper is totally different from the traditional perturbation analysis.
Analysis of Octree Coding for 3D Point Cloud Frame
Authors: Li Pei-Heng , Lin Juo-Wei , Huang Yi-Lun , Lin Ting-Lan
Published: November 2019

The octree coding has been used extensively for 3D point cloud compression. For encoding, the recursive octree partition is used for the 3D point cloud frame until only one point is contained in the cube bin, and the representative bits are recorded. For decoding, the reversal procedure is performed to reconstruct the 3D point cloud frame. During the reconstruction, the reconstructed point in a particular bin is usually quantized to a particular corner of the bin for the reconstructed 3D point cloud frame; this introduces coding distortion in the point location. In this paper, nine reconstructed locations are tested to distinguish their distortion results, and the bit cost is also analyzed.
Some Fundamental Properties on the Sampling Free Nabla Laplace Transform
Authors: Wei Yiheng , Chen Yuquan , Wang Yong , Chen YangQuan
Published: November 2019

Discrete fractional order systems have attracted more and more attention in recent years. Nabla Laplace transform is an important tool to deal with the problem of nabla discrete fractional order systems, but there is still much room for its development. In this paper, 14 lemmas are listed to conclude the existing properties and 14 theorems are developed to describe the innovative features. On one hand, these properties make the Ntransform more effective and efficient. On the other hand, they enrich the discrete fractional order system theory.
A Non-Traditional Variant Nonlinear Energy Sink: Transient Responses
Authors: Jin Youzuo , Liu Kefu , Li Deli , Xiong Liuyang , Tang Lihua
Published: November 2019

In this paper, a non-traditional variant nonlinear energy sink (NES) is developed for simultaneous vibration suppression and energy harvesting in a broad frequency band. The non-traditional variant NES consists of a cantilever beam attached by a pair of magnets at its free end, a pair of the so-called continuous-contact blocks, and a pair of coils. The beam is placed between the continuous-contact blocks. The constraint of the continuous-contact blocks forces the beam to deflect nonlinearly. Each of the magnet-coil pairs forms an electromagnetic energy harvester. Different from a traditional way that attaches the coils to the primary mass, the developed setup has the coils fixed to the base. First, the developed apparatus is described. Subsequently, the system modeling and parameter identification are addressed. The performance of the apparatus under transient responses is examined by using computer simulation. The results show that the proposed apparatus behaves similarly as the NES with the following features: 1:1 resonance, targeted energy transfer, initial energy dependence, etc.
Automatically Generating 60,000 CAD Variants for Big Data Applications
Authors: Ramnath Satchit , Haghighi Payam , Kim Ji Hoon , Detwiler Duane , Berry Michael , Shah Jami J. , Aulig Nikola , Wollstadt Patricia , Menzel Stefan
Published: November 2019

Machine learning is opening up new ways of optimizing designs but it requires large data sets for training and verification. While such data sets already exist for financial, sales and business applications, this is not the case for engineering product design data. This paper discusses our efforts in curating a large Computer Aided Design (CAD) data set with desired variety and validity for automotive body structural compositions. Manual creation of 60,000 CAD variants is obviously not viable so we examine several approaches that can be automated with commercial CAD systems such as Parametric Design, Feature Based Design, Design Tables/Catalogs of Variants and Macros. We discuss pros and cons of each method and how we devised a combination of these approaches. This hybrid approach was used in association with DOE tables. Since the geometric configurations and characteristics need to be correlated to performance (structural integrity), the paper also demonstrates automated workflows to perform FEA on CAD models generated. Key simulation results can then be associated with CAD geometry and, for example, processes using machine learning algorithms for both supervised and unsupervised learning. The information obtained from the application of such methods to historical CAD models may help to understand the reasoning behind experiential design decisions. With the increase in computing power and network speed, such datasets together with novel machine learning methods, could assist in generating better designs, which could potentially be obtained by a combination of existing ones, or might provide insights into completely new design concepts meeting or exceeding the performance requirements.
Autonomous Door Opening With the Interacting-BoomCopter UAV
Authors: McArthur Daniel R. , Chowdhury Arindam B. , Cappelleri David J.
Published: November 2019

This paper presents the design of a light-weight, compliant end-effector and an image processing strategy that together enable the Interacting-BoomCopter (I-BC) unmanned aerial vehicle (UAV) to perform an autonomous door opening task. Autonomy is achieved through the use of feedback from an on-board camera for door detection & localization, and embedded force and distance sensors in the end-effector for detecting the physical interaction with the door. The results of several experimental flight tests are presented in which the end-effector and image processing strategy were deployed on the I-BC to successfully open a small enclosure door autonomously.
Additive Manufacture of Fibre-Reinforced Structures: Design Process and Principles
Authors: Camburn Bradley , Ismail Elyud , Perez K. Blake , Lauff Carlye , Wood Kristin
Published: November 2019

Fiber-reinforcement of structures built with additive manufacturing (AM) has been the focus of many recent innovations in the AM space. These innovations have further enabled AM’s progress from a prototyping technology to a viable manufacturing process for end use parts under normal load conditions. This paper introduces a set of design principles to drive innovation and the creation of novel AM technologies capable of producing fiber-reinforced components. The principles were developed through a comprehensive survey of the literature and patents to identify fundamental design insights that made the published achievements and innovations possible. From the collected body of insights, 23 unique design principles are identified. These principles are formalized and organized within the framework of a matrix representation, connecting established fiber-reinforced composite guidelines to specific sub-functions of AM. Finally, a fiber-reinforced additive manufacturing machine is developed by employing a subset of the identified principles as a demonstration of their utility.
Post-Disruption Performance Recovery to Enhance Resilience of Interconnected Network Systems
Authors: Wu Jiaxin , Wang Pingfeng
Published: November 2019

Mitigating the effect of potential disruptive events at the operating phase of an engineered system therefore improving the system’s failure resilience is an importance yet challenging task in system operation. For complex networked system, different stakeholders complicate the analysis process by introducing different characteristics, such as different types of material flow, storage, response time, and flexibility. With different types of systems, the resilience can be improved by enhancing the failure restoration capability of the systems with appropriate performance recovery strategies. These methods include but not limit to, rerouting paths, optimal repair sequence and distributed resource centers. Considering different characteristics of disruptive events, effective recovery strategies for the failure restoration must be selected correspondingly. However, the challenge is to develop a generally applicable framework to optimally coordinate different recovery strategies and thus lead to desirable failure restoration performances. This paper presents a post-disruption recovery decision-making framework for networked systems, to help decision-makers optimize recovery strategies, in which the overall recovery task is formulated as an optimization problem to achieve maximum resilience. A case study of an electricity distribution system is used to demonstrate the feasibility of the developed framework and the comparison of several recovery strategies for disruption management.