bluuebunny/crossref_metadata_2025 huggingface dataset:
An Investigation of the Wake and Vortex Formation of a Helicopter Rotor Blade
Authors: Pulok Mohammad Khairul Habib , Chakravarty Uttam K.
Published: January 2022

Vortices are present in many engineering applications and are systematically generated by lifting surfaces. The vortex characteristics and the wake surrounding a helicopter rotor blade play an important role because they affect the flow physics surrounding the rotor blade. Therefore, an advanced mathematical and computational model of rotor wake and blade vortex gives a better understanding of the helicopter rotor dynamics. The strength of the vortex depends on the blade geometry, loading, and the aircraft’s operational state. A concentrated tip vortex line, an inboard trailing vortex sheet, and a shed vortex are accountable for aerodynamic airload generation. Among these, tip vortices have the maximum contribution and are formed by the rolling up of trailing vortices near the tip of the wing. In this study, tip vortex models are used to characterize the vortex core structure and prescribed wake models are utilized for analyzing the hovering flight. A Bo 105 composite, hingeless helicopter rotor blade is considered for the computational analysis. A fluid-structure interaction model is developed by coupling the finite element model of the rotor blade with a computational fluid dynamics model of the surrounding air to analyze the helicopter rotor blade dynamic response and to investigate vortex formation due to the fluid-structure interaction. The swirl velocity is minimum, and the axial velocity is maximum at the vortex center. The axial velocity decreases and swirl velocity increases with increasing the distance from the vortex center to the core radius.
Prognostic Health Monitoring Method for Thermal Fatigue Failure of Power Modules Based on Finite Element Method-Based Lagrangian Neural Networks
Authors: Kano Akira , Monda Tomoko , Suzuki Tomoyuki , Uehara Hideaki , Fumikura Tomoya , Hirohata Kenji
Published: January 2022

Prognostic health monitoring technologies for power electronic systems assess their performance degradation, load histories, and degrees of fatigue in order to increase maintenance effectiveness, reliability design methods, and equipment availability under conditions of actual use. To improve reliability and reduce downtime, prediction of reliability in terms of thermal fatigue life under field conditions is important, as is the use of load and health monitoring data from the field in cases of performance degradation during use, maintenance, and field failure. The fatigue life of solder joints is also affected by whether the load history waveform is symmetric or asymmetric. In this paper, we propose a novel health monitoring method for thermal fatigue failure corresponding to time-dependent inelastic strain response, such as in asymmetric cycles, by use of a surrogate model obtained by a finite element method-based thermal stress simulation. We applied this method to an insulated-gate bipolar transistor power module capable of monitoring module temperature, electrical performance, and number of revolutions of the cooling fan. With the proposed method, inelastic strain cycles and thermal fatigue life distribution of solder joints could be estimated from their temperature monitoring history. The method was judged to be useful for assessing thermal load histories and estimating thermal fatigue life in prognostic health monitoring.
Surface Defect Detection in Steel Plates Using Machine Vision
Authors: Mantoni Aaron , Chauhan Vedang
Published: January 2022

Surface defect detection and classification in small size steel plates using machine vision inspection has been researched and presented in this paper. The steel plates that are used in the automobile drive chains for power transmissions are used as the test parts. The components of chains undergo the manufacturing steps such as punching, heat treatment and polishing before the final assembly. Due to a high temperature and loading conditions, sometimes the plates get distorted. The research project was set out to detect, classify and sort non-defective and defective plates into separate bins using machine vision inspection. A database of non-defective and defective parts was generated using the vision acquisition program. The number of images in the database were increased using data augmentation techniques. Various vision inspection techniques such template matching based object classification implemented using NI Vision Builder Software and Convolutional Neural Networks (CNN) implemented in MATLAB have been trained and tested. The vision algorithms communicated pass or fail decision through the serial communication and controlled the sorting system using a microcontroller. Depending on the decision, the parts were sorted into accepted (non-defective parts) or rejected (defective parts) bins. The project was successful in achieving the milestones defined in the research objective. The results with the two inspection methods, Object classification and CNN based method, have been reported. A classification accuracy of 96 % was achieved using the object classification method, while the CNN based method resulted in the 100 % classification accuracy. The developed algorithms can be implemented on a high-speed smart camera and the system can be used for realtime online inspection.
Safety Technology Advancements for Autonomous Cars; Prospective of Manufacturing, Regulatory and Society
Authors: Pourgol Mohamad Mohammad , Pourgol Mohamad Amin
Published: January 2022

We have witnessed remarkable technology advancements and competitions in autonomous and connected vehicles. There has been a vigorous technological development effort in the past few years to introduce self-driving smart vehicles for a connected world. If applied correctly, these technologies can enable solutions to help city transportation systems improve the economics of transportation, environmental concerns, and quality of life for everyone. The problem requires a holistic approach. While technological development has been intriguing, competitive, and vigorous, the industry’s advances on the issues of safety, risk, and reliability have been dismal. Despite its limited uses and manufacturers’ stated goal of making autonomous cars demonstrably safer than an average human-controlled car, several accidents and near-misses have already occurred. The mean distance driven to an unsafe condition, near miss or accident has been far shorter than the conventional road vehicles. While the public at large is intrigued about these technologies, the safety concerns are profound. This article is aimed to review the safety of AV systems from design and manufacturing, society and ethics, advancement of the safety/reliability technologies assessing their readiness and a review from academic point of view to understand the area for further research.
A Novel Computational Framework for the Effective Transport Properties of Heterogeneous Materials Reconstructed From Digital Images
Authors: Ogbuanu Kelechi O. , Roy R. Valéry
Published: January 2022

In computational material science, Digital Image Processing and Big Data analysis play a crucial role in Microstructure Characterization and Reconstruction (MCR), especially in the estimation of structure-property relationships. In this work, we are interested in the calculation of the effective transport properties of composite materials from digital images. Because most MCR techniques are heavily statistical, they may suffer from significant microstructure information loss as they are incapable of reproducing exact images of microstructures. Here, we take advantage of pattern recognition algorithms to extract nearly exact morphological information pertaining to the interphase boundaries from digital microstructural images, thereby minimizing information loss. The data extracted then serves as the basis for our effective transport property module for calculating the effective properties of two-phase composite materials in a way that is automated, fast, stable, memory efficient, and accurate. Our current formulation is limited to circular or near-circular inclusions, with very large contrast properties. Preliminary numerical tests on four cases of 2D, two-phase microstructure images yielded relative errors ranging from 0.1% to 2.0%, for image pixel density around 1000 × 1000 pixels. These relative errors are perfectly acceptable without having to resort to unrealistic image sizes.
Senior Capstone Project: A Classroom Heat Exchanger Demonstration Kit
Authors: Quigley Matthew , Klebba Jason , Jawad Badih , Liu Liping
Published: January 2022

Funded by an Undergraduate Program Equipment Grant from ASHARE, five undergraduate students in Mechanical Engineering were tasked to design and build a heat-exchanger demonstration kit as a teaching aid for classroom usage. The students were allotted one semester for design and one semester for assembly. The team researched existing products, performed theoretical calculations, and further identified their constraints with student surveys. The team also consulted several faculty members who are teaching Heat Transfer and Thermal Science Lab to get their input in order to provide a design and construction that best serves the teaching purpose. The final product is a rolling display board (approximately 4 feet wide and 5 feet tall) featuring a concentric tube heat exchanger prominently. An LCD screen allows students to see real-time temperature readings at four predetermined locations. Flow meters output the individual fluid flow rate of the coolant contained in two discrete piping loops. The fluid in these loops can operate in either parallel or counter-flow modes with the flip of a switch. Provisions were made to ensure sustainability and environmental consciousness, such as serviceable components and non-toxic coolant. The project concluded on time and under budget. This teaching kit is expected to help implementing active collaborative learning (ACL) activities in the classroom.
A Methodology for Risk Assessment to Improve the Resilience and Sustainability of Critical Infrastructure With Case Studies From the United States Army
Authors: Blackwell Neil , Evans Aubrey , Lee Phoebe , Panlasigui Christine , Russell Duncan , Wells Ke'Shaun , McCarthy Stephen , McCoy Brad , Davidson F. Todd
Published: January 2022

Reliable performance of energy and water infrastructure is central to the mission readiness of the United States Army. These systems are vulnerable to coordinated attacks from an adversary as well as disruption from natural events. The objectives of this work were to investigate Army installations in North America, identify best practices for improving the resilience and sustainability of critical energy and water infrastructure, and develop a framework and methodology for analyzing the resilience of an installation under varying outage scenarios. This work was accomplished using a multi-layered decision process to identify unique case studies from the 117 active-duty domestic Army installations. A framework for analyzing and assessing the resilience of an installation was then developed to help inform stakeholders. Metered energy and water data from buildings across Fort Benning, GA were curated to inform the modeling framework, including a discrete-event simulation of the supply and demand for energy and water on the installation using ProModel. This simulation was used to study the scale of solutions required to address outage events of varying frequency, duration, and magnitude, the combination of which is described as the severity of outages at a given site. This project helps develop a framework to inform how installations might meet Army Directive 2020-03, which states that installations must be able to sustain mission requirements for a minimum of 14 days after a disruption has occurred.
Thermodynamic, Environmental and Cost Evaluation of Compression-Absorption Parallel and Cascade Refrigeration Chiller
Authors: Kadam Sambhaji , Khan Muhammad Saad , Kyriakides Alexios-Spyridon , Papadopoulos Athanasios I. , Hassan Ibrahim , Rahman Mohammad Azizur , Seferlis Panos
Published: January 2022

A district cooling system (DCS), that generally operates with vapor compression refrigeration (VCR) chillers, is superior to conventional air conditioning as it helps to reduce energy consumption and to protect the environment by reducing carbon dioxide emissions. The advantages of the district cooling plant can be further enhanced by integrating the VCR system with a vapor absorption refrigeration system (VAR). In this context, this paper presents the comparative assessment of a VCR chiller and two configurations of an integrated VCR and VAR chiller, consisting of the parallel and the cascade configuration. Two refrigerant-absorbent mixtures in the VAR system are considered, namely the conventional NH3/H2O and the novel acetaldehyde/N,N-dimethylformamide (Acet/DMF). The energy, exergy, environmental and economic analysis of the systems have been performed considering the coefficient of performance (COP), the exergy efficiency (ηexergy), the total equivalent warming impact (TEWI) and the cost rate (Ċtot) as performance indicators. It is observed that the connection of the evaporator of the VAR with the condenser of the VCR in the cascade configuration increases the COP of the VCR unit by 292% compared to the stand-alone VCR system. Overall, the COP of the parallel and the cascade refrigeration system with the novel Acet/DMF is better than that of NH3/H2O. This performance can further be improved by enhancing the exergy efficiency. Overall, the thermodynamic, environmental and cost benefits of the novel Acet/DMF with the cascade arrangement of the VCR and the VAR system are superior to those of NH3/H2O.
Nonlinear Dynamics of a Two-Cam System
Authors: Yousuf Louay S. , Marghitu Dan B.
Published: January 2022

In this paper, a multi-body dynamic system of two cams, flat-faced follower with a revolute joint, and guides are discussed and analyzed. The input moments as a function of angular velocity are applied for the rotation of the two cams. SolidWorks software is used to simulate the multi body system. The nonlinear dynamics is analyzed with phase plane, and Poincare’ diagrams. The cams with different angular velocity are considered. The influence of different angular velocities of the cam and different internal dimensions of the follower guide on nonlinear dynamics behavior are taken into consideration. The friction between the follower stem and the guide has been taken into account. The clearance between the follower’s stem and the guides leads to impacts.
Fatigue Assessment of Pipelines With Dent and Crack Subjected to Cyclic Pressure Loading
Authors: Al-Nutifat Shadid A. , Pu Yongchang , Al-Shammari Abdulrahman S.
Published: January 2022

Subsea pipelines are subjected to external damage by fishing trawlers or dragged anchors which may result in a pipe defect such as a puncture, dent, gouge, crack or a combination of such defects (Allouti et al., 2014). Therefore, evaluation of these defects is very important in terms of assessment and for continued safe operation. This study is to evaluate the effect of dent with crack defects on the fatigue life of natural gas transmission pipelines. In order to illustrate the effect of a crack on the dented pipe, this study is divided into two parts. The first part is to study on the effect of dents alone on the fatigue life of the material, while the second part is to study on the effect of dents and crack on the fatigue life. Therefore, a parametric study using finite element numerical models was conducted to study the effect of plain dent and dent with crack on the fatigue life of the pipeline.
A Computational Study of the Evolution of Fabri-Choke in a Two-Dimensional Supersonic Ejector
Authors: C. V. Sumesh Babu , Lijo V.
Published: January 2022

An ejector refrigeration system (ERS) can significantly reduce electricity consumption compared to traditional compressor-based systems. Fabri-choking is an indication of an ejector operating in the idealized condition with a maximum entrainment ratio. Backpressure has a significant influence on ejector performance. Severe degradation in performance is observed when the backpressure increases from the design value. Until now, many works have been performed to design and evaluate the ejector systems. In the majority of these works, it is assumed that the ejector is working with fixed designed backpressure, which gives maximum performance. In almost all of the practical applications of ERS, the backpressure varies, mainly as the cooling load requirement changes. In such practical applications, the flow in the ejector is very interesting, and this paper takes a new look at the transient operation of an ejector with varying backpressure. In the present study, numerical simulations have been used to provide detailed flow physics and, in particular, the occurrence of Fabri-choke in a supersonic ejector. The results obtained reveal compound choking, multiple evolutions of Fabri-choke, and its relation to wave reflections. Results showed that the first and second occurrences of Fabri-choke occurred when the backpressure is reduced by 6.0% and 8.0%, respectively. Methods to ascertain Fabri-choke in numerical simulations and experimental studies were also separately addressed.
Nanostructuring of Metallic Additively Manufactured Surfaces for Enhanced Jumping Droplet Condensation
Authors: Ho Jin Yao , Rabbi Kazi Fazle , Sett Soumyadip , Wong Teck Neng , Leong Kai Choong , Miljkovic Nenad
Published: January 2022

Vapor condensation on metallic surfaces is a phase-change phenomenon that has widespread applications in many processes. Jumping-droplet-enhanced condensation is an effective mode of dropwise condensation due to its higher droplet removal rate, enabling more efficient heat transfer. However, maintaining stable jumping-droplet condensation, requires surface structures to be suitably designed to prevent droplet pinning and surface flooding. In recent years, using metal additive manufacturing (AM) processes to create heat exchanger surfaces has received significant attention due to its design freedom and versatility in fabricating highly complex functional parts. Here, we present a highly scalable method of fabricating superhydrophobic (SHP) AM surfaces from aluminum alloy, AlSi10Mg, and an experimental investigation of their thermal performance during steam condensation. The test samples were fabricated by Selective Laser Melting (SLM), an AM technique for producing metallic parts. Through detailed material characterizations, we found that it is possible to achieve superior superhydrophobicity on AM surfaces, with unique cellular-like nanoscale surface features, by simple chemical etching and functionalization processes.

To understand the droplet dynamics and obtain insights on the effects of AM nanostructures on the condensate droplet morphology and jumping, we carried out condensation experiments with an environmental scanning electron microscope (ESEM) at low supersaturation of ∼1.06. The important relations between the fabricated AM nanostructure morphology and droplet dynamics are established by characterizing the droplet departure diameter and droplet jumping frequency. To determine the anti-flooding and condensation heat transfer performances of the AM SHP surfaces, pure vapor condensation experiments under higher supersaturation conditions were carried out in a well-controlled environmental chamber. Together with the aid of high-resolution imaging and heat transfer measurements, we demonstrate significant reduction in droplet pinning sites due to the implementation of the AM cellular-like structure. This reduces the thermal barrier between the condensing surface and surrounding vapor, and hence, increases the condensation heat transfer. Our results show that excellent droplet jumping performance and better droplet mobility can be achieved by using AM SHP surfaces as compared to conventional SHP aluminum extruded tubing. These results underscore the potential of advancing AM structured surfaces for jumping-droplet-enhanced condensation under high heat flux conditions.
Development of Bi-axial Tensile Testing for Porous Polymer Membranes and Its Deformation Characteristics
Authors: Kodaira Yasuhisa , Miura Tatsuma , Takano Yoshinori , Yonezu Akio
Published: January 2022

Porous polymer membranes are generally polymeric materials having numerous pores and complicate network structure. Due to their features, these materials sometimes exhibit anisotropic deformation in their elasto-plastic deformation. It is thus important to investigate the deformation behavior of materials, including anisotropic deformation under multi-axial loading. Here we developed a new testing machine for bi-axial tension for porous polymer membranes, in order to evaluate the deformation behavior under bi-axial tension and elucidate the deformation mechanism based on their microstructure. First, uni-axial tensile tests were conducted in each direction to investigate the change in Young’s modulus and yield strength depending on the tensile direction. It was found that there was deformation anisotropy. Next, we newly developed a bi-axial tensile testing for the present membranes. Since the present membrane has lower deformation rigidity and the thickness is very thin, gripping of specimen and applying uniform deformation are difficult. Thus, this study developed the gripping part to enable uniform tensile deformation during the test. Stress-strain curves of each loading axis were obtained by changing the applying strain ratio. Based on the results, a yield surface was created to investigate the deformation behavior under bi-axial tensile loading. We also investigated the deformation mechanism of the microstructure (porous structure) by using SEM observation.
Navigation Method for UGV on Aerial Elevation Maps for Autonomous Missions in Sandy Deserts
Authors: Bjelotomic Marko , Subramaniam Prashanth , Ismail Hesham , Aljasmi Abdallah
Published: January 2022

Autonomous navigation in wide outdoor areas faces challenges not present in structured environments. Simultaneous localization and mapping (SLAM) is a popular method of creating the map using the robot, and navigating in it. SLAM is difficult to achieve where there is no paved roads, buildings, and trees like in the sandy deserts. Autonomous robots cannot predict what is waiting behind the sand dune. Even if the terrain was mapped earlier, sand dunes can shift unpredictably. Therefore, mapping and GPS-based path planning should be done before every autonomous mission in such a dynamically shifting environment. Navigation can rely on GPS signals given the lack of obstructions. We develop a method for an Unmanned Aerial Vehicle (UAV) to autonomously take hundreds of images, convert terrain images into an elevation map, analyze the elevation map and generate traversable GPS waypoints for the Unmanned Ground Vehicle (UGV).
A Sensitivity-Based Approach for Interval Reliability Analysis of Structures Under Random Excitation
Authors: Giunta Filippo , Muscolino Giuseppe , Sofi Alba
Published: January 2022

The present study is devoted to the reliability analysis of linear discretized structures, with uncertain-but-bounded mass and stiffness parameters, subjected to stationary Gaussian multi-correlated random excitation. The reliability function for the extreme value stress process is evaluated in the framework of the first-passage theory. Due to the interval uncertainties affecting structural parameters, the reliability function is an interval function.

The aim of the paper is to propose an efficient procedure for the evaluation of the bounds of the interval reliability function which provides a range of structural performance. To this aim, a sensitivity-based approach is applied. So operating, the dangerous overestimation of the solution, caused by the dependency phenomenon, is overcome.

The main advantage of this approach is to provide appropriate combinations of the values of the uncertain-but-bounded parameters which yield accurate predictions of the bounds of the interval reliability function for the extreme value stress process. A case study is analyzed to demonstrate the accuracy and efficiency of the presented method.
Evanescent Coupling Between Aluminum Pillars
Authors: Akiki Rock , Pennec Yan , Noual Adnane , Lheurette Eric , Bonello Bernard , Djafari Rouhani Bahram
Published: January 2022

We theoretically investigate with the help of the finite element method, the interaction between aluminum pillars erected on top of a semi-infinite substrate of silicon in the low frequency range. Our interest is to control and manipulate the propagation of surface acoustic waves (SAW) along the linear chain of pillars for frequencies in the [0, 2] GHz range. We show that a pair or a chain of pillars can interact together through the excitation of the resonant compressional and bending eigen-modes, depending on the length of the secant line between the two pillars and the angle with respect to the incident surface acoustic wave. The interaction comes from the coupling between the compressional mode with the out-of-plane motion of the Rayleigh wave. Such a coupling can be achieved when the pillars are closed enough from each other to allow the recovery of the evanescent fields.
Bell 412 Full Flight Envelope Aircraft Simulation Model Development and Evaluation With Nonlinear Equations of Motion
Authors: Crain Alexander , Ricciardi Joseph , Stachiw Terrin
Published: January 2022

Flight models are used to accurately predict the aircraft performance and response and are used for aircraft development, engineering analysis, and pilot training. It is common practice to use linearized small perturbation equations of motion for the identification of the stability and control derivatives that form the basis of flight models using system identification. Due in large part to advances in computer technology and optimization techniques, it is feasible to use nonlinear equations of motion for time-domain system identification. This report compares two full flight envelope aircraft models that were developed with identical data: one developed using linearized equations of motion in a state space form, and the other with nonlinear equations. The global flight models were developed for the NRC Bell 412 helicopter in forward flight across its range of speeds, altitudes, and configurations. Use of the nonlinear equations of motion produced a model with less parameter variance and its corresponding global model had improved trim characteristics.
Modelling the Time-Dependent Behavior of Elastomers Using Fractional Viscoelastic Material Formulations
Authors: Leenders Arne , Vahdati Zadeh Hamed , Wangenheim Matthias
Published: January 2022

Elastomer materials are often used for components such as tire treads or hydraulic sealings, when deformable and damping behavior of components are desired and high dynamic loads appear. Such elastomers show time- and frequency-dependent characteristics, called viscoelasticity. The modelling of viscoelastic material is mainly implemented in simulations by rheological models, which often consists of elastic and damping elements. A viscoelastic model can be parametrized to experimental data to describe a specific elastomer with high accuracy. The most common model is the Prony-series. This model uses several Maxwell-branches (connection of one elastic and one damping element in series). Every branch is only able to fit the experimental behavior at one single excitation frequency. This fact makes it necessary to use a lot of parameters for adapting the frequency- and temperature-dependent characteristics over decades of the excitation frequency.

To overcome this need for a huge amount of parameters we formulate a fractional viscoelastic model approach that gets along with a much smaller set of parameters, using finite elements. In order to reduce the numerical effort, a similarly formulated model is set up on force-displacement level additionally. In this way, the complexity of the simulation can be reduced with mapping of the material behavior.
Fabrication, Processing and Characterization of Carbon Fibre Reinforced Laminated Composite Embedded With Graphene Lattice Sheets
Authors: Jadhav Vishwas S. , Kelkar Ajit D.
Published: January 2022

This manuscript introduces the challenges in the fabrication of graphene sheet reinforced non-crimp fabric (NCF) composite laminates and their influence on the interlaminar strength of the composite laminates. In the current work, the laminates were fabricated using non-crimp carbon fabric prepreg along with 50,120 and 240 μm thick graphene sheets at the mid-plane. Double Cantilever Beam (DCB) tests are done as per ASTM 5528 using INSTRON electromechanical testing system. Modified Beam Theory method used to compute Mode I fracture toughness, using load, displacement, specimen dimension, and crack opening displacement.

The graphene sheets are brittle; little bonding between the graphene and matrix observed during the fabrication process results in a fragile interface. To overcome this problem, graphene sheets were converted into a lattice structure. The lattice structure used in the present research had horizontal, vertical, and square grids. Effects of sheet thickness, grid pattern were evaluated by Mode I fracture toughness, with and without nanoengineered enhanced laminates. Axio Image upright microscope used to compare the bonding at the midplane after the DCB test. The results indicate that the composite laminates fabricated using lattice graphene structure had better interlaminar strength than the laminates fabricated with straight graphene sheets.
A Combined Theoretical and Experimental Investigation of the Overall Energy Consumption in a Wet Dual Clutch System During a Driving Profile
Authors: Liu Zhihong , He Ping , Rinderknecht Stephan
Published: January 2022

Reduction of the energy consumption and increase of the energy efficiency of the wet dual clutch system are important factors for vehicle transmission improvement. The demand of a precise investigation of the overall energy consumption in the clutch system has therefore increased significantly. A wet dual clutch system represents in this paper dual clutch packs and their electro-hydraulic system. The energy, which is not efficiently transferred in the power flow path but consumed in the wet dual clutch system, is considered here as the energy consumption. The possible energy consumption in the wet dual clutch system are hydrodynamic drag torques between the disengaged discs, frictional torques during the clutch engagement and electro-hydraulic energy usage for actuating and cooling systems.

The aim of this paper is to evaluate the energy consumption in a whole wet dual clutch system at the system level. Firstly, due to lack of experimental data on the system level, all the available analytical models for predicting the hydrodynamic drag torque are analyzed and compared based on the varied influential parameters. The energy dissipation mechanisms in the clutch engaging phase and the energy usage in the electro-hydraulic system are explained based on the measured signals. One driving profile is applied here and the hydrodynamic energy dissipation is calculated with the chosen analytical model, while the other energy usage in the wet dual clutch system is analyzed with the measured signals. Based on the evaluation on the system level, the majority of the energy is dissipated in the clutch packs for reducing the relative speed, while the energy usage in the actuating system comes next. The hydrodynamic energy losses and the consumption in the cooling system share the lowest proportion.
Controlling Global Surface Variations in Face Milling of Variable Stiffness Structure Based on Iterative Prediction via FEMU and GA
Authors: Liu Shun , Jin Sun , Tian Ang , Gu Qunfei , Chen Kun , Mo Wei
Published: January 2022

To control the global surface variations is highly important for improvement of surface properties and it relies on robust process design of process parameters and fixture layout. However, due to the changes of milling conditions, the controlling of surface variations based on discrete sampling of interest points is hard to meet the global optimal in entire milling surface. To address this issue, this paper attempts to provide a methodology to optimize process parameters and fixture layout iteratively towards minimum the machined global surface variations based on the finite element model updating (FEMU) method and genetic algorithm (GA). The global surface variations are determined by a coupled numerical model via FEMU, which enable iterative finite element simulations to decouple the force-deformation coupling at each instant milling moment and also renew the updating of changing milling conditions along with the changing of milling locations during the whole face milling process. In optimization process, the milling parameters and fixture layout are updated in finite element model via FEMU method and optimally selected via GA based on the global surface variations prediction. Based on the proposed method, the continuous milling parameters and discrete fixture layout can be optimized with minimum global surface variations simultaneously. It provides a comprehensive methodology to control the global surface variations in face milling of variable stiffness structure for its industry implementation.
Investigating the Difference in Cortical Bone Adaptation at Endocortical and Periosteal Surfaces by Fluid Flow Analysis
Authors: Singh Sanjay , Singh Satwinder Jit , Prasad Jitendra
Published: January 2022

Load-induced fluid flow in lacunar-canalicular porosity in bone has been suggested to play an essential role in bone adaptation. The applied load causes the fluid inside the lacunar-canalicular system to flow. The osteocytes are believed to sense the shear stress exerted due to the fluid flow and drive new bone formation. The energy dissipated in moving fluid may be considered as a stimulus for bone adaptation. The endocortical bone surfaces are also believed to adapt differently compared to the periosteal surfaces. We investigate such differences and present a finite element poroelasticity-based mathematical model on estimating bone formation rate at mid-diaphysis of a C57BL6 mouse tibia subjected to cantilever loading. A weighted average of dissipation energy in the zone of influence has been considered in accordance with the literature. The model predicts bone formation rate (BFR) at the periosteal surface as well as on the endocortical surface. As desired, the model can differentiate between a continuous cyclic loading and a rest-inserted cyclic loading. The model establishes that the difference in bone formation at the two surfaces, viz. endocortical and periosteal, may be due to the difference in dissipation energy density only, caused by different boundary conditions at the two surfaces.
An Extended Multi-Actuated Optimized Reconfigurable Freeform Surface (e-MORFS) Mold With Targeted Variability Capacity
Authors: Yang Kunlin , Chen Rui , Qaiser Zeeshan , Johnson Shane
Published: January 2022

Custom manufacturing of freeform surfaces, such as that of sheet metal components for automobiles, or the body panels and the composite parts of aircraft provides major challenges for traditional dedicated manufacturing systems (DMSs) due to the following factors: (1) mass customization, (2) rapid prototyping, (3) time and personnel cost, and (4) system complexity. Typically, flexible manufacturing systems (FMSs) and reconfigurable manufacturing systems (RMSs) are designed for fixed and high variability in the design parameters resulting in high system complexity. These design methodologies have many opportunities stemming from some limitations including: (1) lacking feature analysis of high variability products, (2) high system complexity, (3) reduced capacity for manufacturing of high curvature surfaces, and/or (4) low repeatability. An extended Multi-actuated Optimized Reconfigurable Freeform Surface (e-MORFS) mold is developed for a targeted application for the mass production of the freeform surfaces, e.g. custom foot orthoses (CFOs). The e-MORFS mold aims at the following goals: (1) to achieve size and shape variability for a complex product with a large population, (2) to reduce system complexity considering product features, and (3) to achieve high curvature surface reconstruction with proper boundary conditions (BCs) to avoid wrinkling and stretching. The e-MORFS mold achieves the maximum error range of 0.3–0.5mm for the whole population with only 6 actuators. This study provides the e-MORFS mold and design algorithm potentially used for targeted application of freeform surface manufacturing, e.g. CFOs. These design methodologies may guide designs of freeform surface manufacturing in applications, e.g. automobile, aerospace, biomechanics, and architecture.
A Novel, Low-Cost Thermal System for Integrating Laboratory Experiences in Undergraduate Controls Courses
Authors: Terrill Trevor J.
Published: January 2022

Many undergraduate system dynamics & controls courses have limited laboratory experiences. In courses that include labs, many of the experiences include dynamics of motors, electrical systems, and unstable mechanical systems. The dynamics of these systems are often so fast that the system response cannot be viewed or interpreted real-time. This paper presents a novel thermal system that has been designed to address these challenges and provide meaningful lab experiences to students in undergraduate feedback control courses. The presented system offers multiple advantages that are designed to provide impactful lab experiences. The system can be used for multiple lab experiences that span the entire range of topics in a typical undergraduate controls course, including system modeling, time & frequency domain system analysis, design of controllers, and evaluation of controller performance. The system has been designed with the undergraduate student experience in mind, including the use of MATLAB for all student work, safety features that ensure minimal risk to students, and system dynamics that have been sized so that students can watch and interpret the system response real-time. The paper describes the system design and setup, along with sizing calculations used to create appropriate system dynamics. The thermal modeling used to design controllers is then detailed. The laboratory sessions are then described, including topics in thermal system modeling, system parameter identification, frequency analysis, and controller design. The paper concludes by assessing the use of the system in an undergraduate controls course and addressing topics that can be explored for future lab sessions.
A Machine Learning Approach for Predicting Melt-Pool Dynamics of Ti-6Al-4V Alloy in the Laser Powder-Bed Fusion Process
Authors: Rahman M. Shafiqur , Ciaccio Jonathan , Chakravarty Uttam K.
Published: January 2022

This paper presents a supervised machine learning (ML) model to predict the melt-pool geometries of Ti-6Al-4V alloy in the laser powder-bed fusion (L-PBF) process. The ML model is developed based on the normalized values of the five key features (i.e., the laser and material parameters) — laser power, scanning speed, spot size, powder layer thickness, and powder porosity. The two target variables are the melt-pool width and depth, which define the melt-pool geometry and strongly correlate the geometry with the melt-pool dynamics. Information about the features and the corresponding target variables are compiled from an extensive literature survey. A trained data set is created with the melt-pool evolution data collected from experiments. The data set is divided into training and testing sets before any feature engineering, visualization, and analysis, to prevent any data leakage. The k-fold cross-validation technique is applied to minimize the error and find the best performance. Multiple regression methods are trained and tested to find the best model to predict the melt-pool geometry data. Extra trees regressor is found to be the model with the least amount of error using the mean absolute error function. The verification of the ML model is performed by comparing its results with the experimental and CFD modeling results for the melt-pool geometry at a given combination of the processing parameters in the L-PBF process. The melt-pool geometry outputs obtained for the ML model are consistent with the experimental and CFD modeling results.
Study on Underwater Friction Stir Welded AA 2024-T3 Pipes Using Machine Learning Algorithms
Authors: Sabry Ibrahim , Mourad Abdel-Hamid I. , Thekkuden Dinu Thomas
Published: January 2022

Underwater friction stir welding, a new variant of friction stir welding process in which the weld coupons and tool-specimen interface are completely immersed in the water, has been successful to achieve wide popularity among researchers recently. In most of the studies, the underwater friction stir welding process is limited to join the flat plates. The research conducted on the underwater friction stir welding of pipes is rare due to the complexity in the design of the fixture and setup. Therefore, the current research is aimed to investigate the scope of underwater friction stir welding process for producing quality welded pipe joints. Initially, the current research focused on developing a system with proper components and fixture attached to the vertical milling machine for underwater friction stir welding of pipes. Twenty-seven experiment runs with three intermittent levels of process parameters — spindle speed of milling machine (1000 rpm, 1400 rpm, 1800 rpm), travel speed (10 mm/min, 16 mm/min, 20 mm/min) and shoulder diameter of tool (10 mm, 15 mm, 20 mm) are designed. Secondly, Al 2024-T3 pipes having an outer diameter of 30 mm and a thickness of 3 mm are welded using an underwater friction stir welding process for every combination of the process parameter. The elongation percentage, yield strength and tensile strength are experimentally evaluated from the tensile tests. Finally, the prediction capability of machine learning algorithms such as artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS) and adaptive neuro-fuzzy inference system with Harris hawks optimization (ANFIS-HHO) for 70% training data and 30% testing data was evaluated. The prediction capability of the machine learning algorithms was evaluated using the Mean Absolute Error, R2 statistic and Root Mean Square Error. ANN was found to the best with the highest R2 and least RMSE for predicting all three responses. Though the ANFIS exhibited the highest R2 and highest RMSE for every response, the incorporation of Harris hawks optimization to the ANFIS slightly improved the prediction capability of ANFIS. The prediction accuracy for elongation percentage, yield strength and tensile strength is found to be in the increasing order of ANFIS, ANFIS-HHO and ANN. The underwater friction stir welding process, machine learning algorithms, methods and results discussed in the paper are promising and useful for experts in the industries.
Acoustic Emission-Based Structural Health Monitoring for Future Lunar Pipelines
Authors: Escarcega Mario , Cephus Meghan , Hughes Skyler , Tsosie Nakii , Kelso Kimberly , Sandoval Raechelle , Ebrahimkhanlou Arvin
Published: January 2022

This paper explores the use of acoustic-based structural health monitoring (SHM) in lunar habitats to detect damage and failure in pipelines used for resource transportation. Acoustic-based SHM on Earth is a well-studied field of research. Various studies validate the effectiveness of acoustic-based SHM to detect, locate, and characterize damage in pipelines. Relevant literature shows that little to no research has been conducted on SHM regarding simulated lunar pipelines. In this paper, acoustic emission (AE) waveforms were collected and analyzed for aluminum pipe sections that were damaged from three separately simulated lunar conditions. Experiments simulating lunar regolith abrasion, internal galvanic corrosion, and irradiation were conducted on aluminum pipes. Pipes on the lunar surface will be constantly exposed to radiation, abrasion, and corrosion. As such, it is important to detect, localize, and predict damage resulting from these lunar hazards. The waveform data were clustered based on hit-driven properties. These clusters showed distinct differences between the datasets, which allowed for comparison and characterization of the data. It was found that variations in cluster shape and placement in peak, centroid, and average frequency could reliably distinguish between corrosive and abrasive processes. Understanding the differences in the data that contribute to distinctions between event types, and those that do not, will enable AE monitoring systems to better identify, characterize, and predict lunar pipeline failure.
Forebody Optimization Using Response Surface Methodology With Genetic Algorithm
Authors: Kandemir Omer , Tuncer Ismail H.
Published: January 2022

Aerodynamic design of a forebody geometry has a significant effect on aircraft performance and stability. Although the studies conducted on aircraft performance so far, mostly, focus on optimization of wing-like structures, the contribution coming from an effective forebody design to the aircraft performance could be as high as the contribution coming from wing-like structures. A proper forebody design can reduce the wave drag and provide better lateral characteristics at high angles of attack. The reduced drag may enable the aircraft to achieve higher speeds and consume less fuel which eventually results in higher endurance and range to be achieved. On the other hand, achieving better lateral characteristics at high angles of attack may enable aircraft to withstand higher gust loads during take-off and landing phases. In addition to that, it may provide improved spin characteristics. In this paper, the forebody optimization of a jet trainer aircraft is studied. While doing so, two objectives are considered. Turbulent flow solutions are obtained with SU2. Response surface methodology is used as database generator and Pareto-optimal solutions are searched by using non-dominated sorting genetic algorithm–II. The optimization study improves the aircraft performance in the aspects of the wave drag and the lateral stability.
Potentials for PdAgCu Metal Hydrides Energy Simulations
Authors: Hijazi Iyad , Zhang Chaonan , Fuller Robert
Published: January 2022

Palladium hydride (Pd-H) is a metallic palladium that can absorb substantial amount of H at room temperature. Because this H absorption is recoverable, it can be utilized in a variety of energy applications. When Pd is alloyed with silver (Ag), sulfur poisoning remains a problem, but adding Ag improves Pd mechanical properties, boosts hydrogen permeability and solubility, and narrows the Pd-H system miscibility gap region. Pd alloyed with copper (Cu) has a lower H permeability and solubility compared to pure Pd and Pd-Ag alloys, but adding Cu gives better sulfur and carbon monoxide poisoning resistance and hydrogen embrittlement resistance, as well as better mechanical properties and a wider operating temperature range than pure Pd. These findings show that alloying Pd with a mix of Ag and Cu to make Pd-Ag-Cu ternary alloys improves Pd’s overall performance while also lowering its cost. Thus, in this paper, we provide the first embedded atom method potentials (EAM) for the quaternary hydrides Pd1-y-zAgyCuzHx. The EAM potentials can capture the preferred H occupancy locations, and determine the trends for the cohesive energies, lattice constants and elastic constants during MD simulations. The potentials also captured the existence of a miscibility gap for the Pd1-y-zAgyCuzHx and predicted it to narrow and disappear when Ag and Cu concentration increases, as was predicted by the experimental findings.