bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of Crushing Response of Limited Bonding of a Composite Core With a Cross Tube
Authors: Jenson Sean , Ali Muhammad , Alam Khairul
Published: February 2021

Rectangular and round tubular structures are typically used in a vehicles’ front structure to increase the energy absorption capacity in the event of an accident. There is significant interest in lighter structures for improving automobiles’ fuel efficiency with the challenge of maintaining or preferably exceeding the energy absorption properties of the structure. The structural members are designed to take on the challenge of absorbing maximum amount of energy in a relatively short period of time, while also maintaining reactive forces below damaging levels as they undergo progressive deformation under axial loading. The type of deformation mode is critical as it defines the overall configuration of force-displacement curve. There are different types of deformation modes for cross tube under axial loading. Likewise, cellular structures exhibit distinct deformation modes under in-plane loading. The work presented here investigates the effects of bonding of composite cellular core structure on deformation modes of cross tubes under axial loading. The numerical simulations were performed in ABAQUS finite element software. Four cases were considered for analysis. The first case did not contain core bonding. The second case consisted of 3 bonding sites. In the third case, 5 bonding zones were defined and in the final case, 7 bonding sites were assigned. Bonding of the composite core resulted in an increase of up to 39.2% energy absorption as compared to the unbonded case. The results show discrete bonding of composite cellular core with the tube has significant effect on progressive deformation of tubes and therefore, presents an opportunity to re-configure force-displacement curve for improved protection of automobile structures under impact loading.
Initial Testing and Constitutive Modeling of Cellular Rubber Subjected to Large Strains and High Strain Rates
Authors: Bieler James A. , Davis Brad G.
Published: February 2021

In order to allow for the numerical modeling of impacts for the design of live fire facilities commonly used by military and law enforcement personnel against next generation and environmentally friendly ammunition currently in development, constitutive models for novel target materials must be developed. Many existing facilities are constructed from AR500 steel, coupled with a layer of cellular rubber to reduce impact velocities and contain projectile fragments. High strain rate models, such as the commonly used Johnson-Cook constitutive model, are widely available to characterize AR500 steel, but calibrated models do not currently exist to characterize the cellular rubber. This project seeks to address this shortfall and provide a suitable material model for designers of these facilities in order to ensure the safety of users and the public. Appropriate constitutive models that account for the large strain, high strain rates, and temperature effects experienced during ballistic events and the porosity of the material were researched and a plan developed for future materials testing. Three suitable models were selected for further analysis — A Non-Linear Elastic Model described by Johnson in his work with polyurethane coupled with a Mie-Gruneisen equation of state to account for the porosity of the material, an Osborn-Hull model developed for use with crushable solids, and the Holmquist-Johnson-Cook Model commonly used for cementitious materials.
Education and Workforce Development Programs in the Center for Advanced Automotive Technology
Authors: Liao Y. Gene , Yeh Chih-Ping , Petrosky Joseph , Hutchison Donald
Published: February 2021

The automotive industry is currently experiencing a revolutionary technological transformation including electrification, connectivity, automated/autonomous, lightweighting, and sustainability. This paper presents the education and workforce development programs developed and delivered by Wayne State University and Macomb Community College partnership in meeting industry needs for future workforce in advanced automotive technology. Through funding from the National Science Foundation, a Center for Advanced Automotive Technology (CAAT) was established as an Advanced Technological Education center to support the partnering work, developing and leading systemic curricula reforms. The center worked with industry partners identifying curriculum gaps and provided professional development for teachers to fill those gaps. CAAT also supported new automotive technology university/college programs through its seed funding program which funded others to create, implement, and share new curricula. The center is a preeminent resource for educating engineers and technicians in advanced automotive technology as all materials that were developed in partnership with CAAT were reviewed by industry experts and offered as a free resource through website. CAAT continues its tasks supporting the United States in its efforts to build and maintain a competent workforce ready to use the skills of the 21st century to move industries ahead.
Nonlinear Fluid-Elastic Behavior of a Flapping Wing With Low-Order Chord-Wise Flexibility
Authors: Majumdar Dipanjan , Bose Chandan , Sarkar Sunetra
Published: February 2021

The present study attempts to capture the fluid-structure interaction dynamics of a chord-wise flexible flapping wing system using a limited mode structural model coupled with a high-fidelity Navier-Stokes (N-S) solver. The wing is modeled as two elliptic rigid foils connected by a non-linear torsional spring that incorporates the chord-wise bending stiffness. The front link is subjected to an active pitching-plunging motion while the rear link undergoes flow-induced passive oscillation. The structural governing equation for the rear link takes the form of a Duffing equation subjected to base excitation and external aerodynamic forcing. The aerodynamic loads on the foil are computed using a discrete forcing Immersed Boundary Method based in-house N-S solver which is coupled with the structural solver by a staggered weak coupling strategy. A bifurcation study is performed considering the free-stream velocity as the control parameter, in the presence of both structural and aerodynamic non-linearities. A dynamical transition in the unsteady flow-field from a periodic reverse-Kármán wake to an aperiodic wake is observed as the flow parameters are varied. The same transition is also reflected in the passive oscillation of the rear foil when analyzed with tools from the dynamical systems theory.
Constitutive Modeling and Initial Validation of Cellular Concrete Subjected to Large Strains and High Strain Rates
Authors: Davis Brad G. , Dequenne Jared A.
Published: February 2021

The development of lead-free small caliber weapon systems has inadvertently resulted in rounds with more material penetration capabilities. The increased penetration may mean that existing live-fire facilities will no longer be adequate for the training and certification of military and law enforcement personnel. Constraints on training in many live-fire shoot house facilities are already in place, with some allowing only single round impact during training. With no existing constitutive model for the cellular concrete commonly used in these facilities, it is not currently possible to analyze existing facilities or design new facilities against the most recent generation of ammunition currently being fielded. This project utilizes unconfined compression, uniaxial tension, triaxial confinement, and uniaxial strain from the US Army Corps of Engineers Engineer Research and Development Center and Sandia National Laboratory to characterize cellular concrete using a Holmquist-Johnson-Cook Concrete model for use in numerical simulations. This model is then initially validated using data from existing single projectile impact experiments against a similar material, showing results with reasonable accuracy. Additional experiments to fully validate the proposed model are discussed.

This model provides the facility owner a potential tool to validate the safety of their facility against new projectiles and provides the designer of new facilities a tool for optimizing future configurations using these materials.
Elastic-Viscoplastic Mechanics of Lithium in a Standard Dry Room
Authors: Dienemann Lara L. , Saigal Anil , Zimmerman Michael A.
Published: February 2021

In electrochemical-mechanical modeling of solid-state batteries, there is a lack of understanding of the mechanical parameters and mode of deformation of lithium metal. Understanding these characteristics is crucial for predicting the propagation of lithium dendrites through the electrolyte — a key element of battery safety. Past theories have assumed linear elastic as well as elastic-plastic deformation of lithium. However, recent experiments show that the primary mode of deformation is creep. This study replicates the temperature dependent mechanical experiments but inside an industrial dry room, where battery cells are manufactured at high volume. Furthermore, this work conducts time dependent studies — also inside the dry room — to gain insight of the large deformation theories of lithium metal. The results confirm the activation energy, which dictates the creep mechanism, is correlated to core diffusion rather than lattice diffusion.
Predicting the Combustion Phasing of a Natural Gas Spark Ignition Engine Using the K-Nearest Neighbors Algorithm
Authors: Liu Jinlong , Ulishney Christopher , Dumitrescu Cosmin E.
Published: February 2021

Location of the peak cylinder pressure and the crank angle associated with half of the energy releases during the combustion process are generally used to define the engine combustion phasing and control the engine efficiency. To accelerate the optimization of a natural gas spark ignition internal combustion engine, this study proposes a black box modeling approach that will reduce the experimental or computational time needed to estimate the high efficient operating conditions at a particular engine speed and load via combustion phasing information. Specifically, a k-nearest neighbors (KNN) algorithm applied key engine operating variables such as the spark timing, air-fuel ratio, and engine speed as inputs to predict combustion phasing parameters such as the crank angles associated with peak cylinder pressure and 50% energy release. After training the correlative model, the selected engine variables produced acceptable errors for most operating conditions investigated. The results showed that the KNN algorithm predicted much better the location of the peak pressure than the location of the 50% energy release, as evidenced by the larger R2 values and smaller prediction errors. In addition, the regression model built in this study produced larger errors in the sparse-distributed region. Therefore, a more uniformly distributed training dataset is suggested for KNN algorithm, at least for the situations investigated in this research.
Demonstrating the Generation of Bond Graphs From 3D Assemblies
Authors: Alicchio Corey J. , Vitiello Justin S. , Radhakrishnan Pradeep
Published: February 2021

The bond graph method provides a generic and simple way to compute differential equations and dynamic responses for complex mechatronic systems. This paper will illustrate the process of automatically generating bond graphs from 3D CAD assemblies of gear-trains. Using appropriate CAD application programming interfaces (APIs), information on parts and mates within an existing assembly is extracted. The extracted information is stored as an identity graph, which also stores all geometry and mass related information of every part. Grammar rules are then used to transform the identity graph to a system graph, which is then converted to bond graph using an existing bond graph generation program. The paper will discuss the process, challenges and planned future work.
Radial Wall Jet Flow Over Sigmoidal Surfaces
Authors: Pease Leonard F. , Minette Michael J. , Bamberger Judith Ann
Published: February 2021

Radial wall jet flows across flat smooth surfaces have been studied for decades. These studies show that the radial velocity of these jets decays inversely with distance from the nozzle with modest contribution from friction (Poreh, et al., 1967; Rajaratnam, 1976). However, the extent to which flat surface results apply to curved surfaces remains unclear. In this paper we explore the influence of settled particle bed slope on radial wall jet velocity profiles. Jet flows over particle beds often introduce curvature in the particle bed profile, but the influence of the developed curvature on the velocity profile has not been explored. We model the step change in thickness as a sigmoidal curve of variable steepness and use conservation of momentum to evaluate the velocity profile for steady fixed beds. We find that surface curvature has a significant influence on the velocity decay coefficients, provided there is a slip velocity in the vicinity of the particle bed interface, which is strictly true for particle surfaces. We show that the velocity profile attenuates because of curvature. Indeed, conservation of momentum predicts conditions where the forward momentum of the flow is directed completely upward. The solution identifies two new dimensionless groups that determine whether a curved surface is sufficient to block radial flow and force flow vertically.
A Comparison of Probabilistic-Monte Carlo and Fuzzy-Monte Carlo Simulation Approaches for Dynamic Fault Tree: Case of Renewable Power Systems
Authors: Asghari Jafar , Pourgol Mohammad Mohammad
Published: February 2021

Conventional Fault Tree Analysis (FTA) suffers from a variety of shortcomings which must be considered in critical analysis. The main disadvantage of FTA is its inability to model the dynamic failure behaviors of the components. Accordingly, Dynamic Fault Tree Analysis (DFTA) has been proposed to overcome such limitation. In this study, first, Monte Carlo simulation (MSC) approach is used to handle internal calculations of dynamic gates. The second main weakness of common FTA is about handling the different types of uncertainties. Hence, in the second step of this study, a combined of fuzzy numbers and MCS has been proposed to overcome the limitation of FTA in dealing with uncertainties. The main purpose of this paper is a comparative study on differences between MCS and Fuzzy-Monte Carlo simulation (FMCS) approaches for solving DFTA of a typical mechanical system. From available literatures, our proposed approaches have been demonstrated on different renewable energy systems, as case studies, and results are discussed. A comparison between MCS and FMCS shows that the results of FMCS method are reasonable and more realistic. Finally, in the last section, conclusions and some of the future wok are proposed.
Crashworthiness Optimization Based on the Probability of Traumatic Brain Injury Accounting for Simulation Noise and Impact Conditions
Authors: Ahmadisoleymani Seyed Saeed , Missoum Samy
Published: February 2021

Finite element-based crashworthiness optimization is nowadays extensively used to improve the safety of vehicles. However, the responses of a crash simulation are notoriously noisy. In addition, the actual or simulated responses during a crash can be highly sensitive to uncertainties. These uncertainties appear in various forms such as uncontrollable random parameters (e.g., impact conditions).

To address these challenges, an optimization algorithm based on a Stochastic Kriging (SK) and an Augmented Expected Improvement (AEI) infill criterion is proposed. A SK enables the approximation of a response while accounting for the noise-induced aleatory variance. In addition, SK has the advantage of reducing the dimensionality of the problem by implicitly accounting for the influence of random parameters and their contribution to the overall aleatory variance. In the proposed algorithm, the aleatory variance is initially estimated through direct sampling and subsequently approximated by a regression kriging. This aleatory variance approximation, which is refined adaptively, is used for the computation of the infill criterion and probabilistic constraints.

The algorithm is implemented on a crashworthiness optimization problem that involves a sled and dummy models subjected to an acceleration pulse. The sled model includes components of a vehicle occupant restraint system such as an airbag, seatbelt, and steering column. In all problems considered, the objective function is the probability of traumatic brain injury, which is computed through the Brain Injury Criterion (BrIC) and a logistic injury risk model. In some cases, probabilistic constraints corresponding to other types of bodily injuries such as thoracic injury are added to the optimization problem. The design variables correspond to the properties of the occupant restraint system (e.g., loading curve that dictates the airbag vent area versus pressure). In addition to the inherent simulation noise, uncertainties in the loading conditions are introduced in the form of a random scaling factor of the acceleration pulse.
Developing an Efficient Approach for Unmanned Aerial Vehicle Reliability Analysis
Authors: Khayyati Ahmad , Pourgol-Mohammad Mohammad
Published: February 2021

Unmanned Aerial Vehicles (UAV) are increasingly get popularity in many applications. Their operation requires high level of safety and reliability to accomplish successful missions. In this study, the reliability was comparatively analyzed by different available approaches to select the efficient method. First, failure model of the system is developed. Then, three different scenarios are considered to study the effect of redundancies on the system reliability results. In the first scenario, there is no redundancy where in the second scenario there is only one redundant component and in the third scenario, there are three redundant components. Static reliability analysis such as Fault Tree Analysis (FTA), Reliability Block Diagram (RBD), Markov Chain (MC), and Bayesian Networks (BN) are applied on proposed scenarios and results are obtained. Regarding to time dependencies between redundant components, a dynamic-based methodology is also developed in this study through applying Dynamic Fault Tree (DFT) analysis. Proposed static and dynamic approaches are applied on an UAV as a case study and results are discussed. Finally, characteristics of each methodology and related conditions are clarified for selecting the efficient reliability analysis approach.
Numerical Study of the Percussive Riveting Process: Simulation Results
Authors: Krovvidi Sai C. , Ramulu M. , Reinhall Per G.
Published: February 2021

Percussive riveting is a widely used assembly method in the aerospace industry. The joints produced using this technique have consistently high fatigue strength. It is a manual assembly technique but automation has been introduced in certain instances on the work floor to assist assembly workers. In this paper, study was set up to analyze the effect of important geometric parameters on the residual stress and strain distributions within the riveting stackup.

In the current paper, a realistic set of boundary conditions have been adopted with both movable riveting die and movable bucking bar in an axisymmetric thermomechanical model that has a countersunk rivet.

The knowledge of this evolution is important to gain understanding of the differences between quasi-static squeeze riveting process and the percussive riveting process. The distribution of residual strains and stresses play an important role in influencing the fatigue strength of the assembled joined. Most if not all of the percussive research till date is focused on the process automation advances but enough work has not been done to understand the properties of the assembled joint using the percussive technique.

The percussive results will be compared with quasi-static squeeze process results. Strain rate effects and thermal effects are negligible in the quasi-static process while these effects are present in the percussive process. So, the results and observations from quasi-static DOE will be used as a benchmark against which the percussive DOE results will be compared. The Johnson-Cook material model has been used for describing the flow stress of the alloys used in the percussive process.
A Machine Learning Based Approach for Energy Consumption Forecasting in K-12 Schools
Authors: Doiphode Ganesh , Najafi Hamidreza
Published: February 2021

Energy costs are the second highest operational expense for K-12 schools in the United States. Improving energy efficiency and moving towards sustainable school buildings not only result in substantial cost savings and reduction of environmental emissions, but also provides an opportunity to enhance students’ awareness regarding energy, environment, and sustainability. Effective tools and techniques that provide thorough understanding of energy consumption in school buildings are valuable to school districts by helping them with prioritizing energy efficiency projects. In the present paper, a multi-layer perceptron (MLP) neural network model is developed for estimating monthly energy consumption of K-12 schools in Brevard County, Florida. The inputs to the network are considered as number of occupants, days of operation per months, building’s area, average monthly outdoor dry-bulb temperature and relative humidity, as well as the month’s number and the output from the network is monthly energy consumption. Various network topologies are considered and tested to achieve the optimal configuration for the network. The selected network is successfully trained using three years of energy consumption data for 25 schools in Brevard County, FL (high schools, middle schools, and elementary schools). The results showed that the developed neural network model is capable of accurate estimation of monthly energy consumption of schools. The network tested and validated using the data from schools which were not included in the training dataset and the errors between the known values and estimated values for monthly energy consumptions are evaluated and discussed. Although the current study covers one particular school district (Brevard county) in a given climate zone (2a-hot and humid), the developed approach can be extended to incorporate various climate zones and serve as an effective tool for school energy conservation managers. The end user may obtain a clear idea of the energy consumption of the school building and how it compares against other buildings within the same category and climate zone, with minimum input data required.
A Multi-Fidelity Approach for the Reliability Assessment of Shell and Tube Heat Exchangers
Authors: Pidaparthi Bharath , Missoum Samy , Li Peiwen
Published: February 2021

The objective of this paper is to efficiently perform the reliability assessment of shell and tube heat exchangers. Although inexpensive empirical/analytical heat exchanger models exist and could be used for brute force Monte-Carlo simulations (MCS) based reliability analysis, they typically do not characterize the shell side flow accurately. Hence, higher fidelity models are often needed for predicting the shell and tube heat exchanger performance with a desired level of accuracy. These higher fidelity models are generally associated with higher computational costs, making them impractical for MCS-based reliability analysis. To circumvent this problem, a multi-fidelity technique leveraging the lower and higher fidelity models is proposed to locally construct the failure boundaries using support vector machines (SVM). For this purpose, an adaptive sampling scheme, which explores the regions of inconsistency between failure boundaries from lower and higher fidelity models, is developed.
Reverse Electrowetting-on-Dielectric Energy Harvesting Integrated With Charge Amplifier and Rectifier for Self-Powered Motion Sensors
Authors: Adhikari Pashupati R. , Tasneem Nishat T. , Biswas Dipon K. , Reid Russell C. , Mahbub Ifana
Published: February 2021

This paper presents a reverse electrowetting-on-dielectric (REWOD) energy harvester integrated with rectifier, boost converter, and charge amplifier that is, without bias voltage, capable of powering wearable sensors for monitoring human health in real-time. REWOD has been demonstrated to effectively generate electrical current at a low frequency range (< 3 Hz), which is the frequency range for various human activities such as walking, running, etc. However, the current generated from the REWOD without external bias source is insufficient to power such motion sensors. In this work, to eventually implement a fully self-powered motion sensor, we demonstrate a novel bias-free REWOD AC generation and then rectify, boost, and amplify the signal using commercial components. The unconditioned REWOD output of 95–240 mV AC is generated using a 50 μL droplet of 0.5M NaCl electrolyte and 2.5 mm of electrode displacement from an oscillation frequency range of 1–3 Hz. A seven-stage rectifier using Schottky diodes having a forward voltage drop of 135–240 mV and a forward current of 1 mA converts the generated AC signal to DC voltage. ∼3 V DC is measured at the boost converter output, proving the system could function as a self-powered motion sensor. Additionally, a linear relationship of output DC voltage with respect to frequency and displacement demonstrates the potential of this REWOD energy harvester to function as a self-powered wearable motion sensor.
Optimization of Cu(In,Ga)Se2 Solar Cell and its Comparative Performance Analysis for Employing Different Buffer and Window Layers Through Numerical Simulation and Analysis Using SCAPS-1D
Authors: Zulkarnain Meah Imtiaz , Islam Nazmul
Published: February 2021

In this research, a numerical simulation and analysis of the second generation thin film solar cell Copper Indium Gallium diselenide, Cu(In,Ga)Se2 or, CIGS, is conducted in order to optimize its performance and compare among the cells using different materials for buffer and window layers. The one-dimensional solar cell simulation program SCAPS-1D (Solar Cell Capacitance Simulator) is used for the simulation and analysis purpose. The effects of variation of bandgap, concentration and thickness of the p-type CIGS absorber layer on the efficiency of CIGS solar cell are investigated. The change in CIGS solar cell efficiency with change in temperature is studied, too. Two different buffer layers namely CdS and In2S3 are considered for the simulation of the CIGS solar cell. The thickness of the buffer layer, its bandgap and concentration are taken into consideration for optimization. As for the window layer, ZnO and SnO2 are employed for the numerical simulation. The thickness of the window layer is varied and its effect on the efficiency of the solar cell is investigated. The open-circuit voltage, short-circuit current density, fill factor and quantum efficiency of the CIGS solar cell are observed from the SCAPS simulation besides the solar cell efficiency. A comparison among the different CIGS cell structures employing different buffer layers and window layers is performed in terms of efficiency and other essential parameters as mentioned above. The solar cell performances of the structures explored in this work were also put in comparison against some laboratory research cell output. The simulation result shows a possible better performance for all the simulated CIGS cell structures compared to the experimental results. In2S3 appears to increase efficiency and thus poses a great potential for non-toxic CIGS solar cell. Though CIGS absorber layer requires more thickness for desired output, successful application of much thinner SnO2 replacing ZnO buffer layer paves the way to less thicker CIGS thin film solar cell.
Shape Memory Polymer Foam With Tunable Properties for Treatment of Intracranial Aneurysm
Authors: Pineda-Castillo Sergio A. , Luo Jishan , Bohnstedt Bradley N. , Lee Chung-Hao , Liu Yingtao
Published: February 2021

Intracranial aneurysms have the potential to be fatal; when detected, they must be treated promptly by surgical clipping or by endovascular methods. The latter, while having better long-term overall survival than the former, fail to provide complete occlusion of the aneurysm lumen, creating risks for therapy-related adverse events, such as embolic device migration or recanalization. Polyurethane shape memory polymers (SMPs) have the potential to provide patient-specific treatment to reduce rates of incomplete occlusion and mass effect. In this study, SMP matrices are infiltrated with carbon nanotubes (CNTs) to induce electrical conductivity and provide a precise triggering method for deployment of the embolic device. Through thermomechanical characterization of the composite, it was determined that CNTs play a significant role in resistivity of the SMP foam and its ultimate shape recovery properties. Cyclic mechanical testing allowed to determine that CNTs might induce polymeric matrix damage, creating the need for new approaches to CNT infiltration. The studied composite foams were able to occlude an in vitro idealized aneurysm phantom model, which allowed to conclude that the proposed CNT-infiltrated SMP foams exhibit potential as biomedical devices for endovascular therapy of intracranial aneurysms.
Defect Detection in Additively Manufactured Metal Parts Using In-Situ Steady-State Ultrasonic Response Data
Authors: Jacobson Erica M. , Cummings Ian T. , Fickenwirth Peter H. , Flynn Eric B. , Wachtor Adam J.
Published: February 2021

The increasing implementation of additively manufactured parts into safety-critical applications is accelerating the demand for non-destructive evaluation as a means of quality control for defect detection during the build process. Identification of a critical defect in the part before its completion can enable early termination of the build, resulting in both reduced material costs and machine time. Additionally, current post-build inspection techniques have limited resolution capability as the size of the manufactured part increases.

An adaptation of Acoustic Wavenumber Spectroscopy technology was implemented into a laser powder bed fusion machine to perform in-situ direct-part measurements and provide a three-dimensional inspection volume of the entire build. The processing of data for each layer is quick enough to be performed during the lasing of the subsequent layer, enabling the potential for early termination of the build when critical defects are identified.

Various processing techniques were used to detect changes in the steady-state ultrasonic response that indicate different defect types. The data analyses used to identify regions of defects based on the response data are presented. This work ultimately demonstrates a practical means for in-situ monitoring of additive manufacturing parts to ensure quality control for safety-critical applications.
Design of Robotic Manipulator to Hollow Out Zucchini
Authors: Alkhatib Rami , El Bobo Tarek , Swaidan Afif , Al Soussi Jad , Diab Mohamad O. , Khaled Nassim
Published: February 2021

Robotics entered the food industry starting from packaging to cooking. Zucchini is an important dish in the Middle Eastern kitchen. The eventual challenge of hollowing out Zucchini is to avoid poking its bottom with the corer. This paper introduces a novel robotic mechanism for hollowing out zucchini tasks precisely and efficiently. The mobility of the robot arm ensured a smooth hollowing while the corer is put in motion. Moreover, frames are assigned to the tip of the corer, holder, zucchini and camera to avoid stabbing the zucchini bottom. Accordingly, the special Euclidean group of the homogenous transformation matrices derived between different links are discussed in the context of their properties. The kinematic analysis is based on Mozzi-Chasles’ theorem rather than using the traditional Denavit Hartenberg convention for better task-oriented planning of hollowing out zucchini mechanism. Results indicate a promising mechanism that is well designed, simple and easy to build, maintained and most importantly to perform the required task. This paper forms an important block in building the whole automated system to hollow out Zucchini.
Advanced Control Techniques for Semi-Active Suspension Systems
Authors: Maradey Lazaro Jessica Gissella , Cáceres Mojica Kevin Sebastián , Navarro Quintero Silvia Juliana
Published: February 2021

Semiactive suspension system provides comfort and precise support for any type of driving in vehicles. Their main feature consists in the modification of the damping coefficient by applying an external control. Commonly, these suspensions work with non-linear dampers, such as magnetorheological, electrorheological, pneumatic, dry friction, among others; which generate a discontinuous behavior of force, causing an annoying noise known as “chattering”; however, this can be deleted by the correct application of the control technique. So, control strategy selection is a key task in the modeling of dynamic behavior and to describe the variation of characteristics, as well as to achieve the best vehicle’s driving experience in terms of comfort, performance, reliability, stability, and safety.

This article shows three advanced control techniques used to design a semi-active vehicle suspension taking the quarter car as the model. From the review of the state of the art, relevant works and authors on the subject are reported. After, the application of the control techniques is shown together with the results obtained, specially, the performance of the system is carried out by means of computer simulations in the Matlab/Simulink virtual environment, accompanied by near-reality disturbances to verify the effectiveness of this study.
Ethanol Mechanism Reduction Based on DRGEPSA Method at Various Operating Ranges
Authors: Roy Shrabanti , Askari Omid
Published: February 2021

Reducing the size of a detail chemical kinetic is necessary in the prospect of numerical computation. In this work a skeleton reduction is done on a detail mechanism of ethanol. The detailed ethanol mechanism used here is developed through reaction mechanism generator (RMG). The generated mechanism is validated at wide range of engine relevant operating conditions using laminar burning speed (LBS), ignition delay time (IDT) and species mole fraction calculation at different reactor conditions. This detail mechanism consists of 67 species and 1031 reactions. Though the mechanism is in a very good agreement at various operating ranges with experimental data, it is costly to use a detail mechanism for 3D computational fluid dynamics (CFD) analysis. To make the mechanism applicable for CFD simulation further reduction of species and reactions is essential. In this work a skeleton mechanism is generated using directed relation graph technique with error propagation and sensitivity analysis (DRGEPSA). The DRGEPSA method, works based on error calculation at user defined condition. This technique is a combination of two methods, directed relation graph with error propagation (DRGEP) and directed relation graph with sensitivity analysis (DRGASA). To ensure the wide range of applicability of the skeleton mechanism, IDT is calculated at temperature, pressure, and equivalence ratio ranges from 700–2000 K, 1–40 atm and 0.6–1.4 respectively. A 10% error estimation is considered during the process. Initially DRGEP is applied on the detail mechanism to eliminate unimportant species. Further, sensitivity analysis helps to identify and reduce more unimportant species from the mechanism. Reactions related to the deleted species are automatically removed from the mechanism in each step. The final skeleton mechanism has 42 species and 464 reactions. This skeleton mechanism is validated and compared with different IDT data for the conditions not used in reduction technique. Results of LBS and different species concentration from reactor conditions is considered for validation. The skeleton mechanism can reduce computational time by 35% for LBS and 25% for IDT calculation. For future work, this skeleton mechanism will be considered in optimum reduction process.
On the Modulation of Origami Phononic Structure for Adaptive Wave Transmission in Brillouin Zone
Authors: Hathcock Megan , Popa Bogdan-Ioan , Wang K. W.
Published: February 2021

Recently the presence of a Dirac cone within the band structure of graphene has inspired research on phononic crystals with Dirac-like behaviors — including structures mimicking zero refractive index materials. The interesting phenomena produced by these structures occur at fixed frequencies and cannot be adaptive to needs and environmental changes. To address this constraint, researchers have designed tunable phononic structures; however, the tunable frequency ranges from the studies reported to date are limited by geometric constraints. Using a reconfigurable origami structure to modulate between different classes of phononic Bravais lattices, this research numerically investigates the effects of phononic lattice perturbation to produce drastic changes in the frequency of useful accidental degeneracies.
Vibration Isolation Using Continuous Beams
Authors: Rai George , Rahn Christopher D. , Smith Edward , Marr Conor
Published: February 2021

Vibration Isolation involves an inertially coupled system with a mass-lever combination where the inertial forces cancel spring induced forces, thus permitting a high degree of isolation at a relatively low frequency in discrete dynamic systems. This paper shows that the lever combination can be clamped at the root rather than pinned and modeled as a continuous dynamic system. It is theoretically proven that this model can be tuned to achieve isolation with zero displacement, force, and moment transmissibility. The frequency response is calculated based on Euler Bernoulli assumptions for a beam with a tip mass under point force loading. A tip mass equivalent to the mass of the beam can reduce the first isolation frequency by 71% for shear at the root, 72% for moment at the root, and 64% for tip displacement, relative to a cantilever without a tip mass.
IV Cutoff Mechanism for Low Resource Settings
Authors: Brehm Samuel , Adams Hunter , Damaraju Aneel
Published: February 2021

Intravenous (IV) fluid regulation is necessary in developing nations to prevent IV-overhydration in the pediatric patients of low-resource hospitals. Traditionally, regulation is achieved by calculating the total fluid outflow from an IV bag and restricting flow before the patient is injected with dangerous levels of fluid. However, standard fluid regulation devices include infusion pumps and burettes, which are costly and often ill-suited for low-resource environments. This research proposes a low-cost, easy to use device that regulates the volume of intravenous (IV) fluid delivered to a patient in a low-resource clinical setting. Laboratory accuracy tests (N = 32) over a range of clinically-relevant fluid volumes yielded a median and max error of 4 and 8mL respectively, falling within specific error thresholds (p < le-5). Non-clinical usability tests (N = 25) showed median and max device setup times to be 40 and 55 seconds respectively (p < le-5). Additionally, all participants found the device “easy to use” and were able to set up and use the device with less than 20 minutes of training.
An Optimized Statistical Model for Predicting Composite Modulus of Elasticity
Authors: Hage Ilige S. , Hage Re-Mi , Ghnatios Chady , Baydoun Ahmad M. R. , Hamade Ramsey F.
Published: February 2021

Composites are the revolutionary materials that were developed for the ease of the technology. Similar to all families of materials, composites are being extensively studied nowadays. One of the composites ‘main studies is the homogenization study to determine composites modulus of elasticity function of multiple variables based on differentiating several inclusions’ geometries, or quantities or orientations. However, homogenization studies require extensive numerical and analytical work. This work uses a statistical optimized tool TSREG (tabu search combined with statistical regression proven to achieve models with the highest R-squared and lowest p-values for each variable in addition to the lowest MAPE (mean absolute percentage error)) to predict a model relating composite modulus of elasticity to inclusions shape (as aspect ratio), volume fraction, and orientation (0-30-60-90°). Experimental data of modulus of elasticity compressed 3D printed ABS plastics cubes of 16 × 16 × 16 mm3 size having one inclusion (as empty spheres or ellipsoids with zero Young’s modulus) were utilized. For the voids, their geometries were varied to cover spherical and elliptical shapes with several aspect ratios (0.2-0.4-0.65-0.75-0.9-1), volume fractions (0-0.1-0.2-0.3-0.35-0.4-0.5-1), and orientations (0-30-60-90°). This model helps researchers to determine the composite modulus of elasticity using one significant and accurate expression without using numerical analysis.
Design, Modelling and Simulation of a Rotational Robotic Arm
Authors: Wei Bin
Published: February 2021

In this paper, a rotational robotic arm is designed, modelled and optimized. The 3D model design and optimization are conducted by using SolidWorks. Forward kinematics are derived so as to determine the position vector of the end effector with respect to the base, and subsequently being able to calculate the angular velocity and torque of each joint. For the goal positioning problem, the PD control law is typically used in industry. It is employed in this application by using virtual torsional springs and frictions to generate the torques and to keep the system stable.
Numerical Analysis of Depth and Sizing in Skin Cancer Lesions
Authors: Regla-Felix J. Eliseo B. , Hernandez-Guerrero Abel , Luviano-Ortiz J. Luis , Moreno-Torres Tomas
Published: February 2021

Melanoma is one of the most common types of skin cancer that afflicts our society. Although melanoma accounts for 1% of the cases of skin cancer, due to its aggressiveness, it is responsible for most skin cancer-related deaths. Each year, approximately 132 000 new cases of melanoma are diagnosed worldwide, according to the World Health Organization, and just in USA an approximate of 7 230 people will die because of it. Early detection can lead to a significant reduction in melanoma death rates.

Nowadays, there are various invasive and non-invasive detection methods of skin cancer. A type of non-invasive method uses an infrared thermal imaging camera, which can detect the difference in thermal behavior between healthy and malignant tissue during the thermal recovery process after a cooling stress applied to the skin. Such a thermal behavior can be simulated computationally, with a good approximation to reported case studies. This study proposes a numerical model that takes advantage of infrared thermal imaging to determine the effect of geometry and depth of the lesion with the cooling and recovery process using Design of Experiments (DoE). The results show that diameter and geometric shape of the lesion are the parameters that most influence the thermal response.
Reactive Online Motion Re-Planning for Crash Mitigation in Autonomous Vehicles Using Bezier Curve Optimization
Authors: Khattar Vanshaj , Eskandarian Azim
Published: February 2021

Crash avoidance and mitigation is still one of the major challenges faced by the autonomous vehicles industry. Path planning in autonomous vehicles is a crucial phase during crash avoidance with other vehicles. It is important for the path planning algorithm to be reactive in uncertain situations which usually arise in urban road scenarios. This study proposes a reactive online path planning strategy for obstacle avoidance and crash mitigation for an imminent collision with another vehicle. A cubic Bezier curve trajectory generation method is used for creating a maneuver around the obstacle vehicle. Relative hitting heading angle is considered to account for the crash severity between two vehicles. Two cases are considered where one is an imminent crash scenario and the other is where an obstacle can be avoided with a minimum safety distance. This obstacle avoidance problem is then converted to an optimization problem where potential crash severity, vehicle kinematic constraints and path smoothness are considered as constraints. The resulting cost function consists of a quadratic convex function and a piecewise defined function. This is further solved using a novel methodology where the piecewise function is included in the inequality constraints, so that the problem can be solved using quadratic programming method. This will also lead to a quick real time implementation. It is shown that the proposed method is able to avoid collisions and also minimizes the crash severity in case of an imminent collision.
Deep 3D Convolution Neural Network Methods for Brain White Matter Hybrid Computational Simulations
Authors: Wu Xuehai , Pelegri Assimina A.
Published: February 2021

Material properties of brain white matter (BWM) show high anisotropy due to the complicated internal three-dimensional microstructure and variant interaction between heterogeneous brain-tissue (axon, myelin, and glia). From our previous study, finite element methods were used to merge micro-scale Representative Volume Elements (RVE) with orthotropic frequency domain viscoelasticity to an integral macro-scale BWM. Quantification of the micro-scale RVE with anisotropic frequency domain viscoelasticity is the core challenge in this study.

The RVE behavior is expressed by a viscoelastic constitutive material model, in which the frequency-related viscoelastic properties are imparted as storage modulus and loss modulus for the composite comprised of axonal fibers and extracellular glia. Using finite elements to build RVEs with anisotropic frequency domain viscoelastic material properties is computationally very consuming and resource-draining. Additionally, it is very challenging to build every single RVE using finite elements since the architecture of each RVE is arbitrary in an infinite data set. The architecture information encoded in the voxelized location is employed as input data and is consequently incorporated into a deep 3D convolution neural network (CNN) model that cross-references the RVEs’ material properties (output data). The output data (RVEs’ material properties) is calculated in parallel using an in-house developed finite element method, which models RVE samples of axon-myelin-glia composites. This novel combination of the CNN-RVE method achieved a dramatic reduction in the computation time compared with directly using finite element methods currently present in the literature.
Two-step growth of β-Ga2O3 films on (100) diamond via low pressure chemical vapor deposition
Authors: Karim Md Rezaul , Chen Zhaoying , Feng Zixuan , Huang Hsien-Lien , Johnson Jared M. , Tadjer Marko J. , Hwang Jinwoo , Zhao Hongping
Published: February 2021

One of the major challenges in β-Ga2O3-based high power and high frequency devices is anticipated to be related to the low thermal conductivity of the material which is on the order of 10–30 W/m K. The use of diamond (thermal conductivity ∼2000 W/m K) as a substrate can be one effective approach for achieving better thermal management in β-Ga2O3-based devices. In this work, low pressure chemical vapor deposition was used to grow β-Ga2O3 films on (100) oriented, single-crystalline diamond substrates. A two-step growth technique was employed to avoid the oxidation of the diamond surface at high temperatures. From x-ray diffraction measurements, the β-Ga2O3 films grew along the ⟨−201⟩ crystalline axis with the β-Ga2O3 (002) planes rotated by ±24.3–27° with respect to the diamond (111) planes. High-magnification scanning transmission electron microscopy imaging revealed an abrupt β-Ga2O3/diamond interface without any voids which is essential for the high rate of heat transfer across the interface. N-type electrical conductivity was measured in a Si-doped β-Ga2O3 film with 1.4 × 1019 cm−3 electron concentration and ∼3 cm2/V s electron mobility. This work demonstrates the feasibility of heteroepitaxy of β-Ga2O3 films on diamond substrates for potential device design and device fabrication with efficient thermal management.