bluuebunny/crossref_metadata_2025 huggingface dataset:
The Effect of Membrane Topology on Separation Performance of Vacuum Membrane Distillation Module
Authors: Caspar Justin , Xue Guanyang , Krysko Robert , Oztekin Alparslan
Published: January 2022

2D Large Eddy Simulations (LES) were conducted to study the effect of channel geometry on the Vacuum Membrane Distillation process. The geometry was altered by imposing a sinusoidal (“wiggly”) wall profile. The results of the study show at a critical Reynolds number between 750 and 1,000, transient vortices appear in the channel. As the Reynolds number is increased from 1,000 to 1,500, the origin of the vortices moves further upstream, and the frequency and intensity of the vortex activity increase. Areas, where vortex shedding provides mixing, serve to enhance the performance of membrane distillation profoundly. The mixing reduces temperature and concentration polarization along the membrane surface. With better mixing provide at Reynolds number 1,500 versus 1,000, the difference in performance versus the corresponding flat sheet membrane case is increased. The vapor flux in the wiggly channel module increases 6% at Reynolds number 1,000 and 22% at Reynolds number 1,500 compared to the flat channel module. The change in flux is from 61.6 to 65.7 kg/m2/h at Reynolds number 1,000 and 66.5 to 81.4 kg/m2/h at Reynolds number 1,500. Temperature polarization was also mitigated at Reynolds number 1,500 even though the flux was increased.
A Comparative Analysis of Object Detection Algorithms in Naturalistic Driving Videos
Authors: Zhang Ce , Eskandarian Azim
Published: January 2022

Intelligent vehicle research has been rapidly developing. Object detection is one of the most critical study areas for intelligent vehicle’s driving safety. This paper conducts a comparative analysis for two popular real-time object detection algorithms: Yolo-v4 and deconvolutional single shot multibox detector (DSSD) under a naturalistic driving environment. An 80-classes COCO dataset trains each neural network at first, then fine-tuned by the BDD100k dataset. The detection results are compared by True/False Positive Results, Precision-Recall Curve, and average precision @ intersection of union 50 and average precision @ intersection of union 75 results. According to the analysis results, the Yolo-v4 outperforms the DSSD algorithm in bad weather, nighttime conditions, and small object detections. The Yolo-v4 and DSSD mean average precision for the BDD dataset is 22.63 and 11.86, respectively. The Yolo-v4 precision is 90.81% better than the DSSD algorithm, proving that the Yolo-v4 is a better fit for real-world driving environment studies.
A Parametric Study: Influence of Geometry and Material Properties on the Response of the Femoral Head Through Biofluid
Authors: Paliwal Manish
Published: January 2022

Friction-induced stick-slip phenomenon has been reported in 1–20% of patients with ceramic-on-ceramic total hip replacement. The friction behavior of the bearing surfaces is ruled by the lubrication conditions, which may be from hydrodynamic lubrication to mixed or boundary lubrication. In the latter two situations, surface-to-surface mechanical contact may give rise to the friction-induced stick-slip phenomenon. Essentially, stick-slip occurs when the film lubrication is broken. Stick-slip is an undesired phenomenon and is understood to give rise to the squeaking phenomenon in the hip bearing surfaces. In this study, the influence of the relative densities of biofluid, size, mass, and femoral head material is investigated to study the system’s response and the approach of the femoral head towards the acetabulum shell (initial contact to pre-swing phase). Two configurations were developed, which included ball-on-plane and ballon socket configurations. Utilizing parametric studies, the role of these variables was studied. Higher velocity-derived energy may contribute to the vibration of the system via stick-slip. High approach velocity combined with high-density material may influence and lead to surface-surface articulation.
Correlation Between Process Parameters and Fracture Property of 316L Stainless Steel Parts Fabricated by Selective Laser Melting
Authors: Jin Jianhang , Xie Zhuowen , Yang Guanghui , Jiang Wei
Published: January 2022

Compact tension (CT) specimens of 316L stainless steel (SS) were fabricated by selective laser melting (SLM) technology using different combination of process parameters, including laser power, scanning speed, layer thickness and scanning strategy. The correlation between these process parameters and fracture property was investigated by Taguchi experiment. Crack opening displacement (COD) of the specimens were measured by digital image correlation (DIC) method. Through the analysis of range (ANOR) and analysis of variance (ANOVA), the influence of process parameters on the fracture property of pre-cracked CT specimens was found in the order of laser power, layer thickness, scanning strategy and scanning speed. The load increases gradually under the same COD value with the increase of laser power, and with the reduction of scanning speed and layer thickness. Within the selected range of parameters, the fracture property was optimal at the process parameters with a laser power of 200W, a scanning speed of 500mm/s, a layer thickness of 0.03mm and a parallel scanning strategy. This paper may provide guidance for process parameter selection to improve fracture property of selective laser melted parts.
Climate Change and Global Warming - The Forgotten Factors
Authors: Conkol Gary K.
Published: January 2022

The recent global pandemic has provided an unparalleled opportunity to examine and potentially calibrate our responses to Global Warming. Since 1992 there has been much debate but also vast deployment of technology from satellites to atmospheric monitoring stations to study climate change and, specifically, global warming. Copious amounts of atmospheric temperature and Greenhouse Gas (GHG) data have been continuously recorded. Data throughout the 2019 pandemic to present, now provide the rare opportunity to test understanding of Global Warming and resulting Climate Change.

Herein, changes in temperature and Green House Gases with respect to the time, during which global activities shut down or were significantly decreased, are used to design a multi-faceted approach to further examine our understanding and actions relative to Global Warming. A combination of perturbation and sensitivity analysis are proposed to draw attention to short and long-term efforts that have the potential to help further understand and calibrate efforts to manage Global Warming. The primary focus is to utilize changes noted during the pandemic to inform calculations and global warming predictions and actions.
The Consistency of Helicopter ‘Ground Resonance’ and the Unstable Lateral-Torsional Vibration in Standard Rotor Systems
Authors: Qian Xin , Fan Yu , Li Lin , Wang Wenjun
Published: January 2022

Ground resonance is a specific unstable vibration caused by the modal coupling between the blades and fuselage of a helicopter structural system. On the other hand, the unstable vibration in a standard rotor model can also be triggered by lateral-torsional coupling. This paper studies the consistency of instability mechanisms between the ground resonance and the lateral-torsional coupling vibration. Based on the two-dimensional equivalent model of helicopter system, the critical elements leading to the ground resonance are firstly studied by modal analysis. Comparison between the ground resonance and the lateral-torsional coupling vibration is then performed in two aspects: critical elements causing instability in dynamic matrices and modal shapes in the modal coupling ranges. Results demonstrate that the instability mechanism of the ground resonance is consistent with which of the lateral-torsional coupling vibration. The reason why similar instability does not occur in the general rotor system with elastic supports is also clarified.
Effect of Die Velocity on Tube Deformation Mechanics During Low Pressure Tube Hydroforming Process Sequence Variation
Authors: Nikhare Chetan P. , Buddi Tanya , Kotkunde Nitin , Singh Swadesh Kumar
Published: January 2022

Tube hydroforming is one of the successful manufacturing processes to create a variety of shapes using fluid pressure. The process fills the tube with fluid and pressurizes it to deform in various cross-sections. The method is categorized in three types: high pressure, pressure sequencing and low-pressure tube hydroforming. Tube hydroforming has gained popularity due to its many advantages such as part consolidation, uniform deformation, quality of the formed part and the possibility of unique shapes with indents or angles. Due to uniform thinning in the formed part, the parts can be lower weight and thus proven to be the technology to create light-weight parts for automotive and aerospace industries to increase the fuel economy. This paper focuses on low-pressure tube hydroforming. In low-pressure tube hydroforming, during the closing of the die the tube is marginally pressurized to a fixed volume. The previous study which was published in IMECE2019 and 2020 was focused on to investigate the effect of variation of thickness on deformation mechanics of the tube with variation in the process sequence during low-pressure tube hydroforming. In this part of the research, the study focused on how the velocity of the die effect the deformation mechanics with variation of the process sequence during low-pressure tube hydroforming. The circular tube was formed in a square shape. The four sides of die edges were considered as individual edges and the motion of these edges will be varied to achieve the final shape. The deformation mechanics in each condition was presented and analyzed. The die velocity effect on die filling, thickness and strain distribution were studied. It was found that the die velocity effects the tube deformation for the thinner tube and buckling could be eliminated using low pressure with tight die filling.
UGV Localization With AI-Assisted EKF for Multi-Terrain Environments
Authors: Shaukat Salman Ali , Althani Thani , Anzil Mohammed Minhas , Ismail Hesham
Published: January 2022

Localization of Unmanned Ground Vehicle (UGV) in multi-terrain environments, specifically soft terrain, is challenging. High slip scenarios make localization a difficult task. The internal sensors of the UGV are highly dependent on the terrain structure and are prone to errors. Thus, an appropriate measure should be in place to address the mentioned challenges to achieve precise navigation of the UGV. To address this issue, we propose using the GNSS-RTK/IMU/odometer/optical flow-based EKF system to improve state estimation of the UGV and compare it with some legacy approaches. The ground-facing camera will be integrated with image processing techniques such as optical flow to get linear and angular velocities. Additionally, a convolutional neural network (CNN) is used to classify the terrain conditions and update the covariance matrices for the odometer in EKF accordingly.
Nonlinear Vibrations of Beams With Bilinear Hysteresis at Supports: Interpretation of Experimental Results
Authors: Balasubramanian Prabakaran , Franchini Giulio , Ferrari Giovanni , Painter Brian , Karazis Kostas , Amabili Marco
Published: January 2022

Several structures of important industrial relevance feature large-amplitude vibration, which can have an initially hardening or a softening behavior. Models with quadratic and cubic nonlinear stiffness terms are often used to predict the nonlinear dynamics of such structures. If boundary conditions constitute an important cause of nonlinearity, however, it may not be possible to describe the nonlinear behavior of these systems by means of these nonlinear terms. The bundles of fuel rods immersed in the coolant flow of pressurized water reactors constitute an important example of extreme softening behavior, which is not described accurately by the simple adoption of nonlinear stiffness terms proportional to the square and to the cube of displacement in the equation of motion. In fact, the spacer grids, which support the nuclear fuel rods inside the reactors, constitute nonlinear boundary conditions, and are responsible of the peculiar softening behavior. Dedicated experiments on the rotational constraint applied by the spacer grids were performed, revealing a softening stiffness, which conforms extremely well with a bilinear model with hysteresis, such as the one formulated by Caughey. Therefore, a single degree-of-freedom equation with bilinear stiffness terms was employed to model the large-amplitude vibrations of single and bundled fuel rods immersed in quiescent water, which were detailed by previous stepped-sine experiments. A viscous dissipative term was initially retained for modelling damping, since several sources of dissipation are present for fuel rods immersed in water, besides hysteresis at the spacer grid supports. A satisfying fit of the experimental frequency- and time-domain curves was achieved through the use of an optimization algorithm for the tuning of stiffness and damping terms. Viscous damping, however, is not constant during large-amplitude vibrations, but is amplitude-dependent. Therefore, the value of the relevant parameter had to be changed at each forcing level. The model was then refined by introducing four additional switch points for stiffness, besides the initial one. Moreover, a nonlinear damping term of the quadratic type, suitable for softening structures immersed in fluids, was included. The resulting equation of motion with a five-switch piecewise linear stiffness describes with improved accuracy the experimental results. Also, one set of damping parameters is capable of describing the experimental results in the entire forcing (vibration amplitude) range. All this clarifies that a simple multilinear stiffness model, with the inclusion of quadratic damping, can be successfully employed to describe the behavior of rods immersed in fluid, in presence of nonlinear boundary conditions introduced by spacer grids.
Analyzing Core Failure in Composite Sandwich Structures Using a Non-Local Anisotropic Damage Approach
Authors: Zhuang Linqi , Najafi Ali
Published: January 2022

In this work, a non-local anisotropic damage model is used to study the failure of Balsa core in a sandwich structure under various loading conditions. The adopted anisotropic damage model was developed to account for the anisotropic elastic response and degradation of the material for typical anisotropic materials. An implicit gradient enhance formulation was also derived to avoid singularities caused by local strain softening and thus realize a mesh-independent solution. To evaluate the capability of adopted damage model, two different scenarios are considered, one is a sandwich beam with Balsa core in 4-point bending and the other is a tapered sandwich beam subjected to uniaxial tension. For both cases, mesh independency using non-local damage model is verified, damage patterns and other related findings are also summarized.
Crushable Foam-Filled Cellular Core and Discrete Bonding: A Finite Element Study of Thin-Walled Cross Tube
Authors: Jenson Sean , Ali Muhammad
Published: January 2022

Automobile chassis are constantly being redesigned to improve crashworthiness and decrease overall weight to assist in increased fuel efficiency. Typically, thin-walled axial members such as rectangular and circular tubes are employed as energy absorbers in front and side collisions. These members are designed to absorb a maximum amount of energy in a short period of time by utilizing their collapse behaviors. During collapse, these axial crush tubes undergo progressive folding which exhibits moderate and relatively constant plateau stress regions as collapse occurs. This study is a continuation of the investigation into cross-shaped crush tubes and the addition of a composite graded cellular core addition. The cross shaped tube and graded cellular core have shown to have distinct deformation modes and behaviors under axial loading conditions. Additionally, the work presented here further investigates this structure through the addition of crushable foam material within the cell voids. This foam addition along with bonding techniques of the inner core to external tube structure assist in altering the crush behavior of the tubes while increasing stability and energy absorbing capacity of the structure. Numerical simulations were conducted in ABAQUS finite element software for cross tubes under axial impact loading conditions. Four cases were considered for the present study: no bonding, 3 bonding sites, 5 bonding sites, and 7 bonding sites. These cases were matched with the previous study results to determine the effects of crushable foam addition to the graded cellular core structure. The results show that the addition of crushable foam material to the cellular core structure further increases the stability of the structure and is less susceptible to Euler type buckling. The crushable foam improved structural strength and increased overall energy absorbing capacity. The results presented are a positive indicator of the potential to tune automobile chassis energy absorbers to significantly increase energy absorbing potential and alter the behavior of these members to perform favorably under axial impact loading conditions.
Development of a Contrived Tool Wear Method in Machining
Authors: Grimm Tyler J. , Potthoff Nils , Kharat Nilesh Ashok , Mears Laine , Wiederkehr Petra
Published: January 2022

Tool wear in machining is generally observed as early and late stage tool wear. During early stage tool wear, the tool is rapidly worn during a break-in period, followed by a stable region of tool wear. After machining more material, the tool reaches late stage tool wear. At this point, tool wear becomes unstable; tool failure occurs quickly or it may take some time. Therefore, late stage tool wear represents a bifurcation point, making it difficult to predict tool wear past this point.

Tool wear is well known to be stochastically influenced. Due to this effect, it is difficult to perform studies on late stage tool wear since machining tools will be affected differently up to this point, introducing unknown variables. A novel method is presented in this research which utilized artificial wear to reach late stage tool wear. This method, termed contrived tool wear, may be capable of reducing the stochastic tool wear that occurs during early stage tool wear. As an initial investigation, machining tool inserts were worn by taking several passes over a grinding wheel with the tool rotating in reverse. Several parameters were tested in an attempt to match the natural worn state as close as possible. Subsequent to artificial wear, the inserts were used to machine IN718. The presented method of contrived wear was found to be a good approach, but could not sufficiently replicate the tool wear typically produced in IN718 machining. Future work should aim at implementing a multi-axis approach to enable grinding at various angles to the rake face of the insert.
Experimental Performance Evaluation of Fixed-Geometry Hydrodynamic Thrust Bearings With Variable Taper Depths
Authors: Fais Collier , Ali Muhammad , Yasko Isaiah , Walker Rick , Lutfullaeva Anbara
Published: January 2022

This paper presents experimental performance characteristics of fixed-geometry hydrodynamic thrust bearings machined to different helical taper depths. Theoretical analysis based on the Reynold’s equation states that under favorable conditions, these taper depths can produce and maintain load-supporting hydrodynamic pressure yet result in characteristically different oil-film pressure distribution profiles and magnitudes of friction torque. These characteristic performance indicators have not previously been observed experimentally for unidirectional fixed-geometry hydrodynamic thrust bearings with helically tapered pads. An experimental test rig was developed by re-purposing a horizontal milling machine capable of subjecting the test bearings to speeds up to 1,265 rpm and axial loads up to 250 lbf (1,112 N). Under various combinations of constant speed, load, and lubrication supply conditions, the steady-state oil-film pressure distribution across the bearing pad and active friction torque are measured. The effects of variable taper-depth on hydrodynamic pressure distribution and friction torque are compared and discussed.
A Snapshot of the State of Biologically Inspired Design for Researchers, Practitioners, and Public
Authors: Jastrzembski Mia , Watson Bryan C. , Weissburg Marc J. , Bras Bert
Published: January 2022

Biologically Inspired Design implements natural features into technologies to improve performance. Given the success of Biologically Inspired Design we are interested in the research question: How is Biologically Inspired Design currently employed? Answering this question can help design the tools used to support Biologically Inspired Design, provide an understanding of the current “state of Biologically Inspired Design”, and identify where Biologically Inspired Design solutions have not been widely utilized. Identifying gaps in utilization could prompt investigation into Biologically Inspired Design methods in fields that have not incorporated this approach into their design methodology. To answer this research question, 540 Biologically Inspired Design examples was gathered equally from three data sources: Google Scholar, the Asknature.org “Innovations” database, and Google News. The data were coded across 5 categories and 42 sub-categories. The results of our coding provide insights into two areas. First, we identify subcategories that have been underexplored by Biologically Inspired Design. For example, 63% of the biomimicry examples were applications to physical artifacts and 82% of the examples impacted the usage phase of a product’s Life Cycle. Secondly, by comparing BID results between sources (news, scholarship, and practitioners) we have insight into mismatches between the three. This solution survey and analysis provides Biologically Inspired Design researchers and practitioners valuable insight into the current state of the field, with the goal of motivating future research, outreach, and application.
Development of a Novel 4-Stroke Spark Ignition Opposed Piston Engine
Authors: Nunes Alexandre , Brojo Francisco
Published: January 2022

This project aimed to develop a low-cost, 4-stroke gasoline-powered opposed piston engine (OPE), joining two conventional internal combustion engines with side valves on the block and removing the heads. This modified engine has a combustion chamber confined to the space inside the cylinder between the piston heads and the chamber between the valves. The pistons move on the cylinder shaft in opposite directions, a typical feature of OPE.

It was studied the feasibility of building an engine from a different one already in use, to reduce the manufacturing and development costs. In addition, higher power can be obtained with better specific fuel consumption and reduced vibration.

The engine performance was compared between the stock and opposed-piston engines. The engine performance parameters, such as rotational speed, torque and fuel consumption, were measured on an eddy currents dynamometer. With the collected data, power, specific consumption and overall efficiency were calculated. The performance of both stock and opposed-piston engines were compared, allowing to conclude that the opposed-piston engine is a cost-effective solution, delivers more power and has reduced vibration.
A Data-Driven Approach for Estimating Postural Control Using an Inertial Measurement Unit
Authors: Giachin Anthony , Steckenrider J. Josiah , Freisinger Gregory
Published: January 2022

In this paper, we propose a probabilistic multi-Gaussian parameter estimation technique which addresses the complex relationship between acceleration and ground force signals used to derive a human’s static center of pressure. The intent of this work is to develop an accurate accelerometer-based method for determining postural control and neuromuscular status which is more portable and cost-effective than force plate-based techniques. Acceleration data was collected using an inertial measurement unit while ground reaction forces were simultaneously measured using a force plate. Various metrics were calculated from both sensors and probabilistic data models were built to characterize the relationships between the two sensors. These models were used to predict force-based postural control metrics corresponding to observed acceleration metrics. Data collected from one participant was used as a training set to which the test data of two individuals were then applied. We conclude that converted acceleration-based metrics on average can accurately predict all the corresponding force-based metrics we studied here. Furthermore, the proposed multi-Gaussian parameter estimation approach outperforms a more basic linear transformation technique for 75% of the metrics studied, as evidenced by an increase in correlation coefficients between true and estimated force plate metrics.
Analysis and Modeling of Vapor-Liquid Interactions in Condensing Ejectors
Authors: Wang Nanqiao , Bhatt Nirmal , Bhushan Shanti , Cho Heejin , Li Like
Published: January 2022

Ejectors are compact mechanical devices that utilize the expansion of a high-pressure primary fluid to entrain and compress a low-pressure secondary fluid by means of momentum transfer between the two streams of fluid. Condensing ejectors feature both momentum and heat transfer through the interaction between the vapor and liquid streams. This paper focuses on the thermodynamic analysis and computational modeling of the vapor-liquid interactions in two specific types of condensing ejectors — one with primary liquid and secondary vapor flows, and the other with primary vapor and secondary liquid flows. Control volume analysis of the mass, momentum, and energy balance in each phase and across the interface based on one-dimensional (1D) slug flow was conducted for the ejectors. The friction coefficient on the inner wall of the ejectors and the interfacial heat transfer coefficient are identified as controlling parameters for the ejector performance in terms of pressure and temperature distributions along the axis. The 1D slug flow models for both types of ejectors are validated with published results in the literature. After validation, in-depth parametric studies are presented to scrutinize the effects of major geometric parameters and operating conditions on the performance of both types of ejectors.
Performance Analysis of a Travelling-Wave Thermo-Acoustic Engine Using Artificial Neural Network
Authors: Ngcukayitobi M. , Tartibu L. K. , Bannwart F. C.
Published: January 2022

Thermo-acoustic systems can convert thermal energy into acoustic waves and vice-versa. These acoustic waves can be used to induce cooling (thermo-acoustic refrigeration) or generate electricity (thermo-acoustic generator). This conversion is due to the thermo-viscous interaction between the acoustically oscillating gas medium within a porous material, referred to as a regenerator, and the pore internal walls. Although there has been significant progress in the development of efficient thermo-acoustic systems, their relatively low efficiency and the nonlinearity associated with more severe working conditions remain their major issues. Therefore, it is a major potential area of research. In this study, a one-stage travelling-wave thermo-acoustic engine has been modelled using DeltaEC. The simulation was performed by considering various input heat to the hot heat exchanger within the range of 8.2 to 227.91W, and sixty (60) datasets were generated. These data were used to build an Artificial Neural Network (ANN) model. The comparison between the output data extracted from the DeltaEC simulation and the results predicted from the ANN model was done. Both of the results obtained are in good agreement and prove that the ANN can be suitable for predicting configurations that were not previously simulated.
Efficient Digital Modeling and Fabrication Workflow for Individualized Ankle Exoskeletons
Authors: Gebre Biruk A. , Nogueira Rodrigo , Patidar Shubham , Belle-Isle Robert , Nolan Karen , Pochiraju Kishore , Zanotto Damiano
Published: January 2022

We introduce a new design method to tailor the physical structure of a powered ankle-foot orthosis to the wearer’s leg morphology and improve fit. We present a digital modeling and fabrication workflow that combines scan-based design, parametric configurable modeling, and additive manufacturing (AM) to enable the efficient creation of personalized ankle-foot orthoses with minimal lead-time and explicit inputs. The workflow consists of an initial one-time generic modeling step to generate a parameterized design that can be rapidly configured to customizable shapes and sizes using a design table. This step is then followed by a wearer-specific personalization step that consists of performing a 3D scan of the wearer’s leg, extracting key parameters of the wearer’s leg morphology, generating a personalized design using the configurable parametric design, and digital fabrication of the individualized ankle-foot orthosis using additive manufacturing. The paper builds upon the design of the Stevens Ankle-Foot Electromechanical (SAFE) orthosis presented in prior work and introduces a new, individualized structural design (SAFE II orthosis) that is modeled and fabricated using the presented digital workflow. The workflow is demonstrated by designing a personalized ankle-foot orthosis for an individual based on 3D scan data and printing a personalized design to perform preliminary fit testing. Implications of the presented methodology for the design and fabrication of future personalized powered orthoses are discussed, along with avenues for future work.
Reinforced Mixed Mode Bending Fixture for Improved Characterization
Authors: Yekani Fard Masoud , Bonney Christian
Published: January 2022

The Mixed Mode Bending (MMB) test is a standardized material characterization technique used to determine the strain energy release rate and fracture toughness of layered composite materials under a range of combined mode I and mode II loading conditions. The compliance of any fixture’s internal components lessens the material characterization accuracy by introducing error into the displacement measurement. Correcting for system compliance often involves complex post-processing of data. To reduce error in the test and improve material characterization quality, the authors have redesigned the MMB test fixture for minimal compliance. An analytical model of the fixture was developed to isolate the components most responsible for system compliance. The components were modified, guided by a finite element optimization algorithm, to reduce deformation. The redesigned features reinforce the fixture without creating nonlinearity in the system or changing the test’s basic mechanisms that allow for variable mixed-mode ratios. The new MMB fixture will improve the accuracy of the experiment and reduce the complexity of data post-processing, leading to a safer crack-resistant design.
Applications of Electrochemical Impedance Spectroscopy (EIS) for Various Electrode Pattern in a Microfluidic Channel With Different Electrolyte Solutions
Authors: Kabir Shanzida , Ghosh Dipannita , Islam Nazmul
Published: January 2022

Electrochemical impedance spectroscopy (EIS) is a rapidly developing technique in microfluidics for characterizing materials and interfaces. By using equivalent circuits as models, it can determine the electrical properties of heterogeneous systems like membranes or electrolytes in a microfluidics chamber. For measuring Impedance spectroscopy, a small amount of perturbing sinusoidal signal was applied to the electrochemical microfluidic cell and measured the resulting current response. Two main ways to visualize EIS are Nyquist and Bode plot. In our research, both of these plots describe the characteristics of the electrochemical system in their ways. In our studies, we analyzed both the Bode plot and Nyquist plot for two different electrodes arrangement named as T shaped electrode (or orthogonal electrode) and V-shaped electrodes. We also compare these electrodes in three different electrolytes DI water (18.72μS/cm), tap water (666.12 μS/cm) and PBS 1× (8235.24 μS/cm) with three different ranges of conductivity to observe their characteristics changes and to compare them. We analyze the capacitive effect or electric double layer (EDL) effect for the electrode and electrolyte interface and how electron transfer kinetics and diffusional characteristics affect the spectra. As Impedance takes into account all factors such as capacitance, resistance or inductance besides the ideal resistor, it can define the characteristics of each different cell or electrode pattern by the spectra. For our microfluidics system, the capacitive systems are traditionally very large especially at the low frequencies because of impedance. The purpose of this research is to find the optimal operating range for different AC electrokinetic mechanism.
Molecular Dynamics Analysis of the Acceleration of the Degradation of the Strength of a Grain Boundary Under Creep-Fatigue Loads
Authors: Suzuki Shujiroh , Tezuka Shogo , Suzuki Ken , Miura Hideo
Published: January 2022

Since thermal power plants will be required to operate at random power output to compensate for the output instability of renewable energies, it is essential to consider the degradation damage of materials under creep-fatigue loading at high temperatures. Under creep-fatigue loading, the effective lifetime of Ni-based superalloys is known to decrease drastically, and the main reason for this was believed to be the change in the crack initiation and propagation path from transgranular to intergranular. Therefore, it is very important to identify the dominant factors that accelerate the degradation of the effective strength of grain boundaries under creep-fatigue loading.

In this study, molecular dynamics analysis was applied to the analysis of the degradation process of the crystallinity of grain boundaries. Bicrystal structures with different combinations of crystal orientations were modeled by considering the experimental results of the strength of bicrystal structures cut from polycrystalline materials. A strain-controlled creep-fatigue uniaxial load was applied to this bicrystal structure. Clear stress relaxation was observed even when the magnitude of the applied strain was much smaller than the yield criterion. The main reason for the stress relaxation was not only the local generation of dislocations around the grain boundary in the bicrystal structure, but also the accelerated ejection of atoms around the grain boundary, i.e., the grooving of the grain boundary to relieve the local strain concentration due to the lattice mismatch between nearby grains. This grooving behavior corresponds well to the accumulation of fine voids around grain boundaries under creep loads. These results indicate that under creep-fatigue loading, plural damage mechanisms are activated and they accelerate the damage accumulation and degrade the strength of grain boundaries, and thus, accelerate intergranular cracking.
Characterization and Modeling of How Environmental Aging Affects Fatigue Damage Evolution in Fiber Reinforced Polymeric Composites
Authors: Li Zhiye , Lepech Michael
Published: January 2022

Glass Fiber-reinforced polymer composites (GFRPs) are made by combining polymer with reinforcement glass fiber yarns to produce new materials that offer lightweight yet strong, durable, corrosion resistance. Its application is emerging in aerospace, the automotive and solar panel industry. Although decades of application have proved composite as a viable, permanent structural material, a reliable, experimentally validated model for the predictive performance for the composite under the expected environment is needed before this material can be used as a massive construction material. This study is to build a physics-based model to predict mechanical, thermal, weather and aging performance of the composite in the short- and long-term.

A multiscale modeling technique is used to upscale the usage of material model prediction into structural and system levels. In the multiscale computational model, there are two levels: materials level, structure level. The material level model has the smallest length scale. It consists of woven microstructure, periodic boundary conditions, and coupled multi-physical processes (radiation heat transfer, moisture condensation, polymer deterioration, and solid material behavior), which ultimately affect the mechanical performance of the material. These mechanisms will be computationally modeled using COMSOL® multi-physics modeling software. The material model will be used to generate an equivalent homogenized model that can be used at the structural level efficiently while maintaining the same accuracy.

The structure level model heritages the characteristic of the transportation model at the material level model and correlates the material degradation with structure-level mechanical loading such as fatigue damage. The model is validated by UV/moisture exposure and fatigue-damage experiment.

In the long term, the models developed in this study will be combined with life cycle assessment (LCA) tools to better support sustainability focused design of new material, thus reducing costs and environmental impacts of the built environment.
Meeting Electricity Demand With Distributed Wind and Solar Generation: System Flexibility Drives Optimal Siting
Authors: Antonini Enrico G. A. , Ruggles Tyler H. , Farnham David J. , Caldeira Ken
Published: January 2022

Hundreds of gigawatts of renewable technologies, such as wind and solar, need to be installed to reach a zero-carbon electricity system that meets current and future energy needs. Locations of new installations are typically chosen based on wind and solar availability to maximize facilities’ capacity factors. Here, we show that this is not always true in least-cost models, and optimal siting depends also on the flexibility of the electricity system. To show this, we use a macro-scale energy model to evaluate capacities and dispatch in least-cost electricity systems with distributed wind and solar generation supported by battery storage. If battery storage were free and widely available, chosen locations for wind and solar installations would inevitably be in regions with the highest wind and solar capacity factors. However, as the battery storage cost increases and thus storage capacity decreases, chosen locations have lower capacity factors and the electricity system is more reliant on wind generation. In the case of a system without energy storage, only wind generation would in fact meet certain periods of electricity demand. This study suggests that current optimal wind and solar siting may no longer be the least-cost solution as the storage cost decreases.
Process Parameter Effects on Melt Topology and Dimensional Deviation in Electron Beam Melted Ti-6Al-4V
Authors: Bol Eric , Doyle Curtis , Ramulu M.
Published: January 2022

Industry is actively evaluating additive manufacturing (AM) for parts and assemblies, but many applications have strict requirements that manufacturing processes be stable and repeatable. This is currently a challenge for many operators of powder bed fusion (PBF) technologies where limited understanding of how the AM process parameters impact the dimensional deviation from the design and material quality. The experiment described in this paper employed an electron beam melting (EBM) Arcam A2X and Ti-6Al-4V powder to manufacture single lines of melted powder within the bed. This fundamental approach was designed to identify variation and inaccuracy at the micro scale that could provide lessons applicable to the macro scale. It is a subset of a broader ongoing effort intended to characterize the manufacturing repeatability of the EBM PBF process.

The design of this experiment involved the placement of short line segments in various orientations within the build plane. Two different sets of process parameters were utilized to fabricate the CAD build geometry. Each line specimen was imaged and 3D scanned within the surrounding sintered powder to study the topology. Observations from the resulting measurements were correlated with the machine process parameters and log file data. The dimensional deviation of the melt - was characterized along with the minimum feature size. These findings provide valuable EBM design for additive manufacturing guidance to help improve quality and limit deviation in components produced for industrial applications.
Application of Bayesian Calibration to Improve Multiple Ballistic Impact Modeling
Authors: Langone Gregory A. , Davis Brad G. , Reisweber Nicholas A.
Published: January 2022

Analytical impact models for steel penetration, such as the Alekseevskii-Tate and Lambert-Zukas models, are a combination of physics principles and empirically derived constants fit by trial data to represent a specific experimental condition. These models are very useful to predict material performance under single impact conditions of a non-deforming or hydrodynamic projectile given suitable experimental test data but were not developed to account for the effects associated with repeated impact loading. The uncertainty in multiple impact events comes from variability in the impact location, effected area after impact, inertia induced fracture, material response to heating, and many other factors. Because of the meaningful uncertainty in multiple impact modeling, it is useful to apply Bayesian updating to formally combine the predictive capacity of an impact model with limited available test data to improve the model’s accuracy for a specific application and better quantify the uncertainty in the estimates. In this report, existing experimental data for impacts of 0.223 caliber ammunition against AR500 steel panels with 2-inch ballistic rubber is used for Bayesian updating. The existing data from the U.S. Army Aberdeen Test Center was gathered by shooting a steel plate while cycling through sixteen independent locations until one location is perforated. The total number of shots delivered to the plate was recorded as the number of shots to failure. Because sixteen independent plate locations were fired on, however, there is useful data from both locations where failure was not reached and those that were perforated. After creating the prior distribution of plate failure for a range of total impacts test data from all 48 locations is incorporated using Bayes’ Theorem to create a posterior distribution which represents an updated model for plate failure. The posterior density of plate failure strength — measured in number of shots at the failure location — can then be used as one parameter in a model to determine the safe allowable total number of impacts on the target of interest. This future model must also consider parameters such as the distribution of shots across the plate and the area affected by each impact while making assumptions about the practical variability in impact velocity and obliquity. A model of this type will inform decision makers to develop safe inspection criteria and utilize a safe number of impacts in training for current and future ammunition.
Undergraduate Research With Entrepreneurial Approach: Creating New Insulation Materials Using Biomass Fibers
Authors: Dikici Birce
Published: January 2022

Entrepreneurial approach suggests the creation and development of economic ventures. This study describes the activity for students for Clean Energy Systems course. The Undergraduate Research Integration is a project for students which is about writing a proposal report and giving presentations. Each team writes a research proposal during the course of the semester that involves the use of biomass composites. The proposal is assigned in the third week of the semester and is due at the end of the semester. Student teams performed a preliminary study to create, test, and document a new environmentally friendly material that will be used in their dorm insulation. This project introduces sustainable engineering issues to students. Students also have to bring biomass material samples collected from nature as a project deliverable. Adaptability, communication, and management skills influences the way people interact and engage with colleagues. Placing students in groups and giving them tasks that they depend on each other is a great way to utilize the social needs of students. Overall, increased level of student enthusiasm was observed compared to previous years. Students were engaged in group meetings and often lead asking questions at the group presentations in class. The creative nature of the project made students think outside the box and have interesting ideas.
Dynamic Placement of Rapidly Deployable Mobile Sensor Robots Using Machine Learning and Expected Value of Information
Authors: Agogino Alice , Jang Hae Young , Rao Vivek , Batra Ritik , Liao Felicity , Sood Rohan , Fang Irving , Hu R. Lily , Shoichet-Bartus Emerson , Matranga John
Published: January 2022

Although the Industrial Internet of Things has increased the number of sensors permanently installed in industrial plants, there will be gaps in coverage due to broken sensors or sparse density in very large plants, such as in the petrochemical industry. Modern emergency response operations are beginning to use Small Unmanned Aerial Systems (sUAS) that have the ability to drop sensor robots to precise locations. sUAS can provide longer-term persistent monitoring that aerial drones are unable to provide. Despite the relatively low cost of these assets, the choice of which robotic sensing systems to deploy to which part of an industrial process in a complex plant environment during emergency response remains challenging.

This paper describes a framework for optimizing the deployment of emergency sensors as a preliminary step towards realizing the responsiveness of robots in disaster circumstances. AI techniques (Long short-term memory, 1-dimensional convolutional neural network, logistic regression, and random forest) identify regions where sensors would be most valued without requiring humans to enter the potentially dangerous area. In the case study described, the cost function for optimization considers costs of false-positive and false-negative errors. Decisions on mitigation include implementing repairs or shutting down the plant. The Expected Value of Information (EVI) is used to identify the most valuable type and location of physical sensors to be deployed to increase the decision-analytic value of a sensor network. This method is applied to a case study using the Tennessee Eastman process data set of a chemical plant, and we discuss implications of our findings for operation, distribution, and decision-making of sensors in plant emergency and resilience scenarios.