bluuebunny/crossref_metadata_2025 huggingface dataset:
Contact Search Using a Kd-Tree for Non-Rigid Variation Simulation
Authors: Sadeghi Tabar Roham , Lindau Björn , Lindkvist Lars , Wärmefjord Kristina , Söderberg Rikard
Published: February 2023

Geometric variation is one of the causes of aesthetic and functional issues in mechanical assemblies. To predict the geometric variation in assemblies of rigid and non-rigid parts, statistical variation simulation is introduced. For non-rigid parts, bending and deformation occur during the assembly process. In non-rigid variation simulation, contact modeling is utilized to avoid the virtual penetration of the components in the adjacent areas. Contact modeling imposes non-linear behavior to the MIC approach for variation simulation, and thereby the problem complexity and simulation time increase. Traditionally, iterative node search is used to identify and define the computational contact nodes. However, iterative search is time-demanding, specifically in large-scale models, as the search space increases by the number of nodes included in the assembly. To allow for faster contact search, a data structuring method using Kd-trees and nearest neighbor search (NN) is implemented and integrated into a computer aided tolerancing tool, enhancing the search functionality and reducing the search time compared to iterative one-by-one node search. The method is applied to three reference assemblies of different size, and the identified contact nodes and the time needed to perform the search is compared to an iterative node search. The results show that the K-tree structure and nearest neighbor search perform considerably, 96%, faster than the iterative node search. The method increases the search performance, while the identified contact points are similar to the ones identified by an iterative search. The approach efficiently enables the contact search of large models and reduces the modeling time required for non-rigid variation simulation.
Monitoring and Diagnosis of Dimensional Deviation in Assembly Process Using Tensor Regression
Authors: Sun Rui , Jin Sun , Liu Yinhua
Published: February 2023

The monitoring and diagnosis of dimensional deviation is an important means for the continuous improvement of assembly capacity in manufacturing systems. As optical scanning measurements become more common, statistical models based on 3D point cloud data have gained widespread attention. This paper introduces a general tensor regression method that builds a linear regression model between input and output. First, voxel technology is used to transform the 3D point cloud with deviation information into tensor form. Secondly, a Tensor-on-Scalar regression model is established for quality monitoring, and a Tensor-on-Tensor regression model is established for fault diagnosis. Then, tensor decomposition is used to reduce the number of parameters to be estimated in the regression model. Finally, the learning of parameter values is achieved by combining alternating least squares and gradient descent or coordinate descent. A case study of the door inner panel assembly process evaluates the predictive performance of a tensor regression model. The results show that the proposed method outperforms most existing methods in terms of prediction accuracy. Hence, the tensor regression model can achieve high-performance quality monitoring and fault diagnosis.
Numerical Simulation and Occupant Injury Prediction Under Side Impact Loading Using Human Surrogate Model
Authors: Arathanaikotti Prasanna , Prakash Raghu V.
Published: February 2023

Side Impact, after frontal impact is one of the major causes of concern for seated occupants during road accidents. Study of injury to occupants under side impact scenarios is important to design and develop reliable and efficient safety systems that can reduce the effect during crashes. In the present work, a typical side impact scenario is modelled using finite element method and human surrogates. Aluminum plates were modelled that represent a scenario in a side impact road accident where a door may infringe into the occupant seating area. The plates were impacted at a constant velocity of 4.3 m/s along the right side of the 50th Percentile Male LSTC World Side Impact Dummy (WSID) Finite Element Model and the biofidelic response was evaluated. The pelvis and lower extremity plates were offset by 10 cm closer to the subject to simulate a typical geometry of a side door panel during a side impact. The model is validated against experimental data available in the literature by considering the forces on the plates and nodal acceleration response on full body side impact studies using Anthropomorphic Test Devices (ATD) and Post Mortem Human Subjects (PMHS). The severity of injury in this scenario is found to be more than frontal impact since the occupant is struck on the side and is seated in close proximity to the side structures. Also, safety mechanisms in the vehicle like the seat belt may not be effective in negating the injury from a side impact. The simulation results were found to be well within the PMHS response available in the experimental data. The biofidelic response of the FE surrogates was also studied to estimate the severity of the injury based on a set of injury criteria/injury assessment risk curves (IARC) that has been developed for the WSID dummy. The simulation predicted severe pelvic injuries due to the offset of the pelvis plate. Also the pelvic forces obtained on the plates in the simulation were higher than the actual PMHS response. The simulation predicted that there was a 30% risk of thoracic injuries. Injury patterns in side impact scenarios were studied in detail and probabilities based on IARC were estimated to predict injury severity and compared with standard IARV (Injury Assessment Reference Values). The numerical model developed in the present approach can be a valuable tool in assessing the performance of passenger side automotive airbags during its design and initial development phase.
Urban Air Mobility: Design of a Virtual Reality Testbed and Experiments for Human Factors Evaluation
Authors: Shankar Praveen , Marayong Panadda , Strybel Thomas , Battiste Vernol , Nguyen Hanson , Cheung Justin , Viramontes Jesus
Published: February 2023

Urban Air Mobility (UAM) has the potential to transform the transportation landscape for movement of small number of passengers and good across citywide distances. However, the successful integration of such a concept into the National Air Space will require a significant effort focused on development and testing of both the vehicles and the supporting infrastructure. In this paper, the development of a virtual reality (VR) environment for testing urban air mobility operation concepts has been presented. The VR environment that is simulated in a CAVE system includes a quadcopter type vehicle that can transport passengers across citywide distances. The design features are primarily focused on cockpit input and display interfaces while the vehicle’s motion is sufficiently realistic. An experimental design to execute a mission in San Francisco city has been tested by participants with and without prior piloting experience. Preliminary analysis of the flight data collected indicates minimal impact of prior flight experience in completing the mission.
Gravity Impact on Post-Resonance Backward Whirl Excitation by the Nonsynchronous Whirl
Authors: Abdul Nasar Rafath , A. AL-Shudeifat Mohammad
Published: February 2023

Rotordynamical systems are usually exposed to recurrent transition through their resonance rotational speeds during runup and coast-down operations. As a result, a nonsynchronous whirl between the shaft rotation and its lateral whirling occurs at the neighborhood of the critical resonance speeds. This nonsynchronous whirl has a significant impact on the system when a breathing crack starts to propagate. The horizontal Jeffcott rotor model with a breathing crack is considered here to study the combined effect of the gravity force vector and the nonsynchronous whirl on post-resonance backward whirl (Po-BW) excitation. The numerical simulation results show that the gravity further intensifies the excitation of the Po-BW in the horizontal cracked rotor compared with the vertical one at relatively small crack depths. In addition, the unbalance force vector orientation has been found to significantly affect the Po-BW excitation and its recurrence.
Environmental Sustainability of Additive Manufacturing: A Case Study of Indian Manufacturing Industry
Authors: Yadav Alok , Sachdeva Anish Kumar , Agrawal Rajeev , Garg Rajiv Kumar
Published: February 2023

Manufacturing industries across the globe are now adopting additive manufacturing (AM) practices over the traditional manufacturing process due to less waste generation and other economic and emissions benefits. Additive manufacturing can also be considered a key enabling technology for the high technology plan. However, the practices related to additive manufacturing in developing and developed economies are limited due to knowledge and technological advancements. Environmental impact assessment is an emerging research area highlighted in the last few years. At this point, research and industry attention is focused on determining where AM can replace or create new manufacturing systems. This study compares the environmental impact assessment of traditional and additive manufacturing processes by considering a case of pattern making. This paper also investigates how additive manufacturing technologies contribute to creating a sustainable environment in the manufacturing industry. A real-time case study is performed in SMEs of India, showing that additive manufacturing processes help lower the environmental impacts.

The present study also highlighted the opportunities for additive manufacturing in sustainability. The gate-to-gate analysis is performed, and impact assessment is done by GABI software version 9 on Windows 10 operating system. In this report, a case study has been done to compare the traditional IC and AM processes using Aluminum alloy (Al-Si-Cu) in terms of environmental Sustainability. Results show that 28.77% reduction in GWP, 74.04% reduction in emission to Air, 36.30% reduction in AP and 45.62% reduction in HTP by using AM process. Overall, AM process is an environmentally sustainable process. This study would help researchers and the manufacturing industry determine the emissions associated with pattern making using the conventional IC process under Indian climatic conditions. It assists manufacturing industries in choosing the best available IC alternative regarding reduced environmental emissions.
Distributed Acoustic Sensing (DAS) for Intelligent In-Motion Transportation Condition Monitoring
Authors: Taheri Hossein , Jones Michael , Bueso Quan Suyen , Gonzalez Bocanegra Maria , Taheri Mohammad
Published: February 2023

Safety is the top priority for every transportation system. Although various aspects of transportation infrastructure’s safety have been studied, in-motion monitoring and detection of defect is still a big concern. Understanding the trend of anomalies, and how to monitor undesired conditions are of high interest in transportation. In this study, the technology of Distributed Acoustic Sensing (DAS) for in-motion rail condition monitoring is studied through experimental testing and simulation modeling. DAS uses fiber optic cables along the track to detect any anomaly indicator. DAS permit the measurement of a desired parameter as a function of length along the fiber. Despite any conventional Nondestructive Testing (NDT) technique where the coverage or scanning area of the sensors are very limited, DAS provides a full, fast and accurate coverage of all section under the test. The objective of this research is to provide an assessment of anomaly detection and monitoring techniques based on DAS for transportation investigation. It presents the experimental evaluations and numerical simulations on the current methodologies in DAS systems. DAS was used to evaluate the transportation traffic condition in a rural area by connecting an available underground dark fiber to the DAS interrogator and system as well as simulated traffic condition in smaller scale in a parking lot. COMSOL Multiphysics software was used to model the interaction of ambient vibration with the fiber optic. Results show that the condition of the transportation can be monitored and detected by DAS with an appropriate accuracy. DAS information can be used for traffic condition monitoring, object tracking and flaw detections in the transportation lines.
Circulating Tumor Cell Separation in a Zigzag Channel Using Dielectrophoresis Based Inertial Microfluidics
Authors: Islam Md Sadiqul , Uddin Mohammed Raihan , Chen Xiaolin
Published: February 2023

Circulating tumor cells (CTCs) are known to be a primary indicator of vital diagnostic and clinical information for early-stage cancer detection. Effective separation of CTCs from blood is crucial for genetic characterization of CTCs, drug development, and improvement of cell cycle-targeted therapies. Many conventional microfluidic platforms isolate CTCs based on their size difference from other blood cells which renders them impractical for sorting overlapping-sized cells. To address this issue, we propose a method using a zigzag channel for continuous, label-free, and high throughput separation of CTCs coupling Dielectrophoresis (DEP) with inertial microfluidics. This hybrid channel exhibits enhanced similar-sized cell separation resolution and single-step retrieval of viable CTCs by combining inertial lift force, DEP force, and alternating curvature-induced Dean force. Through numerical investigation, separation of MDA-231 CTCs from identical-sized WBCs has been achieved at a relatively high Reynolds number of 125. Furthermore, the working parameters such as Reynolds number, voltage, and electrode configuration have been optimized for enhancing the separation efficiency. The proposed design can provide valuable insight into the development of a versatile, efficient, inexpensive, and novel platform with reduced analysis time for cancer diagnosis and prognosis.
Supervised and Unsupervised Deep Learning Applications for Visual SLAM: A Review
Authors: Ukaegbu Uchechi Faithful , Tartibu Lagouge Kwanda , Lim Chee Wah
Published: February 2023

Visual Simultaneous Localization and Mapping (V-SLAM) is a trending robotics research concept as well as the basis for autonomous and smart navigation. It is an integral part of vision-based applications which include virtual reality, unmanned aerial vehicles, augmented reality, and unmanned ground vehicles. V-SLAM carries out localization and mapping by learning relevant feature points from images and estimating their pose based on the correlation between the camera and the feature points. It also represents the ability of a robot to effectively navigate itself, employing visual sensors and prior information of the given location, in an uncharted environment while updating and constructing a coordinated map of the scene. However, due to the challenges of data association triggered by illumination, different viewpoints and environment dynamics, there has been rapid adoption of deep learning in the area of feature extraction/description, pose/depth estimation, mapping, loop closure detection and global optimization as it concerns visual SLAM. This paper sets out to elucidate diverse applications of supervised and unsupervised deep learning methods in all aspects of visual SLAM. It also briefly explains a case study regarding the application of both deep learning and SLAM for underground mining applications. It highlights recent research developments in addition to limitations hindering their effective application and investigates how a combination of deep learning with other methods offers a promising direction for visual SLAM research.
Evaluation of Deep Learning Networks for Predicting Truss Topology Optimization Results
Authors: Gorguluarslan Recep M. , Ates Gorkem Can
Published: February 2023

The applicability of artificial neural networks (ANNs) on the prediction of the structural optimization results of a truss structure is investigated. Two different ANN architectures are employed and the effect of using various optimizers and activation functions on their prediction performance is evaluated. Unlike the traditional machine learning network strategies where usually a physical response of the truss optimization (such as compliance, stress, etc.) is predicted, in this study, a new way of prediction is utilized for the truss-like structures; particularly predicting the optimized thickness values of the strut members by the ANNs. Thus, the input data used in these networks are the thickness values of the strut members at a certain initial iteration while the optimized thickness values are predicted as the outputs. A cantilever beam example is presented for the truss optimization to show the efficacy of the presented ANNs. The results indicate that using the thickness values at a certain initial iteration as inputs and final iteration thicknesses as outputs in ANNs are promising for the structural optimization prediction of the presented truss problem with the appropriate selection of the architecture, optimizer, activation function, and the input-output data formation.
Design, Construction, and Thermodynamic Analysis of a Direct-Expansion Solar Assisted Heat Pump for Cold Climates
Authors: Elgamal Nadia , Sambi Jessica , Patel Dhruvi , Marasinghe Charuka , Pulikkottil Edwin , Virtusio Kerwin , Mwesigye Aggrey , Li Simon
Published: February 2023

Direct expansion solar assisted heat pump (DX-SAHP) systems have the potential to provide the heat load required for domestic hot water (DHW) sustainably and with minimum emissions. DX-SAHPs utilize a solar thermal collector to evaporate a working fluid. By using less energy in the process, these systems can achieve higher coefficients of performance (COP) than those afforded by conventional air source heat pumps. With Calgary possessing the highest solar potential in Canada of about 2396 hours of sunlight available 333 days a year [1], the implementation of such systems would make technical and economic sense. In this paper, the design, fabrication, and testing of a DX-SAHP system for cold climates is presented. A mathematical model representing the system was developed by combining the Hottel-Whillier-Bliss equation for the solar collector and a control volume analysis using the first law of thermodynamics for the heat pump cycle. Theoretical results demonstrate that a COP in the range of 3.4–4.5 is achievable. With the promising theoretical results, an experimental test setup was designed, constructed, and instrumented to determine the long-term performance of a DX-SAHP under local climatic conditions.
Independence of Environmental and Mechanical Damages on Silicone Adhesive Stored in a Thermo-Oxidative Environment
Authors: Alazhary Sharif , Mohammadi Hamid , Shaafaey Mamoon , Dargazany Roozbeh
Published: February 2023

Elastomeric polymer materials hold a special place in today’s industrial sectors with respect to structural application needs. Low quality materials are detrimental to industries like aerospace, and automotive engineering. Assessment of the durability of elastomers for structural applications has been of much interest among the literary circles for decades and new materials keep outperforming the existing ones. Polymeric adhesives are one of the most abundantly used materials in these industries. All polymeric materials get damaged when in contact with aggressive environments in presence of high temperature and oxygen. Commonly referred to as thermo-oxidation, this environment exposes the material to heat and oxidation reactions in presence of oxygen. Resultantly, during service life, the damage to the polymer matrix is primarily caused by two factors: mechanical damage and environmental aging. Environmental aging is an irreversible phenomenon caused by changes in the molecular structure while mechanical damage maintains the shape of the polymer matrix, and the deterioration is mostly due to polymer chain mobility. Environmental aging can be caused by a single environmental agent or by a synergized impact of several environmental elements. Increasing temperature is found to be proportional to decreasing tensile strength and toughness of material. The rate and extent of degradation can be accessed by scrutinizing the changes in constitutive behavior of material through mechanical and chemical properties. Accelerated thermal aging is among the most common modes of process related degradation, leading generally to chain scission, and crosslinking phenomena and reduced resistance to fracture stress, and strain. In this experimental study, our goal is to separate the environmental degradation from mechanical damage. A silicone-based adhesive was aged in thermo-oxidative at (0%RH) aging environment. The damage and decay mechanisms have been used to draw a distinction between environmental degradation and mechanical damage. Material characterization included uniaxial tensile test (failure and cyclic) and scanning electron microscopy (SEM) tests on as-received and aged samples. Aging was conducted at three different temperatures (60°C, 80°C and 95°C) and six different exposure durations (1, 3, 10, 30, 90 and 200 days). This work confirms that environmental damage is superposed on top of the mechanical damage, and thus, they are separable. The total mechanical and environmental damage is a synergized effect of all exposure conditions and parameters involved i.e., aging time, temperature, and oxygen. The chemistry and mechanics of the polymer degradation were found to be in good agreement with each other.
Development of the Ultrasonic System Integration With 3D Polymer Printing
Authors: England Jonathan , Darnell Ethan , Bhakta Janak , D’Orazio Maria , Chukovenkova Mariya , Zagrai Andrei
Published: February 2023

Non-destructive testing using ultrasonic sensors supplies manufacturers with methods of monitoring a part’s integrity as it is being produced. The purpose of this experiment is to demonstrate the usefulness and viability of using ultrasonic sensors to monitor the 3D printing process. In order to accomplish this task, an attachment for the build plate of a 3D printer was developed that holds an ultrasonic sensor against the build plate while the printer is running initial tests. The ultrasonic sensor was used to analyze printing filaments and the build plate included with the printer. The results of ultrasonic investigation have demonstrated inefficiency of the composite plate in transduction of elastic waves and a steel build plate was suggested for further testing. Initial studies were conducted to explore material characteristics of the built plates and the printing materials. Ultrasonic setup with longitudinal and shear wave transducers were utilized to measure material properties such as Young’s modulus, shear modulus and the Poisson ratio. It is anticipated that material characterization will also be conducted during the printing process. This means heat will be introduced into the system and as a result the speed of sound through the build plate and filament will vary as a function of temperature. To better understand the role of temperature in real-time ultrasonic NDE, an FEA model is developed to determine the transient temperature gradient through the steel build plate and filament during the printing process. Thermal imaging data is considered to assess the accuracy of the FEA model for the dynamic temperature distribution. Once relationships between temperature variation and sound speed have been established properties such as Young’s modulus can be calculated. It is anticipated that application of this approach will allow for assessment of material properties in near real time, which is critical for process monitoring and ensuring quality of the additively manufactured parts.
Graphene-Conductive Polymer-Based Electrochemical Sensor for Dopamine Detection
Authors: Ghosh Dipannita , Rahman Md Ashiqur , Ashraf Ali , Islam Nazmul
Published: February 2023

The central nervous system’s (CNS) dopaminergic system dysfunction has been linked to neurological illnesses like schizophrenia and Parkinson’s disease. As a result, sensitive and selective detection of dopamine is critical for the early diagnosis of illnesses associated with aberrant dopamine levels. In this research, we have investigated the performance of electrochemical screen-printed sensors for different concentrations of dopamine detection using graphene-based conductive PEDOT: PSS(G-PEDOT: PSS) and Polyaniline(G-PANI) inks on the working electrode and compared the sensitivity. SEM characterization technique has been performed to visualize the microstructures of the proposed inks. We have investigated cyclic voltammetry (CV) electrochemical techniques with ferri/ferrocyanide redox couple to assess the efficiency of the designed electrodes in detecting dopamine. G-PANI ink has shown to have better LOD and stability to detect dopamine with screen-printed electrodes. Further, we have also studied electrochemical analysis for the selective detection of dopamine without the interference of Ascorbic Acid (AA).
Application of Nickel Deposition on Electropolishing (EP), Chempolishing (CP), and As-Built Additively Manufactured (AM) Metal Components
Authors: Sanchez Pablo , Waqar Zafar , Tyagi Pawan
Published: February 2023

Existing additive manufacturing (AM) technologies produce metal components with a rough surface that generally display fatigue characteristics, leading to component failure and undesirable friction coefficients to the printed part. Small cracks formed at regions of high surface roughness in rough surfaces act as a stress raiser or crack nucleation site. Hence, as-produced parts’ direct use is limited and introduces a challenge related to smoothening the surface. The present study explores the application of electroless nickel deposition. It examines the surface finishing techniques such as Chempolishing (CP) and Electropolishing (EP) for post-processing on additively manufactured stainless-steel samples. Previous studies have demonstrated that CP offers a major advantage in providing consistent, smooth surfaces, regardless of the component size or geometry. Surface smoothness is increased, and surface roughness is decreased to the sub-micrometer range via EP. The study also investigates nickel deposition on EP, CP, and as-built AM components, utilizing electroless nickel solutions. Alloys are exposed to an electroless nickel plating process in order to enhance the hardness and surface resistance of produced components to the hostile environment. The medium-phosphorus (6–9% P), and high-phosphorus (10–13% P) was used. The Ni deposition experiments were optimized using the L9 Taguchi design of experiments (DOE), which involve the prosperous content in the solution, surface preparation, plane orientation of the sample geometry, and Nickel strike exposition time. The pre- and post-processed surface of the AM parts is being investigated by the KEYENCE Digital Microscope VHX-7000. This work is in progress concerning the complete Scratch analysis and Design of Experiment (DOE) analysis using the Qualitek-4 software.
Techno-Economic Analysis for Comparing Stereolithography and Wax Injection for Pattern Manufacturing in Investment Casting
Authors: Mandolini Marco , Sartini Mikhailo , Favi Claudio , Germani Michele
Published: February 2023

Investment casting (IC) is a manufacturing process for making components giving an excellent surface finish, dimensional accuracy, and complex shapes. Despite these benefits, IC requires high cost and lead time for realizing the metallic mold for pattern manufacturing. To avoid the shortcoming of casting processes, Additive Manufacturing (AM) is widely used for fabricating patterns, cores, and molds (Rapid Casting - RC). Several applications concerning rapid investment casting (RIC) through Fused Filament Fabrication (FFF) and Stereolithography (SLA) were developed. However, a techno-economic analysis based on SLA application for RIC is missing. This paper presents a techno-economic analysis regarding SLA adoption for RIC. SLA is compared with wax injection, the traditional approach for realizing wax patterns. The article provides a decision-making tool that supports stakeholders in evaluating when AM is convenient (cost and lead time) for creating wax patterns, considering different production scenarios. For the compared technologies, the authors developed analytical cost models capable of assessing the cost of the entire production process and evaluating the postprocessing phases. The following characteristics were considered: (i) different production volume, (ii) machine load factor, and (iii) parts features (i.e., dimensions and shape). The results show that SLA, for small parts, is more convenient than wax injection when the production volume is higher than 1E+03.
Investigation of Mass Savings Potential of Zeolite Integrated Motor Thermal Management Systems in All-Electric Commercial Aircraft
Authors: Malone Nathan , Chakravarty Sourav , Zhang Shiyu , Talebi Dorsa , Sankarraman Sri Vignesh , Pool Erick , Park Deokgeun , Iverson Ethan T. , Wiley Chase , Shamberger Patrick , Antao Dion , Gardner Matthew C. , Toliyat Hamid , Enjeti Prasad , Rasmussen Bryan , Grunlan Jaime , Benedict Moble , Felts Jonathan
Published: February 2023

This study investigates a novel hybrid cooling method for more weight efficient thermal management of aerospace electric propulsion motors using thermal energy storage (TES) elements. The proposed system utilizes the latent heating of TES in the form of SAPO-34 zeolite slabs hydrated with water to maintain stable operating temperatures during takeoff. The TES operates in parallel with a fluid cooling system comprised of minichannel heatsinks attached to the stator windings and exterior air heat exchanger. Thermoelectric performance benefits of TES inclusion are evaluated using network analysis under assumed flight path load. Complex non-linear thermofluid and electromagnetic behaviors in the network are replaced with lookup table interpolants generated using results of numerical simulations swept across a series of input parameters. Subsequent solution of two-hundred systems with varying TES volume indicated a maximum TMS mass savings of 14.8% compared to the lightest thermal management system without TES inclusion.
Multiphase Flow and Heat Transfer in an Electric Motor
Authors: Pandey Ashutosh , Madduri Bharath , Perng Chin-Yuan , Srinivasan Chiranth , Dhar Sujan
Published: February 2023

Electric vehicles are becoming increasingly common due to environmental needs. Due to this, efficiency in design process of electric motors (E-motor) is becoming critical in the industry. To assess performance capabilities for an E-motor, thermal predictions are of utmost consequence. This study describes a computational method based on unsteady Reynolds-averaged Navier-Stokes equations that resolves the gas-liquid interface to examine the unsteady multiphase flow and heat transfer in a concentrated winding E-motor. The study considers all important parts of the motor i.e., coils, bobbins, stator laminate (yolk), rotor laminate, magnets etc. The study highlights the ease of capturing complex and intricate flow paths with a robust mesh generation tool in combination with a robust high-fidelity interface capturing VOF scheme to resolve the gas-liquid interfaces. Results obtained show the dominant processes that determine the oil distribution to be the centrifugal force from rotation of the rotor, the flow rate of oil injected in the stator assembly as well as in the rotor assembly and gravity. A novel heat transfer approach (mixed time-scale coupling) is used to solve for the temperatures in the stator and rotor solids. The approach first requires achieving a quasi-steady flow solution before initiating heat transfer calculation for faster turnaround times. The approach separates the conjugate heat transfer calculation into a fluid heat simulation and a solid heat simulation while setting up a communication method to exchange the thermal boundary conditions between the two simulations. This study also considers the anisotropic nature of thermal conductivities resulting from the wound-around arrangement of the coils and the laminate nature of stator/rotor laminates in the assignment of the thermal conductivities of these solids. Results of thermal simulation show the solid temperatures to be in direct correlation with the oil distribution near those solids. This computational study was validated by comparing the computed and measured temperatures at specified locations on the coils and good agreements with experiments were found.
Build Chamber and Start Plate Variability During Electron Beam Melting Machine Setup
Authors: Kelley Garrett , Mamidala Ramulu
Published: February 2023

Electron beam melting (EBM) is an additive manufacturing process that utilizes a metallic powder as the feedstock material. During the setup of an Arcam A2X machine, the operator is first required to load the feedstock into the hoppers and set the “zero” position of the start plate relative to the rake. This manual process relies on operator-experience and is hypothesized to have a detrimental impact on process repeatability by modifying the local layer thickness. The potential effect that this has on the as-built quality and performance of EBM-manufactured components is unknown. Therefore, this study presents a device used to measure the variability that exists during A2X machine operations. Consideration is given to both the build basin as well as the start plate during ten machine setups. Assuming a mean particle diameter and commensurate layer thickness of 50 μm for Ti-6Al-4V, data indicate that local thickness deviations greater than ten layers are achievable using the prescribed zeroing routine. These deviations are shown to manifest in the measured mass of specimens within a test build. While not directly considered in this study, a discussion regarding powder pile size during fetching operations and how this may affect bed coverage and build quality is also provided.
Hyper-Viscoelastic 3D Response of Axons Subjected to Repeated Tensile Loads in Brain White Matter
Authors: Agarwal Mohit , Pelegri Assimina A.
Published: February 2023

A novel finite element method (FEM) is developed to study mechanical response of axons embedded in extra cellular matrix (ECM) when subjected to harmonic uniaxial stretch under purely non-affine kinematic boundary conditions. The proposed modeling approach combines hyper-elastic (such as Ogden model) and time/frequency domain viscoelastic constitutive models to evaluate the effect of parametrically varying oligodendrocyte-axon tethering under harmonic stretch at 50Hz. A hybrid hyper-viscoelastic material (HVE) model enabled the analysis of repeated uniaxial load on stress propagation and damage accumulation in white matter.

In the proposed FEM, oligodendrocyte connections to axons are depicted via a spring-dashpot model. This tethering technique facilitates contact definition at various locations, parameterizes connection points and varies stiffness of connection hubs. Results from a home-grown FE submodel configuration of a single oligodendrocyte tethered to axons at various locations are presented. Root mean square deviation (RMSD) are computed between stress-strain plots to depict trends in mechanical response. Steady-state dynamic (SSD) simulations show stress relaxation in axons. Gradual axonal softening under repetitive loads is illustrated employing Prony series - HVE models. Representative von-Mises stress plots indicate that undulated axons experience bending stresses along their tortuous path, suggesting greater susceptibility to damage accumulation and fatigue failure due to repeated strains.
A Review of the Design and Implementation of Digital Twins for Smart Manufacturing
Authors: Ali Shafahat , Abdallah Said , Pervaiz Salman
Published: February 2023

The current massive use of machine learning and the 5G networks have supported the high demand for the digital twin and made it more popular and common in the industrial sector and scientific research related to smart manufacturing. As part of this research study, the currently available opportunities for smart manufacturing using digital twins have been reviewed and discussed in the industry 4.0 field. While digital twins have garnered much attention in the industrial internet of things, their use in smart manufacturing has been much less common. This discussion here focuses on the open challenges in smart manufacturing and industry 4.0 and suggests that in some cases. Digital twins should be treated differently to enhance industrial processes and smart manufacturing applications. On the other hand, this research examines the impact of digital twins on smart manufacturing and sustainable production rates, aiming to promote the industry’s digital transformation to meet the required production rate. The research discussed the digital twin concept and its origins and perspectives from academia and industrial sectors. It reveals its potential for the digitalization of manufacturing. Also, the review discussed how the digital twins could support the integrated, flexible, and collaborative manufacturing environments associated with the fourth industrial revolution.

Different industrial operational technologies and communication technologies have profoundly changed smart manufacturing. Intelligent and automated information exchange, automated machine control, and interoperable production systems have all been enabled by Industry 4.0. System-level CPS and digital twins can collaborate through Smart Service Platforms for Digital Twins. In addition to optimizing production configurations, the digital twin is used to determine the impact of decisions made during modifications or upgrades. By analyzing the predictive maintenance of manufacturing lines, the time between production delays will be reduced. A specific alarm or notification will be sent to the user to enable them to take quick action. A digital twin application analyzes and simulates data by controlling, monitoring, and optimizing variables based on various factors in both online and offline modes. This study seeks to evaluate the evolution of digital twin concepts and their relevance to smart manufacturing. It summarized and explained the current state of digital twins in manufacturing literature, highlighting future directions for studies and the highest potential for future applications.
Probing the human epidermis by combining ToF-SIMS and multivariate analysis
Authors: Delvaux Xavier , Noël Céline , Poumay Yves , Houssiau Laurent
Published: February 2023

The mammalian organism is continuously exposed to various biological and chemical threats from its surroundings. In order to provide protection against these threats, mammals have developed a specialized defense system at the interface with their environment. This system, known as the epidermis, is mainly composed of stratified keratinocytes organized in a complex self-renewing structure providing a mechanical and chemical barrier at the skin surface. However, numerous skin-related pathologies can interfere with the proper formation and function of the epidermal barrier. The pathogenesis of these alterations is often very complex. Understanding the changes induced in epidermal tissues by these pathologies at a molecular level is key for their treatment and prevention. In this context, this work aims at developing a thorough and reproducible characterization methodology of the human epidermis by applying ToF-SIMS to the study of an in vitro epidermal model known as reconstructed human epidermis (RHE). Indeed, although the potential of ToF-SIMS for the characterization of the mammalian skin has already been demonstrated, very few studies focus their efforts on the human epidermis itself. Here, we performed static ToF-SIMS characterizations of RHE cryosections, combining both high mass and high lateral resolution acquisitions. In addition, principal components analysis was used as a multivariate analysis tool. This contributed to the decorrelation of the complex datasets obtained from these biological systems and allowed capturing of their most statistically representative spectral features. Remarkably, this tool proved to be successful in extracting meaningful biological information from the datasets by yielding principal components distinguishing the cornified layers from the metabolically active epidermal cells. Finally, on the basis of multiple ToF-SIMS acquisitions, we showed that this methodology allows for the convenient production of experimental replicates, a key feature often difficult to achieve in ex vivo approaches.
VO2max and Velocity at VO2max Play a Role in Ultradistance Trail-Running Performance
Authors: Sabater-Pastor Frederic , Tomazin Katja , Millet Grégoire P. , Verney Julien , Féasson Léonard , Millet Guillaume Y.
Published: February 2023

Purpose: Previous research has shown that maximal oxygen uptake (VO2max) significantly influences performance in trail-running races up to 120 km but not beyond. Similarly, the influence of running economy on performance in ultratrail remains unclear. The aim of our study was, therefore, to determine the physiological predictors of performance in a 166-km trail-running race. Methods: Thirty-three experienced trail runners visited the laboratory 4 to 8 weeks before the race to undergo physiological testing including an incremental treadmill test and strength assessments. Correlations and regression analyses were used to determine the physiological variables related to performance. Results: Average finishing time was 37:33 (5:52) hours. Performance correlated significantly with VO2max (r = −.724, P < .001), velocity at VO2max (r = −.813, P < .001), lactate turn point expressed as percentage of VO2max (r = −.510, P = .018), cost of running (r = −.560, P = .008), and body fat percentage (r = .527, P = .012) but was not related to isometric strength. Regression analysis showed that velocity at VO2max predicted 65% of the variability in performance (P < .001), while a model combining VO2max and cost of running combined predicted 62% of the variability (P = .008). Conclusion: This is the first study to show that VO2max and velocity at VO2max are significant predictors of performance in a 166-km trail-running race. This suggests that ultratrail runners should focus on the development of these 2 qualities to optimize their race performance.
Training Load, Neuromuscular Fatigue, and Well-Being of Elite Male Volleyball Athletes During an In-Season Mesocycle
Authors: Rebelo André , Pereira João R. , Martinho Diogo V. , Amorim Gerson , Lima Ricardo , Valente-dos Santos João
Published: February 2023

Purpose: Most high-intensity bouts of exercise in volleyball consist of jumping activities, which are responsible for inducing muscle damage, high levels of fatigue, and muscle soreness. Therefore, the aim of the current study was to quantify and analyze the training loads, neuromuscular fatigue, and perceptual well-being of a 5-week in-season mesocycle carried out by a professional male volleyball team. Methods: Fifteen volleyball players (age 28.51 [5.39] y; height 193.19 [9.87] cm; body mass 88.46 [13.18] kg) participated in this study. Internal training load assessed through the rating of perceived exertion, external training load (ETL; evaluated using an inertial motion unit), countermovement jump (CMJ) height and peak power, and wellness questionnaire responses were obtained from all athletes. Results: Results indicated a progressive decrease of the internal training load during the week and by the undulatory pattern of the ETL during the microcycles. Moreover, training monotony increased across the microcycles and was negatively associated with CMJ peak power (r = −.681, P < .05). Finally, sleep quality (ρ = −.747, P < .01) and fatigue (ρ = −.789, P < .01) were negatively associated with weekly ETL. Conclusions: This study indicated that sleep quality and fatigue were negatively associated with weekly ETL. Therefore, decreases in weekly ETL might be needed to improve sleep quality and decrease fatigue in professional volleyball players. Plus, higher values of training monotony were associated with lower values of CMJ peak power. Consequently, avoiding training monotony might be important to improve jumping performance in professional volleyball athletes.
Coordinated activity of a central pathway drives associative opioid analgesic tolerance
Authors: Hou Yiwen , Zou Guichang , Wang Xianglian , Guo Hui , Ma Xiao , Cheng Xingyu , Xie Zhiyong , Zuo Xin , Xia Jing , Mao Huanhuan , Yuan Man , Chen Qi , Cao Peng , Yang Yupeng , Zhang Li , Xiong Wei
Published: February 2023

Opioid analgesic tolerance, a root cause of opioid overdose and misuse, can develop through an associative learning. Despite intensive research, the locus and central pathway subserving the associative opioid analgesic tolerance (AOAT) remains unclear. Using a combination of chemo/optogenetic manipulation with calcium imaging and slice physiology, here we identify neuronal ensembles in a hierarchically organized pathway essential for AOAT. The association of morphine-induced analgesia with an environmental condition drives glutamatergic signaling from ventral hippocampus (vHPC) to dorsomedial prefrontal cortex (dmPFC) cholecystokininergic (CCKergic) neurons. Excitation of CCKergic neurons, which project and release CCK to basolateral amygdala (BLA) glutamatergic neurons, relays AOAT signal through inhibition of BLA μ-opioid receptor function, thereby leading to further loss of morphine analgesic efficacy. This work provides evidence for a circuit across different brain regions distinct for opioid analgesic tolerance. The components of this pathway are potential targets to treat opioid overdose and abuse.
Anthropogenic N input increases global warming potential by awakening the “sleeping” ancient C in deep critical zones
Authors: Qin Shuping , Yuan Haijing , Hu Chunsheng , Li Xiaoxin , Wang Yuying , Zhang Yuming , Dong Wenxu , Clough Timothy , Luo Jiafa , Zhou Shungui , Wrage-Mönnig Nicole , Ma Lin , Oenema Oene
Published: February 2023

Even a small net increase in soil organic carbon (SOC) mineralization will cause a substantial increase in the atmospheric CO
2
concentration. It is widely recognized that the SOC mineralization within deep critical zones (2 to 12 m depth) is slower and much less influenced by anthropogenic disturbance when compared to that of surface soil. Here, we showed that 20 years of nitrogen (N) fertilization enriched a deep critical zone with nitrate, almost doubling the SOC mineralization rate. This result was supported by corresponding increases in the expressions of functional genes typical of recalcitrant SOC degradation and enzyme activities. The CO
2
released and the SOC had a similar
14
C age (6000 to 10,000 years before the present). Our results indicate that N fertilization of crops may enhance CO
2
emissions from deep critical zones to the atmosphere through a previously disregarded mechanism. This provides another reason for markedly improving N management in fertilized agricultural soils.