bluuebunny/crossref_metadata_2025 huggingface dataset:
Experimental Approach and Conventional Analytical Techniques to the Carbon Nanotube Network Interphase in 3-Phase Polymer Matrix Nano-Composites
Authors: Yekani Fard Masoud , Swanstrom Joel
Published: January 2022

The interaction between the CNT network and the surrounding polymer and between BP and the surrounding polymer occurs via interphase with different morphology than the bulk matrix. This interphase’s properties have not been given enough attention in the literature, and the purpose of this study is to investigate the interphase properties experimentally and analytically. Atomic Force Microscopy based Peak Force Quantitative Nanomechanics Mapping (PFQNM) technique with the high lateral resolution was used for the characterization of the interphase in 3-phase polymer matrix nano-composites at the nanoscale. Details of the calibration parameters such as probe stiffness, spring constant, tip radius, tapping force, deformation level, synchronous distance, drive3 amplitude sensitivity (DDS3), and deflection sensitivity were discussed. AFM Multimode 8, scanner type J with a maximum scanning window of 125μm × 125μm, was used. The Derjaguin, Muller, Toropov (DMT) equation was applied to the retract curve to calculate the elastic modulus. BP is heterogeneous at the nanoscale due to nonuniform resin impregnation. The average interphase thickness for the CNT network is 27nm in BP, higher than ∼10nm between epoxy and fiber, confirming stronger interphase. The CNT network size in BP nanocomposite is influenced by the inter-bundle and intra-bundle pores in the BP. The Kolarik, Quali, and Takayanagi models for interphase of the CNT network were investigated.
Validation Study of Reynolds Stress Model Coupled With Gamma Transition for UAV Propellers
Authors: Pisharoti Naina , Brizzolara Stefano
Published: January 2022

The current study is carried out to investigate complex near-wall flow effects like separation and cross-flow and their impact on UAV performance. Furthermore, the study proposes using the novel SSG/LRR-ω-γ model, which is a second-order closure, Reynolds stress transport-based transition turbulence model, that can help capture the near-wall flow observed in low Reynolds number flows. To prove the credibility of the model, it is validated against experimental data available for the DJI Phantom 3 propeller. The SSG/LRR-ω-γ model is then compared against other transition models as well as fully turbulent models and was found to show better performance when assessed on their ability to predict rotor performance characteristics as well as near-wall flow behavior.
Corrosion Performance of Different Aluminum Alloy Deposits Fabricated by Lateral Friction Surfacing
Authors: Relue William , Seidi Ebrahim , Hihara Lloyd H. , Miller Scott F.
Published: January 2022

Friction surfacing technique is a thermo-mechanical approach for metallic deposition, suitable for a broad range of materials and applications. Friction surfacing can be employed for various industrial purposes such as coating, welding, repairing defective parts, surface hardening, and improving corrosion performance. In this technique, frictional heat generated at the interface of the consumable tool and substrate results in a severe plastic deformation at the end of the rod, enabling the deposition of a consumable material on the substrate surface.

In this investigation, a novel method in friction surfacing, lateral friction surfacing, is employed to deposit the aluminum coatings. In this novel approach, the side of the consumable tool is pressed against the surface of the substrate, and the material transfer happens from the lateral surface of the tool. This technique provides extremely thin and smooth deposits, which are more consistent compared to the conventional approach of friction surfacing. Moreover, this technique enables fabricating of deposits in lower temperatures, lessening the thermal impacts on the microstructures and mechanical properties of the deposits.

In this investigation plates of 1018 mild steel were partially coated with various aluminum alloys and corroded in an accelerated corrosion test chamber. The corrosion performance of the partially coated sample was evaluated by mass loss measurement. It was found that AA5086 offered the most corrosion protection. After 13 cycles of GM9540P test, equivalent to approximately 3½ years exposure at a mild/moderate marine site in Hawaii, almost all of the deposited aluminum was corroded off.
Bloch Wave Dynamics of a Branched Locally Resonant Metamaterial With a Discrete Periodic Resonating Branch
Authors: Bastawrous Mary V. , Hussein Mahmoud I.
Published: January 2022

This paper presents a novel metamaterial unit-cell configuration that may exhibit local resonance (LR) band gaps with exceptional properties — e.g., extreme width. The proposed configuration is comprised of a base wave-propagating medium to which a discrete periodic resonating branch — e.g., a branch made of a finite number of repeating diatomic unit cells — is connected. Such periodicity causes waves propagating in the branch to experience attenuation within the branch unit-cell Bragg band gap. The branch may also vibrate in resonance within its Bragg band gap due to the effect of the boundaries introduced upon truncating the nominal periodic medium. Such Bragg band-gap resonances exhibited by the branch are key to the proposed configuration as the metamaterial LR band gaps that form around them may possess exceptional properties. This paper shows that these exceptional LR band gaps are highly tunable and can be systematically designed using a semi-analytical design approach. The design approach is in part based on a recently derived analytical method that predicts, in advance, whether the branch would exhibit resonance and anti-resonance frequencies in its Bragg band-gap. Finally, a numerical case is discussed to showcase the proposed metamaterial configuration and design approach; it presents a metamaterial unit cell that demonstrates an extremely wide LR band gap. These findings open a route towards exploiting discrete, e.g., granular, periodic resonators to realize highly tunable LR band gaps.
Atomistic Simulation of Interface Effects in Hybrid Carbon Fiber Reinforced Polymer Composites Incorporating ZnO Nanowires
Authors: Marashizadeh Parisa , Abshirini Mohammad , Saha Mrinal C. , Huang Liangliang , Liu Yingtao
Published: January 2022

This paper reports a molecular dynamics (MD) simulation study for evaluating the interfacial properties of ZnO nanowire (NW)/carbon fiber reinforced polymer (CFRP) hybrid composites. Molecular structures of the hybrid composite components, including cross-linked epoxy, graphene sheet representing carbon fiber surface, and ZnO NW are simulated. A representative volume element (RVE) is modeled at the nanoscale containing a ZnO NW vertically aligned on the carbon fiber surface and embedded in the epoxy matrix. Normal displacement load is applied to the carbon fiber sheet to separate it from the ZnO NW perpendicular to the fiber sheet. The traction-separation properties of the interface between fiber and the enhanced matrix are evaluated. The cohesive parameters, including the interfacial strength and the cohesive energy in the ZnO NW hybrid model, are compared with the bare model (fiber and epoxy). The MD simulation results show a 98% improvement in the cohesive energy and 130% improvement in interfacial strength of the hybrid CFRP composites. This study demonstrates the promising effect of aligning ZnO on the fibers for enhancing fiber-matrix adhesion.
Wire Resistance Model for Temperature and Force Analysis of Twisted and Coiled Polymer Actuators
Authors: Zhang Cennan , Wan Lei , Wu Yannan , Li Hua
Published: January 2022

In this paper, self-sensing TCPAs, i.e., TCPAs wrapped with conductor were manufactured, their resistances were firstly measured in various temperatures. The experimental results have shown that TCPAs have constant thermal driving capacity in a wide temperature region from low temperature (below zero) to high temperature (above zero). The driving force of TCPAs changes linearly with temperature. Based on the experimental data, a mathematical model of the temperature with respect to resistance was derived, and was subsequently used to investigate the driving force of TCPAs. Despite the linear relationship between temperature and driving force, hysteresis between the TCPAs temperature and the conductor temperature was observed. There is also a hysteresis between the resistance of conductor and temperature of TCPAs. A model of TCPAs temperature with respect to resistance was derived, its parameters were obtained by parameter identification. These parameters are related to the diameter of TCPAs and the experimental environment. The proposed model is feasible for resistance and temperature measurement, which facilitates the control of TCPAs temperature and driving force. Both the experiment and the model characterize the mechanical properties of TCPAs over the effective temperature range.
Finite Element Analysis of Deformation Characteristics in Warm Skew Rolling of Copper Ball
Authors: Yuan Jiayao , Sun Baoshou , Chen Xing , Shu XueDao , Ma Houliang
Published: January 2022

The skew rolling is a ideal metal forming technique for producing ball parts of various sizes. In order to analyze the forming mechanism ensuring the highest quality of copper ball during warm skew rolling, in this paper, a new modeling method was used for roller design based on the CREO platform. By using commercial FEM software Simufact 14.0, an FE simulation of warm skew rolling was established to predict the distribution of strain field, stress field, temperature field. meanwhile, the variation of rolling force and torque for copper balls during warm skew rolling were analyzed. Based on numerical simulation results, the deformation characteristics of copper ball during warm skew rolling is clarified. The simulation and experimental results Highly consistent and the copper balls have a high manufacturing quality confirm that the developed FE-simulation is reliable. This study was developed a new modeling method to overcome the difficulties and deficiencies in available finite element modeling process for complicated roller and lays a theoretical foundation for the high-quality copper balls manufacturing during warm skew rolling.
Modifying “Manufacturing Processes” Laboratory for Online/Hybrid Learning Due to COVID-19
Authors: Jahan Muhammad , Hu Yingbin , Yeboah Kwaku , Stahley James
Published: January 2022

This paper aims to present innovative modifications of the contents and delivery mode of “Manufacturing Processes” laboratory for Mechanical and Manufacturing Engineering students during the global pandemic due to coronavirus (COVID-19). The objective was to maintain high level of student engagement and academic rigor, while minimizing face-to-face activities in the lab and ensuring social distancing when performing lab activities. Modifications are done in the lab to replace some of the previous activities heavily focused on machining processes with additive manufacturing, as activities focusing on machining processes need more face-to-face interactions. Out of three labs and one final project, the major modifications have been done to casting lab to make it fully online and to final project to make it about 90% online. Students were allowed for face-to-face activities that are very critical to students’ learning, and all other activities were performed virtually either by synchronous or asynchronous classes. In the other two labs (bulk deformation, i.e., forging and rolling, lab and the machining lab), students were divided into groups and they took turn to take face-to-face instructions in order to maintain social distancing and safety in the lab. Students were surveyed at the end of the semester to assess their perceptions on the modifications done in the lab and level of engagement in the course, and whether learning outcomes were achieved. Students found the level of engagement appropriate and agree that they have learned new and key concepts of various manufacturing processes and will be able to apply knowledge in the real-life applications. However, the students also reported that hybrid-mode lab instruction cannot completely replace in-person lab instruction, as many of them faced challenges to keep themselves engaged and motivated in all online lab activities.
Confinement Effects on Molecular Mechanics and Structure of the Liquid Layers at Solid-Liquid Interface
Authors: Zou An , Poudel Sajag , Maroo Shalabh C.
Published: January 2022

Liquid layer structuring occurs at the solid-liquid interface. Here we present an investigation of the confinement effects on the first layer adjacent to the solid surface in a nanopore. Compared to a thin film on a surface with free liquid-vapor interface, strong confinement effects were observed in relatively small nanopores, where only structured layers exist and the first layer is affected by both surfaces. The confinement effects are weak in relatively large pores, where bulk liquid exists and the first layer is affected by the adjacent surface only.
Development and Calibration of a Low-Cost Machine Vision Pipeline for Connected and Autonomous Vehicle (CAV) Research
Authors: Mehr Goodarz , Eskandarian Azim
Published: January 2022

Autonomous vehicles promise a safer future with a cleaner, more cost-efficient, and more reliable transportation system. However, the current approach to autonomy for vehicles has focused on building small, expensive, disparate intelligences that are closed off to the rest of the world. Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) connectivity can bridge some of that gap through enabling communication between a vehicle and its surrounding environment. This has to be paired with a low-cost approach to perception to enable broader research into and adoption of connected and autonomous vehicles (CAVs). To that end, this paper presents the development and calibration process of a low-cost, easy-to-deploy machine vision pipeline for multiple cameras that does not sacrifice image quality or frame rate. The pipeline is integrated with the CARMA Platform, developed by the FHWA for connected vehicle research.
Highly Efficient Mid-Wavelength Infrared (MWIR) Polarizer by ORMOCHALC Composite With Improved Thermomechanical Stability and Spectral Selectivity
Authors: Islam Md Didarul , Liu Sipan , Derov John , Urbas Augustine M. , Ku Zahyun , Sihn Amy , Smith Evan M. , Boyd Darryl A. , Kim Woohong , Sanghera Jasbinder S. , Nguyen Vinh Q. , Myers Jason D. , Baker Colin C. , Ryu Jong Eun
Published: January 2022

Mid-wavelength infrared (MWIR, λ = 3–5 μm) materials are of great importance due to their applications in optical sensors and devices for military, industry, and non-invasive medical diagnostics. Specifically, MWIR polarimetry has significantly improved biometric recognition and camouflaged detection. Most commercial polarizers are based on expensive inorganic materials that are heavy, fragile, and brittle. Thus a suitable polymeric material for MWIR optics is highly desired. Herein, sulfur-based organically modified chalcogenides (ORMOCHALC) polymers have been utilized to fabricate MWIR polarizers by a simple thermal imprinting method followed by Ay deposition. A parametric study to choose suitable geometry for the polarizer was conducted, and highly efficient devices were designed that possess competitive extinction coefficients to the commercial polarizers. However, a significant limitation of the ORMOCHALC polymer is that to increase the refractive index of the polymer, the chalcogenide (i.e., S) content needs to be increased, which results in reduced Young’s modulus and lower glass transition temperature. This decayed thermomechanical stability compromises the structural integrity of ORMOCHALC optical devices. In addition to polymeric MWIR polarizer fabrication, composite materials were also synthesized and characterized for future MWIR device fabrications. Poly(S-r-DIB) was reinforced with zinc sulfide nanoparticles to simultaneously improve the refractive index and the thermomechanical properties. The addition of ZnS nanoparticles significantly improved the glass transition temperature (Tg) of the ORMOCHALC (9.6 °C to 31.4 °C), and the refractive index (Δn = 6.6 %). Then, a figure of merit subwavelength wire-grid polarizers was also analyzed based on the optically and mechanically reinforced composites. If fabricated, nanoparticles reinforced polarizers will possess superior structural integrity due to higher glass transition temperature. Moreover, the polarizers show a spectral selectivity as the resonance wavelength of the transmitted-reflected curve was redshifted to larger wavelengths for ZnS reinforced ORMOCHALC composite. These polarizers with superior extinction coefficient, spectral selectivity, and improved thermomechanical stability demonstrate a border implementation opportunity in the MWIR optics.
Study on Convective Heat Transfer Characteristics of Supercritical CO2 in Printed Circuit Heat Exchanger Under Ocean Condition
Authors: Li Shulei , Liu Dechao , Qin Lei , Xie Gongnan
Published: January 2022

The supercritical carbon dioxide (sCO2) Brayton cycle has a wide application prospect in the field of the waste-heat utilization of the marine gas turbine due to its characteristics of high efficiency, compact, safety and good economy. Inspired by this, the convective heat transfer characteristics of sCO2 in PCHE under static and ocean conditions are studied in this paper. Firstly, a numerical model is established to explore the flow and heat transfer behaviors of sCO2. Then, the heat transfer enhance (HTE) phenomenon of sCO2 flowing in the PCHE channel with airfoil fin under static condition is discussed. Finally, the effects of ocean oscillation on heat transfer performance and frictional pressure drop of sCO2 were investigated under different rolling parameters. Under static state, it can be found that the secondary flow induced by the buoyancy effect obviously increases turbulent dissipation on the upper surface of the channel when mass flow of hot side is lower, which finally results in significant heat transfer difference between the upper and lower walls. However, buoyancy effect has little effect on heat transfer performance at high mass flow rate of hot side. Under rolling condition, the time-average frictional pressure drop of the cold side always increases, but the increment is small with maximum increment of 4.2%. The rolling motion has drag reduction effect on the fluids of the hot side, and the time-average pressure drop at the hot side can be reduced by 20.3% at the high mass flow rate. The time-average heat transfer performance under rolling motion tends to be strengthened, which becomes more significant at low mass flow rate of hot side. Compared with the static state, the time-average heat transfer coefficient can be increased by up to 4.0%. The results have a helpful guiding significance for the design of marine waste heat recovery system.
Tolerance Specification Model for Systematic Application of GD&T in Product Design
Authors: Petruccioli Andrea , Pini Fabio , Leali Francesco
Published: January 2022

The Dimensional Management (DM) is well known as the reference methodology for the management of dimensional and geometric variations of industrial products. Over the years, it has assumed a central role, thanks to the development of a specific design approach, known as Design for Tolerancing (DfT). Based on the Geometric Dimensioning and Tolerancing (GD&T) symbolic language, DfT allows to check and verify functional and qualitative requirements from the early design phases. Although its strength and potential to improve design optimization, DfT industrial application is still limited. Consolidated design practices, complexity of tolerance specification process, lack of support from Computer-Aided tools still limit the tolerance specification to final validation of product design. The paper aims to define a tolerance specification model for systematic application of GD&T specification. The model formalizes the identification and translation of product requirements on the components geometry, through the definition of the main step of tolerance design. Based on the integration between the GD&T-based approach and parametric three-dimensional CAD modelling, the model has been applied to validate the GD&T and the tolerance specification of two mechanical assemblies with common features. The methodology proves its general effectiveness to support engineers in tolerance design and selection of the most suitable GD&T schemes.
Parkinsons Disease: Tremor Suppression With Wearable Device
Authors: Winston Sam E. , Dehmer Riley C. , Doughty Timothy A.
Published: January 2022

Parkinson’s Disease (PD) is a neurodegenerative disorder that affects nearly a million people in the United States. Hand tremors are a well-known symptom associated with PD and result in anxiety, frustration, and malnutrition. While there is no cure, several approaches attempt to treat the symptoms. Many are invasive, including the use of pharmaceuticals and surgery [1]. Noninvasive technologies are often cumbersome and do not address the conspicuous nature experiencing tremors in public. This study is motivated by design criteria established from previous research [2], with a goal of an affordable, purely mechanical solution. In both cases, human subject testing echoed lab tests in effective tremor reduction. The extension to a wearable device gives the user the ability to hold or handle any object, or no object, with a significant reduction in tremor.

Two separate wearable devices were tested for effectiveness while the simulated user ‘held’ two different objects to simulate different applications. Biomechanical modeling of the human hand informed the development of an adjustable mechanical hand-tremor system for testing. Models of the devices and the hand-device interface were used to simulate the dynamic response of the coupled systems. Each device was secured to the mechanical hand-tremor system and harmonic stimulus and response data was collected over the range of typical tremor frequencies. The results demonstrate the versatility of both designs for reducing the oscillations associated with tremors. The Ratio of Reduction (RoR) was defined to compare the tremor amplitude of the hand-tremor system with and without the device. Both designs were considered effective for each object with a max RoR of 28.09 for Device A and a max RoR of 99.32 for Device B.
A Prediction Software to Evaluate Frisbee Movement
Authors: Yang Haowen
Published: January 2022

Frisbee is a popular item for both entertainment and professional sport. The aerodynamics study of the frisbee is crucial to understand its movement and optimize its design. In this paper, I used basic fluid analysis to investigate the effects of parameters on the flying trajectory, as well as maximum distance and maximum height of a frisbee. First, the aerodynamic forces on a moving frisbee, including lift force, drag force, and gravity, were analyzed. Second, a set of governing equations describing the movement of the frisbee was derived. Third, a Matlab-based program to evaluate the trajectory of a flying frisbee was developed. Finally, I designed the user graphic interface and published the software for public use. By inputting the settings of the frisbee movement, such as frisbee diameter, initial velocity, attack angle, wind speed, etc., any user, without knowing the aerodynamic theories, can use this software to quickly determine the trajectory and the maximum distance of a moving frisbee. With the developed software, I investigated how the parameters influence the aerodynamic characteristics and a frisbee’s flying performance.
Effect of Tensile Strain on Electron Transport Properties of Dumbbell-Shape Graphene Nanoribbons With Metallic-Semiconducting Interfaces
Authors: Suzuki Ken , Zhang Qinqiang , Qiao Xiangyu
Published: January 2022

In this study, first-principles calculations based on density functional theory (DFT) were performed to analyze in detail the electronic transport properties of dumbbell-shape graphene nanoribbons (DS-GNRs) and their strain dependence as a strong function of the combination of the basic structure of GNRs in the narrow segment and the structures at both ends of DS-GNRs. Then, the current-voltage characteristics (I-V characteristics) and orbital distributions of DS-GNRs were investigated to develop a highly sensitive DS-GNR-based strain sensor. By combining two GNRs with metallic and semiconducting electronic properties, a non-negligible transition layer (gradient Schottky barrier) was formed near the junction. The length of the transition layer was about five six-membered rings of carbon atoms. The formation of this transition layer is considered to be due to the exudation of the wave function from the wide segment to the narrow segment in DS-GNR. In the DS-GNR with metal-semiconductor interfaces, the strain dependence of the electronic transport properties was very complicated due to the presence of the transient Schottky barrier. On the other hand, in a DS-GNR consisting of two metallic GNRs, the Schottky barrier and the transition layer disappeared, and stable current-voltage and piezoresistive characteristics close to those of a single GNR were observed. The predicted gauge factor of DS-GNRs was larger than that of conventional metal foils (gauge factor 2–5) and close to that of conventional polysilicon (gauge factor ±30). These results indicate that DS-GNRs have the potential to produce highly sensitive and reliable strain sensors.
Optimizing Power Output of a Wave Energy Converter by Employing Superposed Hydrodynamic Model
Authors: Kathyayani Nandakumar , Samad Abdus
Published: January 2022

Optimization of wave energy converters (WECs) through robust controls is mandatory to maximize the energy absorption in the face of sea waves’ stochastic nature. Single optimization criterion predicted by linear models is rendered ambiguous when modulated by viscous forces, dominant at the controlled conditions. An efficient hydrodynamic model capable of identifying suitable parameters for nonlinear controller design is desirable but missing. Hence, this paper proposes a superposed hydrodynamic model (SPHM) to optimize the power output of a scaled-down point absorber WEC. Two variants of SPHM are considered to evaluate the differences between linear and nonlinear viscous models. Optimization is guided by a non-predictive latch control strategy. The model is numerically solved using the fourth Runge-Kutta method to obtain the time domain response of buoy. The nonlinear SPHM reveals a new optimization parameter based on the maximum velocity criterion. At off-resonant states, the controller enhances the system power by eleven times.
An Ultra-Compliant and Flexible Structural Sensing Neural System for Damage Detection in Wind Turbine Blades
Authors: Wang Junzhen , Shen Yanfeng , Peng Xuezhi , Han Zhengyang , Jiang Shaopeng
Published: January 2022

This paper presents a new ultra-compliant and flexible structural sensing neural system for damage detection in wind turbine blades. The entire sensing cluster is integrated inside a flexible printed circuit (FPC), which complies the structural geometric features as a neural skin planted on the structural surfaces. It is worth of noting that the proposed sensing system can be mounted on arbitrary locations of a wind turbine blade, mimicking the neurons of the human biological system to detect and monitor the damage in the blade. Besides, all the sensing elements are interfaced with a laptop-controlled data acquisition board to receive the structural dynamic responses. In addition, a miniature electromagnetic actuator is utilized to excite the blade. Additional mass is employed to simulate the damage situation. Several signal processing techniques are implemented to analyze the oscillatory responses, such as wavelet analysis, fast Fourier transform (FFT), and short time Fourier transform (STFT). Furthermore, the damage indices (DIs) which correlate the structural spectral power density of both pristine and damaged cases can accurately identify the location of damage. Such a sensing neural system possesses the tremendous potential in future Structural Health Monitoring (SHM) and Nondestructive Evaluation (NDE) applications. This paper finishes with discussion, concluding remarks, and suggestions for future work.
A Numerical Study Into the Importance of Equivalence Ratio Measurement Accuracy for Spark Ignition Engines
Authors: Yang Ruomiao , Sun Xiaoxia , Liu Zhentao , Zhang Yu , Fu Jiahong
Published: January 2022

The internal combustion engines will continue to be the major power source for transportation. Spark ignition (SI) engines are still widely used for mobility due to their wide range of operating conditions. The engine key operating variables are primarily controlled by an already calibrated engine control unit (ECU). However, a less precise sensor may lead to larger variations in engine performance and emissions. The goal of this study was to investigate the importance of an air-fuel ratio sensor sensitivity during various engine operations. A one-dimensional (1D) computational fluid dynamics (CFD) model was utilized in this study to analyze the engine responses caused by a slight change of equivalence ratio at various engine speeds and loads. The results indicated that variations in the fuel-air ratio had a significant effect on emissions. Carbon monoxide was most sensitive to the air-fuel ratio, followed by nitrogen oxides, while unburned hydrocarbons were not sensitive to it. For engine performance, it varied slightly with small changes in the fuel-to-air ratio. The results also demonstrated that at higher engine speeds, slight changes in the air-fuel ratio resulted in smaller changes in emissions. Overall, for precise combustion control, it is recommended that the accuracy of the sensor is higher than 1% at least for the engine investigated in this study.
Development of a Robust and Real-Time Thermal Deformation Prediction System for Machine Tool by Multi-Point Temperature Measurement
Authors: Tanaka Shun , Marukawa Yuya , Kizaki Toru , Tomita Kenichi , Tsujimura Shinji , Noda Daisuke , Kobayashi Hisashi , Sugita Naohiko
Published: January 2022

More than 70% of machining errors in machine tools are caused by thermal displacement. In this paper, we proposed a method of estimating for thermal displacement by measuring the temperature at a large number of points to achieve high-precision machining under disturbances such as cutting fluid. The sensor locations were determined from the results of the thermal simulation in which the heat generation at various heat sources, such as bearings and ball screws, were determined according to the results of the operational tests. The tool center point (TCP) error was estimated from the temperature distribution measured by 284 temperature sensors. The proposed method reduced the estimation error by 50% compared to the conventional method with 17 temperature measuring locations, and the accuracy was confirmed to be unchanged even when cutting fluid was supplied. In addition, a real-time method to estimate TCP relative displacement was developed to implement thermal deformation compensation in a machine tool. Considering actual machining, it is necessary to reduce the computational load of the finite element method (FEM) or to consider a faster displacement estimation model to output the TCP relative displacements at multiple points. By implementing this thermal displacement estimation system, it may be possible to achieve high-precision machining even with machines that do not have high precision.
Evaluation of Normalization Methods in a Cerebral Artery Atlas for Automatic Labeling
Authors: Jin Kazuyoshi , Kitamura Ko , Mugikura Shunji , Mori Naoko , Ohta Makoto , Anzai Hitomi
Published: January 2022

An existence probability atlas has been used for automatic labeling of cerebral arteries. However, the number of arteries varies frequently because of image quality and individual variation of the artery structure. To moderate the influence of number imbalance on labeling accuracy, we propose a new normalized atlas for automatic labeling of cerebral artery centerlines.

The number of arteries, which was obtained from magnetic resonance angiography, varies from 11 to 46 among the artery sites. Based on the centerline and diameter, the arterial volume was reconstructed into a voxel space for each subject. After superimposing arteries from 46 subjects, three normalization methods were compared: dividing by the number of subjects (N), by N and the arterial length (L), and by N and the arterial volume (V). To compare the labeling accuracy and precision, the summation of probability and labeling method was also used.

The accuracy of all normalization methods was > 85% in all arteries. The precision improved in some parts, with the atlas normalized by N-L and by N-V. The use of N-L and N-V changed the relative value of the existence probability among the parts. Consequently, some normalization methods changed the tendency toward misclassification, which changed the precision.
Stochastic Predictive Control for Crash Avoidance in Autonomous Vehicles Based on Stochastic Reachable Set Threat Assessment
Authors: Khattar Vanshaj , Eskandarian Azim
Published: January 2022

Unexpected hazardous road situations frequently arise on the roads, which lead to crashes. Detecting a threat in advance and generating a fallback trajectory are some of the major challenges faced by autonomous vehicles. Stochastic Model Predictive Control (SMPC) approaches have recently proven to be highly effective in controlling systems in highly uncertain environments. However, the chance-constrained formulation of the SMPC makes it computationally expensive for fast real-time implementation. This paper presents a fast, proactive decision-making approach for crash avoidance in autonomous vehicles based on SMPC. Two problems are addressed in this study: 1) Assessing threat to the autonomous vehicle from the surrounding vehicles and 2) Fast safe trajectory generation for the autonomous vehicle in case of a future predicted crash. Threat assessment is addressed using stochastic reachability analysis for the surrounding vehicles, which accounts for surrounding drivers likely future motion and intents. We have proposed a fast, proactive decision-making algorithm to generate crash avoidance trajectories based on Stochastic Model Predictive Control (SMPC). We reformulate the SMPC probabilistic constraints as deterministic constraints using convex hull formulation, allowing for faster real-time implementation. This deterministic SMPC implementation ensures in real-time that the vehicle maintains a minimum probabilistic safety. It is shown that the proposed decision-making approach is successful in avoiding crash scenarios with a medium risk factor range.
Methodical Modeling of Product and Process Data of Design Methods Using the Example of Modular Lightweight Design
Authors: Hanna Michael , Schwede Lea-Nadine , Schwenke Johann , Laukotka Fabian , Krause Dieter
Published: January 2022

This paper shows how the methodically modeling of product and process data of design methods using the example of modular lightweight design to improve data traceability and continuity can be implemented. Therefore, the underlying methods from the areas of modular lightweight design, Model-Based Systems Engineering and methodical process steps are analyzed and their challenges collected. As basis a data-driven linkage of product and process models for methods is used. To establish this within the method of the modular lightweight design, the six main steps were analyzed with regards to possible inconsistencies and links. In this context, it is particularly important which input and which output data are required or generated in each of these steps. Using this information, the link between the process and product data models can be established. With this link, the consistency and continuity of the data can be improved, as uses and changes in one step can be traced to other relevant steps. Because the data itself now is more consistent, the steps and the method itself provide a better consistency and continuity. A SysML-model is presented, with which the product data model can be consistently linked with the process data model, based on a data tree. This integrated process and product data model is applied to aircraft cabin development to develop a continuous, consistent models in a methodical manner.
An Integrative and Transdisciplinary Approach for a Human-Centered Design of AI-Based Work Systems
Authors: Schlicht Larissa , Melzer Marlen , Rösler Ulrike , Voß Stefan , Vock Silvia
Published: January 2022

Psychological and ethical criteria are to date not systematically covered in the system design process. We suggest to extend existing model-based system engineering approaches by new elements that are capable to capture these criteria and, in particular, allow for an implementation of psychological risk analysis and ethical evaluation of work systems already in the design phase.

The need for a systematic integration of not only safety but also ethical and psychological criteria in the system design is strengthened by the growing complexity of work systems and the increasing use of artificial intelligence-based algorithms, which have the potential to replace distinctive human capabilities and are associated with a shift of responsibility from humans to machines.

We identify essentially two factors impeding the development of an innovative integrative system design approach. First, at present, there is no legally predefined iterative process including an open feedback loop between the operator and the system designer that enables continuous risk assessment.

Second, available methods do not provide a framework to integrate ethical and psychological criteria.

We propose four steps for the development of an integrative system design approach: (1) an in-depth investigation of current methods suitable for holistic system design processes, (2) the development of a transdisciplinary terminology, (3) the development of a procedure which allows to identify ethical criteria meeting both individual and societal requirements and (4) testing of the developed approach in a digital system model by using a suitable use case.
Leveraging Vibrations and Guided Waves in a Human Skull
Authors: Kohtanen Eetu , Mazzotti Matteo , Ruzzene Massimo , Erturk Alper
Published: January 2022

This work is centered on high-fidelity modeling, analysis, and rigorous experiments of vibrations and guided (Lamb) waves in a human skull in two connected tracks: (1) layered modeling of the cranial bone structure (with cortical tables and diploë) and its vibration-based elastic parameter identification (and validation); (2) transcranial leaky Lamb wave characterization experiments and radiation analyses using the identified elastic parameters in a layered semi analytical finite element framework, followed by time transient simulations that consider the inner porosity as is. In the first track, non-contact vibration experiments are conducted to extract the first handful of modal frequencies in the auditory frequency regime, along with the associated damping ratios and mode shapes, of dry cranial bone segments extracted from the parietal and frontal regions of a human skull. Numerical models of the bone segments are built with a novel image reconstruction scheme that employs microcomputed tomographic scans to build a layered bone geometry with separate homogenized domains for the cortical tables and the diploë. These numerical models and the experimental modal frequencies are then used in an iterative parameter identification scheme that yields the cortical and diploic isotropic elastic moduli of each domain, whereas the corresponding densities are estimated using the total experimental mass and layer mass ratios obtained from the scans. With the identified elastic parameters, the average error between experimental and numerical modal frequencies is less than 1.5% and the modal assurance criterion values for most modes are above 0.90. Furthermore, the extracted parameters are in the range of the results reported in the literature. In the second track, the focus is placed on the subject of leaky Lamb waves, which has received growing attention as a promising alternative to conventional ultrasound techniques for transcranial transmission, especially to access the brain periphery. Experiments are conducted on the same cranial bone segment set for leaky Lamb wave excitation and radiation characterization. The degassed skull bone segments are used in submersed experiments with an ultrasonic transducer and needle hydrophone setup for radiation pressure field scanning. Elastic parameters obtained from the first track are used in guided wave dispersion simulations, and the radiation angles are accurately predicted using the aforementioned layered model in the presence of fluid loading. The dominant radiation angles are shown to correspond to guided wave modes with low attenuation and a significant out-of-plane polarization. The experimental radiation spectra are finally compared against those obtained from time transient finite element simulations that leverage geometric models reconstructed from microcomputed tomographic scans.
Wet Gas Hydrocarbon Centrifugal Compressor – Performance Test Results and Evaluation
Authors: Mæland Dagfinn , Bakken Lars E.
Published: January 2022

In the oil and gas industry a large portion of the compressor feed streams are characterised as wet gas, with a liquid volume content of between zero and five percent. Typically, this liquid is separated upstream of the compressor and handled separately. Such compressor systems have a large footprint, high weight, and high cost. In addition, if the liquid separation is not sufficiently good, trace amounts of liquid will enter the compressor and eventually cause fouling and performance degradation and possibly mechanical damage. The promising technology of wet gas compression is attractive to the oil and gas producers as it attempts to simplify the compressor systems thus reducing the footprint, weight, and cost. Furthermore, if the liquid amount is always sufficient to allow for liquid at the compressor discharge, fouling will not occur as the machine is continuously washed. This can allow for wet gas compressors continuously operating for years without any interventions. Installing such a wet gas compressor near the well head will provide increased recovery from the reservoirs.

Wet gas compressors are designed and used in a variety of operating conditions. Dependent on reservoir depletion, well stream compressors experience a gradual shift in inlet pressure and fluid behaviour. A major challenge both to designers and operators of wet gas compressors, is related to the impact of changing fluid conditions, such as gas mass fraction and density ratio, on performance.

Several single stage, two stage and multistage wet gas compressor test campaigns have been conducted at K-Lab. A large range of inlet conditions has been tested, i.e. inlet pressure ranging from 12 to 110 bar, gas mass fraction between 0.7 and 1.0, and combinations of hydrocarbon gas, hydrocarbon liquid, and water have been used as test fluids.

Performance test results from one of these wet gas test campaigns are presented in order to expose the impact of variables such as the fluid density ratio. The reference full-scale tests were conducted in real conditions i.e. realistic hydrocarbon composition, pressures, and temperatures. A large range of suction pressures were investigated, with a gas mass fraction ranging from 0.7 to 1.0. The density ratio between gas and liquid is of great importance as it relates to the flow regime, phase segregation and phase slip. Special emphasis is made to relate the performance shift between dry and wet conditions to the density ratio and other wet gas parameters, and a model is proposed that will incorporate these parameters to this shift.
Optimization of Injection-Molding Parameters for the Warpage of Green Parts of Metal Injection Molding by the Taguchi Method
Authors: Chung Chen-Yuan , Chen Yu-Peng
Published: January 2022

Historically, metal injection molding (MIM) is a fairly new injection-molding technique; it can realize parts with a complex exterior that are otherwise highly difficult to produce and thus remarkable widen the scope of powder metallurgy application. MIM has been applied to the production of precision metal parts due to its advantages of high productivity and high complexity. MIM has been developed as a powerful method for manufacturing high value-added metal components. Control of the injection-molding process is crucial. The combination of feedstock, which is composed of a binder and metal powder, also complicates the rheological behavior. Therefore, powder–binder separation often occurs during the filling stage. Injection-molding simulation is an effective tool for predicting the molding process.

The procedure for analysis has two major steps. First, flow front simulation is performed to validate the experimental short-shot results. Second, the experimental design of the Taguchi method is adopted to determine the optimal process parameters to reduce the green parts’ warpage. This approach eliminates the inherent uncertainties when operators have different levels of experience.

The short-shot results demonstrate that the simulated flow front is similar to the experimental one. Furthermore, the position of the weld line can be well predicted. The Taguchi method for minimized warpage shows improved dimensional precision. Moreover, the optimal process parameters can reduce the cycle time of three seconds compared with the original process parameters, which significantly benefits dimensional precision and the production rate.
Modeling Air Flow in Pathological Human Airway With Patient Specific CT-Data
Authors: Islam Adnan , Rouhollahi Amir , Lauria Michael , Santhanam Anand , Ilegbusi Olusegun
Published: January 2022

This study investigates the effects of different pathological conditions of human trachea on flow distribution in the tracheo-bronchial tree (TBT) of human airways. Pathological conditions including hereditary Left Pulmonary Artery Sling (LPAS) and Chronic Obstructive Pulmonary Disease (COPD) often cause stenosis in the tracheal airway while a widening of the airway has been reported for patients with pulmonary fibrosis. This study assesses the airflow distribution in the human airway under such pathological conditions relative to normal flow condition, utilizing Computational Fluid Dynamics (CFD). Realistic 3D airway geometry is first reconstructed from anonymized CT scan data of human respiratory system and used for the CFD analysis. Specific pathological conditions are simulated by the modification of the tracheal geometry to account for the consequent shape deviation, and the resulting flow in the central airway is analyzed. Different breathing conditions (rest and mild activity) are modeled by imposing appropriate boundary conditions. The results demonstrate marked dependence of the predicted flow distribution and wall shear stress in the trachea on the pathological conditions. Tracheal stenosis exhibits mass flow split between the right and left bronchi similar to healthy case while bronchial stenosis significantly changes the mass flow split with less air coming out of the left main bronchus compared to the healthy case. The next phase of the study aims to assess the effect of the upstream vessel obstruction on the spatio-temporal airflow distribution in the lung and the overall breathing pattern. Such capabilities will directly address the regional flow distribution associated with diseases such as COPD and LPAS.