bluuebunny/crossref_metadata_2025 huggingface dataset:
Turbocharged Decoupling and Turbine Electrification Design for Mild-Hybrid Vehicle
Authors: Capata Roberto
Published: January 2022

The research aims to verify the feasibility of an on-the-road prototype of a power train for a hybrid-powered vehicle. The current propulsion systems are built to increase the power of internal combustion engines as much as possible. The aim is to achieve this by keeping the size of the engine contained, but the complexity is such that to increase the power of a powertrain, maintaining its original dimensions and geometries unchanged, therefore its displacement, it is necessary to increase its maximum speed of rotation (rpm) or to increase the thermal and volumetric efficiency of the engine itself. It has been seen that the increase in power can be achieved through supercharging, i.e. through the introduction of a greater amount of air inside the cylinder, improving, through this device, the filling coefficient and therefore the volumetric efficiency. In addition, the research status is focused on ensuring lower fuel consumption, with cleaner and more efficient engines, in line with stringent anti-pollution regulations. This need has generated technical solutions such as downsizing and down speeding, for which it has been possible to reduce the number of cylinders, displacements, and rotational regimes in favor of efficiency. It should not be forgotten in this context the efforts made to ensure the reduction of the phenomenon of turbo-lag, together with the need to improve the operation of the engine in transients, especially at low speeds where greater torque is required. In detail, the study focuses on decoupling the overfeeding group. The preliminary proposal is to mechanically disconnect the compressor/turbine complex, supporting the rotation of compressor C with a dedicated electric motor and creating a turbine T connected to a generator. Mechanical decoupling C/T allows both machines to be designed so that they operate near the maximum efficiency point for most of the expected real operating range. Thus, the turbine will presumably have a slightly lower rotational speed than the original group and will therefore be slightly larger. Since the turbine is now disconnected from the compressor, the surplus is recovered at the high speeds that are usually discharged through the waste-gate valve, providing further turbine expansion. The subsequent generation of additional electrical power, can, after being cut from that required by the electric motor + compressor complex, be used where required (for example to power auxiliaries or recharge batteries in hybrid configuration). The study concludes, at the moment, with the evaluation of mechanical and thermal stresses (through a FEM analysis) to evaluate the coupling with the high-speed electric generator.
3D-Printed Hierarchical Re-Entrant Honeycomb With Improved Structural Stability Under Quasi-Static Compressive Loading
Authors: Zhan Chi , Li Mingzhe , McCoy Robert , Zhao Linda , Lu Weiyi
Published: January 2022

Re-entrant honeycombs with negative Poisson’s ratio have shown great potential as lightweight energy absorbers for various applications. However, due to its bending-dominated behavior, the structural stability and energy absorption capacity of reentrant honeycombs are yet to be further improved. It has been demonstrated that hierarchical structures exhibit a combination of lightweight and superior mechanical properties. We hypothesize that by introducing the triangular hierarchical substructures into the conventional cell walls, the bending-dominated behavior of re-entrant honeycombs can be converted into the stretching-dominated one. Consequently, the overall structural stability of the hierarchical re-entrant honeycombs can be promoted through local deformation of hierarchy, which can potentially benefit the energy absorption capacity of the resulted structure.

To test our hypothesis, we first fabricate the hierarchical reentrant honeycombs with length scale ranging from micrometer to centimeter using Polyjet 3D-printing technique. Regular reentrant honeycombs with solid struts have been fabricated as baseline structures. The mechanical performance of the honeycombs has been characterized through uniaxial quasi-static compression tests. Besides, the local deformation mechanisms of the hierarchical structure have been revealed by the Digital Image Correlation (DIC). In comparison to the regular re-entrant honeycomb, the global failure strain of hierarchical re-entrant honeycomb is enhanced by 36%. This is due to the improved structural stability from local fracture and densification of the triangular hierarchy. Both the regular and hierarchical honeycombs exhibit the same specific energy absorption capacity. As predicted by the existing scaling laws, the hierarchical re-entrant honeycomb has great potential to outperform regular one by optimizing the relative density of the structure.

A finite element model of the hierarchical re-entrant honeycomb has been developed by using commercial software Abaqus/CAE 2020. The model has been calibrated by the experimental data. Within the elastic region, the simulated deformation modes show good agreement with experimental observations. When the relative density of the regular re-entrant honeycombs equals to the hierarchical ones, the model predicts that the hierarchical re-entrant honeycombs have superior energy absorption performance with enhanced stiffness and yield strength in comparison to the regular ones.

In conclusion, this study has demonstrated that by introducing hierarchical structure into re-entrant honeycomb, the structural stability has been improved. Furthermore, the hierarchical structure endows re-entrant honeycomb with lightweight yet competitive energy absorption capacity.
Investigation of a Coanda-Effect Enhanced HVAC Diffuser Using CFD Analysis
Authors: Kokash Hussein , Burzo Mihai G. , Khanafer Khalil , Gokeda Bharat
Published: January 2022

In this investigation we show how better air diffuser designs can help optimize the air mixing process in a typical office room, thus achieving better thermal comfort with less energy consumption. The ANSYS Fluent software was used to investigate the flow behavior of the air supplied to the office room through a newly proposed Coanda effect enhanced diffuser. This was done for both the heating and cooling modes of the HVAC system. The proposed diffuser promotes the Coanda effect by delivering airflow jets which “hang” longer to the ceiling without the need for additional energy. The advantages of the new design are showcased by comparing its performance with that of an existing diffuser, namely the widely used “Multicone” design, where the flow is ejected at a predetermined angle. Various performance and ASHRAE Standard 55 thermal comfort parameters of building occupants are computed. The results show that the proposed diffuser presents a distinct advantage over existing designs, especially in cooling mode where it outperforms the standard Multi-cone diffuser by achieving better energy consumption and thermal comfort for the same input parameters. An added advantage of the proposed design is that it is expected to be cost effective to produce and install.
Numerical Modeling of a T-Junction Static Micromixer With a Periodic Porous Architecture
Authors: Alzoubi Mahmoud A. , Al-Ketan Oraib , Muthusamy Jayaveera , Sasmito Agus , Poncet Sébastien
Published: January 2022

The interest in static micromixers has increased in recent years due in part to their compact design, high area-to-volume ratio, and the absence of moving parts. The passive mixers rely mainly on the flow energy provided by the pumping system. These advantages give passive mixers an apparent edge over conventional active mixers. On the other contrary, the microflow in the static mixers typically occurs in a laminar regime at a low Reynolds number, which leads to a low mixing performance. The mixing is mainly dependent on the diffusion and the impinging of two opposite streams. To obtain a better mixing efficiency, a porous structure could be installed in the mixer’s microchannel. However, a higher pressure across the mixer is to be expected. This paper introduces an innovative mixing enhancement method based on a triply periodic minimal surfaces (TPMSs) porous structure using additive manufacturing (AM) processing. The AM technology presents great potential to develop and optimize various porous matrices that could be used in advanced micro and nano-devices. Gyroid matrix has the capability to provide a better mixing performance at a moderate pressure drop compared to other TPMSs structures. Therefore, in this study, a Gyroid structure is placed in the downstream channel, aiming to boost the mixing performance. A three-dimensional mathematical model that considers conservation of mass, momentum, and species has been derived and implemented to simulate the effect of the proposed structure on the mixing index, pressure drop, and performance index. The latter is introduced as an optimization term to ensure that the optimal configuration will provide high mixing at a relatively low-pressure drop. A parametric study highlighting the impact of Reynolds and Schmidt numbers on the mixing efficiency has been conducted. The results compare the mixing index, pressure drop, and performance index of a micromixer filled with a 20% porosity Gyroid matrix with an identical plain mixer. The results indicate that the Gyroid porous structure significantly improves the mixing efficiency by almost 172%, especially at higher Reynolds numbers (Re = 100 and 500). The penalty, however, is a higher pressure drop. Therefore, installing these structures requires careful consideration during the design and fabrication stage to ensure optimal performance. In addition, the results suggest that the impact of the Schmidt number on the mixing index decreases with increasing Reynolds number. The effect is negligible at Re = 500. The proposed structure could be used to enhance the mixing performance of micromixers in chemical or pharmaceutical applications.
On the Dynamics and Optimal Control of the Rotational Inverted Pendulum
Authors: Borrás Pinilla Carlos , González Diaz Alan Javier
Published: January 2022

The rotational inverted pendulum (Furuta pendulum) was designed and built in the laboratory of the school of mechanical engineering of the Universidad Industrial de Santander as a learning challenge of implementing control strategies for graduate students. In this research work, it’s developed a full dynamics model using Lagrangian formulation. The math dynamic model includes real physic parameters, the mass of each component, inertia terms, dimensions, viscous frictions, and DC high torque motor dynamics.

With a linearized state-space model of the system dynamics, the PID approach and the optimal control gain for the linear quadratic regulator (LQR) controller and the linear quadratic Gaussian (LQG) regulator were computed and the dynamic and disturbance response were evaluated and compared for each control strategies to determine the best performance: a lower percentage of Peak Overshoot (PO). Steady-State Error (Ess), lower settling time (Settling Time (Ts)) and control (u) cost.

PID controller presented the lowest performance in the control response to disturbances, unlike LQR, this does not take into account the cost-performance ratio, the controllers LQG and LQR modeled in the state space produce a feedback gain matrix which allows the Furuta pendulum to have regulated behavior making the pendulum quickly find the equilibrium point.
Digital Twin Additive Reconstruction Tool for Micromechanical Modeling of 3D-Printed Parts
Authors: Gidwani Akshay , Vasilyan Hayk , Susantyoko Rahmat Agung , Alyammahi Mozah
Published: January 2022

This paper aimed to implement a Digital Twin Additive Reconstruction tool to create an explicit characterization of layer-by-layer 3D printed parts in CAD software. While there have been previous approaches to 3D printed CAD reconstruction, they have either faced shortcomings in depicting the internal structure accurately or have had accurate depictions of internal structure at the cost of computational time, multiple software interfaces, and complicated workflows.

The novelty of our approach lies in outlining a principle of digital twin reconstruction that can be applied to multiple CAD software while keeping a separate universal G-Code Parser module written in Python script. The later module can be adapted to any CAD interface in principle. Our method tried to maintain a simple workflow without compromising the accuracy of internal structure yet preserves the integrity of the reconstructed module per CAD interface without loss of information. Moreover, the user can reduce the computational time by excluding the Boolean Union operation if necessary and selectively reconstruct and union just specific layers upon specifying the layer numbers in our algorithm.
Methods of Dealing With Co-Products in a Life-Cycle Assessment of Biodiesel Fuel Produced From Waste Cooking Oil
Authors: Torres Hannah , Macken Nelson
Published: January 2022

Biodiesel fuel has received considerable attention as a more sustainable alternative to traditional fuel. This paper presents a life cycle assessment (LCA) for producing biodiesel fuel from waste vegetable oil (WVO). Comparisons are made for different methods of dealing with additional products. The LCA is a cradle to fuel model that includes the following unit processes: soybean farming, soy meal and soy oil extraction, processing of soy oil, cleaning/drying waste oil, transesterification to produce useful biodiesel and transportation to various sites. Metrics evaluated to determine sustainability include global warming potential (GWP) and cumulative energy demand (CED). Values are obtained using GREET1. Credits for additional products must be applied in the LCA. WVO is a byproduct of oil produced for cooking fried products. We account for oil consumed in the cooking process using two approaches. In the first approach, the amount of oil consumed in the cooking process is credited to the WVO. All the cooking oil is considered WVO. In the second approach, the WVO is considered a “free” product. This means only the CED and GWP associated with WVO transportation, processing and transesterification are included in the LCA. Other co-products are considered applying two traditional methods used in LCA: mass-based allocation and displacement. In mass-based allocation, CED and GWP are adjusted considering the mass fraction of soy oil produced from soybeans and the mass fraction of biodiesel produced from WVO in the transesterification process. In the displacement method, soymeal is considered to displace soybeans as animal feed and glycerin displaces synthetic glycerin. The CED and GWP of the displaced products are subtracted as credits. LCA results for the various approaches to additional products are compared. We demonstrate a wide range of results are possible. These results should provide useful information for dealing with additional products in determining the sustainability of producing biodiesel fuel from waste vegetable oil.
Probabilistic Study of Corrosion Pit-Induced Fatigue
Authors: Starr Benjamin , Shishkin Serge L. , Sahay Chittaranjan , Ghosh Suhash
Published: January 2022

Corrosion fatigue is the major damage mechanism responsible for the premature failure of the aircrafts and turbine parts, especially in the marine environment. It has been seen that even relatively mild corrosive atmospheres can reduce the fatigue strength of many structures considerably as compared to their fatigue strength in dry air. The process starts with the surface degradation due to the corrosion pits, that become fatigue initiation sites and the initial damage when the part is loaded. Microstructure and morphology of the surface pits is critical for the crack initiation. It is assumed that the cracks are initiated at the sharp corners and bottoms of the narrow “micropits”. The paper provides a statistical characterization of the crack initiation process based on these pits’ density and microstructure distribution. Based on the surface damage initiation analysis, new morphological characteristics combining the pit size and highest curvature are introduced and have shown to be the efficient metrics for pitting fatigue with the distribution of introduced morphological characteristics. The distribution of these characteristics is estimated from the measured data. Effects of pitting morphology are evaluated for various heat-treated Aluminum 2024 specimens, with varying distribution of pit shapes and curvatures. The statistical distribution of specimen life is estimated using the “weakest link” approach, that is, by computing the probability that at least one crack is initiated anywhere on the surface. The paper contains a detailed description of crack initiation’s statistical model, methodology of corrosion parameter estimation and representative numerical examples of statistical modeling. The surface pit characterization has been nondestructively measured on a Zygo ZeGage 3D profiler. The ZeGage uses a Coherence Scanning Interferometry (CSI) technique which uses the wavelength of light to define its high precision. A carefully calibrated CSI profiler can measure a larger range of surface qualities with repeatable results in sub-nanometer precision. High magnification (20x, 50x, 100x) lenses increase the versatility in measuring even smoother surfaces. Large area scanning was done using a segmentation approach. A large field of view of the selected lens and automated rapid scanning allowed for reasonably smaller data files obtained after stitching these individual segments.
An Artificial Neural Network Model for Flexoelectric Actuation and Control of Beams
Authors: Yu Pengcheng , Fu Xiaogang , Fan Mu
Published: January 2022

The converse flexoelectric effect has been applied to precision actuation and vibration control of flexible structures. High stress concentration caused by a single flexoelectric actuator can be alleviated by placing multiple actuators on the structure. In the presented work, a neural network model was established to optimize the positions of multiple flexoelectric actuators on a cantilever beam. It was proved that the neural network can recognize the relationship between actuator position and tip displacement and forecast the tip displacement of the beam accurately with reduced computational effort and higher effectiveness. By using the neural network, the displacement data generated by all possible combinations of actuator positions were predicted, and the optimal positions of multiple flexoelectric actuators can be obtained in term of maximum transverse tip displacement. The effect of actuator size with various actuator numbers was discussed. The results showed that applied voltage can be reduced by increasing the number of flexoelectric actuators when placed on optimal positions.
Feasibility of Pumped Hydroelectric Storage Within Existing USACE Facilities: a Methodological Approach
Authors: Kass Kyle J. , Davidson F. Todd
Published: January 2022

Variable, renewable energy (VRE) generation such as solar power has seen a rapid increase in usage over the past decades. These power generation sources offer benefits due to their low marginal costs and reduced emissions. However, VRE assets are not dispatchable, which can result in a mismatch of the electric supply and demand curves. Pumped-storage hydropower (PSH) seeks to solve this by pumping water uphill during times of excess energy production and releasing the water back downhill through turbines during energy shortages, thus serving as a rechargeable battery. Creating new PSH systems, however, requires a large amount of capital and suitable locations. The United States Army Corps. of Engineers (USACE) is the largest producer of hydroelectric power within the United States, and as such, may have favorable sites for the addition of PSH. This study seeks to develop a method for evaluating these existing hydroelectric facilities using techno-economic methods to assess the potential for adding PSH. Each USACE facility was evaluated based on site specific characteristics from previously unpublished data to estimate the power generation and energy storage potential. The temporal nature of local wholesale electricity prices was accounted for to help estimate the financial feasibility of varying locations. Sensitivity analysis was performed to highlight how the method would identify the viability of facilities with different operational conditions. The methodologies detailed in this study will inform decision-making processes, and help enable a sustainable electric grid.
Effects of Turbulence Modeling and Turbulent Schmidt Number on Supersonic Mixing Simulations
Authors: Chowdhury Md. Navid , Aziz Sarfaraz , Shingh Shanto Kumar , Ali Mohammad , Amin M. Ruhul
Published: January 2022

The supersonic mixing flow field of a Helium jet in cross-stream air is numerically simulated in the present study by solving the two-dimensional Reynolds-Averaged Navier-Stokes equations. Turbulence contribution is obtained from the Realizable k-ε and the SST k-ω model. Each model is incorporated separately with four different turbulent Schmidt numbers, i.e., 0.50, 0.35, 0.25, and 0.20. The focus of this paper is to guide the selection of a suitable turbulence model with an appropriate turbulent Schmidt number for these types of complex mixing simulations. The results show that both of the models can predict the general flow behavior while exhibiting their advantages. A better agreement with the experimental data is obtained when the turbulent Schmidt number is gradually decreased. However, examining the critical characteristics like upstream flow separation, bow shock prediction, and mass concentration of Helium the SST k-ω model with turbulent Schmidt number 0.20 can be considered for the reasonable estimation of the supersonic mixing flow field.
Terrestrial Mission Extender for Weather Balloon Radiosonde
Authors: Chun Carrington , McBride Joseph , Torabzadeh Kaveh , Smith Andrew , Roberts Santana
Published: January 2022

Thousands of balloon-assisted meteorological sensor packages, known as radiosondes, are launched every day from various monitoring stations across the continental United States. However, only a small fraction of these instrument payloads are ever recovered, with most ending up as hazardous electronics waste strewn across the country. By creating a terrestrial landing system that can be retrofitted to common commercially available radiosondes, the landing survivability of these instrument payloads may be able to be improved. Furthermore, such a landing platform could also support continued meteorological data acquisition and transmission, allowing the radiosonde to transition from high-altitude monitoring to surface level sensor monitoring. Not only would such a terrestrial mission extension module fitted to a radiosonde drastically increase the potential utility of an existing radiosonde, but such a device could also improve radiosonde recovery rates, and therefore reduce the electronics waste being produced by regular weather balloon launches.
An Approach to Variation Simulation of Final Aircraft Assembly With Presence of Sealant
Authors: Eliseev Artem , Lupuleac Sergey , Grigor'ev Boris , Shinder Julia
Published: January 2022

Sealant is usually put between joined parts of an aircraft prior to final assembly. This paper presents an attempt to estimate the influence of sealant on assembly quality in terms of variation analysis. The modeling approach is based on simulation of two-way coupled fluid-structure interaction between fluid sealant and compliant parts. Reynolds lubrication approximation is used in the fluid dynamics problem and variational formulation of contact problem combined with static condensation is used in the structural one. An approach based on initial gap modelling is used for variation analysis.

The joining of two aircraft panels is used as a numerical test for demonstration of developed approach. Various phenomena connected with the presence of sealant are demonstrated. In particular, the difference in fasteners loosening due to sealant flow between different types of fasteners was investigated. Results of variation simulation show that presence of sealant may be considered among determining factors in the analysis of assembly quality.
Methods for the Design of Individual Mechanisms for the Fabrication by Additive Manufacturing
Authors: Schroeffer Andreas , Irlinger Franz , Lueth Tim
Published: January 2022

Additive Manufacturing (AM) enables the quick and cost-effective generation of complex geometries and therefore new business models such as individualized products. The time-consuming step thereby is no longer the production, but the design of the parts. The key to solve this issue is the development of algorithms for automated process-specific design.

Currently, the design process for parts fabricated by AM is still characterized by the procedure used for traditional fabrication processes. Several manual steps are necessary, requiring time and expert knowledge.

At our institute, a MATLAB integrated design toolbox is developed, trying to overcome these issues. The basic idea is an algorithmic approach to design problems and a direct generation of surface models that can be fabricated in an AM process. It can be used to realize design tools that allow to define parts by their functionality and not by their geometry.

In this work, the toolbox is used to create automated design algorithms for individual compliant mechanisms. A novel droplet-based AM process enabling hard/soft multi material printing is used to fabricate the parts. The scope of the software provides a component library of flexure hinges, mechanical connectors, and grippers that are generated from functional descriptions given by the design engineer.

Several application examples of compliant mechanisms realized with the software are shown. An experiment is presented showing investigations of how well functional specifications can be reached.
Validation Approach for Energy Optimization Models of Grid-Interactive Buildings Using Co-Simulation
Authors: McCurdy Patrick J. , Pattawi Kaleb , Wang Chenli , Roth Thomas , Nguyen Cuong , Liu Yuhong , Lee Hohyun
Published: January 2022

The consumption and production of energy are more dynamic as distributed energy resources (DERs) such as solar photovoltaics (PV) are deployed within the electric distribution system. The existing techniques for bulk generation do not take full advantage of DERs and can lead to wasted energy and higher costs for both utility companies and consumers. Commercial and residential building energy management systems are usually on a fixed schedule and are not able to respond to changes in energy price instantaneously. There is a need for a real-time pricing structure that can accommodate the fluctuating cost of energy based on supply and demand, and for an energy management system that is able to respond to the dynamic utility rate. As such, there is a need for a robust energy management control strategy and methodology to validate new approaches.

To address this gap, a strategy to control heating, ventilation, and air conditioning (HVAC) systems in a residential house was developed along with a validation methodology. A model of predictive control was implemented to optimize the thermostat setpoints and minimize energy cost for an individual residential house while maintaining thermal comfort of residents. This model was integrated with EnergyPlus simulation via an open source co-simulation platform previously developed at the National Institute of Standards and Technology (NIST). Total energy consumption and cost for consumers were compared between a case with the proposed model and a baseline case that used fixed-temperature setpoint control. The simple dynamic pricing model used in simulations was proportional to the demand of energy at that time of day. This work will contribute to the development of dynamic utility pricing models and residential control strategies for grid-interactive buildings and homes. The outcome of this research can be expanded to different building models or locations in future work.
Improving Real-Time Methane Monitoring in Longwall Coal Mines Through System Response Characterization of a Multi-Nodal Methane Detection Network
Authors: Cappellini Brian , Johnson Derek , Clark Nigel , Barr Amber
Published: January 2022

Methane released from coal during underground mining operations imposes a significant threat to the workers safety and consequently limits production. This paper introduces a method for the monitoring of methane emissions that are released during longwall coal mining operations. Furthermore, it describes the methodology used to test and develop the system’s response characteristics for improved measurement accuracy. The Methane Watchdog System (MWS) is a multi-nodal network of sensors currently under development to improve the safety and productivity during mining operations. The MWS consists of 10 compact sampling units designed to be integrated within the current roof support equipment of mines. Each unit contains an array of sensors to continuously monitor the environmental conditions which include methane concentration, temperature, pressure, and relative humidity. Reduced one-dimensional (1-D) modeling studies provided a useful tool to simulate the longwall mining environment. From the 1-D studies, multiple scenarios were constructed to generate temporal methane distributions that were the result of ventilation and production patterns. Model results were extracted from the proposed MWS sampling locations and used to demonstrate its usefulness and effectiveness within the laboratory setting. The resulting outputs from the system were then used to develop a signal reconstruction technique, which effectively sharpened response times and improved real time measurement accuracy.
A Reactor Train System for Efficient Solar Thermochemical Fuel Production
Authors: Patankar Aniket S. , Wu Xiao-Yu , Choi Wonjae , Tuller Harry L. , Ghoniem Ahmed F.
Published: January 2022

Thermochemical redox cycles are a promising route for the production of solar fuels. In this paper we present a novel Reactor Train system for efficient conversion of solar thermal energy to hydrogen. This system is capable of recovering thermal energy from redox materials, which is necessary for achieving high efficiency, but has been difficult to realize in practice. The Reactor Train System overcomes technical challenges of high temperature thermochemical reactors like solid conveying and sealing, while enabling continuous, round-the-clock fuel production and incorporating efficient gas transfer processes and thermal energy storage.

The Reactor Train is comprised of several identical reactors arranged in a closed loop and cycling between reduction and oxidation steps. In between these steps, the reactors undergo solid heat recovery in a radiative counterflow heat exchanger. We report a heat recovery effectiveness of 75–82% with a train consisting of 56 reactors and a cycle time of 84 minutes. With ceria as the redox material, 23% of the high temperature thermal energy input is converted to hydrogen, while 49% is recovered as intermediate-temperature heat at 750 °C.
Modeling of Residual Stress in Micro-Grinding Considering Texture Effect
Authors: Zhao Man , Liang Steven Y.
Published: January 2022

Residual stress is an important mechanical property parameter and a key evaluation index of the surface integrity. Residual stress induced in micro-grinding is related to the process parameters, the wheel properties, and material microstructure. The micro-grinding process is distinct from the conventional grinding owing to size effect, and the crystal effect. Typically, the effects of crystallographic orientation (CO) on process behaviors are significant by influencing the flow stress of workpiece material due to the depth of cut is usually less than the average grain size. In this paper, a Taylor factor model is developed to estimate the effect of CO on the flow stress and plastic modulus of monocrystalline materials. The flow stress model takes into account strain, strain rate, temperature, and material microstructure including grain size, CO, and dislocation density. The plastic modulus of monocrystalline materials h is given as the function of hardness, strain, and microstructure. The analytical model of residual stress is proposed considering the effects of CO. The hybrid McDowell algorithm is used to predict the residual stress with the developed plastic modulus. Finally, the sensitivity analysis is carried out, with the result showing that the effect of CO on residual stress is significant.
Effect of the External Multi-Frequency Excitations on Dynamics of a Ring Structure Rested on Elastic Foundation
Authors: Gao Nan , Wang Shiyu
Published: January 2022

This work aims to reveal the connections between the basic parameters and instabilities induced by the multi-frequency excitations on an elastic ring structure. An analytical dynamic model considering the geometric nonlinearity is established by using Hamilton’s principle and the nonlinear in-extensional assumption. Based on this assumption, the external excitations arise at the stiffness coefficients of vibration equations, which is different from the current researches. The external excitations not only affect natural characteristics but also lead to parametric instability. The natural frequency split occurs owing to the distributions of the excitations. Considering the presence of multi-frequency such as the rotation and fluctuation frequencies, the effects of the multi-frequency excitations on parametric vibrations are investigated. By discussing the parameters, two cases are examined and the instability zones are obtained by using Floquét theory. The results show that the parametric instabilities induced by the multi-frequency excitations are not a simple superposition of instability zones regarding each single-frequency excitation. Furthermore, the instabilities of the intersection regions of each frequency are larger than expected, and the extra zones can be found when the combination frequencies are closed to the natural frequency and its multiples. The instabilities are more complex when the natural frequency split is involved. The demonstration and analysis of this model could be an innovative understanding for similar rotational symmetry structures.
Protic Ionic Liquids as Lubricant Additives
Authors: Saran Om , Stoyanovich Brandon , Guo Hong , Iglesias Patricia
Published: January 2022

Protic ionic liquids (PILs) are an emerging class of environmentally friendly lubricants and lubricant additives PILs can be easily synthesized through proton transfer from a Brønsted acid to a Brønsted base and exhibit significant potential as lubricant additives on account of their high thermal stability, non-flammability, low melting points, lack of vapor pressure, low cost, and biodegradability. This research covers the tribological performance of three halogen-free protic ionic liquids, 2-hydroxyethylammonium 2-ethylhexanoate (Eet), 2-hydroxyethylammonium p-toluenesulfonate (Ets), and 2-hydroxyethylammonium 4-dodecylbenzenesulfonate (Eds) which are designed and synthesized using the same base (ethanolamine) but different acids of varying acidity and alkyl chain length. The relationship among their ionicity, molecular structures, and tribological properties are investigated when these protic ionic liquids are used as lubricant additives to water. Each PIL was evaluated as a lubricant additive in a 1 wt.% aqueous solution. The solutions were tested using a ball-on-flat reciprocating tribometer under room temperature for steel-ceramic contact using distilled water was used as a base line lubricant. PIL solutions yielded significant reductions in frictional coefficients and wear volumes. The wear mechanisms and surface interactions were also discussed in terms of PIL-steel surface interactions from SEM and EDX data.
Towards an Assistance and Simulation Augmented Reality Environment for the Manufacturing Area
Authors: Valdivia Puga José Abraham , Urbina Coronado Pedro Daniel , García Martínez Rubén Febronio , Ahuett Garza Horacio , Orta Castañon Pedro Antonio
Published: January 2022

The present work was carried in a manufacturing context, using augmented reality as the main tool. The main goal is to explore the capabilities of augmented reality used in manufacturing environments through connectivity and a digital shadow. Novel features implemented include control, interactions, and display of information not only of machines but any element connected to the industrial IoT. These features are addressed by the implementation of infrastructure prepared to communicate with different kinds of protocols. Additionally, a discrete event simulation of the manufacturing cell is created through specific software and connected with its 3D model to visualize the process and relevant information in AR. With this implementation, it is possible to establish a communication environment between machines, robots, and any element connected to the network. Also, this concept enables the visualization, control, interaction, and sending/receiving information of processes in real-time. Then, any person can see process information anywhere and interact within the AR model using a capable device. Therefore, AR applied in combination with other I4.0 tools allows to have high-level intelligent processes and increase operator’s abilities in manufacturing environments. The application of the proposed concept into modern manufacturing facilities was discussed and reviewed.
Gravity Balancing Design of a 3-DOF Hybrid Robotic Manipulator With Variable Payloads
Authors: Nguyen Vu Linh
Published: January 2022

This paper presents a design method for compensating the gravity effect of a three-degrees-of-freedom (3-DoF) hybrid robotic manipulator with variable payloads. The manipulator is constructed by a pair of 2-DoF parallelogram-based five-bar parallel mechanisms combined with a 1-DoF serial mechanism. The balancing design of the manipulator is realized by attaching two balancing units to the five-bar parallel mechanism, where each unit is made by a geared seven-bar mechanism with a linear spring. The parameters of the balancing units are analytically derived from the static equilibrium of the mechanism. The design method is also effective when the payload is varied and the spring stiffnesses are prescribed. Examples are then given to illustrate the effectiveness of the proposed method. The method was also validated by simulation software. The simulation results showed that, by using the balancing design, the actuation torques of the manipulator could be reduced by more than 98% with different applied payloads.
A Proposed Method for Online Condition Monitoring of Pneumatic Systems Under Different Operating Conditions and Parameters for Optimal Energy Consumption
Authors: Peerapur Anil U. , Dhavalikar Mangesh N. , Dingare Sunil V. , Patle Bhumeshwar K.
Published: January 2022

Pneumatics presents an alternative to electric and hydraulic actuators used in manufacturing industries. Pneumatic components provide a safe and reliable opportunity to automate a production line. However, pneumatic systems are notoriously expensive to operate as a result of system losses and inefficiencies. Typical systems have an output efficiency of 10%–12%. The Problems are — there is a fluctuating system pressure, which can cause air tools and other air-operated equipments to function less efficiently, affecting production; excess compressor capacity, resulting in higher than necessary costs due to no tracking of air consumption; decreased service life and increased maintenance of supply equipment due to unnecessary cycling and increased run time. This offers a significant improvement opportunity to meet targets concerning energy consumption. Leakages and excessive pressures are commonly identified as major sources of waste. Leaks or chokes in a compressed air system can be in various types due to diversified reasons. The proposed simulation method aims at the detection of faults based on signatures obtained. It has significance in terms of potential energy savings, decrease in breakdowns and increase in the service life of components. The Transfer function of a system is obtained by mathematical modelling of a system. The fault conditions are simulated in MATLAB SimulinkR to get results.
Model Reduction for Mid-Frequency Transient Vibration Analysis of Beam Structures by the Augmented DTFM
Authors: Zhang Yichi , Yang Bingen
Published: January 2022

Mid-frequency transient vibration analysis of flexible structures plays an important role in a variety of engineering applications. In a mid-frequency region, neither low-frequency methods like the finite element analysis (FEA) nor high-frequency methods like the statistical energy analysis (SEA) are directly applicable to transient vibration analysis. For optimal design of multi-body structures, a mid-frequency transient vibration analysis tool with a good balance of accuracy and efficiency in computation is in demand. In this paper, to address the aforementioned issue, a model reduction method is developed for mid-frequency transient vibration analysis of beam structures. The method is based on the augmented distributed transfer function method (augmented DTFM).

In this work, the augmented DTFM is modified for model reduction in mid-frequency analysis of beam structures, which is an extension of the authors’ previous effort. The idea behind this approach is to properly select several modes in the low-frequency region and a number of modes in a mid-frequency region that encompasses the excitation frequency spectrum, from the infinite series given by the augmented DTFM. This way, a reduced model of a beam structure for mid-frequency transient analysis is systematically obtained. The proposed model reduction method is validated in numerical examples, where the augmented method is compared with other methods, including the FEA. The accuracy and efficiency of the new method on the computation of transient displacement and shear force is demonstrated. As shown in the simulation results, a proper balance between accuracy and efficiency in model reduction can be achieved by the augmented DTFM. The computation savings by the proposed method, compared with the traditional numerical methods, can be of several orders of magnitude.
An Empirical Study of Machine Learning and Deep Learning Algorithms on Bearing Fault Diagnosis Benchmarks
Authors: Rezaeianjouybari Behnoush , Shang Yi
Published: January 2022

Rolling element bearings are critical components regarding the reliability and safety of rotating machinery. A reliable and continuous monitoring system with high prediction accuracy prevents machine downtime, increases productivity, and reduces maintenance costs. Vibration analysis via machine learning tools is a well-established approach. In recent years, deep learning methods have received increasing attention from researchers and engineers because of their inherent capability of dealing with big data, mining complex representations, and overcoming the disadvantage of traditional fault classification and feature selection algorithms based on hand-crafted features. However, the literature lacks a well-structured set of rules and comprehensive evaluation of the existing methods and resources and it is not clear how to choose the best algorithm for certain situations to achieve the optimal outcome. This work evaluates traditional machine learning and recent deep learning-based fault classification methods based on two benchmark rolling element bearing datasets and provides a comprehensive evaluation of the methods. Both time-frequency domain statistical features and raw inputs were used. The comparisons were made based on classification accuracy, training time, and hyperparameter tuning, Based on the evaluation results, we discuss technical challenges and provide suggestions for method selection and improvement.
Adaptive Intrusion Detection System for Cyber-Manufacturing System
Authors: Prasad Romesh , Moon Young
Published: January 2022

While Cyber-Manufacturing System security must involve three separate yet interrelated processes (prediction, detection, and prevention), the detection process is the focus of research presented in this paper. Current intrusion detection systems often result in high false positive and false negative rates. Also, the actual detection time may take long time-up to several months. The current intrusion detection systems rely heavily on the network data, but do not utilize the physical data such as side channel, sensor reading, image, keystrokes., which are generated during manufacturing processes. An adaptive intrusion detection system composed of two security layers is proposed to detect cyber-physical intrusions. Model-free deep reinforcement learning is used in the two security layers: the network layer and the physical layer. The capability of reinforcement learning through trial and error and a course of actions based on observations in an environment makes it more robust to the continuously changing attack vectors in current manufacturing industry. The proposed intrusion detection system demonstrates that it can reduce the false positive rate and generate alerts to a wide range of attack patterns.
Enhanced Pool Boiling Critical Heat Flux on Tilted Heating Surfaces Using Columnar-Post Wicks
Authors: Borumand Mohammad , Hwang Gisuk
Published: January 2022

The upper heat flux limit of nucleate pool-boiling heat transfer (NPHT), i.e., Critical Heat Flux (CHF), results in system burnouts in various energy and industrial applications, and the understandings of the tailored CHF mechanisms are crucial to develop robust thermal management systems. In various applications, the understandings of the tailored CHF mechanisms are essential for design flexibility and operation sustainability, but previous CHF tailoring studies focused on upward-facing heater orientation. This study examines the tailored hydrodynamic-instability using columnar post wick array to enhance CHF on tilted heater surfaces (with surface orientation θ = 60°–130°). Liquid supply enhances via the capillary flow through the post wicks, while the produced vapor efficiently escapes through pore space among the post wicks. The enhanced CHF are predicted using a modified interfacial lift-off CHF hydrodynamic model that relies on classical two-dimensional interfacial instability theory. On the tilted plain surface with the surface orientation from 60° to 130°, the model predicts the CHF, qCHF = 126.5 to 92.5 W/cm2 at the critical hydrodynamic instability wavelength, λcr = 9.2 to 12.7 mm, respectively, using water as a working fluid. The enhanced CHF is predicted at the surface orientations of θ = 90° and 120°, showing a maximum of 185% and 250% increase, respectively. The maximum enhancement occurs at the smallest columnar-post pitch distances, lp = 2.5 mm, where qCHF increases from 104 to 295 W/cm2 for θ = 90°, and from 89 to 313 W/cm2 for θ = 120°. The developed model will provide insights into the tailored hydrodynamic instability wavelength at tilted angle via engineered surface.