bluuebunny/crossref_metadata_2025_split huggingface dataset:
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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.
Dynamic Response of Cross Tube With Crushable Foam-Filled Cellular Core
Authors: Jenson Sean , Ali Muhammad 
Published: January 2022

Abstract
Thin-walled crush tubes and other axial members are often employed as energy absorbers in vehicle chassis to improve crashworthiness of front and side chassis members. Thin-walled axial crushing members are primarily used due to their high strength to weight ratios. Previous works cover extensively the study of thin-walled members under axial crushing loads. Additionally, work has been done exploring the effects of core addition to a standalone thin-walled structure. Functionally graded cellular structures are often employed to enhance energy absorption due to their high strength and stability with minimal added weight burden. Previously, investigation on the addition of composite functionally graded hexagonal extruded cores proved to increase energy absorption capacity and improve stability of the structure. The present study is a continuation of the previous work on functionally graded core material addition to thin-walled crush tubes. Additionally, this study investigated the addition of crushable foam material to the volume of the cellular structures. This study was conducted utilizing ABAQUS explicit dynamic modeling environment. The addition of graded cellular core material with crushable foam provided increased energy absorption capacity of the structure through increased structural stiffness and decreased crush stroke. The structure exhibited progressive folding/collapse mechanisms with a more global crushing response as compared to an empty tube structure. As compared to previous graded cellular core structures, the crushable foam addition promoted a more global structural response and allowed for total energy absorption before structure densification. The addition of core materials within thin-walled crush tubes have shown positive influences on energy absorbing capacity and overall performance of crush tube members.
Simulating Dynamic Tension Effects From an Out-of-Round Unwind Roll
Authors: Reish Benjamin 
Published: January 2022

Abstract
Web handling systems maintain a certain amount of tension in the web and a process speed. Non-circular rolls of material are not uncommon in the real world arising from storing the rolls or imprecise control of parameters. Non-circular rolls at the beginning of a web handling system cause tension spikes in the web as they are unwound. Simulating the tension effects of the non-circular unwind roll is the aim of this paper. A review of numerical models, called primitive elements, for web handling systems is included. The parameters required to describe a web handling system are reviewed. A primitive element for modeling a non-circular roll is introduced. The web handling system model, which uses linear and nonlinear elements in simulation, is compared with experimentally measured data.
Detachable Fine Bump Connection Using Multi-Walled Carbon-Nanotube Bundles for 3D Semiconductor Modules
Authors: Kobayashi Masasuke , Suzuki Ken , Miura Hideo 
Published: January 2022

Abstract
In the 3D chip stacking structure, fine TSV (Through Silicon Via) structures are used in the stacked chips and fine metallic bumps are jointed between the stacked chips for the 3D interconnection. It is not easy, however, to make perfect reliable joints of the huge number of fine bumps in micro scale due to the large bending deformation of each chip with different surface interconnection and dielectric structures and the height fluctuation among the bumps. It is, therefore, very important to establish the largely deformable bump joint system with easy detachability.
In order to solve these problems of fine metallic bump joint structures, multi-walled carbon nanotube (MWCNT) bundle structures were applied to the bump joint structure. To investigate the possibility of detachable fine bumps, high quality MWCNTs were grown by thermal CVD method using acetylene gas. The area-arrayed MWCNTs bundle structures were grown on a silicon substrate and the deformation behavior by compression was measured. The MWCNTs bundles exhibited elastic deformation in the range of strain addition up to 3%. The electrical properties were measured by jointing the MWCNTs films. In the range of compressive strain up to about 30%, the connection between MWCNTs films shows stable ohmic contacts due to the point and side-wall contacts by each MWCNTs. The contact resistance did not change so much even after the 10 cyclic mounting and dismounting.
Numerical Analysis of Flow and Heat Transfer for Supercritical CO2 and Liquid Sodium in Semicircular Mini-Channels
Authors: Qin Lei , Xie Gongnan , Li Shulei 
Published: January 2022

Abstract
The Brayton cycle of supercritical carbon dioxide (S-CO2), is an ideal choice to replace the outdated power cycle. In order to improve the heat transfer performance, the Print Circuit Heat Exchanger (PCHE) has been attracted more attention, since it has a larger specific heat transfer area, compact structure, high efficiency. Based on this inspiration, the flow and heat transfer mechanism of S-CO2 and liquid metal sodium in a straight horizontal semicircular channel were studied, and the flow and coupled heat transfer was numerically analyzed. The influences of flow direction, Reynolds number and channel diameter on heat transfer performance and pressure drop in the semicircular straight channel were further studied. The results demonstrate that the performance of countercurrent designs 8.5% higher than that of the downstream pattern. The total heat transfer coefficient and pressure drop of both cold and hot channels in PCHE increase linearly with the rise in Reynolds number. The buoyancy effect affects the heat transfer when the pipeline velocity is small. The effect of buoyancy on heat transfer basically disappears when the pipeline velocity is high. When the diameter of the hot side channel is fixed and the diameter of the cold side channel is increased from 0.8mm to 1.1mm, the total heat transfer coefficient in the cold channel is increased by 8%, while the total heat transfer coefficient in the hot channel is increased by 51.6%. Through the above research in this paper, some heat transfer characteristics of sodium and supercritical carbon dioxide in PCHE are obtained, which is contribute to the design and optimization of the heat exchanger in sodium cooled fast reactor.
Towards a Digital Twin Setup for Individualized Production of Fabricated Components
Authors: Hultman Hugo , Cedergren Stefan , Söderberg Rikard , Wärmefjord Kristina 
Published: January 2022

Abstract
As the aerospace industry continues its shift towards digital manufacturing, an increased use of inline sensors and data collection is creating an opportunity to further optimize the production process. Measurements from individual parts make it possible to adapt each process to current conditions rather than running all processes nominally. This is sometimes described as individualized production as opposed to traditional mass production. The concept of a digital twin for manufacturing has recently gained more attention as a promising method for individualized production. A digital twin collects data from a real environment to create a virtual copy of a physical phenomenon, which can be used to predict how its real counterpart is going to behave. The approach has been proposed for a manufacturing environment where it would be used to predict the outcome of a production process. This could prove particularly useful for fabrication processes, a method used for making aero engine parts by joining large assemblies of smaller parts through welding. This paper presents functionalities that can be used to implement a digital twin in a high precision fabrication process, outlining different approaches for data collection, data analysis, and adaptive process adjustments. An example is shown where physical measurements are used to improve the predictive capabilities of a welding simulation in order to enable more accurate process adjustments.
Validation of an Indian Rail Vehicle Model Using Ride Indices From Oscillation Test Trials
Authors: Singh Sultan , Kumar Anil 
Published: January 2022

Abstract
Safety and comfort are more critical factors prior to efficient and economical travel for any passenger train. Due to the wheel-rail interaction at high speed, high amplitude vibrations occur that deteriorate the ride comfort of the passengers. In this paper, a multi-body dynamic model is developed by using Adams/VI-Rail software. Actual parameters of track and LHB coach are considered to simulate the rail vehicle model. Sperling’s ride index (Wz) method determines the ride indices values at different speeds with random track irregularity. The proposed multi-body dynamic model is analysed, and the results are compared with oscillation test trials performed and reported by the Research Design and Standards Organisation (RDSO). Obtained results were in good agreement and within permission values. The validated model can be extended to study the improvements in ride quality and ride comfort by introducing a semi-active suspension system based on an MR damper.
Experimental Investigation of High-Speed Flows Past Pillow Plates
Authors: Sundermeier Stephan , aus der Wiesche Stefan 
Published: January 2022

Abstract
This paper presents an experimental investigation of highspeed flows past Pillow-Plate Heat Exchanger (PPHE) geometries by means of conventional and focussing schlieren optics. Past investigations have already shown that PPHE has positive flow behaviours compared to other heat exchangers. The static pressure drop along a pillow-plate surface is relatively low, but the profile offers a good mixing and heat transfer behaviour. These characteristics were not very well researched for higher Mach numbers until now.
Performance Characterization of Hollow Fiber Direct Contact Membrane Distillation Module
Authors: Asiri Jaber M. , Alasiri Abdulaziz M. , Caspar Justin , Xue Guanyang , Oztekin Alparslan 
Published: January 2022

Abstract
Computational fluid dynamics (CFD) simulations were carried out to study the performance of a single hollow fiber in a direct contact membrane distillation (HF-DCMD) module for a desalination process. The feed solution is seawater with a salt (NaCl) concentration of 35 g/L. The Navier-Stokes, mass and energy transport equations are considered, with a coupled boundary condition imposed by the membrane. The system is investigated to examine sensitivity toward the membrane thickness, pore size, and inner hollow fiber diameter based on existing commercial fibers. Two membrane thicknesses (300 μm, 500 μm), two membrane pores sizes (0.2 μm, 0.45 μm), and two inner diameters (1.2 mm, 1.8 mm) are studied in the laminar regime at fixed operating conditions. The presence of temperature polarization causes a significant drop in the water permeation in the DCMD system due to reduced driving force across the membrane. The characterization of polarization inside the hollow fiber will be the focus of this work. It was found that the vapor flux was most sensitive to the membrane thickness (a 30% flux increase) versus the inner diameter (2% flux increase). The pore size is also a very influential parameter (20% flux increase), moving from optimal to less-optimal properties.
Three-Dimensional Deviation Analysis of High-Speed Spindle Assembly Based on Skin Model Shapes
Authors: Tian Ang , Jin Sun , Chen Kun , Liu Shun , Li Hangyu , Niu Zhihua 
Published: January 2022

Abstract
The high-speed motorized spindle is the core component of the machine tool, and its assembly accuracy directly determines the quality of the processing product and the service life of the spindle itself. As a typical revolving components assembly, it is critical to ensure that the radial and axial runout performance of the assembly is extremely excellent to satisfy the requirements of high precision and rigidity. Meanwhile, geometric deviations are inevitably observable on manufactured components of spindle, especially the form deviations of revolving part have huge influences on the quality and function of spindle. However, geometric deviations are reduced to dimensional and orientation defects without considering form deviations in most previous models of deviation analysis. Skin Model Shape of a work piece is a discrete geometry representation of the physical interface between the work piece and its environment, which is based on a representation of non-ideal work pieces employing discrete geometry representation schemes. This paper presents a deviation analysis method for high-speed motorized spindle assembly using Skin Model Shapes, concerning all kinds of geometric deviations of the components. Deviations of the components are represented by the Skin Model Shapes, which is a point cloud-based discrete representative that is able to model the actual toleranced surfaces instead of the ideal or associated ones in an assembly. This paper solves the constrained objective function by means of the ideas of sequential quadratically constrained quadratic programming (SQCQP) method, which can solve problems with high degree of non-linearity and also has relatively small amount of calculation. The procedures outlined in the paper are quite general and can be used for tolerance analysis of any assembly process.
Dynamic Trajectory Planning of a 7-DOF Surgical Robot Based on HER-DDPG Algorithm
Authors: Hou Qitao , Gu Chenchen , Wang Xiaoyu , Zhang Yating , Zhao Ping 
Published: January 2022

Abstract
Traditional trajectory planning approaches are currently lacking in intelligence and autonomy. We used the reinforcement learning approach to solve the autonomous trajectory planning of the robot arm to avoid obstacles with uniform motion and hit the target point quickly with obstacle avoidance planning for surgical robots taken as the practical background. We used the algorithm of experience playback mechanism combined with off-policy DDPG based on reinforcement learning, and after several iterations, the robot completed trajectory planning with obstacle avoidance autonomously. Moving obstacles were added to roughly simulate the autonomous obstacle avoidance of a surgical robotic arm with moving medical personnel or mobile instruments in the operating room, based on the simple trajectory planning example of Open-AI Open-Source Project Baseline, combined with the research context. Sparse rewards were used for each iteration based on the HER algorithm, so that each attempt could gain experience. The HER-DDPG method can quickly complete the manipulator’s trajectory planning in a simulation environment, which is critical for the surgical robot’s autonomous positioning in the real world. Furthermore, the experience playback system has been tested to allow full use of sparse rewards and handle parallel tasks equally well.