bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Propagation of Plasticity in Uniaxial Compression
Authors: White M. P. , Griffis LeVan 
Published: March 2021

Abstract
A theoretical investigation of the mechanism of uniaxial compression impact on elastic-plastic materials is described in this paper. The method of analysis is similar in some respects to that previously given for tension impact on such materials. It is concluded that four different kinds of behavior can occur, depending upon the impact velocity. In the lowest velocity range the behavior in compression is similar to that found in tension. In this case stress and strain are propagated from the point of impact as a zone or wave front of ever-increasing length. This type of behavior ends at a velocity corresponding to the “critical” velocity found in tension impact. Within the next higher velocity range, stress and strain are propagated as a shock-type wave, or wave of very small length in which the transition from low to high stress and strain is very abrupt. At still higher impact velocities, there occurs “flowing deformation” in which the material is too weak to maintain coherency. Here there is a steady flow of the material toward and against the hammer, after which it flows in a thin sheet radially outward over the face of the hammer. The final possible state occurs at impact velocities greater than the speed of an elastic wave, so that no disturbance can escape from the hammer into the medium. Here the behavior is essentially that of a fluid, impact force being independent of strength of material.
The Decay of Isotropic Turbulence
Authors: Frenkiel F. N. 
Published: March 2021

Abstract
The equation of decay of isotropic turbulence is determined in the two cases of large and small Reynolds number of turbulence by using the von Kármán-Howarth equations and applying Loitsianskii’s theorem of the conservation of the disturbance moment. The theoretical curves are compared with the results of measurements behind grids, made by various experimenters in the United States and in England. The decay of the longitudinal turbulent energy seems to agree quite well with the theoretical equations for large Reynolds number of turbulence. The theory does not give the variation of the transverse scale of turbulence measured in the experiments, but only the “disturbance length,” which is a function of the longitudinal correlation. Thus the comparison for the scale is only qualitative. It is not possible to show agreement with the theoretical variation of the scale deduced from the equations. The difference is explained by the imperfect isotropy, which has a much greater influence on the variation of the scale than it has on the energy decay. The present comparison of the theory with the experiments differs from similar prior comparisons by the fact that the decay is given as a function of the initial conditions of the turbulence at a chosen moment, without using arbitrary constants.
Transient Large Eddy Simulation of Slurry Erosion in Submerged Impinging Jets
Authors: Wang Qiuchen , Huang Qiyu , Sun Xu , Zhang Jun , Karimi Soroor , Shirazi Siamack A. 
Published: March 2021

Abstract
Submerged impingement jets are widely used in erosion/corrosion experiments as it is easy to control jet standoff distance, jet angle, and flow velocities in experiments. In addition to experiments, typically computational fluid dynamics (CFD) technique has been used to simulate slurry flow in this geometry to investigate erosion process and develop erosion models or equations. The traditional CFD simulations of erosion in this geometry use the Reynolds-averaged Navier–Stokes (RANS) equations with turbulence models. By using this technique, time-averaged fluid flow is revealed, and thus, time-averaged erosion rate can be obtained by tracking particles in the fluid flow field. However, this seemingly simple flow displays unsteady flow structures in the stagnation zone of the flow field and its effects on the erosion process were previously unclear. In this study, large eddy simulation (LES) is used to simulate unsteady fluid flow in different impingement jets in an Eulerian scheme. Then, transient particle tracking is performed in a Lagrangian scheme. Particles are injected randomly at the inlet plane and tracked to simulate unsteady erosion that occurs on the target surface. Finally, an erosion equation is used to calculate solid particle erosion rates. The LES Eulerian–Lagrangian erosion modeling is further validated by available experimental data for fluid velocities and an erosion profile. The results show that the accuracy of erosion prediction of small particles is improved significantly by using the LES method. In addition, the unsteady particle motion and erosion process can be revealed by using this method.
Study of Pressure Pulsations in a Francis Turbine Designed for Frequent Start-Stop
Authors: Trivedi Chirag 
Published: March 2021

Abstract
The energy market aims for high flexibility that allows guaranteed power to the consumers with minimum carbon footprint. Over the last three decades, hydropower has been a reliable and an efficient option to meet the fluctuating energy demand as it allows high-ramping rate and quick start-stop. However, such critical operations bring certain challenges for hydro turbines, i.e., high-amplitude stochastic loading and the fatigue. Credible investigation of unsteady pressure pulsations and their signature is important to understand the consequences. The present work aims to study pressure pulsations in a model Francis turbine, which is designed for the frequent start–stop operations. A total of 112 numerical simulations, across the hill diagram, are conducted. Pressure pulsations in the vaneless space, blade channels, and draft tube are investigated. The results show distinct patterns of rotor-stator interaction frequencies in the turbine. In the regions of high rotational speed and low flow rate, stochastic pulsations are predominant.
Quantitative Characterization of Shale Porosities of Different Origins by Integrating Pore Genesis and Logging Analysis
Authors: Wang Jianguo , Gu Daihong , Meng Xiaoyan , Yang Daoyong 
Published: March 2021

Abstract
In this paper, a new and pragmatic technique has been developed to identify pore types and characterize porosities of shales with various origins. By comparing the genesis of pore types (i.e., organic, brittle, and clay mineral porosities) in shales, the corresponding pore volumes per unit mass are determined as a function of the total porosity, density, and the content of each pore type from core samples. Subsequently, a new inverse framework was proposed and successfully applied to quantify different types of porosities in the Silurian Longmaxi formation shale in the Zhaotong area. The pore volume per unit mass of organic matter is calculated to be around 0.185–0.190 cm3/g, which is 10–21 and 8–19 times more than that of brittle mineral and clay mineral, respectively, indicating that pore space of organic matter contributes greater to the total porosity than that of the clay and brittle minerals. Using single well data, the porosity in organic matter is found to follow the same pattern as the total porosity in the vertical direction. Such an identified porosity type leads to more accurate sweet spots as well as more appropriate drilling locations for horizontal wells in shale reservoirs.
A Review on Corrosion and Wear of Additively Manufactured Alloys
Authors: Renner Peter , Jha Swarn , Chen Yan , Raut Ajinkya , Mehta Siddhi G. , Liang Hong 
Published: March 2021

AbstractProducts made from additive manufacturing processes have attracted great attention in engineering, health care, and society at large. However, there is little knowledge about the failure of additively manufactured alloys, in particular, corrosion and wear seen in most engineering applications. The haphazard and inefficient usage of such alloys raised concerns about safety, compatibility, reliability, cost, and consumer satisfaction. To address those concerns, we studied the mechanisms of the most common failure modes, corrosion and wear, of alloys fabricated through additive manufacturing based on published literature. It was found that the processing conditions have profound influence on microstructure and thus corrosion and wear resistance of alloys. Because of the layered structure, the initiation and growth of both corrosion and wear exhibited anisotropic behavior. The insights from this review could be used as a reference of the state-of-the art and to help in the development of future additively manufactured alloys with improved corrosion and wear properties.
Dynamic Analysis of the Optimized Savonius Vertical Axis Wind Turbine Composite Blades
Authors: Ghoneam Sobhy M. , Hamada Ahmed A. , Sherif Taha S. 
Published: March 2021

Abstract
This article presents a comprehensive study of the dynamic behavior of small vertical-axis wind turbines (VAWTs) based on local fabricated Savonius VAWTs, which is suitable for countries that have a moderate wind speed. The merits of this design are cleanliness, silent, start-up under low wind speed, independent wind directions, adaptability, and ease of manufacturing. Also, this article presents an experimental validation study for the optimized Savonius VAWT. Four verification test configurations of the optimized VAWT composite blades are designed, simulated, and fabricated of Glass—Polyester with different stacking sequence layout for each. Modified mechanical parameters are introduced to improve the scalability, reliability, and accuracy of the developed models. Based on wind energy conversion system basics, aerodynamic characteristics (tip speed ratio (λ) and coefficient of power (Cp)) and dynamic characteristics (natural frequencies and mode shapes) of Savonius rotor models are presented and simulated within solidworks simulation 2020 software. The dynamic characteristics such as frequency, mode shape, and damping factor are extensively investigated using fast Fourier transform (FFT) analyzer. The results show that the role of composite material blades in improving the dynamic performance of a wind turbine is significant.
Optimization of Herringbone Grooved Thrust Air Bearings for Maximum Load Capacity
Authors: Yu Yunluo , Pu Guang , Jiang Tianchu , Jiang Kyle 
Published: March 2021

Abstract
Many studies in herringbone grooved thrust bearings are focused on searching for the optimal groove parameters to improve the load capacity, but none of them adopt different grooves in different sections. In this study, a novel optimization method of herringbone grooved thrust air bearings is proposed for maximum load capacity by seeking the optimal groove parameters in each section of the bearing independently. An example of an optimized thrust air bearing is presented, and its performance is compared with a non-optimized bearing and a conventionally optimized bearing without dividing grooves into sections. The resultant herringbone grooves are found to have different parameters in the inner and outer sections, which is uncommon in existing grooves. Numerical results show that the novel bearing has a higher load capacity than the non-optimized reference bearing and conventionally optimized bearing. The study shows that the new design can increase load capacity by 30.77%, verified by experiments.
Triboinformatics Approach for Friction and Wear Prediction of Al-Graphite Composites Using Machine Learning Methods
Authors: Hasan Md Syam , Kordijazi Amir , Rohatgi Pradeep K. , Nosonovsky Michael 
Published: March 2021

Abstract
Data-driven analysis and machine learning (ML) algorithms can offer novel insights into tribological phenomena by establishing correlations between material and tribological properties. We developed ML algorithms using tribological data available in the literature for predicting the coefficient of friction (COF) and wear-rate of self-lubricating aluminum graphite (Al/Gr) composites. We collected data on effects of material variables (graphite content, hardness, ductility, yield strength, silicon carbide content, and tensile strength), processing procedure, heat treatment and tribological test variables (normal load, sliding speed, and sliding distance) on tribological properties and established two-parameter relationships. These data are analyzed using several ML algorithms: artificial neural network (ANN), K nearest neighbor (KNN), support vector machine (SVM), gradient boosting machine (GBM), and random forest (RF). The trained ML models can predict the tribological behavior from material variables and test conditions, beyond what is possible from two-parameter correlations. GBM outperformed other ML algorithms in predicting friction behavior, while RF had the best prediction of the wear behavior. ML analysis identified graphite content and hardness and as the most significant variables in predicting the COF, while graphite content and sliding speed were the most dominant variables for wear-rates.
Feature Recognition for Manufacturability Analysis
Authors: Regli William C. , Gupta Satyandra K. , Nau Dana S. 
Published: March 2021

Abstract
While automated recognition of features has been attempted for a wide range of applications, no single existing approach possesses the functionality required to perform manufacturability analysis. In this paper, we present a methodology for taking a CAD model of a part and extracting a set of machinable features that contains the complete set of alternative interpretations of the part as collections of MRSEVs (Material Removal Shape Element Volumes, a STEP-based library of machining features). The approach handles a variety of features including those describing holes, pockets, slots, and chamfering and filleting operations. In addition, the approach considers accessibility constraints for these features, has an worst-case algorithmic time complexity quadratic in the number of solid modeling operations, and modifies features recognized to account for available tooling and produce more realistic volumes for manufacturability analysis.
Decomposing a Delta Volume Into Maximal Convex Volumes and Sequencing Them for Machining
Authors: Sakurai Hiroshi 
Published: March 2021

Abstract
A method has been developed to decompose a polyhedral delta volume, which is the volume difference between the raw material and the finished part, into maximal convex volumes by intersecting the halfspaces of the faces of the delta volume. The hypothesis behind this effort is that in machining a delta volume of complex shape it is more efficient to divide it into volumes of simple shapes and remove volume by volume with large cutters than to remove it as a single volume with a single small cutter. The maximality of a maximal convex volume represents the possibility of using a large cutter and its convexity represents the simplicity of the shape of the volume. To prove the utility of maximal convex volumes, a small computer program was developed that sequences the maximal convex volumes based on a few heuristics on machining efficiency and tested it with a few objects. It generated good machining sequences.
The basic idea of the decomposition method is to intersect a polyhedral delta volume with the halfspaces of its faces having concave edges. The combinations of such halfspaces that result in maximal convex volumes when they are intersected with the delta volume are determined efficiently by examining the relationships among the halfspaces. This basic idea works well for polyhedral delta volumes but does not work for delta volumes having curved faces since curved faces cannot always be extended infinitely. To cope with the delta volumes having cylindrical faces, a separate decomposition method has been developed. This method works only for the delta volumes that can be decomposed into 2½D machining volumes.
Reducing Setup Cost by Automated Generation of Redesign Suggestions
Authors: Das Diganta , Gupta Satyandra K. , Nau Dana S. 
Published: March 2021

Abstract
All mechanical designs pass through a series of forma] and informal redesign steps, involving the analysis of functionality, manufacturability, cost and other life-cycle factors. The speed and efficacy of these steps has a major influence on the lead time of the product from conceptualization to launching.
In this paper we propose a methodology for automatically generating redesign suggestions for reducing setup costs for machined parts. Our approach is based on interpreting the design as a collection of machinable features. Our methodology generates alternate machining features by making geometric changes to the part, and adds them to the feature set of the original part. The designer may provide restrictions indicating that certain surfaces and volumes should not be changed, in which case all redesign suggestions generated by our approach honor those restrictions. Using features from the extended feature set generated above, one or more new designs may be found that need fewer setups than the original part.
Super-Finishing Tool Path Generation for Digitized Models Supported by Super-Finishing Form Feature Recognition
Authors: Saglio Emilio , Mandorli Ferruccio , Cugini Umberto 
Published: March 2021

Abstract
The realization of sculptured shapes using CAD systems is still today a very complex and time consuming operation. For these reasons, design by physical modeling is still in use and remains in force in many industries (automotive, ski boots, sport articles).
For the manufacturing of complex free-form surfaces, in situations in which it is more desirable to proceed from a physical model to a numerical definition rather than use mathematics to derive the physical part, copy milling techniques are widely used.
This paper gives a brief overview about copy milling techniques for 3 axis copy milling machines, and proposes a feature based method to support an automatic tool path generation for the super-finishing phase. The proposed method is divided in two parts: super-finishing features recognition and tool path generation.
Using copy milling techniques, the model of the object to be milled is obtained by digitizing. Therefore a global mathematical surface description of the model does not exist.
In such a situation a model interpretation phase is required to recognize the super-finishing features and thus proceed to the tool path generation.
A two step algorithm for super-finishing feature recognition on a digitized model is proposed: features arc recognized on the basis of the digitized point density and the normal vectors of the triangles generated by the surface reconstruction (based on Delaunay triangulation method).
The tool path is then generated using a method based on the calculation of the Voronoi diagram on the area identified as super-finishing feature.
The super-finishing feature recognition and tool path generation modules have been integrated as part of a more general CAM system for copy milling called HICAM. The architecture of such a system will be presented together with examples of solutions obtained by means of the use of the implemented prototype modules.
Fuzzy Part Coding for Group Technology
Authors: Ben-Arieh D. , Lee S. E. , Chang Ping Teng 
Published: March 2021

Abstract
Contemporary Group Technology (GT) methods apply coding schemes as a popular method for capturing the design and manufacturing information pertinent to the parts to be grouped. Coding schemes are very popular and many different coding systems are commercially available. The main disadvantage of current coding systems, however, is their generality and lack of informative representation of the parts.
This paper presents a new methodology for coding parts using fuzzy codes. The methodology is general and applies to attributes that have a crisp value (e.g. “length”, “ratio of length to diameter”), an interval value (e.g. “tolerance”, “surface roughness”) or a fuzzy value (e g. “primary shape”).
The methodology considers the range of attributes relevant for the grouping, and therefore is tuned and adjusted to the specific collection of parts of interest This method creates a more informative coding scheme which leads to improved variant process planning methods, scheduling and inventory control as well as other manufacturing functions that utilize GT.
A Database Tool for Managing Customer and Design Information During Product Definition
Authors: Khadilkar Dileep V. , Gershenson John A. , Stauffer Larry A. 
Published: March 2021

Abstract
We developed a new database tool to manage information during the product definition process. This tool is a result of an ongoing research program to coordinate marketing and design engineering efforts in new product developments, and consider the related life cycle issues early in the design process. The database tool facilitates a methodology that integrates customer and design information, and allows reuse of this information during redesign problems. This paper presents the development, implementation, and an example use of the database tool.
A Design Expert System for Full Journal Bearings
Authors: Badar M. Affan , Guntur Rao R. 
Published: March 2021

Abstract
Various architectures used in design expert systems are reviewed. An architecture consisting of several stages of grouped rules is employed and its features are discussed. The architecture uses a rule based production system. Different methodologies for designing hydrodynamic journal bearings are reviewed and an integrated and dependable design methodology is developed In this Turbo Prolog program, initially, the user is asked to enter the required prescriptive and functional specifications and the decision-criterion. Knowledge bases pertaining to this design problem are represented appropriately. The design solutions of successive states are examined for any violations of the design constraints. The expert system ‘Fbear’ makes an exhaustive search for all the solutions. Utility value of each of the final solutions is calculated and the design solutions having utility values above a certain limit are printed in an output file. The results of ‘Fbear’ are compared with those of the previous workers to illustrate its usefulness.
Design of Products for an Agile Manufacturing Environment
Authors: Kusiak Andrew , Feng Chang-Xue 
Published: March 2021

Abstract
Many manufacturing companies have been striving to reduce setup times in order to produce smaller lot sizes and to obtain quicker responses to frequently changing market demands. This paper focuses on the reduction of setup time by design improvements of products. Based on the basic principles of setups and concepts from concurrent engineering, rules for design of products at the feature level are presented. Examples and computational results illustrate that the inter-lot setups and in-lot setups can be reduced by the feature-based design rules. The proposed approach for setup reduction appears to be more cost effective than optimizing the processes and operations where the product designs have been fixed. This research intends to bridge the gap between engineering design and manufacturing.
A Hybrid Approach to Computer-Aided Process Planning for Prismatic Parts
Authors: Zhang Y. F. , Nee A. Y. C. , Fuh J. Y. H. 
Published: March 2021

Abstract
One of the most difficult tasks in automated process planning is the determination of operation sequencing. This paper describes a hybrid approach for identifying the optimal operation sequence of machining prismatic parts on a three-axis milling machining centre. In the proposed methodology, the operation sequencing is carried out in two levels of planning: set-up planning and operation planning. Various constraints on the precedence relationships between features are identified and rules and heuristics are created. Based on the precedence relationships between features, an optimization method is developed to find the optimal plan(s) with minimum number of set-ups in which the conflict between the feature precedence relationships and set-up sequence is avoided. For each set-up, an optimal feature machining sequence with minimum number of tool changes is also determined using a developed algorithm. The proposed system is still under development and the hybrid approach is partially implemented. An example is provided to demonstrate this approach.