15 resultados para mechanical analysis
em Cochin University of Science
Resumo:
The dynamic mechanical properties such as storage modulus, loss modulus and damping properties of blends of nylon copolymer (PA6,66) with ethylene propylene diene (EPDM) rubber was investigated with special reference to the effect of blend ratio and compatibilisation over a temperature range –100°C to 150°C at different frequencies. The effect of change in the composition of the polymer blends on tanδ was studied to understand the extent of polymer miscibility and damping characteristics. The loss tangent curve of the blends exhibited two transition peaks, corresponding to the glass transition temperature (Tg) of individual components indicating incompatibility of the blend systems. The morphology of the blends has been examined by using scanning electron microscopy. The Arrhenius relationship was used to calculate the activation energy for the glass transition of the blends. Finally, attempts have been made to compare the experimental data with theoretical models.
Resumo:
This thesis aims to develop new toughened systems for epoxy resin via physical and chemical modifications. Initially the synthesis of DGEBA was carried out and the properties compared with that of the commercial sample. Subsequently the modifier resins to be employed were synthesized. The synthesized resin were characterized by spectroscopic method (FTIR and H NMR), epoxide equivalent and gel permeation chromatography. Chemical modification involves the incorporation of thermoset resins such a phenolics, epoxy novolacs, cardanol epoxides and unsaturated polyester into the epoxy resin by reactive belnding. The mechanical and thermal properties of the blends were studied. In the physical modification route, elastomers, maleated elastomers and functional elastomers were dispersed as micro-sized rubber phase into the continuous epoxy phase by a solution blending technique as against the conventional mechanical blending technique. The effect of matrix toughening on the properties of glass reinforced composites and the effect of fillers on the properties of commercial epoxy resin were also investigated. The blends were characterized by thermo gravimetric analysis, differential scanning calorimetry, dynamic mechanical analysis, scanning electron microscopy and mechanical property measurements. Among the thermoset blends, substantial toughening was observed in the case of epoxy phenolic novolacs especially epoxy para cresol novolac (ECN). In the case of elastomer blending , the toughest blends were obtained in the case of maleic anhydride grafted NBR. Among functional elastomers the best results were obtained with CTBN. Studies on filled and glass reinforced composites employing modified epoxy as matrix revealed an overall improvement in mechanical properties
Resumo:
Nanoscale silica was synthesized by precipitation method using sodium silicate and dilute hydrochloric acid under controlled conditions. The synthesized silica was characterized by Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), BET adsorption and X-Ray Diffraction (XRD). The particle size of silica was calculated to be 13 nm from the XRD results and the surface area was found to be 295 m2/g by BET method. The performance of this synthesized nanosilica as a reinforcing filler in natural rubber (NR) compound was investigated. The commercial silica was used as the reference material. Nanosilica was found to be effective reinforcing filler in natural rubber compound. Filler-matrix interaction was better for nanosilica than the commercial silica. The synthesized nanosilica was used in place of conventional silica in HRH (hexamethylene tetramine, resorcinol and silica) bonding system for natural rubber and styrene butadiene rubber / Nylon 6 short fiber composites. The efficiency of HRH bonding system based on nanosilica was better. Nanosilica was also used as reinforcing filler in rubber / Nylon 6 short fiber hybrid composite. The cure, mechanical, ageing, thermal and dynamic mechanical properties of nanosilica / Nylon 6 short fiber / elastomeric hybrid composites were studied in detail. The matrices used were natural rubber (NR), nitrile rubber (NBR), styrene butadiene rubber (SBR) and chloroprene rubber (CR). Fiber loading was varied from 0 to 30 parts per hundred rubber (phr) and silica loading was varied from 0 to 9 phr. Hexa:Resorcinol:Silica (HRH) ratio was maintained as 2:2:1. HRH loading was adjusted to 16% of the fiber loading. Minimum torque, maximum torque and cure time increased with silica loading. Cure rate increased with fiber loading and decreased with silica content. The hybrid composites showed improved mechanical properties in the presence of nanosilica. Tensile strength showed a dip at 10 phr fiber loading in the case of NR and CR while it continuously increased with fiber loading in the case of NBR and SBR. The nanosilica improved the tensile strength, modulus and tear strength better than the conventional silica. Abrasion resistance and hardness were also better for the nanosilica composites. Resilience and compression set were adversely affected. Hybrid composites showed anisotropy in mechanical properties. Retention in ageing improved with fiber loading and was better for nanosilica-filled hybrid composites. The nanosilica also improved the thermal stability of the hybrid composite better than the commercial silica. All the composites underwent two-step thermal degradation. Kinetic studies showed that the degradation of all the elastomeric composites followed a first-order reaction. Dynamic mechanical analysis revealed that storage modulus (E’) and loss modulus (E”) increased with nanosiica content, fiber loading and frequency for all the composites, independent of the matrix. The highest rate of increase was registered for NBR rubber.
Resumo:
A detailed study of the blends of ethylene-propylene-diene rubber (EPDM) and chlorobutyl rubber (CIIR) is proposed in this study. These blends may find application in the manufacture of curing diaphragms/curing envelopes for tire curing applications. EPDM possesses better physical properties such as high heat resistance, ozone resistance, cold and moisture resistance, high resistance to permanent defonnation, very good resistance to flex cracking and impact. Because of the low gas and moisture penneability, good weathering resistance and high thermal stability of CIIR, blends of EPDM with CIlR may be attractive, if sufficient mechanical strength can be developed. Although a lot of work has been done on elastomer blends, studies on the blends of EPDM and CIIR rubbers are meagre. Hence in this investigation it is proposed to make a systematic study on the characteristics of EPDM and CIIR rubber blends.The mechanical and physical properties of an elastomer blend depend mainly on the blend compatibility. So in the first part of the study, it is proposed to develop compatible blends of EPDM with CIIR. Various commercial grades of ethylenepropylene- diene rubber are proposed to be blended with a specific grade of chlorobutyl rubber at varying proportions. The extent of compatibility in these blends is proposed to be evaluated based on their mechanical properties such as tensile strength, tear strength and ageing resistance. In addition to the physical property measurements, blend compatibility is also proposed to be studied based on the glass transition behavlour of the blends in relation to the Tg's of the individual components using Differential Scanning Calorimetry (DSC) and Dynamic Mechanical Analysis (DMA). The phase morphology of the blends is also proposed to be investigated by Scanning Electron Microscopy (SEM) studies of the tensile fracture surfaces. In the case of incompatible blends, the effect of addition of chlorosulfonated polyethylene as a compatibiliser is also proposed to be investigated.In the second part of the study, the effect of sulphur curing and resin curing on the curing behaviour and the vulcanizate properties of EPDM/CIIR blends are planned to be evaluated. Since the properties of rubber vulcanizates are determined by their network structures, it is proposed to determine the network structure of the vulcanizates by chemical probes so as to correlate it with the mechanical properties.In the third part of the work, the effect of partial precuring of one of the components prior to blending as a possible means of improving the properties of the blend is proposed to be investigated. This procedure may also help to bring down the viscosity mismatch between the constituent e1astomers and provide covulcanization of the blend.The rheological characteristics and processability of the blends are proposed to be investigated in the last part of the study. To explore their possible applications, the air permeability of the blend samples at varying temperatures is proposed to be measured. The thermal diffusivity behaviour of EPDM/CIlR blends is also proposed to be investigated using novel laser technique. The thermal diffusivity of the blends along with the thermal degradation resistance may help to determine whether the blends are suitable for high temperature applications such as in the manufacturing of curing envelope.
Resumo:
The thesis describes studies on development of short Nylon-6 fibre composites based on rubber-toughened polystyrene (PS). Toughening was done using natural rubber (NR), styrene-butadiene rubber (SBR) and whole tyre reclaim (WTR). The composites were prepared by melt mixing in an internal mixer at 170 oC. It was found that the optimum blend ratio was 85/15 for PS/NR, 90/10 for PS/SBR and 90/22 for PS/WTR blends. The effect of dynamic vulcanisation on 85/15 PS/NR and 90/10 PS/SBR blends using dicumyl peroxide (DCP) at various concentrations were also studied. The dynamic crosslinking improved the tensile properties, flexural properties, impact strength and dynamic mechanical properties of both the blends. The effect of unmodified and resorcinol formaldehyde latex (RFL)-coated short Nylon-6 fibres on the mechanical properties, morphology and dynamic mechanical properties of 85/15 PS/NR, 90/10 PS/SBR and 90/22 PS/WTR blends were studied. Fibre loading was varied from 0 to 3 wt.%. For 85/15 PS/NR blend, there was a significant enhancement in tensile properties, flexural properties and impact strength with 1 wt.% of both unmodified and RFL-coated fibres. Dynamic mechanical analysis revealed that the storage modulus at room temperature was maximum at 1 wt.% fiber loading for both composites. The surface functionality of the fiber was improved by giving alkali treatment. Maleic anhydride-grafted-polystyrene (MA-g-PS) was prepared and used as a compatibiliser. The effect of MA-g-PS on the composites was investigated with respect to mechanical properties, morphology and dynamic mechanical properties. The compatibiliser loading was varied from 0 to 2 wt.%. The properties were enhanced significantly in the case of treated and untreated fibre composites at a compatibiliser loading of 0.75 wt.%. SEM analysis confirmed better bonding between the fibre and the matrix. Dynamic mechanical studies showed that the storage modulus at room temperature improved for treated fibre composites in the presence of compatibiliser. In the case of 90/10 PS/SBR composites, the addition of short Nylon-6 fibres at 1 wt.% loading improved the tensile modulus, flexural properties and impact strength while the tensile strength was marginally reduced. The surface treated fibers along with compatibiliser at 0.5 wt.% improved the tensile properties, flexural properties and impact strength. DMA reveale that the storage modulus at room temperature was better for composites containing untreated fibre and the compatibiliser. In the case of 90/22 PS/WTR blends, 1 wt.% unmodified fibre and 0.5 wt.% RFL-coated fibres improved tensile modulus, flexural properties and impact strength. Tensile strength was improved marginally. The surface treatment of Nylon fibre and the addition of compatibiliser at 0.5 wt.% enhanced the tensile properties, flexural properties and impact strength. The dynamic mechanical analysis showed that the storage modulus at room temperature was better for untreated fibre composites in conjunction with the compatibiliser. The thermal stability of PS/NR was studied by TGA. Thermal stability of the blends improved with dynamic vulcanisation and with the incorporation of RFL-coated Nylon fibres. The untreated and partially hydrolyzed fibre composites in conjunction with the compatibiliser enhanced the thermal stability. Kinetic studies showed that the degradation of the blends and the composites followed first order kinetics.
Resumo:
High styrene rubber ionomers were prepared by sulfonating styrene–butadiene rubber of high styrene content (high styrene rubber) in 1,2-dichloroethane using acetyl sulfate reagent, followed by neutralization of the precursor acids using methanolic zinc acetate. The ionomers were characterized using X-ray fluorescence spectroscopy, Fourier transform infrared spectroscopy (FTIR), nuclear magnetic resonance spectroscopy (NMR), dynamic mechanical analysis (DMA), and also by the evaluation of mechanical properties. The FTIR studies of the ionomer reveal that the sulfonate groups are attached to the benzene ring. The NMR spectra give credence to this observation. Results of DMA show an ionic transition (Ti) in addition to glass–rubber transition (Tg). Incorporation of ionic groups results in improved mechanical properties as well as retention of properties after three cycles of processing
Resumo:
Hybrid polymer networks (HPNs) based on unsaturated polyester resin (UPR) and epoxy resins were synthesized by reactive blending. The epoxy resins used were epoxidised phenolic novolac (EPN), epoxidised cresol novolac (ECN) and diglycidyl ether of bisphenol A (DGEBA). Epoxy novolacs were prepared by glycidylation of the novolacs using epichlorohydrin. The physical, mechanical, and thermal properties of the cured blends were compared with those of the control resin. Epoxy resins show good miscibility and compatibility with the UPR resin on blending and the co-cured resin showed substantial improvement in the toughness and impact resistance. Considerable enhancement of tensile strength and toughness are noticed at very low loading of EPN. Thermogravimetric analysis (TGA), dynamic mechanical analysis (DMA) and diVerential scanning calorimetry (DSC) were employed to study the thermal properties of the toughened resin. The EPN/ UPR blends showed substantial improvement in thermal stability as evident from TGA and damping data. The fracture behaviour was corroborated by scanning electron microscopy (SEM). The performance of EPN is found to be superior to other epoxy resins
Resumo:
Graphene has captured the attention of scientific community due to recently emerging high performance applications. Hence, studying its reinforcing effects on epoxy resin is a significant step. In this study, microwave exfoliated reduced graphene oxide (MERGO) was prepared from natural graphite for subsequent fabrication of epoxy nanocomposites using triethylenetetramine (TETA) as a curing agent via insitu polymerization. Thermogravimetric analysis (TGA), X-ray diffraction (XRD), Raman spectroscopy, Fourier transform infrared spectroscopy (FTIR), C13 NMR spectroscopy, X-ray photoelectron spectroscopy (XPS) and ultravioletevisible (UVevis) spectroscopy were employed to confirm the simultaneous reduction and exfoliation of graphene oxide. The reinforcing effect of MERGO on epoxy resin was explored by investigating its static mechanical properties and dynamic mechanical analysis (DMA) at MERGO loadings of 0 to 0.5 phr. The micro-structure of epoxy/MERGO nanocomposites was investigated using scanning electron microscope (SEM), transmission electron microscope (TEM) and XRD techniques. The present work reports an enhancement of 32%, 103% and 85% in tensile, impact and flexural strength respectively of epoxy by the addition of even 0.25 phr MERGO. At this loading elastic and flexural moduli also increased by 10% and 65%, respectively. Single-edge-notch three-point-Bending (SEN-TPB) fracture toughness (KIC) measurements were carried out where a 63% increase was observed by the introduction of 0.25 phr MERGO. The interfacial interactions brought about by graphene also benefited the dynamic mechanical properties to a large extent in the form of a significant enhancement in storage modulus and slightly improved glass transition temperature. Considerable improvements were also detected in dielectric properties. The epoxy nanocomposite also attained an ac conductivity of 10 5 S/m and a remarkable increase in dielectric constant. The simple and cost effective way of graphene synthesis for the fabrication of epoxy/MERGO nanocomposites may be extended to the preparation of other MERGO based polymer nanocomposites. This remarkable class of materials has thrown open enormous opportunities for developing conductive adhesives and in microelectronics
Resumo:
Three dimensional (3D) composites are strong contenders for the structural applications in situations like aerospace,aircraft and automotive industries where multidirectional thermal and mechanical stresses exist. The presence of reinforcement along the thickness direction in 3D composites,increases the through the thickness stiffness and strength properties.The 3D preforms can be manufactured with numerous complex architecture variations to meet the needs of specific applications.For hot structure applications Carbon-Carbon(C-C) composites are generally used,whose property variation with respect to temperature is essential for carrying out the design of hot structures.The thermomechanical behavior of 3D composites is not fully understood and reported.The methodology to find the thermomechanical properties using analytical modelling of 3D woven,3D 4-axes braided and 3D 5-axes braided composites from Representative Unit Cells(RUC's) based on constitutive equations for 3D composites has been dealt in the present study.High Temperature Unidirectional (UD) Carbon-Carbon material properties have been evaluated using analytical methods,viz.,Composite cylinder assemblage Model and Method of Cells based on experiments carried out on Carbon-Carbon fabric composite for a temparature range of 300 degreeK to 2800degreeK.These properties have been used for evaluating the 3D composite properties.From among the existing methods of solution sequences for 3D composites,"3D composite Strength Model" has been identified as the most suitable method.For thegeneration of material properies of RUC's od 3D composites,software has been developed using MATLAB.Correlaton of the analytically determined properties with test results available in literature has been established.Parametric studies on the variation of all the thermomechanical constants for different 3D performs of Carbon-Carbon material have been studied and selection criteria have been formulated for their applications for the hot structures.Procedure for the structural design of hot structures made of 3D Carbon-Carbon composites has been established through the numerical investigations on a Nosecap.Nonlinear transient thermal and nonlinear transient thermo-structural analysis on the Nosecap have been carried out using finite element software NASTRAN.Failure indices have been established for the identified performs,identification of suitable 3D composite based on parametric studies on strength properties and recommendation of this material for Nosecap of RLV based on structural performance have been carried out in this Study.Based on the 3D failure theory the best perform for the Nosecap has been identified as 4-axis 15degree braided composite.
Resumo:
To ensure quality of machined products at minimum machining costs and maximum machining effectiveness, it is very important to select optimum parameters when metal cutting machine tools are employed. Traditionally, the experience of the operator plays a major role in the selection of optimum metal cutting conditions. However, attaining optimum values each time by even a skilled operator is difficult. The non-linear nature of the machining process has compelled engineers to search for more effective methods to attain optimization. The design objective preceding most engineering design activities is simply to minimize the cost of production or to maximize the production efficiency. The main aim of research work reported here is to build robust optimization algorithms by exploiting ideas that nature has to offer from its backyard and using it to solve real world optimization problems in manufacturing processes.In this thesis, after conducting an exhaustive literature review, several optimization techniques used in various manufacturing processes have been identified. The selection of optimal cutting parameters, like depth of cut, feed and speed is a very important issue for every machining process. Experiments have been designed using Taguchi technique and dry turning of SS420 has been performed on Kirlosker turn master 35 lathe. Analysis using S/N and ANOVA were performed to find the optimum level and percentage of contribution of each parameter. By using S/N analysis the optimum machining parameters from the experimentation is obtained.Optimization algorithms begin with one or more design solutions supplied by the user and then iteratively check new design solutions, relative search spaces in order to achieve the true optimum solution. A mathematical model has been developed using response surface analysis for surface roughness and the model was validated using published results from literature.Methodologies in optimization such as Simulated annealing (SA), Particle Swarm Optimization (PSO), Conventional Genetic Algorithm (CGA) and Improved Genetic Algorithm (IGA) are applied to optimize machining parameters while dry turning of SS420 material. All the above algorithms were tested for their efficiency, robustness and accuracy and observe how they often outperform conventional optimization method applied to difficult real world problems. The SA, PSO, CGA and IGA codes were developed using MATLAB. For each evolutionary algorithmic method, optimum cutting conditions are provided to achieve better surface finish.The computational results using SA clearly demonstrated that the proposed solution procedure is quite capable in solving such complicated problems effectively and efficiently. Particle Swarm Optimization (PSO) is a relatively recent heuristic search method whose mechanics are inspired by the swarming or collaborative behavior of biological populations. From the results it has been observed that PSO provides better results and also more computationally efficient.Based on the results obtained using CGA and IGA for the optimization of machining process, the proposed IGA provides better results than the conventional GA. The improved genetic algorithm incorporating a stochastic crossover technique and an artificial initial population scheme is developed to provide a faster search mechanism. Finally, a comparison among these algorithms were made for the specific example of dry turning of SS 420 material and arriving at optimum machining parameters of feed, cutting speed, depth of cut and tool nose radius for minimum surface roughness as the criterion. To summarize, the research work fills in conspicuous gaps between research prototypes and industry requirements, by simulating evolutionary procedures seen in nature that optimize its own systems.
Resumo:
In this thesis, the applications of the recurrence quantification analysis in metal cutting operation in a lathe, with specific objective to detect tool wear and chatter, are presented.This study is based on the discovery that process dynamics in a lathe is low dimensional chaotic. It implies that the machine dynamics is controllable using principles of chaos theory. This understanding is to revolutionize the feature extraction methodologies used in condition monitoring systems as conventional linear methods or models are incapable of capturing the critical and strange behaviors associated with the metal cutting process.As sensor based approaches provide an automated and cost effective way to monitor and control, an efficient feature extraction methodology based on nonlinear time series analysis is much more demanding. The task here is more complex when the information has to be deduced solely from sensor signals since traditional methods do not address the issue of how to treat noise present in real-world processes and its non-stationarity. In an effort to get over these two issues to the maximum possible, this thesis adopts the recurrence quantification analysis methodology in the study since this feature extraction technique is found to be robust against noise and stationarity in the signals.The work consists of two different sets of experiments in a lathe; set-I and set-2. The experiment, set-I, study the influence of tool wear on the RQA variables whereas the set-2 is carried out to identify the sensitive RQA variables to machine tool chatter followed by its validation in actual cutting. To obtain the bounds of the spectrum of the significant RQA variable values, in set-i, a fresh tool and a worn tool are used for cutting. The first part of the set-2 experiments uses a stepped shaft in order to create chatter at a known location. And the second part uses a conical section having a uniform taper along the axis for creating chatter to onset at some distance from the smaller end by gradually increasing the depth of cut while keeping the spindle speed and feed rate constant.The study concludes by revealing the dependence of certain RQA variables; percent determinism, percent recurrence and entropy, to tool wear and chatter unambiguously. The performances of the results establish this methodology to be viable for detection of tool wear and chatter in metal cutting operation in a lathe. The key reason is that the dynamics of the system under study have been nonlinear and the recurrence quantification analysis can characterize them adequately.This work establishes that principles and practice of machining can be considerably benefited and advanced from using nonlinear dynamics and chaos theory.
Resumo:
Timely detection of sudden change in dynamics that adversely affect the performance of systems and quality of products has great scientific relevance. This work focuses on effective detection of dynamical changes of real time signals from mechanical as well as biological systems using a fast and robust technique of permutation entropy (PE). The results are used in detecting chatter onset in machine turning and identifying vocal disorders from speech signal.Permutation Entropy is a nonlinear complexity measure which can efficiently distinguish regular and complex nature of any signal and extract information about the change in dynamics of the process by indicating sudden change in its value. Here we propose the use of permutation entropy (PE), to detect the dynamical changes in two non linear processes, turning under mechanical system and speech under biological system.Effectiveness of PE in detecting the change in dynamics in turning process from the time series generated with samples of audio and current signals is studied. Experiments are carried out on a lathe machine for sudden increase in depth of cut and continuous increase in depth of cut on mild steel work pieces keeping the speed and feed rate constant. The results are applied to detect chatter onset in machining. These results are verified using frequency spectra of the signals and the non linear measure, normalized coarse-grained information rate (NCIR).PE analysis is carried out to investigate the variation in surface texture caused by chatter on the machined work piece. Statistical parameter from the optical grey level intensity histogram of laser speckle pattern recorded using a charge coupled device (CCD) camera is used to generate the time series required for PE analysis. Standard optical roughness parameter is used to confirm the results.Application of PE in identifying the vocal disorders is studied from speech signal recorded using microphone. Here analysis is carried out using speech signals of subjects with different pathological conditions and normal subjects, and the results are used for identifying vocal disorders. Standard linear technique of FFT is used to substantiate thc results.The results of PE analysis in all three cases clearly indicate that this complexity measure is sensitive to change in regularity of a signal and hence can suitably be used for detection of dynamical changes in real world systems. This work establishes the application of the simple, inexpensive and fast algorithm of PE for the benefit of advanced manufacturing process as well as clinical diagnosis in vocal disorders.
Resumo:
Data centre is a centralized repository,either physical or virtual,for the storage,management and dissemination of data and information organized around a particular body and nerve centre of the present IT revolution.Data centre are expected to serve uniinterruptedly round the year enabling them to perform their functions,it consumes enormous energy in the present scenario.Tremendous growth in the demand from IT Industry made it customary to develop newer technologies for the better operation of data centre.Energy conservation activities in data centre mainly concentrate on the air conditioning system since it is the major mechanical sub-system which consumes considerable share of the total power consumption of the data centre.The data centre energy matrix is best represented by power utilization efficiency(PUE),which is defined as the ratio of the total facility power to the IT equipment power.Its value will be greater than one and a large value of PUE indicates that the sub-systems draw more power from the facility and the performance of the data will be poor from the stand point of energy conservation. PUE values of 1.4 to 1.6 are acievable by proper design and management techniques.Optimizing the air conditioning systems brings enormous opportunity in bringing down the PUE value.The air conditioning system can be optimized by two approaches namely,thermal management and air flow management.thermal management systems are now introduced by some companies but they are highly sophisticated and costly and do not catch much attention in the thumb rules.
Resumo:
Natural systems are inherently non linear. Recurrent behaviours are typical of natural systems. Recurrence is a fundamental property of non linear dynamical systems which can be exploited to characterize the system behaviour effectively. Cross recurrence based analysis of sensor signals from non linear dynamical system is presented in this thesis. The mutual dependency among relatively independent components of a system is referred as coupling. The analysis is done for a mechanically coupled system specifically designed for conducting experiment. Further, cross recurrence method is extended to the actual machining process in a lathe to characterize the chatter during turning. The result is verified by permutation entropy method. Conventional linear methods or models are incapable of capturing the critical and strange behaviours associated with the dynamical process. Hence any effective feature extraction methodologies should invariably gather information thorough nonlinear time series analysis. The sensor signals from the dynamical system normally contain noise and non stationarity. In an effort to get over these two issues to the maximum possible extent, this work adopts the cross recurrence quantification analysis (CRQA) methodology since it is found to be robust against noise and stationarity in the signals. The study reveals that the CRQA is capable of characterizing even weak coupling among system signals. It also divulges the dependence of certain CRQA variables like percent determinism, percent recurrence and entropy to chatter unambiguously. The surrogate data test shows that the results obtained by CRQA are the true properties of the temporal evolution of the dynamics and contain a degree of deterministic structure. The results are verified using permutation entropy (PE) to detect the onset of chatter from the time series. The present study ascertains that this CRP based methodology is capable of recognizing the transition from regular cutting to the chatter cutting irrespective of the machining parameters or work piece material. The results establish this methodology to be feasible for detection of chatter in metal cutting operation in a lathe.
Resumo:
This paper presents the results from an experimental program and an analytical assessment of the influence of addition of fibers on mechanical properties of concrete. Models derived based on the regression analysis of 60 test data for various mechanical properties of steel fiber-reinforced concrete have been presented. The various strength properties studied are cube and cylinder compressive strength, split tensile strength, modulus of rupture and postcracking performance, modulus of elasticity, Poisson’s ratio, and strain corresponding to peak compressive stress. The variables considered are grade of concrete, namely, normal strength 35 MPa , moderately high strength 65 MPa , and high-strength concrete 85 MPa , and the volume fraction of the fiber Vf =0.0, 0.5, 1.0, and 1.5% . The strength of steel fiber-reinforced concrete predicted using the proposed models have been compared with the test data from the present study and with various other test data reported in the literature. The proposed model predicted the test data quite accurately. The study indicates that the fiber matrix interaction contributes significantly to enhancement of mechanical properties caused by the introduction of fibers, which is at variance with both existing models and formulations based on the law of mixtures