Measuring Feed Force in Machining Using a Strain Gage

Measuring the forces that work during machining has been being concerned by researchers for years. There are three main forces that work in turning: thrust force, axial force, and radial force. Thus, feeding force measurement is needed in machine manufacturing. This research attempts to develop measurement method through feeding force, using strain gauge sensor. The aim of measurement of feeding force in this research is to find out the influence parameter of machine towards feeding force. The research used experimental method with design experiment Taguchi to know the influence of machine parameters to feeding force in turning process. The measurement tool is strain gauge sensor connected to cutting tool. The workspace is alluminium 6061 with 15 mm in diameter and 150 mm in length. The parameters for this research are speed rate (140 rpm, 215 rpm, and 330 rpm), feed rate (0,043 mm/r , 0,065 mm/r , and 0,081 mm/r), and depth of cut (0,2 mm, 0,4 mm, and 0,6 mm). The result showed that speed rate is the most significant parameter, with the contribution percentage is 92 %. Speed rate and feed rate parameter have insignificant influence. The contribution percentage of speed rate is 2% while the feed rate has % contribution percentage. The conclusion of the research is that the bigger number of speed rate, the bigger feeding force it will have.

Equation of State for the Lennard-Jones Truncated and Shifted Fluid with a Cut-off Radius of 2.5 σ based on Perturbation Theory and its Applications to Interfacial Thermodynamics

An equation of state is presented for describing thermodynamic properties of the Lennard-Jones truncated and shifted (LJTS) potential with a cut-off radius of 2.5 σ. It is developed using perturbation theory with a hard-sphere reference term and labelled with the acronym PeTS (perturbed truncated and shifted). The PeTS equation of state describes the properties of the bulk liquid and vapour and the corresponding equilibrium of the LJTS fluid well. Furthermore, it is developed so that it can be used safely in the entiremetastable and unstable region, which is an advantage compared to existing LJTS equations of state. This makes the PeTS equation of state an interesting candidate for studies of interfacial properties. The PeTS equation of state is applied here in two theories of interfaces, namely density gradient theory (DGT) and density functional theory (DFT). The influence parameter of DGT as well as the interaction averaging diameter of DFT are fitted to data of the surface tension of the LJTS fluid obtained from molecular simulation. The results from both theories agree very well with those from the molecular simulations.

A comparison of dyadic and social network assessments of peer influence

The present study compares two methods for assessing peer influence: the longitudinal actor–partner interdependence model (L-APIM) and the longitudinal social network analysis (L-SNA) Model. The data were drawn from 1,995 (49% girls and 51% boys) third grade students ( M age = 9.68 years). From this sample, L-APIM ( n = 206 indistinguishable dyads and n = 187 distinguishable dyads) and L-SNA ( n = 1,024 total network members) subsamples were created. Students completed peer nominations and objective assessments of mathematical reasoning in the spring of the third and fourth grades. Patterns of statistical significance differed across analyses. Stable distinguishable and indistinguishable L-APIM dyadic analyses identified reciprocated friend influence such that friends with similar levels of mathematical reasoning influenced one another and friends with higher math reasoning influenced friends with lower math reasoning. L-SNA models with an influence parameter (i.e., average reciprocated alter) comparable to that assessed in L-APIM analyses failed to detect influence effects. Influence effects did emerge, however, with the addition of another, different social network influence parameter (i.e., average alter influence effect). The diverging results may be attributed to differences in the sensitivity of the analyses, their ability to account for structural confounds with selection and influence, the samples included in the analyses, and the relative strength of influence in reciprocated best as opposed to other friendships.

Using genetic programming to model the bond strength of GFRP bars in concrete under the effects of design guidelines

Purpose This paper aims to use a derivative of genetic programming to predict the bond strength of glass fiber-reinforced polymer (GFRP) bars in concrete under the effects of design guidelines. In developing bond strength prediction models, this paper prioritized simplicity and meaningfulness over extreme accuracy. Design/methodology/approach Assessing the bond strength of GFRP bars in concrete is a critical issue in designing and building reinforced concrete structures. Findings Ultimately, the equation of a linear form of a particular design guideline was suggested as the optimal prediction model. Improvements to the current design guidelines suggested by this model include setting a 1.31 magnification and considering the effects of the three significant parameters of bar diameter (db), minimum cover-to-bar diameter (C/db) and development length to bar diameter (l/db) under an acceptable root mean square error accuracy of around 2 MPa. Furthermore, the model suggests that the original influence parameter of concrete compressive strength (fc) may be removed from bond strength calculations. Originality/value The model suggests that the original influence parameter of concrete compressive strength (fc) may be removed from bond strength calculations.

Biomedical Applications of Biomaterials Functionalized with Magnetic Nanoparticles

The combination of magnetic nanoparticles and a biocompatible material leads to the manufacturing of a multifunctional and remotely controlled platform useful for diverse biomedical issues. If a static magnetic field is applied, a magnetic scaffold behaves like an attraction platform for magnetic carriers of growth factors, thus being a potential tool to enhance magnetic drug delivery in regenerative medicine. To translate in practice this potential application, a careful and critical description of the physics and the influence parameter is required. This chapter covers the mathematical modeling of the process and assesses the problem of establishing the influence of the drug delivery system on tissue regeneration. On the other hand, if a time-varying magnetic field is applied, the magnetic nanoparticles would dissipate heat, which can be exploited to perform local hyperthermia treatment on residual cancer cells in the bone tissue. To perform the treatment planning, it is necessary to account for the modeling of the intrinsic nonlinear nature of the heat dissipation dynamic in magnetic prosthetic implants. In this work, numeric experiments to investigate the physiopathological features of the biological system, linked to the properties of the nanocomposite magnetic material, to assess its effectiveness as therapeutic agents are presented.

Parameter Estimation in Uncertain Heat Equations

Uncertain heat equations are aimed to model the variation of temperature in a given region over time under uncertain influence. Parameter estimation is an important and significant topic in uncertain heat equations because after we construct a uncertain heat equation according to the specific problem to model a dynamic system, it is natural that the uncertain heat equation contains unknown parameters such as the unknown thermal diffusivity and unknown parameters of strength of heat source. For that matter, this paper first employs the moment method to estimate unknown parameters in uncertain heat equations. To show the process of parameter estimation, two numerical examples are given.

TORSIONAL STIFFNESS AS AN INFLUENCE PARAMETER ON ARCH STABILITY

Arch bridge springs can be connected to concrete abutments either by prestressing bars or by connectors. In both options, the torsional stiffness is substantially reduced, compared to the full arch cross sectional area. The influence of this lack of torsional stiffness on arch buckling is being researched, both numerically and experimentally. To reduce any residual stress during tests, wooden rods that simulate the arch were submerged in water and subsequently bent to the desired shape. Imperfections of the arch samples are measured. Two unequal concentrated loads are applied to the samples, thus simulating the effect of movable loads across half of the arch span. During loading, lateral deflections were measured until elastic buckling occurred. The simulation of more flexible rotation of the springs required replacing the cross section by thin equivalent side plates. Since all parameters have not been isolated, the results are limited yet. However, comparing the failure load of similar conditions, the reduction of torsion stiffness by 81.48% reduces the failure load by 26.3%. This indicates that total prevention of axial rotation may not be imperative for arch bridges.

Effect of sintered electrode on microhardness and microstructure in electro discharge deposition of magnesium alloy

In this study, an endeavour have been made to depositing the electrode materials over the surface of the magnesium alloy using electrical discharge machining (EDM) with WC-Cu powder compacted sintered electrode. Various process parameters such as compaction load, discharge current and pulse on time are selected to carry out the experiment in order to attain the maximum material migration rate (MMR) or deposition rate and microhardness (MH). It was concluded that the MMR and MH increased with increase in discharge current and pulse on time at low compacted electrode but it is decreased at lower discharge current and pulse on time. Highest MMR and MH were attained successfully at partial sintered low compaction load electrode. Microstructure evaluation has been carried out on deposited surface using scanning electron microscopy (SEM) and presence of electrode element in the deposited surface was confirmed by energy dispersive spectroscopy (EDS). Defects mechanism such as globules and craters are formed during EDC with high current and pulse on time respectively, which diminishes the surface roughness. It was observed that the compaction load is the influence parameter on the MMR and MH.

Climate change impacts model parameter sensitivity – What does this mean for calibration?

Hydrological models are useful tools to explore the hydrological impact of climate change. Many of these models require calibration. A frequently employed strategy is to calibrate the five parameters that were found to be most relevant as identified in a sensitivity analysis. However, parameter sensitivity varies over climate, and therefore climate change could influence parameter sensitivity. In this study we explore the change in parameter sensitivity within a plausible climate change rate, and investigate if changes in sensitivity propagate into the calibration strategy. We employed three frequently used hydrological models (SAC, VIC, and HBV), and explored parameter sensitivity changes across 605 catchments in the United States by comparing a GCM-forced historical and future period. Consistent among all models is that the sensitivity of snow parameters decreases in the future. Which parameters increase in sensitivity is less consistent among the models. In 43 % to 49 % of the catchments, dependent on the model, at least one parameter changes in the future in the top-5 most sensitive parameters. The maximum number of changes in the parameter top-5 is two, in 2–4 % of the investigated catchments. The value of the parameters that enter the top-5 cannot easily be identified based on historical data, because the model is not yet sensitive to these parameters. This requires an adapted calibration strategy for long-term projections, for which we provide several suggestions. The disagreement among the models on processes becoming relevant in future projections also calls for a strict evaluation of the adequacy of the model structure and the model parameters implemented therein.

Influence of Analyzed Sequence Length on Parameters in Laryngeal High-Speed Videoendoscopy

Laryngeal high-speed videoendoscopy (HSV) allows objective quantification of vocal fold vibratory characteristics. However, it is unknown how the analyzed sequence length affects some of the computed parameters. To examine if varying sequence lengths influence parameter calculation, 20 HSV recordings of healthy females during sustained phonation were investigated. The clinical prevalent Photron Fastcam MC2 camera with a frame rate of 4000 fps and a spatial resolution of 512 × 256 pixels was used to collect HSV data. The glottal area waveform (GAW), describing the increase and decrease of the area between the vocal folds during phonation, was extracted. Based on the GAW, 16 perturbation parameters were computed for sequences of 5, 10, 20, 50 and 100 consecutive cycles. Statistical analysis was performed using SPSS Statistics, version 21. Only three parameters (18.8%) were statistically significantly influenced by changing sequence lengths. Of these parameters, one changed until 10 cycles were reached, one until 20 cycles were reached and one, namely Amplitude Variability Index (AVI), changed between almost all groups of different sequence lengths. Moreover, visually observable, but not statistically significant, changes within parameters were observed. These changes were often most prominent between shorter sequence lengths. Hence, we suggest using a minimum sequence length of at least 20 cycles and discarding the parameter AVI.