Scatter Analysis of Fatigue Life and Prediction of S–N Curve

In this study, the effects of salt solution, the presence of notch on fatigue life scatter, and sample size selection for estimation of fatigue life under different probabilities and confidence levels have been investigated. Comparison has been made with smooth specimen tested in air medium. It is seen that notches have significantly higher effect than other factors (salt solutions, smooth geometry, etc.). The minimum number of specimens required for fatigue life estimation within tolerable error, R _o, at different fatigue testing conditions has also been presented both for log normal and Weibull distribution models. It has been found that estimation of fatigue life using Weibull model needs higher sample size than log normal model. Beyond a certain sample size, fatigue life estimation is independent of sample size. The article also presents a method for minimum sample size selection procedure to estimate fatigue life or to draw S?CN curve.     

Heat Capacities and Joule–Thomson Coefficients of HFC Refrigerants

In this report, we have examined the behavior of heat capacities and Joule–Thomson coefficients in low- and moderate-density regions based on recent theoretical studies of the ideal-gas heat capacity and virial coefficients of R-32, R-125, R-134a, R-143a, and R-152a. The results have been compared with those derived from empirical equations of state which have been recently developed, based on a large quantity of experimental data for these refrigerants. Both results are in good agreement. Proper behaviors for these second-derivative properties justify the use of the empirical equations of state in low-temperature and low-density regions where no experimental data are available.     

Transient simulation of a miniature Joule–Thomson (J–T) cryocooler with and without the distributed J–T effect

The aim of this work is to develop a transient program for the simulation of a miniature Joule–Thomson (J–T) cryocooler to predict its cool-down characteristics. A one dimensional transient model is formulated for the fluid streams and the solid elements of the recuperative heat exchanger. Variation of physical properties due to pressure and temperature is considered. In addition to the J–T expansion at the end of the finned tube, the distributed J–T effect along its length is also considered. It is observed that the distributed J–T effect leads to additional cooling of the gas in the finned tube and that it cannot be neglected when the pressure drop along the length of the finned tube is large. The mathematical model, method of resolution and the global transient algorithm, within a modular object-oriented framework, are detailed in this paper. As a part of verification and validation of the developed model, cases available in the literature are simulated and the results are compared with the corresponding numerical and experimental data.     

Relationship between the cooldown characteristics of J–T refrigerators and mixture composition

The performance of Joule–Thomson (J–T) refrigerators is strongly influenced by the composition of the refrigerant mixture used. The mixture composition changes if leaks occur, or when a silica-gel drier is used in the system. In this experimental study, we show how the composition changes can be estimated from the cooldown characteristics of J–T refrigerators without using a gas chromatograph. A novel way of representing the cooldown characteristics of J–T refrigerators is presented. The variation of compressor power during the cooldown is also discussed. The results presented here are useful for developers as well as field service engineers in selectively modifying the composition without discarding the entire mixture.     

On the Correction of the Melting Curve of the Eutectic Co–C for the Effect of the Thermal Inertia of the Furnace

This paper considers the influence of the thermal inertia of the furnace on the shape of the melting curve of the eutectic Co–C. To this end, melting experiments have been performed in a uniform three-zone furnace, with an inherent substantial thermal inertia. The thermal inertia has been quantified by measuring the step-response of the furnace with the sample in its solid state, just below its melting temperature. From the analysis of the effect of the thermal inertia of the furnace, it turned out that during melting the temperature distribution within the furnace, surrounding the crucible, is bound to be in a non-stationary state. This provided the key to properly finalizing the correction to be applied. The shape of the corrected curve differs considerably from that of the curve, as measured, in that the former shows a flatter melting plateau, and a larger curvature on the way down to the solidus point. As regards the liquidus temperature \(T_{\mathrm{liq}}\)—of major interest in the characterization of the transition temperature of high-temperature fixed points—it is demonstrated that the thermal inertia of the furnace shows a kind of self-compensating mechanism. But the effects of the thermal inertia of the furnace on the parameters defining the Scheil fit, involved in the correction procedure, were considerable.     

Prediction of Fracture Toughness of Reactor Pressure-Vessel Steels Using the “Master Curve” Concept and Probabilistic Model

Using a probabilistic model and the Master curve approach, the temperature dependence of the brittle fracture toughness of reactor pressure-vessel steel 15Kh2NMFA in the initial state and highly embrittled state is predicted from the results of fracture toughness testing of a cracked Charpy-type specimen at a given temperature. A comparative analysis has shown that for the steel in the initial state the curves calculated by the probabilistic model and by the Master-curve approach are in good agreement. By testing compact-tension specimens of embrittled 2T-CT steel in a wide temperature range the authors have obtained experimental fracture toughness values and compared them with the calculated curves. It is demonstrated that, in the case of the embrittled steel, the curve as calculated by the Master-curve approach fails to describe adequately the experimental results, while the curves plotted by the probabilistic model agree well with the experimental fracture toughness values.     

Application of Liquid Solution Models for the Prediction of Corrosion Phenomena in the Na–K Melt

With the mathematical tool of pseudo-regular solutions, we calculated the solubility of Fe, Cr, Ni, V, Mn, and Mo in eutectic Na–K melt and compared the calculation results with the available experimental data in the literature on the mass transfer of austenitic chrome-nickel steel components in a sodium-potassium loop in nonisothermal conditions. We show that the Wagner parameters of the interaction between oxygen and transition metal might be applied to predict the corrosion behavior of the construction materials in sodium-potassium melt under the presence of oxygen impurity. We present the calculation results of the threshold oxygen concentration required to form ternary sodium oxides with transition metals (Fe, Cr, Ni, V, Mn, Mo) in conditions in which the pure metal is in contact with eutectic Na–K melt.     

Value Capture in the Global Electronics Industry: Empirical Evidence for the “Smiling Curve” Concept

This research asks who captures the greatest value in the global electronics industry by testing the concept of the “smiling curve”, which predicts that the greatest value is captured by upstream and downstream firms, and the lowest value is captured in the middle of the value chain. We test the concept using the Electronic Business 300 data-set for 2000–2005. We find that lead firms and component suppliers earn higher gross margins and net margins compared to contract manufacturers. However, the differences are minimal for return on assets (ROA) and return on equity (ROE). We also find that active component suppliers gain higher profits than passive component suppliers. These findings suggest that the smiling curve is right if value is defined in terms of gross margins, but the cost of sustaining a position on either end of the curve is so high that returns on investment are similar across the curve.     

Operational Readiness Prediction Method and the Implementation of Orcads

１ＩｎｔｒｏｄｕｃｔｉｏｎＴｈｅｔｏｔａｌｔａｒｇｅｔｏｆａｎｙｎｅｗｅｑｕｉｐｍｅｎｔｓｙｓｔｅｍｍｕｓｔｍｅｅｔａｍｉｌｉｔａｒｙｒｅｑｕｉｒｅｍｅｎｔｗｉｔｈａｎａｃｃｅｐｔａｂｌｅｃｏｓｔ．Ｔｈｅｋｅｙｔｏａｃｈｉｅｖｅｔｈｅｔａｒｇｅｔｉ...     

The cool-down behaviour of a miniature Joule–Thomson (J–T) cryocooler with distributed J–T effect and finite reservoir capacity

The objective of this work is to study the effect of the reservoir pressure and volume on the cool-down behaviour of a miniature Joule–Thomson (J–T) cryocooler considering the distributed J–T effect. As the supply pressure to the J–T cooler reduces in case of a reservoir with finite capacity, the volume and the initial pressure of the reservoir are crucial for the operation of the cryocooler. These parameters affect the cool down time, cooling effect and the time for which the cooling effect is obtained at the required cryogenic temperature. A one dimensional transient model is formulated for the fluid streams and the solid elements of the recuperative heat exchanger of the cryocooler. Argon gas is used as the working fluid and its physical properties are evaluated at the local conditions of temperature and pressure. Cases with different reservoir capacities and pressures are worked out to study their effect on the transient behaviour of the cryocooler.     

Study of (Solid–Liquid) Phase Equilibria for Mixtures of Energetic Material Stabilizers and Prediction for Their Subsequent Performance

Solid-liquid equilibria for three binary mixtures of 2-nitrodiphenylamine (1) + diphenylamine (2), ethyl centralite (1) + N-ethyl-4-nitro-N-nitrosoaniline (2), and 2,2 $^{\prime }$ -dinitrodiphenylamine (1) + N-ethyl-4-nitro-N-nitrosoaniline (2) were measured using a differential scanning calorimeter. Simple eutectic behaviors for these systems were observed. The experimental results were correlated by means of original and modified NRTL, Wilson, and UNIQUAC equations. The root–mean–square deviations of the solubility temperatures for all measured data vary from 0.63 K to 3.73 K and depend on the particular model used. The best solubility correlation was obtained with the UNIQUAC model.     

A Global–Local Numerical Model for the Prediction of Impact Induced Damage in Composite Laminates

Delamination and other damage mechanisms, such as matrix cracks, fibre-matrix debonding and fiber failure can appear as a consequence of impact events with foreign objects under in service conditions and maintenance operations. These phenomena are seldom analyzed together without discussing how the interferences between the different damage mechanisms can influence their evolution under different loading conditions. The present work is focused on the development of a specific numerical procedure, able to take into account the failure modes interaction in composite laminated structures subject to a low velocity impact. As a matter of fact, a very fine mesh refinement is required to correctly evaluate the stress state where the impact induced damage onsets. Hence, in order to reduce the computational cost without compromising the accuracy of results, a global/local approach, characterized by a very refined mesh in the critical impact region interacting with a coarser mesh in the rest of the geometrical domain, has been implemented in the FE model. In the present work, Multi-Point-Constraints (MPC) has been used to link the refined local domain to the coarse global domain without using transition meshes. The implementation and the analyses have been performed in the ABAQUS® FE environment.     

Prediction and characterization of growth temperatures in Al–Zn–Mg alloys

Growth temperatures of α-Al, intermetallic τ and eutectic α + τ phases in Al-12 wt.% Zn 6 wt.% Mg alloy has been determined as a function of growth velocity in the range of 3 × 10^? 5 to 1 × 10^? 3 m/s at a temperature gradient of 2500 K/m, using a directional solidification technique. The experimental results are found to be in good agreement with predictions of growth temperatures of competing constituents for multicomponent systems.     

Least Square Fitting for Adaptive Wavelet Generation and Automatic Prediction of Defect Size in the Bearing Using Levenberg–Marquardt Backpropagation

In this communication, an attempt has been made to develop an algorithm for automatic prediction of the size of the bearing defect during operation of a machine. Features for the purpose are meticulously designed so as defect commencement and termination events in the signal could be easily spotted. Information on commencement of defect in the signal, in general, is very weak. It is enhanced by approximating the burst in the signal to a wavelet, making use of least squares fitting. Levenberg–Marquardt back propagation network is used for prediction of defect size from defect features. The comparison shows that the Levenberg–Marquardt back propagation network outperforms another network in terms of accuracy. The experimental validation of the proposed scheme is carried out for four different defect sizes each for the inner race, outer race, and roller defect. The maximum deviation in the width measurement result is 5.35% which occurs in the case of bearing with roller defect of width 1.12 mm. The performance evaluation of the method is also carried out using t test. The result of t test validates the accuracy of proposed method in the prediction of defect width.     

Prediction of iron ore mineral liberation behavior using the Andrews–Mika diagram and beta distribution

A combined grinding and liberation model was studied to predict the liberation characteristics of iron ore comminuted by a ball mill. Comminution characteristics were obtained using the one-size-fraction method; then, the iron ore samples were crushed and separated into several narrow-size fractions by screening. The size fractions were further divided into three classes by magnetic separation, namely concentrate, middling, and tailings. Subsequently, various size classes were subjected to ball milling, and the results were analyzed in the kinetic grinding model. The mineralogical textures of the ground products were analyzed using mineral liberation analysis. The beta distribution and Andrews–Mika diagram characterized the distribution of the iron content within the size fractions. The breakage characteristics of the iron ore samples varied slightly with the iron content. However, the liberation characteristics were well-described by adjusting the four parameters of the beta distribution. The variation in grinding kinetics with composition and liberation model parameters was used in the combined liberation–comminution model to predict the evolution of the size–composition matrix as grinding proceeded. The predicted results align with the experimental results. The developed model can construct a yield–recovery graph and calculate the liberation efficiency to determine the size reduction threshold for efficient separation.     

Prediction of the temperature dependence of fracture toughness of 12Cr–2Ni–Mo refractory steel

We study the influence of temperature and the size of the specimens on the characteristics of static crack resistance of 12Cr–2Ni–Mo refractory steel. It is shown that, in the temperature range 20–450°C, the increase in the thickness of specimens leads to an insignificant increase in fracture toughness obtained along a 5% secant line according to the standards of evaluation of the characteristics of crack resistance. The evaluation of the characteristics of crack resistance of 12Cr–2Ni–Mo steel with regard for the scale effect according to an earlier developed numerical-experimental model reveals the existence of satisfactory agreement with the experimental data in the entire investigated temperature range. Translated from Problemy Prochnosti, No. 4, pp. 78–88, July–August, 2009.