Use of a ring probe to determine thermal conductivity coefficients

A method for using a constant-power ring probe to determine thermal conductivity coefficients is considered.Translated from Inzhenerno-Fizicheskii Zhurnal, Vol. 46, No. 3, pp. 451–455, March, 1984.     

Weibull regression models for reliability data

Regression models based on the Weibull distribution are reviewed, and a number of applications given involving reliability data. The main techniques involved are numerical maximum likelihood as a near-universal technique for fitting models, and probability plots to assess goodness of fit. Several examples are used to illustrate these techniques, a common theme being the discrepancy between fitted models and those suggested by simple physical arguments. The reasons for this are examined in some detail. It is suggested that neither physical reasoning nor statistical analysis is adequate by itself, but that some combination of the two is required.     

Review of effective thermal conductivity models for foods

The literature associated with modelling and predicting the thermal conductivities of food products has been reviewed. The uncertainty involved in thermal conductivity prediction increases as the differences between the food components' thermal conductivities increase, which means that there is greater uncertainty involved with predicting the thermal conductivity of foods which are porous and/or frozen, than with unfrozen, non-porous foods. For unfrozen, non-porous foods, a number of simple effective thermal conductivity models that are functions only of the components' thermal conductivities and volume fractions may be used to provide predictions to within ±10%. For frozen and/or porous foods, the prediction procedure is more complicated, and usually requires the prediction of porosity and/or ice fraction, which introduces another source of error. The effective thermal conductivity model for these foods may require an extra parameter (in addition to the components' thermal conductivities and volume fractions) whose value must often be determined empirically. Recommendations for selecting models for different classes of foods are provided. There is scope for more research to be done in this area.     

A correlation of thermal conductivity data for helium

A correlation for the thermal conductivity of helium has been developed which covers the temperature range from temperatures just above the lambda line to 830 K, and densities up to about 160 kg m⁻³. The data used incorporate some recent experimental results which cover the temperature range from 4 K to 20 K including the critical region. The correlation gives an equation which generally fits the experimental data within ± 5%. However, at low temperature, the experimental data deviate up to about 10% from predictions based upon viscosity measurements or molecular dynamics calculations.     

Modeling transient absorption and thermal conductivity in a simple nanofluid

Molecular dynamics simulations are used to simulate the thermal properties of a model fluid containing nanoparticles (nanofluid). By modeling transient absorption experiments, we show that they provide a reliable determination of interfacial resistance between the particle and the fluid. The flexibility of molecular simulation allows us to consider separately the effect of confinement, particle mass, and Brownian motion on the thermal transfer between fluid and particle. Finally, we show that in the absence of collective effects, the heat conductivity of the nanofluid is well described by the classical Maxwell Garnet equation model.     

Using degradation data to assess reliability: a case study on train wheel degradation

Degradation experiments are usually used to assess the lifetime distribution of highly reliable products, which are not likely to fail under the traditional life tests or accelerated life tests. In such cases, if there exist product characteristics whose degradation over time can be related to reliability, then collecting ‘degradation data’ can provide information about product reliability. In general, the degradation data are modeled by a nonlinear regression model with random coefficients. If we can obtain the estimates of parameters under the model, then the failure‐time distribution can be estimated. In order to estimate those parameters, three basic methods are available, namely, the analytical, numerical and the approximate. They are chosen according to the complexity of the degradation path model used in the analysis. In this paper, the numerical and the approximate methods are compared in a simulation study, assuming a simple linear degradation path model. A comparison with traditional failure‐time analysis is also performed. The mean‐squared error of the estimated 100pth percentile of the lifetime distribution is evaluated for each one of the approaches. The approaches are applied to a real degradation data set. Copyright © 2008 John Wiley & Sons, Ltd.     

实测数据对大气颗粒物浓度计算模式的验证

针对常用的大气颗粒物(PM10、PM2.5)浓度计算模式计算结果偏差较大的问题,由太原市城区例行监测的PM10浓度估算出燃煤电厂导致的大气颗粒物(PM10、PM2.5)浓度推算值,使用AERMOD和CALPUFF模式计算燃煤电厂排放源导致的大气颗粒物浓度,对大气颗粒物浓度的计算值与实测值进行了比较分析与评估。结果表明:在城市区域,性能较佳的大气颗粒物浓度计算模式是AERMOD模式。     

Accelerated failure time models for reliability data analysis

Despite the popularity of the proportional hazards model (PHM) in analysing many kinds of reliability data, there are situations in which it is not appropriate. The accelerated failure time model (AFT) then provides an alternative. In this paper, a unified treatment of the accelerated failure time model is outlined for the standard reliability distributions (Weibull, log-normal, inverse Gaussian, gamma). The problem of choosing between the accelerated failure time models and proportional hazard models is discussed and effects of misspecification are reported. The techniques are illustrated in the analysis of data from a fatigue crack growth experiment.     

A simple method to assess detonation temperature without using any experimental data and computer code

Detonation temperature of C(a)H(b)N(c)O(d) explosives can be predicted from a, b, c, d and calculated gas phase heat of formation of explosives without using any assumed detonation products and experimental data. Two new correlations are introduced for calculation of detonation temperature of aromatic and non-aromatic explosive compounds so that it is shown here how simply calculated heat of formation by additivity rule and atomic composition are only necessary data for this simple prediction. Calculated detonation temperatures by the introduced correlations for both pure and explosive formulations show good agreement with respect to measured detonation temperatures and complicated computer codes. The average mean absolute error in detonation temperature is within about 7.0%.     

Extension of soil thermal conductivity models to frozen meats with low and high fat content

Thermal conductivity models of frozen soils were analyzed and compared with similar models developed for frozen foods. In total, eight thermal conductivity models and 54 model versions were tested against experimental data of 13 meat products in the temperature range from 0 to −40 °C. The model by deVries, with water+ice (wi) as the continuous phase, showed overall the best predictions. The use of wi leads generally to improved predictions in comparison to ice; water as the continuous phase is beneficial only to deVries model, mostly from −1 to −20 °C; fat is advantageous only to meats with high fat content. The results of this work suggest that the more sophisticated way of estimating the thermal conductivity for a disperse phase in the deVries model might be more appropriate than the use of basic multi-phase models (geometric mean, parallel, and series). Overall, relatively small differences in predictions were observed between the best model versions by deVries, Levy, Mascheroni, Maxwell or Gori as applied to frozen meats with low content of fat. These differences could also be generated by uncertainty in meat composition, temperature dependence of thermal conductivity of ice, measurement errors, and limitation of predictive models.     

Use of the linear heat flow for poor conductors and its application to the thermal conductivity of nylon

Thermal conductivity measurements have been carried out on Polypenco 101 and Comco brands of nylon 66 (polyhexamethylene adiapamide) rods along the direction of extrusion. The temperature range covered was 1.2 to 350 K, Below 20 K our date (estimated uncertainty ± 2%), together with all known published data, conforms to the expression λ = 0.00193T^1.30Wm^?1K^?1 to within 10%. Radiative effects above 100 K were demonstrated by performing measurements with and without batting; at 300 K there was a 50% difference between the two sets of data. It is concluded that other radiative effects are present besides direct losses of heat. An increase in the slope of the conductivity versus temperature curve was observed for both samples at the brittleness temperature (T_B = 188 K) and a value of λ_max = 0.371 Wm^?1K^?1 was obtained at the glass transition temperature $\text{T}{}_{\mathrm{g}}\text{? 330 K}$. Above 200 K, λ is nearly independent of temperature. A value of 0.365 W m^?1 K^?1 ±3% was found at 300 K, which is about 25% greater than values obtained previously by radial measurements. Anisotropy is a probable cause of this difference. Thermal conductivity integrals have been constructed from the data.     

Theoretically based data assessment for the correlation of the thermal conductivity of dilute gases

This paper presents two schemes for a theoretically based data assessment of the thermal conductivity of dilute polyatomic gases. The first employs the simplified Thijsse expression, combined with accurate experimental data obtained from a transient hot-wire apparatus, as reference. The second makes use of theoretical results for the temperature dependence of the ratio D _int/D. Both methods lead to mutually consistent results for linear molecules and to useful criteria for discriminating between experimental data sets. The paper also demonstrates the influence of data burdened with systematic errors upon the final results of different correlation schemes.     

热障涂层导热率的测量及控制技术

摘要：作为一种有效的改善发动机的性能、减少发动机零部件的成本，延长其使用寿命的技术，热障涂层(TBC)已得到了越来越广泛的应用。在所有涉及热障涂层性能的物理参数中，导热率被认为是最重要的指标之一。本文介绍了热障涂层技术的发展现状，总结了热障涂层导热率测量的3种主要方法(激光发射法、3-ω法和光声法)的优缺点及适用范围，讨论了减少热障涂层导热率的主要技术。从试验数据来看，加入特殊的添加剂、改善涂层的微观组织构、采用多层复合结构是降低若障涂层导热率的有效方法。     

A cross-cultural procedure to assess reliability and measurement invariance

Steenkamp and Baumgartner (1998) developed a procedure to assess measurement invariance across cultures. The study presented here applied their procedure to a scale to measure cognitive age (Barak, 1979; 1987; 1998; Barak and Schiffman, 1981) and relied on data collected in three Non-Western societies: India (N=195), China (N=250), and Korea (N=251). The results from a series of confirmatory factor analyses indicate that the technique provides a valuable tool to assess measurement invariance across cultures. The results further showed the cognitive age scale to be applicable in the three diverse cultures surveyed.     

Using simulation to assess the service reliability of a train maintenance depot

This paper describes the construction of a discrete‐event simulation model of a proposed train maintenance depot for an underground transportation facility in the UK. The company who were bidding to operate the depot had traditionally been involved in manufacture and so had no experience of either operating such a facility or meeting the type of performance indicators specified in the service‐level agreement. The simulation proved successful in providing a greater understanding of the operation of the depot and the effect of various strategies for meeting demand. It also proved to be an excellent communication tool during the bid process in helping to show capability to the client in meeting proposed service level targets over time and thus prove service reliability. Copyright © 2000 John Wiley & Sons, Ltd.     

Comparison of thermal conductivity data for partially stabilized zirconia with values derived from thermal diffusivity results

The thermal conductivity of partially stabilized zirconia was measured over the temperature range 320–1273 K using the radial heat flow method. The data have an absolute uncertainty of about ±2% and repeat measurements showed no evidence of changes in the thermal conductivity at high temperatures. This also was true for the thermal diffusivity data, which were obtained in vacuum over the temperature range 300–1473 K. Both sets of thermal conductivity data pass through minima at high temperatures. Quantitative differences were observed in the temperatures and thermal conductivities of the two minima. The results were analyzed by assuming parallel conduction by phonons and photons, and the phonon component was identified by fitting lower-temperature data. Extrapolating this curve allowed identification of the photon contribution to the thermal conductivity at high temperatures. The photon contribution approached a T ³ function and was larger in the thermal conductivity specimens. The difference in the photon contributions correlates with changes in the optical properties of the samples produced during the high temperature measurments.