Crystallographic features of phase transformations in solids

The paper reviews the current knowledge and understanding of the crystallographic features of phase transformations in solid materials – metals, ceramics and alloys. It covers both of the broad classes of phase transformations in crystalline solids – martensitic or ‘displacive’ and ‘diffusional’ or ‘reconstructive’. The factors that govern the crystallographic features of these two classes of transformations are compared and contrasted. This provides an appropriate basis for examining the ‘diffusional–displacive’ transformations that appear to exhibit the characteristics of both classes. After a brief summary of the considerable body of experimental data available on the crystallographic characteristics of these various types of phase transformation, the different models/theories advanced to account for these observations are discussed. The main emphasis is on those models/theories that are capable of predicting, rather than just rationalising or explaining, these crystallographic features. The review purposely adopts a unifying approach and attempts to reconcile the controversy that has on occasions existed between the ‘displacive’ group and the ‘diffusional’ group – particularly in respect of the ‘diffusional–displacive’ transformation. Developing a comprehensive understanding of the crystallographic features of all classes of phase transformations is obviously the ultimate goal. The review concludes by assessing how close we are to this final achievement, identifies the gaps in current knowledge and suggests future work.     

Generalized renewal process for analysis of repairable systems with limited failure experience

Repairable systems can be brought to one of possible states following a repair. These states are: ‘as good as new’, ‘as bad as old’, ‘better than old but worse than new’, ‘better than new’, and ‘worse than old’. The probabilistic models traditionally used to estimate the expected number of failures account for the first two states, but they do not properly apply to the last three, which are more realistic in practice. In this paper, a robust solution to a probabilistic model that is applicable to all of the five after repair states, called generalized renewal process (GRP), is presented. This research demonstrates that the GRP offers a general approach to modeling repairable systems and discusses application of the classical maximum likelihood and Bayesian approaches to estimation of the GRP parameters. This paper also presents a review of the traditional approaches to the analysis of repairable systems as well as some applications of the GRP and shows that they are subsets of the GRP approach. It is shown that the proposed GRP solution accurately describes the failure data, even when a small amount of failure data is available.Recent emphasis in the use of performance-based analysis in operation and regulation of complex engineering systems (such as those in space and process industries) require use of sound models for predicting failures based on the past performance of the systems. The GRP solution in this paper is a promising and efficient approach for such performance-based applications.     

Analysis of the gas compressibility effects on the constant-entropy reversible processes of refrigerants and refrigerant mixtures

Thermally and calorically real gas modelling based on the Martin–Hou equation of state is assumed for pure and mixed refrigerants in the superheated vapour phase. It allows the constant-entropy reversible processes which take place within the work transfer components of ideal vapour compression cycles to be properly analysed. These processes, in fact, occur in a region of the Mollier diagram close to the saturated vapour curve where covolume and molecular forces alter the equation of state of an ideal gas. Thus, real gas effects are significant and cannot be ignored. They give a more accurate indication of the refrigerant end temperature associated with an isentropic compression as well as of the corresponding work exchanged and volumetric efficiency. In particular, it is shown that the gas compressibility effects play a ‘favourable’ role during the isentropic compression processes since they allow the work transferred to be reduced up to 10% for HFC-refrigerant 134a, and HFC-refrigerant mixtures 407C and 410A. But, at the same time, they play an ‘unfavourable’ role since they can reduce the compressor volumetric efficiency (i.e. refrigerant mass flow rate) and, consequently, the cooling (or heating) capacity of the vapour compression system up to 7%.     

Major system change through stepwise reconfiguration: A multi-level analysis of the transformation of American factory production (1850–1930)

The common view is that major transitions come about through breakthroughs of technological discontinuities. This article proposes gradual and stepwise reconfiguration as an alternative transition pathway. In it, new elements are adopted in the existing socio-technical regime to help solve particular problems. But as more is learned and circumstances change, these elements may trigger further changes in technology, user practice, infrastructure, and policies, eventually altering the basic architecture of the regime. These notions are integrated in a multi-level perspective on transitions and system changes. The resulting reconfiguration perspective is illustrated with a historical case study of the transition from traditional factories to mass production in America (1850–1930). The analysis shows that mass production was the last step in a much longer reconfiguration process involving cumulative changes in machine tools, building materials, materials handling technologies, power generation, and power-distribution technologies. The reconfiguration perspective has wider relevance for other systems that function through the interplay of multiple technologies, e.g., agriculture, retailing, and hospitals.     

Assessment of reversible multi-state k-out-of-n:G/F/Load-Sharing systems with flow-graph models

This paper presents a flow-graph-based approach to analyze a Multi-State k-out-of-n:G/F/Load-Sharing systems. The Multi-State k-out-of-n:G/F/Load-Sharing systems comprises ‘n’ identical units, which are under state monitoring and recovery function. The units have ‘r’ states that their state transit models (i.e. Semi-Markov) are presented with flow-graph model. This newly developed analytical approach provides Multi-state Time-To-State information, such as the probability, and mean and standard deviation time for the unit/system being in certain state. A solved example is presented to demonstrate the application of the approach for Multi-State k-out-of-n:G/F/Load-Sharing systems.     

Multiplicative cases from additive cases: Extension of Kolmogorov–Feller equation to parametric Poisson white noise processes

In this paper the response of nonlinear systems driven by parametric Poissonian white noise is examined.As is well known, the response sample function or the response statistics of a system driven by external white noise processes is completely defined. Starting from the system driven by external white noise processes, when an invertible nonlinear transformation is applied, the transformed system in the new state variable is driven by a parametric type excitation. So this latter artificial system may be used as a tool to find out the proper solution to solve systems driven by parametric white noises. In fact, solving this new system, being the nonlinear transformation invertible, we must pass from the solution of the artificial system (driven by parametric noise) to that of the original one (driven by external noise, that is known). Moreover, introducing this invertible nonlinear transformation into the Itô’s rule for the original system driven by external input, one can derive the Itô’s rule for systems driven by a parametric type excitation, directly. In this latter case one can see how natural is the presence of the Wong–Zakai correction term or the presence of the hierarchy of correction terms in the case of normal and Poissonian white noise, respectively. Direct transformation on the Fokker–Planck and on the Kolmogorov–Feller equation for the case of parametric input are found.     

Thermodynamic performance limit considerations for dual-evaporator, non-azeotropic refrigerant mixture-based domestic refrigerator-freezer systems

Non-azeotropic refrigerant mixtures (NARMs) are investigated for a two-temperature level heat exchange process found in a domestic refrigerator-freezer. Ideal (constant air temperature) heat exchange processes are assumed. The results allow the effects of intercooling between the evaporator refrigerant stream and the condenser outlet stream to be examined in a systematic manner. For the conditions studied, an idealized NARM system will have a limiting coefficient of performance (COP) that is less than that of the best performing pure refrigerant component. However, for non-ideal heat exchange processes (gliding air temperature), the NARM-based system can have a higher limiting COP than a system running on either pure NARM component. Intercooling significantly affects the COP of NARM-based systems; however, depending on the location of ‘pinch points’ in the heat exchangers, only one intercooling heat exchanger may be needed to obtain a NARM's maximum refrigerator COP. The results are presented for mixtures of R22–R142b, R22–R123 and R32–R142b.     

Considerations on the elements of quantifying human reliability

This paper attempts to provide a contribution for the discussion of what the term ‘data’ means and how the qualitative perspective can be linked with the quantitative one. It will argue that the terms ‘quantitative data’ and ‘qualitative data’ are not distinct but a continuum that spans over the entire spectrum of the expertise that has to be involved in the HRA process. It elaborates the rational behind any human reliability quantification figure and suggests a scientific way forward to better data for human reliability assessment.     

A response-modeling approach to characterization and propagation of uncertainty specified over intervals

Computational simulation methods have advanced to a point where simulation can contribute substantially in many areas of systems analysis. One research challenge that has accompanied this transition involves the characterization of uncertainty in both computer model inputs and the resulting system response. This article addresses a subset of the ‘challenge problems’ posed in [Challenge problems: uncertainty in system response given uncertain parameters, 2001] where uncertainty or information is specified over intervals of the input parameters and inferences based on the response are required. The emphasis of the article is to describe and illustrate a method for performing tasks associated with this type of modeling ‘economically’-requiring relatively few evaluations of the system to get a precise estimate of the response. This ‘response-modeling approach’ is used to approximate a probability distribution for the system response. The distribution is then used: (1) to make inferences concerning probabilities associated with response intervals and (2) to guide in determining further, informative, system evaluations to perform.