The proeutectoid cementite transformation in steels

A comprehensive, critical, and up to date review is presented for the proeutectoid cementite transformation in steels. It is believed that many of the new findings, features, and concepts presented here for this classic phase transformation in steels serve as a model which may be more broadly applicable to test against many other phase transformations systems as well. There were a number of early investigations of cementite morphology, and this review considers those early results in light of many newer studies that provide critical new insight into cementite morphologies in both two and three dimensions. A number of different orientation relationships (ORs) between proeutectoid cementite and the austenite matrix from which it forms have been reported in the literature, in some cases leading to confusion, and they are critically evaluated here, as are the habit plane, growth direction, and interfacial structure of various morphologies of proeutectoid cementite. Quantitative experimental and theoretical investigations of the growth kinetics of the proeutectoid cementite transformation are considered next, and the nucleation site of proeutectoid cementite in austenite is also discussed in some detail. This review considers all of these issues in a critical way in which differences, commonalities, important features, and redundancies are sorted out, in order to present a unified picture that will add some clarity to this subject. The different features and issues of this transformation that are considered in detail throughout this review are finally brought together in a comprehensive way in the last major section of this paper on ‘Formation mechanism(s) of proeutectoid cementite’, in order to provide a complete, modern view of the formation of proeutectoid cementite from austenite. To the best knowledge of the present authors, before this review a thorough assessment of this classic phase transformation in steels had not been undertaken since 1962, when Professor Hubert I. Aaronson covered this topic in a section of the book entitled ‘The Decomposition of Austenite by Diffusional Processes’. In large part due to a number of ground breaking new findings on the proeutectoid cementite transformation since then (particularly in the last decade), it is very timely for a new review on this topic

Efficient Sensor Deployments for Spatio-Temporal Environmental Monitoring

IEEE This paper addresses the problem of efficiently deploying sensors in spatial environments, e.g., buildings, for the purposes of monitoring spatio-temporal environmental phenomena. By modeling the environmental fields using spatio-temporal Gaussian processes, a new and efficient optimality-cost function of minimizing prediction uncertainties is proposed to find the best sensor locations. Though the environmental processes spatially and temporally vary, the proposed approach of choosing sensor positions is proven not to be affected by time variations, which significantly reduces computational complexity of the optimization problem. The sensor deployment optimization problem is then solved by a practical and feasible polynomial algorithm, where its solutions are theoretically proven to be guaranteed. The proposed method is also theoretically and experimentally compared with the existing works. The effectiveness of the proposed algorithm is demonstrated by implementation in a real tested space in a university building, where the obtained results are highly promising

Spatio-temporal environmental monitoring for smart buildings

© 2017 IEEE. The paper addresses the problem of efficiently monitoring environmental fields in a smart building by the use of a network of wireless noisy sensors that take discretely-predefined measurements at their locations through time. It is proposed that the indoor environmental fields are statistically modeled by spatio-temporal non-parametric Gaussian processes. The proposed models are able to effectively predict and estimate the indoor climate parameters at any time and at any locations of interest, which can be utilized to create timely maps of indoor environments. More importantly, the monitoring results are practically crucial for building management systems to efficiently control energy consumption and maximally improve human comfort in the building. The proposed approach was implemented in a real tested space in a university building, where the obtained results are highly promising

Efficient spatio-temporal sensor deployments: A smart building application

© 2017 IEEE. The paper addresses the problem of efficiently deploying sensors in spatial environments, e.g. smart buildings, for the purpose of monitoring environmental phenomena. By modelling the environmental fields using spatio-temporal Gaussian processes, a new and efficient optimality criterion of minimizing prediction uncertainties is proposed to find the best sensor locations. Though the environmental processes spatially and temporally vary, the proposed approach of choosing sensor positions is not affected by time variations, which significantly reduces computational complexity of the optimization problem. The sensor deployment problem is then solved by a practically and feasibly polynomial algorithm, where its solutions are guaranteed. The proposed approaches were implemented in a real tested space in a university building, where the obtained results are highly promising

Synthesis of accelerograms compatible with the Chinese GB 50011-2001 design spectrum via harmonic wavelets: artificial and historic records

A versatile approach is employed to generate artificial accelerograms which satisfy the compatibility criteria prescribed by the Chinese aseismic code provisions GB 50011-2001. In particular, a frequency dependent peak factor derived by means of appropriate Monte Carlo analyses is introduced to relate the GB 50011-2001 design spectrum to a parametrically defined evolutionary power spectrum (EPS). Special attention is given to the definition of the frequency content of the EPS in order to accommodate the mathematical form of the aforementioned design spectrum. Further, a one-to-one relationship is established between the parameter controlling the time-varying intensity of the EPS and the effective strong ground motion duration. Subsequently, an efficient auto-regressive moving-average (ARMA) filtering technique is utilized to generate ensembles of non-stationary artificial accelerograms whose average response spectrum is in a close agreement with the considered design spectrum. Furthermore, a harmonic wavelet based iterative scheme is adopted to modify these artificial signals so that a close matching of the signals’ response spectra with the GB 50011-2001 design spectrum is achieved on an individual basis. This is also done for field recorded accelerograms pertaining to the May, 2008 Wenchuan seismic event. In the process, zero-phase high-pass filtering is performed to accomplish proper baseline correction of the acquired spectrum compatible artificial and field accelerograms. Numerical results are given in a tabulated format to expedite their use in practice

Spontaneously Healed Pathologic Fracture over a Critical-Size Calcaneal Cyst

Simple bone cysts are nonsymptomatic lesions. They typically involve the medullary cavity, but they can also be found in nonlong bones such as the calcaneum. Their treatment remains controversial varying from observation and conservative healing to irritating injections or bone grafting. In the case of a pathologic fracture, surgical treatment seems most appropriate especially when the cyst is situated on a weight-bearing bone. We present herein the rare case of a spontaneously healed pathological fracture over a critical-size calcaneal cyst of a patient reluctant to undergo surgical treatment. An interpretation of the healing procedure as well as a review of the literature is presented

Electrochemical evaluation of the de-/re-activation of oxygen evolving Ir oxide

Understanding the influence of dynamic and stationary polarization on the deactivation of state-of-the-art IrOx catalysts is imperative for the design and operation of robust and efficient proton exchange membrane water electrolyzers. In this work, the deactivation and activity regeneration of a commercial IrOx catalyst investigated under potentiodynamic and potentiostatic conditions in acidic media by means of rotating disk electrode and electrogravimetry. Systematic electrochemical protocols were designed to decouple reversible from irreversible activity losses. Cyclic voltammetry provided a metric of the active surface area and traced the charge growth under different oxygen evolution reaction conditions. A direct logt dependent charge growth is observed, accompanied by the same fractional kinetic activity decay under potentiodynamic conditions. The loss is essentially recoverable after electrochemical reductive treatment, however at the expense of mild material dissolution. In contrast, extended potentiostatic operation induced irreversible intrinsic degradation after a critical time (0.5-1 h), accompanied by stability enhancement. This irreversible deactivation attributed to a gradual transformation of the hydrated IrOx to a dehydrated condensed oxide. Our results suggest that Ir dissolution during the regenerative treatment is not prohibitive, as long as the low potential modulations are not frequent

System Identification of a Nonlinear Mode for the Shuttle Radar Topography Mission

A study is presented to identify a nonlinear bending mode for a 60-m space structure. This study was done in support of the Shuttle Radar Topography Mission (SRTM) and postflight height reconstruction efforts. For this purpose, one linear model and three nonlinear models of the structural mode were considered and evaluated. The best model was determined based on in-flight data collected during the mission and was implemented as part of the final ground software that was used for reconstructing relative radar antenna motion for the SRTM interferometer payload. High accuracy estimates of the relative states were essential for supporting the motion compensation algorithm used in the radar interferometry processor for calculating the desired topographic maps. The improvement resulting fromidentifying nonlinear modal behavior contributed to meeting mission performance requirements

Sparse Deterministic Approximation of Bayesian Inverse Problems

We present a parametric deterministic formulation of Bayesian inverse problems with input parameter from infinite dimensional, separable Banach spaces. In this formulation, the forward problems are parametric, deterministic elliptic partial differential equations, and the inverse problem is to determine the unknown, parametric deterministic coefficients from noisy observations comprising linear functionals of the solution. We prove a generalized polynomial chaos representation of the posterior density with respect to the prior measure, given noisy observational data. We analyze the sparsity of the posterior density in terms of the summability of the input data's coefficient sequence. To this end, we estimate the fluctuations in the prior. We exhibit sufficient conditions on the prior model in order for approximations of the posterior density to converge at a given algebraic rate, in terms of the number $N$ of unknowns appearing in the parameteric representation of the prior measure. Similar sparsity and approximation results are also exhibited for the solution and covariance of the elliptic partial differential equation under the posterior. These results then form the basis for efficient uncertainty quantification, in the presence of data with noise