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The goal of this study is to investigate the thermal conductivity, viscosity and thermal performance in a single-phase natural circulation mini loop of Ag-water nanofluid which can be a potential working fluid for natural convective flat-plate solar collectors. The silver-water nanofluid with 5 wt% concentration, which contains also polyvinylpyrrolidone (PVP) with 1.25 wt%, was purchased. Then, the sample was diluted with de-ionized water to four different concentrations of 0.25, 0.5, 0.75 and 1 wt%. Thermal conductivity and viscosity were measured by 3ω method and Brookfield rheometer, respectively. An effectiveness factor was used to define the thermal performance of Ag-water nanofluids for different inclination angles and heating powers. The results showed that nanofluid samples are thermally less conductive than the literature, at ambient temperature (23 °C). The viscosity of nanofluid decreases significantly with increasing temperature and increases with increasing concentration. Our measurements appear to be more compatible with PVP solution results available in the literature. Effectiveness is enhanced up to 11% with 1 wt% concentrated nanofluid compared to de-ionized water and the effectiveness of the mini loop indicates an enhancement with increase in inclination angle and particle concentration at whole applied power. According to obtained results, it is concluded that Ag-water nanofluid has a promising potential to be used in natural convective flat-plate solar collector. [ABSTRACT FROM AUTHOR]

Lithium-ion batteries are sensitive to temperature changes over their life. High operational temperatures can negatively affect the battery and lead to capacity fade and lifespan reduction. Air-cooled thermal management systems are widely used in electrified vehicles. A novel air-cooled battery design is introduced. Aluminum fin cooling features are directly integrated onto prismatic cells rather than established by the use of an auxiliary polymer component. When the cells are arranged in a battery array, the on-cell features generate cooling channels. A forced-convection testbed is used to determine thermal management performance. Shear resistance experiments are used to measure the mechanical resistance of the battery cell assemblies. The study demonstrates that a configuration with parallel channel cell-wall integrated fins recovers the performance of the system with the standard polymer space but provides a 20% improvement in temperature uniformity under fan power control. This configuration, however, lacks mechanical resistance in the assembly. A poka-yoke based configuration with tapered channels enhanced by secondary fins provides mechanical resistances and also performs better in both flow and fan power control. This configuration maintains the cell maximum temperature as the assembly via polymer spacers but improves the temperature uniformity by 50%. • Advantageous cooling performance of battery cells with cell-body integrated features is demonstrated. • Optimization of cooling performance achieved through tapered channels and secondary fin features. • Interlocking of battery assembly by using segmented cooling features leading. • Advantageous assembly process and mechanical shear resistance due to segmented features. [ABSTRACT FROM AUTHOR]

• Shows how student and peer evaluation of teaching relate to performance appraisal principles. • Exposes risks of bias in qualitative approaches to teaching evaluation. • Clarifies how robust behavioral ratings instruments can be used for evaluating teaching. • Identifies job analysis as a fundamental step in evaluating teaching. • Clarifies how to collect targeted teaching evaluation data from multiple stakeholders. As research on student evaluations of teaching (SET) has dominated our understanding of teaching evaluation, debate over SET implementation has turned attention away from basic principles for appraising employee performance as established in human resources literature. Considering SET research and its practical significance in isolation from relevant human resources literature not only risks unlawful remedies for issues such as bias in SET but also risks replacing one form of bias with another. Meanwhile, the full potential of human resources tools to support consistent evaluation of teaching remains unrealized. To address this gap, this article clarifies how teaching evaluation can be conducted as sound performance appraisal by deploying SET and peer review of teaching within a larger framework of established human resources techniques. A review of recent literature articulates prominent themes in research on SET and peer review of teaching and outlines key principles for performance appraisal and performance management. Those principles are used to analyze representative faculty evaluation policies and procedures and clarify the weaknesses of both traditional and recently revised approaches to teaching evaluation. The final section elaborates performance appraisal techniques relevant to teaching evaluation. These include planful use of results and/or behavior approaches to performance appraisal, robust rating instruments for behavioral performance appraisal, targeted collection of information from multiple stakeholders, and job analysis. Efforts to de-emphasize quantitative SET data to address issues such as bias can be strengthened through the incorporation of performance appraisal tools that clearly articulate performance criteria and standards and that gather both qualitative and quantitative data on employee performance. [ABSTRACT FROM AUTHOR]

Abstract: This paper uses mixture priors for Bayesian assessment of performance. In any Bayesian performance assessment, a prior distribution for performance parameter(s) is updated based on current performance information. The performance assessment is then based on the posterior distribution for the parameter(s). This paper uses a mixture prior, a mixture of conjugate distributions, which is itself conjugate and which is useful when performance may have changed recently. The present paper illustrates the process using simple models for reliability, involving parameters such as failure rates and demand failure probabilities. When few failures are observed the resulting posterior distributions tend to resemble the priors. However, when more failures are observed, the posteriors tend to change character in a rapid nonlinear way. This behavior is arguably appropriate for many applications. Choosing realistic parameters for the mixture prior is not simple, but even the crude methods given here lead to estimators that show qualitatively good behavior in examples. [Copyright &y& Elsevier]

Abstract: This paper addresses the problem of assessing the current performance of a system, given that performance can change over time. In many problems of interest, although a significant body of historical evidence is available, current performance information is too sparse to be the sole basis for an assessment of how well the system is currently performing. Therefore, it is desirable to apply current data within a Bayesian framework, making use of a broader body of evidence. However, both noninformative priors and simple informative priors have drawbacks for this application. The present work shows that ‘mixture’ priors have relatively desirable properties for performance assessment. These properties are illustrated using a simple example in assessment of reliability performance. It is also shown that one implementation of the mixture prior (the ‘fixed-constituent model’) is formally equivalent to methods used in signal detection, statistical decision rules in medical diagnosis, and many other applications. Building on the medical analogy, the potential benefits of an integrated treatment of reliability data and inspection results are illustrated. A companion paper develops a more sophisticated implementation of the mixture prior (the ‘variable-constituent model’), and extends the treatment to more complex examples. [Copyright &y& Elsevier]