Characterization of the thermal structure of different building constructions using in-situ measurements and Bayesian analysis

A dynamic method, comprising a two lumped-thermal-mass model and Markov Chain Monte Carlo sampler, was used to analyze in-situ-monitored data and estimate the thermophysical properties of two walls of different construction. This method, unlike maximum a posteriori approaches, estimates the parameters’ probability distributions, providing insight into the wall’s thermal structure. Total R-values were well defined for both walls, whilst constituent estimated R-values for a solid wall having layers of materials with similar thermal properties were anticorrelated (thermal mass locations weakly constrained), but were not correlated for an insulated cavity wall with thermally distinct layers (thermal mass locations strongly thermally constrained)

Estimation of thermophysical properties from in-situ measurements in all seasons: quantifying and reducing errors using dynamic grey-box methods

Robust characterisation of the thermal performance of buildings from in-situ measurements requires error analysis to evaluate the certainty of estimates. A method for the quantification of systematic errors on the thermophysical properties of buildings obtained using dynamic grey-box methods is presented, and compared to error estimates from the average method. Different error propagation methods (accounting for equipment uncertainties) were introduced to reflect the different mathematical description of heat transfer in the static and dynamic approaches. Thermophysical properties and their associated errors were investigated using two case studies monitored long term. The analysis showed that the dynamic method (and in particular a three thermal resistance and two thermal mass model) reduced the systematic error compared to the static method, even for periods of low internal-to-external average temperature difference. It was also shown that the use of a uniform error as suggested in the ISO 9869-1:2014 Standard would generally be misrepresentative. The study highlighted that dynamic methods for the analysis of in-situ measurements may provide robust characterisation of the thermophysical behaviour of buildings and extend their application beyond the winter season in temperate climates (e.g., for quality assurance and informed decision making purposes) in support of closing the performance gap

Development of a new screening tool for cyber pornography. Psychometric properties of the Cyber Pornography Addiction Test (CYPAT)

Objective: Internet pornography addiction typically involves viewing, downloading and trading online pornography or engagement in adult fantasy role-play. There are some well-validated inventories measuring perceived addiction to internet pornography but these instruments are often too long for a functionally use and fast scoring. The aim of this study was to evaluate the psychometric properties of the cyber pornography addiction test (CYPAT), a new, brief, screening measure for assessing cyber pornography.Method: Participants of this study completed the CYPAT, the CPUI, the TAS-20 and the FACES-IV. Descriptive statistics were calculated and Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were applied.Results: Cronbach's alpha coefficient suggested excellent reliability of the measure. Results of this study revealed also good construct, convergent and divergent validity.Conclusions: CYPAT is a brief self-report screening scale composed of 11 items scored on a five-point Likert scale with good psychometrics properties. The implications of these findings for future theoretical and empirical research in this field are discusse

Characterising the effects of wind-driven rain on the thermophysical performance of cavity walls by means of a Bayesian framework

Cavity wall is one of the most common construction types in temperate maritime climates, including the UK. However, water penetration may lead to damp within the structure, freeze-thaw damage at the outer surface and a reduction in thermal resistance. The magnitude of wetting effects on the energy performance of cavity walls is still unclear, with potentially significant implications for climate-change-mitigation strategies. This paper investigates the thermophysical performance of uninsulated and insulated cavity walls and its degradation as the element is wettened. Experiments were performed in a hygrothermal laboratory where two cavity-wall specimens (one of which coated with external waterproofing treatment) were tested under a high wind-driven rain exposure. Changes in the thermophysical performance between dry and wet conditions were evaluated through U-value testing and Bayesian inference. Substantial U-value increase was observed for wet uninsulated specimens (compared to dry conditions); conversely, closer U-value ranges were obtained when insulated with EPS grey beads. Moreover, latent-heat effects through the external masonry leaf of the untreated specimen were predicted by the Bayesian framework. Results suggest a negligible efficacy of waterproofing surface treatments as strategies for the reduction of heat transfer within the element, and possible effects of these agents on the evaporative and drying process

Energy Density Functionals From the Strong-Coupling Limit Applied to the Anions of the He Isoelectronic Series

Anions and radicals are important for many applications including environmental chemistry, semiconductors, and charge transfer, but are poorly described by the available approximate energy density functionals. Here we test an approximate exchange-correlation functional based on the exact strong-coupling limit of the Hohenberg-Kohn functional on the prototypical case of the He isoelectronic series with varying nuclear charge $Z<2$, which includes weakly bound negative ions and a quantum phase transition at a critical value of $Z$, representing a big challenge for density functional theory. We use accurate wavefunction calculations to validate our results, comparing energies and Kohn-Sham potentials, thus also providing useful reference data close to and at the quantum phase transition. We show that our functional is able to bind H$^-$ and to capture in general the physics of loosely bound anions, with a tendency to strongly overbind that can be proven mathematically. We also include corrections based on the uniform electron gas which improve the results.Comment: Accepted for the JCP Special Topic Issue "Advances in DFT Methodology

Distributed control in virtualized networks

The increasing number of the Internet connected devices requires novel solutions to control the next generation network resources. The cooperation between the Software Defined Network (SDN) and the Network Function Virtualization (NFV) seems to be a promising technology paradigm. The bottleneck of current SDN/NFV implementations is the use of a centralized controller. In this paper, different scenarios to identify the pro and cons of a distributed control-plane were investigated. We implemented a prototypal framework to benchmark different centralized and distributed approaches. The test results have been critically analyzed and related considerations and recommendations have been reported. The outcome of our research influenced the control plane design of the following European R&amp;D projects: PLATINO, FI-WARE and T-NOVA

A Bayesian dynamic method to estimate the thermophysical properties of building elements in all seasons, orientations and with reduced error

The performance gap between the expected and actual energy performance of buildings and elements has stimulated interest in in-situ measurements. Most research has employed quasi-static analysis methods that estimate heat loss metrics such as U-values, without taking advantage of the rich time series data that is often recorded. This paper presents a dynamic Bayesian-based method to estimate the thermophysical properties of building elements from in-situ measurements. The analysis includes Markov chain Monte Carlo (MCMC) estimation, priors, uncertainty analysis, and model comparison to select the most appropriate model. Data from two case study dwellings is used to illustrate model performance; U-value estimates from the dynamic and static methods are within error estimates, with the dynamic model generally requiring much shorter time series than the static model. The dynamic model produced robust results at all times of year, including when the average indoor-to-outdoor temperature difference was low, when external temperatures had large daily variation, and measurements were subjected to direct solar radiation. Further, the probability distributions of parameters may provide insights into the thermal performance of elements. Dynamic methods such as that presented herein may enable wider characterisation of the performance of building elements as built, supporting work to reduce the performance gap