A probabilistic energy model for non-domestic building sectors applied to analysis of school buildings in greater London

The diversity of non-domestic buildings at urban scale poses a number of difficulties to develop models for large scale analysis of the stock. This research proposes a probabilistic, engineering-based, bottom-up model to address these issues. In a recent study we classified London's non-domestic buildings based on the service they provide, such as offices, retail premise, and schools, and proposed the creation of one probabilistic representational model per building type. This paper investigates techniques for the development of such models. The representational model is a statistical surrogate of a dynamic energy simulation (ES) model. We first identify the main parameters affecting energy consumption in a particular building sector/type by using sampling-based global sensitivity analysis methods, and then generate statistical surrogate models of the dynamic ES model within the dominant model parameters. Given a sample of actual energy consumption for that sector, we use the surrogate model to infer the distribution of model parameters by inverse analysis. The inferred distributions of input parameters are able to quantify the relative benefits of alternative energy saving measures on an entire building sector with requisite quantification of uncertainties. Secondary school buildings are used for illustrating the application of this probabilistic method. © 2012 Elsevier B.V. All rights reserved.

Modelling and Fragility Analysis of Non-Ductile Reinforced Concrete Buildings in Low-to-Moderate Seismic Zones

Reinforced concrete buildings in low-to-moderate seismic zones are often designed only for gravity loads in accordance with the non-seismic detailing provisions. Deficient detailing of columns and beam-column joints can lead to unpredictable brittle failures even under moderate earthquakes. Therefore, a reliable estimate of structural response is required for the seismic evaluation of these structures. For this purpose, analytical models for both interior and exterior slab-beam-column subassemblages and for a 1/3 scale model frame were implemented into the nonlinear finite element platform OpenSees. Comparison between the analytical results and experimental data available in the literature is carried out using nonlinear pushover analyses and nonlinear time history analysis for the subassemblages and the model frame, respectively. Furthermore, the seismic fragility assessment of reinforced concrete buildings is performed on a set of non-ductile frames using nonlinear time history analyses. The fragility curves, which are developed for various damage states for the maximum interstory drift ratio are characterized in terms of peak ground acceleration and spectral acceleration using a suite of ground motions representative of the seismic hazard in the region.

The vibro-acoustic analysis of built-up systems using a hybrid method with parametric and non-parametric uncertainties

An existing hybrid finite element (FE)/statistical energy analysis (SEA) approach to the analysis of the mid- and high frequency vibrations of a complex built-up system is extended here to a wider class of uncertainty modeling. In the original approach, the constituent parts of the system are considered to be either deterministic, and modeled using FE, or highly random, and modeled using SEA. A non-parametric model of randomness is employed in the SEA components, based on diffuse wave theory and the Gaussian Orthogonal Ensemble (GOE), and this enables the mean and variance of second order quantities such as vibrational energy and response cross-spectra to be predicted. In the present work the assumption that the FE components are deterministic is relaxed by the introduction of a parametric model of uncertainty in these components. The parametric uncertainty may be modeled either probabilistically, or by using a non-probabilistic approach such as interval analysis, and it is shown how these descriptions can be combined with the non-parametric uncertainty in the SEA subsystems to yield an overall assessment of the performance of the system. The method is illustrated by application to an example built-up plate system which has random properties, and benchmark comparisons are made with full Monte Carlo simulations. © 2012 Elsevier Ltd. All rights reserved.

Structural analysis of plate-type fuel assemblies and development of a non-destructive method to assess their integrity

This work is concerned with the structural behaviour and the integrity of parallel plate-type nuclear fuel assemblies. A plate-type assembly consists of several thin plates mounted in a box-like structure and is subjected to a coolant flow that can result in a considerable drag force. A finite element model of an assembly is presented to study the sensitivity of the natural frequencies to the stiffness of the plates' junctions. It is shown that the shift in the natural frequencies of the torsional modes can be used to check the global integrity of the fuel assembly while the local natural frequencies of the inner plates can be used to estimate the maximum drag force they can resist. Finally a non-destructive method is developed to assess the resistance of the inner plates to bear an applied load. Extensive computational and experimental results are presented to prove the applicability of the method presented. © 2013 Elsevier B.V. All rights reserved.

First-principles energetics of water clusters and ice: a many-body analysis.

Standard forms of density-functional theory (DFT) have good predictive power for many materials, but are not yet fully satisfactory for cluster, solid, and liquid forms of water. Recent work has stressed the importance of DFT errors in describing dispersion, but we note that errors in other parts of the energy may also contribute. We obtain information about the nature of DFT errors by using a many-body separation of the total energy into its 1-body, 2-body, and beyond-2-body components to analyze the deficiencies of the popular PBE and BLYP approximations for the energetics of water clusters and ice structures. The errors of these approximations are computed by using accurate benchmark energies from the coupled-cluster technique of molecular quantum chemistry and from quantum Monte Carlo calculations. The systems studied are isomers of the water hexamer cluster, the crystal structures Ih, II, XV, and VIII of ice, and two clusters extracted from ice VIII. For the binding energies of these systems, we use the machine-learning technique of Gaussian Approximation Potentials to correct successively for 1-body and 2-body errors of the DFT approximations. We find that even after correction for these errors, substantial beyond-2-body errors remain. The characteristics of the 2-body and beyond-2-body errors of PBE are completely different from those of BLYP, but the errors of both approximations disfavor the close approach of non-hydrogen-bonded monomers. We note the possible relevance of our findings to the understanding of liquid water.

An Ultra Low Power Non-volatile Memory in Standard CMOS Process for Passive RFID Tags

An ultra low power non-volatile memory is designed in a standard CMOS process for passive RFID tags. The memory can operate in a new low power operating scheme under a wide supply voltage and clock frequency range. In the charge pump circuit the threshold voltage effect of the switch transistor is almost eliminated and the pumping efficiency of the circuit is improved. An ultra low power 192-bit memory with a register array is implemented in a 0.18 mu M standard CMOS process. The measured results indicate that, for the supply voltage of 1.2 volts and the clock frequency of 780KHz, the current consumption of the memory is 1.8 mu A (3.6 mu A) at the read (write) rate of 1.3Mb/s (0.8Kb/s).