Thermal building model identification using time-scaled identification methods

International audienceThe aim of this paper is to propose a robust and accurate method for the parametric identification of the thermal behaviour of low consumption buildings. These buildings are known to have a two-time scale structure, which, if not handled properly, results in poor conditioning of the parametric identification. We compare three identification methods, one uses the data on the whole frequency domain (ARX) when the other methods use the same data but separated on local frequency domain (time scaled methods). All three methods identify a reduced second order model. Robustness is tested by corrupting the input and output before the identification, and comparing the simulation results for the various models and the original uncorrupted input. The numerical results clearly show that the time scaled methods are superior both in accuracy (noise free identification and simulation) and robustness (when identification is performed on corrupted data)

Effective electrothermal analysis of electronic devices and systems with parameterized macromodeling

We propose a parameterized macromodeling methodology to effectively and accurately carry out dynamic electrothermal (ET) simulations of electronic components and systems, while taking into account the influence of key design parameters on the system behavior. In order to improve the accuracy and to reduce the number of computationally expensive thermal simulations needed for the macromodel generation, a decomposition of the frequency-domain data samples of the thermal impedance matrix is proposed. The approach is applied to study the impact of layout variations on the dynamic ET behavior of a state-of-the-art 8-finger AlGaN/GaN high-electron mobility transistor grown on a SiC substrate. The simulation results confirm the high accuracy and computational gain obtained using parameterized macromodels instead of a standard method based on iterative complete numerical analysis

Concrete Static Stress Estimation Using Computer Vision-Based Digital Image Processing

Department of Urban and Environmental Engineering (Urban Infrastructure Engineering)As increasing interests about structural safety due to occasionally occurring collapse of structures and social infrastructures, efforts to identify and monitor the current state of structure are also increasing. Recently, most structures have been built of concrete, so identification of safety level of concrete structures becomes a critical issue. One of such techniques is to evaluate the current stress state in concrete. This technique is essential in various fields involved in an investigation of tensile stress of tendons in pre- and post-tensioned structures, building remodeling which needs to remove bearing walls and adds other foundations, and identification of load distribution in enlarged concrete structures. In other words, current stress level in concrete is an important factor to check the safety level of the structures in service. Although it is obvious that a technique for estimating the static stress level of concrete is essential, the method to identify the stress state of the currently used concrete structure is definitely limited. Several efforts for estimating the current stress state have been developed in previous research, including a stress-strain relationship based on elastic theory and a stress relaxation method (SRM) for concrete. These methods in the previous researches have made a certain contribution in this field but practical use in real structures is still inadequate. Therefore, an objective of this study is to develop a static stress estimation technique which can be applied to real concrete structures. This study proposes a method that can measure the static stress level of concrete by incorporating SRM and computer vision-based image processing. Applying a small damage to concrete specimen can release the current stress state and induce stress field change inside concrete around the damage. Computer vision-based measurement can measure the deformation due to this stress field change. This deformation measurement is used in the static stress estimation algorithm developed in this study. The proposed method is validated using several concrete specimens and consequently demonstrates the performance.clos

Neural network approach for predicting drum pressure and level in coal-fired subcritical power plant

There is increasing need for tighter controls of coal-fired plants due to more stringent regulations and addition of more renewable sources in the electricity grid. Achieving this will require better process knowledge which can be facilitated through the use of plant models. Drum-boilers, a key component of coal-fired subcritical power plants, have complicated characteristics and require highly complex routines for the dynamic characteristics to be accurately modelled. Development of such routines is laborious and due to computational requirements they are often unfit for control purposes. On the other hand, simpler lumped and semi empirical models may not represent the process well. As a result, data-driven approach based on neural networks is chosen in this study. Models derived with this approach incorporate all the complex underlying physics and performs very well so long as it is used within the range of conditions on which it was developed. The model can be used for studying plant dynamics and design of controllers. Dynamic model of the drum-boiler was developed in this study using NARX neural networks. The model predictions showed good agreement with actual outputs of the drum-boiler (drum pressure and water level)

Case studies of outdoor testing and analysis of building components

The construction and development of the PASSYS/PASLINK outdoor test cells were funded by the European Commission, with the objective of providing high-quality test environments for quantifying the performance of passive solar building components. Over the years since the original test cells were commissioned, the initial concept for outdoor testing has been extended to include other test cell types. Significant improvements have been made to the experimental procedures and analysis techniques, and a broad range of components has been tested. This paper describes representative experiments that have been conducted using these highly controlled outdoor test environments, indicates some of the related analysis, and shows the type of information that can be obtained from such tests. It demonstrates the way in which component performance can be ascertained in the realistic external environment. The case studies chosen range from building component tests within EC research projects to commercial tests, and from conventional building components to novel integrated facade systems. They also include a large range of passive and active components. Each case study summarises the test component, the purpose of the test, details of the test configuration (period of test, instrumentation, etc.), results and analysis, and associated modelling and monitoring where appropriate. The paper concludes with an appraisal of the advantages and limitations of the test cells for the various component types

Harbor Security System

Harbors and ports provide the infrastructure for commercial trade and naval facilities. It is vital to ensure the safety of these locations. The Harbor Security System provides an optical ‘gate’ using underwater lasers and photodetectors. This system allows monitoring of both surface and submarine vessels traveling into and out of the harbor. Also, the system provides real time alerts when unauthorized vessels enter the harbor. This project provides a proof of concept for a Harbor Security System to be implemented in Portsmouth Harbor. A scaled model of the detection system was constructed and tested. This detection system is capable of detecting surface and submarine vessels along with their velocity and length. Results of the study showed that the average error of the size estimate was 15% and the average error of the velocity estimation ratio(slope) was 9%

K^+ production in the reaction 58Ni+58Ni^{58}Ni+^{58}Ni at incident energies from 1 to 2 AGeV

Semi-inclusive triple differential multiplicity distributions of positively charged kaons have been measured over a wide range in rapidity and transverse mass for central collisions of $^{58}$Ni with $^{58}$Ni nuclei. The transverse mass ($m_t$) spectra have been studied as a function of rapidity at a beam energy 1.93 AGeV. The $m_t$ distributions of K^+ mesons are well described by a single Boltzmann-type function. The spectral slopes are similar to that of the protons indicating that rescattering plays a significant role in the propagation of the kaon. Multiplicity densities have been obtained as a function of rapidity by extrapolating the Boltzmann-type fits to the measured distributions over the remaining phase space. The total K^+ meson yield has been determined at beam energies of 1.06, 1.45, and 1.93 AGeV, and is presented in comparison to existing data. The low total yield indicates that the K^+ meson can not be explained within a hadro-chemical equilibrium scenario, therefore indicating that the yield does remain sensitive to effects related to its production processes such as the equation of state of nuclear matter and/or modifications to the K^+ dispersion relation.Comment: 24 pages Latex (elsart) 7 PS figures to be submitted to Nucl. Phys