Estimation of building component UA and gA from outdoor tests in warm and moderate weather conditions

Accurate knowledge of the thermal properties of building components is necessary to implement adequate energy saving strategies in buildings. Outdoor experiments using test cells are very useful tools for realistic estimation of these properties. This paper describes the analyses performed, and the procedure followed in identifying and solving some problems found when building components are tested for UA and gA in a test cell under warm and moderate weather conditions. A window component was tested in a PASLINK test cell at the CIEMAT’s ‘Plataforma Solar de Almería (PSA-CIEMAT)’ in Tabernas (Almería, Spain) and several data sets recorded under quite different weather and test conditions were analysed. First the problems identified when applying the usual test and linear analysis procedures are described. Then hypotheses about the cause of these problems are formulated. Afterwards, strategies followed for testing these hypotheses are described. Once the cause of the problems had been identified, they were fine tuned to find a model for accurate UA and gA estimation. This study demonstrated that nonlinear models, in which long wave radiation is considered as nonlinear effect, yield remarkably better performance than the commonly used linear models, for estimating the component UA and gA values.     

Formation of niobium oxide nanowires by thermal oxidation

In this report, we describe simple thermal oxidation of niobium for the fabrication of niobium oxides, emphasizing that niobium oxide nanowires can be prepared upon the concentration of oxygen in the environment. For example, dense Nb₂O₅ nanowires on thin oxide film are produced if the annealing is performed in a restricted concentration of oxygen (herein, 3 Torr vacuum). If most of the oxygen is removed in the environment, the nanowires are sparely formed. The nanowires consist of a superlattice monoclinic Nb₂O₅ with a growth direction of [0 0 1].     

Modulo Path History for the Reduction of Pipeline Overheads in Path-based Neural Branch Predictors

Neural-inspired branch predictors achieve very low branch misprediction rates. However, previously proposed implementations have a variety of characteristics that make them challenging to implement in future high-performance processors. In particular, the path-based neural predictor (PBNP) and the piecewise-linear (PWL) predictor require deep pipelining and additional area to support checkpointing for misprediction recovery. The complexity of the PBNP predictor stems from the fact that the path history length, which determines the number of tables and pipeline stages, is equal to the history length, which is typically very long for high accuracy. We propose to decouple the path-history length from the outcome-history length through a new technique called modulo-path history. By allowing a shorter path history, we can implement the PBNP and PWL predictors with significantly fewer tables and pipeline stages while still exploiting a traditional long branch outcome history.     

Workshop Report: Modeling the Molecular Mechanism of Bacterial Spore Germination and Elucidating Reasons for Germination Heterogeneity

ABSTRACT:  Over the course of 2 days, top researchers in the fields of bacterial spore biology and computational biology discussed approaches to determine the cause of spore germination heterogeneity. Biological and mathematical data gaps were identified, and experimental approaches and computational strategies for modeling spore germination were presented and evaluated. As a result of these interactions, future research directions were defined, the outcome of which should result in a robust model to help define the molecular mechanism(s) of spore germination. Mechanistic understanding of germination will be instrumental for developing novel sterilization, treatment, and decontamination strategies to mitigate threats posed by spores.     

Thermal fatigue estimation due to thermal stratification in the RCS branch line using one-way FSI scheme

The scheme and procedure for thermal fatigue estimation of a thermally stratified branch line were developed. One-way FSI (fluid and structure interaction) scheme was applied to evaluate the thermal stratification piping. Thermal flow analysis, stress analysis and fatigue estimation were performed in serial order. Finally, detailed monitoring locations and mitigation scheme for the integrity maintenance of piping were recommended. All wall mesh and transient temperature distribution data obtained from the CFD (computational fluid dynamics) analysis were directly imported into the input data of stress analysis model without any calculation for heat transfer coefficients. Cumulated usage factors for fatigue effect review with nodes were calculated. A modified method that combines ASME Section III, NB-3600 with NB-3200 was used because the previous method cannot consider the thermal stratification stress intensity. As the results of evaluation, the SCS (shutdown cooling system) line, branch piping of the RCS (reactor coolant system) line, shows that the CUF (cumulative usage factor) value exceeds 1.0, ASME Code limit, in case thermal stratification load is included. The HPSI (high pressure safety injection) line, re-branch piping, shows that temperature difference between top and bottom of piping exceeds the criterion temperature, 28°C, and that the CUF value exceeds 1.0. Therefore, these branch pipings require a detailed review, monitoring or analysis. In particular, it is recommended that the HPSI piping should be shifted backward to decrease the influence of turbulent penetration intensity from the RCS piping. This paper was recommended for publication in revised form by Associate Editor Jae Young Lee Kwang-Chu Kim received his B.S., M.S. and Ph.D degrees from department of mechanical engineering, Kyunghee University in 1993, 1995 and 2000, respectively. He has worked for Korea Power Engineering Company since 1995 and he is now a senior researcher. Dr. Kim’s research area includes CFD analysis, flow control, plant design and simulator. Jong-Han Lim received his B.S. degree from department of mechanical engineering, Chosun University in 1981, M.S. and Ph.D degrees from department of mechanical engineering, Kyunghee University in 1986 and 1992, respectively. He worked for Hyundai Motors Company during 1986-95. He is now a professor in department of mechanical & automotive engineering, Kyungwon University. Dr. Lim’s research interests are in the area of thermal flow, internal combustion and liquid atomization. Jun-Kyu Yoon received his B.S. degree from department of mechanical engineering, Chosun University in 1981, M.S. degree from department of mechanical engineering, Kyunghee University in 1987 and Ph.D degree from department of mechanical engineering, Myongji University in 2001. He worked for Hyundai Motors Company and Asia Motors Company during 1985–96. He is now a professor in department of mechanical & automotive engineering, Kyungwon University. Dr. Yoon’s research interests are in the area of flow control, heat transfer, liquid atomization, spray and combustion.     

Application of a Recurrent Neural Network to Prediction of Drug Dissolution Profiles

The Elman Recurrent Neural Network was employed for the prediction of in-vitro dissolution profiles of matrix controlled release theophylline pellet preparation, leading to the potential use of an intelligent learning system in the development of pharmaceutical products with desired drug release characteristics. A total of six different formulations containing various matrix ratios of substance to control the release rate of theophylline were used for experimentation. By using the leave-one-out cross-validation approach, the dissolution profiles of all the matrix ratios were consumed for training, except for one set that was taken as a reference profile, with which the network predicted profiles were compared. Performance of the network was assessed using the similarity factor, f ₂ , a criterion for dissolution profile comparison recommended by the United States Food and Drug Administration. Simulation results indicated that the Elman network was capable of predicting dissolution profiles that were similar to the reference profiles with an error of less than 8%. In addition, the Bootstrap method was used to estimate the confidence intervals of the f ₂ values. The results revealed the potential of a neural-network-based intelligent system in solving non-linear time-series prediction problems in pharmaceutical product development.     

The "rainbow" model: an attempt at a global approach to the drug problem

A global, tridimensional, and comprehensive model for the drug problem is presented. On a flat matrix with five components (growing, production, processing, traffic/distribution, and consumption) and seven dimensions (individual, family, restricted group, neighborhood, city/region, national, and international), six different perspectives are employed (psychobiological, social/political, economics, legal, historical/cultural, and geographical). Each psychoactive substance may be analyzed separately.     

Novel efficient approach for the design of equiripple quadraturemirror filters

Quadrature mirror filters have been used extensively in subband coding of speech signals. The authors introduce a novel efficient approach for the design of equiripple quadrature mirror filters. The new approach is more efficient than the previously proposed design method in terms of computer time and memory requirement     

Measuring the outcomes of psychotherapy: Findings of the Penn Psychotherapy Project.

Reports analyses of outcome measures obtained from patients, therapists, and clinical observers in the Penn Psychotherapy Project, a 5-yr study of factors that predict outcome in outpatient psychotherapy. The data from the "method factors" study by D. S. Cartwright et al (see record 1963-06833-001) were also reanalyzed. Results in both studies were very similar. Substantial agreement was found among viewpoints about broadly defined treatment outcomes, although distinct viewpoints did clearly exist. Contrary to a common opinion, consensus measures of psychotherapy outcome could be meaningfully defined. Relationships among posttreatment ratings of benefits from therapy and measures of adjustment obtained before and after treatment were explored. A strong relationship was found between the residual gain score and ratings of benefits, suggesting that posttreatment ratings of outcome take account of the fact that the amount of change to be expected depends on the initial level of functioning. (31 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)