Automatic extraction of Reduced order models from CFD simulations for building energy modeling

Thermal comfort is defined as “that condition of mind which expresses satisfaction with the thermal environment’ [1] [2]. Field studies have been completed in order to establish the governing conditions for thermal comfort [3]. These studies showed that the internal climate of a room was the strongest factor in establishing thermal comfort. Direct manipulation of the internal climate is necessary to retain an acceptable level of thermal comfort. In order for Building Energy Management Systems (BEMS) strategies to be efficiently utilised it is necessary to have the ability to predict the effect that activating a heating/cooling source (radiators, windows and doors) will have on the room. The numerical modelling of the domain can be challenging due to necessity to capture temperature stratification and/or different heat sources (radiators, computers and human beings). Computational Fluid Dynamic (CFD) models are usually utilised for this function because they provide the level of details required. Although they provide the necessary level of accuracy these models tend to be highly computationally expensive especially when transient behaviour needs to be analysed. Consequently they cannot be integrated in BEMS. This paper presents and describes validation of a CFD-ROM method for real-time simulations of building thermal performance. The CFD-ROM method involves the automatic extraction and solution of reduced order models (ROMs) from validated CFD simulations. The test case used in this work is a room of the Environmental Research Institute (ERI) Building at the University College Cork (UCC). ROMs have shown that they are sufficiently accurate with a total error of less than 1% and successfully retain a satisfactory representation of the phenomena modelled. The number of zones in a ROM defines the size and complexity of that ROM. It has been observed that ROMs with a higher number of zones produce more accurate results. As each ROM has a time to solution of less than 20 seconds they can be integrated into the BEMS of a building which opens the potential to real time physics based building energy modelling.

Automatic extraction of reduced-order models from CFD simulations for building energy modelling

Accurate modelling of the internal climate of buildings is essential if Building Energy Management Systems (BEMS) are to efficiently maintain adequate thermal comfort. Computational fluid dynamics (CFD) models are usually utilised to predict internal climate. Nevertheless CFD models, although providing the necessary level of accuracy, are highly computationally expensive, and cannot practically be integrated in BEMS. This paper presents and describes validation of a CFD-ROM method for real-time simulations of building thermal performance. The CFD-ROM method involves the automatic extraction and solution of reduced order models (ROMs) from validated CFD simulations. ROMs are shown to be adequately accurate with a total error below 5% and to retain satisfactory representation of the phenomena modelled. Each ROM has a time to solution under 20seconds, which opens the potential of their integration with BEMS, giving real-time physics-based building energy modelling. A parameter study was conducted to investigate the applicability of the extracted ROM to initial boundary conditions different from those from which it was extracted. The results show that the ROMs retained satisfactory total errors when the initial conditions in the room were varied by ±5°C. This allows the production of a finite number of ROMs with the ability to rapidly model many possible scenarios.

Improved Process Monitoring Using Nonlinear Principal Component Models

This paper presents two new approaches for use in complete process monitoring. The firstconcerns the identification of nonlinear principal component models. This involves the application of linear
principal component analysis (PCA), prior to the identification of a modified autoassociative neural network (AAN) as the required nonlinear PCA (NLPCA) model. The benefits are that (i) the number of the reduced set of linear principal components (PCs) is smaller than the number of recorded process variables, and (ii) the set of PCs is better conditioned as redundant information is removed. The result is a new set of input data for a modified neural representation, referred to as a T2T network. The T2T NLPCA model is then used for complete process monitoring, involving fault detection, identification and isolation. The second approach introduces a new variable reconstruction algorithm, developed from the T2T NLPCA model. Variable reconstruction can enhance the findings of the contribution charts still widely used in industry by reconstructing the outputs from faulty sensors to produce more accurate fault isolation. These ideas are illustrated using recorded industrial data relating to developing cracks in an industrial glass melter process. A comparison of linear and nonlinear models, together with the combined use of contribution charts and variable reconstruction, is presented.

Surrogate-Based Optimization Using Multifidelity Models with Variable Parameterization and Corrected Space Mapping

Surrogate-based-optimization methods provide a means to achieve high-fidelity design optimization at reduced computational cost by using a high-fidelity model in combination with lower-fidelity models that are less expensive to evaluate. This paper presents a provably convergent trust-region model-management methodology for variableparameterization design models: that is, models for which the design parameters are defined over different spaces. Corrected space mapping is introduced as a method to map between the variable-parameterization design spaces. It is then used with a sequential-quadratic-programming-like trust-region method for two aerospace-related design optimization problems. Results for a wing design problem and a flapping-flight problem show that the method outperforms direct optimization in the high-fidelity space. On the wing design problem, the new method achieves 76% savings in high-fidelity function calls. On a bat-flight design problem, it achieves approximately 45% time savings, although it converges to a different local minimum than did the benchmark.

Mixed-dimensional coupling in finite element models

In many finite element analysis models it would be desirable to combine reduced- or lower-dimensional element types with higher-dimensional element types in a single model. In order to achieve compatibility of displacements and stress equilibrium at the junction or interface between the differing element types, it is important in such cases to integrate into the analysis some scheme for coupling the element types. A novel and effective scheme for establishing compatibility and equilibrium at the dimensional interface is described and its merits and capabilities are demonstrated. Copyright (C) 2000 John Wiley & Sons, Ltd.

THE EFFECT OF RAPID NEUTRAL-NEUTRAL REACTIONS ON CHEMICAL-MODELS OF DENSE INTERSTELLAR CLOUDS

Recent experiments on rapid neutral-neutral reactions involving the radical CN at low temperature and the neutral C atom at room temperature suggest that atom-neutral and radical-neutral reactions may be generally more rapid at low temperature than hitherto thought. We have included a variety of rapid neutral-neutral reactions in our gas-phase chemical models of quiescent, dense interstellar clouds. We find the calculated abundances of many molecules to be greatly changed from previous values. In particular, the peak 'early-time' abundances of organic molecules are reduced.

Abeta oligomer toxicity inhibitor protects memory in models of synaptic toxicity

BACKGROUND AND PURPOSE:

Amyloid-ß (Aß) aggregation into synaptotoxic, prefibrillar oligomers is a major pathogenic event underlying the neuropathology of Alzheimer's disease (AD). The pharmacological and neuroprotective properties of a novel Aß aggregation inhibitor, SEN1269, were investigated on aggregation and cell viability and in test systems relevant to synaptic function and memory, using both synthetic Aß(1-42) and cell-derived Aß oligomers.
EXPERIMENTAL APPROACH:

Surface plasmon resonance studies measured binding of SEN1269 to Aß(1-42) . Thioflavin-T fluorescence and MTT assays were used to measure its ability to block Aß(1-42) -induced aggregation and reduction in cell viability. In vitro and in vivo long-term potentiation (LTP) experiments measured the effect of SEN1269 on deficits induced by synthetic Aß(1-42) and cell-derived Aß oligomers. Following i.c.v. administration of the latter, a complex (alternating-lever cyclic ratio) schedule of operant responding measured effects on memory in freely moving rats.
KEY RESULTS:

SEN1269 demonstrated direct binding to monomeric Aß(1-42) , produced a concentration-related blockade of Aß(1-42) aggregation and protected neuronal cell lines exposed to Aß(1-42) . In vitro, SEN1269 alleviated deficits in hippocampal LTP induced by Aß(1-42) and cell-derived Aß oligomers. In vivo, SEN1269 reduced the deficits in LTP and memory induced by i.c.v. administration of cell-derived Aß oligomers.
CONCLUSIONS AND IMPLICATIONS:

SEN1269 protected cells exposed to Aß(1-42) , displayed central activity with respect to reducing Aß-induced neurotoxicity and was neuroprotective in electrophysiological and behavioural models of memory relevant to Aß-induced neurodegeneration. It represents a promising lead for designing inhibitors of Aß-mediated synaptic toxicity as potential neuroprotective agents for treating AD.

Orally bioavailable small molecule drug protects memory in Alzheimer's disease models

Oligomers of beta-amyloid (Aß) are implicated in the early memory impairment seen in Alzheimer's disease before to the onset of discernable neurodegeneration. Here, the capacity of a novel orally bioavailable, central nervous system-penetrating small molecule 5-aryloxypyrimidine, SEN1500, to prevent cell-derived (7PA2 [conditioned medium] CM) Aß-induced deficits in synaptic plasticity and learned behavior was assessed. Biochemically, SEN1500 bound to Aß monomer and oligomers, produced a reduction in thioflavin-T fluorescence, and protected a neuronal cell line and primary cortical neurons exposed to synthetic soluble oligomeric Aß1-42. Electrophysiologically, SEN1500 alleviated the in vitro depression of long-term potentiation induced by both synthetic Aß1-42 and 7PA2 CM, and alleviated the in vivo depression of long-term potentiation induced by 7PA2 CM, after systemic administration. Behaviorally, oral administration of SEN1500 significantly reduced memory-related deficits in operant responding induced after intracerebroventricular injection of 7PA2 CM. SEN1500 reduced cytotoxicity, acute synaptotoxicity, and behavioral deterioration after in vitro and in vivo exposure to synthetic Aß and 7PA2 CM, and shows promise for development as a clinically viable disease-modifying Alzheimer's disease treatment. © 2013 Elsevier Inc.

An optimisation of Gaussian mixture models for integer processing units

This paper investigates sub-integer implementations of the adaptive Gaussian mixture model (GMM) for background/foreground segmentation to allow the deployment of the method on low cost/low power processors that lack Floating Point Unit (FPU). We propose two novel integer computer arithmetic techniques to update Gaussian parameters. Specifically, the mean value and the variance of each Gaussian are updated by a redefined and generalised "round'' operation that emulates the original updating rules for a large set of learning rates. Weights are represented by counters that are updated following stochastic rules to allow a wider range of learning rates and the weight trend is approximated by a line or a staircase. We demonstrate that the memory footprint and computational cost of GMM are significantly reduced, without significantly affecting the performance of background/foreground segmentation.

Novel comparison of kinetic models for the adsorption-coupled reduction of Cr(VI) using untreated date pit biomaterial

Biosorption of Cr(VI) onto date pit biomass has been investigated via kinetic studies as functions of initial Cr(VI) concentration, solution temperature and date pit particle size. Kinetic experiments indicated that chromate ions accumulate onto the date pits and then reduce to less toxic Cr(III) compounds. The López-García, Escudero and Park Cr(VI) biosorption kinetic models, which take into consideration the direct reduction, the passivation process and the follow-on decrease of the active surface area of reaction, were applied to the kinetic data. The models represented the experimental data accurately at low Cr(VI) concentration (0.480 mM) and small particle size (0.11–0.22 mm) at which the Cr(VI) was completely removed from the aqueous solution and completely reduced to Cr(III) after 420 min. Date pit biomass thus offers a green chemical process for the remediation of chromium from wastewater. This investigation will help researchers employ the adsorption-coupled reduction of Cr(VI) models and simplify their application to kinetic experimental data.

REDUCED ORDER MODELLING OF THE THERMAL BEHAVIOUR OF AN OFFICE SPACE

Reduced Order Models (ROMs) have proven to be a valid and efficient approach to model the thermal behaviour of building zones. The main issues associated with the use of zonal/lumped models are how to (1) divide the domain (lumps) and (2) evaluate the pa- rameters which characterise the lump-to-lump exchange of energy and momentum. The object of this research is to develop a methodology for the generation of ROMs from CFD models. The lumps of the ROM and their average property values are automatically ex- tracted from the CFD models through user defined constraints. This methodology has been applied to validated CFD models of a zone of the Environmental Research Insti- tute (ERI) Building in University College Cork (UCC). The ROM predicts temperature distribution in the domain with an average error lower than 2%. It is computationally efficient with an execution time of 3.45 seconds. Future steps in this research will be the development of the procedure to automatically extract the parameters which define lump-to-lump energy and momentum exchange. At the moment these parameters are evaluated through the minimisation of a cost function. The ROMs will also be utilised to predict the transient thermal behaviour of the building zone.

Late Holocene sea-level fall and turn-off of reef flat carbonate production: Rethinking bucket fill and coral reef growth models

Relative sea-level rise has been a major factor driving the evolution of reef systems during the Holocene. Most models of reef evolution suggest that reefs preferentially grow vertically during rising sea level then laterally from windward to leeward, once the reef flat reaches sea level. Continuous lagoonal sedimentation ("bucket fill") and sand apron progradation eventually lead to reef systems with totally filled lagoons. Lagoonal infilling of One Tree Reef (southern Great Barrier Reef) through sand apron accretion was examined in the context of late Holocene relative sea-level change. This analysis was conducted using sedimentological and digital terrain data supported by 50 radiocarbon ages from fossil microatolls, buried patch reefs, foraminifera and shells in sediment cores, and recalibrated previously published radiocarbon ages. This data set challenges the conceptual model of geologically continuous sediment infill during the Holocene through sand apron accretion. Rapid sand apron accretion occurred between 6000 and 3000 calibrated yr before present B.P. (cal. yr B.P.); followed by only small amounts of sedimentation between 3000 cal. yr B.P. and present, with no significant sand apron accretion in the past 2 k.y. This hiatus in sediment infill coincides with a sea-level fall of similar to 1-1.3 m during the late Holocene (ca. 2000 cal. yr B.P.), which would have caused the turn-off of highly productive live coral growth on the reef flats currently dominated by less productive rubble and algal flats, resulting in a reduced sediment input to back-reef environments and the cessation in sand apron accretion. Given that relative sea-level variations of similar to 1 m were common throughout the Holocene, we suggest that this mode of sand apron development and carbonate production is applicable to most reef systems.

An invasive-native mammalian species replacement process captured by camera trap survey random encounter models

Camera traps are used to estimate densities or abundances using capture-recapture and, more recently, random encounter models (REMs). We deploy REMs to describe an invasive-native species replacement process, and to demonstrate their wider application beyond abundance estimation. The Irish hare Lepus timidus hibernicus is a high priority endemic of conservation concern. It is threatened by an expanding population of non-native, European hares L. europaeus, an invasive species of global importance. Camera traps were deployed in thirteen 1 km squares, wherein the ratio of invader to native densities were corroborated by night-driven line transect distance sampling throughout the study area of 1652 km2. Spatial patterns of invasive and native densities between the invader’s core and peripheral ranges, and native allopatry, were comparable between methods. Native densities in the peripheral range were comparable to those in native allopatry using REM, or marginally depressed using Distance Sampling. Numbers of the invader were substantially higher than the native in the core range, irrespective of method, with a 5:1 invader-to-native ratio indicating species replacement. We also describe a post hoc optimization protocol for REM which will inform subsequent (re-)surveys, allowing survey effort (camera hours) to be reduced by up to 57% without compromising the width of confidence intervals associated with density estimates. This approach will form the basis of a more cost-effective means of surveillance and monitoring for both the endemic and invasive species. The European hare undoubtedly represents a significant threat to the endemic Irish hare.

Nonsteroidal Anti-Inflammatory Drug Use is Not Associated With Reduced Risk of Barrett’s Esophagus

OBJECTIVES: Regular use of nonsteroidal anti-inflammatory drugs (NSAIDs) is associated with a reduced risk of esophageal adenocarcinoma. Epidemiological studies examining the association between NSAID use and the risk of the precursor lesion, Barrett’s esophagus, have been inconclusive.

METHODS: We analyzed pooled individual-level participant data from six case-control studies of Barrett’s esophagus in the Barrett’s and Esophageal Adenocarcinoma Consortium (BEACON). We compared medication use from 1474 patients with Barrett’s esophagus separately with two control groups: 2256 population-based controls and 2018 gastroesophageal reflux disease (GERD) controls. Study-specific odds ratios (OR) and 95% confidence intervals (CI) were estimated using multivariable logistic regression models and were combined using a random effects meta-analytic model.

RESULTS: Regular (at least once weekly) use of any NSAIDs was not associated with the risk of Barrett’s esophagus (vs. population-based controls, adjusted OR = 1.00, 95% CI = 0.76–1.32; I2=61%; vs. GERD controls, adjusted OR = 0.99, 95% CI = 0.82–1.19; I2=19%). Similar null findings were observed among individuals who took aspirin or non-aspirin NSAIDs. We also found no association with highest levels of frequency (at least daily use) and duration (≥5 years) of NSAID use. There was evidence of moderate between-study heterogeneity; however, associations with NSAID use remained non-significant in “leave-one-out” sensitivity analyses.

CONCLUSIONS: Use of NSAIDs was not associated with the risk of Barrett’s esophagus. The previously reported inverse association between NSAID use and esophageal adenocarcinoma may be through reducing the risk of neoplastic progression in patients with Barrett’s esophagus.

MicroRNA signatures differentiate preserved from reduced ejection fraction heart failure

AIMS: Differentiation of heart failure with reduced (HFrEF) or preserved (HFpEF) ejection fraction independent of echocardiography is challenging in the community. Diagnostic strategies based on monitoring circulating microRNA (miRNA) levels may prove to be of clinical value in the near future. The aim of this study was to identify a novel miRNA signature that could be a useful HF diagnostic tool and provide valuable clinical information on whether a patient has HFrEF or HFpEF.

METHODS AND RESULTS: MiRNA biomarker discovery was carried out on three patient cohorts, no heart failure (no-HF), HFrEF, and HFpEF, using Taqman miRNA arrays. The top five miRNA candidates were selected based on differential expression in HFpEF and HFrEF (miR-30c, -146a, -221, -328, and -375), and their expression levels were also different between HF and no-HF. These selected miRNAs were further verified and validated in an independent cohort consisting of 225 patients. The discriminative value of BNP as a HF diagnostic could be improved by use in combination with any of the miRNA candidates alone or in a panel. Combinations of two or more miRNA candidates with BNP had the ability to improve significantly predictive models to distinguish HFpEF from HFrEF compared with using BNP alone (area under the receiver operating characteristic curve >0.82).

CONCLUSION: This study has shown for the first time that various miRNA combinations are useful biomarkers for HF, and also in the differentiation of HFpEF from HFrEF. The utility of these biomarker combinations can be altered by inclusion of natriuretic peptide. MiRNA biomarkers may support diagnostic strategies in subpopulations of patients with HF.