259 research outputs found
An Kopf und Fuß angenehme Turbulenzen, Klimatisierung: Superrechner erlaubt erstmals Strömungssimulation in Echtzeit
No full textHeißer Kopf, kalte Füße. Der Dummy in der Flugzeugkabine schwitzt und friert gleichzeitig. Aus den Belüftungsdüsen strömt viel zu warme Luft direkt in sein Gesicht. Dafür herrscht an seinen Füßen Eiszeit, deshalb auch die warmen Socken. "Die Klimatisierung von Innenräumen ist eine Kunst für sich", sagt Dr. Christoph van Treeck von der TU München
Man kann nicht nicht lernen. Informelles Lernen in der Ausbildung von Lehrkräften
No full textMertens C, Claes S, Becker P. Man kann nicht nicht lernen. Informelles Lernen in der Ausbildung von Lehrkräften. In: Heuchemer S, Siller F, van Treeck T, eds. Hochschuldidaktik forscht zu Vielfalt und Offenheit. Profilbildung und Wertefragen in der Hochschulentwicklung I. Forschung und Innovation in der Hochschulbildung. Vol 2. Berlin: DUZ Medienhaus; 2018: 105-119
Das eCoFolio – ein reflexives E‐Portfolio in der Lehramtsausbildung für Berufsschulen
No full textClaes S, Fischer Y, Mertens C. Das eCoFolio – ein reflexives E‐Portfolio in der Lehramtsausbildung für Berufsschulen. In: Heuchemer S, Szczyrba B, van Treeck T, eds. Hochschuldidaktik und Hochschulentwicklung ‐ Praxisperspektiven zwischen Profilbildung und Wertefragen . Blickpunkt Hochschuldidaktik. Vol 136. Bielefeld: wbv Publikation; 2020: 207-214
Berechnung der Wärmestrahlungsausbreitung für die thermische Komfortanalyse in Innenräumen
No full textBoth air convection and thermal radiation have relevant impact on climate and comfort in indoor environments. In addition to the simulation and the evaluation of air flow and turbulences a detailed examination of the radiative heat exchange and its mutual interdependencies is necessary. In the research project COMFSIM (van Treeck et al., 2007) different simulation and comfort assessment methods will be implemented within an interactive, real time 3D simulation environment (Computational Steering Environment, CSE) (Wensich, 2008). This contribution will provide an overview over the current work, i.e. the implementation of numerical methods for the simulation of the thermal radiation into the CSE by presenting first results of such simulations
Indoor environment data time-series reconstruction using autoencoder neural networks
No full textAs the number of installed meters in buildings increases, there is a growing number of data time-series that could be used to develop data-driven models to support and optimize building operation. However, building data sets are often characterized by errors and missing values, which are considered, by the recent research, among the main limiting factors on the performance of the proposed models. Motivated by the need to address the problem of missing data in building operation, this work presents a data-driven approach to fill these gaps. In this study, three different autoencoder neural networks are trained to reconstruct missing short-term indoor environment data time-series in a data set collected in an office building in Aachen, Germany. This consisted of a four year-long monitoring campaign in and between the years 2014 and 2017, of 84 different rooms. The models are applicable for different time-series obtained from room automation, such as indoor air temperature, relative humidity and CO2 data streams. The results prove that the proposed methods outperform classic numerical approaches and they result in reconstructing the corresponding variables with average RMSEs of 0.42 °C, 1.30 % and 78.41 ppm, respectively
A gap-filling method for room temperature data based on autoencoder neural networks
No full textThis study explores the applicability of a deep learning-based approach for reconstructing missing room temperature data from different domains where relatively few training samples are available. For that purpose, the existing convolutional, long short-term memory (LSTM) and feed-forward autoencoders were combined with a suitable domain adaptation procedure. Eventually, the developed models were evaluated on data collected in four buildings with significant differences in thermal mass, design and location. The findings pointed out that the domain adaptation can be conducted effciently by using a small data sample from the target domain. Additionally, the results showed that the proposed model can reconstruct up to 80 % of the missing daily room temperature inputs with RMSE accuracy of 0.6 °C
Augmenting energy time-series for data-efficient imputation of missing values
No full textThis study explores the applicability of data augmentation techniques for reconstructing missing energy time -series in limited data regimes. In particular, multiple synthetic copies of a relatively small training dataset are stacked together with pseudo-random noise. First, an existing convolutional denoising autoencoder is selected from a previous work, as the base imputation model of this study. Then, an optimal augmentation rate, which minimizes the training set of the model, is chosen based on the preliminary results obtained from one building. The results proved that, augmenting 80 times a nine days-long training set could reduce the initial average root mean squared error (RMSE) by 37% and 48%, for continuous and random missing scenarios. Additionally, the augmented model outperformed the benchmark methods with 23% and 12% lower average RMSE. No additional tuning or calibration costs were required for the existing base imputation model. Therefore, the presented data augmentation technique could significantly reduce the expensive computational costs associated with deep learning models
'Financialisation' in Post-Keynesian models of distribution and growth - a systematic review
No full textWe review recent attempts to integrate 'financialisation' processes into Post-Keynesian distribution and growth models and distinguish three principal channels of influence: 1. objectives and finance restrictions of firms, 2. new opportunities for households' wealth-based and debt-financed consumption, and 3. distribution between capital and labour, on the one hand, and between management and workers on the other hand. Starting from a re-interpretation of the Post-Keynesian theory of the firm we bridge the gap between micro- and macro-analysis of 'financialisation' and we trace the main characteristics and effects of 'financialisation' from the micro to the macro level taking into account stock-flow interactions. Our review of the theoretical literature on 'financialisation' shows that expansive effects may arise under certain conditions, in particular when there are strong wealth effects in firms' investment decisions (via Tobin's q) and in households' consumption decisions. However, our review also suggests that even an expansive finance-led economy may build up major financial imbalances, i.e. increasing debt-capital or debt-income ratios, which make such economies prone to financial instability.Financialisation, Post-Keynesian distribution and growth models
The political economy debate on ‘financialisation’ – a macroeconomic perspective
No full textA number of important contributions to the political economy literature have argued that changes in the financial sector have been amongst the main reflections, or even the driving forces, of recent transformations of capitalism in the rich countries. This hypothesis has been referred to as 'financialisation'. We argue in this article that the interdisciplinary literature could be enriched if the macroeconomic dimension of financialisation was more explicitly taken into account. In particular, important macroeconomic constraints regarding the determination of profits, in the face of a decreasing importance of physical investment and an increased importance of financial operations, are often not explicitly considered. We compare our macroeconomic approach with contributions from different strands in the existing literature, including empirical analyses of new patterns of profit generation, the 'varieties of capitalism' approach, the British 'social accounting' literature, and the French 'regulationist' literature. Our theoretical framework is illustrated by means of an empirical comparison of the effects of financialisation in the USA and in Germany.Financialisation, political economy, varieties of capitalism, social accounting, regulationism
A Synthetic, Stock-Flow Consistent Macroeconomic Model of Financialisation
No full textThis article is centred around the notions of shareholder value orientation and financialisation. Shareholder value orientation is reflected by a high dividend payout ratio applied by firms and the reluctance of firms to finance physical investment via new equity issues. Financialisation is the more general development towards an increased importance of the financial sector of the economy relative to the non-financial sector. In this article, a synthetic, stock-flow consistent model is developed that attempts to encompass and at times adjust some important recent works on the effects of financialisation. This includes contributions from the fields of mainstream information economics and Post Keynesian economics. We conduct simulations reflecting increased shareholder value orientation and show that the model produces a number of results that appear consistent with many stylised facts particularly of the US economy since the early 1980s.Stocks and Flows, Corporate Governance, Investment Finance, Payout Policy, Income Distribution
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