Development of the consistent second-order plate theory for transversely isotropic plates and its analytical assessment from the three-dimensional perspective

Financial support of this research by The Royal Society (UK) International Exchanges award (IE161021) and by the German Science Foundation (DFG) under Project-No. Ki 284/25-1 is gratefully acknowledgedPeer reviewedPostprin

PREFACE

Abstract. Simply defined, a Smart City is a city overlaid by a digital layer, which is used for the governance of the city. A Smart City uses intelligent technology to enhance our quality of life in urban environments, bringing together people and data from disparate sources such as sensors, demographics, topographic and 3D mapping, Building Information Models and many more. Increasingly, Smart Cities use this data in a variety of ways, to address key challenges related to transportation, communications, air quality, noise, well-being of the citizens, decision making relating to education and health and urban planning, as well as in relation to initiatives such as startups and fostering economic growth and employment within the city. As more data becomes available, the challenges of storing, managing and integrating such data are also multiplied.The first Urban Data Management Symposium (UDMS) was held in 1971 in Bonn, Germany, made the choice of hosting the 6th international conference on Smart Data and Smart Cities (SDSC) in Stuttgart a very natural one. SDSC was established in 2016 as the successor of the UDMS, and this year we celebrate the 40th anniversary of the series of symposia and conferences. The SDSC 2021 will be part of the scientific week on intelligent cities at HFT Stuttgart. Together four events were held during the week of 14th – 17th September 2021, and alongside SDSC participants were invited to attend the "Energy, water and food for the cities of the future" conference, the "LIS-City – liveable, intelligent, and sustainable City" workshop, and the mobility day Stuttgart. Participant interaction – and the ability to attend sessions across the four events – was particularly encouraged. SDSC 2021 itself was organised by the Urban Data Management Society (UDMS www.udms.net), ISPRS and HFT Stuttgart (the University of Applied Science Stuttgart), and Professor Volker Coors Chaired the SDSC committee.As in previous years, three key conference themes were proposed to represent the Smart Cities: Smart Data (sensor network databases, on-the-fly data mining, geographic and urban knowledge modeling and engineering, green computing, urban data analytics and big data, big databases and data management), Smart People (volunteered information, systems for public participation) and Smart Cities (systems of territorial intelligence, systems for city intelligence management, 3D modeling of cities, internet of things, social networks, monitoring systems, mobility and transportation, smart-city-wide telecommunications infrastructure, urban knowledge engineering, urban dashboard design and implementation, new style of urban decision-making systems, geovisualization devoted to urban problems, disaster management systems).This volume consists of 18 papers, which were selected from 41 submissions on the basis of peer review. These papers present novel research concerning the use of spatial information and communication technologies in Smart Cities, addressing different aspects relating to Smart Data. Selected papers tackle different aspects of Smart Cities: transport, sustainable mobility; dashboards and web GIS; citizen engagement and participation; sensors; urban decision making.The editors are grateful to the members of the Scientific Committee for their time and valuable comments, which contributed to the high quality of the papers. Reviews were contributed by: Alias Abdul-Rahman, Giorgio Agugiaro, Ken Arroyo Ohori, John Barton, Martina Baucic, Filip Biljecki, Lars Bodum, Pawel Boguslawski, Azedine Boulmakoul, Matteo Caglioni, Caesar Cardenas, Eliseo Clementini, Volker Coors, Youness Dehbi, Abdoulaye Abou Diakité, Adil El Bouziri, Claire Ellul, Tarun Ghawana, Gesquiere Gilles, Didier Grimaldi, Ori Gudes, Stephen Hirtle, Martin Kada, Lamia Karim, Robert Laurini, Christina Mickrenska-Cherneva, Christopher Petit, Alenka Poplin, Ivana Racetin, Dimos Pantazis, Preston Rodrigues, Camilo Leon Sanchez, Genoveva Vargas Solar, Nils Walravens, Parag Wate, Besri Zineb, Sisi Zlatanova. We are also grateful to the work of the local organising committee at HFT Stuttgart, without whom this conference would not have been possible

PREFACE

Abstract. Simply defined, a Smart City is a city overlaid by a digital layer, which is used for the governance of the city. A Smart City uses intelligent technology to enhance our quality of life in urban environments, bringing together people and data from disparate sources such as sensors, demographics, topographic and 3D mapping, Building Information Models and many more. Increasingly, Smart Cities use this data in a variety of ways, to address key challenges related to transportation, communications, air quality, noise, well-being of the citizens, decision making relating to education and health and urban planning, as well as in relation to initiatives such as startups and fostering economic growth and employment within the city. As more data becomes available, the challenges of storing, managing and integrating such data are also multiplied.The first Urban Data Management Symposium (UDMS) was held in 1971 in Bonn, Germany, made the choice of hosting the 6th international conference on Smart Data and Smart Cities (SDSC) in Stuttgart a very natural one. SDSC was established in 2016 as the successor of the UDMS, and this year we celebrate the 40th anniversary of the series of symposia and conferences. The SDSC 2021 will be part of the scientific week on intelligent cities at HFT Stuttgart. Together four events were held during the week of 14th – 17th September 2021, and alongside SDSC participants were invited to attend the "Energy, water and food for the cities of the future" conference, the "LIS-City – liveable, intelligent, and sustainable City" workshop, and the mobility day Stuttgart. Participant interaction – and the ability to attend sessions across the four events – was particularly encouraged. SDSC 2021 itself was organised by the Urban Data Management Society (UDMS www.udms.net), ISPRS and HFT Stuttgart (the University of Applied Science Stuttgart), and Professor Volker Coors Chaired the SDSC committee.As in previous years, three key conference themes were proposed to represent the Smart Cities: Smart Data (sensor network databases, on-the-fly data mining, geographic and urban knowledge modeling and engineering, green computing, urban data analytics and big data, big databases and data management), Smart People (volunteered information, systems for public participation) and Smart Cities (systems of territorial intelligence, systems for city intelligence management, 3D modeling of cities, internet of things, social networks, monitoring systems, mobility and transportation, smart-city-wide telecommunications infrastructure, urban knowledge engineering, urban dashboard design and implementation, new style of urban decision-making systems, geovisualization devoted to urban problems, disaster management systems).This volume consists of 14 papers, which were selected from 41 submissions on the basis of double blind review, with each paper being reviewed by a minimum of three reviewers. These papers present novel research concerning the use of spatial information and communication technologies in Smart Cities, addressing different aspects of Smart Data and Smart Citizens. The selected papers tackle different aspects of Smart Cities: 3D; Citizen Engagement; transport, sustainable mobility; dashboards and web GIS; citizen engagement and participation; sensors; urban decision making.The editors are grateful to the members of the Scientific Committee for their time and valuable comments, which contributed to the high quality of the papers. Reviews were contributed by: Alias Abdul-Rahman, Giorgio Agugiaro, Ken Arroyo Ohori, John Barton, Martina Baucic, Filip Biljecki, Lars Bodum, Pawel Boguslawski, Azedine Boulmakoul, Matteo Caglioni, Caesar Cardenas, Eliseo Clementini, Volker Coors, Youness Dehbi, Abdoulaye Abou Diakité, Adil El Bouziri, Claire Ellul, Tarun Ghawana, Gesquiere Gilles, Didier Grimaldi, Ori Gudes, Stephen Hirtle, Martin Kada, Lamia Karim, Robert Laurini, Christina Mickrenska-Cherneva, Christopher Petit, Alenka Poplin, Ivana Racetin, Dimos Pantazis, Preston Rodrigues, Camilo Leon Sanchez, Genoveva Vargas Solar, Nils Walravens, Parag Wate, Besri Zineb, Sisi Zlatanova. We are also grateful to the work of the local organising committee at HFT Stuttgart, without whom this conference would not have been possible

PREFACE

n/

PREFACE

n/

Effect of Treatment and Cultivar on the Ensiling of Corn Stover

Nine cultivars of corn stover selected for ethanol potential were harvested (34 to 40% dry matter) and each ensiled with six treatments: untreated, lactic acid bacteria, cell-wall degrading enzymes, sulfuric acid, bacteria-enzyme combination and enzyme-acid combination. Ensiling was carried out in vacuum-sealed bags at ~22°C for 60 d. The untreated stovers ensiled well. Lactic acid bacteria and enzyme treatments had no effect on pH, but the bacteria-enzyme combination lowered pH in some cultivars. The acid and acid-enzyme treatments had low pH values ranging from 1.3 to 1.5. Lactic acid was generally highest in the bacteria-enzyme treatment whereas acetic acid was highest for the acid treatments. The acid treatments substantially reduced hemicellulose. Potential ethanol yield on average was highest in the bacteria-enzyme treatments

Framework for emulation and uncertainty quantification of a stochastic building performance simulator

A good framework for the quantification and decomposition of uncertainties in dynamic building performance simulation should: (i) simulate the principle deterministic processes influencing heat flows and the stochastic perturbations to them, (ii) quantify and decompose the total uncertainty into its respective sources, and the interactions between them, and (iii) achieve this in a computationally efficient manner. In this paper we introduce a new framework which, for the first time, does just that. We present the detailed development of this framework for emulating the mean and the variance in the response of a stochastic building performance simulator (EnergyPlus co-simulated with a multi agent stochastic simulator called No-MASS), for heating and cooling load predictions. We demonstrate and evaluate the effectiveness of these emulators, applied to a monozone office building. With a range of 25–50 kWh/m2, the epistemic uncertainty due to envelope parameters dominates over aleatory uncertainty relating to occupants' interactions, which ranges from 6–8 kWh/m2, for heating loads. The converse is observed for cooling loads, which vary by just 3 kWh/m2 for envelope parameters, compared with 8–22 kWh/m2 for their aleatory counterparts. This is due to the larger stimuli provoking occupants' interactions. Sensitivity indices corroborate this result, with wall insulation thickness (0.97) and occupants' behaviours (0.83) having the highest impacts on heating and cooling load predictions respectively. This new emulator framework (including training and subsequent deployment) achieves a factor of c.30 reduction in the total computational budget, whilst overwhelmingly maintaining predictions within a 95% confidence interval, and successfully decomposing prediction uncertainties

Development of a fluorescence-based method for monitoring glucose catabolism and its potential use in a biomass hydrolysis assay

<p>Abstract</p> <p>Background</p> <p>The availability and low cost of lignocellulosic biomass has caused tremendous interest in the bioconversion of this feedstock into liquid fuels. One measure of the economic viability of the bioconversion process is the ease with which a particular feedstock is hydrolyzed and fermented. Because monitoring the analytes in hydrolysis and fermentation experiments is time consuming, the objective of this study was to develop a rapid fluorescence-based method to monitor sugar production during biomass hydrolysis, and to demonstrate its application in monitoring corn stover hydrolysis.</p> <p>Results</p> <p>Hydrolytic enzymes were used in conjunction with <it>Escherichia coli </it>strain CA8404 (a hexose and pentose-consuming strain), modified to produce green fluorescent protein (GFP). The combination of hydrolytic enzymes and a sugar-consuming organism minimizes feedback inhibition of the hydrolytic enzymes. We observed that culture growth rate as measured by change in culture turbidity is proportional to GFP fluorescence and total growth and growth rate depends upon how much sugar is present at inoculation. Furthermore, it was possible to monitor the course of enzymatic hydrolysis in near real-time, though there are instrumentation challenges in doing this.</p> <p>Conclusion</p> <p>We found that instantaneous fluorescence is proportional to the bacterial growth rate. As growth rate is limited by the availability of sugar, the integral of fluorescence is proportional to the amount of sugar consumed by the microbe. We demonstrate that corn stover varieties can be differentiated based on sugar yields in enzymatic hydrolysis reactions using post-hydrolysis fluorescence measurements. Also, it may be possible to monitor fluorescence in real-time during hydrolysis to compare different hydrolysis protocols.</p

DEVELOPMENT OF QGIS PLUGIN FOR URBAN ENERGY SIMULATION USING 3D CITY MODEL AT THE CITY DISTRICT LEVEL

In the context of climate change, the increasing demand for energy-efficient buildings and sustainable urban development has become a pressing issue due to the significant proportion of global energy consumption and carbon dioxide (CO2) emissions attributable to the building sector. This requires a concerted effort to reduce its environmental impact, and Geographic Information System (GIS) applications are vital tools for achieving this by optimizing heat supply, calculating costs, analyzing profitability, and balancing CO2 emissions. This study aims to address the challenge of achieving energy efficiency and reducing CO2 emissions in the building sector, specifically at the district level. To this end, the research objective is to develop a QGIS plugin that can simulate urban energy demand at the district level by integrating 2D data with CityGML files and connecting QGIS to SimStadt software via API to visualize the simulated urban energy results in 3D on the Web Globe. The proposed plugin leverages the open-source QGIS tool QField to capture building conditions and connect 2D and 3D data on urban energy simulation. Supplementary to this, this plugin provides up-to-date information on energy demand, consumption, CO2 emissions, building component conditions via updating related tables in the database. Decision-makers can use this comprehensive and user-friendly tool to understand and act on the results, ultimately leading to a CO2-neutral district by 2045. The development of the QGIS plugin represents a significant step towards sustainable urban development and climate change mitigation by utilizing GIS applications for optimizing energy demand and reducing CO2 emissions in the built environment