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Optimizing building design for daylighting

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Optimizing building design for daylighting

IIE Annual Conference and Expo 2013

作者： Futrell, Benjamin J. Ozelkan, Ertunga C. School of Architecture Infrastructure and Environmental Systems Ph.D. Program University of North Carolina at Charlotte Charlotte NC 28223 United States Systems Engineering and Engineering Management University of North Carolina at Charlotte Charlotte NC 28223 United States

ISBN: (纸本)9780983762423

We address the challenging problem of optimizing building design to minimize lighting loads, which is one of the two largest sources of energy consumption in buildings, besides thermal (heating and cooling) loads. Judiciously designed building envelopes, which employ daylight harvesting characteristics, can reduce these loads by 50%. Robust and validated lighting tools exist for the performance evaluation of building designs;however, they are not commonly used to explore the performance of many design alternatives. In practice, their use is often limited to validating one or several designs. Building design optimization programs have been developed;however, most of these tools focus exclusively on the optimization of envelope thermal loads or use simple, outdated lighting evaluation methods. The inclusion of rigorous holistic lighting performance evaluation for optimization is important because lighting energy represents about 40% of the total electricity used by commercial buildings. We present a new methodology, using state-of-the-art dynamic climate-based lighting simulations and the COMPLEX Method of Constrained Optimization, to optimize building design for daylighting performance. The results indicate that the design space region of optimum performance can be found quickly, but converge is sometimes slow.

关键词： Energy utilization

Monotonic Torsion of Vat Photopolymerized Tough Resin Polymers: The Effects of Gage Length and Ultraviolet Post-Curing

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SSRN 2023年

作者： Sadaghian, Hamed Khalilzadehtabrizi, Sahand Khodadoost, Saeed Yeon, Jung Heum School of Architecture Building and Civil Engineering Loughborough University LoughboroughLE11 3TU United Kingdom Department of Civil and Environmental Engineering Centre for Infrastructure Systems Engineering University of Surrey Guilford United Kingdom Department of Civil Engineering University of Tabriz Tabriz Iran Civil Engineering Program Ingram School of Engineering Texas State University San MarcosTX78666 United States

Numerous materials, including soft sensors, microgrippers, metamaterials, bone substitutes, photopolymers, and functionally graded materials, undergo torsional loading throughout their service life. With the widespread adoption of additive manufacturing technology across various fields, many of the foregoing components are fabricated using additive manufacturing technology. Hence, it is essential to characterize the torsional behavior of additively-manufactured components before using them. More importantly, studies on additively-manufactured resin polymers are scarce, if any. To this end, the vat photopolymerization (VPP) technique was employed to fabricate 48 torsion specimens. These specimens were additively manufactured from the AnyCubic ultraviolet (UV) Tough Resin Material in a vertical build orientation. The study involved four different gage lengths: 20, 40, 60, and 80 mm. Additionally, five UV post-curing times (0, 15, 30, 60, 90, and 120 minutes) were considered as variables. Monotonic torsion was applied to the specimens at a rate of 0.1 revolutions per minute until failure. The results revealed that the failure patterns of all specimens were ductile. It was observed that longer post-curing times correlated with increased torsional capacities and shear moduli. However, no definitive conclusion could be drawn regarding the energy absorption per unit volume of the specimens. Furthermore, a normalized trilinear model was proposed to characterize the behavior of additively-manufactured resin polymers under monotonic torsion. This model is applicable for finite element software, enabling numerical simulation of the material’s response. © 2023, The Authors. All rights reserved.

关键词： Photopolymerization

Torsional Performance of Vat-Photopolymerized Tough Resins: Influences of Gauge Length and Uv Post-Curing

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SSRN 2024年

A myriad of materials, ranging from soft sensors to bone substitutes, undergo torsional loading throughout their operational lifespan, often produced using additive manufacturing (AM) technology due to its broad applicability. Understanding the torsional behavior of these AM components is paramount prior to their utilization. However, research concerning the torsional behavior of solid additively-manufactured resin polymers remains limited. To bridge this gap, 48 torsion specimens were fabricated using vat photopolymerization (VPP) with AnyCubic UV Tough Resin. These specimens varied in gage lengths (20, 40, 60, and 80 mm) and were subjected to five UV post-curing durations (0, 15, 30, 60, 90, and 120 minutes). Monotonic torsion was applied until failure at a rate of 0.1 revolutions per minute, revealing ductile failure patterns across specimens. Longer post-curing times correlated with increased torsional capacities and shear moduli, although conclusions regarding energy absorption per unit volume remained inconclusive. Additionally, a normalized trilinear model was proposed to characterize the behavior of additively-manufactured resin polymers under monotonic torsion, facilitating numerical simulation of material responses in finite element software. © 2024, The Authors. All rights reserved.

关键词： Torsional stress

On How Data are Used in Model Development: The Elephant in the Room

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SSRN 2023年

作者： Maier, Holger R. Zheng, Feifei Gupta, Hoshin Chen, Junyi Mai, Juliane Savic, Dragan Loritz, Ralf Wu, Wenyan Guo, Danlu Bennett, Andrew Zhao, Jianshi School of Architecture and Civil Engineering The University of Adelaide Adelaide Australia College of Civil Engineering and Architecture Zhejiang University China Department of Hydrology and Atmospheric Sciences The University of Arizona Tucson United States Computational Hydrosystems Helmholtz Centre for Environmental Research–UFZ Leipzig Germany Center for Scalable Data Analytics and Artificial Intelligence–ScaDS.AI Leipzig Germany KWR Water Research Institute Netherlands Centre for Water Systems University of Exeter Exeter United Kingdom Institute of Water and River Basin Management Karlsruhe Germany Department of Infrastructure Engineering The University of Melbourne Melbourne Australia School of Engineering College of Engineering Computing & Cybernetics Australian National University Canberra Australia Department of Hydraulic Engineering Tsinghua University Beijing China

Models are widely used to support the development of understanding regarding the physical nature of Earth and environmental systems, with a view to improving their planning and management. Data is crucial to the development of such models, and it is common to partition the available data into separate subsets to be used for model development and evaluation. Although the manner by which the data is partitioned can significantly affect the model’s ability to generalize to novel conditions, this issue has (surprisingly) been largely ignored (i.e., the elephant in the room). Here we highlight the importance of careful attention to this aspect of the model development process and how it can impact the generalization ability of models. We report on the problems with commonly used, as well as more advanced data-splitting approaches. We also map out a way forward to enable us to address the elephant in the room. © 2023, The Authors. All rights reserved.

关键词： Data handling

Author Correction: High-resolution, large-scale laboratory measurements of a sandy beach and dynamic cobble berm revetment

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Scientific data 2021年第1期8卷 86页

作者： Chris E Blenkinsopp Paul M Bayle Daniel C Conley Gerd Masselink Emily Gulson Isabel Kelly Rafael Almar Ian L Turner Tom E Baldock Tomas Beuzen Robert T McCall Huub Rijper Ad Reniers Peter Troch David Gallach-Sanchez Alan J Hunter Oscar Bryan Gwyn Hennessey Peter Ganderton Marion Tissier Matthias Kudella Stefan Schimmels Centre for Infrastructure Geotechnics and Water Engineering Department of Architecture and Civil Engineering University of Bath Bath BA2 7AY UK. c.blenkinsopp@bath.ac.uk. Centre for Infrastructure Geotechnics and Water Engineering Department of Architecture and Civil Engineering University of Bath Bath BA2 7AY UK. School of Biological and Marine Sciences Plymouth University Drake Circus PL4 8AA Plymouth UK. IRD-LEGOS UMR5566 18 Av. Edouard Belin 31400 Toulouse France. Water Research Laboratory School of Civil and Environmental Engineering UNSW Sydney NSW 2052 Australia. School of Civil Engineering University of Queensland Brisbane QLD 4072 Australia. Department of Statistics University of British Columbia Vancouver Canada. Department of Marine and Coastal Systems Deltares Boussinesqweg 1 2629 HV Delft the Netherlands. Royal Boskalis Westminster N.V. Rosmolenweg 20 3356 LK Papendrecht the Netherlands. Faculty of Civil Engineering and Geosciences Delft University of Technology Stevinweg 1 2628 CN Delft The Netherlands. Department of Civil Engineering Ghent University Technologiepark 60 Ghent B-9052 Belgium. DEME Group Scheldedijk 30 2070 Zwijndrecht Belgium. Department of Mechanical Engineering University of Bath Bath BA2 7AY UK. Forschungszentrum Küste (FZK) Merkurstraße 11 30419 Hannover Germany.

A Correction to this paper has been published: https://***/10.1038/s41597-021-00874-2.

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Monitoring and Control of Forest Seedling Quality in Europe

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SSRN 2023年

作者： Mataruga, Milan Cvjetković, Branislav De Cuyper, Bart Aneva, Ina Zhelev, Petar Cudlín, Pavel Metslaid, Marek Kankaanhuhta, Ville Collet, Catherine Annighöfer, Peter Mathes, Thomas Marianthi, Tsakaldimi Despoina, Paitaridou Jónsdóttir, Rakel J. Monteverdi, Maria Cristina Dato, Giovanbattista de Mariotti, Barbara Kolevska, Dana Dina Lazarević, Jelena Fløistad, Inger Sundheim Klisz, Marcin Gil, Wojciech Paiva, Vasco Fonseca, Teresa Nicolescu, Valeriu-Norocel Popović, Vladan Devetaković, Jovana Repáč, Ivan Božič, Gregor Kraigher, Hojka Andivia, Enrique Diez, Julio J. Böhlenius, Henrik Löf, Magnus Bilir, Nebi Villar-Salvador, Pedro Faculty of Forestry University of Banja Luka Stepe Stepanovića 75a Banja Luka Serbia Research Institute for Nature and Forest Gaverstraat 4 Geraardsbergen9500 Belgium Institute of Biodiversity and Ecosystem Research Bulgarian Academy of Sciences Sofia Bulgaria University of Forestry Sofia Bulgaria Global Change Research Institute Department of Ecosystem Function Analysis of the Landscape Academy of Sciences of the Czech Republic v.v.i. Lipová 9 České Budějovice370 05 Czech Republic Institute of Forestry and Engineering Estonian University of Life Sciences Tartu51006 Estonia Latokartanonkaari 9 Helsinki00790 Finland Université de Lorraine AgroParisTech INRAE UMR Silva Nancy54000 France Forest and Agroforest Systems TUM School of Life Sciences Technical University of Munich Germany Aristotle University of Thessaloniki School of Agriculture Forestry and Natural Environment Dept. of Silviculture Thessaloniki Greece Ministry of Environment and Energy General Directorate of Forest and Forest Environment Directorate of Forest works and Infrastructure Section of Forest Nurseries & Forest Genetic Resources & Reforestation Athens Greece Icelandic Forest Research Krókeyri AkureyriIS-600 Iceland CREA Research Centre for Forestry and Wood Viale Santa Margherita Arezzo80 52100 Italy University of Florence Firenze Italy Hans Em Faculty of Forest Sciences Landscape Architecture and Environmental Engineering 16 Makedonska brigada Str. 1 Skopje1000 Macedonia Biotechnical Faculty Center for Forestry University of Montenegro Mihaila Lalića 15 Podgorica81 000 Montenegro Norwegian Institute of Bioeconomy Research Division of Forest and Forest Resources P.O. Box 115 ÅsNO-1431 Norway Department of Silviculture and Genetics of Forest Trees Forest Research Institute Sękocin Stary Poland University of Trás-os-Montes and Alto Douro Vila Real 5001-801 Portugal School of Agriculture University of Lisbon Tapada da Ajuda Lisboa1349-017 Portugal Faculty o

The relationship between the quality of forest seedlings and their outplanting survival and growth has long been recognized. Various attributes have been proposed to measure the quality of planted seedlings in forest regeneration projects, ranging from simple morphological traits to more complex physiological and performance attributes, or a combination thereof. However, the utility and meaning of seedling quality attributes can differ significantly among regions, nursery practices, site planting conditions, species and the establishment purpose. Here, we provide a comprehensive review of current practices, experiences, legislation and standards for seedling quality across *** differences exist in measuring seedling quality across countries. The control of the origin of seed and vegetative material (genetic component of plant quality), and control of pests and diseases are common practices in all countries. Morphological attributes are widely used and mandatory in most cases. However, physiological attributes are little used at the operative level and are mainly concentrated to Fennoscandia. Quality control legislation and seedling quality standards are less strict in northern European countries where seedling production is high, and quality control relies more on the agreements between producers and local plant material users. In contrast, quality standards are stricter in Southern Europe, especially in the Mediterranean *** control of seedling quality based on plantation and reforestation success is uncommon and depends on the conditions of the planting site, the traditional practices in and the financial support provided by each country. Overall, European countries do not apply the "target seedling concept" for seedling production except for seed origin. Seedling production in many countries is still driven by traditional "know-how" and much less by scientific knowledge progress, which is not adequately disseminated and transferred to the end-u

关键词： Quality control