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RISS 인기검색어
- 검색키워드
- 저자 : Lubitz (검색결과 6 건)
- 무료
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- 유료
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A neural network shelter model for small wind turbine siting near single obstacles
Brunskill, Andrew William,Lubitz, William David Techno-Press 2012 Wind and Structures, An International Journal (WAS Vol.15 No.1
Many potential small wind turbine locations are near obstacles such as buildings and shelterbelts, which can have a significant, detrimental effect on the local wind climate. A neural network-based model has been developed which predicts mean wind speed and turbulence intensity at points in an obstacle's region of influence, relative to unsheltered conditions. The neural network was trained using measurements collected in the wakes of 18 scale building models exposed to a simulated rural atmospheric boundary layer in a wind tunnel. The model obstacles covered a range of heights, widths, depths, and roof pitches typical of rural buildings. A field experiment was conducted using three unique full scale obstacles to validate model predictions and wind tunnel measurements. The accuracy of the neural network model varies with the quantity predicted and position in the obstacle wake. In general, predictions of mean velocity deficit in the far wake region are most accurate. The overall estimated mean uncertainties associated with model predictions of normalized mean wind speed and turbulence intensity are 4.9% and 12.8%, respectively.
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Energy and environment policy case for a global project on artificial photosynthesis
Faunce, Thomas A.,Lubitz, Wolfgang,Rutherford, A. W. (Bill),MacFarlane, Douglas,Moore, Gary F.,Yang, Peidong,Nocera, Daniel G.,Moore, Tom A.,Gregory, Duncan H.,Fukuzumi, Shunichi,Yoon, Kyung Byung,Arm The Royal Society of Chemistry 2013 Energy & environmental science Vol.6 No.3
<P>A policy case is made for a global project on artificial photosynthesis including its scientific justification, potential governance structure and funding mechanisms.</P> <P>Graphic Abstract</P><P>Lord Howe Island August 2011-site of the first International Conference on a Global Artificial Photosynthesis (GAP) Project <IMG SRC='http://pubs.rsc.org/services/images/RSCpubs.ePlatform.Service.FreeContent.ImageService.svc/ImageService/image/GA?id=c3ee00063j'> </P>
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A neural network shelter model for small wind turbine siting near single obstacles
Andrew William Brunskill,William David Lubitz 한국풍공학회 2012 Wind and Structures, An International Journal (WAS Vol.15 No.1
Many potential small wind turbine locations are near obstacles such as buildings and shelterbelts, which can have a significant, detrimental effect on the local wind climate. A neural networkbased model has been developed which predicts mean wind speed and turbulence intensity at points in an obstacle’s region of influence, relative to unsheltered conditions. The neural network was trained using measurements collected in the wakes of 18 scale building models exposed to a simulated rural atmospheric boundary layer in a wind tunnel. The model obstacles covered a range of heights, widths, depths, and roof pitches typical of rural buildings. A field experiment was conducted using three unique full scale obstacles to validate model predictions and wind tunnel measurements. The accuracy of the neural network model varies with the quantity predicted and position in the obstacle wake. In general, predictions of mean velocity deficit in the far wake region are most accurate. The overall estimated mean uncertainties associated with model predictions of normalized mean wind speed and turbulence intensity are 4.9% and 12.8%, respectively.
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Simulation of an Earth-Air Heat Exchanger in a Commercial Greenhouse to Improve Energy Efficiency
Nauta Alex,Tasnim Syeda Humaira,Lubitz William David 한국농업기계학회 2023 바이오시스템공학 Vol.48 No.3
Purpose Greenhouses in colder northern climates typically require significant supplemental heating for year-round operation, usually provided by natural gas combustion. One potential method of reducing greenhouse energy use is to incorporate an earth-air heat exchanger (EAHE) for seasonal heat storage; however, there is little guidance in the literature on the feasibility of this technology in cold-climate greenhouses. Methods This study uses simulations to examine the potential energy savings that could be achieved in cold-climate greenhouses by incorporating an EAHE system. A lumped parameter greenhouse energy model previously developed and tested against experimental data from several commercial and passive greenhouses was modified to simulate the addition of an EAHE in a commercial-scale lettuce greenhouse. The operation and energy use of this greenhouse was simulated at several locations across Canada. Crop evapotranspiration was included in the energy balance, and the greenhouse was assumed to deploy a thermal curtain at night. Results The EAHE sub-model was validated against experimental results available in the literature and was found to accurately predict the outlet air temperature of an EAHE. The predicted change in required supplemental heating with an operating EAHE varied from a 100% reduction in Victoria, BC, to a 13.3% reduction in Winnipeg, Manitoba. Conclusions EAHE use could reduce, or in a few locations with milder winters, even remove the need for supplemental heating at commercial-scale Canadian greenhouses.
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A Genetic Risk Score for Atrial Fibrillation Predicts the Response to Catheter Ablation
Won-Seok Choe,Jun Hyuk Kang,Eue-Keun Choi,Seung Yong Shin,Steven A. Lubitz,Patrick T. Ellinor,Seil Oh,Hong Euy Lim 대한심장학회 2019 Korean Circulation Journal Vol.49 No.4
Background and Objectives: The association of susceptibility loci for atrial fibrillation (AF) with AF recurrence after ablation has been reported, although with controversial results. In this prospective cohort analysis, we aimed to investigate whether a genetic risk score (GRS) can predict the rhythm outcomes after catheter ablation of AF. Methods: We determined the association between 20 AF-susceptible single nucleotide polymorphisms (SNPs) and AF recurrence after catheter ablation in 746 patients (74% males; age, 59±11 years; 56% paroxysmal AF). A GRS was calculated by summing the unweighted numbers of risk alleles of selected SNPs. A Cox proportional hazard model was used to identify the association between the GRS and risk of AF recurrence after catheter ablation. Results: AF recurrences after catheter ablation occurred in 168 (22.5%) subjects with a median follow-up of 23 months. The GRS was calculated using 5 SNPs (rs1448818, rs2200733, rs6843082, rs6838973 at chromosome 4q25 [PITX2] and rs2106261 at chromosome 16q22 [ZFHX3]), which showed modest associations with AF recurrence. The GRS was significantly associated with AF recurrence (hazard ratio [HR] per each score, 1.13; 95% confidence interval [CI], 1.03–1.24). Patients with intermediate (GRS 4–6) and high risks (GRS 7–10) showed HRs of 2.00 (95% CI, 0.99–4.04) and 2.66 (95% CI, 1.32–5.37), respectively, compared to patients with low risk (GRS 0–3). Conclusions: Our novel GRS using 5 AF-susceptible SNPs was strongly associated with AF recurrence after catheter ablation in Korean population, beyond clinical risk factors. Further efforts are warranted to construct a generalizable, robust genetic prediction model which can guide the optimal treatment strategies.
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