1,720,952 research outputs found
Update Offshore Wind Atlas: Implementing a variable sea surface roughness
No full textIn 2005 the Energy research Centre of the Netherlands (ECN) published its first version of the Offshore Wind Atlas of the Dutch part of the North Sea [3]. This version has been updated and improved using longer time series and another approach for the calculation of the roughness of the sea surface. In contradiction to other Wind Atlases which are based on measurements [28], use is made of data from the Numerical Weather Prediction model Hirlam. Measurements of wind speeds and directions are only used to validate the Wind Atlas. For the Offshore Wind Atlas, the Hirlam data is interpolated where for the vertically interpolation use is made of the Businger-Dyer profiles in combination with the Monin-Obukhov length [3]. One of the required parameters for the interpolation is the surface roughness. For land, it can be assumed constant while for sea it is variable. In the previous version of the Offshore Wind Atlas, the sea surface roughness has been determined using Charnock’s relation [9], where the so-called Charnock parameter is constant. In the new version, the equation of Hsu is introduced which states that the Charnock parameter is variable and dependent on the wave steepness i.e. the wave height divided by the wave length [19]. Assuming that the North Sea is a shallow sea and using the general wave equation, which relates the sea depth and wave length to the phase velocity of the waves, it was found that the wave steepness can be rewritten in a fraction of the wave height over the wave period multiplied by the square root of the sea depth times the gravitational acceleration. These quantities are derived from measured values which are interpolated to the location of interest. Using this approach, it is tried to improve the prediction of the wind speed distributions for a given location and altitude. Using wind measurements at several locations it was found that adding the wave data to the computations show a small improvement in the estimation of the wind speed distribution compared to the previous version of the Offshore Wind Atlas. For each measurement location and method, a two parameter Weibull distribution has been made, after which a comparison was done between the various shape and scale parameters. Generally, the scale parameter was overestimated by both versions of the Offshore Wind Atlas compared to the measurements. The cause of this behavior might be found in the data used to make the Atlas. The shape parameter is well predicted by the new version of the Offshore Wind Atlas due to the use of wave data. The influence of the wave data is found to be larger for lower altitudes than for higher altitudes. Besides Weibull distributions, also maps with average wind speeds are given by the Offshore Wind Atlas which are compared to older mapsAerospace Engineerin
Kinetics of the photoinduced dissociative electron transfer reduction of the antimalarial endoperoxide, Artemisinin
No full textThe rate constants (k) for reactions between a series of excited singlet state donors and the antimalarial agent, Artemisinin (ART), were measured in acetonitrile using fluorescence quenching techniques. A plot of log(k) correlates with the excited state oxidation potential of the donor, E-D(/D*).+, while a similar plot of log(k) versus the singlet energy of the donor, E-s, which if linear would indicate an energy transfer reaction process, shows a poor correlation. The results suggest that the determined rate constants are for dissociative electron transfer (ET) from the excited slate donor to the O-O bond in ART. Using our recently determined standard dissociative reduction potential for ART, E-diss(0), the rate constants are related to the free energy of ET, DeltaG(ET)(0). Analysis of the kinetic data as a function of DeltaG(ET)(0) correlates well with theories of ET modified for the non-adiabatic nature of the ET to peroxides. A number of thermochemical parameters are estimated from the analysis, in particular the intrinsic barrier (DeltaG(0)(not equal)) that is comprised of the solvent reorganization energy (lambda) and the bond dissociation enthalpy of the O-O bond. (C) 2001 Elsevier Science B.V. All rights reserved.PT: J; CR: ANDRIEUX CP, 1998, J AM CHEM SOC, V120, P4167 ANTONELLO S, 1997, J AM CHEM SOC, V119, P12595 ANTONELLO S, 1997, J AM CHEM SOC, V119, P9541 ANTONELLO S, 1999, J AM CHEM SOC, V121, P9668 BHISUTTHIBHAN J, 1998, J BIOL CHEM, V273, P16192 CHAN KL, 1997, PHYTOCHEMISTRY, V46, P1209 COSTENTIN C, 2000, J PHYS CHEM A, V104, P7492 DONKERS RL, UNPUB EUR J CHEM DONKERS RL, 1998, J PHYS CHEM B, V102, P4061 DONKERS RL, 1999, J AM CHEM SOC, V121, P7239 ENCINAS MV, 1982, J PHOTOCHEM, V20, P153 ENGEL PS, 1983, J PHYS CHEM-US, V87, P10 HAYNES RK, 1997, ACCOUNTS CHEM RES, V30, P73 INGOLD KU, 1984, CHEM PHYS LETT, V110, P433 ISSE AA, 1999, ACTA CHEM SCAND, V53, P1013 JIANG HL, 1997, INDIAN J CHEM B, V36, P154 KLAYMAN DL, 1985, SCIENCE, V228, P1049 KOJIMA H, 1975, J AM CHEM SOC, V97, P6317 MESHNICK SR, 1996, MICROBIOL REV, V60, P301 POSNER GH, 1998, J MED CHEM, V41, P940 POSNER GH, 1999, J MED CHEM, V42, P300 ROBERT A, 1998, CHEM SOC REV, V27, P273 ROBERT M, 2000, J AM CHEM SOC, V122, P514 SAVEANT JM, 1987, J AM CHEM SOC, V109, P6788 SAVEANT JM, 1990, ADV PHYS ORG CHEM, V26, P1 SAVEANT JM, 1992, J AM CHEM SOC, V114, P10595 SAVEANT JM, 1994, ADV ELECT T, V4, P53 SCAIANO JC, 1981, J AM CHEM SOC, V103, P640 STEWART LC, 1983, J AM CHEM SOC, V105, P3605 URANO T, 1984, J PHOTOCHEM, V26, P69 WAGNER PJ, 1989, HDB ORGANIC PHOTOCHE, V2, P251 WORKENTIN MS, 1998, J AM CHEM SOC, V120, P2664 WU WM, 1998, J AM CHEM SOC, V120, P3316 WU YK, 1999, ANGEW CHEM INT EDIT, V38, P2580 ZHANG F, 1992, BIOCHEM PHARMACOL, V43, P1805; NR: 35; TC: 10; J9: J PHOTOCHEM PHOTOBIOL A-CHEM; PG: 6; GA: 383HHSource type: Electronic(1
Update Offshore Wind Atlas: Implementing a variable sea surface roughness
No full textIn 2005 the Energy research Centre of the Netherlands (ECN) published its first version of the Offshore Wind Atlas of the Dutch part of the North Sea [3]. This version has been updated and improved using longer time series and another approach for the calculation of the roughness of the sea surface. In contradiction to other Wind Atlases which are based on measurements [28], use is made of data from the Numerical Weather Prediction model Hirlam. Measurements of wind speeds and directions are only used to validate the Wind Atlas. For the Offshore Wind Atlas, the Hirlam data is interpolated where for the vertically interpolation use is made of the Businger-Dyer profiles in combination with the Monin-Obukhov length [3]. One of the required parameters for the interpolation is the surface roughness. For land, it can be assumed constant while for sea it is variable. In the previous version of the Offshore Wind Atlas, the sea surface roughness has been determined using Charnock’s relation [9], where the so-called Charnock parameter is constant. In the new version, the equation of Hsu is introduced which states that the Charnock parameter is variable and dependent on the wave steepness i.e. the wave height divided by the wave length [19]. Assuming that the North Sea is a shallow sea and using the general wave equation, which relates the sea depth and wave length to the phase velocity of the waves, it was found that the wave steepness can be rewritten in a fraction of the wave height over the wave period multiplied by the square root of the sea depth times the gravitational acceleration. These quantities are derived from measured values which are interpolated to the location of interest. Using this approach, it is tried to improve the prediction of the wind speed distributions for a given location and altitude. Using wind measurements at several locations it was found that adding the wave data to the computations show a small improvement in the estimation of the wind speed distribution compared to the previous version of the Offshore Wind Atlas. For each measurement location and method, a two parameter Weibull distribution has been made, after which a comparison was done between the various shape and scale parameters. Generally, the scale parameter was overestimated by both versions of the Offshore Wind Atlas compared to the measurements. The cause of this behavior might be found in the data used to make the Atlas. The shape parameter is well predicted by the new version of the Offshore Wind Atlas due to the use of wave data. The influence of the wave data is found to be larger for lower altitudes than for higher altitudes. Besides Weibull distributions, also maps with average wind speeds are given by the Offshore Wind Atlas which are compared to older maps.Aerospace Engineerin
Model dialkyl peroxides of the Fenton mechanistic probe 2-methyl-1-phenyl-2-propyl hydroperoxide (MPPH): kinetic probes for dissociative electron transfer
No full textTwo dialkyl peroxides, devised as kinetic probes for the heterogeneous electron transfer (ET), are studied using heterogeneous and homogeneous electrochemical techniques. The peroxides react by concerted dissociative ET reduction of the O-O bond. Under heterogeneous conditions, the only products isolated are the corresponding alcohols from a two-electron reduction as has been observed with other dialkyl peroxides studied to date. However, under homogeneous conditions, a generated alkoxyl radical undergoes a rapid beta-scission fragmentation in competition with the second ET resulting in formation of acetone and a benzyl radical. With knowledge of the rate constant for fragmentation and accounting for the diffuse double layer at the electrode interface, the heterogeneous ET rate constant to the alkoxyl radicals is estimated to be 1500 cm s(-1). The heterogeneous and homogeneous ET kinetics of the O-O bond cleavage have also been measured and examined as a function of the driving force for ET, DeltaG(ET), using dissociative electron transfer theory. From both sets of kinetics, besides the evaluation of thermochemical parameters, it is demonstrated that the heterogeneous and homogeneous reduction of the O-O bond appears to be non-adiabatic.PT: J; CR: *NIST, 2003, NIST STAND REF DAT P ANDO W, 1992, ORGANIC PEROXIDES ANDRIEUX CP, 1978, J ELECTROANAL CHEM, V87, P39 ANDRIEUX CP, 1980, J ELECTROANAL CHEM, V113, P19 ANDRIEUX CP, 1992, J AM CHEM SOC, V114, P6892 ANTONELLO S, 1997, J AM CHEM SOC, V119, P12595 ANTONELLO S, 1997, J AM CHEM SOC, V119, P9541 ANTONELLO S, 1999, J AM CHEM SOC, V121, P9668 ANTONELLO S, 2001, J AM CHEM SOC, V123, P9577 ANTONELLO S, 2002, J AM CHEM SOC, V124, P11503 ANTONELLO S, 2003, J AM CHEM SOC, V125, P2874 ARENDS IWCE, 1995, J AM CHEM SOC, V117, P4710 BARD AJ, 2001, ELECTROCHEMICAL METH BARTON DHR, 1992, ACCOUNTS CHEM RES, V25, P504 BARTON DHR, 1994, TETRAHEDRON, V50, P19 BARTON DHR, 1996, CHEM SOC REV, V25, P237 BARTON DHR, 1996, SYNLETT, P229 BENSON SW, 1976, THERMOCHEMCIAL KINET CARDINALE A, 2002, ELECTROCHEM COMMUN, V4, P767 CASTEEL DA, 1992, NAT PROD REP, V9, P289 CASTEEL DA, 1999, NAT PROD REP, V16, P55 CHEN K, 1999, CHEM COMMUN, P1375 CHEN K, 2001, J AM CHEM SOC, V123, P6327 CHEN K, 2002, J CHEM SOC DA, V5, P672 COOKSON PG, 1976, J CHEM SOC CHEM COMM, P1022 DAASBJERG K, 1991, ACTA CHEM SCAND, V45, P424 DAASBJERG K, 1993, ACTA CHEM SCAND, V47, P398 DAASBJERG K, 1999, GEN ASPECTS CHEM RAD, P385 DEMONTELLANO PRO, 1995, CYTOCHROME P450 STRU DONKERS RL, 1998, J PHYS CHEM B, V102, P4061 DONKERS RL, 1999, CHEM COMMUN 0121, P135 DONKERS RL, 1999, J AM CHEM SOC, V121, P7239 DONKERS RL, 2001, CHEM-EUR J, V7, P4012 FUHLENDORFF R, 1989, ACTA CHEM SCAND, V43, P803 GROVES JT, 1985, J CHEM EDUC, V62, P928 GROVES JT, 1995, CYTOCHROME P450 STRU, P3 HAGHBEEN K, 1998, J ORG CHEM, V63, P4503 HAPIOT P, 1995, J AM CHEM SOC, V117, P1428 HIATT RR, 1963, J ORG CHEM, V28, P1893 HORNING EC, 1955, SYNTHESIS AZOBENZENE, V3, P103 HOWARD JA, 1997, RADICAL REACTION RAT, V18 HU Z, 2000, BIOMIMETIC OXIDATION, P269 IMBEAUX JC, 1973, J ELECTROANAL CHEM, V44, P169 INGOLD KU, 2000, BIOMIMETIC OXIDATION, P45 JENSEN MP, 2003, J AM CHEM SOC, V125, P2113 KELLNER DG, 2002, J BIOL CHEM, V277, P9641 KIM J, 1996, J AM CHEM SOC, V118, P4373 KJAER NT, 1995, ACTA CHEM SCAND, V49, P848 KOJIMA H, 1975, J AM CHEM SOC, V97, P6317 KOJIMA T, 1993, J AM CHEM SOC, V115, P11328 LANGE SJ, 1999, J AM CHEM SOC, V121, P6330 LEISING RA, 1990, INORG CHEM, V29, P2553 LEISING RA, 1991, J AM CHEM SOC, V113, P8555 LEISING RA, 1993, J AM CHEM SOC, V115, P9524 LUND H, 1997, ACTA CHEM SCAND, V51, P135 LUND T, 1987, ACTA CHEM SCAND B, V41, P93 LUND T, 2003, ORG BIOMOL CHEM, V1, P1020 MACFAUL PA, 1997, J AM CHEM SOC, V119, P10594 MACFAUL PA, 1997, J CHEM SOC PERK FEB, P135 MACFAUL PA, 1998, ACCOUNTS CHEM RES, V31, P159 MAGRI DC, 2001, J PHOTOCH PHOTOBIO A, V138, P29 MARAN F, 2001, ADV PHYS ORG CHEM, V36, P85 MARCUS RA, 1985, BIOCHIM BIOPHYS ACTA, V811, P265 MASADA H, 1980, B CHEM SOC JPN, V53, P1181 MCLAIN JL, 2000, BIOMIMETIC OXIDATION, P91 MEUNIER B, 2000, BIOMIMETIC OXIDATION, P171 MIYAKE H, 2001, INORG CHEM, V40, P3534 NADJO L, 1985, J ELECTROANAL CH INF, V196, P23 NEIMANN K, 1999, INORG CHEM, V38, P3575 OCCHIALINI D, 1990, ACTA CHEM SCAND, V44, P715 OCCHIALINI D, 1992, ACTA CHEM SCAND, V46, P474 OCCHIALINI D, 1993, ACTA CHEM SCAND, V47, P1100 PEDERSEN SU, 1989, ACTA CHEM SCAND, V43, P301 PEDERSEN SU, 1991, ACTA CHEM SCAND, V45, P397 PEDERSEN SU, 1998, ACTA CHEM SCAND, V52, P657 PERKINS MJ, 1996, CHEM SOC REV, V25, P229 PERRIN CL, 2000, J AM CHEM SOC, V122, P4569 RABION A, 1995, J AM CHEM SOC, V117, P12356 ROHDE JU, 2003, SCIENCE, V299, P1037 ROSENZWEIG AC, 1994, ACCOUNTS CHEM RES, V27, P229 SAVEANT JM, 1975, J ELECTROANAL CHEM, V61, P251 SAVEANT JM, 1985, J ELECTROANAL CH INF, V196, P1 SAVEANT JM, 1993, ACCOUNTS CHEM RES, V26, P455 SAVEANT JM, 1994, ADV ELECT T, V4, P53 SAVEANT JM, 2000, ADV PHYS ORG CHEM, V35, P117 SAVEANT JM, 2002, J PHYS CHEM B, V106, P9387 SAWYER DT, 1996, ACCOUNTS CHEM RES, V29, P409 SCHLICHTING I, 2000, SCIENCE, V287, P1615 SNELGROVE DW, 1996, TETRAHEDRON LETT, V37, P823 SONO M, 1996, CHEM REV, V96, P2841 STRINGLE DLB, 2003, CHEM COMMUN, P1246 WALLING C, 1975, ACCOUNTS CHEM RES, V8, P125 WALLING C, 1998, ACCOUNTS CHEM RES, V31, P155 WAYNER DDM, 1988, J AM CHEM SOC, V110, P132 WAYNER DDM, 1993, ACCOUNTS CHEM RES, V26, P287 WORKENTIN MS, 1995, J AM CHEM SOC, V117, P2120 WORKENTIN MS, 1998, J AM CHEM SOC, V120, P2664 ZANG Y, 1997, J AM CHEM SOC, V119, P4197; NR: 98; TC: 4; J9: ORG BIOMOL CHEM; PG: 12; GA: 725MRSource type: Electronic(1
Automatic generation of CityGML LoD3 building models from IFC models
No full textCityGML is a standardized data format used to store the semantic information and geometries of buildings and other object classes of 3D city models. The Level of Detail of current state of the art city models (LoD2) is not sufficient for accurate environmental simulations like noise, the solar potential of windows and other types of analyses. An LoD3 building model represents the full architectural exterior of a building with balconies, windows and so forth. The generation of these models needs to be automated as it is otherwise infeasible due to the required high amount of manual labour. In the architectural world, detailed building models are created in IFC format. This thesis shows that it is possible to automatically generate valid and semantically rich CityGML LoD3 building models directly from IFC models. Also an initial investigation is done on the possibilities for the conversion of IFC models to CityGML LoD4. For the conversion the semantic and geometric validity requirements are determined for CityGML. A methodology for the conversion is developed and a prototype implementation is made to prove the effectiveness of the conversion. The conversion consists of three parts: 1) The extraction and mapping of IFC semantics to CityGML semantics; 2) A geometric generalization which extracts the exterior shell using a transformation based on Boolean and morphological operations; 3) Semantic and geometric refinements which optimize the model for analyses. The developed prototype is able to successfully convert IFC models to CityGML LoD3. All the resulting models were geometrically validated according to the ISO19107 standard, and semantics were checked manually. Few improper semantics occur in the output due to missing semantics in IFC. For example, there are no semantics for balconies or dormers in IFC. Recommendations are given to improve the alignment between the two formats. For IFC additional semantics are recommended whereas it is important for CityGML to specify how certain aspects are to be modelled. The research presented in this thesis can be used as the foundation for future work on the interoperability between Architecture and Geomatics. The software package is open source and freely available at https://github.com/tudelft-gist/ifc2citygml.GeomaticsGIS technologyOTB Research Institute for the Built Environmen
Requirements Management within Grontmij Randstad Techniek: How to improve the Requirements Management Process Quality within Grontmij Randstad Techniek
No full textGrontmij is an international Design and Engineering company, active in the areas of, among others, Civil Engineering, Mobility, Industry and Energy. One of the organisational units in The Netherlands is Planning and Design - Stedelijk Gebied Randstad - Team Techniek, abbreviated as Grontmij Randstad Techniek. Within Grontmij Randstad Techniek there are two problem owners: the Grontmij Randstad Techniek Management and the Design and Implementation (D&l) team. These problem owners want to improve the quality of the Grontmij Randstad Techniek products in projects. 'Product Quality' is defined as: the products of Grontmij Randstad Techniek should meet the customer and stakeholder requirements.TILTransport, Infrastructure and LogisticsDelft University of Technolog
Slimme exploitatiestrategie voor bodemenergie bij hoge grondwaterstroomsnelheid
No full textGrondwaterstroming is een probleem bij de open winning van bodemenergie met warmte-koudeopslag. Hierdoor kunnen warm en koud water wegstromen van de bronnen. Bij systemen met meerdere warme en koude bronnen is hier iets aan te doen. Tauw bv en Universiteit Utrecht ontwikkelden een nieuw beheermodel.Water ManagemnetCivil Engineering and Geoscience
Automatic conversion of IFC datasets to geometrically and semantically correct CityGML LOD3 buildings
No full textAlthough the international standard CityGML has five levels of detail (LODs), the vast majority of available models are the coarse ones (up to LOD2, i.e. block-shaped buildings with roofs). LOD3 and LOD4 models, which contain architectural details such as balconies, windows and rooms, rarely exist because, unlike coarser LODs, their construction requires several datasets that must be acquired with different technologies, and often extensive manual work is needed. In this article we investigate an alternative to obtaining CityGML LOD3 models: the automatic conversion from already existing architectural models (stored in the IFC format). Existing conversion algorithms mostly focus on the semantic mappings and convert all the geometries, which yields CityGML models having poor usability in practice (spatial analysis, for instance, is not possible). We present a conversion algorithm that accurately applies the correct semantics from IFC models and that constructs valid CityGML LOD3 buildings by performing a series of geometric operations in 3D. We have implemented our algorithm and we demonstrate its effectiveness with several real-world datasets. We also propose specific improvements to both standards to foster their integration in the future
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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