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Rydén, Jesperorcid.org/0000-0002-5451-4563

Open this publication in new window or tab >>Accuracy and precision of 3 intraoral scanners and accuracy of conventional impressions: A novel in vivo analysis method### Nedelcu, Robert

### Olsson, Pontus

### Nyström, Ingela

### Rydén, Jesper

PrimeFaces.cw("AccordionPanel","widget_formSmash_j_idt184_0_j_idt188_some",{id:"formSmash:j_idt184:0:j_idt188:some",widgetVar:"widget_formSmash_j_idt184_0_j_idt188_some",multiple:true}); ### Thor, Andreas

PrimeFaces.cw("AccordionPanel","widget_formSmash_j_idt184_0_j_idt188_otherAuthors",{id:"formSmash:j_idt184:0:j_idt188:otherAuthors",widgetVar:"widget_formSmash_j_idt184_0_j_idt188_otherAuthors",multiple:true}); Show others...PrimeFaces.cw("SelectBooleanButton","widget_formSmash_j_idt184_0_j_idt188_j_idt202",{id:"formSmash:j_idt184:0:j_idt188:j_idt202",widgetVar:"widget_formSmash_j_idt184_0_j_idt188_j_idt202",onLabel:"Hide others...",offLabel:"Show others..."}); 2018 (English)In: Journal of Dentistry, ISSN 0300-5712, E-ISSN 1879-176X, Vol. 69, p. 110-118Article in journal (Refereed) Published
##### Abstract [en]

##### Place, publisher, year, edition, pages

ELSEVIER SCI LTD, 2018
##### Keywords

Digital impression, Intraoral scanner, Polyether impression, Accuracy, Precision, In vivo
##### National Category

Dentistry
##### Identifiers

urn:nbn:se:uu:diva-349829 (URN)10.1016/j.jdent.2017.12.006 (DOI)000425888000014 ()29246490 (PubMedID)
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Available from: 2018-05-07 Created: 2018-05-07 Last updated: 2018-05-07Bibliographically approved

Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Oral and Maxillofacial Surgery.

Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.

Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala Univ, Dept Informat Technol, Ctr Image Anal, Box 337, S-75105 Uppsala, Sweden..

Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Mathematics, Applied Mathematics and Statistics.

Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Oral and Maxillofacial Surgery.

Objective: To evaluate a novel methodology using industrial scanners as a reference, and assess in vivo accuracy of 3 intraoral scanners (IOS) and conventional impressions. Further, to evaluate IOS precision in vivo.

Methods: Four reference-bodies were bonded to the buccal surfaces of upper premolars and incisors in five subjects. After three reference-scans, ATOS Core 80 (ATOS), subjects were scanned three times with three IOS systems: 3M True Definition (3M), CEREC Omnicam (OMNI) and Trios 3 (TRIOS). One conventional impression (IMPR) was taken, 3M Impregum Penta Soft, and poured models were digitized with laboratory scanner 3shape D1000 (D1000). Best-fit alignment of reference-bodies and 3D Compare Analysis was performed. Precision of ATOS and D1000 was assessed for quantitative evaluation and comparison. Accuracy of IOS and IMPR were analyzed using ATOS as reference. Precision of IOS was evaluated through intra-system comparison.

Results: Precision of ATOS reference scanner (mean 0.6 mu m) and D1000 (mean 0.5 mu m) was high. Pairwise multiple comparisons of reference-bodies located in different tooth positions displayed a statistically significant difference of accuracy between two scanner-groups: 3M and TRIOS, over OMNI (p value range 0.0001 to 0.0006). IMPR did not show any statistically significant difference to IOS. However, deviations of IOS and IMPR were within a similar magnitude. No statistical difference was found for IOS precision.

Conclusion: The methodology can be used for assessing accuracy of IOS and IMPR in vivo in up to five units bilaterally from midline. 3M and TRIOS had a higher accuracy than OMNI. IMPR overlapped both groups. Clinical significance: Intraoral scanners can be used as a replacement for conventional impressions when restoring up to ten units without extended edentulous spans.

Open this publication in new window or tab >>Combining Total Monte Carlo and Unified Monte Carlo: Bayesian nuclear data uncertainty quantification from auto-generated experimental covariances### Helgesson, Petter

### Sjöstrand, Henrik

### Arjan, J. Koning

### Rydén, Jesper

PrimeFaces.cw("AccordionPanel","widget_formSmash_j_idt184_1_j_idt188_some",{id:"formSmash:j_idt184:1:j_idt188:some",widgetVar:"widget_formSmash_j_idt184_1_j_idt188_some",multiple:true}); ### Rochman, Dimitri

### Alhassan, Erwin

### Pomp, Stephan

PrimeFaces.cw("AccordionPanel","widget_formSmash_j_idt184_1_j_idt188_otherAuthors",{id:"formSmash:j_idt184:1:j_idt188:otherAuthors",widgetVar:"widget_formSmash_j_idt184_1_j_idt188_otherAuthors",multiple:true}); Show others...PrimeFaces.cw("SelectBooleanButton","widget_formSmash_j_idt184_1_j_idt188_j_idt202",{id:"formSmash:j_idt184:1:j_idt188:j_idt202",widgetVar:"widget_formSmash_j_idt184_1_j_idt188_j_idt202",onLabel:"Hide others...",offLabel:"Show others..."}); 2017 (English)In: Progress in nuclear energy (New series), ISSN 0149-1970, E-ISSN 1878-4224, Vol. 96, p. 76-96Article in journal (Refereed) Published
##### Abstract [en]

##### Place, publisher, year, edition, pages

Elsevier, 2017
##### Keywords

Nuclear data, Uncertainty propagation, Total Monte Carlo, Experimental correlations, Unified Monte Carlo
##### National Category

Subatomic Physics
##### Identifiers

urn:nbn:se:uu:diva-313644 (URN)10.1016/j.pnucene.2016.11.006 (DOI)000392676800007 ()
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Available from: 2017-01-23 Created: 2017-01-23 Last updated: 2018-04-16Bibliographically approved

Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics. Nucl Res & Consultancy Grp NRG, Petten, Netherlands.

Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.

Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics. Nucl Res & Consultancy Grp NRG, Petten, Netherlands.

Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Mathematics, Applied Mathematics and Statistics.

PSI, Villigen, Switzerland.

Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.

Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.

The Total Monte Carlo methodology (TMC) for nuclear data (ND) uncertainty propagation has been subject to some critique because the nuclear reaction parameters are sampled from distributions which have not been rigorously determined from experimental data. In this study, it is thoroughly explained how TMC and Unified Monte Carlo-B (UMC-B) are combined to include experimental data in TMC. Random ND files are weighted with likelihood function values computed by comparing the ND files to experimental data, using experimental covariance matrices generated from information in the experimental database EXFOR and a set of simple rules. A proof that such weights give a consistent implementation of Bayes' theorem is provided. The impact of the weights is mainly studied for a set of integral systems/applications, *e.g.*, a set of shielding fuel assemblies which shall prevent aging of the pressure vessels of the Swedish nuclear reactors Ringhals 3 and 4.

In this implementation, the impact from the weighting is small for many of the applications. In some cases, this can be explained by the fact that the distributions used as priors are too narrow to be valid as such. Another possible explanation is that the integral systems are highly sensitive to resonance parameters, which effectively are not treated in this work. In other cases, only a very small number of files get significantly large weights, *i.e.*, the region of interest is poorly resolved. This convergence issue can be due to the parameter distributions used as priors or model defects, for example.

Further, some parameters used in the rules for the EXFOR interpretation have been varied. The observed impact from varying one parameter at a time is not very strong. This can partially be due to the general insensitivity to the weights seen for many applications, and there can be strong interaction effects. The automatic treatment of outliers has a quite large impact, however.

To approach more justified ND uncertainties, the rules for the EXFOR interpretation shall be further discussed and developed, in particular the rules for rejecting outliers, and random ND files that are intended to describe prior distributions shall be generated. Further, model defects need to be treated.

Open this publication in new window or tab >>Polynomial probability distribution estimation using the method of moments### Munkhammar, Joakim

### Mattsson, Lars

### Rydén, Jesper

PrimeFaces.cw("AccordionPanel","widget_formSmash_j_idt184_2_j_idt188_some",{id:"formSmash:j_idt184:2:j_idt188:some",widgetVar:"widget_formSmash_j_idt184_2_j_idt188_some",multiple:true}); PrimeFaces.cw("AccordionPanel","widget_formSmash_j_idt184_2_j_idt188_otherAuthors",{id:"formSmash:j_idt184:2:j_idt188:otherAuthors",widgetVar:"widget_formSmash_j_idt184_2_j_idt188_otherAuthors",multiple:true}); 2017 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 12, no 4, p. 1-14, article id e0174573Article in journal (Refereed) Published
##### Abstract [en]

##### National Category

Probability Theory and Statistics Engineering and Technology
##### Identifiers

urn:nbn:se:uu:diva-319998 (URN)10.1371/journal.pone.0174573 (DOI)000399954800004 ()28394949 (PubMedID)
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##### Funder

Swedish Energy AgencySwedish Research Council, 2015-04505
Available from: 2017-04-12 Created: 2017-04-12 Last updated: 2017-11-29Bibliographically approved

Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Solid State Physics.

Nordita, Stockholms University.

Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Mathematics, Applied Mathematics and Statistics.

We suggest a procedure for estimating *N*th degree polynomial approximations to unknown (or known) probability density functions (PDFs) based on *N* statistical moments from each distribution. The procedure is based on the method of moments and is setup algorithmically to aid applicability and to ensure rigor in use. In order to show applicability, polynomial PDF approximations are obtained for the distribution families Normal, Log-Normal, Weibull as well as for a bimodal Weibull distribution and a data set of anonymized household electricity use. The results are compared with results for traditional PDF series expansion methods of Gram–Charlier type. It is concluded that this procedure is a comparatively simple procedure that could be used when traditional distribution families are not applicable or when polynomial expansions of probability distributions might be considered useful approximations. In particular this approach is practical for calculating convolutions of distributions, since such operations become integrals of polynomial expressions. Finally, in order to show an advanced applicability of the method, it is shown to be useful for approximating solutions to the Smoluchowski equation.

Open this publication in new window or tab >>Simulating intra-hourly wind power ﬂuctuations on a power system level### Olauson, Jon

### Bergkvist, Mikael

### Rydén, Jesper

Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Mathematics, Applied Mathematics and Statistics.PrimeFaces.cw("AccordionPanel","widget_formSmash_j_idt184_3_j_idt188_some",{id:"formSmash:j_idt184:3:j_idt188:some",widgetVar:"widget_formSmash_j_idt184_3_j_idt188_some",multiple:true}); PrimeFaces.cw("AccordionPanel","widget_formSmash_j_idt184_3_j_idt188_otherAuthors",{id:"formSmash:j_idt184:3:j_idt188:otherAuthors",widgetVar:"widget_formSmash_j_idt184_3_j_idt188_otherAuthors",multiple:true}); 2017 (English)In: Wind Energy, ISSN 1095-4244, E-ISSN 1099-1824, Vol. 20, no 6, p. 973-985Article in journal (Refereed) Published
##### Abstract [en]

##### Keywords

Wind power, Sub-hourly ﬂuctuations, Simulation, FFT, Power system studies
##### National Category

Electrical Engineering, Electronic Engineering, Information Engineering
##### Identifiers

urn:nbn:se:uu:diva-302826 (URN)10.1002/we.2074 (DOI)000400860700003 ()
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##### Funder

Swedish Civil Contingencies Agency, 2010-2787
Available from: 2016-09-10 Created: 2016-09-10 Last updated: 2017-07-07Bibliographically approved

Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Electricity.

Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Electricity.

In wind integration studies, sub-hourly, load synchronous wind data are often preferable. These datasets can be generatedby a hybrid approach, combining hourly measurements or output from meteorological models with a stochastic simulationof the high-frequency ﬂuctuations. This paper presents a method for simulating aggregated intra-hourly wind power ﬂuc-tuations for a power system, taking into account the time-varying volatility seen in measurements. Some key elements inthe modelling were transformations to stationarity, the use of frequency domain techniques including a search for appropri-ate phase angles and an adjustment of the resulting time series in order to get correct hourly means. Generation data fromDenmark and Germany with 5 and 15 min temporal resolution were used for training models. It is shown that the distribu-tion and non-stationarity of simulated deviations from hourly means closely follow those of measurements. Power spectraldensities and step change distributions agree well. Of particular importance is that the results are good also when the train-ing and objective power systems are not the same. The computational cost is low in comparison with other approaches forgenerating high-frequency data.

Open this publication in new window or tab >>Statistical modelling of warm-spell duration series using hurdle models### Rydén, Jesper

Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Mathematics, Applied Mathematics and Statistics.PrimeFaces.cw("AccordionPanel","widget_formSmash_j_idt184_4_j_idt188_some",{id:"formSmash:j_idt184:4:j_idt188:some",widgetVar:"widget_formSmash_j_idt184_4_j_idt188_some",multiple:true}); PrimeFaces.cw("AccordionPanel","widget_formSmash_j_idt184_4_j_idt188_otherAuthors",{id:"formSmash:j_idt184:4:j_idt188:otherAuthors",widgetVar:"widget_formSmash_j_idt184_4_j_idt188_otherAuthors",multiple:true}); 2017 (English)In: SORT - Statistics and Operations Research Transactions, ISSN 1696-2281, Vol. 41, no 1, p. 177-188Article in journal (Refereed) Published
##### Abstract [en]

##### National Category

Probability Theory and Statistics
##### Research subject

Statistics
##### Identifiers

urn:nbn:se:uu:diva-326703 (URN)10.2436/20.8080.02.57 (DOI)000407307600009 ()
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Available from: 2017-07-25 Created: 2017-07-25 Last updated: 2017-11-16Bibliographically approved

Regression models for counts could be applied to the earth sciences, for instance when studying trends of extremes of climatological quantities. Hurdle models are modified count models which can be regarded as mixtures of distributions. In this paper, hurdle models are applied to model the sums of lengths of periods of high temperatures. A modification to the common versions presented in the literature is presented, as left truncation as well as a particular treatment of zeros is needed for the problem. The outcome of the model is compared to those of simpler count models.

Open this publication in new window or tab >>Statistical studies of the Beta Gumbel distribution: estimation of extreme levels of precipitation### Jonsson, Fredrik

### Rydén, Jesper

Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Mathematics, Applied Mathematics and Statistics.PrimeFaces.cw("AccordionPanel","widget_formSmash_j_idt184_5_j_idt188_some",{id:"formSmash:j_idt184:5:j_idt188:some",widgetVar:"widget_formSmash_j_idt184_5_j_idt188_some",multiple:true}); PrimeFaces.cw("AccordionPanel","widget_formSmash_j_idt184_5_j_idt188_otherAuthors",{id:"formSmash:j_idt184:5:j_idt188:otherAuthors",widgetVar:"widget_formSmash_j_idt184_5_j_idt188_otherAuthors",multiple:true}); 2017 (English)In: Statistica Applicata, Vol. 29, p. 5-27Article in journal (Refereed) Published
##### National Category

Probability Theory and Statistics
##### Research subject

Mathematical Statistics
##### Identifiers

urn:nbn:se:uu:diva-326702 (URN)
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Available from: 2017-07-25 Created: 2017-07-25 Last updated: 2017-07-31Bibliographically approved

Open this publication in new window or tab >>Wind turbine performance decline in Sweden### Olauson, Jon

### Edström, Per

### Rydén, Jesper

Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Mathematics, Applied Mathematics and Statistics.PrimeFaces.cw("AccordionPanel","widget_formSmash_j_idt184_6_j_idt188_some",{id:"formSmash:j_idt184:6:j_idt188:some",widgetVar:"widget_formSmash_j_idt184_6_j_idt188_some",multiple:true}); PrimeFaces.cw("AccordionPanel","widget_formSmash_j_idt184_6_j_idt188_otherAuthors",{id:"formSmash:j_idt184:6:j_idt188:otherAuthors",widgetVar:"widget_formSmash_j_idt184_6_j_idt188_otherAuthors",multiple:true}); 2017 (English)In: Wind Energy, ISSN 1095-4244, E-ISSN 1099-1824, Vol. 20, no 12, p. 2049-2053Article in journal (Refereed) Published
##### Abstract [en]

##### National Category

Energy Systems
##### Identifiers

urn:nbn:se:uu:diva-327406 (URN)10.1002/we.2132 (DOI)000417631900011 ()
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Available from: 2017-08-10 Created: 2017-08-10 Last updated: 2018-03-07Bibliographically approved

Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Electricity.

Sweco.

We show that Swedish wind turbines constructed before 2007 lose 0.15 capacity factor percentage points per year, corresponding to a lifetime energy loss of 6%. A gradual increase of downtime accounts for around one third of the deterioration and worsened efficiency for the remaining. Although the performance loss in Sweden is considerably smaller than previously reported in the UK, it is statistically significant and calls for a revision of the industry practice for wind energy calculations. The study is based on two partly overlapping datasets, comprising 1,100 monthly and 1,300 hourly time series spanning 5–25 years each.

Open this publication in new window or tab >>Sampling of systematic errors to estimate likelihood weights in nuclear data uncertainty propagation### Helgesson, Petter

Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.### Sjöstrand, Henrik

Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.### J. Koning, Arjan

### Rydén, Jesper

Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Mathematics, Applied Mathematics and Statistics.PrimeFaces.cw("AccordionPanel","widget_formSmash_j_idt184_7_j_idt188_some",{id:"formSmash:j_idt184:7:j_idt188:some",widgetVar:"widget_formSmash_j_idt184_7_j_idt188_some",multiple:true}); ### Rochman, Dimitri

### Alhassan, Erwin

Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.### Pomp, Stephan

Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.PrimeFaces.cw("AccordionPanel","widget_formSmash_j_idt184_7_j_idt188_otherAuthors",{id:"formSmash:j_idt184:7:j_idt188:otherAuthors",widgetVar:"widget_formSmash_j_idt184_7_j_idt188_otherAuthors",multiple:true}); Show others...PrimeFaces.cw("SelectBooleanButton","widget_formSmash_j_idt184_7_j_idt188_j_idt202",{id:"formSmash:j_idt184:7:j_idt188:j_idt202",widgetVar:"widget_formSmash_j_idt184_7_j_idt188_j_idt202",onLabel:"Hide others...",offLabel:"Show others..."}); 2016 (English)In: Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, ISSN 0168-9002, E-ISSN 1872-9576, Vol. 807, p. 137-149Article in journal (Refereed) Published
##### Abstract [en]

##### Place, publisher, year, edition, pages

Elsevier, 2016
##### Keywords

Nuclear data, Uncertainty propagation, Experimental correlations, Systematic uncertainty, Total Monte Carlo
##### National Category

Physical Sciences
##### Research subject

Physics with specialization in Applied Nuclear Physics
##### Identifiers

urn:nbn:se:uu:diva-265321 (URN)10.1016/j.nima.2015.10.024 (DOI)000365596200019 ()
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Available from: 2015-10-27 Created: 2015-10-27 Last updated: 2018-04-16

Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics. IAEA.

Paul Scherrer Institute PSI, Villigen, Switzerland.

In methodologies for nuclear data (ND) uncertainty assessment and propagation based on random sampling, likelihood weights can be used to infer experimental information into the distributions for the ND. As the included number of correlated experimental points grows large, the computational time for the matrix inversion involved in obtaining the likelihood can become a practical problem. There are also other problems related to the conventional computation of the likelihood, e.g., the assumption that all experimental uncertainties are Gaussian. In this study, a way to estimate the likelihood which avoids matrix inversion is investigated; instead, the experimental correlations are included by sampling of systematic errors. It is shown that the model underlying the sampling methodology (using univariate normal distributions for random and systematic errors) implies a multivariate Gaussian for the experimental points (i.e., the conventional model). It is also shown that the likelihood estimates obtained through sampling of systematic errors approach the likelihood obtained with matrix inversion as the sample size for the systematic errors grows large. In studied practical cases, it is seen that the estimates for the likelihood weights converge impractically slowly with the sample size, compared to matrix inversion. The computational time is estimated to be greater than for matrix inversion in cases with more experimental points, too. Hence, the sampling of systematic errors has little potential to compete with matrix inversion in cases where the latter is applicable. Nevertheless, the underlying model and the likelihood estimates can be easier to intuitively interpret than the conventional model and the likelihood function involving the inverted covariance matrix. Therefore, this work can both have pedagogical value and be used to help motivating the conventional assumption of a multivariate Gaussian for experimental data. The sampling of systematic errors could also be used in cases where the experimental uncertainties are not Gaussian, and for other purposes than to compute the likelihood, e.g., to produce random experimental data sets for a more direct use in ND evaluation.

Open this publication in new window or tab >>A Statistical Analysis of Trends for Warm and Cold Spells in Uppsala by Means of Counts### Ryden, Jesper

Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Mathematics, Applied Mathematics and Statistics.PrimeFaces.cw("AccordionPanel","widget_formSmash_j_idt184_8_j_idt188_some",{id:"formSmash:j_idt184:8:j_idt188:some",widgetVar:"widget_formSmash_j_idt184_8_j_idt188_some",multiple:true}); PrimeFaces.cw("AccordionPanel","widget_formSmash_j_idt184_8_j_idt188_otherAuthors",{id:"formSmash:j_idt184:8:j_idt188:otherAuthors",widgetVar:"widget_formSmash_j_idt184_8_j_idt188_otherAuthors",multiple:true}); 2015 (English)In: Geografiska Annaler. Series A, Physical Geography, ISSN 0435-3676, E-ISSN 1468-0459, Vol. 97, no 3, p. 431-436Article in journal (Refereed) Published
##### Abstract [en]

##### Keywords

warm spell, cold spell, trend, Poisson regression
##### National Category

Mathematics
##### Identifiers

urn:nbn:se:uu:diva-264064 (URN)10.1111/geoa.12083 (DOI)000361234200001 ()
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Available from: 2015-10-05 Created: 2015-10-05 Last updated: 2017-12-01Bibliographically approved

Statistical studies of extremes are of interest in the climatic sciences, in particular trends of periods of unusually warm or cold weather, which could be labelled warm and cold spells, respectively. We study the yearly number of spells in Uppsala, Sweden which from a data-analytic point of view truly are counts, and employ theory and methods from the field of regression models for counts. A possible trend for the period 1840-2012 was investigated. The trend for warm spells is positive and demonstrated to be larger in magnitude compared with the one for cold spells, and is found to be statistically significant. The methodology could be extended to analyse other climate indicators.

Open this publication in new window or tab >>Is a White Christmas becoming rarer in southern parts of Sweden?### Rydén, Jesper

Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Mathematics, Applied Mathematics and Statistics.PrimeFaces.cw("AccordionPanel","widget_formSmash_j_idt184_9_j_idt188_some",{id:"formSmash:j_idt184:9:j_idt188:some",widgetVar:"widget_formSmash_j_idt184_9_j_idt188_some",multiple:true}); PrimeFaces.cw("AccordionPanel","widget_formSmash_j_idt184_9_j_idt188_otherAuthors",{id:"formSmash:j_idt184:9:j_idt188:otherAuthors",widgetVar:"widget_formSmash_j_idt184_9_j_idt188_otherAuthors",multiple:true}); 2015 (English)In: Journal of Theoretical and Applied Climatology, ISSN 0177-798X, E-ISSN 1434-4483, Vol. 121, no 1-2, p. 53-59Article in journal (Refereed) Published
##### Abstract [en]

##### National Category

Meteorology and Atmospheric Sciences
##### Identifiers

urn:nbn:se:uu:diva-258758 (URN)10.1007/s00704-014-1220-1 (DOI)000356539300005 ()
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Available from: 2015-07-20 Created: 2015-07-20 Last updated: 2017-12-04Bibliographically approved

The notion of White Christmas, for instance snow conditions at Christmas Day, is occasionally discussed among people in certain countries in the northern hemisphere. In this paper, the state of snow occurrence at Christmas Day at locations in Sweden are primarily considered binary events and methodology for statistical analysis of time series with binary responses is employed to investigate trend over time. None of the six locations studied showed a significant change over time.