Methodologies for the development of quality assessment of Experimental models in structural Engineering
The focus of this research are develops computation methods for managing the uncertainties in experimental models used in various engineering field, with emphasis in structural engineering models. These methods enable the rigorous assessment of models considering measurement uncertainty based on a statistical analysis of observation and the uncertainty derived from a process equation as well as an uncertainty model of the parameters. Uncertainties are ubiquitous in structural engineering. The effect of measurement uncertainty is commonly mentioned in discussions of model accuracy, but this effect is also typically ignored. Advanced methods for representing the sources of uncertainty and propagating them though, experimental/observation models, computational models, are necessary for designing safe and robust structures and cost constraints. In this context, Bayesian theory, Evidence based theory, Fuzzy theory are the powerful tool for propagating the uncertainty through models, so that measurement uncertainty can be easily incorporated into model calibration and validation, and solve typical questions of safety, sensitivity analysis and decision making.
The topics to be covered are:
- Expressing, evaluating and propagating measurement uncertainties; designing efficient algorithms to compute various parameters, such as mean, median and others percentiles, variance, interquantile range, moments and confidence limits; summarizing the computability of such statististic from imprecise data
- Parametic uncertainty analysis considering measurement uncertainty in the structural simulation
- Calibration of experiments
- Uncertainty quantification (UQ) of the outcomes of laboratory and field experiments and the parameters and predictions of mathematical models using the theories of probability and statistics
- Quality assessment of experimental models
- Sensitivity analysis
- An example of model validation based on experiments on a real structure
Peer reviewed journal papers:
Keitel, H.; Jung, B.; Motra, H. B.; Stutz, H. : Assessment of prognosis quality of coupled partial models considering soil-structure coupling. In: Engineering Structures, 59(2014) pp. 565-573 .
Motra, H. B.; Dimmig-Osburg, A.; Hildebrand, J.: Evaluation of Experimental Measurement Uncertainty in Engineering Properties of PCC Samples, Journal of Civil Engineering Research, Vol. 3 No. 3, 2013, pp. 104-113.
Keitel, K.; Jung, B.; Stutz, H.; Motra, H. B.: Prediction quality of coupled models - Influence of different coupling scenarios on the soil-structure interaction, Bautechnik- Special Edition "Modellqualitäten" 90(2013)19-25.
Scheiber, F.; Motra, H. B.: Structural health monitoring and numerical simulation , Bautechnik-Special Edition"Modellqualitäten" 90(2013) 63-68
Motra, H. B.; Dimmig-Osburg, A. ; Hildebrand, J.: Quality assessment of strain measurement in concrete structures, Bautechnik Special Edition "Modellqulitäten" 90(2013) 69-75.
Motra, H.B.; Hildebrand, J.; Dimmig-Osburg, A.: Quality assessment of models with an application to cyclic prediction of concrete. In: Journal of Quality and Reliability Engineering, Accepted for publication.
Motra, H.B.; Hildebrand, J.; Dimmig-Osburg. A.: Assessment of strain measurement technique to characterize mechanical properties of structural steel. In: Engineering Science and Technology, an International Journal, Accepted for publication.
Motra, H.B.; Hildebrand, J., Dimmig-Osburg, A.: Influence of specimen dimensions and orientation on the tensile properties of structural steel. In: Material Testing, Accepted for Publication.
Motra, H.B.; Hildebrand, J.; Dimmig-Osburg, A.; Stutz, H.: A probabilistic method for quality evaluation of experiments in civil engineering. In: Measurement, Journal of the International Measurement Confederation (IMEKO), Submitted, 2014.
Scheiber, F.; Motra, H.B.; Legatiuk, D.; Werner, F.: On coupling of mathematical and physical models. In: Probabilistic Engineering Mechanics, Work-in progress.
Motra, H.B.; Hildebrand, J.; Dimmig-Osburg, A., Wuttke, F.: Monte Carlo method for evaluation of measurement uncertainty: application to determine material properties. Work-in-progress.
Motra, H.B.; Hildebrand, j.; Dimmig-Osburg, A.; Lahmer, T.: Reliability of measurement results for materials testing. In: Proceedings of 12th International Probabilistic Workshop, IPW2014, 4th-5th November 2014 Weimar/Germany, Accepted.
Scheiber, F.; Motra, H.B.; Legatiuk, D. Werner, F.: Model coupling in structural engineering. In: Proceedings of 12th International Probabilistic Workshop, IPW2014, 4th-5th November 2014, Weimar/Germany, Accepted.
Scheiber, F.; Motra, H. B.: Approach to hybrid modeling in structural engineering-Evaluation of mathematical and physical models coupling. In 7th symposium Experimental investigation of structures, Technical University Dresden Germany, 5th September 2013, ISSN 1613-6934, pp. 21-33.
Motra, H.B.; Dimmig-Osburg, A.; Hildebrand, J.: Uncertainty quantification on creep deflection of concrete beam subjected to cyclic loading. In: 11th International Conference on Structural Safety & Reliability, Columbia University, New York, NY, 16 - 20 June 2013, USA.
Motra, H.B.; Dimmig-Osburg, A.; Hildebrand, J.: Influence of Measurement Uncertainties on Results of Creep Prediction of Concrete under Cyclic Loading. In: Proceedings of the 8th International Conference on Fracture Mechanics of Concrete and Concrete Structures. March 10-14, 2013 / Toledo - Spain, ISBN 978-84-941004-1-3, pp. 805-814.
Motra, H.B.; Dimmig-Osburg, A.; Hildebrand, J.: Probabilistic assessment of concrete creep models under repeated loading with correlated and uncorrelated input variables. In: Proceedings of the 10th International Probabilistic Workshop, Stuttgart, Germany, 15 - 16 November 2012, ISBN 978-3-921837-67-2, pp. 285-301.
Motra, H.B.; Dimmig-Osburg, A.; Hildebrand, J.: Uncertainty Quantification and Sensitivity Analysis on cyclic creep prediction of concrete. In: Proceedings of the 19th International Conference on the Application of Computer Science and Mathematics in Architecture and Civil Engineering, Weimar, 04 - 06 July 2012, ISSN 1611-4086