Temperaturinduktion in Betontragwerke

Clauß, Felix; Löschmann, Jens; Ahrens, Alexander; Mark, Peter

doi:10.1002/best.202100010

Cited by 8 publications

(8 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…However, a validation is needed to check the prediction capabilities of the approach. The developed concept is applied to a supported beam, using data monitored during a beam test [5].…”

Section: Methodological Approach For Real-time Assessment Of the Stru...mentioning

confidence: 99%

See 1 more Smart Citation

Structural stress prediction based on deformations using artificial neural networks trained with artificial noise

Gottardi

Freitag

Meschke

2023

Proc Appl Math and Mech

View full text Add to dashboard Cite

Artificial Neural Networks (ANN) have found application for multiple problems in structural mechanics and civil engineering. In the new approach developed here, ANNs are used for the determination of the maximum stress resultants in a structure on the basis of monitored displacements. Initially, a simple supported beam subjected up to two vertical forces is considered. The beam is solved analytically for different combinations of load positions and magnitudes defined by Monte‐Carlo sampling. The resulting beam deflections and maximum stress resultants are employed for the training of feedforward neural networks in order to generate metamodels able to predict the maximum bending moment knowing only a few beam input deflections. Subsequently, the concept is applied to a real beam experiment, where a reinforced concrete beam has been tested. It is shown, that the perfect correlation of the beam displacements used as inputs for the ANN training leads to extrapolations when the metamodel is applied to the measured displacements of the real experiment, which are not perfectly correlated. This is source of wrong predictions when the network is applied to these data. The introduction of artificial noise in the synthetic input data in a controlled way before training helps to overcome extrapolation and to increase repeatability and robustness of the metamodels. Various noise levels are applied to the synthetic data to monitor how the ANN performances change over increasing noise and the results along with the limitations of the approach are illustrated.

show abstract

“…However, a validation is needed to check the prediction capabilities of the approach. The developed concept is applied to a supported beam, using data monitored during a beam test [5].…”

Section: Methodological Approach For Real-time Assessment Of the Stru...mentioning

confidence: 99%

“…The beam experiment which was used to validate the method is the one reported in [5]. A reinforced concrete beam with two longitudinal rebar layers (with steel areas of A s = 402 mm 2 and A ′ s = 100.5 mm 2 ) spanning over the full length of it was casted and underwent a four-point bending test.…”

Section: Experimental Setup and Structural Modelmentioning

confidence: 99%

Structural stress prediction based on deformations using artificial neural networks trained with artificial noise

Gottardi

Freitag

Meschke

2023

Proc Appl Math and Mech

View full text Add to dashboard Cite

show abstract

“…The heat is induced via two heating mats 38 with a length of 1.0 m and a width of 0.25 m (see Figure 2, marked in red). In a previous study, 39 among other methods, this technique for temperature induction was investigated: the low weight but especially their high flexibility regarding deformations qualifies the heating mats for this application. In order to separate the test specimen to be heated from the colder outside air, it was completely encased in polystyrene of 20 cm thickness.…”

Section: Methodsmentioning

confidence: 99%

Thermo‐mechanical experiments on reinforced concrete beams: Assessing thermal, mechanical, and mixed impacts on fiber optic measurements

Clauß

Ahrens

Mark

2022

Structural Concrete

Self Cite

View full text Add to dashboard Cite

Strain and temperature measurements on reinforced concrete structures with Rayleigh-based fiber optic sensors (FOS) promise dense data networks of crucial structural parameters. In this context, the measurement of temperature and mechanical strain is invariably intertwined, precipitating in a frequency shift recorded via FOS. Consecutive experiments were carried out on reinforced concrete beams under mechanical, thermal, and thermo-mechanical loading. Basic analysis of fiber optics equations indicates the sensitivities toward both influences. These are quantified and juxtaposed in experiments, first separately and subsequently combined. As concerns temperature measurement, the slightest tensile forces exerted onto the FOS may engender distortions of several degrees Celsius. Conversely, strain measurements are affected by temperature changes to a lesser degree. Nevertheless, the level of strain to be sensed and the severity of corrupting temperature shifts must be carefully weighted. The article raises awareness for the coupling of temperature and strain and enables the practitioner to identify and assess perturbations.

show abstract

“…Anschließend wurden die Versuchskörper gleichmäßig mit einem PTFE‐isolierten Heizband (maximale Heizleistung: 260 °C, Schalttemperatur auf 1 °C einstellbar, Hysterese ± 1 °C, vgl. hierzu auch [16]) umwickelt. An der Oberseite sowie an den seitlichen Flächen wurde eine 20 cm dicke Dämmschicht aus Steinwolle angebracht, sodass der Rahmen sowie die Kraft‐ und Wegaufnehmer während der Erwärmung der Versuchskörper nahezu keine Temperaturänderung erfuhren.…”

Section: Experimentelle Untersuchungenunclassified

Experimentelle und numerische Untersuchungen zu Zwangkräften aus Temperaturdifferenzen

Walsemann

Albert

Mark

2022

Beton und Stahlbetonbau

Self Cite

View full text Add to dashboard Cite

Für eine sichere und wirtschaftliche Bemessung von zwangbeanspruchten Stahlbetonbauteilen ist eine realistische Abschätzung der Zwangkraft von großer Bedeutung. Frühere Arbeiten legen nahe, dass hierbei unterschieden werden sollte, ob Betonschwinden oder eine Temperaturdifferenz die Ursache der Zwangbeanspruchung darstellt. Im vorliegenden Beitrag werden Untersuchungen beschrieben, bei denen beidseitig gehaltene Stahlbetonstäbe unter gleichförmigen Temperaturdifferenzen von bis zu 70 K experimentell untersucht wurden. Die sich einstellende Rissbildung sowie dazu korrespondierende Kräfte werden herausgearbeitet, mit Ergebnissen aus numerischen Simulationsrechnungen verglichen und dabei erweitert um die Variation von Längsbewehrungsgrad, Betonzugfestigkeit und Behinderungsgrad. Die deutlichen Unterschiede des Tragverhaltens gegenüber Bauteilen, die Zwang infolge von Schwinden ausgesetzt sind, werden bestätigt. Zudem zeigt sich, dass das abgeschlossene Rissbild des jeweiligen Bauteils bereits bei deutlich geringeren Dehnungen als 0,8 ‰ erreicht werden kann. Das übliche Vorgehen bei einer kombinierten Beanspruchung aus Last und Zwang, bei dem die Bemessung für beide Beanspruchungsarten getrennt erfolgt und dann der größere der beiden ermittelten Bewehrungsquerschnitte vorgesehen wird, kann z. T. deutlich auf der unsicheren Seite liegen.

show abstract

Temperaturinduktion in Betontragwerke

Cited by 8 publications

References 21 publications

Structural stress prediction based on deformations using artificial neural networks trained with artificial noise

Structural stress prediction based on deformations using artificial neural networks trained with artificial noise

Thermo‐mechanical experiments on reinforced concrete beams: Assessing thermal, mechanical, and mixed impacts on fiber optic measurements

Experimentelle und numerische Untersuchungen zu Zwangkräften aus Temperaturdifferenzen

Contact Info

Product

Resources

About