The Experts below are selected from a list of 24672 Experts worldwide ranked by ideXlab platform
Ruben Van Coile - One of the best experts on this subject based on the ideXlab platform.
-
review of current practice in probabilistic Structural Fire engineering permanent and live load modelling
Fire Technology, 2020Co-Authors: Balsa Jovanovic, Ruben Van Coile, Danny Hopkin, Negar Elhami Khorasani, David Lange, Thomas GernayAbstract:Probabilistic analysis is receiving increased attention from Fire engineers, assessment bodies and researchers. It is however often unclear which probabilistic models are appropriate for the analysis. For example, in probabilistic Structural Fire engineering, the models used to describe the permanent and live loads differ widely between studies. Through a literature review, it is observed that these diverging load models are based on surveys conducted between 1893 and 1976 and that widely adopted assumptions, such as the rule for combining permanent and live loads into the total load effect, are commonly adopted based on precedent. The diverging current models however relate to mostly the same underlying datasets and basic methodologies. Differences can be attributed (largely) to specific assumptions in different background papers, which have become consolidated through repeated use in research papers and adoption in background documents to codes. By reviewing the studies underlying currently applied probabilistic load models in Structural Fire engineering, a consolidated probabilistic load model is proposed in this paper. It is concluded that the total load effect is ideally described by KE·(G + Q), with KE the model uncertainty for the load effect, G the permanent load, and Q the imposed load. The model uncertainty KE can be described by a lognormal distribution with mean equal to unity and coefficient of variation (COV) of 0.10. The permanent load is preferably modelled by a normal distribution with mean equal to the nominal permanent load, and a COV which can either be assessed on a project specific basis, or can be set to 0.10 for a first assessment. For common occupancies (office, residential), the live load is preferably modelled by a Gamma distribution. The mean live load can be taken as 0.2 times the nominal, and the live load COV can be taken as 0.60 for large load areas (> 200 m2) and 0.95 for smaller load areas (< 100 m2). Comparison between the failure probabilities of steel and concrete columns subject to Fire, considering the proposed consolidated model and two currently commonly used models, indicates that relative differences of the probability of failure can be in the order of 10%. Live load models for evacuation routes and warehouses require specific study and are outside the scope of the review.
-
Resilience targets for Structural Fire design : an exploratory study
2019Co-Authors: Ruben Van Coile, Thomas Gernay, Danny Hopkin, Negar Elhami KhorasaniAbstract:The adequacy of Structural Fire engineering designs is determined by the ALARP requirement, under the condition of design tolerabil-ity. The ALARP requirement applies both to traditional Fire safety goals such as life safety, but also to questions of resilience. When confronted with uncertainty, however, an ALARP evaluation entails a detailed full probabilistic analysis, greatly increasing computational complexity. The application of a limit state approach and target safety levels as in Structural engineering for normal design condi-tions would allow for a practical approximation of the ALARP as-sessment. In the presented exploratory study, the background of the target safety levels for normal design conditions are revisited, as well as their applicability for Fire design. Based on these concepts, a similar approach is presented for the derivation of resilience targets (reliability indices). When the failure probabilities for the collapse and resilience (downtime) limit states are small, their target safety levels can be considered independent.
-
Efficient uncertainty quantification method applied to Structural Fire engineering computations
Engineering Structures, 2019Co-Authors: Thomas Gernay, Ruben Van Coile, Negar Elhami Khorasani, Danny HopkinAbstract:Abstract Probabilistic Risk Assessment methodologies are gaining traction in Fire engineering practice as a (necessary) means to demonstrate adequate safety for uncommon buildings. This induces a need to apply uncertainty quantification to Structural Fire engineering problems. Yet, the combination of probabilistic methods and advanced numerical Fire engineering tools has been limited due to the absence of a methodology which is both efficient (i.e. requires a limited number of model evaluations) and unbiased (i.e. without prior assumptions regarding the output distribution type). In this paper, the recently proposed MaxEnt method is combined with the dedicated Structural Fire engineering software SAFIR to evaluate the ability of the method to achieve efficient, unbiased assessments of Structural Fire performance. The case studies include the probability density function (PDF) of (i) the standard Fire resistance of a composite column; (ii) the load bearing capacity of a composite floorplate exhibiting tensile membrane action, after 90 min of standard Fire exposure; (iii) the load bearing capacity of the same composite floorplate, considering a parametric Fire exposure including cooling phase; and (iv) the maximum temperature reached in a protected steel element under realistic Fire exposure. In the first application, the MaxEnt PDF correctly and efficiently captures the distribution obtained using Monte Carlo Simulations. The floorplate example under parametric Fire exposure shows the true strength of the MaxEnt method as an unbiased assessment, as different failure modes are observed in the cooling phase resulting in an irregular shape of the load-bearing capacity PDF. For this case, reliance on a traditional assumption of lognormality for the capacity would result in an overestimation of the capacity at lower quantiles. The last case study yields a bi-modal output due to the physics-based duality between localized (traveling) and post-flashover Fire development. While the MaxEnt captures this bi-modality, it does not accurately reproduce the distribution obtained by Monte Carlo Simulation. Limitations of the MaxEnt method and needs for further research are discussed at the end of the paper.
-
Permanent and live load model for probabilistic Structural Fire analysis : a review
2019Co-Authors: Ruben Van Coile, Danny Hopkin, Negar Elhami Khorasani, David Lange, Thomas GernayAbstract:Probabilistic analysis is receiving increased attention from Fire engineers, assessment bodies and researchers. It is however often unclear which probabilistic models are appropriate for the analysis. For example, in probabilistic Structural Fire engineering, the models used to describe the permanent and live load differ widely between studies. Through a literature review, it is observed that these diverging load models largely relate to the same underlying datasets and basic methodologies, while differences can be attributed (largely) to specific assumptions in different background papers which have become consolidated through repeated use in application studies by different researchers. Taking into account the uncovered background information, consolidated probabilistic load models are proposed.
-
The MaxEnt method for probabilistic Structural Fire engineering : performance for multi-modal outputs
2019Co-Authors: Danny Hopkin, Thomas Gernay, Negar Elhami Khorasani, Ruben Van CoileAbstract:Probabilistic Risk Assessment (PRA) methodologies are gaining traction in Fire engineering practice as a (necessary) means to demonstrate adequate safety for uncommon buildings. Further, an increasing number of applications of PRA based methodologies in Structural Fire engineering can be found in the contemporary literature. However, to date, the combination of probabilistic methods and advanced numerical Fire engineering tools has been limited due to the absence of a methodology which is both efficient (i.e. requires a limited number of model evaluations) and unbiased (i.e. without prior assumptions regarding the output distribution type). An uncertainty quantification methodology (termed herein as MaxEnt) has recently been presented targeted at an unbiased assessment of the model output probability density function (PDF), using only a limited number of model evaluations. The MaxEnt method has been applied to Structural Fire engineering problems, with some applications benchmarked against Monte Carlo Simulations (MCS) which showed excellent agreement for single-modal distributions. However, the power of the method is in application for those cases where ‘validation’ is not computationally practical, e.g. uncertainty quantification for problems reliant upon complex modes (such as FEA or CFD). A recent study by Gernay, et al., applied the MaxEnt method to determine the PDF of maximum permissible applied load supportable by a steel-composite slab panel undergoing tensile membrane action (TMA) when subject to realistic (parametric) Fire exposures. The study incorporated uncertainties in both the manifestation of the Fire and the mechanical material parameters. The output PDF of maximum permissible load was found to be bi-modal, highlighting different failure modes depending upon the combinations of stochastic parameters. Whilst this outcome highlighted the importance of an un-biased approximation of the output PDF, in the absence of a MCS benchmark the study concluded that some additional studies are warranted to give users confidence and guidelines in such situations when applying the MaxEnt method. This paper summarises one further study, building upon Case C as presented in Gernay, et al.
Thomas Gernay - One of the best experts on this subject based on the ideXlab platform.
-
review of current practice in probabilistic Structural Fire engineering permanent and live load modelling
Fire Technology, 2020Co-Authors: Balsa Jovanovic, Ruben Van Coile, Danny Hopkin, Negar Elhami Khorasani, David Lange, Thomas GernayAbstract:Probabilistic analysis is receiving increased attention from Fire engineers, assessment bodies and researchers. It is however often unclear which probabilistic models are appropriate for the analysis. For example, in probabilistic Structural Fire engineering, the models used to describe the permanent and live loads differ widely between studies. Through a literature review, it is observed that these diverging load models are based on surveys conducted between 1893 and 1976 and that widely adopted assumptions, such as the rule for combining permanent and live loads into the total load effect, are commonly adopted based on precedent. The diverging current models however relate to mostly the same underlying datasets and basic methodologies. Differences can be attributed (largely) to specific assumptions in different background papers, which have become consolidated through repeated use in research papers and adoption in background documents to codes. By reviewing the studies underlying currently applied probabilistic load models in Structural Fire engineering, a consolidated probabilistic load model is proposed in this paper. It is concluded that the total load effect is ideally described by KE·(G + Q), with KE the model uncertainty for the load effect, G the permanent load, and Q the imposed load. The model uncertainty KE can be described by a lognormal distribution with mean equal to unity and coefficient of variation (COV) of 0.10. The permanent load is preferably modelled by a normal distribution with mean equal to the nominal permanent load, and a COV which can either be assessed on a project specific basis, or can be set to 0.10 for a first assessment. For common occupancies (office, residential), the live load is preferably modelled by a Gamma distribution. The mean live load can be taken as 0.2 times the nominal, and the live load COV can be taken as 0.60 for large load areas (> 200 m2) and 0.95 for smaller load areas (< 100 m2). Comparison between the failure probabilities of steel and concrete columns subject to Fire, considering the proposed consolidated model and two currently commonly used models, indicates that relative differences of the probability of failure can be in the order of 10%. Live load models for evacuation routes and warehouses require specific study and are outside the scope of the review.
-
Review of Current Practice in Probabilistic Structural Fire Engineering: Permanent and Live Load Modelling
Fire Technology, 2020Co-Authors: Balša Jovanović, Danny Hopkin, Ruben Van Coile, David Lange, Negar Elhami Khorasani, Thomas GernayAbstract:Probabilistic analysis is receiving increased attention from Fire engineers, assessment bodies and researchers. It is however often unclear which probabilistic models are appropriate for the analysis. For example, in probabilistic Structural Fire engineering, the models used to describe the permanent and live loads differ widely between studies. Through a literature review, it is observed that these diverging load models are based on surveys conducted between 1893 and 1976 and that widely adopted assumptions, such as the rule for combining permanent and live loads into the total load effect, are commonly adopted based on precedent. The diverging current models however relate to mostly the same underlying datasets and basic methodologies. Differences can be attributed (largely) to specific assumptions in different background papers, which have become consolidated through repeated use in research papers and adoption in background documents to codes. By reviewing the studies underlying currently applied probabilistic load models in Structural Fire engineering, a consolidated probabilistic load model is proposed in this paper. It is concluded that the total load effect is ideally described by K _ E ·( G + Q ), with K _ E the model uncertainty for the load effect, G the permanent load, and Q the imposed load. The model uncertainty K _ E can be described by a lognormal distribution with mean equal to unity and coefficient of variation (COV) of 0.10. The permanent load is preferably modelled by a normal distribution with mean equal to the nominal permanent load, and a COV which can either be assessed on a project specific basis, or can be set to 0.10 for a first assessment. For common occupancies (office, residential), the live load is preferably modelled by a Gamma distribution. The mean live load can be taken as 0.2 times the nominal, and the live load COV can be taken as 0.60 for large load areas (> 200 m^2) and 0.95 for smaller load areas (
-
Resilience targets for Structural Fire design : an exploratory study
2019Co-Authors: Ruben Van Coile, Thomas Gernay, Danny Hopkin, Negar Elhami KhorasaniAbstract:The adequacy of Structural Fire engineering designs is determined by the ALARP requirement, under the condition of design tolerabil-ity. The ALARP requirement applies both to traditional Fire safety goals such as life safety, but also to questions of resilience. When confronted with uncertainty, however, an ALARP evaluation entails a detailed full probabilistic analysis, greatly increasing computational complexity. The application of a limit state approach and target safety levels as in Structural engineering for normal design condi-tions would allow for a practical approximation of the ALARP as-sessment. In the presented exploratory study, the background of the target safety levels for normal design conditions are revisited, as well as their applicability for Fire design. Based on these concepts, a similar approach is presented for the derivation of resilience targets (reliability indices). When the failure probabilities for the collapse and resilience (downtime) limit states are small, their target safety levels can be considered independent.
-
Efficient uncertainty quantification method applied to Structural Fire engineering computations
Engineering Structures, 2019Co-Authors: Thomas Gernay, Ruben Van Coile, Negar Elhami Khorasani, Danny HopkinAbstract:Abstract Probabilistic Risk Assessment methodologies are gaining traction in Fire engineering practice as a (necessary) means to demonstrate adequate safety for uncommon buildings. This induces a need to apply uncertainty quantification to Structural Fire engineering problems. Yet, the combination of probabilistic methods and advanced numerical Fire engineering tools has been limited due to the absence of a methodology which is both efficient (i.e. requires a limited number of model evaluations) and unbiased (i.e. without prior assumptions regarding the output distribution type). In this paper, the recently proposed MaxEnt method is combined with the dedicated Structural Fire engineering software SAFIR to evaluate the ability of the method to achieve efficient, unbiased assessments of Structural Fire performance. The case studies include the probability density function (PDF) of (i) the standard Fire resistance of a composite column; (ii) the load bearing capacity of a composite floorplate exhibiting tensile membrane action, after 90 min of standard Fire exposure; (iii) the load bearing capacity of the same composite floorplate, considering a parametric Fire exposure including cooling phase; and (iv) the maximum temperature reached in a protected steel element under realistic Fire exposure. In the first application, the MaxEnt PDF correctly and efficiently captures the distribution obtained using Monte Carlo Simulations. The floorplate example under parametric Fire exposure shows the true strength of the MaxEnt method as an unbiased assessment, as different failure modes are observed in the cooling phase resulting in an irregular shape of the load-bearing capacity PDF. For this case, reliance on a traditional assumption of lognormality for the capacity would result in an overestimation of the capacity at lower quantiles. The last case study yields a bi-modal output due to the physics-based duality between localized (traveling) and post-flashover Fire development. While the MaxEnt captures this bi-modality, it does not accurately reproduce the distribution obtained by Monte Carlo Simulation. Limitations of the MaxEnt method and needs for further research are discussed at the end of the paper.
-
Permanent and live load model for probabilistic Structural Fire analysis : a review
2019Co-Authors: Ruben Van Coile, Danny Hopkin, Negar Elhami Khorasani, David Lange, Thomas GernayAbstract:Probabilistic analysis is receiving increased attention from Fire engineers, assessment bodies and researchers. It is however often unclear which probabilistic models are appropriate for the analysis. For example, in probabilistic Structural Fire engineering, the models used to describe the permanent and live load differ widely between studies. Through a literature review, it is observed that these diverging load models largely relate to the same underlying datasets and basic methodologies, while differences can be attributed (largely) to specific assumptions in different background papers which have become consolidated through repeated use in application studies by different researchers. Taking into account the uncovered background information, consolidated probabilistic load models are proposed.
Danny Hopkin - One of the best experts on this subject based on the ideXlab platform.
-
Review of Current Practice in Probabilistic Structural Fire Engineering: Permanent and Live Load Modelling
Fire Technology, 2020Co-Authors: Balša Jovanović, Danny Hopkin, Ruben Van Coile, David Lange, Negar Elhami Khorasani, Thomas GernayAbstract:Probabilistic analysis is receiving increased attention from Fire engineers, assessment bodies and researchers. It is however often unclear which probabilistic models are appropriate for the analysis. For example, in probabilistic Structural Fire engineering, the models used to describe the permanent and live loads differ widely between studies. Through a literature review, it is observed that these diverging load models are based on surveys conducted between 1893 and 1976 and that widely adopted assumptions, such as the rule for combining permanent and live loads into the total load effect, are commonly adopted based on precedent. The diverging current models however relate to mostly the same underlying datasets and basic methodologies. Differences can be attributed (largely) to specific assumptions in different background papers, which have become consolidated through repeated use in research papers and adoption in background documents to codes. By reviewing the studies underlying currently applied probabilistic load models in Structural Fire engineering, a consolidated probabilistic load model is proposed in this paper. It is concluded that the total load effect is ideally described by K _ E ·( G + Q ), with K _ E the model uncertainty for the load effect, G the permanent load, and Q the imposed load. The model uncertainty K _ E can be described by a lognormal distribution with mean equal to unity and coefficient of variation (COV) of 0.10. The permanent load is preferably modelled by a normal distribution with mean equal to the nominal permanent load, and a COV which can either be assessed on a project specific basis, or can be set to 0.10 for a first assessment. For common occupancies (office, residential), the live load is preferably modelled by a Gamma distribution. The mean live load can be taken as 0.2 times the nominal, and the live load COV can be taken as 0.60 for large load areas (> 200 m^2) and 0.95 for smaller load areas (
-
review of current practice in probabilistic Structural Fire engineering permanent and live load modelling
Fire Technology, 2020Co-Authors: Balsa Jovanovic, Ruben Van Coile, Danny Hopkin, Negar Elhami Khorasani, David Lange, Thomas GernayAbstract:Probabilistic analysis is receiving increased attention from Fire engineers, assessment bodies and researchers. It is however often unclear which probabilistic models are appropriate for the analysis. For example, in probabilistic Structural Fire engineering, the models used to describe the permanent and live loads differ widely between studies. Through a literature review, it is observed that these diverging load models are based on surveys conducted between 1893 and 1976 and that widely adopted assumptions, such as the rule for combining permanent and live loads into the total load effect, are commonly adopted based on precedent. The diverging current models however relate to mostly the same underlying datasets and basic methodologies. Differences can be attributed (largely) to specific assumptions in different background papers, which have become consolidated through repeated use in research papers and adoption in background documents to codes. By reviewing the studies underlying currently applied probabilistic load models in Structural Fire engineering, a consolidated probabilistic load model is proposed in this paper. It is concluded that the total load effect is ideally described by KE·(G + Q), with KE the model uncertainty for the load effect, G the permanent load, and Q the imposed load. The model uncertainty KE can be described by a lognormal distribution with mean equal to unity and coefficient of variation (COV) of 0.10. The permanent load is preferably modelled by a normal distribution with mean equal to the nominal permanent load, and a COV which can either be assessed on a project specific basis, or can be set to 0.10 for a first assessment. For common occupancies (office, residential), the live load is preferably modelled by a Gamma distribution. The mean live load can be taken as 0.2 times the nominal, and the live load COV can be taken as 0.60 for large load areas (> 200 m2) and 0.95 for smaller load areas (< 100 m2). Comparison between the failure probabilities of steel and concrete columns subject to Fire, considering the proposed consolidated model and two currently commonly used models, indicates that relative differences of the probability of failure can be in the order of 10%. Live load models for evacuation routes and warehouses require specific study and are outside the scope of the review.
-
Resilience targets for Structural Fire design : an exploratory study
2019Co-Authors: Ruben Van Coile, Thomas Gernay, Danny Hopkin, Negar Elhami KhorasaniAbstract:The adequacy of Structural Fire engineering designs is determined by the ALARP requirement, under the condition of design tolerabil-ity. The ALARP requirement applies both to traditional Fire safety goals such as life safety, but also to questions of resilience. When confronted with uncertainty, however, an ALARP evaluation entails a detailed full probabilistic analysis, greatly increasing computational complexity. The application of a limit state approach and target safety levels as in Structural engineering for normal design condi-tions would allow for a practical approximation of the ALARP as-sessment. In the presented exploratory study, the background of the target safety levels for normal design conditions are revisited, as well as their applicability for Fire design. Based on these concepts, a similar approach is presented for the derivation of resilience targets (reliability indices). When the failure probabilities for the collapse and resilience (downtime) limit states are small, their target safety levels can be considered independent.
-
Efficient uncertainty quantification method applied to Structural Fire engineering computations
Engineering Structures, 2019Co-Authors: Thomas Gernay, Ruben Van Coile, Negar Elhami Khorasani, Danny HopkinAbstract:Abstract Probabilistic Risk Assessment methodologies are gaining traction in Fire engineering practice as a (necessary) means to demonstrate adequate safety for uncommon buildings. This induces a need to apply uncertainty quantification to Structural Fire engineering problems. Yet, the combination of probabilistic methods and advanced numerical Fire engineering tools has been limited due to the absence of a methodology which is both efficient (i.e. requires a limited number of model evaluations) and unbiased (i.e. without prior assumptions regarding the output distribution type). In this paper, the recently proposed MaxEnt method is combined with the dedicated Structural Fire engineering software SAFIR to evaluate the ability of the method to achieve efficient, unbiased assessments of Structural Fire performance. The case studies include the probability density function (PDF) of (i) the standard Fire resistance of a composite column; (ii) the load bearing capacity of a composite floorplate exhibiting tensile membrane action, after 90 min of standard Fire exposure; (iii) the load bearing capacity of the same composite floorplate, considering a parametric Fire exposure including cooling phase; and (iv) the maximum temperature reached in a protected steel element under realistic Fire exposure. In the first application, the MaxEnt PDF correctly and efficiently captures the distribution obtained using Monte Carlo Simulations. The floorplate example under parametric Fire exposure shows the true strength of the MaxEnt method as an unbiased assessment, as different failure modes are observed in the cooling phase resulting in an irregular shape of the load-bearing capacity PDF. For this case, reliance on a traditional assumption of lognormality for the capacity would result in an overestimation of the capacity at lower quantiles. The last case study yields a bi-modal output due to the physics-based duality between localized (traveling) and post-flashover Fire development. While the MaxEnt captures this bi-modality, it does not accurately reproduce the distribution obtained by Monte Carlo Simulation. Limitations of the MaxEnt method and needs for further research are discussed at the end of the paper.
-
Permanent and live load model for probabilistic Structural Fire analysis : a review
2019Co-Authors: Ruben Van Coile, Danny Hopkin, Negar Elhami Khorasani, David Lange, Thomas GernayAbstract:Probabilistic analysis is receiving increased attention from Fire engineers, assessment bodies and researchers. It is however often unclear which probabilistic models are appropriate for the analysis. For example, in probabilistic Structural Fire engineering, the models used to describe the permanent and live load differ widely between studies. Through a literature review, it is observed that these diverging load models largely relate to the same underlying datasets and basic methodologies, while differences can be attributed (largely) to specific assumptions in different background papers which have become consolidated through repeated use in application studies by different researchers. Taking into account the uncovered background information, consolidated probabilistic load models are proposed.
Hergen Eilers - One of the best experts on this subject based on the ideXlab platform.
-
Nanoscale Ex Situ Thermal Impulse Sensors for Structural Fire Forensics.
Applied Spectroscopy, 2017Co-Authors: Benjamin R. Anderson, Ray Gunawidjaja, Natalie Gese, Hergen EilersAbstract:We developed nanoscale ex situ thermal impulse (i.e., the temperature and duration of a heating event) sensors for Structural Fire forensics using a mixture of two lanthanide-doped oxide precursors (precursor Eu:ZrO2 and precursor Dy:Y2O3) that undergo irreversible phase changes when heated. These changes are probed using photoluminescence (PL) spectroscopy with the PL spectra being dependent on the thermal impulse (TI) experienced by the sensors. By correlating the PL spectra to different in-lab TIs, we are able to produce a spectroscopic calibration for our sensors. This calibration allows us to determine an unknown TI of a heating event using only the PL spectrum of the heated TI sensors. In this study, we report on the calibration of these sensors for isothermal heating durations up to 600 s and isothermal temperatures up to 1273 K. Using this calibration, we also demonstrate their ability to determine an unknown TI and demonstrate their functionality when dispersed into paint, which is heated in the presence of drywall.
-
Structural Fire forensics: using optically active nanoparticles to determine a Fire’s thermal impulse
Frontiers in Optics 2016, 2016Co-Authors: Benjamin R. Anderson, Ray Gunawidjaja, Natalie Gese, Gediminas Markevicius, Helena Diez-y-riega, Hergen EilersAbstract:One difficulty in Structural Fire forensics is accurately determining a Fire’s thermal impulse. To address this difficulty we develop optically active nanoparticles whose spectral properties irreversibly change when heated.
Mario Fontana - One of the best experts on this subject based on the ideXlab platform.
-
Modeling elevated-temperature mechanical behavior of high and ultra-high strength steels in Structural Fire design
Materials & Design, 2017Co-Authors: Martin Neuenschwander, Markus Knobloch, Claudio Scandella, Mario FontanaAbstract:Abstract High and ultra-high strength steels are increasingly used in structures of tall and super-tall buildings, where Fire safety has a substantial impact on the Structural design. However, more widespread employment in engineering practice is substantially impeded by the lack of suitable design models for the constitutive mechanical behavior of such steels at elevated temperatures; and respective available experimental research is limited to investigations of unusually thin plate material with respect to Structural applications. The present study completes the current database with an extensive series of strain-rate controlled tensile tests at different strain-rates with coupon specimens from high and ultra-high strength steel plates of varying thickness, and approves on the basis of this novel most comprehensive and consistent database that existing constitutive Fire design models for mild carbon steels are only restrictedly adoptable for high strength steels. Analysis of the impact of the revealed model shortcomings at the material level on Structural Fire designs shows that the model's overestimation of the elevated-temperature yield strength leads to unsafe Fire designs of Structural applications with strength-induced failure modes, whereas in contrast the model's underestimation of the elevated-temperature Young's modulus leads to occasionally highly overconservative Fire designs of Structural applications with stability-induced failure modes.
-
assessing the level of safety for performance based and prescriptive Structural Fire design of steel structures
Fire Safety Science, 2014Co-Authors: Gianluca De Sanctis, Michael Havbro Faber, Mario FontanaAbstract:The level of safety in Structural Fire safety is implemented by combining passive and active Fire safety measures. Prescriptive and some performance based codes provide requirements to achieve this level of safety without explicitly quantifying it. Here, a reliability based method is used to quantify the level of safety of a design. A generic representation of the building facilitates the application of the methodology on different buildings and to consider the requirements of the codes. Engineering models are used to consider the effect of Fire safety measures including the Fire brigade intervention under realistic Fire conditions. The uncertainties associated with these engineering models are considered through a probabilistic approach. The reliability of the structure is assessed through an advanced Monte Carlo technique called subset simulation. The methodology is applied for retail buildings. The benefits using performance based codes are addressed and compared with the results of prescriptive codes. The methodology can be used for verifying equivalency in Fire safety design as well.
-
On the use of Fire brigade statistics for Structural Fire safety engineering
Applications of Structural Fire Engineering, 2013Co-Authors: Gianluca De Sanctis, Jochen Köhler, Mario FontanaAbstract:In this paper the Fire brigade intervention is considered for the assessment of Structural Fire safety through the concept of a maximal controllable Fire area. Based on a literature survey probabilistic models are developed to consider the uncertainties associated with the Fire development and the Fire brigade intervention. A sensitivity analysis identifies the most important parameters and suggestions for future data collection are made to improve the probabilistic models.
