A technique based on the Wiener path integral (WPI) is developed for determining the stochastic response of diverse nonlinear systems with fractional derivative elements. Specifically, a reduced-order WPI formulation is proposed, which can be construed as an approximation-free dimension reduction approach that renders the associated computational cost independent of the total number of stochastic dimensions of the problem. In fact, the herein developed technique can determine, directly, any lower-dimensional joint response probability density function corresponding to a subset only of the response vector components. This is done by utilizing an appropriate combination of fixed and free boundary conditions in the related variational, functional minimization, problem. Notably, the reduced-order WPI formulation is particularly advantageous for problems where the interest lies in few only specific degrees-of-freedom whose stochastic response is critical for the design and optimization of the overall system. An indicative numerical example is considered pertaining to a stochastically excited tuned mass-damper-inerter nonlinear system with a fractional derivative element. Comparisons with relevant Monte Carlo simulation data demonstrate the accuracy and computational efficiency of the technique.
{"title":"A Reduced-Order Wiener Path Integral Formalism for Determining the Stochastic Response of Nonlinear Systems with Fractional Derivative Elements","authors":"I. Mavromatis, I. Kougioumtzoglou","doi":"10.1115/1.4056902","DOIUrl":"https://doi.org/10.1115/1.4056902","url":null,"abstract":"\u0000 A technique based on the Wiener path integral (WPI) is developed for determining the stochastic response of diverse nonlinear systems with fractional derivative elements. Specifically, a reduced-order WPI formulation is proposed, which can be construed as an approximation-free dimension reduction approach that renders the associated computational cost independent of the total number of stochastic dimensions of the problem. In fact, the herein developed technique can determine, directly, any lower-dimensional joint response probability density function corresponding to a subset only of the response vector components. This is done by utilizing an appropriate combination of fixed and free boundary conditions in the related variational, functional minimization, problem. Notably, the reduced-order WPI formulation is particularly advantageous for problems where the interest lies in few only specific degrees-of-freedom whose stochastic response is critical for the design and optimization of the overall system. An indicative numerical example is considered pertaining to a stochastically excited tuned mass-damper-inerter nonlinear system with a fractional derivative element. Comparisons with relevant Monte Carlo simulation data demonstrate the accuracy and computational efficiency of the technique.","PeriodicalId":44694,"journal":{"name":"ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B-Mechanical Engineering","volume":"54 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2023-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73819695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
H. Bui, T. Sakurahara, S. Reihani, E. Kee, Z. Mohaghegh
Addressing safety concerns in commercial Nuclear Power Plants (NPPs) often requires the use of advanced modeling and simulation (M&S) in association with the Probabilistic Risk Assessment (PRA). Advanced M&S are also needed to accelerate the analysis, design, licensing, and operationalization of advanced nuclear reactors. However, before a simulation model can be used for PRA, its validity must be adequately established. The objective of this research is to develop a systematic and scientifically justifiable validation methodology, namely, Probabilistic Validation (PV), to facilitate the validity evaluation (especially when validation data are not sufficiently available) of advanced simulation models that are used for PRA in support of risk-informed decision-making and regulation. This paper is the first in a series of two papers related to the PV that provides the theoretical foundation and methodological platform. The second paper applies the PV methodological platform for a case study of Fire PRA of NPPs. Although the PV methodology is explained in the context of PRA of the nuclear industry, it is grounded on a cross-disciplinary review of literature and so applicable to validation of simulation models, in general, not necessarily associated with PRA or nuclear applications.
{"title":"Probabilistic Validation: Theoretical Foundation and Methodological Platform","authors":"H. Bui, T. Sakurahara, S. Reihani, E. Kee, Z. Mohaghegh","doi":"10.1115/1.4056883","DOIUrl":"https://doi.org/10.1115/1.4056883","url":null,"abstract":"\u0000 Addressing safety concerns in commercial Nuclear Power Plants (NPPs) often requires the use of advanced modeling and simulation (M&S) in association with the Probabilistic Risk Assessment (PRA). Advanced M&S are also needed to accelerate the analysis, design, licensing, and operationalization of advanced nuclear reactors. However, before a simulation model can be used for PRA, its validity must be adequately established. The objective of this research is to develop a systematic and scientifically justifiable validation methodology, namely, Probabilistic Validation (PV), to facilitate the validity evaluation (especially when validation data are not sufficiently available) of advanced simulation models that are used for PRA in support of risk-informed decision-making and regulation. This paper is the first in a series of two papers related to the PV that provides the theoretical foundation and methodological platform. The second paper applies the PV methodological platform for a case study of Fire PRA of NPPs. Although the PV methodology is explained in the context of PRA of the nuclear industry, it is grounded on a cross-disciplinary review of literature and so applicable to validation of simulation models, in general, not necessarily associated with PRA or nuclear applications.","PeriodicalId":44694,"journal":{"name":"ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B-Mechanical Engineering","volume":"7 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2023-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73986590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Decommissioning is expensive and can be a complex operation involving a series of distinct phases, including cessation of operation, site preparation, decontamination, dismantling (demolition) and disposal. Each decommissioning phase has associated risks, which need to be identified, controlled, and minimised as far as reasonably practicable. A risk-based approach has been recognised, both for ensuring safety and reducing the total decommissioning period with cost savings. A traditional HAZOP Study can be conveniently extended to Decommissioning HAZOP, which is a guideword-based collective multi-discipline study identifying types of risks associated with decommissioning and allocates actions to the contractor and specialists departments for implementation. A Decommissioning HAZOP enables to address the hazards and risks of decommissioning activities holistically, addresses all major contingencies and results in safe decommissioning within budget. The presented Decommissioning HAZOP study itself was completed ahead of time, without major accidents. While there are other methods, Decommissioning HAZOP and risk assessment was recognised as one of the effective methods for achieving the safety and project cost objectives.
{"title":"Practical Experience From Risks of Decommissioning of Petrochemical Facilities","authors":"R. Raman, S. Medonos","doi":"10.1115/1.4055797","DOIUrl":"https://doi.org/10.1115/1.4055797","url":null,"abstract":"\u0000 Decommissioning is expensive and can be a complex operation involving a series of distinct phases, including cessation of operation, site preparation, decontamination, dismantling (demolition) and disposal. Each decommissioning phase has associated risks, which need to be identified, controlled, and minimised as far as reasonably practicable. A risk-based approach has been recognised, both for ensuring safety and reducing the total decommissioning period with cost savings. A traditional HAZOP Study can be conveniently extended to Decommissioning HAZOP, which is a guideword-based collective multi-discipline study identifying types of risks associated with decommissioning and allocates actions to the contractor and specialists departments for implementation. A Decommissioning HAZOP enables to address the hazards and risks of decommissioning activities holistically, addresses all major contingencies and results in safe decommissioning within budget. The presented Decommissioning HAZOP study itself was completed ahead of time, without major accidents. While there are other methods, Decommissioning HAZOP and risk assessment was recognised as one of the effective methods for achieving the safety and project cost objectives.","PeriodicalId":44694,"journal":{"name":"ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B-Mechanical Engineering","volume":"10 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74247779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. Moura, Michael Beer, G. D. de Souza, E. Patelli
N/A
N/A
{"title":"Special Section on Decommissioning and Life Extension of Complex Industrial Assets","authors":"R. Moura, Michael Beer, G. D. de Souza, E. Patelli","doi":"10.1115/1.4055799","DOIUrl":"https://doi.org/10.1115/1.4055799","url":null,"abstract":"\u0000 <jats:p>N/A</jats:p>","PeriodicalId":44694,"journal":{"name":"ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B-Mechanical Engineering","volume":"17 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88322806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Karen A. Souza, L. C. M. Barbosa, Tiago M. S. Jacques, Vitor Bourbon
The Brazilian decommissioning industry faces challenges in onshore and offshore environments that could potentially lead to operational safety problems and environmental impacts. In 2020, the Brazilian regulators brought innovations to the decommissioning plans, implementing a new regulation. On the economic aspect, this instrument aims to promote the sector's business conditions and to adapt itself to recognized internationally decom technical standards. On the regulatory side, it aims to compare alternative solutions for the decommissioning of facilities whose analysis must adopt at least technical and environmental criteria, social, safety, and economic. The existing framework was discussed with different stakeholders, involving industry, society, and academics. Several improvements and opportunities for the sector were identified, suggesting the necessity of improving the local decom infrastructure and technological enhancements for extension of the lifecycle of fields. The adoption of Conceptual and Executive IDP by the resolution allowed the operator to determine the general lines of actions related to the decommissioning, allowing better planning, and reducing project uncertainties. As seen, the IDP requires the consideration of a multi-criteria analysis and the need to be cautionary. The Conceptual IDP ensures a better field development and the best decommissioning planning in initial stages. The new regulation established well-defined rules aimed at field life extension and the recovery factor, lowering costs, and preventing premature decommissioning of the field in a safe manner, minimizing risks to people and the environment, in addition to establishing that the contractor must evaluate the possibility of using the asset for another purposes.
{"title":"New Regulatory Instrument for Brazilian Decommissioning of Oil and Gas Installations","authors":"Karen A. Souza, L. C. M. Barbosa, Tiago M. S. Jacques, Vitor Bourbon","doi":"10.1115/1.4055798","DOIUrl":"https://doi.org/10.1115/1.4055798","url":null,"abstract":"\u0000 The Brazilian decommissioning industry faces challenges in onshore and offshore environments that could potentially lead to operational safety problems and environmental impacts. In 2020, the Brazilian regulators brought innovations to the decommissioning plans, implementing a new regulation. On the economic aspect, this instrument aims to promote the sector's business conditions and to adapt itself to recognized internationally decom technical standards. On the regulatory side, it aims to compare alternative solutions for the decommissioning of facilities whose analysis must adopt at least technical and environmental criteria, social, safety, and economic. The existing framework was discussed with different stakeholders, involving industry, society, and academics. Several improvements and opportunities for the sector were identified, suggesting the necessity of improving the local decom infrastructure and technological enhancements for extension of the lifecycle of fields. The adoption of Conceptual and Executive IDP by the resolution allowed the operator to determine the general lines of actions related to the decommissioning, allowing better planning, and reducing project uncertainties. As seen, the IDP requires the consideration of a multi-criteria analysis and the need to be cautionary. The Conceptual IDP ensures a better field development and the best decommissioning planning in initial stages. The new regulation established well-defined rules aimed at field life extension and the recovery factor, lowering costs, and preventing premature decommissioning of the field in a safe manner, minimizing risks to people and the environment, in addition to establishing that the contractor must evaluate the possibility of using the asset for another purposes.","PeriodicalId":44694,"journal":{"name":"ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B-Mechanical Engineering","volume":"33 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80746439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In order to impact physical mechanical system design decisions and realize the full promise of high-fidelity computational tools, simulation results must be integrated at the earliest stages in the design process. This is particularly challenging when dealing with uncertainty and optimizing for system-level performance metrics, as full-system models (often notoriously expensive and time-consuming to develop) are generally required to propagate uncertainties to system- level quantities of interest. Methods for propagating parameter and boundary condition uncertainty in networks of interconnected components hold promise for enabling design under uncertainty in real-world applications. These methods avoid the need for time consuming mesh generation of full-system geometries when changes are made to components or subassemblies. Additionally, they explicitly tie full-system model predictions to component/subassembly validation data which is valuable for qualification. These methods work by leveraging the fact that many engineered systems are inherently modular, being comprised of a hierarchy of components and subassemblies that are individually modified or replaced to define new system designs. By doing so, these methods enable rapid model development and the incorporation of uncertainty quantification earlier in the design process. The resulting formulation of the uncertainty propagation problem is iterative. We express the system model as a network of interconnected component models, which exchange solution information at component boundaries. We present a pair of approaches for propagating uncertainty in this type of decomposed system and provide implementations in the form of an open-source software library. We demonstrate these tools on a variety of applications and demonstrate the impact of problem-specific details on the performance and accuracy of the resulting UQ analysis. This work represents the most comprehensive investigation of these network uncertainty propagation methods to date.
{"title":"Network Uncertainty Quantification for Analysis of Multi-Component Systems","authors":"John Tencer, Edward Rojas, Benjamin Schroeder","doi":"10.1115/1.4055688","DOIUrl":"https://doi.org/10.1115/1.4055688","url":null,"abstract":"\u0000 In order to impact physical mechanical system design decisions and realize the full promise of high-fidelity computational tools, simulation results must be integrated at the earliest stages in the design process. This is particularly challenging when dealing with uncertainty and optimizing for system-level performance metrics, as full-system models (often notoriously expensive and time-consuming to develop) are generally required to propagate uncertainties to system- level quantities of interest. Methods for propagating parameter and boundary condition uncertainty in networks of interconnected components hold promise for enabling design under uncertainty in real-world applications. These methods avoid the need for time consuming mesh generation of full-system geometries when changes are made to components or subassemblies. Additionally, they explicitly tie full-system model predictions to component/subassembly validation data which is valuable for qualification. These methods work by leveraging the fact that many engineered systems are inherently modular, being comprised of a hierarchy of components and subassemblies that are individually modified or replaced to define new system designs. By doing so, these methods enable rapid model development and the incorporation of uncertainty quantification earlier in the design process. The resulting formulation of the uncertainty propagation problem is iterative. We express the system model as a network of interconnected component models, which exchange solution information at component boundaries. We present a pair of approaches for propagating uncertainty in this type of decomposed system and provide implementations in the form of an open-source software library. We demonstrate these tools on a variety of applications and demonstrate the impact of problem-specific details on the performance and accuracy of the resulting UQ analysis. This work represents the most comprehensive investigation of these network uncertainty propagation methods to date.","PeriodicalId":44694,"journal":{"name":"ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B-Mechanical Engineering","volume":"16 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90889410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Multi Parameter-Path length method for Resilience (MP-PLMR), has been proposed to determine the resilience of system multi-parameter considerations. It was applied to two engineering situations : (i) Passive catalytic device for hydrogen management in Nuclear Power Plant (NPP) (ii) Engineered systems for hydrogen mitigation in NPP. The method involves normalizations of the system parameters, the time domain and correlation coefficient across the parameters. The path length for the transient was defined using all the parameters and their correlations. The resilience value in the two case studies depended on the number of parameters considered and correlations. System resilience without the consideration of correlation was also estimated. The difference between the correlated and uncorrelated resilience was significant. While there is no established metric against which the calculated values could be compared, these values can be used to define system effectiveness in conjunction with reliability of systems.
{"title":"Application of Multi Parameter Path Length Method for Resilience (MP-PLMR) to Engineering Systems","authors":"M. Prasad, V. Gopika, J. Andrews","doi":"10.1115/1.4055290","DOIUrl":"https://doi.org/10.1115/1.4055290","url":null,"abstract":"\u0000 Multi Parameter-Path length method for Resilience (MP-PLMR), has been proposed to determine the resilience of system multi-parameter considerations. It was applied to two engineering situations : (i) Passive catalytic device for hydrogen management in Nuclear Power Plant (NPP) (ii) Engineered systems for hydrogen mitigation in NPP. The method involves normalizations of the system parameters, the time domain and correlation coefficient across the parameters. The path length for the transient was defined using all the parameters and their correlations. The resilience value in the two case studies depended on the number of parameters considered and correlations. System resilience without the consideration of correlation was also estimated. The difference between the correlated and uncorrelated resilience was significant. While there is no established metric against which the calculated values could be compared, these values can be used to define system effectiveness in conjunction with reliability of systems.","PeriodicalId":44694,"journal":{"name":"ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B-Mechanical Engineering","volume":"9 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82302189","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Arthur H. A. Melani, Miguel A. C. Michalski, R. F. da Silva, G. D. de Souza
The integrity assessment of aged or worn out large electromechanical equipment unit, such as in hydroelectric generators, for possible life extension has been identified as a growing challenge in the electrical power generation industry worldwide. Although the available recommended practices provide a general assessment process, it is necessary to have more detailed guidelines. This can be achieved by adding relevant theories and models which can capture time-dependent equipment unit degradation more precisely. Seeking to fulfill this gap, this work aims to present a framework that combines several techniques of data analysis, reliability, and decision-making to support engineers, operators, and managers in the often-complex decision process, between whether or not to extend the time in service of an equipment or system, thus postponing the moment of a scheduled maintenance shutdown. To demonstrate the application of the proposed framework, a case study is presented considering simulated scenarios based on data and information from a real Hydroelectric Power Plant. The results show how the reliability of the components and the remaining useful life of those in fault can impact the decision-making regarding the in-service life extension of a system.
{"title":"A Framework for In-Service Life Extension of Hydroelectric Generation Assets","authors":"Arthur H. A. Melani, Miguel A. C. Michalski, R. F. da Silva, G. D. de Souza","doi":"10.1115/1.4055220","DOIUrl":"https://doi.org/10.1115/1.4055220","url":null,"abstract":"\u0000 The integrity assessment of aged or worn out large electromechanical equipment unit, such as in hydroelectric generators, for possible life extension has been identified as a growing challenge in the electrical power generation industry worldwide. Although the available recommended practices provide a general assessment process, it is necessary to have more detailed guidelines. This can be achieved by adding relevant theories and models which can capture time-dependent equipment unit degradation more precisely. Seeking to fulfill this gap, this work aims to present a framework that combines several techniques of data analysis, reliability, and decision-making to support engineers, operators, and managers in the often-complex decision process, between whether or not to extend the time in service of an equipment or system, thus postponing the moment of a scheduled maintenance shutdown. To demonstrate the application of the proposed framework, a case study is presented considering simulated scenarios based on data and information from a real Hydroelectric Power Plant. The results show how the reliability of the components and the remaining useful life of those in fault can impact the decision-making regarding the in-service life extension of a system.","PeriodicalId":44694,"journal":{"name":"ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B-Mechanical Engineering","volume":"10 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87070293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Engineering decisions that have the greatest effect on worker and public safety occur early in the design process. During these decisions, engineers rely on their experience and intuition to estimate the severity and likelihood of undesired future events like failures, equipment damage, injuries, or environmental harm. These initial estimates can then form the basis of investment of limited project resources in mitigating those risks. Behavioral economics suggests that most people make significant and predictable errors when considering high consequence, low probability events. Yet, these biases have not previously been studied quantitatively in the context of engineering decisions. This paper describes results from a set of computer-based engineering assessment and decision experiments with undergraduate engineering students estimating, prioritizing, and making design decisions related to risk. The subjects included in this experiment overestimated the probability of failure, deviated significantly from anticipated risk management preferences, and displayed worsening biases with increasing system complexity. These preliminary results suggest that considerably more effort is needed to understand the characteristics and qualities of these biases in risk estimation and understand what kinds of interventions might best ameliorate these biases and enable engineers to more effectively identify and manage the risks of technology.
{"title":"A Set of Estimation and Decision Preference Experiments for Exploring Risk Assessment Biases in Engineering Students","authors":"Jeremy M. Gernand","doi":"10.1115/1.4055156","DOIUrl":"https://doi.org/10.1115/1.4055156","url":null,"abstract":"\u0000 Engineering decisions that have the greatest effect on worker and public safety occur early in the design process. During these decisions, engineers rely on their experience and intuition to estimate the severity and likelihood of undesired future events like failures, equipment damage, injuries, or environmental harm. These initial estimates can then form the basis of investment of limited project resources in mitigating those risks. Behavioral economics suggests that most people make significant and predictable errors when considering high consequence, low probability events. Yet, these biases have not previously been studied quantitatively in the context of engineering decisions. This paper describes results from a set of computer-based engineering assessment and decision experiments with undergraduate engineering students estimating, prioritizing, and making design decisions related to risk. The subjects included in this experiment overestimated the probability of failure, deviated significantly from anticipated risk management preferences, and displayed worsening biases with increasing system complexity. These preliminary results suggest that considerably more effort is needed to understand the characteristics and qualities of these biases in risk estimation and understand what kinds of interventions might best ameliorate these biases and enable engineers to more effectively identify and manage the risks of technology.","PeriodicalId":44694,"journal":{"name":"ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B-Mechanical Engineering","volume":"35 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77703019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Experimental toxicology studies for the purposes of setting occupational exposure limits for aerosols have drawbacks including excessive time and cost which could be overcome or limited by the development of computational approaches. A quantitative, analytical relationship between the characteristics of emerging nanomaterials and related in vivo toxicity can be utilized to better assist in the subsequent mitigation of exposure toxicity by design. Predictive toxicity models can be used to categorize and define exposure limitations for emerging nanomaterials. Model-based no-observed-adverse-effect-level (NOAEL) predictions were derived for toxicologically distinct nanomaterial clusters, referred to as MP-NOAELs. The lowest range of MP-NOAELs for the polymorphonuclear neutrophil (PMN) response observed by CNTs was found to be 21 - 35 µg/kg (cluster "A"), indicating that the CNT belonging to cluster "A" showed the earliest signs of adverse effects. Only 25% of the MP-NOAEL values for the CNTs can be considered rationalquantitatively defined at present. The lowest observed MP-NOAEL range for the metal oxide nanoparticles was Cobalt oxide nanoparticles (Cluster III) for the Macrophage (MAC) response at 54 - 189 µg/kg. Nearly 50% of the derived MP-NOAEL values for the metal oxide nanoparticles can be considered rationalquantitatively defined based on current data. A sensitivity analysis of the MP-NOAEL derivation highlighted the dependency of the process on the shape and type of the fitted dose response model, its parameters, dose selection and spacing, and the sample size analyzed.
{"title":"Evaluation of Risk and Uncertainty for Model-Predicted NOAELs of Engineered Nanomaterials Based On Dose-Response-Recovery Clusters","authors":"V. Ramchandran, Jeremy M. Gernand","doi":"10.1115/1.4055157","DOIUrl":"https://doi.org/10.1115/1.4055157","url":null,"abstract":"\u0000 Experimental toxicology studies for the purposes of setting occupational exposure limits for aerosols have drawbacks including excessive time and cost which could be overcome or limited by the development of computational approaches. A quantitative, analytical relationship between the characteristics of emerging nanomaterials and related in vivo toxicity can be utilized to better assist in the subsequent mitigation of exposure toxicity by design. Predictive toxicity models can be used to categorize and define exposure limitations for emerging nanomaterials. Model-based no-observed-adverse-effect-level (NOAEL) predictions were derived for toxicologically distinct nanomaterial clusters, referred to as MP-NOAELs. The lowest range of MP-NOAELs for the polymorphonuclear neutrophil (PMN) response observed by CNTs was found to be 21 - 35 µg/kg (cluster \"A\"), indicating that the CNT belonging to cluster \"A\" showed the earliest signs of adverse effects. Only 25% of the MP-NOAEL values for the CNTs can be considered rationalquantitatively defined at present. The lowest observed MP-NOAEL range for the metal oxide nanoparticles was Cobalt oxide nanoparticles (Cluster III) for the Macrophage (MAC) response at 54 - 189 µg/kg. Nearly 50% of the derived MP-NOAEL values for the metal oxide nanoparticles can be considered rationalquantitatively defined based on current data. A sensitivity analysis of the MP-NOAEL derivation highlighted the dependency of the process on the shape and type of the fitted dose response model, its parameters, dose selection and spacing, and the sample size analyzed.","PeriodicalId":44694,"journal":{"name":"ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B-Mechanical Engineering","volume":"102 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89313408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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