Simulation, Epistemic Opacity, and ‘Envirotechnical Ignorance’ in Nuclear Crisis

Ionescu, Tudor B.

doi:10.1007/s11023-018-9488-z

Cited by 3 publications

(3 citation statements)

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“…Hence, they should be rendered more flexibly adaptable, less tightly coupled, more easily reconfigurable, and more transparent for experts, who inherit legacy models and system components, some of which date from the 1980s. As I have pointed out elsewhere [65], these issues require a change of mindset towards accepting "non-knowledge" about the worst-case scenario as an inherent component of emergency preparedness cultures in addition to the concepts of risk and uncertainty. Such a change would require the revision of emergency protocols to explicitly allow for a period of adjustment of models and systems before the first results are used for decision making.…”

Section: Discussionmentioning

confidence: 99%

From Containing the Atom to Mitigating Residual Risk: The German Imaginary of Nuclear Emergency Preparedness

Ionescu

2020

Atmosphere

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Grounded in a social scientific research approach, the present case study traces the shift in the German nuclear regulatory culture from prevention to preparedness, the latter of which built upon decision support systems for nuclear emergency management. These systems integrate atmospheric dispersion models for tracing radioactive materials released accidentally from nuclear facilities. For atmospheric dispersion modelers and emergency managers, this article provides a critical historical perspective on the practical, epistemic, and organizational issues surrounding the use of decision support systems for nuclear emergency management. This perspective suggests that atmospheric dispersion models and technologies are embedded within an entire assemblage of institutions, technologies, and practices of preparedness, which are challenged by the uniqueness of each nuclear accident.

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Section: Discussionmentioning

confidence: 99%

From Containing the Atom to Mitigating Residual Risk: The German Imaginary of Nuclear Emergency Preparedness

Ionescu

2020

Atmosphere

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“…In recent years, philosophers have turned their attention to computer simulations and their epistemological value in scientific modeling and scientific practice. When faced with these issues, authors employ one of several strategies: they compare the epistemological power of computer simulations to laboratory experimentation (Morgan 2003;Parker 2009;Symons and Alvarado 2019;Ionescu 2018;Boge 2019); they analyze different forms of inferring knowledge from simulations (Winsberg 2001;Beisbart 2012); they hold extensive discussions on the notion of simulated data as different in kind from experimental and observational data (Barberousse and Marion 2013;Humphreys 2013); or they show how computer simulations are at the center of methodological, conceptual, and industrial changes in scientific research (Lenhard 2014).…”

Section: Introductionmentioning

confidence: 99%

What is a Simulation Model?

Durán

2020

Minds & Machines

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Many philosophical accounts of scientific models fail to distinguish between a simulation model and other forms of models. This failure is unfortunate because there are important differences pertaining to their methodology and epistemology that favor their philosophical understanding. The core claim presented here is that simulation models are rich and complex units of analysis in their own right, that they depart from known forms of scientific models in significant ways, and that a proper understanding of the type of model simulations are fundamental for their philosophical assessment. I argue that simulation models can be distinguished from other forms of models by the many algorithmic structures, representation relations, and new semantic connections involved in their architecture. In this article, I reconstruct a general architecture for a simulation model, one that faithfully captures the complexities involved in most scientific research with computer simulations. Furthermore, I submit that a new methodology capable of conforming such architecture into a fully functional, computationally tractable computer simulation must be in place. I discuss this methodology-what I call recasting-and argue for its philosophical novelty. If these efforts are heading towards the right interpretation of simulation models, then one can show that computer simulations shed new light on the philosophy of science. To illustrate the potential of my interpretation of simulation models, I briefly discuss simulation-based explanations as a novel approach to questions about scientific explanation.

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“…Para esos cálculos deben saberse las características de las emisiones radiactivas, los cambios metereológicos y el comportamiento del público (OIEA, 2013b). No obstante haberse elaborado sofisticados modelos computacionales de dispersión atmosférica y deposición de elementos radiactivos, existen serias dudas de que esas simulaciones logren reproducir un escenario de accidente real (Ionescu, 2019).…”

Section: ¿Pueden Explotar Los Reactores Nucleares?unclassified

El carácter único del riesgo nuclear y radiológico

Calcines Pedreira

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Simulation, Epistemic Opacity, and ‘Envirotechnical Ignorance’ in Nuclear Crisis

Cited by 3 publications

References 40 publications

From Containing the Atom to Mitigating Residual Risk: The German Imaginary of Nuclear Emergency Preparedness

From Containing the Atom to Mitigating Residual Risk: The German Imaginary of Nuclear Emergency Preparedness

What is a Simulation Model?

El carácter único del riesgo nuclear y radiológico

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