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![Fluka geometry of the Linac4 civil engineering (top) and the beam dump shielding (side view (bottom left) and front view (bottom right)) [22,23].](profile/Laurent-Tabourot/publication/260031605/figure/fig2/AS:269840548102173@1441346408803/Fluka-geometry-of-the-Linac4-civil-engineering-top-and-the-beam-dump-shielding-side.png)
Fluka geometry of the Linac4 civil engineering (top) and the beam dump shielding (side view (bottom left) and front view (bottom right)) [22,23].
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A core issue during the planning of a maintenance intervention in a facility with ionizing radiation is the minimization of the integrated equivalent dose contracted by the maintenance workers during the intervention. In this work, we explore the use of a technical-scientific software program facilitating the intervention planning in irradiated env...
Citations
... An environment mapping and path planning for underwater navigation of a low-cost μAUV (micro autonomous underwater vehicle) in a cluttered nuclear storage pond was developed to enable a low-cost μAUV to navigate and work safely in an enclosed cluttered underwater environment (Peng and Green, 2019). Using a case study of decommissioning of a nuclear facility, Fabry et al. (2014) proposed a practical use of an interactive visualization and planning tool for intervention planning in particle accelerator environments with ionizing radiation. The possibility of deploying smart robots and other controlled devices in complex radioactive environments is a subject of ongoing research. ...
Optimal walking-path planning is one of the most effective measures to minimize radiation exposure of workers in radioactive environments. Several algorithms have been proposed to control workers' exposure especially during normal operations of a nuclear facility. However, when an emergency or accident occurs, the radioactive environment becomes dynamic and complex, rendering the conventional shortest path algorithms non-optimal and inefficient. This work presents a state-aware adaptive pathfinder (SAP), a method to solve the minimum dose path for an emergency worker in a dynamic nuclear environment. The algorithm dynamically tracks and updates the state of both the radiation source and the (human) target, and adaptively presents the minimum dose path based on the current state. The advantages of the proposed SAP approach are evaluated in two experiments with eight (8) different scenarios. In the first experiment, a minimum dose walking path is obtained for a worker in a static environment with three scenarios. In the second experiment, cumulative dose by the emergency worker along a path is dynamically computed in three scenarios that define both the worker and the radiation source moving in uniform and non-uniform speed. Compared with conventional methods, the results show that the proposed SAP is simpler, more flexible, and effective for path planning in a complex radioactive environment. The performance evaluation result of SAP in both static and dynamic environments, and during a nuclear emergency is discussed in this paper.
... These calculations are integral in cases where a human, instead of a robot, intervention is obligatory. Fabry et al. [4,5] discusses the issue of minimizing integrated dose acquired during maintenance operations. They present a software program to plan and optimize the maintenance interventions in a facility with ionizing radiation. ...
... The simulated dose rates were used to estimate the integrated doses for different cases using MATLAB. Unlike the tools and methods described in [1,3], which are developed to calculate in-situ doses over a period of residence, the approach herein is focused on evacuation scenarios and is similar to [4,5]. While the work presented in [4,5] is centered on trajectory optimization during maintenance interventions, the proposed work is motivated by the need of expedient decisions in responding to emergency and evacuation scenarios. ...
... Unlike the tools and methods described in [1,3], which are developed to calculate in-situ doses over a period of residence, the approach herein is focused on evacuation scenarios and is similar to [4,5]. While the work presented in [4,5] is centered on trajectory optimization during maintenance interventions, the proposed work is motivated by the need of expedient decisions in responding to emergency and evacuation scenarios. The results of this work are crucial to prevent and mitigate large dose acquisitions in accidental-operation scenarios at Missouri S&T generator facility. ...
Any source of ionizing radiations could lead to considerable dose acquisition to individuals in a nuclear facility. Evacuation may be required when elevated levels of radiation is detected within a facility. In this situation, individuals are more likely to take the closest exit. This may not be the most expedient decision as it may lead to higher dose acquisition. The strategy followed in preventing large dose acquisitions should be predicated on the path that offers least dose acquisition. In this work, the neutron generator facility at Missouri University of Science and Technology was analyzed. The Monte Carlo N-Particle (MCNP) radiation transport code was used to model the entire floor of the generator's building. The simulated dose rates in the hallways were used to estimate the integrated doses for different paths leading to exits. It was shown that shortest path did not always lead to minimum dose acquisition and the approach was successful in predicting the expedient path as opposed to the approach of taking the nearest exit.
... A proof-of-concept software tool for computer-aided intervention planning, implementing this model has been conceived [1], and tested [2,3] in the context of CERN. The software allows for intervention planning in a visual, interactive way in a three-dimensional virtual environment. ...
An important aspect in the design and operation of high-energy particle accelerators is the planning of maintenance interventions. In the planning of these interventions, optimizing the exposure of the maintenance workers to ionizing radiation is a core issue. In this context, we have addressed the need for an interactive visual software tool. The intervention planning has been modeled mathematically. A proof-of-concept software tool has been implemented using this model, providing interactive visualization of facilities and radiation levels, tools for trajectory planning and automatic calculation of the expected integrated equivalent radiation dose. We explore the use of the software using a large experimental hall at CERN as a case study. Interactive visualization of the facilities and radiation levels, tools for interactive trajectory planning as well as automatic calculation of the expected integrated equivalent dose contracted during an intervention are explored. The obtained results prove the relevance of the developed methodology and software tool and demonstrate, among others, a better exploitation of the simulation data, leading to a potential accuracy gain.
... The software is also benchmarked against an existing dose planning. This work has been published in [71]. ...
... Finally, in section 6.3, we discuss and illustrate how the accuracy of the trajectory and intervention planning in the software is influenced by a variety of parameters and circumstances. This work has been published in [71]. 89 ...
... En même temps, une analyse comparative du nouveau logiciel et des procédures de planification de des activités avec prise en compte des paramètres radiologiques est menée. Ce travail aété publié dans [71]. ...
Radiation is omnipresent. It has many interesting applications: in medicine, where it allows curing and diagnosing patients; in communication, where modern communication systems make use of electromagnetic radiation; and in science, where it is used to discover the structure of materials; to name a few. Physically, radiation is a process in which particles or waves travel through any kind of material, usually air. Radiation can be very energetic, in which case it can break the atoms of ordinary matter (ionization). If this is the case, radiation is called ionizing. It is known that ionizing radiation can be far more harmful to living beings than non-ionizing radiation. In this dissertation, we are concerned with ionizing radiation. Naturally occurring ionizing radiation in the form of radioactivity is a most natural phenomenon. Almost everything is radioactive: there is radiation emerging from the soil, it is in the air, and the whole planet is constantly undergoing streams of energetic cosmic radiation. Since the beginning of the twentieth century, we are also able to artificially create radio-active matter. This has opened a lot of interesting technological opportunities, but has also given a tremendous responsibility to humanity, as the nuclear accidents in Chernobyl and Fukushima, and various accidents in the medical world have made clear. This has led to the elaboration of a radiological protection system. In practice, the radiological protection system is mostly implemented using a methodology that is indicated with the acronym ALARA: As Low As Reasonably Achievable. This methodology consists of justifying, optimizing and limiting the radiation dose received. This methodology is applied in conjunction with the legal limits. The word "reasonably" means that the optimization of radiation exposure has to be seen in context. The optimization is constrained by the fact that the positive effects of an operation might surpass the negative effects caused by the radiation. Several industrial and scientific procedures give rise to facilities with ionizing radiation. Most technical and scientific facilities also need maintenance operations. In the spirit of ALARA, these interventions need to be optimized in terms of the exposure of the maintenace workers to ionizing radiation. This optimization cannot be automated since the feasibility of the intervention tasks requires human assessment. The intervention planning could however be facilitated by technical-scientific means, e.g. software tools. In the context sketched above, this thesis provides technical-scientific considerations and the development of technical-scientific methodologies and software tools for the implementation of radiation protection.In particular, this thesis addresses the need for an interactive visual intervention planning tool in the context of high energy particle accelerator facilities.
This work proposes a methodology to handle complexity in organizations byfocusing on innovative and collaborative planning and scheduling methods dedicated to the optimization of interventions in environments emitting ionizing radiations. By taking as work environment highly complex and technological scientific facilities such as the ones of CERN in Geneva (Switzerland) and GSI in Darmstadt (Germany), we analyze the needs and requirements induced in intervention planning and scheduling by hazardous environments in general, and then more specifically by ionizing radiations. The implications of collaborative work are then scrutinized, and an ontological model for interventions is designed in order to select the methods best suited to our problem. The framework we present in this work relies on methods sucessfully used in project planning and scheduling and innovative product design like the Design Structure Matrix (DSM). It also introduces in these fields methods borrowed to artificial intelligence planning and scheduling such as the temporal qualitative algebras, constraint propagation, and the search of compromises in case of conflicts. This so called “Collaborative DSM” has been implemented in a prototype software application tested at CERN and GSI on practical applications. The very first one and its results are presented in the final chapter of this thesis. This framework aims at placing resources (mostly human resources) and temporal constraints at the heart of the planning and scheduling process. It focuses on collaboration between the different actors involved, from coordinators to technicians, and on simulation and multiple-criteria comparison of several scenarios, rather than searching for a unique optimum, which often tends to be non-practical, should one even be found.
