Technical Know-How for Modeling of Geological Environment: Part 1—Overview and Groundwater Flow Modeling

2010 ◽  
Author(s):  
Hiromitsu Saegusa ◽  
Shinji Takeuchi ◽  
Keisuke Maekawa ◽  
Hideaki Osawa ◽  
Takeshi Semba
Keyword(s):  
Decision Making ◽  
Research And Development ◽  
Groundwater Flow ◽  
Research Laboratory ◽  
Site Characterization ◽  
Decision Making Process ◽  
Geological Environment ◽  
Flow Modeling ◽  
Know How ◽  
Underground Research Laboratory

It is important for site characterization projects to manage the decision-making process with transparency and traceability and to transfer the technical know-how accumulated during the research and development to the implementing phase and to future generations. The modeling for a geological environment is to be used to synthesize investigation results. Evaluation of the impact of uncertainties in the model is important to identify and prioritize key issues for further investigations. Therefore, a plan for site characterization should be made based on the results of the modeling. The aim of this study is to support for the planning of initial surface-based site characterization based on the technical know-how accumulated from the Mizunami Underground Research Laboratory Project and the Horonobe Underground Research Laboratory Project. These projects are broad scientific studies of the deep geological environment that are a basis for research and development for the geological disposal of high-level radioactive wastes. In this study, the work-flow of the groundwater flow modeling, which is one of the geological environment models, and is to be used for setting the area for the geological environment modeling and for groundwater flow characterization, and the related decision-making process using literature data have been summarized.

Technical Know-How for Modeling of a Geological Environment: Part 2—Geological Modeling

2010 ◽  
Author(s):  
Toshiyuki Matsuoka ◽  
Kenji Amano ◽  
Hideaki Osawa ◽  
Takeshi Semba
Keyword(s):  
Research And Development ◽  
Research Laboratory ◽  
Site Characterization ◽  
Initial Surface ◽  
Geological Environment ◽  
Know How ◽  
Environment Model ◽  
High Level ◽  
Underground Research Laboratory ◽  
The Impact

It is important for site characterization projects to manage the decision-making process with transparency and traceability and to transfer the technical know-how developed and accumulated during the research and development to the implementing phase as well as to future generations. The modeling of a geological environment supports efforts to clarify the degree of understanding regarding that geological environment, including uncertainty. Evaluation of the impact of uncertainties in a geological environment model is important to identify and prioritize key issues for further investigations. Therefore, a plan for site characterization should be made based on the results of the modeling. The aim of this study is to support the planning of initial surface-based site characterization based on the technical know-how accumulated from the Mizunami Underground Research Laboratory Project and the Horonobe Underground Research Laboratory Project. These projects are broad scientific studies of the deep geological environment that are a basis for research and development for the geological disposal of high-level radioactive wastes. In this study, the work-flow followed in developing the geological model, one of the geological environment models, and the related technical know-how acquired from literature data have been summarized.

Mizunami Underground Research Laboratory in Japan: Pre-Excavation Site Characterization and Influence on Design Concepts

2001 ◽  
Author(s):  
Glen F. McCrank ◽  
Kenji Amano ◽  
Kaoru Koide ◽  
Hiroya Matsui ◽  
Shinichiro Mikake ◽  
...  
Keyword(s):  
Research Laboratory ◽  
Conceptual Models ◽  
Site Characterization ◽  
Geological Environment ◽  
Central Japan ◽  
Design Concepts ◽  
Experimental Programme ◽  
Nuclear Cycle ◽  
Underground Research Laboratory ◽  
Excavation Site

Abstract The Mizunami Underground Research Laboratory (MIU) will be constructed by the Japan Nuclear Cycle Development Institute (JNC) in central Japan. The project is planned in three overlapping phases consisting of I) Surface-based Investigation II) Construction and III) Operations Phases. This paper addresses the methods used to investigate the geological environment, the integration of the site knowledge into conceptual models and the application of the knowledge in designing the facility; some aspects of the future experimental programme are discussed.

Technical Know-How of Site Descriptive Modeling for Site Characterization

2011 ◽  
Author(s):  
Hiromitsu Saegusa ◽  
Tadafumi Niizato ◽  
Ken-ichi Yasue ◽  
Hironori Onoe ◽  
Ryosuke Doke
Keyword(s):  
Site Characterization ◽  
Current Status ◽  
Initial Surface ◽  
Geological Environment ◽  
Implementation Phase ◽  
Know How ◽  
Long Duration ◽  
High Level ◽  
Underground Research Laboratory ◽  
Technical Basis

The site descriptive model covering the current status of characteristics of geological environment and the site evolution model for estimation of the long-term evolution of site conditions are used to integrate multi-disciplinary investigation results. It is important to evaluate uncertainties in the models, to specify issues regarding the uncertainties and to prioritize the resolution of specified issues, for the planning of site characterization. There is a large quantity of technical know-how in the modeling process. It is important to record the technical know-how with transparency and traceability, since site characterization projects generally need long duration. The transfer of the technical know-how accumulated in the research and development (R&D) phase to the implementation phase is equally important. The aim of this study is to support the planning of initial surface-based site characterizations based on the technical know-how accumulated from the underground research laboratory projects. These projects are broad scientific studies of the deep geological environment and provide a technical basis for the geological disposal of high-level radioactive wastes. In this study, a comprehensive task flow from acquisition of existing data to planning of field investigations through the modeling has been specified. Specific task flow and decision-making process to perform the tasks have been specified.

The JNC Generic URL Research Program - Providing a Knowledge Base to Support both Implementer and Regulator in Japan

2006 ◽  
Vol 932 ◽  
Author(s):  
Hiroyuki Umeki ◽  
Kazuhiko Shimizu ◽  
Toshihiro Seo ◽  
Akira Kitamura ◽  
Hirohisa Ishikawa
Keyword(s):  
Knowledge Base ◽  
Safety Assessment ◽  
Atomic Energy Commission ◽  
Phase 1 ◽  
Site Characterization ◽  
Crystalline Rock ◽  
Know How ◽  
Safety Regulations ◽  
Site Characteristics ◽  
Underground Research Laboratory

ABSTRACTIn accordance with the R&D framework specified by the Atomic Energy Commission of Japan in 2000 for the implementing phase of HLW disposal, the Japan Nuclear Cycle Development Institute (JNC) continues to be responsible for R&D activities aimed at enhancing the reliability of disposal technologies and safety assessment methodologies and associated databases. JNC has thus been actively promoting technical R&D with a view to contributing to both the implementation of disposal and the formulation of safety regulations.One of JNC's key roles is to establish and demonstrate site characterization methodologies based on investigations in two purpose-built generic URL (underground research laboratory) projects: one at Mizunami in crystalline rock and the other at Horonobe in sedimentary rock.Through the surface-based investigations in the Mizunami and Horonobe projects (phase 1), integration of work from different disciplines into a “geosynthesis” has been illustrated and is planned to be developed further in the underground facilities at these sites (phases 2 and 3). These projects also serve for developing and testing the tools and methodologies required for site characterization. Further know-how will be gained through participation in foreign underground laboratory projects, transfer of experience from these projects to Japan and tailoring it to Japanese conditions and requirements.This experience represents an important knowledge base, which is obviously important for the implementer but is also needed by the regulator, in order to assess how key site characteristics are derived and what uncertainties are associated with this process.

Prenatal Genetic Diagnosis for Pediatricians

PEDIATRICS ◽  
1994 ◽  
Vol 93 (6) ◽  
pp. 1010-1015
Author(s):  
Keyword(s):  
Decision Making ◽  
Genetic Counseling ◽  
Prenatal Diagnosis ◽  
Diagnostic Tests ◽  
Genetic Disorder ◽  
Genetic Diagnosis ◽  
Decision Making Process ◽  
Know How ◽  
Prenatal Genetic Diagnosis ◽  
The Family

Pediatricians may be called upon to counsel a family in which prenatal diagnosis is being considered or in which there is a fetus with a genetic disorder. In some settings, the pediatrician may be the primary resource for counseling the family. More frequently, counseling may already have been provided by a clinical geneticist and/or obstetrician. However, because of a previous relationship with the family, the pediatrician may be called upon to review this information and to assist the family in the decision-making process. The pediatrician should be familiar with the principles of prenatal genetic diagnosis and know how to apply them to specific problems in genetic counseling, diagnosis, and management in clinical practice. At the same time, pediatricians should be familiar with resources available in their region for obtaining information about whether and how a specific disorder can be diagnosed and when and where to refer patients for prenatal genetic diagnosis. The technology of prenatal diagnosis is changing rapidly, and genetic consultants can assist pediatricians in the appropriate utilization and interpretation of the diagnostic tests that are available.

Toward a Perspective on R&D Outsourcing: RBV and Firm Performance

2018 ◽  
Vol 15 (05) ◽  
pp. 1850040 ◽  
Author(s):  
Anne W. Fuller
Keyword(s):  
Decision Making ◽  
Firm Performance ◽  
Research And Development ◽  
Competitive Advantage ◽  
Industrial Research ◽  
Vital Role ◽  
Decision Making Process ◽  
Resource Based View ◽  
The Impact

This paper looks at the vital role of industrial research and development (R&D). The increased outsourcing of industrial R&D is contrasted with a resource-based view of competitive advantage which maintains capabilities that are valuable, rare, imitable, and non-substitutable (VRIN), and should be internalized in the firm. Traditional business formation literature is also supportive of keeping R&D “inhouse”. R&D outsourcing research is leveraged to posit possible reasons for the increased amount of outsourced R&D. Testable propositions are included that look at factors for R&D outsource decisions and also the impact of these decisions on firm performance. An R&D entropy statistic is introduced as well as several R&D characteristics useful in the decision-making process to create R&D.

scholarly journals Explaining probabilistic Artificial Intelligence (AI) models by discretizing Deep Neural Networks

2021 ◽  
Author(s):  
Rabia Saleem ◽  
Bo Yuan ◽  
Fatih Kurugollu ◽  
Ashiq Anjum
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Decision Making ◽  
Process Model ◽  
Deep Neural Networks ◽  
Computational Cost ◽  
Black Box ◽  
Decision Making Process ◽  
Deterministic Models ◽  
Know How

Artificial Intelligence (AI) models can learn from data and make decisions without any human intervention. However, the deployment of such models is challenging and risky because we do not know how the internal decision- making is happening in these models. Especially, the high-risk decisions such as medical diagnosis or automated navigation demand explainability and verification of the decision making process in AI algorithms. This research paper aims to explain Artificial Intelligence (AI) models by discretizing the black-box process model of deep neural networks using partial differential equations. The PDEs based deterministic models would minimize the time and computational cost of the decision-making process and reduce the chances of uncertainty that make the prediction more trustworthy.

Assessing the Credibility of Young Children's Allegations of Sexual Abuse: Clinical Issues*

1987 ◽  
Vol 32 (7) ◽  
pp. 610-614 ◽  
Author(s):  
Halina Klajner-Diamond ◽  
William Wehrspann ◽  
Paul Steinhauer
Keyword(s):  
Decision Making ◽  
Sexual Abuse ◽  
Developmental Stage ◽  
Decision Making Process ◽  
Clinical Issues ◽  
Know How

In assessing the credibility of young children's (ages 2–7) allegations of sexual abuse clinicians need to know how dynamics of sexual abuse affect disclosure, what situations are most commonly associated with fictitious allegations and how the child's developmental stage affects disclosures. Understanding these issues allows for clear decision making. A clear decision making process flows naturally from an understanding of these issues.

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