ABSTRACT: A New Process Model for Turbidity Current Mudwaves (Sediment Waves) : Evidence from Toyama Deep-Sea Channel Levees, Japan Sea

AAPG Bulletin ◽  
2002 ◽  
Vol 86 ◽  
Author(s):  
Takeshi Nakajima1, Mikio Satoh1
2020 ◽  
Vol 90 (7) ◽  
pp. 687-700
Author(s):  
Jamie L. Hizzett ◽  
Esther J. Sumner ◽  
Matthieu J.B. Cartigny ◽  
Michael A. Clare

ABSTRACT Seafloor sediment density flows are the primary mechanism for transporting sediment to the deep sea. These flows are important because they pose a hazard to seafloor infrastructure and deposit the largest sediment accumulations on Earth. The cohesive sediment content of a flow (i.e., clay) is an important control on its rheological state (e.g., turbulent or laminar); however, how clay becomes incorporated into a flow is poorly understood. One mechanism is by the abrasion of (clay-rich) mud clasts. Such clasts are common in deep-water deposits, often thought to have traveled over large (more than tens of kilometers) distances. These long travel distances are at odds with previous experimental work that suggests that mud clasts should disintegrate rapidly through abrasion. To address this apparent contradiction, we conduct laboratory experiments using a counter rotating annular flume to simulate clast transport in sediment density flows. We find that as clay clasts roll along a sandy floor, surficial armoring develops and reduces clast abrasion and thus enhances travel distance. For the first time we show armoring to be a process of renewal and replenishment, rather than forming a permanent layer. As armoring reduces the rate of clast abrasion, it delays the release of clay into the parent flow, which can therefore delay flow transformation from turbidity current to debris flow. We conclude that armored mud clasts can form only within a sandy turbidity current; hence where armored clasts are found in debrite deposits, the parent flow must have undergone flow transformation farther up slope.


2005 ◽  
Vol 14 (03) ◽  
pp. 399-423 ◽  
Author(s):  
BINGRU YANG ◽  
JIANGTAO SHEN ◽  
WEI SONG

Knowledge Discovery in Knowledge Base (KDK) opens new horizons for research. KDK and KDD (Knowledge Discovery in Database) are the different cognitive field and discovery process. In most people's view, they are independent each other. In this paper we can summarize the following tasks: Firstly, we discussed that two kinds of the process model and mining algorithm of KDK based on facts and rules in knowledge base. Secondly, we proves that the inherent relation between KDD and KDK (i.e. double-basis fusion mechanism). Thirdly, we gained the new process model and implementation technology of KDK*. Finally, the imitation experimentation proved that the validity of above mechanism and process model.


2018 ◽  
Vol 62 (1) ◽  
pp. 14-24 ◽  
Author(s):  
Lisa Zimmermann ◽  
Conny H. Antoni

Abstract. Coaching research has to keep pace with the rapidly developing coaching practice. In order to strengthen theoretical and empirical knowledge, it is necessary to examine the efficacy of coaching, but even more important to develop a model of the underlying processes. By gaining a deeper insight into the coaching process and its causal mechanisms, knowledge can be generated that will enhance the efficiency of coaching in the future. In this paper, a new process model is developed, which draws on insights and methodological tools from psychotherapy research that are then applied to the coaching process. This model expands on existing process models by making new assumptions about concrete independent and intervening variables that influence coaching outcomes, and about the specific causal paths linking these variables. Special emphasis is placed on crucial variables that can play an important role in the improvement of coaching processes and in the prevention of negative coaching effects. In the second part of the paper, research on coaching is related to and integrated into the model. Finally, possible limitations of the model and present recommendations for future research are discussed.


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