کد مقاله کد نشریه سال انتشار مقاله انگلیسی ترجمه فارسی نسخه تمام متن
507109 865094 2016 10 صفحه PDF ندارد دانلود رایگان
عنوان انگلیسی مقاله
Growth by Optimization of Work (GROW): A new modeling tool that predicts fault growth through work minimization
ترجمه فارسی عنوان
رشد با بهینه سازی کار(رشد): یک ابزار مدل سازی جدید که رشد خطا از طریق به حداقل رساندن کار را پیش بینی می کند
کلمات کلیدی
رشد، رشد توسط بهینه سازی؛ Wext، کار خارجی؛ Wext / ΔA، به حداقل رساندن کار؛ پیوند سخت ؛ پیوند نرم ؛ روش المان مرزی (BEM)؛ مدلسازی عددی؛ قدرت انتشار؛ انتشار
GROW, GRowth by Optimization of Work; Wext, external work; Wext/ΔA, external work divided by new fracture areaFault propagation; Work minimization; Hard-linkage; Soft-linkage; Boundary element method (BEM); Numerical modeling; Propagation power; Releasing
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
چکیده انگلیسی


• First program to model fault growth through work optimization.
• Fault growth by work minimization as alternative to Coulomb failure planes.
• GROW models fault initiation, propagation and interactions.
• Work optimization detects soft- and hard-linkage.

Growth by Optimization of Work (GROW) is a new modeling tool that automates fracture initiation, propagation, interaction, and linkage. GROW predicts fracture growth by finding the propagation path and fracture geometry that optimizes the global external work of the system. This implementation of work optimization is able to simulate more complex paths of fracture growth than energy release rate methods. In addition, whereas a Coulomb stress analysis determines two conjugate planes of potential failure, GROW identifies a single failure surface for each increment of growth. GROW also eliminates ambiguity in determining whether shear or tensile failure will occur at a fracture tip by assessing both modes of failure by the same propagation criterion. Here we describe the underlying algorithm of the program and present GROW models of two propagating faults separated by a releasing step. The discretization error of these models demonstrates that GROW can predict fault propagation paths within the numerical uncertainty produced by discretization. Model element size moderately influences the propagation paths, however, the final fault geometry remains similar between models with significantly different element sizes. The propagation power of the fault system, calculated from the change in work due to fault propagation, indicates when model faults interact through both soft- and hard-linkage.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Geosciences - Volume 88, March 2016, Pages 142–151
نویسندگان
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