Gyksyj's starred repositories
topology_optimize_data
拓扑优化整理资料
Adaptive_ML-SCFEM
MATLAB toolbox for computing adaptive stochastic collocation finite element approximations for elliptic PDEs with random inputs
ANSYS-APDL-subroutine-CZM-uncoupled-model
ANSYS Mechanical APDL subroutine to define cohesive laws obtained by linear or polynomial interpolation of the respective points entered using the TBDATA command. The purpose of this subroutine is to define cohesive laws of any shape in ANSYS by means of the linear or polynomial interpolation of a given set of interpolating points of the cohesive laws, in particular for each Modes it is possible to choose a different number of points that are not necessarily equal spaced apart. By means of linear interpolation, the cohesive law is defined by an initial linear elastic section and by a softening branch consisting of linear sections. By means of polynomial interpolation, the cohesive law is defined by an initial linear section and by a polynomial softening branch .This cohesive zone model is intrinsic model, unilateral effect (i.e. the difference in tensile and compressive behavior in the direction normal to the interface plane in Mode I) is took in account, while the through-thickness compressive stress effect is ignored. This CZM is developed for non-linear static analysis.
FEniCS-Phase_Field_Approach
A phase field approach for twinning and fracture in brittle materials using monolithic scheme
Stabilized_Peridynamics_Code
This code to implement stabilized non-ordinary state-based peridynamics on the matlab platform
Peridynamics
So can I
1DPeridynamics
Vectorized Implementation of Benchmark Problem in 1D using Bond-Based Peridynamics
An-ordinary-state-based-peridynamics-OSBPD-
An-ordinary-state-based-peridynamics-OSBPD-
Micropolar_PDDO_Code
The code is for implementing fracture behavior of micropolar continuum with peridynamic differential operator method.
MatlabPeridynamicsCode
Matlab Peridynamics Code
adaptive-time-phase-field-fracture
Implementation of the phase-field model with adaptive time field scheme .
MATLAB-GEK-multisurrogate
Create Reduced Order Models of CFD using Gradient Enhanced Kriging - Multiple Surrogates
Point_cloud_tools_for_Matlab
Various point cloud tools for Matlab
ML_Inverse_Design_CTL
Source codes and dataset for data-driven inverse design of composite triangular lattice structures
EGC_3DTOP
A three-dimensional (3D) topology optimization approach based on extruded geometric components (EGCs) is proposed. Each EGC is constructed by extruding a convex/non-convex polygon along the axis of the EGC and rounding the ends of the EGC. Using an adaptive mapping technique which allows mapping each ECG onto a support domain, the EGCs are mapped onto an analytical grid to obtain an effective density field for material interpolation. Moreover, 2D-plane calculations can be utilized to replace 3D-space calculations to enhance computing efficiency. The positions and the cross-sectional areas of the ECGs are simultaneously optimized through the determination of an optimum set of geometry parameters. Some structural benchmark problems were investigated to verify the applicability of the proposed approach. Compared with the solid isotropic material penalization (SIMP) approach, the underlying approach does not require any filtering or projection techniques. Hence, it can produce a stiffer optimum design with an explicit boundary description whilst the number of design variables dramatically reduces.
GENCO-Investment-Strategies-by-Simulation-for-Demand-Side-Role-for-Investments-and-Capacity-Adequacy
This project will present an applied and game-like approach to simulating the load growth, investment decisions by two types of generation technologies, demand-price responsiveness, and reliability, of a test-case power system. The simulation begins as a 9-bus system with existing generation (3 generators) and transmission lines (8 lines). System topology can be viewed in a figure throughout the game with the yearly generation and load at each bus. In addition, dynamic color-coding is used to highlight transmission lines that exceed MVA ratings and highlight bus voltages that violate any limits. The winning objective of the player company (you) is to maximize his profit. Reliability can be tracked by viewing the N-1 generator and line contingencies every year, but this does not influence profits. There are two generation technologies used: coal and gas turbine. Each technology will have a similar competitor in the simulation. The competitor can bring down the market price and reduce the player’s profits significantly. The clock starts at T=0 in the investment game with a historical record of past prices and projected prices based on lack of investment. As time moves forward in yearly increments, the load, prices, investment costs, and other variables are adjusted to that of the player’s performance. The player has the opportunity to study various profitable and unprofitable investment alternatives each year of the simulation. If he invests at the right location, and in the right planning year, his company can make windfall profits. Competitors randomly participate in adding extra generation in random areas of the system based on the competition level settings. The challenge for the user is to study the effects of his investment decisions on market prices, reliability, and his profitability.
IH-GAN_CMAME_2022
IH-GAN, data generation, and topology optimization code associated with our CMAME 2022 paper: "IH-GAN: A Conditional Generative Model for Implicit Surface-Based Inverse Design of Cellular Structures."
thesis-repo
This repository is created for my undergraduate final project on gradient based optimization of structural and heat topology
TopOpt_EigenMatch
Topology optimization code for design of resonant structures by resonance and antiresonance matching, plus boundary conditions matching
topopt2dquadelem
topology optimization in two dimensions using quadrilateral elements for minimization of strain energy in matlab