save all files

Author: Kevinletsgo

run/meshMotion/cylinderMotion/Allclean

@@ -4,6 +4,6 @@ cd "${0%/*}" || exit                                # Run from this directory
 #------------------------------------------------------------------------------
 
 rm -rf cylinderMotionExperiment
-rm -f *.out *.err log*.* *.dat
+rm -f *.out *.err log*.* *.log *.dat
 
-#------------------------------------------------------------------------------
+#------------------------------------------------------------------------------

run/meshMotion/cylinderMotion/Allrun

@@ -3,6 +3,8 @@ cd "${0%/*}" || exit                                # Run from this directory
 . ${WM_PROJECT_DIR:?}/bin/tools/CleanFunctions      # Tutorial clean functions
 #------------------------------------------------------------------------------
 
+./Allclean
+
 python cylinder-motion.py
 
-#------------------------------------------------------------------------------
+#------------------------------------------------------------------------------

run/meshMotion/cylinderMotion/cylinder-motion.py

@@ -112,6 +112,9 @@ def visualization_points(n_points):
 
     # Make sure all datasets are avaialble in the smartredis database.
     local_time_index = 1
+    learning_rate = 1e-02
+    optimizer = optim.Adam(model.parameters(), lr=learning_rate)
+
     while True:
 
         print (f"Time step {local_time_index}")
@@ -178,9 +181,9 @@ def visualization_points(n_points):
                                                                             test_size=0.2, random_state=42)
 
         # PYTORCH Training Loop
-        optimizer = optim.Adam(model.parameters(), lr=1e-04)
         loss_func = nn.MSELoss()
-        epochs = 10000
+        epochs = 100000
+        n_epochs = 0 
         mean_mag_displ = torch.mean(torch.norm(displ_train, dim=1))
         validation_rmse = []
         model.train()
@@ -199,12 +202,16 @@ def visualization_points(n_points):
             optimizer.step()
 
             # Forward pass on the validation data, with torch.no_grad() for efficiency
+            n_epochs = n_epochs + 1
             with torch.no_grad():
                 displ_pred_val = model(points_val)
                 mse_loss_val = loss_func(displ_pred_val, displ_val)
                 rmse_loss_val = torch.sqrt(mse_loss_val)
                 validation_rmse.append(rmse_loss_val)
+                if (rmse_loss_val < 1e-03):
+                    break
 
+        print (f"RMSE {validation_rmse[-1]}, number of epochs {n_epochs}")
         # Visualize validation RMSE
         #plt.loglog()
         #plt.title("Validation loss RMSE")
@@ -235,12 +242,12 @@ def visualization_points(n_points):
         # Update time index
         local_time_index = local_time_index + 1
 
-        if client.poll_key("end_time_index", 10, 10):
+        if client.poll_key("end_time_index", 10, 100):
             print ("End time reached.")
             break
 
 except Exception as e:
     print("Caught an exception: ", str(e))
 
 finally:
-    exp.stop(db)
+    exp.stop(db)

run/meshMotion/cylinderMotion/cylinderMotionExperiment/.smartsim/telemetry/manifest.json

@@ -0,0 +1,92 @@
+{
+  "schema info": {
+    "schema_name": "entity manifest",
+    "version": "0.0.4"
+  },
+  "experiment": {
+    "name": "cylinderMotionExperiment",
+    "path": "/home/jin/OpenFOAM/openfoam-smartsim/run/meshMotion/cylinderMotion/cylinderMotionExperiment",
+    "launcher": "Local",
+    "out_file": "/home/jin/OpenFOAM/openfoam-smartsim/run/meshMotion/cylinderMotion/cylinderMotionExperiment/.smartsim/telemetry/logs/smartsim.out",
+    "err_file": "/home/jin/OpenFOAM/openfoam-smartsim/run/meshMotion/cylinderMotion/cylinderMotionExperiment/.smartsim/telemetry/logs/smartsim.err"
+  },
+  "runs": [
+    {
+      "run_id": "37755ce",
+      "timestamp": 1761598029919685939,
+      "model": [],
+      "orchestrator": [
+        {
+          "name": "orchestrator",
+          "type": "redis",
+          "interface": [
+            "lo"
+          ],
+          "shards": [
+            {
+              "name": "orchestrator_0",
+              "hostname": "127.0.0.1",
+              "port": 8000,
+              "cluster": false,
+              "conf_file": null,
+              "out_file": "/home/jin/OpenFOAM/openfoam-smartsim/run/meshMotion/cylinderMotion/cylinderMotionExperiment/.smartsim/telemetry/cylinderMotionExperiment/37755ce/database/orchestrator/orchestrator_0/orchestrator_0.out",
+              "err_file": "/home/jin/OpenFOAM/openfoam-smartsim/run/meshMotion/cylinderMotion/cylinderMotionExperiment/.smartsim/telemetry/cylinderMotionExperiment/37755ce/database/orchestrator/orchestrator_0/orchestrator_0.err",
+              "memory_file": "",
+              "client_file": "",
+              "client_count_file": "",
+              "telemetry_metadata": {
+                "status_dir": "/home/jin/OpenFOAM/openfoam-smartsim/run/meshMotion/cylinderMotion/cylinderMotionExperiment/.smartsim/telemetry/cylinderMotionExperiment/37755ce/database/orchestrator/orchestrator_0",
+                "step_id": null,
+                "task_id": "2713",
+                "managed": false
+              }
+            }
+          ]
+        }
+      ],
+      "ensemble": []
+    },
+    {
+      "run_id": "566a318",
+      "timestamp": 1761598030553112680,
+      "model": [
+        {
+          "name": "of_model",
+          "path": "/home/jin/OpenFOAM/openfoam-smartsim/run/meshMotion/cylinderMotion/cylinderMotionExperiment/of_model",
+          "exe_args": [
+            "-case",
+            "cylinder",
+            "-parallel"
+          ],
+          "run_settings": {
+            "exe": [
+              "/home/jin/OpenFOAM/OpenFOAM-v2412/platforms/linux64GccDPInt32Opt/bin/moveDynamicMesh"
+            ],
+            "run_command": "/usr/bin/mpirun",
+            "run_args": {
+              "np": "4"
+            }
+          },
+          "batch_settings": {},
+          "params": {},
+          "files": {
+            "Symlink": [],
+            "Configure": [],
+            "Copy": []
+          },
+          "colocated_db": {},
+          "telemetry_metadata": {
+            "status_dir": "/home/jin/OpenFOAM/openfoam-smartsim/run/meshMotion/cylinderMotion/cylinderMotionExperiment/.smartsim/telemetry/cylinderMotionExperiment/566a318/model/of_model",
+            "step_id": null,
+            "task_id": "2929",
+            "managed": false
+          },
+          "out_file": "/home/jin/OpenFOAM/openfoam-smartsim/run/meshMotion/cylinderMotion/cylinderMotionExperiment/.smartsim/telemetry/cylinderMotionExperiment/566a318/model/of_model/of_model.out",
+          "err_file": "/home/jin/OpenFOAM/openfoam-smartsim/run/meshMotion/cylinderMotion/cylinderMotionExperiment/.smartsim/telemetry/cylinderMotionExperiment/566a318/model/of_model/of_model.err"
+        }
+      ],
+      "orchestrator": [],
+      "ensemble": []
+    }
+  ]
+}

run/meshMotion/wingMotion/README.md

@@ -25,7 +25,7 @@ which creates `mesh-motion_MachineLearning`, which has sub-folders for the Smart
 Both `Allrun.LaplaceMeshMotion` and `Allrun.MachineLearningMeshMotion` will compute mesh quality metrics (most important ones are non-orthogonality and skewness), and `.foam` files that ParaView needs to recognize OpenFOAM folders. A paraview state file is prepared that compares the decrease in non-orthogonality, visualizing the difference between Laplace non-orthogonality and MLP non-orthogonality, run it as
 
 ```
-wingMotion> paraview --state=visualize-non-orth-difference.pvsm
+wingMotion> paraview --state=diff.pvsm
 ```
 
 This will show how the Laplace causes an increase of non-orthogonality at the worst possible place - next to the airfoil. The increase is up to 35 degrees, w.r.t a simple MLP. 

run/meshMotion/wingMotion/adam_lbfgs.py

@@ -0,0 +1,27 @@
+from torch.optim import Adam, LBFGS, Optimizer
+
+class Adam_LBFGS(Optimizer):
+    def __init__(self, params, switch_epochs, adam_params, lbfgs_params):
+        # defaults = dict(switch_epoch=switch_epoch, adam_params=adam_params, lbfgs_params=lbfgs_params)
+
+        self.switch_epochs = sorted(switch_epochs)
+        self.params = list(params)
+        self.adam = Adam(self.params, **adam_params)
+        self.lbfgs_params = lbfgs_params
+        # self.lbfgs = LBFGS(self.params, **lbfgs_params)
+
+        super(Adam_LBFGS, self).__init__(self.params, defaults={})
+
+        self.state['epoch'] = 0
+
+    def step(self, closure=None):
+        if self.state['epoch'] < self.switch_epochs[0]:
+            self.adam.step(closure)
+        else:
+            # (Re)start LBFGS optimizer
+            if self.state['epoch'] in self.switch_epochs:
+                print(f'Starting LBFGS optimizer at epoch {self.state["epoch"]}')
+                self.lbfgs = LBFGS(self.params, **self.lbfgs_params)
+            self.lbfgs.step(closure)
+
+        self.state['epoch'] += 1

run/meshMotion/wingMotion/annealing_scheduler.py

@@ -0,0 +1,13 @@
+import numpy as np
+
+def annealing_weight(epoch, T_start, T_end, sharpness=10):
+
+    if epoch < T_start:
+        return 0.0
+    elif epoch > T_end:
+        return 1.0
+    else:
+        # 标准化到 [0,1]
+        x = (epoch - T_start) / (T_end - T_start)
+        # S 型函数，中心点在 0.5
+        return float(1 / (1 + np.exp(-sharpness * (x - 0.5))))