# On the In-Die Conditions and Process Parameter Settings in Indirect Squeeze Casting

^{1}

^{2}

^{3}

^{*}

## Abstract

**:**

## 1. Background

## 2. Experimental Work

#### 2.1. Material

#### 2.2. Casting Process and Component

#### 2.3. Experimental Design

^{TM}software (StateEase Inc., Minneapolis, MN, USA). At each setting, 10 samples were taken. In the execution of the experiments, 10 dummy shots were made before sample taking to reach a new steady state for the new conditions. A total of 400 castings were made, of which 200 castings were evaluated. The data presented are the averages of the 10 evaluated runs at each set-point combination, Table 2.

## 3. Results and Discussion

#### 3.1. Process Parameter and Pressure Acceleration

_{2}/dt)

^{2}

_{Max}was evaluated as a function of the process parameters, Table 3. It should be noted that the pressure acceleration was transformed after a Box–Cox analysis suggesting the use of the natural logarithm.

^{2}are significant model terms. Values greater than 0.1000 were used to disregard model terms that were not significant. The lack-of-fit F-value of 0.57 implies the lack-of-fit is not significant relative to the pure error. There is a 79.72% chance that a lack-of-fit F-value this large could occur due to noise.

_{2}/dt)

^{2}

_{Max}and in the first stages speed is linear and similar to what Fiorese et al. [2] showed in their sensitivity analysis with nearly linear dependence. The acceleration of the pressure in the die (dP

_{2}/dt)

^{2}

_{Max}bears similar importance as the piston acceleration in Equation (1), and it is the large impact of the intensification pressure on both the rate of pressure acceleration and piston acceleration that is the focus of the current paper.

#### 3.2. Mathematical Analysis of the Correlation between In-Die Pressure and the Process Parameters

^{6}/s

^{2}), and Q is the volumetric flow (m

^{3}/s). Variations in speed and pressure affect the pump and the volumetric flow, which can be evaluated by taking the time derivative of Equation (3) as:

^{2}) at 3 in Figure 3 and v is piston speed (m/s). Taking the derivative of Equation (6) and reintroducing it into Equation (5) allows for the elimination of the volumetric flow, expressing the relationship between pressure and piston speed:

## 4. Concluding Remarks

_{2}/dt)

^{2}

_{Max}, translates to an increase of ${\alpha}_{RMS}$. However, it must be stressed that this interaction has a more far-reaching influence than the actual speed setting. Furthermore, this also pinpoints the need for improvements in the hydraulics system designs to decouple the intensification pressure from the filling piston motion control.

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

## References

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**Figure 1.**The component illustrating the metal levels for the switch points during filling [4].

**Figure 2.**The level of acceleration, (dP

_{2}/dt)

^{2}

_{Max}, between the first and second phase filling as a function of B-First phase speed and C-Intensification pressure.

**Figure 3.**Schematic drawing of the plunger intensifier with, 1—pump, 2—conical on-off valve, 3—hydraulic cylinder, 4—conical proportional/servo valve and 5—oil tank.

**Figure 4.**The level of acceleration between the first and second phase filling as a function of B-First phase speed and C-Intensification pressure according to Equation (38) with: (

**a**) squared values (dP

_{2}/dt)

^{2}

_{Max}for comparison with the ANOVA model; and (

**b**) actual predicted acceleration values (dP

_{2}/dt)

_{Max}.

Si | Mg | Fe | Cu | Zn | Mn | Ti | Al |
---|---|---|---|---|---|---|---|

6.5–7.5 | 0.25–0.45 | 0.2 | 0.2 | 0.2 | 0.1 | 0.1 | Bal |

**Table 2.**Experimental plan and results [4].

Run | Switch Point (mm) | First Phase Speed Valve Setting (%) | Intensification Pressure (%) | (dP_{2}/dt)^{2}_{Max} | (P_{2})_{Max} |
---|---|---|---|---|---|

1 | 85 | 6 | 50 | 3.6854 × 10^{10} | 40.41 |

2 | 60 | 6 | 24 | 2.6095 × 10^{10} | 43.04 |

3 | 100 | 18 | 50 | 4.885 × 10^{10} | 43.58 |

4 | 60 | 12 | 22 | 2.974 × 10^{10} | 49.99 |

5 | 100 | 6 | 10 | 9.476 × 10^{09} | 40.61 |

6 | 100 | 10 | 33 | 5.6366 × 10^{10} | 49.65 |

7 | 76 | 18 | 33 | 5.746 × 10^{10} | 51.06 |

8 | 76 | 10 | 10 | 9.745 × 10^{09} | 46.82 |

9 | 60 | 6 | 50 | 5.24 × 10^{10} | 45.16 |

10 | 60 | 18 | 10 | 9.786 × 10^{09} | 47.76 |

11 | 100 | 18 | 10 | 7.937 × 10^{09} | 49.27 |

12 | 100 | 18 | 50 | 6.0679 × 10^{10} | 46.75 |

13 | 60 | 13 | 50 | 6.303 × 10^{10} | 46.25 |

14 | 100 | 10 | 33 | 5.2326 × 10^{10} | 46.49 |

15 | 82 | 14 | 50 | 9.077 × 10^{10} | 50.57 |

16 | 60 | 18 | 10 | 2.3336 × 10^{10} | 39.16 |

18 | 82 | 6 | 23 | 7.613 × 10^{09} | 22.30 |

19 | 100 | 18 | 10 | 2.299 × 10^{10} | 24.51 |

20 | 72 | 9 | 37 | 1.2035 × 10^{10} | 37.90 |

Source | Sum of Squares | df | Mean Square | F-Value | p-Value | |
---|---|---|---|---|---|---|

Model | 11.25 | 3 | 3.75 | 51.76 | <0.0001 | significant |

B-First phase | 0.4020 | 1 | 0.4020 | 5.55 | 0.0316 | significant |

C-Intensification | 9.69 | 1 | 9.69 | 133.72 | <0.0001 | significant |

C^{2} | 1.37 | 1 | 1.37 | 18.90 | 0.0005 | significant |

Residual | 1.16 | 16 | 0.0725 | |||

Lack-of-fit | 0.6448 | 11 | 0.0586 | 0.5697 | 0.7972 | not significant |

Pure Error | 0.5145 | 5 | 0.1029 | |||

Cor Total | 12.41 | 19 |

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**MDPI and ACS Style**

Jarfors, A.E.W.; Du, A.; Zhou, J.; Zheng, J.; Yu, G.
On the In-Die Conditions and Process Parameter Settings in Indirect Squeeze Casting. *Technologies* **2022**, *10*, 29.
https://doi.org/10.3390/technologies10010029

**AMA Style**

Jarfors AEW, Du A, Zhou J, Zheng J, Yu G.
On the In-Die Conditions and Process Parameter Settings in Indirect Squeeze Casting. *Technologies*. 2022; 10(1):29.
https://doi.org/10.3390/technologies10010029

**Chicago/Turabian Style**

Jarfors, Anders E. W., Andong Du, Jie Zhou, Jinchuan Zheng, and Gegang Yu.
2022. "On the In-Die Conditions and Process Parameter Settings in Indirect Squeeze Casting" *Technologies* 10, no. 1: 29.
https://doi.org/10.3390/technologies10010029