公开(公告)号：US20210334685A1

公开(公告)日：2021-10-28

申请号：US16859349

申请日：2020-04-27

Applicant: Raytheon Technologies Corporation

Inventor： Masoud Anahid ,  Tahany Ibrahim El-Wardany ,  Sergei F. Burlatsky ,  William K. Tredway

IPC: G06N7/00 ,  G05B19/4099

Abstract: A method of evaluating an additive manufacturing process includes receiving a set of additive manufacturing parameters and an additive manufacturing part design at an analysis module, receiving a set of random values at the analysis module, determining a probability distribution of stochastic flaws within a resultant additively manufactured article using at least one multidimensional space physics model, and categorizing the additive manufacturing part design as defect free when the probability distribution is below a predefined threshold. Each value in the set of random values corresponds to a distinct variable in a set of variables. Each variable in the set of variables at least partially defines at least one of an uncontrolled additive manufacturing parameter and an uncontrollable additive manufacturing parameter.

公开(公告)号：US20230315946A1

公开(公告)日：2023-10-05

申请号：US18194937

申请日：2023-04-03

Applicant: Raytheon Technologies Corporation

Inventor： Sergei F. Burlatsky ,  David U. Furrer ,  Vasisht Venkatesh ,  Ryan B. Noraas ,  Stephen J. Barker

IPC: G06F30/20

CPC classification number: G06F30/20 ,  G06F2111/08

Abstract: The present disclosure provides advantageous probabilistic models and applications for component (e.g., titanium component) design optimization, and related methods of use. More particularly, the present disclosure provides advantageous probabilistic models, systems and applications for component design optimization and related methods of use, and where the probabilistic models, systems and applications can accurately predict the life/failure of components (e.g., titanium components) based on material microstructure statistics and/or product mission specifics and/or variations. Disclosed are probabilistic systems and methods for predicting dwell fatigue behavior of a component (e.g., titanium component). The present disclosure advantageously provides an analytical modeling framework that captures the various physics-based mechanisms for dwell fatigue damage accumulation, crack nucleation, crack propagation and fracture in components or materials (e.g., anisotropic components/materials). The probabilistic modeling framework thereby enables the prediction of dwell fatigue behavior as a function of microstructure (e.g., material microstructure statistics) and/or loading conditions (e.g., product mission specifics).

公开(公告)号：US20230313409A1

公开(公告)日：2023-10-05

申请号：US18194931

申请日：2023-04-03

Applicant: Raytheon Technologies Corporation

Inventor： Sergei F. Burlatsky ,  David U. Furrer

IPC: C30B25/06 ,  C30B25/04 ,  C30B29/22

CPC classification number: C30B25/06 ,  C30B25/04 ,  C30B29/22

Abstract: Disclosed herein is a suspension plasma spray process that comprises suspending metal oxide particles in a carrier fluid to produce a suspension. The suspension is ejected onto a substrate via a plasma flame. The particles are evaporated in the plasma flame to form a gaseous ceramic during their travel to the substrate. The gaseous ceramic is deposited on the substrate to form columnar grains.

公开(公告)号：US11531920B2

公开(公告)日：2022-12-20

申请号：US16859349

申请日：2020-04-27

Applicant: Raytheon Technologies Corporation

Inventor： Masoud Anahid ,  Tahany Ibrahim El-Wardany ,  Sergei F. Burlatsky ,  William K. Tredway

IPC: G06N7/00 ,  G05B19/4099

Abstract: A method of evaluating an additive manufacturing process includes receiving a set of additive manufacturing parameters and an additive manufacturing part design at an analysis module, receiving a set of random values at the analysis module, determining a probability distribution of stochastic flaws within a resultant additively manufactured article using at least one multidimensional space physics model, and categorizing the additive manufacturing part design as defect free when the probability distribution is below a predefined threshold. Each value in the set of random values corresponds to a distinct variable in a set of variables. Each variable in the set of variables at least partially defines at least one of an uncontrolled additive manufacturing parameter and an uncontrollable additive manufacturing parameter.

公开(公告)号：US20240416424A1

公开(公告)日：2024-12-19

申请号：US18334179

申请日：2023-06-13

Applicant: Raytheon Technologies Corporation

Inventor： Sergei F. Burlatsky ,  Andreas Karl Roelofs ,  Masoud Anahid ,  Ranadip Acharya ,  Tahany El-Wardany ,  David U. Furrer

IPC: B22F10/85 ,  B22F10/28 ,  B22F12/20 ,  B33Y10/00 ,  B33Y40/20 ,  B33Y50/02

Abstract: The present disclosure provides improved additive manufacturing methods and systems. More particularly, the present disclosure provides advantageous additive manufacturing methods and systems for the production of hierarchical design optimized components (e.g., composite or composite-like materials). The present disclosure provides a methodology to produce hierarchical design optimized additively manufactured parts/materials that include an inhomogeneous structure with variable local mechanical properties across the entire volume. Hierarchical inhomogeneous structure/composite materials can be produced through a laser powder bed fusion (LPBF) process. A novel LPBF method can be used to obtain location-specific properties through in-situ controlling of the local cooling rate during the additive manufacturing process.

公开(公告)号：US20230321763A1

公开(公告)日：2023-10-12

申请号：US18126596

申请日：2023-03-27

Applicant: Raytheon Technologies Corporation

Inventor： David U. Furrer ,  Sergei F. Burlatsky

IPC: G01N33/207 ,  B23K31/12 ,  G06F30/20

CPC classification number: B23K31/125 ,  G01N33/207 ,  G06F30/20

Abstract: Examples described herein provide a method that includes receiving weld data about a weld. The method further includes analyzing, using a physics-based model, the weld data to predict a formation of a defect in the weld. The method further includes providing feedback to enable process optimization during a design stage or active control during welding to control a welding machine to correct for and eliminate the formation of the defect in the weld.