Abstract: A method for adjusting laser control parameters of a laser additive manufacturing system for construction of a part is provided. The method may include performing a laser scan of a building surface, and detecting spectral and intensity response information indicative of at least a temperature at the building surface. The method may also include correlating the spectral and intensity response information with spatial positioning of the laser during the laser scan to generate spatially-correlated spectral and intensity response information.

Abstract: A method of performing non-destructive evaluation (NDE) of a part or assembly may include receiving image and modeling data for the part or assembly from multiple sources, employing a machine learning model to fuse the image and modeling data into tabular data and fused image data associating predicted stress values with respective locations of the part or assembly, and linking the tabular data and fused image data together for display.

Abstract: An additive manufacturing apparatus includes a laser and a detection system. The laser emits a laser beam to heat a powder bed to form a melt pool, and the melt pool emits light proportional to a temperature of the melt pool. The detection system includes a spectral disperser and one of a) two or more on-axis sensors or b) a line scanner. The two or more on-axis sensors or the line scanner are/is located along an axis of the emitted light, the detection system receives the emitted light from the melt pool, and an intensity of the emitted light detected by the a) two or more on-axis sensors or the b) line scanner is compared with a blackbody spectral map at a particular wavelength of the emitted light to determine a temperature of the melt pool.

Abstract: A method for monitoring and analyzing an additive manufacturing process includes heating a melt zone to fuse an additive media with an active layer to build a part being manufactured based on a part design model, capturing raw melt data of the melt zone, and generating an active layer dataset that is spatially defined. The method may also include analyzing the active layer dataset with respect to a plurality of defect signatures within a defect signature library. The defect signature library may be predefined based on a machine learning processing of historical sensor datasets with corresponding ground truth datasets. The method may also include detecting a defect in the part based on the analysis of the active layer dataset with respect to a plurality of defect signatures, simultaneously with the energy source acting upon the active layer of the part for manufacturing of the part.

Abstract: An improved transparent armor piercing protection system that acts as a vision window in an armor system. The transparent armor piercing protection system comprises ballistic plastic prisms with mirrored external surfaces disposed between armor plates so that the reflection of the image occurs entirely within the prism. The armor sheets are also redesigned with perforations to reduce weight while defeating incoming threats.

Abstract: An improved transparent armor piercing protection system that acts as a vision window in an armor system. The transparent armor piercing protection system comprises ballistic plastic prisms with mirrored external surfaces disposed between armor plates so that the reflection of the image occurs entirely within the prism. The armor sheets are also redesigned with perforations to reduce weight while defeating incoming threats.