Abstract: A method, medium, and system including determining a material property value to assign to each of the plurality of 3D volume elements, wherein the material property values assigned to the plurality of 3D volume elements are classified into a predetermined number of bins that correspond to a plurality of different additive manufacturing (AM) print parameter sets, generating a plurality of transfer functions to determine relationships between the material property values assigned to the plurality of 3D volume elements and a plurality of desired AM print parameter sets, automatically determining, based on the plurality of transfer functions, an assignment of one of the plurality of different AM print parameter sets to each of the plurality of 3D volume elements, and validating the determined assignments of the plurality of different AM print parameter sets for the plurality of 3D volume elements based on the plurality of transfer functions.

Abstract: Methods and apparatus for sensor-based part development are disclosed. An example apparatus includes at least one memory, instructions in the apparatus, and processor circuitry to execute the instructions to translate at least one user-defined material property selection into a desired process observable, the desired process observable including a meltpool property, perform voxel-based autozoning of an input part geometry, the input part geometry based on a computer-generated design, and output a voxelized reference map for the input part geometry based on the desired process observable and the voxel-based autozoning.

Abstract: A method of testing a multi-specimen additive manufacturing build plate includes acquiring and installing the multi-specimen build plate in a test system, aligning one or more force exertion tools with respective selected specimens, imparting a force on the selected specimen(s), collecting test data from each selected specimen, and analyzing the collected data to identify a potential correlation between material behavior for the selected specimen and its applied manufacturing build parameter(s). A system and a non-transitory medium are also disclosed.

Abstract: A method, medium, and system including determining a material property value to assign to each of the plurality of 3D volume elements, wherein the material property values assigned to the plurality of 3D volume elements are classified into a predetermined number of bins that correspond to a plurality of different additive manufacturing (AM) print parameter sets, generating a plurality of transfer functions to determine relationships between the material property values assigned to the plurality of 3D volume elements and a plurality of desired AM print parameter sets, automatically determining, based on the plurality of transfer functions, an assignment of one of the plurality of different AM print parameter sets to each of the plurality of 3D volume elements, and validating the determined assignments of the plurality of different AM print parameter sets for the plurality of 3D volume elements based on the plurality of transfer functions.

Abstract: A method, medium, and system to automatically determine parameter sets for an additive manufacturing (AM) of a part, the method including executing a load analysis on a model of a part to emulate a load on each of a plurality of regions of the part; determining a representation of the model of the part as a plurality of discrete three-dimensional (3D) volume elements; determining, based on an output of the load analysis, a life or material property value to assign to each of the plurality of 3D volume elements; automatically determining an assignment of one of a plurality of additive manufacturing (AM) print parameter sets to each of the plurality of 3D volume elements; and saving a record of the determined assignments of the AM print parameter sets to each of the plurality of 3D volume elements.

Abstract: A method of additive manufacturing machine (AMM) build process control includes obtaining AMM machine and process parameter settings, accessing sensor data for monitored physical conditions in the AMM, calculating a difference between expected AMM physical conditions and elements of the monitored conditions, providing the machine and process parameter settings, monitored conditions, and differences to one or more material property prediction models, computing a predicted value or range for the monitored conditions, comparing the predicted value or range to a predetermined target range, based on a determination that predicted value(s) are within the predetermined range, maintaining the machine and process parameter settings, or based on a determination that one or more of the predicted value(s) is outside the predetermined range, generating commands to compensate the machine and process parameter settings, and repeating the closed feedback loop at intervals of time during the build process.

Abstract: A method, medium, and system to automatically determine parameter sets for an additive manufacturing (AM) of a part, the method including executing a load analysis on a model of a part to emulate a load on each of a plurality of regions of the part; determining a representation of the model of the part as a plurality of discrete three-dimensional (3D) volume elements; determining, based on an output of the load analysis, a life or material property value to assign to each of the plurality of 3D volume elements; automatically determining an assignment of one of a plurality of additive manufacturing (AM) print parameter sets to each of the plurality of 3D volume elements; and saving a record of the determined assignments of the AM print parameter sets to each of the plurality of 3D volume elements.

Abstract: A method of testing a multi-specimen additive manufacturing build plate includes acquiring and installing the multi-specimen build plate in a test system, aligning one or more force exertion tools with respective selected specimens, imparting a force on the selected specimen(s), collecting test data from each selected specimen, and analyzing the collected data to identify a potential correlation between material behavior for the selected specimen and its applied manufacturing build parameter(s). A system and a non-transitory medium are also disclosed.

Abstract: A method of additive manufacturing machine (AMM) build process control includes obtaining AMM machine and process parameter settings, accessing sensor data for monitored physical conditions in the AMM, calculating a difference between expected AMM physical conditions and elements of the monitored conditions, providing the machine and process parameter settings, monitored conditions, and differences to one or more material property prediction models, computing a predicted value or range for the monitored conditions, comparing the predicted value or range to a predetermined target range, based on a determination that predicted value(s) are within the predetermined range, maintaining the machine and process parameter settings, or based on a determination that one or more of the predicted value(s) is outside the predetermined range, generating commands to compensate the machine and process parameter settings, and repeating the closed feedback loop at intervals of time during the build process.

Abstract: A modular fan inlet ice protection system includes a center ring, an outer ring and a plurality of struts. The struts are each coupled at a first end to the center ring, and at a second end to the outer ring. A plurality of shell members are each configured to be removably coupled to a corresponding strut. Moreover, the shell members each include an electrothermal heater element. Preferably the system further includes a plurality of inlet guide vanes each including an electrothermal heater element.