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Josh Fody

Publications and source records attributed to Josh Fody.

6 records
All sourcesNASA NTRSDOE OSTI
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High Temperature Material Property Data and Challenges to Thermal Process Model Predictions and In-Situ/Ex-Situ Measurements for Metallic Additive Manufacturing

Understanding and predicting performance properties of parts produced by metallic additive manufacturing has improved significantly over the past decade; however, difficult to measure material properties and process outcomes continue to be challenges. The qualification or certification of aerospace parts require extensive measures to quantify variable part properties in order to buy down the risk of component failure. The variability, inherent to the additive manufacturing, process adds unwanted uncertainty in the production of load critical structural components. Process modeling has proven valuable in providing predictions and context for understanding outcomes of the additive manufacturing process; however, these physically informed process models require material properties at temperatures that are difficult to measure and rarely available. Further, calibrating or validating such models is difficult because the process itself is challenging to measure. This talk will explore some of the challenges resulting from difficult to acquire input data by relating thermal process model predictions to in-situ and ex-situ optical microscopy measurements.

Process Model↗
NASA NTRSDate not supplied

Automated Probabilistic Finite Element Model Calibration Tool Based on Uncertainty Quantification and Machine Learning

Qualification and certification of safety critical parts is a hurdle to the adoption of metallic additively manufactured components for aerospace vehicle applications. Challenges include variability in part properties due to inconsistent defect distribution and microstructure. Understanding of the process through finite element modeling (FEM), and process control through in-situ monitoring, may result in significant improvements; however, solutions useful to manufacturers will require large volumes of data and automated data utilization. Toward this end, a generalizable automated FEM calibration paradigm is developed. This paradigm leverages existing and novel tools from machine learning and uncertainty quantification to enable the automatic calibration of FEMs without requiring prior knowledge of the model performance across input parameter space, including meshing and solver settings, which can require time consuming manual model probing or cause noisy and inconsistent predictions. The result is a probabilistic distribution of calibrated and validated FEM input parameters targeting measured data.

Additive manufacturing model calibration finite el↗
NASA NTRSDate not supplied

Finite Element Thermal Model for Ultrasonic Welding of Thermoplastic Composites

Ultrasonic welding, UW, is a fast and energy-efficient technique for joining thermoplastic composites. It involves the use of high-frequency mechanical vibrations and a static welding force to melt and join adherends. Ultrasonic welding is an enabling technology to reduce the cost and complexity of in-space construction because lightweight thermoplastic composite components can be packaged compactly for launch and then efficiently assembled using supervised autonomous robotic technologies on site. However, the temperatures in space present challenges to UW, and it is critical that the efficacy of process parameters selected for manufacturing in space is understood prior to launch. To this end, a three-dimensional finite element model is presented in this technical presentation. The model incorporates equations for effects of viscoelastic heating and heat transfer on the welding process. The proposed model is applied to predict the temperature distribution in single lap shear, SLS, samples composed of AS4/PEEK (TC1200) composite that were welded using a terrestrial machine as part of a comprehensive weldability study. Thermocouple and infrared spot sensor data from the SLS samples provide empirical temperature measurements for calibration and validation of the UW thermal model. Calibration and validation of the model is an important step given the significant uncertainties in material properties such as the loss modulus and necessary assumptions in the physics implementations which allow the model to converge in an acceptable amount of time. The validated thermal model can be used to simulate the process for the space environment. Future validation sample testing is planned in a vacuum chamber. The result will be a model capable of guiding process parameter selection to ensure acceptable weld bonds when manufacturing in space.

Josh Fody↗