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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2013

Dynamics and Control of a Disordered System in Space

In this paper, we present some ideas regarding the modeling, dynamics and control aspects of granular spacecraft. Granular spacecraft are complex multibody systems composed of a spatially disordered distribution of a large number of elements, for instance a cloud of N grains in orbit, with N greater than 10(exp 3). These grains can be large (Cubesat-size) or small (mm-size), and can be active, i.e., a fully equipped vehicle capable sensing their own position and attitude, and enabled with propulsion means, or entirely passive. The ultimate objective would be to study the behavior of the single grains and of large ensembles of grains in orbit and to identify ways to guide and control the shape of a cloud composed of these grains so that it can perform a useful function in space, for instance, as an element of an optical imaging system for astrophysical applications. This concept, in which the aperture does not need to be continuous and monolithic, would increase the aperture size several times compared to large NASA observatories such as ATLAST, allowing for a true Terrestrial Planet Imager that would be able to resolve exo-planet details and do meaningful spectroscopy on distant world. In the paper, we address the modeling and autonomous operation of a distributed assembly (the cloud) of large numbers of highly miniaturized space-borne elements (the grains). A multi-scale, multi-physics model is proposed of the dynamics of the cloud in orbit, as well as a control law for cloud shape maintenance, and preliminary simulation studies yield an estimate of the computational effort, indicating a scale factor of approximately N(exp 1.4) as a function of the number of grains. A granular spacecraft can be defined as a collection of a large number of space-borne elements (in the 1000s) designed and controlled such that a desirable collective behavior emerges, either from the interactions among neighboring grains, and/or between the grains and the environment. In this paper, each grain is considered to be a highly miniaturized spacecraft which has limited size and mass, hence it has limited actuation, limited propulsive capability, limited power, limited sensing, limited communication, limited computational resources, limited range of motion, limited lifetime, and may be expendable. The modeling and dynamics of clouds of vehicles is more challenging than with conventional vehicles because we are faced with a probabilistic vehicle composed of a large number of physically disconnected vehicles. First, different scales of motion occur simultaneously in a cloud: translations and rotations of the cloud as a whole (macro-dynamics), relative rotation and translation of one cloud member with respect to another (meso-dynamics), and individual cloud member dynamics (micro-dynamics). Second, the control design needs to be tolerant of the system complexity, of the system architecture (centralized vs. decentralized large scale system control) as well as robust to un-modeled dynamics and noise sources. Figure 1, top left, shows the kinematic parameters of a 1000 element cloud in orbit. The motion of the system is described with respect to a local vertical-local horizontal (LV-LH) orbiting reference frame (x,y,z)=F(sub ORF) of origin O(sub ORF) which rotates with mean motion omega and orbital semi-major axis R(sub 0). The orbital geometry at the initial time is defined in terms of its six orbital elements, and the orbital dynamics equation for point O(sub ORF) is propagated forward in time under the influence of the gravitational field of the primary and other external perturbations, described below. The origin of this frame coincides with the initial position of the center of mass of the system, and the coordinate axes are z along the local vertical, x toward the flight direction, and y in the orbit normal direction. The assumptions we used to model the dynamics are as follows: 1) The inertial frame is fixed at Earth's center. 2) The orbiting Frame ORF follows Keplerian orbit. 3) the cloud system dynamics is referred to ORF. 4) the attitude of each grain uses the principal body frame as body fixed frame. 5) the atmosphere is assumed to be rigidly rotating with the Earth. Regarding the grains forming the cloud: 1) each grain is modeled as a rigid body; 2) a simple attitude estimator provides attitude estimates, 3) a simple guidance logic commands the position and attitude of each grain, 4) a simple local feedback controller based on PD control of local states is used to stabilize the attitude of the vehicle. Regarding the cloud: 1) the cloud as a whole is modeled as an equivalent rigid body in orbit, and 2) an associated graph establishes agent connectivity and enables coupling between modes of motion at the micro and macro scales; 3) a simple guidance and estimation logic is modeled to estimate and command the attitude of this equivalent rigid body; 4) a cloud shape maintenance controller is based on the dynamics of a stable virtual truss in the orbiting frame. Regarding the environmental perturbations acting on the cloud: 1) a non-spherical gravity field including JO (Earth's spherical field) zonal component, J2 (Earth's oblateness) and J3 zonal components is implemented; 2) atmospheric drag is modeled with an exponential model; 3) solar pressure is modeled assuming the Sun is inertially fixed; and 4) the Earth's magnetic field is model using an equivalent dipole model. The equations of motion are written in a referential system with respect to the origin of the orbiting frame and the state is propagated forward in time using an incremental predictor-corrector scheme. A representative cloud with varying number of grains is simulated to identify the limitations in computation time as the number of grains grows. We derive a control law to track a desired surface in the ORF (equivalently to maintain a reference cloud shape) by defining an error from a desired surface shape, and designing a control law that is exponentially stable and reduces the tracking error to zero. Figure 1 (top right) shows a comparison of various requirements for simulation of single spacecraft vs. granular spacecraft, indicating the high degree of complexity that needs to be taken into consideration. The ORF components of control force required by one of the grains is, for this particular case, in the micro-Newton range. However, no attempt has been made yet to reconfigure (or re-orient) the cloud configuration internally, for which forces in the milli-Newton level are expected, depending on the time required to do the reconfiguration. Figure 1, bottom, shows the computation time as a function of the number of grains, indicating an order N(exp 1.43) scaling on a 8 Gb, 1067 MHz RAM MacOSX computer with a 3.06 GHz Intel Core 2 Duo processor. With this metric, the same simulation for a system of N=1000 grains would take 5.4 hours, and 146 hours (i.e., 6 days) for a system with N=10,000 grains. Therefore, efficient ways to simulate this complex system, where not only the time scales of natural system dynamics, but also the sampling times of the Guidance, Navigation, and Control are included, remain to be explored. Additional details on the cloud modeling, dynamics, and control will be described in the paper.

simulation↗
NASA NTRS2015

A 1-D Model of the 4 Bed Molecular Sieve of the Carbon Dioxide Removal Assembly

Developments to improve system efficiency and reliability for water and carbon dioxide separation systems on crewed vehicles combine sub-scale systems testing and multi-physics simulations. This paper describes the development of COMSOL simulations in support of the Life Support Systems (LSS) project within NASA's Advanced Exploration Systems (AES) program. Specifically, we model the 4 Bed Molecular Sieve (4BMS) of the Carbon Dioxide Removal Assembly (CDRA) operating on the International Space Station (ISS).

Coker, Robert↗
NASA NTRS2016

A Virtual Laboratory for the 4 Bed Molecular Sieve of the Carbon Dioxide Removal Assembly

Ongoing work to improve water and carbon dioxide separation systems to be used on crewed space vehicles combines sub-scale systems testing and multi-physics simulations. Thus, as part of NASA's Advanced Exploration Systems (AES) program and the Life Support Systems Project (LSSP), fully predictive COMSOL Multiphysics models of the Four Bed Molecular Sieve (4BMS) of the Carbon Dioxide Removal Assembly (CDRA) on the International Space Station (ISS) have been developed. This Virtual Laboratory is being used to help reduce mass, power, and volume requirements for exploration missions. In this paper we describe current and planned modeling developments in the area of carbon dioxide removal to support future missions as well as the resolution of anomalies observed in the ISS CDRA.

Coker, Robert↗
NASA NTRS2017

An Efficient Modelling Approach for Prediction of Porosity Severity in Composite Structures

Porosity, as a manufacturing process-induced defect, highly affects the mechanical properties of cured composites. Multiple phenomena affect the formation of porosity during the cure process. Porosity sources include entrapped air, volatiles and off-gassing as well as bag and tool leaks. Porosity sinks are the mechanisms that contribute to reducing porosity, including gas transport, void shrinkage and collapse as well as resin flow into void space. Despite the significant progress in porosity research, the fundamentals of porosity in composites are not yet fully understood. The highly coupled multi-physics and multi-scale nature of porosity make it a complicated problem to predict. Experimental evidence shows that resin pressure history throughout the cure cycle plays an important role in the porosity of the cured part. Maintaining high resin pressure results in void shrinkage and collapse keeps volatiles in solution thus preventing off-gassing and bubble formation. This study summarizes the latest development of an efficient FE modeling framework to simulate the gas and resin transport mechanisms that are among the major phenomena contributing to porosity.

Bedayat, Houman↗
NASA NTRS2015

Development of the US3D Code for Advanced Compressible and Reacting Flow Simulations

Aerothermodynamics and hypersonic flows involve complex multi-disciplinary physics, including finite-rate gas-phase kinetics, finite-rate internal energy relaxation, gas-surface interactions with finite-rate oxidation and sublimation, transition to turbulence, large-scale unsteadiness, shock-boundary layer interactions, fluid-structure interactions, and thermal protection system ablation and thermal response. Many of the flows have a large range of length and time scales, requiring large computational grids, implicit time integration, and large solution run times. The University of Minnesota NASA US3D code was designed for the simulation of these complex, highly-coupled flows. It has many of the features of the well-established DPLR code, but uses unstructured grids and has many advanced numerical capabilities and physical models for multi-physics problems. The main capabilities of the code are described, the physical modeling approaches are discussed, the different types of numerical flux functions and time integration approaches are outlined, and the parallelization strategy is overviewed. Comparisons between US3D and the NASA DPLR code are presented, and several advanced simulations are presented to illustrate some of novel features of the code.

CFD↗
NASA NTRS2018

GT SUITE Fuel Cell Model Validation with Power Module Test Data

The AES Modular Power Systems (AMPS) Fuel Cell team at the NASA Glenn Research Center (GRC) has created a Microsoft Excel model of a regenerative fuel cell (RFC) system for potential lunar and Martian applications. Due to some limitations of this model, including the ability to predict transient effects in the thermal and fluidic performance of the system, a system-level transient thermal/fluids model was desired. GT-SUITE is a transient multi-physics simulation tool that is popular in the automotive industry and has a built in template for proton exchange membrane (PEM) fuel cells. However, terrestrial fuel cells used in the automotive industry vary significantly from aerospace fuel cells. A validation effort was undertaken to compare GT SUITE model results to actual data collected during the 2015 AMPS Power Module Demonstration in which the AMPS team used a PEM fuel cell system to power a 478 kg rover assembly at the Dunes test site located at GRC. The purpose of the model was to evaluate the efficacy of using GT SUITE to model a non-flow through PEM fuel cell system. The validation effort examined electrochemical performance including fuel cell stack voltage and power supplied, the thermal performance of the stack namely stack temperature and heat rejection rates, and the fluidic performance of the system including pressures, reactant consumption, and water production rates.

Gilligan, Ryan↗
NASA NTRS2018

Fuel Cell Model Validation with Power Module Test Data

The AES Modular Power Systems (AMPS) Fuel Cell team at the NASA Glenn Research Center (GRC) has created a Microsoft Excel model of a regenerative fuel cell (RFC) system for potential lunar and Martian applications. Due to some limitations of this model, including the ability to predict transient effects in the thermal and fluidic performance of the system, a system-level transient thermal/fluids model was desired. GT-SUITE is a transient multi-physics simulation tool that is popular in the automotive industry and has a built-in template for proton exchange membrane (PEM) fuel cells. However, terrestrial fuel cells used in the automotive industry vary significantly from aerospace fuel cells. A validation effort was undertaken to compare GT SUITE model results to actual data collected during the 2015 AMPS (Advanced Exploration Systems (AES) Modular Power Systems) Power Module Demonstration in which the AMPS team used a PEM fuel cell system to power a 478 kilogram rover assembly at the Dunes test site located at GRC. The purpose of the model was to evaluate the efficacy of using GT SUITE to model a non-flow through PEM fuel cell system. The validation effort examined electrochemical performance including fuel cell stack voltage and power supplied, the thermal performance of the stack namely stack temperature and heat rejection rates, and the fluidic performance of the system including pressures, reactant consumption, and water production rates.

Model Validation↗
NASA NTRS2019

Plasma Science in Planetary Entry

Spacecraft entering a planetary atmosphere dissipate a great deal of energy into the surrounding gas. In the frame of reference of the vehicle, the atmospheric gas suddenly decelerates from hypersonic (Mach ~5-50) to subsonic velocities. The kinetic energy of the gas is rapidly converted to thermal and chemical energy, forming a bow shock behind which a plasma with energies on the order of one electron volt (eV) is produced. The resulting shock layer relaxes from strong thermal non-equilibrium that is translationally hot but internally cold and un-ionized toward a thermochemically equilibrated plasma over a distance of a few centimeters. Composition is dependent upon the planetary atmosphere – Air for Earth, CO2/N2 for Mars and Venus, N2/CH4 for Titan and H2/He/CH4 for Saturn, Neptune and Jupiter. Typical velocities of entry may range from 3-7 km/s (4-25 MJ/kg) for Titan/Mars, 8-14 km/s (30-100 MJ/kg) for Earth/Venus, and 25-40 km/s (300-800 MJ/kg) for outer planets. The equilibrium plasmas produced from these conditions are highly dissociated (up to and above 99%) and ionized (0.1- 15%), with temperatures from 7,000-15,000K and pressures from 0.1-1.0 bar. Understanding the behavior of these plasmas – the way in which they approach equilibrium, how they radiate, and how they interact with materials – is an active area of research necessitated by requirements to predict and test the performance of thermal protection systems (TPS) that enable spacecraft to deliver scientific instruments, and people, to foreign worlds and back to Earth. The endeavor is a multi-physics problem, with key processes highlighted in Fig. 1. This white paper describes the current state of the art in simulating shock layer plasmas both computationally and in ground test facilities. Gaps requiring further research and development are identified.

Cruden, Brett A.↗
NASA NTRS2017

Heating and Thermal Control of Brazing Technique to Break Contamination Path for Potential Mars Sample Return

The potential return of Mars sample material is of great interest to the planetary science community, as it would enable extensive analysis of samples with highly sensitive laboratory instruments. It is important to make sure such a mission concept would not bring any living microbes, which may possibly exist on Mars, back to Earth’s environment. In order to ensure the isolation of Mars microbes from Earth’s Atmosphere, a brazing sealing and sterilizing technique was proposed to break the Mars-to-Earth contamination path. Effectively, heating the brazing zone in high vacuum space and controlling the sample temperature for integrity are key challenges to the implementation of this technique. The break-the-chain procedures for container configurations, which are being considered, were simulated by multi-physics finite element models. Different heating methods including induction and resistive/radiation were evaluated. The temperature profiles of Martian samples in a proposed container structure were predicted. The results show that the sealing and sterilizing process can be controlled such that the samples temperature is maintained below the level that may cause damage, and that the brazing technique is a feasible approach to breaking the contamination path.

Bao, Xiaoqi↗
NASA NTRS2019

eddy Users Manual

eddy is a collection of tools - nonlinear solvers, meshing, post-processing, visualization, optimization, etc. - for performing scale-resolving simulations of multi-physics applications. The framework is designed to enable advanced R&D on a variety of topics by leveraging a mature capability for scale resolving simulations, and simultaneously be an appropriate tool for application analysis and support. Currently, eddy is at a relatively low technical readiness level (TRL), and users and developers should maintain appropriate expectations. The technical details behind eddy are outlined in several publications which can be consulted for more information [1–10]. The solvers are built around an unstructured high-order capability, and heavily utilize the tensor product sum-factorization approach for efficiency. The unsteady formulation utilizes a fully implicit space-time approach with a matrix-free Newton- Krylov method. A primitive steady-state solver is available for testing purposes, but is not expected to converge for all but simple verification cases. The Navier-Stokes fluid solvers do not support either RANS or hybrid-RANS capability, only LES and wall-modeled LES approaches. All of the solvers within eddy support three modes of operation: a primal solve of the full nonlinear problem, and two linearization approaches of the primal solve - the ad joint and the tangent solution. Details on how to select and use these three modes are outlined in Sec. 3.

Murman, Scott M.↗
NASA NTRS2020

LAURA Users Manual: 5.6

This users manual provides in-depth information concerning installation and execution of Laura, version 5. Laura is a structured, multiblock, computational aerothermodynamic simulation code. Version 5 represents a major refactoring of the original Fortran 77 Laura code toward a modular structure afforded by Fortran 95. The refactoring improved usability and maintainability by eliminating the requirement for problem-dependent recompilations, providing more intuitive distribution of functionality, and simplifying inter- faces required for multi-physics coupling. As a result, Laura now shares gas-physics modules, MPI modules, and other low-level modules with the Fun3D unstructured-grid code. In addition to internal refactoring, several new features and capabilities have been added, e.g., a GNU-standard installation process, parallel load balancing, automatic trajectory point sequencing, free-energy minimization, and coupled ablation and flow field radiation.

Aerodynamics↗
NASA NTRS2020

Modeling Electrolytic Conversion of Metabolic CO2 and Optimizing a Macrofluidic Electrochemical Reactor for Advanced Closed Loop Life Support Systems

The International Space Station (ISS) is currently equipped with a complex, heavy, and power consuming system that recovers approximately 50% of O2 from metabolic CO2. Future long duration missions will require a sustainable and highly efficient system capable of yielding a minimum of 75% O2 recovery. A Macrofluidic Electrochemical Reactor (MFECR) technology development effort is currently underway at NASA Marshall Space Flight Center (MSFC) to significantly increase current O2 recovery efficiency and reduce complexity of the system. This paper presents a comprehensive multi-physic 3D model developed at MSFC on CO2 conversion to O2 and C2H4 at standard conditions via MFECR. The 3D spatial domain of the model is a replica of the actual MFECR’s 3D drawing generated for the MFECR fabrication and operated to recover O2 from CO2 yielding C2H4 as byproduct. Electrochemical (EC) physics that includes EC multicomponent reaction mechanisms, mass transport, and current density distributions is coupled in the model with all the other physics phenomena involved in the process, such as free and porous fluid flow, multicomponent mass transfer, heat transfer, and DC electrical current generation along with Joule heating effect. The authors plan to use experimental results to validate this comprehensive and rigorous model and build a reliable simulator that will not only assist the authors on the MFECR design but also optimize its operation.

Dominguez, Jesus A.↗
NASA NTRSDate not supplied

Modeling Electrolytic O2 Recovery from Metabolic CO2 for Advanced Closed Loop Life Support Systems in Extraterrestrial Human Missions

The International Space Station (ISS) is currently equipped with a complex, heavy, and power consuming system that recovers approximately 50% of O2 from metabolic CO2. Future long duration human missions to the Moon and Mars will necessitate a sustainable and highly efficient metabolic oxygen recovery system capable of yielding a minimum of 75% O2 recovery. A Macrofluidic Electrochemical Reactor (MFECR) technology development effort is currently underway at NASA Marshall Space Flight Center (MSFC) to significantly increase current metabolic O2 recovery efficiency, expand mission sustainability, and reduce complexity of the system. The novel design combines CO2 conversion to O2 along with C2H4 as byproduct and water electrolysis (currently conducted in two separate units) into a single compact unit that runs at standard conditions and is theoretically capable of generating O2 with a theoretical maximum metabolic CO2 conversion of 73% while consuming less than metabolic water. This paper presents a comprehensive multi-physic 3D model developed at MSFC on CO2 conversion to O2 and C2H4 at standard conditions via MFECR. The 3D spatial domain of the model is a replica of the actual MFECR’s 3D drawing generated for the MFECR fabrication and operated to recover O2 from CO2 yielding C2H4 as byproduct. Electrochemical (EC) physics that includes EC multicomponent reaction mechanisms, mass transport, and electrical current density distributions is coupled in the model with all the other physics phenomena involved in the MFECR’s process, such as two-phase flow, free and porous fluid regimes, multicomponent mass transfer, heat transfer, and DC electrical current generation along with Joule heating effect. The EC reaction sections of the MFECR consists of two porous gas diffusion electrodes (GDE) and an electrolyte serpentine channel sandwiched in the middle. The CO2 feeds the cathode serpentine channel and part of the O2 product is fed back to the anode serpentine chamber. An alkaline solution feeds the electrolyte serpentine chamber wetting the GDEs of both, the anode and cathode allowing the OH- ionic transport between them. The EC reactions in the cathode’s GDE yield C2H4 from CO2 and H2 from water while the EC reaction in the anode’s GDE yields O2. The authors will present in this paper the validation of the model using experimental data and the utilization of the validated model in building a reliable simulator that will not only assist the authors on the MFECR design but also the optimization of its operation in the ISS and future spatial human missions.

Jesus A Dominguez↗
NASA NTRS2018

Laser power supply thermo-structural analysis for the Mars 2020 rover

Operation of the Laser Power Supply (LPS) module provides the dual challenge of high power dissipation, and the need for strict dielectric isolation, while needing to survive in an environment on Mars that will see a chilly night-time temperature of -123°C, and to a daytime instrument environment in excess of 50°C. Additionally, power restrictions prevent the use of survival heating during the night. The harsh mechanical vibration environment of launch and landing provides an additional challenge to reliability. A multi-physics simulation was created that took into account temperature property variations, as well as solving the transient analysis that also included rapid variation in power-pulsing during the operation of the laser. The steady state analysis employed a more traditional finite element based analysis, but with provisions for Mars gas convection and thermal radiation.

Tuman, David↗
NASA NTRS2018

Mars 2020 Rover Laser Power Supply Thermomechanical Analysis

Operation of the Laser Power Supply (LPS) module provides the dual challenge of high power dissipation, and the need for strict dielectric isolation, while needing to survive in an environment on Mars that will see a chilly night-time temperature of -123°C, and to a daytime instrument environment in excess of 50°C. Additionally, power restrictions prevent the use of survival heating during the night. The harsh mechanical vibration environment of launch and landing provides an additional challenge to reliability. A multi-physics simulation was created that took into account temperature property variations, as well as solving the transient analysis that also included rapid variation in power-pulsing during the operation of the laser. The steady state analysis employed a more traditional finite element based analysis, but with provisions for Mars gas convection and thermal radiation.

Tuman, David↗
NASA NTRSDate not supplied

Pragmatic Stress Prediction on Additively Manufactured Coupons

Prediction of residual stresses from process parameters for additively manufactured large metal parts is computationally expensive. NASA is currently developing meter-scale parts with direct energy deposition. Practically, the predictive computational methods need to efficiently scale-up to meter-scale parts. Coupled thermal-mechanical multi-physics simulations have been developed with the pragmatic method using ABAQUS, COMSOL Multiphysics, ALE3D software. The residual stresses are a result of the manufacturing process which creates thermal cycling of the build layers. The pragmatic method uses lumped thermal layers for stress predictions to reduce computational costs. The stress predictions as well as deformations of the different codes are compared with each other and with ANSYS Additive using identical material models, boundary and initial conditions. The codes were used to simulate three different geometries: a thin wall, hollow cylinder and twin-cantilever part. The coupon parts were then manufactured with Inconel-625. The residual stresses in these parts were measured using X-ray diffraction as well as neutron beam diffraction at NIST. The stress measurements for the two technologies are compared. The pragmatic stress prediction method enabled predictions of the multi-centimeter scale parts using desktop computer workstations in only a few hours for each coupon. The results of the simulated stress predictions compared favorably with the measured stresses even though thermally lumped layers were employed. Finally, a two-meter scale nozzle was simulated using ANSYS Additive. The simulations were used to examine the build orientation trade-space with respect to resulting geometric deformation. The predicted deformations were compared to measurements of an actual subscale part manufactured with direct energy deposition.

Additive Manufacturing↗
NASA NTRSDate not supplied

Hybrid Model Based Approaches for Systems Health Management and Prognostics

To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Latest achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision making. In principle, data driven approaches can replace expensive experimental test-setups as well as reduce the number of simulations needed to explore, e.g., the parametric space of a multi-parameter model. Nonetheless, the limitations of pure data-driven methods came to light rather quickly, at least for some industries. In many industrial applications, data acquisition is costly, and the volume of data that can be collected does not satisfy the requirements for an effective model training and cross-validation. Therefore, some recent works in the area of machine learning is focusing on blending physics with data-driven algorithms, thus mitigating the drawbacks of the two approaches and emphasizing respective advantages. Partial physical knowledge of the problem can aid the learning process by “guiding” the algorithm towards efficient solutions that satisfy the physics driving the system behavior. The result is a hybrid modeling approach combining physical knowledge as well data driven methods to develop a unified hybrid approach. A hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety critical systems is presented. In this framework, physics-based performance models infer unobservable model parameters related to the system's components health solving a calibration problem in the deep learning approach.

Hybrid Modeling↗
NASA NTRSDate not supplied

Pragmatic Stress Prediction on Additively Manufactured Coupons

Prediction of residual stresses from process parameters for additively manufactured large metal parts is computationally expensive. NASA is currently developing meter-scale parts with direct energy deposition. Practically, the predictive computational methods need to efficiently scale-up to meter-scale parts. Coupled thermal-mechanical multi-physics simulations have been developed with the pragmatic method using ABAQUS, COMSOL Multiphysics, ALE3D software. The residual stresses are a result of the manufacturing process which creates thermal cycling of the build layers. The pragmatic method uses lumped thermal layers for stress predictions to reduce computational costs. The stress predictions as well as deformations of the different codes are compared with each other and with ANSYS Additive using identical material models, boundary and initial conditions. The codes were used to simulate three different geometries: a thin wall, hollow cylinder and twin-cantilever part. The coupon parts were then manufactured with Inconel-625. The residual stresses in these parts were measured using X-ray diffraction as well as neutron beam diffraction at NIST. The stress measurements for the two technologies are compared. The pragmatic stress prediction method enabled predictions of the multi-centimeter scale parts using desktop computer workstations in only a few hours for each coupon. The results of the simulated stress predictions compared favorably with the measured stresses even though thermally lumped layers were employed. Finally, a two-meter scale nozzle was simulated using ANSYS Additive. The simulations were used to examine the build orientation trade-space with respect to resulting geometric deformation. The predicted deformations were compared to measurements of an actual subscale part manufactured with direct energy deposition.

pragmatic method↗