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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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At least 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Unsteady Analyses of Valve Systems in Rocket Engine Testing Environments

This paper discusses simulation technology used to support the testing of rocket propulsion systems by performing high fidelity analyses of feed system components. A generalized multi-element framework has been used to perform simulations of control valve systems. This framework provides the flexibility to resolve the structural and functional complexities typically associated with valve-based high pressure feed systems that are difficult to deal with using traditional Computational Fluid Dynamics (CFD) methods. In order to validate this framework for control valve systems, results are presented for simulations of a cryogenic control valve at various plug settings and compared to both experimental data and simulation results obtained at NASA Stennis Space Center. A detailed unsteady analysis has also been performed for a pressure regulator type control valve used to support rocket engine and component testing at Stennis Space Center. The transient simulation captures the onset of a modal instability that has been observed in the operation of the valve. A discussion of the flow physics responsible for the instability and a prediction of the dominant modes associated with the fluctuations is presented.

Shipman, Jeremy↗
NASA NTRS2006

Replaceable Sensor System for Bioreactor Monitoring

A sensor system was proposed that would monitor spaceflight bioreactor parameters. Not only will this technology be invaluable in the space program for which it was developed, it will find applications in medical science and industrial laboratories as well. Using frequency-domain-based fluorescence lifetime technology, the sensor system will be able to detect changes in fluorescence lifetime quenching that results from displacement of fluorophorelabeled receptors bound to target ligands. This device will be used to monitor and regulate bioreactor parameters including glucose, pH, oxygen pressure (pO2), and carbon dioxide pressure (pCO2). Moreover, these biosensor fluorophore receptor-quenching complexes can be designed to further detect and monitor for potential biohazards, bioproducts, or bioimpurities. Biosensors used to detect biological fluid constituents have already been developed that employ a number of strategies, including invasive microelectrodes (e.g., dark electrodes), optical techniques including fluorescence, and membrane permeable systems based on osmotic pressure. Yet the longevity of any of these sensors does not meet the demands of extended use in spacecraft habitat or bioreactor monitoring. It was therefore necessary to develop a sensor platform that could determine not only fluid variables such as glucose concentration, pO2, pCO2, and pH but can also regulate these fluid variables with controlled feedback loop.

Mayo, Mike↗
NASA NTRS2010

2010 ESMD Faculty Fellowship Project

This slide presentation reviews is composed of 6 individual sections. The first is a introductory section that explains the Exploration Systems Mission Directorate (ESMD) Faculty Fellowship Project, the purpose of which is to prepare selected university faculty to work with senior design students to complete projects that have potential to contribute to NASA objectives. The following university presentations represent the chosen projects: (1) the use of Exploration Toolset for the Optimization of Launch and Space Systems (X-TOOLSS) to optimize the Lunar Wormbot design; (2) development of Hardware Definition Language (HDL) realization of ITU G.729 for FGPA; (3) cryogenic fluid and electrical quick connect system and a lunar regolith design; (4) Lunar Landing Pad development; and (5) Prognostics for complex systems.

Carmen, Christina L.↗
NASA NTRSDate not supplied

Preliminary experimental studies into the storage capacity of cryogenic hydrogen in aerogel blanket materials

The abundance and diversity of hydrogen applications necessitates continued and accelerated research into advanced storage technologies. Traditionally, hydrogen has been stored as either a high-pressure, warm gas; or a low-pressure, cryogenic liquid. Methods such as cryo-supercritical and cryo-adsorbed have been explored, but are not yet mainstream. Cryo-adsorbed is attractive because higher storage densities at higher temperatures than liquid may be achieved. Recently NASA, in partnership with Eta Space, Southwest Research Institute, the University of Central Florida, and Air Liquide, have been exploring the use of inexpensive, commercially available silica aerogel blanket materials for cryo-adsorbed hydrogen storage. Unlike most adsorbents, aerogel blanket is not a powder, but a robust, composite material that can be formed into complex shapes to aid in more efficient storage system designs, and has already been proven to uptake large quantities of fluids such as nitrogen and oxygen. Recent experimental efforts into the uptake of low-pressure hydrogen gas at 77 K, and liquid hydrogen at normal boiling point (NBP) will be discussed. Although preliminary in nature, the test results are promising, showing up to a 49% increase in storage density at 77 K over the gas alone, and greater than a one-to-one volume equivalency with NBP LH 2 .

A M Swanger↗
DOE OSTI2020

Multiphysics for nuclear energy applications using a cohesive computational framework

With the recent development of advanced numerical algorithms, software design, and low-cost high-performance computer hardware, reliance on coupled multiphysics to predict the behavior of complex physical systems is beginning to become standard practice. This is especially true in nuclear energy applications where strong nonlinear interdependencies exist between reactor physics, radiation transport, multi-scale nuclear fuels performance, thermal fluids, etc. Resolving these nonlinear dependencies requires choices in multiphysics software approaches. Two main multiphysics modeling and simulation approaches have emerged. The first is based upon "code coupling" where disparate physics codes of different software design, code languages, and spatial and temporal integration schemes are coupled together with relatively complex data passing interfaces. The second multiphysics software approach is to employ a "cohesive" framework where all physics applications are developed with a common software design, i.e., data structures, syntax, input format, integrated spatial and temporal discretization schemes, etc. In this paper we present the Multiphysics Object-Oriented Simulation Environment (MOOSE) development and runtime framework and describe the framework's cohesive modeling and simulation multiphysics approach. Then, a "cohesive-like" extension of the MOOSE framework is presented where MOOSE-based physics software applications are efficiently coupled to non-MOOSE (external) physics codes to form multiphysics applications using MOOSE's unique interface capabilities. Finally, several examples of MOOSE's cohesive and cohesive-like multiphysics applications will be demonstrated. These multiphysics demonstrations will incorporate both MOOSE-based applications and external codes, including Nek5000, RELAP-7, TRACE, BISON, and Pronghorn.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRSDate not supplied

Full-Envelope Aero-Propulsive Model Identification for Lift+Cruise Aircraft Using Computational Experiments

This paper describes a process utilizing computational fluid dynamics experiments to develop a reduced-order, integrated propulsion-airframe aerodynamic model for a lift+cruise electric vertical takeoff and landing (eVTOL) reference aircraft concept. eVTOL configurations exhibit aerodynamic characteristics of both fixed-wing and rotary-wing aircraft as well as complex phenomena, such as propulsion-airframe interactions. Consequently, conventional aircraft aerodynamic modeling strategies require modification when applied to these unique aircraft. A novel aero-propulsive modeling approach using design of experiments techniques and computational fluid dynamics simulations is postulated for modeling a lift+cruise aircraft configuration. Aero-propulsive models are developed throughout the operational flight envelope to enable continuous flight dynamics simulations from hover through forward flight. The model adequacy is assessed using validation data acquired separately from data used to identify the model and indicates that the models have sufficient predictive capability. Research findings are presented with a discussion of unique lift+cruise aircraft aerodynamic characteristics and practical strategies to inform future aero-propulsive modeling and simulation efforts for eVTOL aircraft.

lift+cruise↗
NASA NTRS2001

A Steady State and Quasi-Steady Interface Between the Generalized Fluid System Simulation Program and the SINDA/G Thermal Analysis Program

A general purpose, one dimensional fluid flow code is currently being interfaced with the thermal analysis program SINDA/G. The flow code, GFSSP, is capable of analyzing steady state and transient flow in a complex network. The flow code is capable of modeling several physical phenomena including compressibility effects, phase changes, body forces (such as gravity and centrifugal) and mixture thermodynamics for multiple species. The addition of GFSSP to SINDA/G provides a significant improvement in convective heat transfer modeling for SINDA/G. The interface development is conducted in multiple phases. This paper describes the first phase of the interface which allows for steady and quasisteady (unsteady solid, steady fluid) conjugate heat transfer modeling.

Schallhorn, Paul↗
DOE OSTI2022

Development of machine learning framework for interface force closures based on bubble tracking data

Interfacial force closures in the two-fluid model play a critical role for the predictive capabilities of void fraction distribution. However, the practices of interfacial force modeling have long been challenged by the inherent physical complexity of the two-phase flows. The rapidly expanding computational capabilities in the recent years have made high-fidelity data from the interface-captured direct numerical simulation become more available, and hence potential for data-driven interfacial force modeling has prevailed. In this work, we established a data-driven modeling framework integrated to the HZDR multiphase Eulerian-Eulerian framework for computational fluid dynamics simulations. The data-driven framework is verified in a benchmark problem, where a feedforward neural network managed to capture the non-linear mapping between bubble Reynolds number and drag coefficient and reproduce the void distribution resulting from the baseline model in the test case. The second focus is on utilizing the bubble tracking data set to form a closure for the bubble drag in the turbulent bubbly flow, in which the drag coefficient is set to be correlated with the bubble Reynolds number and the Eötvös number. Pseudo-steady state filtering in the Frenet Frame was carried out to obtain the drag coefficient from the turbulent bubbly flow data. The performance of the data-driven drag model is also examined through a case study, where improvement of model’s prediction near-wall is regarded necessary. In conclusion, discussion and further plans of investigation are provided.

42 ENGINEERING↗
NASA NTRS2012

Spaceflight Effects and Molecular Responses in the Mouse Eye: Observations after NASA Shuttle Mission STS-133

Background: Human space exploration implies a combination of stressors including microgravityinduced cephalad fluid shift and radiation exposure. Ocular changes in astronauts leading to visual impairment are of occupational health relevance. The effect of this complex environment on ocular morphology and function is poorly understood. Material and Methods: Mice were assigned to a Flight (FLT) group flown on shuttle mission STS133, Animal Enclosure Module (AEM), or vivarium (VIV) ground controls. Eyes were collected at 1, 5 and 7 days after landing, and were fixed for histological sectioning. The contralateral eye was used for gene expression profiling by qRT-PCR. Routine histology and immunohistochemistry using 8-hydroxy-2'-deoxyguanosine (8-OHdG), caspase-3, glial fibrillary acidic protein (GFAP) and beta-amyloid were used to study the eyes. Results and Conclusions: 8-OHdG and caspase-3 immunoreactivity was increased in the retina in FLT samples at return from flight (R+1) compared to ground controls, and decreased at day 7 (R+7), suggesting an increase in oxidative stress and cell apoptosis. FLT mice showed evidence of retinal pigment epithelium (RPE) apoptosis possibly secondary to oxidative damage. Although attenuation of RPE has been related to retinal choroidal folds in astronauts, it is yet to be determined whether or not increased RPE apoptosis may contribute to the formation of choroidal folds or may increase the risk for other retinal pathologies, such as AMD. beta-amyloid was seen in the nerve fibers at the post-laminar region of the optic nerve in the flight samples (R+7). Deposition of beta-amyloid has a strong correlation with mechanical trauma. The coexpression of GFAP in astrocytes and oligodentrocytes in these same areas supports the possible mechanical origin probably secondary to intracranial pressure that is transmitted into the nerve, as a result of an increase in venous pressure associated to microgravity-induced cephalic fluid shift. However, there is the need to further investigate the nature of the changes through additional experimental work. Gene expression of oxidative and cellular stress response genes was unregulated in the retina of FLT samples upon landing followed by lower levels by R+7. These results suggest that reversible molecular damage occurs in the retina of mice exposed to spaceflight and that protective cellular and molecular pathways are induced in the retina in response to these changes.

ProsperoPonce, Claudia Maria↗
NASA NTRS2017

Thermally-Conductive Metallic Coatings and Applications for Heat Removal on In-Space Cryogenic Vehicles

For large in-space cryogenic upper stages, substantial axial heat removal from a forward skirt by vapor-based heat interception may not be achieved by simple attachment methods unless sufficient thermal conductance from the skirt to the cooling fluid can be achieved. Preferable methods would allow for the addition of the cooling system to existing structure with minimal impact on the structure. Otherwise, significant modification to the basic structural design andor novel and complex attachment mechanisms with high effective thermal conductance are likely to be required. The approach being pursued by evolvable Cryogenics (eCryo) is to increase the thermal performance of a relatively simple attachment system by applying metallic or other thermally conductive material coatings to the mating surface area of the fluid channel where it is attached the skirt wall. The expectation of candidate materials is that the dramatic increase in conductivity of pure metals at temperatures close to liquid hydrogen vapor temperature will compensate for the reduced actual contact area typical of mechanical joints. Basic contact conductance data at low temperatures for candidate interface materials is required to enable the test approach. A test rig was designed at NASA Glenn Research Center to provide thermal contact resistance testing between small sample coupons coated with conductive material via electron beam evaporation, a low-temperature option that will not affect physical properties of base materials. Average coating thicknesses were 10 k. The test fixture was designed to mount directly to a cryocooler cold head within a vacuum test chamber. The purpose of this test was to determine qualitative contact conductance between various test samples. Results from this effort will be implemented in a sub-scale vapor-based heat interception test, where the applicability for increased heat removal on large structural skirts will be considered.

small scale testing↗
NASA NTRS2015

Mini-Stamp as a Micro-Display for At-A-Glance Subsystem Information for DSN Links

Operators of the Deep Space Network (DSN) attend to numerous tasks with the overall goal of providing continuous support for the world's deep space missions. This high-stakes operations environment requires operators to understand the state of the Deep Space Network and predict what will happen next. Under the Follow-the-Sun initiative which requires remote operations of the highly complex telecommunications equipment, operators will need to remain aware of the state of the entire network rather than just their own facility, and transitioning fluidly between periods of low activity and periods of high demand. I designed a micro-display for operators to see, at a glance, the state of a Deep Space Network support including its subsystems. Using in-depth user-centered and participatory design techniques to identify information requirements, I designed what I called a Postage Stamp (NTR-49720) for individual operators to be able to maintain awareness of their own assigned supports. However, under Follow the Sun, operators must remain aware of all supports. The area occupied by the Postage Stamp must shrink to allow operators to see the state of the entire system, e.g., via a Big Board posted prominently in the operations room. Micro-displays are tools for mental model re-alignment, helping operators to keep their mental models of how the system works and behaves aligned with the changing state of the complex system. Data-driven micro-displays such as the Postage Stamp and Mini-Stamp display information about the system in a consistent way. Like a traffic light, the format of the micro-display never changes: the operator always knows where to look to find a specific piece of information. The Mini-Stamp always looks like the Mini-Stamp, and all of its data fields always lie in the same place on the micro-display. Real-time data flows through the Mini-Stamp to provide information to the operator.

Holloway, Alexandra↗
NASA NTRS1990

Absence of first-order unbinding transitions of fluid and polymerized membranes

Unbinding transitions of fluid and polymerized membranes are studied by renormalization-group (RG) methods. Two different RG schemes are used and found to give rather consistent results. The fixed-point structure of both RG's exhibits a complex behavior as a function of the decay exponent tau for the fluctuation-induced interaction of the membranes. For tau greater than tau(S2) interacting membranes can undergo first-order transitions even in the strong-fluctuation regime. These estimates for tau(S2) imply, however, that both fluid and polymerized membranes unbind in a continuous way in the absence of lateral tension.

Grotehans, Stefan↗
NASA NTRS2002

An Experimental Investigation of Incompressible Richtmyer-Meshkov Instability

Richtmyer-Meshkov (RM) instability occurs when two different density fluids are impulsively accelerated in the direction normal to their nearly planar interface. The instability causes small perturbations on the interface to grow and eventually become a turbulent flow. It is closely related to Rayleigh-Taylor instability, which is the instability of a planar interface undergoing constant acceleration, such as caused by the suspension of a heavy fluid over a lighter one in the earth's gravitational field. Like the well-known Kelvin-Helmholtz instability, RM instability is a fundamental hydrodynamic instability which exhibits many of the nonlinear complexities that transform simple initial conditions into a complex turbulent flow. Furthermore, the simplicity of RM instability (in that it requires very few defining parameters), and the fact that it can be generated in a closed container, makes it an excellent test bed to study nonlinear stability theory as well as turbulent transport in a heterogeneous system. However, the fact that RM instability involves fluids of unequal densities which experience negligible gravitational force, except during the impulsive acceleration, requires RM instability experiments to be carried out under conditions of microgravity. This experimental study investigates the instability of an interface between incompressible, miscible liquids with an initial sinusoidal perturbation. The impulsive acceleration is generated by bouncing a rectangular tank containing two different density liquids off a retractable vertical spring. The initial perturbation is produced prior to release by oscillating the tank in the horizontal direction to produce a standing wave. The instability evolves in microgravity as the tank travels up and then down the vertical rails of a drop tower until hitting a shock absorber at the bottom. Planar Laser Induced Fluorescence (PLIF) is employed to visualize the flow. PLIF images are captured by a video camera that travels with the tank. Figure 1 is as sequence of images showing the development of the instability from the initial sinusoidal disturbance far into the nonlinear regime which is characterized by the appearance of mushroom structures resulting from the coalescence of baroclinic vorticity produced by the impulsive acceleration. At later times in this sequence the vortex cores are observed to become unstable showing the beginnings of the transition to turbulence in this flow. The amplitude of the growing disturbance after the impulsive acceleration is measured and found to agree well with theoretical predictions. The effects of Reynolds number (based on circulation) on the development of the vortices and the transition to turbulence are also determined.

Jacobs, J. W.↗
DOE OSTI2025

Unraveling Hydrogen Induced Geochemical Reaction Mechanisms through Coupled Geochemical Modeling and Machine Learning

Underground hydrogen storage (UHS) provides a promising large-scale, long-term energy storage solution. A reasonable recovery of stored hydrogen is critical for a successful storage scheme. However, in subsurface reservoirs hydrogen is subject to active geochemical reactions that might result in hydrogen loss. In this study, we implemented a geochemical modeling approach coupled with an unsupervised machine learning technique called non-negative matrix factorization (NMF) to unravel the complex brine-rock-H 2 geochemical processes responsible for hydrogen losses, with particular focus on sulfate reduction reactions. NMF is applied to modeled mineral evolution and fluid component profiles to retrieve profiles that can be interpreted to more easily assess competing processes. NMF decouples simulated competing equilibrium reactions. This facilitates separation of overlapping reaction profiles from redox processes, dissolution fronts, and secondary precipitation while considering the effects of simulation parameters such as salinity, temperature, and total H 2 pressure. NMF successfully discriminates these competing effects in nonlinear ways, allowing robust interpretation. In addition, NMF reveals subtle coupled mineral associations and reaction fronts that are invisible to conventional model analysis. This integrated approach strengthens the conceptual understanding of complex nonlinear hydrogen-brine-rock interactions and advances geochemical research on UHS systems to resolve complexities in modeled geochemical systems without the need for direct experiments or prior knowledge. Furthermore, this study highlights the efficacy of combining geochemical modeling with machine learning techniques to enhance the interpretability of the intricate geochemical simulation output through deciphering the overlapping reaction path that cannot be achieved only using conventional analysis of geochemical models alone.

08 HYDROGEN↗
DOE OSTI2020

A hybrid porous model for full reactor core scale CFD investigation of a prismatic HTGR

Three-dimensional (3-D) Computational Fluid Dynamics (CFD) analysis of a whole nuclear reactor core is a tremendous challenge due to the large geometric volume and complex structures. Here, this research presents a hybrid porous (HP) model to simplify a prismatic High Temperature Gas-cooled Reactor (HTGR) core, so 3-D CFD investigation can be performed on a full reactor core scale. In the HP model, the prototypic small coolant channels in the nuclear fuel blocks are lumped together to form multiple equivalent large coolant channels, and then the porous medium flow model is applied to each of them. Therefore, heat transfer in fuel blocks is computed by a hybrid combination of solid energy and porous flow energy equations. The similarity between the HP model and prototypic model is achieved by deriving the porous flow permeability, inertial resistance factor, and artificial thermophysical properties. Compared with the widely used whole porous (WP) flow model, the HP model preserves more realistic geometric structures, and therefore more accurate physical processes. The General Atomics' Modular High Temperature Gas-cooled Reactor (MHTGR) design was chosen as a prototype to demonstrate the methodology. Simulations were performed using the prototypic CFD model and HP model at steady-state forced circulation, steady-state natural circulation, and transient conditions that correspond to normal operation, extended period of pressurized cool down, and short-term transients after reactor shutdown, respectively. The comparison shows good agreement between the HP model and prototypic model in the maximum fuel temperature, average solid temperature, and helium flow rate, which demonstrates the potential applicability of the HP model for a full reactor core scale simulation in the future. As a benefit, the HP model reduces the mesh quantity by a factor of 50 from a prototypic model. Correspondingly, the computation time was reduced by a factor of at least 30.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Scalability analysis of heavy-duty gas turbines using data-driven machine learning

With the increasing integration of variable renewable energy sources into power systems, the role of flexible power generation technologies like gas turbines (GT) in rapid grid balancing remains crucial. This sustained importance underscores the need for scaled and precise modeling of GT to ensure effective integration within evolving energy frameworks. While physics-driven GT models integrate thermodynamics, fluid dynamics, and combustion principles, they often rely on approximate mathematical representations to accommodate scaling that may not capture the actual complex dynamics for GTs and inertial effects associated to GTs with different ratings. In this study, a data-driven model is proposed using machine learning (ML) techniques to conduct GT scalability analysis and performance evaluation with high accuracy. The ML model, trained on data from various operating conditions and performance parameters, aims to uncover intricate relationships and patterns, resembling GT characteristics at different scales (ratings). The model is developed to capture complex system interaction and to adapt to changing operational scenarios at different capacities, providing valuable insights of power system dynamics. In this study, the real-time digital simulator platform was employed to generate training data for the ML model and assess its dynamic characteristics. The ultimate objective was to develop a detailed modeling framework based on governing equations and data-driven ML capable of predicting key performance indicators, in thermal systems such as GTs, including power output, speed, fuel consumption, and exhaust temperature under diverse operating conditions at different scales. The developed ML framework demonstrated high accuracy, with mean relative errors for GT power prediction, reference speed, exhaust temperature, and compressor pressure ratio (CPR) parameters consistently below 0.1% across typical load fluctuation scenarios. Maximum deviations were limited to approximately 0.5 K for exhaust temperature and 0.009 for CPR, underscoring the model’s ability to replicating dynamic GT behavior with high precision. The adaptability of the ML model enables its application across diverse operational conditions and its extension to other thermal systems. By leveraging advanced ML techniques, this study presents a robust and scalable modeling framework that enhances GT simulation precision, facilitating improved integration into evolving power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Mixing in Low Reynolds Number Reacting Impinging Jets in Crossflow

Previous efforts to model uranyl fluoride formation in an impinging jet gas reactor underpredicted spatial mixing and overpredicted chemical conversion into particulates. The previous fluid dynamics model was based on the solution of the Reynolds Averaged Navier Stokes equations. After simulating fluid dynamics, aerosol dynamics were superimposed onto CFD-simulated gas reactant species concentrations. The current work explores the influence of complex unsteady flow features on the overall flow physics and chemistry for a low Reynolds number, opposed flow, impinging jet gas reactor where there is a low Reynolds number cross flow. The objective of this study was to assess the impact of model formulation on scalar mixing and transport. Here, transient flow simulations were performed using Scale Resolving Simulations. Large-Eddy Simulations with the dynamic Smagorinsky turbulence model were performed along with simulations which directly resolved the flow. Average and root-mean-square (RMS) velocities and species concentrations were computed along with modeled and resolved turbulence kinetic energy (TKE), modeled turbulence dissipation, and modeled turbulent viscosity. Lagrangian flow tracers were also used to quantify species concentrations along path lines emanating from the jet tips. Transient simulation data were compared to results from RANS simulations using the k-ω shear stress transport (SST) model and Reynolds Stress Model (RSM). Transient simulations showed spatial mixing patterns which were more consistent with experimental data and helped elucidate the process of particle formation observed in experiments.

42 ENGINEERING↗
DOE OSTI2024

Development of a Method for Shape Optimization for a Gas Turbine Fuel Injector Design Using Metal-Additive Manufacturing

Adjoint shape optimization has enabled physics-based optimal designs for aerodynamic surfaces. Additive manufacturing (AM) makes it possible to manufacture complex shapes. However, there has been a gap between optimal and manufacturable surfaces due to the inherent limitations of commercial computational fluid dynamics (CFD) codes to implement geometric constraints during adjoint computation. In such cases, the design sensitivities are exported and used to perform constrained shape modifications using parametric information stored in computer aided design (CAD) files to satisfy manufacturability constraints. However, modifying the design using adjoint methods in CFD solvers and performing constrained shape modification in CAD can lead to inconsistencies due to different shape parameterization schemes. This paper describes a method to enable the simultaneous optimization of the fluid domain and impose AM manufacturability constraints, resolving one of the key issues of geometry definition for isogeometric analysis. Similar to a grid convergence study, the proposed method verifies the consistencies between shape parameterization techniques present within commercial CAD and CFD software during mesh movement as a part of the adjoint shape optimization routine. By identifying the appropriate parameters essential to a shape optimization study, the error metric between the different parameterization techniques converges to demonstrate sufficient consistencies for justifiable exchange of data between CAD and CFD. For the identified shape optimization parameters, the error metric to measure the deviation between the two parameterization schemes lies within the AM laser-powder bed fusion (L-PBF) process tolerance. Additionally, comparison for subsequent objective function calculations between iterations of the optimization loop showed acceptable differences within 1% variation between the modified geometries obtained using the two parameterization schemes. This method provides justification for the use of multiphysics guided adjoint design sensitivities computed in CFD software to perform shape modifications in CAD to incorporate AM manufacturability constraints during the shape optimization loop such that optimal designs are also additively manufacturable.

33 ADVANCED PROPULSION SYSTEMS↗