Statistical derivation of design criteria for liquid rocket combustion instability Final report
Statistical correlation between engine design and combustion stability in liquid propellant rocket engines
Bastress, E. K.↗
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SLS Model Based Design: A Navigation Perspective
The SLS Program has implemented a Model-based Design (MBD) and Model-based Requirements approach for managing component design information and system requirements. This approach differs from previous large-scale design efforts at Marshall Space Flight Center where design documentation alone conveyed information required for vehicle design and analysis and where extensive requirements sets were used to scope and constrain the design. The SLS Navigation Team is responsible for the Program-controlled Design Math Models (DMMs) which describe and represent the performance of the Inertial Navigation System (INS) and the Rate Gyro Assemblies (RGAs) used by Guidance, Navigation, and Controls (GN&C). The SLS Navigation Team is also responsible for navigation algorithms. The navigation algorithms are delivered for implementation on the flight hardware as a DMM. For the SLS Block 1B design, the additional GPS Receiver hardware model is managed as a DMM at the vehicle design level. This paper describes the models, and discusses the processes and methods used to engineer, design, and coordinate engineering trades and performance assessments using SLS practices as applied to the GN&C system, with a particular focus on the navigation components.
Oliver, T. Emerson↗
Supersonic transport airport and community jet noise during takeoff and initial climb
Engine design and flight characteristics effects on airport and community jet noise environment of fixed-wing supersonic commercial transport
ENGINE DESIGN↗
MACHINE LEARNING-ENABLED PREDICTION OF TRANSIENT INJECTION MAP IN AUTOMOTIVE INJECTORS WITH UNCERTAINTY QUANTIFICATION
Accurate prediction of injection profiles is a critical aspect of linking injector operation with engine performance and emissions. However, highly resolved injector simulations can take one to two weeks of wall-clock time, which is incompatible with engine design cycles with desired turnaround times of less than a day. Hence, it is important to reduce the time-to-solution of the internal flow simulations by several orders of magnitude to make it compatible with engine simulations. This work demonstrates a data-driven approach for tackling the computational overhead of injector simulations, whereby the transient injection profiles are emulated for a side-oriented, single-hole diesel injector using a Bayesian machine-learning framework. First, an interpretable Bayesian learning strategy was employed to understand the effect of design parameters on the total void fraction field. Then, autoencoders are utilized for efficient dimensionality reduction of the flowfields. Gaussian process models are finally used to predict the spatiotemporal void fraction field at the injector exit for unknown operating conditions. The Gaussian process models produce principled uncertainty estimates associated with the emulated flowfields, which provide the engine designer with valuable information of where the data-driven predictions can be trusted in the design space. The Bayesian flowfield predictions are compared with the corresponding predictions from a deep neural network, which has been transfer-learned from static needle simulations from a previous work by the authors. The emulation framework can predict the void fraction field at the exit of the orifice within a few seconds, thus achieving a speed-up factor of up to 38 x 10(6) over the traditional simulation-based approach of generating transient injection maps.
machine learning↗
Catalyst design to direct high-octane gasoline fuel properties for improved engine efficiency
The paraffin-to-olefin (P/O) ratio in gasoline fuel is a critical metric affecting fuel properties and engine efficiency. In the conversion of dimethyl ether (DME) to high-octane hydrocarbons over BEA zeolite catalysts, the P/O ratio can be controlled through catalyst design. Here, we report bimetallic catalysts that balance the net hydrogenation and dehydrogenation activity during DME homologation. The Cu-Zn/BEA catalyst exhibited greater relative dehydrogenation activity attributed to higher ionic site density, resulting in a lower P/O ratio (6.6) versus the benchmark Cu/BEA (9.4). The Cu-Ni/BEA catalyst exhibited increased hydrogenation due to reduced Ni species, resulting in a higher P/O ratio (19). The product fuel properties were estimated with an efficiency merit function and compared against finished gasolines and a typical alkylate blendstock. Merit values for the hydrocarbon product from all three BEA catalysts exceeded those of the comparison fuels (0–5.3), with the product from Cu-Zn/BEA exhibiting the highest merit value (9.7).
Catalyst design↗
Managing the Digital Thread for Structural Applications With Fit for Purpose Materials
With the increased emphasis on reducing the cost and time to market of new materials, the need for analytical tools that enable the virtual design and optimization of materials throughout their processing - internal structure - property - performance envelope, along with the capturing and storing of the associated material and model information across its lifecycle, has become critical. This need is also fueled by the demands for higher efficiency in material testing; consistency, quality and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. Consequently, at NASA Glenn Research Center a robust information management system that manages the digital thread across the full material life (i.e., capture, analysis, maintenance, and dissemination of data) cycle directed at the design of ‘fit-for-purpose materials’ is under development. To this end the Application Table has been incorporated within NASA Glenn Research Center’s ICME Information Management framework within the ANSYS Granta MI tool. The Application Table provides a place where material and structural application information/requirements can be linked to marry the “design-the-material” (structural engineering) and the “design-with-material” (material science) paradigms and thereby enable application-driven design and optimization of materials and structures. In additional several associated toolsets, specifically: AIMAOS (Automated Information Management Across Organizations and Scales), Py MILab, and JARIMIS (Just A Rather Intelligent Material Interrogation System) are also under development to assist in the judicious automation of this process. AIMOAS offers users an interactive graphical user interface for connecting material information management systems with both commercial and in-house simulation tools at various length scales to enable such automation in the handoff across scales and maintenance of material digital twins and the digital thread. Py MILab, is an automatic framework for the capture, analysis, maintenance, and storage of material test data. Py MILab uses a modular approach for capturing raw data, analyzing the data, and storing the data in a database, interfaced by neutral file structures, to promote plug-and-play capabilities for various analysis types. Finally, JARIMIS is an expert system that integrates various materials informatics tools (e.g., MicroNet, Surrogate ML models, ANSYS Granta MI, etc.) to enable inverse design of materials and facilitate the application of machine learning (ML) and data science with human in the loop decision making to rapidly discover and optimize new materials.
Digital Transformation↗
ROTA-CAP™: An Intensified Carbon Capture System Using Rotating Packed Beds (Final Scientific/Technical Report)
GTI Energy and Carbon Clean Solutions Limited successfully designed, constructed, and operated an integrated ROTA-CAP carbon capture skid. ROTA-CAP™ is a process intensification technology, applied for post-combustion carbon capture, which utilizes the centrifugal forces generated from rotation of rotating packed beds as well as advanced solvents to achieve increased mass transfer rates 1-2 orders of magnitude higher than conventional columns while substantially decreasing footprint. The test skid, which consisted of a dual stage RPB absorber with external interstage cooling and a single stage RPB regenerator, was operated at capacities up to 0.5 tonne/day of CO 2 capture with flue gas concentrations ranging from 4% to 22% CO 2 by vol. CO 2 removal rates greater than 95% were achieved, with CO 2 product purity also exceeding 95% by vol. Over 1,600 hours of operation were accumulated throughout the project, including over 1,000 hours of operation of the with real flue gas containing at least 9.8% CO 2 by vol. The skid was operated continuously for 24 hours per day and 7 days per week over the course of 7 long-term test campaigns, with the campaigns ranging from approximately 2-4 weeks per campaign. A techno-economic analysis was performed, and a cost of capture of $\$$41.18/tonne CO 2 was calculated for the ROTA-CAP process, compared to $\$$45.75/tonne for a Cansolv-based process. These results show a cost reduction of approximately 10% compared to the Cansolv-based process. Although this still exceeds the target cost of capture of $\$$30/tonne specified for this project, GTI expects that the cost of capture can be further reduced through further optimization of the design and technology. GTI also performed an engineering design review to determine the scale-up potential of the technology, with the results of the preliminary assessment indicating that it appears to be feasible to scale up the RPB technology to 4,000 TPD. It was also determined that both horizontal and vertical rotor orientations are feasible, though there are mechanical advantages to the vertical orientation.
20 FOSSIL-FUELED POWER PLANTS↗
Tailored Fiber Placement for Complex Preforms
Tailored Fiber Placement (TFP) offers a novel approach to optimize fiber architecture for the fabrication of complex, structural parts not traditionally suitable for advanced composites. This technology not only offers new routes for weight reduction via metal substitution, it also offers cost reduction through minimization of material scrap and reduced labor. This reduction in component weight leads to increased fuel efficiency, and reduced production energy consumption, thereby, helping to achieve the stated IACMI technical goals. This technology leverages centuries of manufacturing development in support of the textile and embroidery industry. One major drawback to this technology is the lack of commercial or non- proprietary structural performance data and robust analytical tools used to optimize fiber architecture and predict performance. This project was structured to utilize common sub-element features to validate analytical performance tools, generate performance data, and gather cost and performance data on components of interest. This project was designed to give industry sponsors the confidence and ability to take full advantage of TFP to fabricate primary, highly loaded structure and integrate features such as metallic fasteners. The project focused principally on the use of high strength carbon fiber, such as T700, and the use of aerospace epoxy resin matrix to primarily support development of new composite applications in vehicle, aerospace, and industrial markets. This project applied previously developed analytical tools to predict the performance of TFP produced parts. This work focused on developing the pipeline to characterize material in order to accurately predict component performance when modifying the TFP print paths and stitch density. This focused on experimental characterization via standardized ASTM testing, alongside experimental testing of more representative service components by testing curved beam strength, beam shear performance, a large scale TFP lug, and ultimately designing a fully TFP clip bracket that reduced weight and cost compared to a traditional metallic component. The new knowledge gained from this program included: 1) development and demonstration of novel analytical tools applied to analysis of TFP preforms; 2) development and demonstration of a building block approach using coupons and sub-elements to optimize the design of a more complex component; 3) demonstration that optimized fiber orientation using TFP can exceed performance of conventional textile composite materials and can open new applications currently limited to metallic components; 4) Demonstration of performance and cost benefits of the TFP process as compared to metallic and conventional textile composites. Recommendations for follow-on work include development of design allowables to assess the impact of high temperature/moisture exposure or saturation during loading, tracking the impact of stitching needle wear on the performance of parts and ability to stitch thicker preforms, using TFP preforms as local reinforcement at areas of bearing or complex loading, and topology optimization of components by tow steering. The expertise developed during the course of this project can be leveraged to provide commercial engineering design and fabrication services using TFP. UDRI is in the process of formalizing their partnership with Spintech, who will serve as the commercialization partner for this technology and provide molding services and deliver finished components to the end user. UDRI will continue to produce the preforms until the economics allow Spintech to procure its own TFP equipment or lease UDRI equipment, at which point UDRI will step away from manufacture and serve as the engineering and design lead on product development.
36 MATERIALS SCIENCE↗
An adaptive sampling augmented Lagrangian method for stochastic optimization with deterministic constraints
The primary goal of this paper is to provide an efficient solution algorithm based on the augmented Lagrangian framework for optimization problems with a stochastic objective function and deterministic constraints. Our main contribution is combining the augmented Lagrangian framework with adaptive sampling, resulting in an efficient optimization methodology validated with practical examples. To achieve the presented efficiency, here we consider inexact solutions for the augmented Lagrangian subproblems, and through an adaptive sampling mechanism, we control the variance in the gradient estimates. Furthermore, we analyze the theoretical performance of the proposed scheme by showing equivalence to a gradient descent algorithm on a Moreau envelope function, and we prove sublinear convergence for convex objectives and linear convergence for strongly convex objectives with affine equality constraints. The worst-case sample complexity of the resulting algorithm, for an arbitrary choice of penalty parameter in the augmented Lagrangian function, is $\mathscr{O}$(ϵ -3-δ ) , where ϵ > 0 is the expected error of the solution and δ > 0 is a user-defined parameter. If the penalty parameter is chosen to be $\mathscr{O}$(ϵ -1 ), we demonstrate that the result can be improved to $\mathscr{O}$(ϵ -2 ) , which is competitive with the other methods employed in the literature. Moreover, if the objective function is strongly convex with affine equality constraints, we obtain $\mathscr{O}$(ϵ -1 log(1/ϵ)) complexity. Finally, we empirically verify the performance of our adaptive sampling augmented Lagrangian framework in machine learning optimization and engineering design problems, including topology optimization of a heat sink with environmental uncertainty.
97 MATHEMATICS AND COMPUTING↗
The design and development of a mixer compound exhaust system for a quiet clean general aviation turbofan
Lower engine fuel consumption has become a dominant factor in turbofan engine design due to rapidly increasing fuel costs. One engine component with a large impact on engine performance is the exhaust system. Previous exhaust system studies have demonstrated the significant exhaust system efficiency gains available through mixing of the core and bypass flows. Typically, a large, costly rig and engine program are required to develop and optimize these gains. The purpose of this paper is to present the results of the low-cost design system used for the quiet, clean general aviation turbofan mixer nozzle design and development. The scale model and full-scale engine test results confirm the predicted 3 to 5% reduction in cruise fuel consumption. This unique design system, which is based on integrating advanced three-dimensional viscous numerical methods with empirical optimization techniques, is summarized and detailed comparisons with test data are presented. The ability to accurately predict relative performance of mixer systems with substantially reduced development time and cost savings is demonstrated.
Blackmore, W. L.↗
Investigation of Cycle-to-Cycle Variations in Internal Combustion Engine Using Proper Orthogonal Decomposition
The understanding, modeling and control of the cycle-to-cycle variation (CCV) in the modern internal combustion engine (ICE) is a key scientific challenge to achieve stable engine operation. High CCV in the engine combustion chamber may contribute to partial burn, misfire and knock, which adversely affects the engine performance and may potentially damage the engine. The objective of the current study is to leverage high-fidelity numerical simulations to improve the understanding of the causes of CCV. Using the massively parallel code, Nek5000, multi-cycle, wall-resolved large-eddy simulations (LES) were performed for the General Motors (GM), Transparent Combustion Chamber (TCC-III) optical engine under motored operating conditions. Further, the large-scale structures of the in-cylinder flow were investigated using a triple proper orthogonal decomposition (POD) technique to explore the characteristics of different parts of the flow and their contributions to CCV. The kinetic energy of the subset of flow structures were determined and correlated between the intake and compression strokes. The insights from the analysis of the large-scale flow structures will be used to assist the development of improved engine designs with reduced CCV and enhance the engine performance.
33 ADVANCED PROPULSION SYSTEMS↗
In situ multimodal imaging for nanoscale visualization of tribofilm formation
A third of the energy from fuel combustion in passenger car gasoline engines is lost due to friction. Carefully designed engine lubricants can recover some of these losses by reducing friction and wear by forming a nanometer-scale chemico-physico tribofilm between surfaces. Accordingly, attention has focused on developing oil formulations that form low-friction tribofilms. However, analyses of resultant tribofilms are typically conducted after tribo-tests with conventional characterization tools and do not offer insights into tribofilm formation and evolution, precluding information critical to tuning tribofilm properties. In this work, we developed a unique multimodal methodology based on Atomic Force Microscopy (AFM) with local probe heating for in situ tribological studies that activates friction modifiers and simultaneously captures the evolution of friction and surface roughness, with nanometer resolution. As a platform to demonstrate the ability of this methodology to visualize dynamics of tribofilm formation in situ, we apply it to molybdenum-based friction modifiers to distinguish key factors in their functionality and correlate nanoscale AFM and Friction Force Microscopy data to bench tribo-tests used in the industry. To decode the formation mechanisms observed in situ and underlying chemistry of tribofilms, we performed ab initio Molecular Dynamics (AIMD) simulations at comparable conditions. AIMD simulations confirmed both nanoscale and bench tribo-test results and showed deviations in molecular organization in tribofilms that are formed from different molybdenum-based friction modifiers that corroborates with surface functionality. With this innovative methodology, we demonstrate proof-of-principle in situ formation of molybdenum-based tribofilms directly on steel surfaces that could be applied generally to studying tribofilm formation.
36 MATERIALS SCIENCE↗
Cyber-informed Engineering Microgrid Analysis Tool
The Cyber-Informed Engineering Microgrid Analysis Tool (CIEMAT) leverages the Department of Energy’s Cyber-Informed Engineering to prompt engineering designers and operators through an analysis of the critical functions to be supported by a microgrid installations, the criticality of those functions, the impacts of denial, disruption or misuse of those functions on the microgrid and dependent functions, and the mitigations which could best prevent impacts to those functions resulting from cyber attack. Through use of this tool, microgrid designers and operators can quickly identify appropriate engineering mitigations to limit impacts from cyber attack and functions where engineering and operational staff can prioritize and guide the application of cybersecurity protections to best support the resiliency of the system.
Wright, VirginiaL [Idaho National Laboratory (INL)↗
Cyber-informed Engineering Battery Analysis Tool
The Cyber-Informed Engineering Battery Analysis Tool (CIEBAT) leverages the Department of Energy’s Cyber-Informed Engineering to prompt engineering designers and operators through an analysis of the critical functions to be supported by a BESS installation, the criticality of those functions, the impacts of denial, disruption or misuse of those functions within the BESS system, and the mitigations which could best prevent impacts to those functions resulting from cyber attack. Through use of this tool, BESS designers and operators can quickly identify appropriate engineering mitigation opportunities to limit impacts from cyber attack and functions where engineering and operational staff can prioritize and guide the application of cybersecurity protections to best support the resiliency of the system.
Lampe, BenjaminR [Idaho National Laboratory (INL),↗
Magnetic Gears: The Key to Robust, Cost-Effective Hydropower Drivetrains
Based on previous demonstrated success at fabricating 5 and 10 kW scale magnetic gearbox (MGB) prototypes, Emrgy and its partners (the project team) proposed to design and construct a 100 kW scale MGB with a 30:1 gear ratio for the low-head hydro applications. The Statement of Project Objectives included tasks covering: 1) Market Applicability; 2) Technical Metrics; 3) Design (initial); 4) Electromagnetic (EM) Load and Structural Analysis; 5) Modal Analysis; 6) Sealing Design and 7) Final Design during Budget Period 1. Budget Period 2 included tasks covering: 1) Materials Procurement and Test Plan Development; 2) Assembly; and 3) Testing. The Market Applicability study (Task 1) led to a clear conclusion and recommendation toward “Low Head” technologies for maximum market share of both New Stream Reach development as well as powering Non-Powered Dams. The findings of this study also identified the opportunity for a larger scale magnetic gearbox-based drive train as a function of increased torque, as opposed to increased speed. The Technical Metrics Study (Task 2) concluded a horizontal orientation was preferred, examined potential loss mechanisms, concluded that a Halbach Array magnetic design was preferred, established a 30:1 gear ratio as optimal, and established a power rating of 100 kW as optimal. The subsequent initial and final detailed design process included electro-magnetic (EM) load and structural analysis (Task 4), a Modal analysis (for vibration) (Task 5), and a sealing design (Task 6) to assure water impermeability. The final design package (Task 7) included 729 individual parts, 117 unique part numbers, and 15 assemblies. In order to facilitate procurement, the full bill of materials was broken down into several sub-components: 1) custom magnetic parts; 2) custom machined parts; 3) custom casted parts; and 4) commercial off the shelf (COTS) parts. The casted parts were fabricated by Oak Ridge National Laboratory (ORNL) via a Cooperative Research and Development Agreement (CRADA) with Emrgy and funded by the Advanced Manufacturing Office (AMO). The procurement effort (Task 8) ultimately covered three time periods based on challenges encountered in meeting the budgeted cost for the prototype. Following the first effort in the early stages of Budget Period 2 in 2017, a no-cost time extension was granted to seek alternative fabrication and procurement options. The project was re-booted in 2020 based on the new ORNL CRADA that would focus on five (5) of the more difficult and expensive parts using their advanced manufacturing expertise. Procurement efforts for the other custom machined parts resulted in quotations that still exceeded the budget by more than $\$$100k. This was, in part, also due to the concurrent COVID-19 pandemic that caused both supply chain disruptions and labor shortages. As the project continued, pricing and availability degraded further. In Q2 FY’22, it was decided to not proceed with the fabrication of the prototype (Task 9) based on budgetary limitations. Outcomes included a full and detailed design of a 100 kW magnetic gearbox and associated indented bill of materials (BOM) and CAD drawings, a full assembly instruction manual with an associated BOM for materials necessary to support assembly, the fabrication of the double Halbach magnetic array for the rotor/stator system, fabrication of five (5) sand-casted/machined parts (via CRADA with ORNL) and an initial draft of a comprehensive testing plan. The most significant non-outcome was the actual fabrication and testing of the prototype gearbox based on budget limitations. Lessons learned included the need for an Application / Design / Cost trade analysis to better elucidate the cost potential of the MGB in the projected volumes anticipated for future demand. This would better establish the efficacy of the original cost target ($\$$0.80/Watt) and/or the need for reconsideration of designs and applications. Likewise, additional consideration of the prototype nature of the gearbox – single use, short lifetime, etc. - either as a separate exercise or in place of the design process completed, to reduce the cost of the demonstration prototype device. Additionally, project continuity was cited as a significant risk based on the loss of the primary design engineering firm after Budget Period 1. A design analysis exercise was conducted at the conclusion of the project to identify potential areas for cost reduction. One concept considered was the removal of the inner ring of magnets (with associated changes in the outer ring magnets) to enable a horizontal collapse of the design. It was estimated this could reduce cost by 10-25% without impacting performance.
13 HYDRO ENERGY↗
Rocket engine analog simulation
Mathematical equations simulate the operation of a rocket engine, simulate destructive and nondestructive tests to verify engine design feasibility, and investigate nonlinear variations in engine performance.
Philyaw, B. K.↗
Preliminary appraisal of hydrogen and methane fuel in a Mach 2.7 supersonic transport
The higher heating value of hydrogen relative to JP fuel is estimated to reduce fuel weight by three fold and gross weight by 40 percent for comparable designed airplanes of equal payload and range. Engine design parameters were varied to determine the influence of lower noise goals on gross weight and direct operating cost. At current fuel prices, the DOC of a hydrogen airplane would be much higher than that of a JP airplane. A methane airplane could offer an 8.5-percent lower KOC than JP. But future shortages may escalate the prices of both JP and methane, whereas the price of hydrogen manufactured hydrolytically could be reduced from present levels. If in the future all three fuels are postulated to have equal costs per unit of energy, the DOC for hydrogen could be as much as 20 percent below that for JP on the reference 4000-nautical-mile mission. Longer ranges or lower noise requirements would improve the advantage of hydrogen.
Whitlow, J. B., Jr.↗
VSCE technology definition study
Refined design definition of the variable stream control engine (VSCE) concept for advanced supersonic transports is presented. Operating and performance features of the VSCE are discussed, including the engine components, thrust specific fuel consumption, weight, noise, and emission system. A preliminary engine design is presented.
Howlett, R. A.↗