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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

Incompressible Turbulent Wing-Body Junction Flow

The overall objective of this study is to contribute to the optimized design of fan bypass systems in advanced turbofan engines. Increasing the engine bypass ratios have provided a major boost in engine performance improvement over the last fifty years. An engine with high bypass ratio (11-16:1) such as the Advanced Ducted Propulsion (ADP) is being developed and is expected to provide an additional 25% improvement in overall efficiency over the early turbofans. Such significant improvements in overall efficiency would reduce the cost per seat mile, which is a major government and Industry challenge for the 21th century. The research is part of the Advanced Subsonic Technology (AST) program that involves a NASA, U.S. Industry and FAA partnership with the goal of a safe and highly productive global air transportation system. The immediate objective of the study is to perform numerical simulation of duct-strut interactions to elucidate the loss mechanisms associated with this configuration that is typical of advanced turbofan engines such as ADP. However, at present experimental data for a duct-strut configuration are not available. Thus, as a first step a wing-body junction flow would be studied and is the specific objective of the present study. At the outset it is to be recognized that while duct-strut interaction flow is similar to that of wing-body junction flows, there are some differences owing to the presence of a wall at both ends of the strut. Likewise, some differences are due to the sheared inflow (as opposed to a uniform inflow) velocity profile. It is however expected that some features of a wing-body junction flow would persist. Next, some of the salient aspects of the complex flow near a wing-body junction, as revealed by various studies reported in the literature will be reviewed. One of the principle characteristics of the juncture flow, is the presence of the mean flow components in a plane perpendicular to the direction of the oncoming free-stream flow. The lateral curvature of the wing/strat causes the oncoming turbulent layer to skew about am axis (x-axis) parallel to the plane (xz-plane) of the mean shear. This is the principle mechanism for the generation of secondary flow. Such skew-induced secondary flows are slow to be attenuated by Reynolds stresses. Additional contribution to the generation of secondary flow comes from anisotropies in Reynolds stresses. Upstream of the strut, the mean-vorticity is directed span wise (along the y-direction). The presence of secondary flow in the vicinity of the strut causes the vorticity to stretch around the obstacle in a horse-shoe shape, with each leg having a vorticity of the opposite sense. The blockage effect of the strut imposes a severe adverse pressure gradient on the oncoming turbulent shear layer, causing boundary layer separation ahead of the leading edge, resulting in a vortex that rolls up and flows downstream into the juncture region. The separation vortices trailing in the wake of the wing can alter the lift or drag characteristics of the surfaces downstream of the wing-body juncture. Likewise, on submarines, the wake flow behind the appendage can degrade the performance of the propeller located downstream. The complex nature of this flow is caused by the presence of all six components of Reynolds stresses. Devenport and Simpson report that in the vicinity of the horse-shoe vortex there is intense recirculation with turbulent stresses being much larger than those normally observed in turbulent flows. These features contribute to making this flow a challenge to predict numerically. Some of the past studies provide useful insights into this flow that would guide our numerical efforts. In measurements reported by Shabaka and Bradshaw, the eddy viscosity tensor is seen to be non-isotropic and has negative components in certain regions. In an effort to evaluate the closure assumptions of various turbulence models, Devenport and Simpson used their own extensive measurements in juncture flows around the nose of a wing-body junction. Measured values of mean-velocity and/or turbulence kinetic energy was used to predict the magnitude of the shear stress vector. Algebraic stress models performed the best followed by Cebeci-Smith eddy viscosity model. The flow is reported to be dominated by a pressure field produced by the wing and the velocity field generated by the horseshoe vortex that is wrapped around the junction between the wing and wall. Kubendran et al. conclude from an experimental study that the shape of leading edge of the wing as characterized by its slenderness ratio is a major factor in determining the flow fields in the juncture region. The more thinner the leading edge of the juncture, the weaker the horseshoe vortex is. Also, with a slender leading edge, the secondary flow in the juncture would be due mainly to the cross-stream gradients of Reynolds stresses rather than due to a lateral skewing of the shear layer.

Krishnamurthy, R.↗
NASA NTRS2012

Mercury Atomic Frequency Standards for Space Based Navigation and Timekeeping

A low power Mercury Atomic Frequency Standard (MAFS) has been developed and demonstrated on the path towards future space clock applications. A self contained mercury ion breadboard clock: emulating flight clock interfaces, steering a USO local oscillator, and consuming approx 40 Watts has been operating at JPL for more than a year. This complete, modular ion clock instrument demonstrates that key GNSS size, weight, and power (SWaP) requirements can be achieved while still maintaining short and long term performance demonstrated in previous ground ion clocks. The MAFS breadboard serves as a flexible platform for optimizing further space clock development and guides engineering model design trades towards fabrication of an ion clock for space flight.

Global Positioning Systems (GPS)↗
DOE OSTI2021

SMART-COM – Scalable Multi-Agent Adaptive Resolution Tools for Collaborative Outage Management

The purpose of this grant was to conduct scientific research and prototype applications to support NPP outage staff in their adaptive decision-making in efficient scheduling and resource allocation while preventing violation of safety technical specifications. The project contributed to scientific knowledge and engineering methods in (1) user interface design, (2) scheduling optimization and risk estimation, and (2) natural language processing that would benefit the nuclear power plants in minimizing schedule overruns and even unexpected shutdowns. The research team conducted site visits at a test reactor facility and an operating nuclear power plant to gather necessary information and inputs for research and development of a software application to support NPP staff in executing their outages. The final software application consisted of three modules. First, the natural language processing module supports interactive processing of technical documentation to build a database for outage staff to query non-permissible actions on system components. This module can alleviate outage staff from reviewing extensive documentation and minimize violation of technical specifications, especially in time-sensitive situations. Second, the schedule optimization module schedules outage activities and compute risk indices that outperform existing software and current practice. This module can reduce completion time of an outage that typically have too many activities for human to optimize based on current practice that does not apply the latest operations research. Finally, the visualization module presents progress and risk information of the overall outage and individual activities, as well as enabling access to the natural language processing and schedule optimization modules. This module can provide outage staff with situation awareness that are necessary to make risk-informed decisions in response to unexpected events during the execution of an outage.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Bridging Equipment Reliability Data and Risk Informed Decisions in a Plant Operation Context

Industry equipment reliability and asset management programs are essential elements that help ensure the safe and economical operation of nuclear power plants. The effectiveness of these programs is addressed in several industry-developed and regulatory programs. The Risk-Informed Asset Management (RIAM) project is tasked to develop tools in support of the equipment reliability and asset management programs at nuclear power plants. These tools are designed to create a direct bridge between component health/lifecycle data and decision making (e.g., maintenance scheduling and project prioritization). The goal of this article is to provide a guide for specific use cases that the RIAM project is targeting. We have grouped uses cases into three main areas. The first area focuses on the analysis of equipment reliability data with a particular emphasis on condition-based data, such as test/surveillance reports and component monitoring data. The second area focuses on the integration of equipment reliability into system/plant reliability models to determine system/plant health and identify the components that are critical to maintain an operational system. Lastly, the third area manages plant resources, such as maintenance activities and replacement scheduling using optimization methods. Here the primary focus is on supporting typical system engineer decisions regarding maintenance activity scheduling and component aging management. This is performed in a risk-informed context where the term “risk” is broadly constructed to include both plant reliability and economics. This framework combines data analytics tools to analyze equipment reliability data with risk-informed methods designed to support system engineer decisions (e.g., maintenance and replacement schedules, optimal maintenance posture) in a customizable workflow.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Steam Generator Model Design Parameter Sensitivity Study Using Advanced Optimization Tools

This study focuses on design parameter sensitivity studies pertaining to a steam generator (SG) model, using both Python and machine-learning tools. The SG model is a mathematical representation (including fluid flow and heat transfer equations/models/correlations) of a steam-generating unit in a pressurized water reactor (PWR)-type small modular reactor (SMR) system. Design studies involve changing the model’s input design parameters (e.g., temperature, pressure, mass flow rate) to observe the resulting effects on the output of the system (e.g., heat transfer coefficient [HTC], Nusselt number, heat transfer performance). Sensitivity studies analyze the degree to which system output and/or desired parameters (e.g., HTC or heat transfer performance) are sensitive to changes in input parameters. By using machine-learning tools such as the Risk Analysis Virtual Environment (RAVEN) developed at Idaho National Laboratory (INL), detailed design parametric sensitivity studies and model optimization were performed. Six input parameters—namely, the pressure, temperature, and mass flow rate for the inlet of the primary-side (hot fluid) and secondary-side (cold fluid) of the SG—were randomly perturbed via RAVEN’s Monte Carlo Sampler module, using uniform distributions (±1% relative changes). The analysis results give valuable insights into SG system performance and optimization, and provide justification for researching optimized sensor placement to effectively monitor and obtain experimental data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Steam Generator Model Design Parameter Sensitivity Study Using Advanced Optimization Tools

This study focuses on design parameter sensitivity studies pertaining to a steam generator (SG) model, using both Python and machine-learning tools. The SG model is a mathematical representation (including fluid flow and heat transfer equations/models/correlations) of a steam-generating unit in a pressurized water reactor (PWR)-type small modular reactor (SMR) system. Design studies involve changing the model’s input design parameters (e.g., temperature, pressure, mass flow rate) to observe the resulting effects on the output of the system (e.g., heat transfer coefficient [HTC], Nusselt number, heat transfer performance). Sensitivity studies analyze the degree to which system output and/or desired parameters (e.g., HTC or heat transfer performance) are sensitive to changes in input parameters. By using machine-learning tools such as the Risk Analysis Virtual Environment (RAVEN) developed at Idaho National Laboratory (INL), detailed design parametric sensitivity studies and model optimization were performed. Six input parameters—namely, the pressure, temperature, and mass flow rate for the inlet of the primary-side (hot fluid) and secondary-side (cold fluid) of the SG—were randomly perturbed via RAVEN’s Monte Carlo Sampler module, using uniform distributions (±1% relative changes). The analysis results give valuable insights into SG system performance and optimization, and provide justification for researching optimized sensor placement to effectively monitor and obtain experimental data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2003

Blended Wing Body Systems Studies: Boundary Layer Ingestion Inlets With Active Flow Control

A CFD analysis was performed on a Blended Wing Body (BWB) aircraft with advanced, turbofan engines analyzing various inlet configurations atop the aft end of the aircraft. The results are presented showing that the optimal design for best aircraft fuel efficiency would be a configuration with a partially buried engine, short offset diffuser using active flow control, and a D-shaped inlet duct that partially ingests the boundary layer air in flight. The CFD models showed that if active flow control technology can be satisfactorily developed, it might be able to control the inlet flow distortion to the engine fan face and reduce the powerplant performance losses to an acceptable level. The weight and surface area drag benefits of a partially submerged engine shows that it might offset the penalties of ingesting the low energy boundary layer air. The combined airplane performance of such a design might deliver approximately 5.5% better aircraft fuel efficiency over a conventionally designed, pod-mounted engine.

Geiselhart, Karl A.↗
DOE OSTI2021

Scalable Approaches to Selecting Key Entities in Large Networked Infrastructure Systems

This work aims at bringing advances in discrete optimization algorithms to solving practical engineering problems at scale. Often times, in many engineering design problems, there is a need to select a small set of influential or representative elements from a large ground set of entities in an optimal fashion. Submodular optimization provides for a formal way to solve such problems. Common examples with infrastructure systems involve sensor placement and identification of key entities with certain objectives. However, scaling these approaches to large infrastructure systems can be challenging because of the high computational complexity of the overall framework that include the optimization algorithms as well as high-complexity compute-oracles that provide the necessary objective function values. In this work, we explore a well-studied and widely-applicable paradigm, namely leader-selection in a multi-agent networked setting in the context of scalable methodologies. We demonstrate novel frameworks that utilize variations of accelerated submodular optimization algorithms along with linear-algebraic methods that can help accelerate the oracle computations. We further explore this combination in conjunction with graph partitioning paradigms to take advantage of the accelerated algorithms in a distributed setting. Finally we demonstrate the key findings on a practical problem in an operational setting. For this, we leverage an example road network with approximately 18k nodes and 27k edges in a traffic control application, where we seek a limited number of k=200 key intersections. This problem can be solved in a serial setting in just under 5 hours providing more than 2 orders of magnitude speed-up over methods that do not consider acceleration techniques.

Visweswara Sathanur, Arun↗
NASA NTRS2023

NASA GRC ICME Schema for Materials Data Management: An Executive Summary

Integrated Computational Materials Engineering (ICME) has received a growing emphasis in attention due its potential impact on rapid material design, reduction in cost and time to market for new applications, and the promise of ‘fit-for-purpose’ materials coupled with recent advances in high performance computing and material characterization tools. However, for an organization to implement ICME practices for material discovery and design, a series of both technical and cultural challenges must be overcome to foster an environment that enables efficient, traceable, and predictive multiscale simulations of material behavior to enable virtual design of materials. In 2016, NASA sponsored a 2040 Vision study to define the potential 25-year future state required for integrated multiscale modeling of materials and systems to improve both the associated time and cost for aerospace and aeronautical innovation. The study envisions a cyber-physical-social ecosystem of experimentally validated computational models, tools, and techniques, along with the associated digital tapestry, that can enable rapid, optimized, ‘fit-for-purpose’ design of materials, components, and systems. A key requirement for such an ecosystem is the development of a robust information management system for materials across their full lifecycle, including material pedigree, experimental (real) and virtual (simulation) data, developed material models, and the implementation of models in engineering applications, such that process-structure-property-performance relationships can be established, thereby enabling the virtual design and optimization of materials. Such an information management system must be able to effectively capture: i) material information at each length scale; ii) test data and analysis; iii) associated material models; and iv) material and model deployment in engineering applications. These systems must also provide traceability between experimental and virtual representations of the material to ensure, when appropriate, the material digital twin is maintained. Additionally, this robust material information management system must be able to seamlessly connect with both commercial and an organization’s in-house software tools, be they analysis tools, other material databases, product lifecycle management (PLM) or simulation data management (SDM) tools, etc., such that automation of the design and analysis of a material across multiple length scales is possible. In this paper, an executive summary of the NASA GRC ICME Schema for materials information management is presented. The database best practices and schema design philosophy specifically for ICME materials data management and an overview description of each element in the schema is given, along with its associated role in an ICME workflow. Additionally, auxiliary tools that interact with the database and provide judicious automation with regards to importing, exporting, and analyzing materials data are presented. Such tools are critical to an ICME ecosystem, not only for their role in enabling optimization, but also in relieving users of tedious manual tasks, thus helping to promote adoption and combat the cultural challenges organizations face in enabling ICME.

Materials↗
DOE OSTI2022

A New Shape Optimization Approach for Lightweighting Electric Machines Inspired by Additive Manufacturing

Minimizing the mass in electric machines while maintaining superior performance is a new requirement for the advancement of drivetrains used in wind energy and electric mobility. Topology optimization (TO) for lightweighting electric machines using traditional approaches typically explores a restricted design space allowed by standard parametrizable geometry and manufacturing, while advanced methods, such as cell-based density approaches, suffer from a lack of robust manufacturability constraints during the optimization process. To overcome these drawbacks, we explore a grid-independent, boundary optimization where the outer shape of the magnet is parameterized using Bezier curves. We conduct a design of experiments (DOE) to study the effect of different magnet shapes on machine performance by varying the control points on the Bezier curves. A machine-learning-based surrogate model is constructed using the data from the DOE to quantify the relationship between the control points, air-gap torque, and mass. The control points are then optimized to maximize the torque density. The approach is used for minimizing electrical steel mass in the International Energy Agency (IEA) 15-MW radial flux direct-drive wind turbine generator. The new approach to shape optimization resulted in smooth and concise shapes that can be easily additively manufactured with up to a 20-ton reduction in electrical steel mass.

additive manufacturing↗
DOE OSTI2023

Scale-up Testing of Advanced Polaris Membrane in CO2 Capture Technology

This final technical report describes work conducted by Membrane Technology and Research, Inc. (MTR) for the U.S. Department of Energy (DOE), National Energy Technology Lab (NETL) on the scale-up and testing of advanced Polaris™ membrane CO2 capture technology at the Technology Centre Mongstad (TCM) under award number DE-FE0031591. The work was performed from August 1, 2018 through January 31, 2023. The overall goal of this project was to design, build and operate an advanced Polaris membrane CO2 capture system at TCM. MTR was assisted in this project by Trimeric Corporation (Trimeric), an engineering design services company, the Carbon Capture Simulation for Industry Impact (CCSI2), a partnership among national laboratories, industry, and academic institutions, and the Technology Centre Mongstad (TCM), who provided the host site for the slipstream field test. This report details the work conducted to scale-up MTR’s second-generation (Gen-2) Polaris membrane and advanced planar membrane modules to a final form factor optimized for commercial use; validate their performance in an engineering-scale field test at TCM; and to show the potential of the MTR process to meet DOE CO2 capture targets from large source point emitters. Work for this project included membrane optimization and scale-up, advanced planar module design and fabrication, design and fabrication of an engineering-scale field test membrane skid, operation of the field test skid processing Residue Fluid Catalytic Cracker (RFCC) industrial flue gas at TCM, and a detailed techno-economic analysis (TEA) of the MTR membrane post-combustion process for CO2 capture. This project validated recent membrane technology advancements at the engineering-scale, moves the MTR advanced post-combustion capture technology to TRL-6, and mitigates risk in future Large Pilot or Demonstration scale-up activities.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS2010

Health Maintenance System (HMS) Hardware Research, Design, and Collaboration

The Space Life Sciences division (SLSD) concentrates on optimizing a crew member's health. Developments are translated into innovative engineering solutions, research growth, and community awareness. This internship incorporates all those areas by targeting various projects. The main project focuses on integrating clinical and biomedical engineering principles to design, develop, and test new medical kits scheduled for launch in the Spring of 2011. Additionally, items will be tagged with Radio Frequency Interference Devices (RFID) to keep track of the inventory. The tags will then be tested to optimize Radio Frequency feed and feed placement. Research growth will occur with ground based experiments designed to measure calcium encrusted deposits in the International Space Station (ISS). The tests will assess the urine calcium levels with Portable Clinical Blood Analyzer (PCBA) technology. If effective then a model for urine calcium will be developed and expanded to microgravity environments. To support collaboration amongst the subdivisions of SLSD the architecture of the Crew Healthcare Systems (CHeCS) SharePoint site has been redesigned for maximum efficiency. Community collaboration has also been established with the University of Southern California, Dept. of Aeronautical Engineering and the Food and Drug Administration (FDA). Hardware disbursements will transpire within these communities to support planetary surface exploration and to serve as an educational tool demonstrating how ground based medicine influenced the technological development of space hardware.

Gonzalez, Stefanie M.↗
DOE OSTI2023

Sensitivity-Driven Experimental Design to Facilitate Control of Dynamical Systems

Control of nonlinear dynamical systems is a complex and multifaceted process. Essential elements of many engineering systems include high-fidelity physics-based modeling, offline trajectory planning, feedback control design, and data acquisition strategies to reduce uncertainties. Here this article proposes an optimization-centric perspective which couples these elements in a cohesive framework. We introduce a novel use of hyper-differential sensitivity analysis to understand the sensitivity of feedback controllers to parametric uncertainty in physics-based models used for trajectory planning. These sensitivities provide a foundation to define an optimal experimental design which seeks to acquire data most relevant in reducing demand on the feedback controller. Our proposed framework is illustrated on the Zermelo navigation problem and a hypersonic trajectory control problem using data from NASA’s X-43 hypersonic flight tests.

42 ENGINEERING↗
NASA NTRS1993

Effect of design selection on response surface performance

The mathematical formulation of the engineering optimization problem is given. Evaluation of the objective function and constraint equations can be very expensive in a computational sense. Thus, it is desirable to use as few evaluations as possible in obtaining its solution. In solving the equation, one approach is to develop approximations to the objective function and/or restraint equations and then to solve the equation using the approximations in place of the original functions. These approximations are referred to as response surfaces. The desirability of using response surfaces depends upon the number of functional evaluations required to build the response surfaces compared to the number required in the direct solution of the equation without approximations. The present study is concerned with evaluating the performance of response surfaces so that a decision can be made as to their effectiveness in optimization applications. In particular, this study focuses on how the quality of approximations is effected by design selection. Polynomial approximations and neural net approximations are considered.

Carpenter, William C.↗
NASA NTRS1981

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.↗
NASA NTRSDate not supplied

Optimization of Rocket Engine Components using Multi-Metallic Additive Manufacturing

Additive manufacturing (AM) is advancing many applications of component design for liquid rocket engines. AM has been demonstrated in various rocket component applications using a variety of monolithic metal alloys, many of which are traditional alloys for extreme environments. NASA and industry partners have focused in recent years to advance processing to create bimetallic and multicomponent AM processes and materials. The role of multi-metallic AM offers advantages since it can further optimize weight, optimize reliability and performance by increasing the strength to weight ratio of a component, and can optimize materials for various engineering requirements. NASA’s Rapid Analysis and Manufacturing Propulsion Technology (RAMPT) project has designed and manufactured a series of additively manufactured (AM) coupled combustion chambers, nozzles, and other engine components to advance new AM processes and materials with the goal of reducing cost and schedule for engine manufacturing. These designs incorporated multimetallic AM, which further enabled carbon-fiber composite overwrap to reduce overall thrust chamber assembly (TCA) mass. Various AM processes were demonstrated on these components using a copper-based alloy/superalloy bimetallic solution. The AM processes being explored individually and in combination for bimetallic applications include Laser Powder Bed Fusion (L-PBF), Laser Powder Directed Energy Deposition (LP-DED), and cold spray. The combination of bimetallic material combinations explored in this research include GRCop-based alloys and superalloys, Inconel 625 or NASA HR-1. One unique development that will be presented is the combustion chamber and nozzle as a single component by using freeform integrated DED to build the nozzle directly onto the aft end of the chamber. The various aspects of the additive manufacturing processes and challenges, materials characterization and mechanical testing, and hot-fire testing of bimetallic components in a relevant rocket engine environment will be discussed.

Additive Manufacturing↗
DOE OSTI2026

Accelerating Traction Motor Optimization Design with AI Surrogate Models

The advancement of artificial intelligence systems enables the use of data-driven physics-based surrogate models to explore design spaces rapidly and deeply for engineering projects. This work presents a surrogate model workflow that accelerates electric traction motor design optimization by replacing finite element analysis (FEA) with an artificial neural network (ANN) and using this model in a genetic algorithm for design optimization. A baseline interior permanent-magnet motor is parameterized and sampled to generate FEA-labeled training data, after which a feed-forward ANN predicts key outputs (e.g., loss components and weight). The validated surrogate enables genetic-algorithm optimization and deep search over the design space without new FEA runs, producing Pareto-optimal trade-offs between weight and losses and set of optimized designs for rapid downselection of manufacturable motor designs.

Ribeiro, Pedro [ORNL] (ORCID:0009000921026641)↗
NASA NTRS1981

Advanced oxygen-hydrocarbon rocket engine study

This study identifies and evaluates promising LO2/HC rocket engine cycles, produces a consistent and reliable data base for vehicle optimization and design studies, demonstrates the significance of propulsion system improvements, and selects the critical technology areas necessary to realize an improved surface to orbit transportation system. Parametric LO2/HC engine data were generated over a range of thrust levels from 890 to 6672 kN (200K to 1.5M 1bF) and chamber pressures from 6890 to 34500 kN (1000 to 5000 psia). Engine coolants included RP-1, refined RP-1, LCH4, LC3H8, LO2, and LH2. LO2/RP-1 G.G. cycles were found to be not acceptable for advanced engines. The highest performing LO2/RP-1 staged combustion engine cycle utilizes LO2 as the coolant and incorporates an oxidizer rich preburner. The highest performing cycle for LO2/LCH4 and LO2/LC3H8 utilizes fuel cooling and incorporates both fuel and oxidizer rich preburners. LO2/HC engine cycles permitting the use of a third fluid LH2 coolant and an LH2 rich gas generator provide higher performance at significantly lower pump discharge pressures. The LO2/HC dual throat engine, because of its high altitude performance, delivers the highest payload for the vehicle configuration that was investigated.

Obrien, C. J.↗