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DOE OSTI2020

A novel active optimization approach for rapid and efficient design space exploration using ensemble machine learning

In this work, a novel design optimization technique based on active learning, which involves dynamic exploration and exploitation of the design space of interest using an ensemble of machine learning algorithms, is presented. In this approach, a hybrid methodology incorporating an explorative weak learner (regularized basis function model) which fits high-level information about the response surface, and an exploitative strong learner (based on committee machine) that fits finer details around promising regions identified by the weak learner, is employed. For each design iteration, an aristocratic approach is used to select a set of nominees, where points that meet a threshold merit value as predicted by the weak learner are selected to be evaluated using expensive function evaluation. In addition to these points, the global optimum as predicted by the strong learner is also evaluated to enable rapid convergence to the actual global optimum once the most promising region has been identified by the optimizer. This methodology is first tested by applying it to the optimization of a two-dimensional multi-modal surface. The performance of the new active learning approach is compared with traditional global optimization methods, namely micro-genetic algorithm (pGA) and particle swarm optimization (PSO). It is demonstrated that the new optimizer is able to reach the global optimum much faster with a significantly fewer number of function evaluations. Subsequently, the new optimizer is also applied to a complex internal combustion (IC) engine combustion optimization case with nine control parameters related to fuel injection, initial thermodynamic conditions, and in-cylinder flow. It is again found that the new approach significantly lowers the number of function evaluations that are needed to reach the optimum design configuration (by up to 80%) when compared to particle swarm and genetic algorithm-based optimization techniques.

Machine learning, active learning, design optimiza↗

NASA NTRS2011

NASA Tech Briefs, September 2011

Topics covered include: Fused Reality for Enhanced Flight Test Capabilities; Thermography to Inspect Insulation of Large Cryogenic Tanks; Crush Test Abuse Stand; Test Generator for MATLAB Simulations; Dynamic Monitoring of Cleanroom Fallout Using an Air Particle Counter; Enhancement to Non-Contacting Stress Measurement of Blade Vibration Frequency; Positively Verifying Mating of Previously Unverifiable Flight Connectors; Radiation-Tolerant Intelligent Memory Stack - RTIMS; Ultra-Low-Dropout Linear Regulator; Excitation of a Parallel Plate Waveguide by an Array of Rectangular Waveguides; FPGA for Power Control of MSL Avionics; UAVSAR Active Electronically Scanned Array; Lockout/Tagout (LOTO) Simulator; Silicon Carbide Mounts for Fabry-Perot Interferometers; Measuring the In-Process Figure, Final Prescription, and System Alignment of Large; Optics and Segmented Mirrors Using Lidar Metrology; Fiber-Reinforced Reactive Nano-Epoxy Composites; Polymerization Initiated at the Sidewalls of Carbon Nanotubes; Metal-Matrix/Hollow-Ceramic-Sphere Composites; Piezoelectrically Enhanced Photocathodes; Iridium-Doped Ruthenium Oxide Catalyst for Oxygen Evolution; Improved Mo-Re VPS Alloys for High-Temperature Uses; Data Service Provider Cost Estimation Tool; Hybrid Power Management-Based Vehicle Architecture; Force Limit System; Levitated Duct Fan (LDF) Aircraft Auxiliary Generator; Compact, Two-Sided Structural Cold Plate Configuration; AN Fitting Reconditioning Tool; Active Response Gravity Offload System; Method and Apparatus for Forming Nanodroplets; Rapid Detection of the Varicella Zoster Virus in Saliva; Improved Devices for Collecting Sweat for Chemical Analysis; Phase-Controlled Magnetic Mirror for Wavefront Correction; and Frame-Transfer Gating Raman Spectroscopy for Time-Resolved Multiscalar Combustion Diagnostics.

Source record↗

DOE OSTI2023

Energy Optimization of Light and Heavy-Duty Vehicle Cohorts of Mixed Connectivity, Automation and Propulsion System Capabilities via Meshed V2V-V2I and Expanded Data Sharing (Final Scientific and Technical Report)

Vehicle connectivity and automated driving technologies individually have the potential to decrease energy consumption and/or increase safety on light, medium or heavy duty vehicles to varying degrees depending on the traffic infrastructure and specific driving scenarios. Due to advances in sensing, perception and computing power, research and development emphasis in the mobility sector has shifted away from connectivity. Prior research has shown that driving automation with the absence of connectivity can in certain circumstances increase energy consumption. The effectiveness of synergizing connectivity and driving automation technologies is the focus of this work, specifically applied to vehicle cohorts of mixed composition, light and heavy duty, and powertrains ranging from all electric to conventional internal combustion engine. The project team is led by Michigan Technological University (MTU) and partnered with AVL Mobility Technologies Inc. (AVL), Borg Warner (BW), Traffic Technology Services (TTS), American Center for Mobility (ACM) and Navistar (NAV). The main thrusts for the team are to develop a micro-traffic simulation environment with specific VD&PT system attributes and CAV capabilities, 2) field a vehicle test fleet of mixed classification, propulsion and CAV capacity, 3) develop artificial intelligence (AI) and machine learning (ML) based multi-agent optimization methods for various traffic infrastructures, 4) integrate the virtual environment and the optimization methods then deploy the system as a CAV hardware in the loop (HiL) for the vehicle test fleet and 5) conduct closed track and public road testing to validate simulation and demonstrated energy and mobility improvements at multiple scales. For a cohort of mixed vehicles, the team will demonstrate a reduction of energy consumption of 10-50% at intersection, arterial roadway and limited access highway scenarios through connectivity and automation in simulation and at a closed test track. The energy reduction objectives of the project are summarized in Table 1, indicating the infrastructure and over what distances are relevant considered. Single scenario energy reductions are not relevant and thus, the research team took the approach to vary parameters associated with the infrastructure, vehicle cohort composition and dynamic behavior to generate energy consumption distributions for both unconnected and connected scenarios.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS1999

Combustion of Metals in Reduced-Gravity and Extraterrestrial Environment

As a result of the ongoing exploration of Mars and the several unmanned and manned missions planned for the future, increased attention has been given to the use of the natural resources of the planet for rocket propellant production and energy generation. Since the atmosphere of Mars consists of approximately 95% carbon dioxide (CO2), this gas is the resource of choice to be employed for these purposes. Unfortunately, CO2 is also a final product in most combustion reactions, requiring further processing to extract useful reactants such as carbon monoxide (CO), oxygen (O2), and hydrocarbons. An exception is the use Of CO2 as an oxidizer reacting directly with metal fuel. Since many metals burn vigorously with CO2, these may be used as an energy source and as propellants for an ascent/descent vehicle in sample-collection missions on Mars. In response to NASA's Human Exploration and Development of Space (HEDS) Enterprise to search for appropriate in-situ resource utilization techniques, this investigation will study the burning characteristics of promising metal/CO2 combinations. The use of reduced gravity is essential to eliminate the intrusive buoyant flows that plague the high-temperature metal reactions, to remove the destructive effect of gravity on the shape of molten metal samples, and to study the influence of radiative heat transfer from solid oxides undisturbed by natural convection. In studies with large metal specimens, the burning process is invariably influenced by strong convective currents that accelerate the reaction and shorten the burning times. Although these currents are nearly absent from small burning particles, the high emissivity of the flames, rapid reaction, small length scales, and intermittent explosions make the gathering of any useful information on burning rates and flame structure very difficult. This investigation has the ultimate goal of providing a careful probing of flame structure and dynamics by taking advantage of large, free-floating spherical metal samples and their corresponding long burning times available in reduced gravity. The first set of experiments has been conducted with magnesium (Mg) samples burning in the low-gravity environment generated by an aircraft flying parabolic trajectories. Owing to its high adiabatic flame temperature, oxidizer/fuel ratio, and heat per unit mass of fuel, as well as its low toxicity and low ignition temperature, Mg has been identified as a promising metal fuel with CO2 as oxidizer. The experimental effort is complemented by the development of a numerical model combining gas-phase chemical kinetics and transport mechanisms.

Abbud-Madrid, A.↗

DOE OSTI2026

A GPU-based compressible combustion solver for applications exhibiting disparate space and time scales

High-speed chemically active flows pose significant computational challenges due to their disparate space and time scales, with stiff chemistry often dominating simulation time. While modern scientific computing programs achieve exascale performance by leveraging graphics processing units (GPUs), existing GPU-based compressible combustion solvers face critical limitations in memory management, load balancing, and handling the highly localized nature of chemical reactions. To this end, we present a high-performance compressible reacting flow solver built on the AMReX framework and optimized for multi-GPU settings. Here, our approach addresses three GPU performance bottlenecks: memory access patterns through column-major storage optimization, computational workload variability via a bulk-sparse integration strategy for chemical kinetics, and multi-GPU load distribution for adaptive mesh refinement applications. The solver adapts existing matrix-based chemical kinetics formulations to multi-grid contexts. Using representative combustion applications, including 2D and 3D detonations and a 3D jet-in-crossflow configuration, we demonstrate 1.4–5× performance improvements over initial implementations on an in-house cluster of NVIDIA H100 GPUs, and near-ideal weak scaling on the Frontier supercomputer (Oak Ridge Leadership Computing Facility) with up to 1024 AMD Instinct MI250X GPUs. Roofline analysis reveals substantial improvements in arithmetic intensity for both convection (∼ 10 ×) and chemistry (∼ 4 ×) routines, confirming efficient utilization of GPU memory bandwidth and computational resources.

42 ENGINEERING↗

NASA NTRS1999

A Design Tool for Liquid Rocket Engine Injectors

A practical design tool for the analysis of flowfields near the injector face has been developed and used to analyze the Fastrac engine. The objective was to produce a computational design tool which was detailed enough to predict the interactive effects of injector element impingement angles and points and the momenta of the individual orifice flows. To obtain a model which could be used to simulate a significant number of individual orifices, a homogeneous computational fluid dynamics model was developed. To describe liquid and vapor sub- and super-critical flows, the model included thermal and caloric equations of state which were valid over a wide range of pressures and temperatures. A homogeneous model was constructed such that the local state of the flow was determined directly, i.e. the quality of the flow was calculated. Such a model does not identify drops or their distribution, but it does allow the flow along the injector face and into the acoustic cavity to be predicted. It also allows the film coolant flow to be accurately described. The initial evaluation of the injector code was made by simulating cold flow from an unlike injector element and from a like-on-like overlapping fan (LOL) injector element. The predicted mass flux distributions of these injector elements compared well to cold flow test results. These are the same cold flow tests which serve as the data base for the JANNAF performance prediction codes. The flux distributions 1 inch downstream of the injector face are very similar; the differences were somewhat larger at further distances from the faceplate. Since the cold flow testing did not achieve good mass balances when integrations across the entire fan were made, the CFD simulation appears to be reasonable alternative to future cold flow testing. To simulate the Fastrac, an RP-1/LOX combustion model must be chosen. This submodel must be relatively simple to accomplish three-dimensional, multiphase flow simulations. Single RP-1 pyrolysis and partial oxidation steps were chosen and the combustion was completed with the wet CO mechanism. Soot was also formed with a single global reaction. To validate the combustion submodel, global data from gas generator tests and from subscale motor test were used to predict qualitatively correct mean molecular weights, temperature, and soot levels. Because such tests do not provide general kinetics rates, the methodology is not necessarily appropriate for other than rocket type flows conditions. Soot predictions were made so that radiation heating to the motor walls can be made. These initial studies of the Fastrac were for a small region close to the injector face and chamber wall which included a segment of the acoustic cavity. The region analyzed includes 11 individual orifice holes to represent the LOL elements and the H2 film coolant holes. Typical results of this simulation are shown in Figure 1. At this point the only available test data to verify the predictions are temperatures measured in the acoustic cavity. These temperatures are in reasonable agreement at about 2000R (1111 K). Future work is expected to include improving the computational efficiency or the CFD model and/or using more computer capacity than the single Pentium PC with which these simulations were made.

Farmer, Richard C.↗

NASA NTRS2002

Quasi-One-Dimensional Modeling of Pulse Detonation Rocket Engines

Pulsed detonation rocket engines (PDREs) have generated considerable research interest in recent years as a chemical propulsion system potentially offering improved performance and reduced complexity compared to conventional rocket engines. The detonative mode of combustion employed by these devices offers a thermodynamic advantage over the constant-pressure deflagrative combustion mode used in conventional rocket engines and gas turbines. However, while this theoretical advantage has spurred a great deal of interest in building PDRE devices, the unsteady blowdown process intrinsic to the PDRE has made realistic estimates of the actual propulsive performance problematic. The recent review article by Kailasanath highlights some of the difficulties in comparing the available experimental measurements with numerical models. In a previous paper by the author, parametric studies of the performance of a single, straight-tube PDRE were reported. A 1-D, unsteady method of characteristics code, employing a constant-gamma assumption behind the detonation front, was developed for that study. Models of this type are computationally inexpensive, and are particularly useful for parametric performance comparisons. For example, a plot showing the specific impulse of various PDRE and steady-state rocket engine (SSRE) configurations as a function of blowdown pressure ratio. The performance curves clearly indicate that a straight-tube PDRE is superior in specific impulse to a SSRE with a sonic nozzle over the entire range of pressure ratios. Note, however, that a straight-tube PDRE in general does not compare favorably to a SSRE fitted with an optimized de Laval supersonic nozzle, particularly at the high pressure ratios typical for boost or in-space rocket applications. However, the calculations also show that if a dynamically optimized, supersonic de Laval nozzle could be could be fitted to a PDRE, then the specific impulse of the device would exceed that of a comparable SSRE. While such a nozzle is a considerable idealization, it is clear that nozzle design and optimization will play a critical role in whether the performance potential of PDREs can be effectively realized in practice. In order to study PDRE nozzle issues with greater accuracy, a quasi-one-dimensional, finite-rate chemistry CFD code has been developed by the author. Comparisons of the code with both the previous MOC model and experimental data from Stanford University are reported. The effect of constant-gamma and finite-rate chemistry assumptions on the flowfield and performance is examined. Parametric studies of the effect of nozzle throat size and expansion ratio, at various blowdown pressure ratios, are reported.

Morris, Christopher I.↗

DOE OSTI2021

Fuel Stratification Influence on NO x Emission in a Premixed Axial Reacting Jet-in-Crossflow at High Pressure

Three reacting jet-in-crossflow (JiC) methane/air flames were numerically investigated in a lean axially staged combustor at a pressure of five atmospheres. A detailed chemistry Star-CCM+ computational fluid dynamics (CFD) model was used with 53 species considered and the result of turbulence-governed finite-rate modeling was validated with in-house experimental data. An optically accessible test section features three side windows, allowing local flow and flame analysis with particle image velocimetry (PIV) and CH* chemiluminescence as well as pressure, temperature, and species exit measurements. The research objective was to predict and verify NO x formation of the premixed 12.7 mm axial jet. Three headend temperature levels were investigated along with three premixed jets at lean (φ Jet = 0.75), near-stoichiometric (φ Jet = 1.07), and rich (φ Jet = 1.78) axial fuel line equivalence ratio. Based on the matching exit emission concentration, global emission benefits were investigated by adjustment of the fuel stratification. The perfectly premixed methane/air flames of this study were shown to ignite at the lee-side of the jet. For the elevated headend temperature level T = 1800 K, the flame extended beyond the windward jet trajectory and caused high axial NO production. For industry application, a firing temperature of 1920 K was achieved with a NO x optimized fuel split of 25%, combining a lean headend (φ Headend = 0.61) with a rich (φ Jet = 1.78) jet equivalence ratio. As a result, this operating point allowed minimization of the combustor residence time at temperatures above 1700 K as well as combustion in a compact flame at the jet lee-side along the counter rotating vortex pair.

03 NATURAL GAS↗

NASA NTRS2004

Investigation of Navier-Stokes Code Verification and Design Optimization

With rapid progress made in employing computational techniques for various complex Navier-Stokes fluid flow problems, design optimization problems traditionally based on empirical formulations and experiments are now being addressed with the aid of computational fluid dynamics (CFD). To be able to carry out an effective CFD-based optimization study, it is essential that the uncertainty and appropriate confidence limits of the CFD solutions be quantified over the chosen design space. The present dissertation investigates the issues related to code verification, surrogate model-based optimization and sensitivity evaluation. For Navier-Stokes (NS) CFD code verification a least square extrapolation (LSE) method is assessed. This method projects numerically computed NS solutions from multiple, coarser base grids onto a freer grid and improves solution accuracy by minimizing the residual of the discretized NS equations over the projected grid. In this dissertation, the finite volume (FV) formulation is focused on. The interplay between the xi concepts and the outcome of LSE, and the effects of solution gradients and singularities, nonlinear physics, and coupling of flow variables on the effectiveness of LSE are investigated. A CFD-based design optimization of a single element liquid rocket injector is conducted with surrogate models developed using response surface methodology (RSM) based on CFD solutions. The computational model consists of the NS equations, finite rate chemistry, and the k-6 turbulence closure. With the aid of these surrogate models, sensitivity and trade-off analyses are carried out for the injector design whose geometry (hydrogen flow angle, hydrogen and oxygen flow areas and oxygen post tip thickness) is optimized to attain desirable goals in performance (combustion length) and life/survivability (the maximum temperatures on the oxidizer post tip and injector face and a combustion chamber wall temperature). A preliminary multi-objective optimization study is carried out using a geometric mean approach. Following this, sensitivity analyses with the aid of variance-based non-parametric approach and partial correlation coefficients are conducted using data available from surrogate models of the objectives and the multi-objective optima to identify the contribution of the design variables to the objective variability and to analyze the variability of the design variables and the objectives. In summary the present dissertation offers insight into an improved coarse to fine grid extrapolation technique for Navier-Stokes computations and also suggests tools for a designer to conduct design optimization study and related sensitivity analyses for a given design problem.

Vaidyanathan, Rajkumar↗

DOE OSTI2020

Scaling Turbulent Combustion Fields in Explosions

We considered the topic of explosions from spherical high-explosive (HE) charges. We studied how the turbulent combustion fields scale. On the basis of theories of dimensional analysis by Bridgman and similarity theories of Sedov and Barenblatt, we found that all fields scaled with the explosion length scale r0. This included the blast wave, the mean and root mean squared (RMS) profiles of thermodynamic variables, combustion variables, velocities, vorticity, and turbulent Reynolds stresses. This was a consequence of the formulation of the problem and our numerical method, which both satisfied the similarity conditions of Sedov. We performed numerical simulations of 1 g charges and 1 kg charges; the solutions were identical (within roundoff error) when plotted in scaled variables. We also explored scaling laws related to three-phase pyrotechnic explosions. We show that although the scaling formally broke down, the fireball still essentially scaled with the explosion length scale r0. However, the discrete Lagrange particles (DLP) (phase 2) and the heterogeneous continuum model (HCM) of the DLP wakes (phase 3) did not scale with r0, and mean and RMS profiles could differ by a factor of 10 in some regions. This was because the DLP particles and wakes introduced an additional scale that broke the similarity conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS2022

A Transient Hydrodynamic Model of Screen Channel Liquid Acquisition Devices for In-Space Cryogenic Propellant Management

Screen channel liquid acquisition devices (LADs) will play a crucial role in future deep space travel. It is essential that vapor-free delivery of propellants during tank-to-tank transfer is ensured to maximize yield from storage tanks and prevent potential combustion instabilities. The screen channel LAD utilizes a fine screen wire mesh that can separate phases in a low Bond number (i.e. microgravity) environment using surface tension forces. This study presents the development and verification of a new model for transient screen compliance, one of the influential factors for screen channel LAD design. Screen compliance is crucial during LAD channel outflow transients because the slight deflection of the screen can provide needed mass to satisfy rapid outflow demands and reduce the pressure difference across the screen. The model is successfully verified against CFD simulations. In addition, the characteristic speed for the governing screen compliance equations is derived which allows for numerical stability criteria to be established. As shown in this study, the transient maximum pressure difference across the screen can greatly exceed the steady state maximum pressure difference across the screen in many cases.

Hydrodynamics Simulations↗

DOE OSTI2024

Electromagnetic Energy-Assisted Thermal Conversion of Fossil-Based Hydrocarbons to Low-Cost Hydrogen

The goal of this project was to develop and optimize catalysts for methane decomposition, particularly focusing on regeneration via an electromagnetic energy-assisted mechanism, to produce hydrogen more cost-effectively compared to electrolysis routes. To achieve this goal, the project pursued several key objectives. The project began with the preparation and testing of various catalysts. A nickel-silica based catalyst was identified as the most promising material for the pyrolysis of methane into carbon and hydrogen. Kinetic parameters for methane decomposition were determined, aiding in computational modeling efforts. Structured catalysts were investigated, highlighting the need for frequent cleaning or regeneration to maintain performance, with methane conversion rates exceeding 70% in tube furnace tests. Computational fluid dynamics modeling was employed to optimize reactor designs and electrode angles, leading the project team to propose a multi-compartment thermal conversion system for larger setups. This modeling work was important in understanding reaction characteristics, carbon deposition rates, and temperature profiles under various conditions. A bench-scale reactor system was assembled to evaluate catalyst regeneration using electromagnetic energy-assisted mechanisms. Experiments demonstrated the potential for carbon removal, though further optimization is needed. The carbon produced from the methane conversion process was evaluated for potential use in lithium-ion battery electrodes. The carbon exhibited properties similar to commercially available high-purity multi-walled carbon nanotubes and nanofibers, with a carbon content greater than 95%. Coin cell batteries assembled with this carbon showed that lower replacement levels (10% to 33%) outperformed the control group, improving specific capacity density and stability. However, higher replacement levels (100%) demonstrated poorer performance, suggesting that excessive carbon substitution negatively impacts battery performance. These findings indicate the potential marketability of the produced carbon as a component in lithium-ion batteries, though further testing is necessary to confirm long-term advantages and disadvantages associated with the use of the carbon product. These results however justified further technoeconomic assessments to determine if the process can provide low-cost hydrogen. The economic feasibility and technical performance of methane decomposition for hydrogen production were assessed, focusing on three plant configurations: 100E (electrically heated), 100C (combustion heated using produced hydrogen), and PE-Hybrid (a combination of pyrolysis (indicating decomposition) and electrolysis). The Levelized Cost of Hydrogen (LCOH) for the pyrolysis configurations was found to be approximately 25% lower than that of electrolysis. The 100E configuration had the lowest LCOH at $\$$3.12/kg. Including carbon product sales significantly improved the economics, with the 100C configuration achieving a negative LCOH of -$\$$0.35/kg. The PE-Hybrid configuration was not economically advantageous compared to pure pyrolysis plants due to its complexity and additional equipment requirements. Ultimately, methane pyrolysis presents a viable method for near carbon dioxide-free hydrogen production, with significant economic advantages over electrolysis, especially when considering the sale of carbon byproducts. The 100E and 100C configurations showed the most promise, with the choice between them ultimately depending on the prices of power and natural gas. In conclusion, this technology has the potential to lower hydrogen production costs by leveraging the methane decomposition process with the sale of valuable carbon byproducts. By optimizing catalyst performance and integrating electromagnetic energy-assisted regeneration, the process can achieve higher efficiency and economic viability, making it a competitive alternative to traditional hydrogen production methods.

08 HYDROGEN↗

NASA NTRS1996

Wave Engine Topping Cycle Assessment

The performance benefits derived by topping a gas turbine engine with a wave engine are assessed. The wave engine is a wave rotor that produces shaft power by exploiting gas dynamic energy exchange and flow turning. The wave engine is added to the baseline turboshaft engine while keeping high-pressure-turbine inlet conditions, compressor pressure ratio, engine mass flow rate, and cooling flow fractions fixed. Related work has focused on topping with pressure-exchangers (i.e., wave rotors that provide pressure gain with zero net shaft power output); however, more energy can be added to a wave-engine-topped cycle leading to greater engine specific-power-enhancement The energy addition occurs at a lower pressure in the wave-engine-topped cycle; thus the specific-fuel-consumption-enhancement effected by ideal wave engine topping is slightly lower than that effected by ideal pressure-exchanger topping. At a component level, however, flow turning affords the wave engine a degree-of-freedom relative to the pressure-exchanger that enables a more efficient match with the baseline engine. In some cases, therefore, the SFC-enhancement by wave engine topping is greater than that by pressure-exchanger topping. An ideal wave-rotor-characteristic is used to identify key wave engine design parameters and to contrast the wave engine and pressure-exchanger topping approaches. An aerodynamic design procedure is described in which wave engine design-point performance levels are computed using a one-dimensional wave rotor model. Wave engines using various wave cycles are considered including two-port cycles with on-rotor combustion (valved-combustors) and reverse-flow and through-flow four-port cycles with heat addition in conventional burners. A through-flow wave cycle design with symmetric blading is used to assess engine performance benefits. The wave-engine-topped turboshaft engine produces 16% more power than does a pressure-exchanger-topped engine under the specified topping constraints. Positive and negative aspects of wave engine topping in gas turbine engines are identified.

Welch, Gerard E.↗

NASA NTRS2002

Overview of the High Performance Antiproton (HiPAT) Experiment

The annihilation of matter with antimatter represents the highest energy density of any known reaction, producing 10(exp 8) MJ/g, approximately 10 orders of magnitude more energy per unit mass than chemical based combustion. To take the first step towards using this energy for propulsion applications the NASA MSFC Propulsion Research Center (PRC) has initiated a research activity examining the storage of low energy antiprotons. Storage was identified as a key enabling technology since it builds the experience base necessary to understand the handling of antiprotons for virtually all utilization and high-density storage concepts. To address this need, a device referred to as the High Performance Antiproton Trap (HiPAT) is under development at the NASA MSFC PRC. The HiPAT is an electromagnetic system (Penning-Malmberg design) consisting of a 4 Tesla superconductor, a high voltage confinement electrode system (operation up to 20 KV), and an ultra high vacuum test section (operating in the 10(exp -12) torr range). The system was designed to be portable with an ultimate goal of maintaining 10(exp 12) charged particles with a half-life of 18 days. Currently, this system is being experimentally evaluated using normal matter ions which are cheap to produce and relatively easy to handle. These normal ions provide a good indication of overall trap behavior, with the exception of assessing annihilation losses. The ions are produced external to HiPAT using two hydrogen ion sources, with adjustable beam energy and current. Ion are transported in a beam line and controlled through the use of electrostatic optics. These optics serve to both focus and gate the incoming ions, providing microsecond-timed pulses that are dynamically captured by cycling the HiPAT electric containment field like a 'trap door'. The layout of this system more closely simulates the operations expected at an actual antiproton production facility where 'packets' of antiprotons with pulse widths measured in 100's of nanoseconds could be provided. Initial dynamic capture experiments have been performed with both trap and ton source system functioning at approximately 10% of maximum levels, minimizing the potential for extraneous effects. Dynamic trapping techniques demonstrated the successful capture of millions of hydrogen ions with good agreement with the predicted loading based on the timing sequence, trap electric field, and ion beam current. These techniques will be expanded to examine multiple shot capture or 'stacking' to increase the total number of ions stored within HiPAT.

Martin, James J.↗

DOE OSTI2024

Microphysical properties of atmospheric soot and organic particles: measurements, modeling, and impacts

Atmospheric soot and organic particles from fossil fuel combustion and biomass burning modify Earth’s climate through their interactions with solar radiation and through modifications of cloud properties by acting as cloud condensation nuclei and ice nucleating particles. Recent advancements in understanding their individual properties and microscopic composition have led to heightened interest in their microphysical properties. This review article provides an overview of current advanced microscopic measurements and offers insights into future avenues for studying microphysical properties of these particles. To quantify soot morphology and ageing, fractal dimension ( D f ) is a commonly employed quantitative metric which allows to characterize morphologies of soot aggregates and their modifications in relation to ageing factors like internal mixing state, core-shell structures, phase, and composition heterogeneity. Models have been developed to incorporate D f and mixing diversity metrics of aged soot particles, enabling quantitative assessment of their optical absorption and radiative forcing effects. The microphysical properties of soot and organic particles are complex and they are influenced by particle sources, ageing process, and meteorological conditions. Furthermore, soluble organic particles exhibit diverse forms and can engage in liquid–liquid phase separation with sulfate and nitrate components. Primary carbonaceous particles such as tar balls and soot warrant further attention due to their strong light absorbing properties, presence of toxic organic constituents, and small size, which can impact human health. Future research needs include both atmospheric measurements and modeling approaches, focusing on changes in the mixing structures of soot and organic particle ensembles, their effects on climate dynamics and human health.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2010

Optical Characterization of a Multipoint Lean Direct Injector for Gas Turbine Combustors: Velocity and Fuel Drop Size Measurements

Performance of a multipoint, lean direct injection (MP-LDI) strategy for low emission aero-propulsion systems has been tested in a Jet-A fueled, lean flame tube combustion rig. Operating conditions for the series of tests included inlet air temperatures between 672 and 828 K, pressures between 1034 and 1379 kPa and total equivalence ratios between 0.41 and 0.45, resulting in equilibrium flame temperatures approaching 1800 K. Ranges of operation were selected to represent the spectrum of subsonic and supersonic flight conditions projected for the next-generation of commercial aircraft. This document reports laser-based measurements of in situ fuel velocities and fuel drop sizes for the NASA 9-point LDI hardware arranged in a 3 3 square grid configuration. Data obtained represent a region of the flame tube combustor with optical access that extends 38.1-mm downstream of the fuel injection site. All data were obtained within reacting flows, without particle seeding. Two diagnostic methods were employed to evaluate the resulting flow path. Three-component velocity fields have been captured using phase Doppler interferometry (PDI), and two-component velocity distributions using planar particle image velocimetry (PIV). Data from these techniques have also offered insight into fuel drop size and distribution, fuel injector spray angle and pattern, turbulence intensity, degree of vaporization and extent of reaction. This research serves to characterize operation of the baseline NASA 9- point LDI strategy for potential use in future gas-turbine combustor applications. An additional motive is the compilation of a comprehensive database to facilitate understanding of combustor fuel injector aerodynamics and fuel vaporization processes, which in turn may be used to validate computational fluid dynamics codes, such as the National Combustor Code (NCC), among others.

Heath, Christopher M.↗

NASA NTRS2017

Numerical and Analytical Assessment of a Coupled Rotating Detonation Engine and Turbine Experiment

An analysis is presented of an experimental rig comprising a rotating detonation engine (RDE) with bypass ejector flow coupled to a downstream turbine. The analysis used a validated computational fluid dynamics RDE simulation combined with straightforward algebraic mixing equations for the bypass flow. The objectives of the analysis were to supplement and interpret the necessarily sparse measurements from the rig, and to assess the performance of the RDE itself, which was not instrumented in this installation. The analysis is seen to agree reasonably well with available data. It shows that the RDE is operating in an unusual fashion, with subsonic flow throughout the exhaust plane. The detonation event itself is producing a total pressure rise relative to the pre-detonative pressure; however, the length of the device and the substantial flow restriction at the inlet yield an overall pressure loss. This is not surprising since the objective of the rig test was primarily aimed at investigating RDE/turbine interactions, and not on performance optimization. Furthermore, the RDE was designed for fundamental detonation studies and not performance. Nevertheless, the analysis indicates that with some small alterations to the design, an RDE with an overall pressure rise is possible.

detonation↗

NASA NTRS2017

Numerical and Analytical Assessment of a Coupled Rotating Detonation Engine and Turbine Experiment

An analysis is presented of an experimental rig comprising a rotating detonation engine (RDE) with bypass flow coupled to a downstream turbine. The analysis used a validated computational fluid dynamics RDE simulation combined with straightforward algebraic mixing equations for the bypass flow. The objectives of the analysis were to supplement and interpret the necessarily sparse measurements from the rig, and to assess the performance of the RDE itself (which was not instrumented in this installation). The analysis is seen to agree reasonably well with available data. It shows that the RDE is operating in an unusual fashion, with subsonic flow throughout the exhaust plane. The detonation event itself is producing a total pressure rise relative to the pre-detonative pressure; however, the length of the device and the substantial flow restriction at the inlet yield an overall pressure loss. This is not surprising since the objective of the rig test was primarily aimed at investigating RDEturbine interactions, and not on performance optimization. Furthermore, the RDE was designed for fundamental detonation studies and not performance. Nevertheless, the analysis indicates that with some small alterations to the design, an RDE with an overall pressure rise is possible.

detonation↗