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DOE OSTI2024

The shape of convection in 2D and 3D global simulations of stellar interiors

Context. Theoretical descriptions of convective overshooting in stellar interiors often rely on a basic one-dimensional parameterization of the flow called the filling factor for convection. Several different definitions of the filling factor have been developed for this purpose, based on: (1) the percentage of the volume, (2) the mass flux, and (3) the convective flux that moves through the boundary. Aims. We examine these definitions of the filling factor with the goal of establishing their ability to explain differences between 2D and 3D global simulations of stellar interiors that include fully compressible hydrodynamics and realistic microphysics for stars. Methods. We study convection and overshooting in pairs of identical two-dimensional (2D) and three-dimensional (3D) global simulations of stars produced with MUSIC , a fully compressible, time-implicit hydrodynamics code. We examine pairs of simulations for (1) a 3 M ⊙ red giant star near the first dredge-up point, (2) a 1 M ⊙ pre-main-sequence star with a large convection zone, (3) the current sun, and (4) a 20 M ⊙ main-sequence star with a large convective core. Results. Our calculations of the filling factor based on the volume percentage and the mass flux indicate asymmetrical convection near the surface for each star with an outer convection zone. However, near the convective boundary, convective flows achieve inward-outward symmetry for each star that we study; for 2D and 3D simulations, these filling factors are indistinguishable. A filling factor based on the convective flux is contaminated by boundary-layer-like flows, making a theoretical interpretation difficult. We present two possible new alternatives to these frequently used definitions of a filling factor, which instead compare flows at two different radial points. The first alternative is the penetration parameter of Anders et al. (2022, ApJ, 926, 169). The second alternative is a new statistic that we call the plume interaction parameter. We demonstrate that both of these parameters captures systematic differences between 2D and 3D simulations around the convective boundary.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2021

Assessment of RANS-based Transition Models based on Experimental Data of the Common Research Model with Natural Laminar Flow

Transition models based on auxiliary transport equations augmenting the Reynolds-averaged Navier-Stokes (RANS) framework often rely upon transition correlations that were derived from a limited number of low-speed experiments and these models often fail to account for all of the relevant transition mechanisms and/or the variation in those mechanisms with respect to changes in the significant flow parameters. Available data from a recent experiment on the Common Research Model with Natural Laminar Flow (CRM-NLF) in the National Transonic Facility at the NASA Langley Research Center are used to assess the current transition modeling capability in NASA's OVERFLOW 2.3b solver for a swept wing configuration with nonzero taper and transonic cruise conditions. Specifically, the OVERFLOW solutions are used to evaluate the accuracy and robustness of the transport-equation-based transition models. Results highlight that the Spalart-Allmaras-based amplification factor transport (AFT-2017b) equation model and Menter’s shear-stress transport equation (SST2003)-based Langtry-Menter transition models (either with or without the modeling of crossflow transition) significantly underpredict the reported extent of laminar flow region over the entire span of the wing, irrespective of which instability mechanism(s) is expected to dominate the onset of the transition process. We show that the transition correlations underlying these models fail to account for the stabilizing effect of compressibility on the Tollmien-Schlichting transition, which is likely to be a major contributor to the underprediction of the laminar flow region on the CRM-NLF. The SST-2003-based Langtry-Menter model also appears to inaccurately predict the chordwise pressure variation along the majority of the wing span at all the flow conditions studied herein, due to how the turbulence intensity levels were enforced in the computations and how that was interfering with the functioning of the underlying turbulence model within the boundary layer. The AFT and Langtry-Menter models appear to be sensitive to the level of the freestream turbulence intensity, but the degree of sensitivity varies across the models.

CFD modeling↗

DOE OSTI2026

Quantum-Inspired Bayesian Sampling for Uncertainty Quantification and Machine Learning (Final Technical Report)

With increasing simulation and measurement data, machine learning and artificial intelligence have been widely used in computational decision-making of complex engineering systems. The resulting tools, such as uncertainty quantification solvers, reinforcement learning, and physics-informed machine learning, have achieved great success in critical DOE tasks such as material discovery and design, energy system modeling and control, and numerical weather and climate prediction. A core topic in scientific machine learning and artificial intelligence is Bayesian inference: given an observed data set, people want to estimate the posterior distribution of a (possibly large) number of hidden parameters. Due to the flexibility and weak assumptions, Bayesian sampling has been the mainstream Bayesian inference solvers despite the rapid progress of approximate Bayesian inference. Classical Bayesian sampling methods such as Markov-chain Monte Carlo suffer from a low-acceptance rate due to the random walk nature, therefore state-of-the-art techniques use Hamiltonian Monte Carlo and its variants to efficiently draw posterior samples in a high dimension. The key idea of Hamiltonian Monte Carlo and its variants is to simulate the Hamiltonian dynamics of a classical particle with a fixed mass, and their performance significantly degrades when the posterior distribution is highly spiky or has multiple modes. Leveraging the idea of quantum physics, this project has investigated new theory, algorithms and applications of Bayesian inference (especially Bayesian sampling). The main results include: (1) novel quantum-inspired Bayesian sampling methods that can lead to better accuracy for challenging multi-modal or spiky distributions, (2) more scalable machine learning framework leveraging tensor-compressed Bayesian inference, and (3) Bayesian and sampling approaches for verifying the robustness of continuous and binary neural networks.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2015

Evaluation of Industry Standard Turbulence Models on an Axisymmetric Supersonic Compression Corner

Reynolds-averaged Navier-Stokes computations of a shock-wave/boundary-layer interaction (SWBLI) created by a Mach 2.85 flow over an axisymmetric 30-degree compression corner were carried out. The objectives were to evaluate four turbulence models commonly used in industry, for SWBLIs, and to evaluate the suitability of this test case for use in further turbulence model benchmarking. The Spalart-Allmaras model, Menter's Baseline and Shear Stress Transport models, and a low-Reynolds number k- model were evaluated. Results indicate that the models do not accurately predict the separation location; with the SST model predicting the separation onset too early and the other models predicting the onset too late. Overall the Spalart-Allmaras model did the best job in matching the experimental data. However there is significant room for improvement, most notably in the prediction of the turbulent shear stress. Density data showed that the simulations did not accurately predict the thermal boundary layer upstream of the SWBLI. The effect of turbulent Prandtl number and wall temperature were studied in an attempt to improve this prediction and understand their effects on the interaction. The data showed that both parameters can significantly affect the separation size and location, but did not improve the agreement with the experiment. This case proved challenging to compute and should provide a good test for future turbulence modeling work.

Turbulent Boundary Layer↗

DOE OSTI2018

Using ducted fuel injection to attenuate or prevent soot formation in mixing-controlled combustion strategies for engine applications

Ducted fuel injection is a strategy that can be used to enhance the fuel/charge-gas mixing within the combustion chamber of a direct-injection compression-ignition engine. The concept involves injecting the fuel through a small tube within the combustion chamber to make the most fuel-rich regions of the micture in the autoignition zone leaner relative to a conventional free-spray configuration (i.e., a fuel spray that is not surrounded by a duct). This study is a follow-on to initial proof-of-concept experiments that also were conducted in a constant-volume combustion vessel. While the initial natural luminosity imaging experiments demonstrated that ducted fuel injection lowers soot incandescence dramatically, this work adds a more quantitative diffuse back-illumination diagnostic to measure soot mass, as well as investigates the effects on performance of varying duct geometry (axial gap, length, diameter, and inlet and outlet shapes), ambient density, and charge-gas dilution level. The result is that ducted fuel injection is further proven to be effective at lowering soot by 35–100% across a wide range of operating conditions and geometries, and guidance is offered on geometric parameters that are most important for improving performance and facilitating packaging for engine applications.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2025

Probabilistic flux limiters

The stable numerical integration of shocks in compressible flow simulations relies on the reduction or elimination of Gibbs phenomena (unstable, spurious oscillations). A popular method to virtually eliminate Gibbs oscillations caused by numerical discretization in under-resolved simulations is to use a flux limiter. A wide range of flux limiters have been studied in the literature, with recent interest in their optimization via machine learning methods trained on high-resolution datasets. The common use of flux limiters in numerical codes as plug-and-play blackbox components makes them key targets for design improvement. Even for deterministic dynamical models, numerical uncertainty is introduced via coarse-graining required by insufficient computational power to solve all scales of motion. Conventional flux limiters are deterministic and lack the capacity to address uncertainties, both aleatoric (inherent randomness) and epistemic (modeling uncertainty due to limited knowledge), which arise in coarse-grained numerical simulations. Here, we introduce a conceptually distinct type of flux limiter that is designed to handle the effects of randomness in the model and uncertainty in model parameters. Unlike traditional single-function flux limiters, these new probabilistic flux limiters incorporate multiple flux limiting functions, each applied with a learned probability drawn from high-resolution data to mitigate the effects of uncertainty in numerical simulations. This approach departs from traditional single-function limiters by explicitly modeling and incorporating uncertainty into the shock capturing process. Using the example of Burgers' equation as a testbed, we show that a machine learned, probabilistic flux limiter may be used in a shock capturing code to more accurately capture shock profiles. In particular, we show that our probabilistic flux limiter outperforms standard limiters and can be successively improved upon (up to a point) by expanding the set of probabilistically chosen flux limiting functions.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

High-Throughput Combinatorial Development of High-Entropy Alloys For Light-Weight Structural Applications

The primary limitation of today’s lightweight structural alloys is that specific yield strengths (SYS) higher than 200MPa x cc/g (typical value for titanium alloys) are extremely difficult to achieve. This holds true especially at a cost lower than 5dollars/kg (typical value for magnesium alloys). Recently, high-entropy alloys (HEA) have shown promising SYS, yet the large composition space of HEA makes screening compositions complex and time-consuming. Over the course of this 2-year project we started from 150 billion compositions and reduced the number of potential low-density (<5g/cc), low-cost (<5dollars/kg) high-entropy alloy (LDHEA) candidates that are single-phase, disordered, solid-solution (SPSS) to a few thousand compositions. This was accomplished by means of machine learning to guide design for SPSS LDHEA based on a combination of recursive partitioning, an extensive, experimental HEA database compiled from 24 literature sources, and 91 calculated parameters serving as phenomenological selection rules. Machine learning shows an accuracy of 82% in identifying which compositions of a separate, smaller, experimental HEA database are SPSS HEA. Calculation of Phase Diagrams (CALPHAD) shows an accuracy of 71-77% for the alloys supported by the CALPHAD database, where 30% of the compiled HEA database is not supported by CALPHAD. In addition to machine learning, and CALPHAD, a third tool was developed to aid design of SPSS LDHEA. Phase diagrams were calculated by constructing the Gibbs-free energy convex hull based on easily accessible enthalpy and entropy terms. Surprisingly, accuracy was 78%. Pursuing these LDHEA candidates by high-throughput experimental methods resulted in SPSS LDHEA composed of transition metals (e.g. Cr, Mn, Fe, Ni, Cu) alloyed with Al, yet the high concentration of Al, necessary to bring the mass density below 5.0g/cc, makes these materials hard and brittle, body-centered-cubic (BCC) alloys. A related, yet multi-phase BCC alloy, based on Al-Cr-Fe-Ni, shows compressive strain >10% and specific compressive yield strength of 229 MPa x cc/g, yet does not show ductility in tensile tests due to cleavage. When replacing Cr in Al-Cr-Fe-based 4- and 5-element LDHEA with Mn, hardness drops 2x. Combined with compression test results, including those on the ternaries Al-Cr-Fe and Al-Mn-Fe suggest that Al-Mn-Fe-based LDHEA are still worth pursuing. These initial results only represent one compressive stress-strain curve per composition without any property optimization. As such, reproducibility needs to be followed by optimization to show their full potential. When including Li, Mg, and Zn, single-phase Li-Mg-Al-Ti-Zn LDHEA has been found with a specific ultimate compressive strength of 289MPa x cc/g. Al-Ti-Mn-Zn showed a specific ultimate compressive strength of 73MPa x cc/g. These initial results after hot isostatic pressing (HIP) of the ball-milled powders represent the lower end of what is possible, since no secondary processing (e.g. extrusion) has been performed to optimize strength and ductility. Compositions for multi-phase (e.g. dual-phase) LDHEA were identified largely by automated searches through CALPHAD databases, while screening for large face-centered-cubic (FCC) volume fractions, followed by experimental verification. This resulted in several new alloys. Li-Mg-Al-Mn-Fe and Mg-Mn-Fe-Co ball-milled powders upon HIP show specific ultimate compressive strengths of 198MPa x cc/g and 45MPa x cc/g, respectively. Several malleable quarternary Al-Zn-based alloys have been found upon arc/induction melting, yet with limited specific compressive yield strength (<75 MPa x cc/g). These initial results are all without any optimization for strength and/or ductility. High-throughput experimentation allowed us to triple the existing experimental HEA database as published in the past 10 years in less than 2 years which happened at a rate 10x higher than previous methods. Furthermore, we showed that high-throughput thin-film combinatorial methods can be used to get insight in isothermal phase diagram slices. Although it is straightforward to map hardness as a function of composition for sputtered, thin-film, compositional gradients by nano-indentation and compare the results to micro-indentation on bulk samples, the simultaneous impact of composition, roughness, film density, and microstructure on hardness requires monitoring all these properties as a function of location on the compositional gradient, including dissecting the impact of these 4 factors on the hardness map. These additional efforts impact throughput significantly. This work shows that a lot of progress has been made over the years in predicting phase formation that aids the discovery of new alloys, yet that a lot of work needs to be done to predict phases more accurately for LDHEA, whether done by CALPHAD or by other means. More importantly, more work needs to be done to predict mechanical properties of novel alloys, like yield strength, and ductility. Furthermore, this work shows that there is a need for the generation of an empirical alloy database covering strategic points in a multi-dimensional composition space to allow for faster and more accurate predictive interpolations to identify the oasis in the dessert more quickly. Finally, this work suggests that it is worth pursuing a ductile alloy with a SYS > 300 MPa x cc/g in a mass density range of 6-7 g/cc, since the chances for a single-phase or majority-phase FCC increase significantly. Today’s lightweight steels are in this density range.

36 MATERIALS SCIENCE↗

DOE OSTI2024

A Review of Modeling Approaches for Predicting Frost Growth and Defrosting on Tube-Fin Heat Exchangers: Preprint

Frost formation and growth on the evaporator surface is a common process that deteriorates the air-refrigerant heat transfer and restricts airflow. This degrades the performance of the vapor compression system by increasing temperature lift and air-side pressure drop. To accurately predict these effects during coil frosting, as well as the energy use and duration of the defrost process, there is a need to estimate the heat and mass transfer, momentum transport, and solid-liquid and liquid-vapor phase change. Therefore, in the past few decades, continuous effort has been made to model frosting and defrosting processes using approaches ranging from empirical correlations to computational fluid dynamic models. To provide a clearer overview for researchers, engineers, and manufacturers in this field, this paper provides a comprehensive literature review for frosting and defrosting models. The paper begins with theoretical background of frost formation and defrost processes, and then reviews the common modeling approaches in literature and their underlying assumptions when trying to account for various physical phenomenon. Based on the literature review, the most critical modeling effort for frost formation is the determination of frost densification rate and frost growth rate. Various methods to predict these two parameters are reviewed. Empirical correlations commonly used for frost density and thermal conductivity are presented and compared. For the defrost process, various multi-stage models have been proposed with different assumptions. Some assume the presence of air gap between the tube wall and the frost, while others consider the melted frost flow due to gravity. We also review physics-based and empirical approaches to integrate defrost models into heat pump models. We conclude by identifying research gaps and providing recommendations.

defrost↗

DOE OSTI2023

Efficient GPU Implementation of Automatic Differentiation for Computational Fluid Dynamics

Many scientific and engineering applications require repeated calculations of derivatives of output functions with respect to input parameters. Automatic Differentiation (AD) is a method that automates derivative calculations and can significantly speed up code development. In Computational Fluid Dynamics (CFD), derivatives of flux functions with respect to state variables (Jacobian) are needed for efficient solutions of the nonlinear governing equations. AD of flux functions on graphics processing units (GPUs) is challenging as flux computations involve many intermediate variables that create high register pressure and require significant memory traffic because of the need to store the derivatives. This paper presents a forward-mode AD method based on multivariate dual numbers that addresses these challenges and simultaneously reduces the floating-point operation count. The dimension of the multivariate dual numbers is optimized for performance. The flux computations are restructured to minimize the number of temporary variables and reduce register pressure. For effective utilization of memory bandwidth, shared memory is used to store the local flux Jacobian. This AD implementation is compared with several other Jacobian implementations on an NVIDIA V100 GPU (V100). For three-dimensional perfect-gas compressible-flow equations implemented in a practical CFD code, the AD implementation of a flux Jacobian based on multivariate dual numbers of dimension 5 outperforms all other GPU AD implementations on V100. Its performance is comparable with the optimized hand-differentiated version. Finally, the implementation achieves 75% of the peak floating-point throughput and 61 % of the peak global device memory bandwidth usage.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS2006

Comanche Helmet-Mounted Display Symbology Simulation

The Aeroflightdynamics Directorate (AMRDEC) conducted a simulation to examine the performance of the Comanche Contact Analog world-referenced symbology displayed on the Comanche HIDSS when compared with a compressed symbology design similar to that specified by the former MIL-STD 1295. Six experimental test pilots flew one modified ADS-33 maneuver (hover turn, bob-up), an unusual attitude recovery, and two terrain flight tactical tasks in the NASA Vertical Motion Simulator (VMS). Analysis of the pilot objective performance data and subjective data showed the following results. Objective test results showed that 1295 symbology yielded more rapid maneuvering in the hover turn bob-up than Contact Analog symbology. The average margin of difference in the time to complete the maneuver was approximately two seconds, which was statistically significant. There were no significant differences measured between symbology sets with respect to altitude or position performance measures for all other maneuvers. The NOE target ID task data showed improved accuracy in determining heading to target when using Contact Analog over MIL-STD-1295. Subjective test results, including handling qualities ratings (HQRs) and NASA-TLX workload ratings, showed small but consistent advantages of 1295 symbology over Contact Analog for most parameters. For the bob-up maneuver, 1295 symbology handling qualities were rated Desired for lateral position error and time to complete whereas Contact Analog was rated adequate. The average HQRs for all other maneuvers were rated the same for both symbology sets. Pilot comments and the results of an online questionnaire more strongly favored 1295 over Contact Analog. Repeated comments from all six pilots led to a focus on design issues with six Contact Analog symbols. Those symbols were the heading tape, horizon line, radar altitude six-second predictor, the position of the torque symbol, the absence of a hover position cue, and the widespread positioning of the symbology to the outer edges of the display field-of-view. Pilots rated the present design of three of the six symbols as having safety-of-flight implications. Those symbols were the heading tape, horizon line, and six-second predictor. To summarize, test results showed no objective data that would warrant restricting experimental test pilots from flying constrained tasks. Small but consistent advantages were recorded for the MILSTD-1295 symbology design when executing ADS-33 constrained tasks. No general performance differences were recorded for the operational maneuvers (NOE, contour flight modes) except for the azimuth-to-target task, which favored the Contact Analog heading tape design. There were consistent and strong pilot comments supporting the MIL-STD-1295 design over Contact Analog in both this current simulation and in Comanche Sim I. Three Contact Analog symbols warrant modification and further evaluation to mitigate safety-of-flight implications noted by participating test pilots. A plan for symbology redesign and testing was developed. However, the Comanche program was cancelled by Department of Army in February 2004.

Turpin, Terry S.↗

DOE OSTI2025

Dark Energy Survey Year 3 Results: Cosmological constraints from second- and third-order shear statistics

Here, we present a cosmological analysis of the third-order aperture mass statistic using Dark Energy Survey Year 3 (DES Y3) data. We perform a complete tomographic measurement of the three-point correlation function of the Y3 weak lensing shape catalog with the four fiducial source redshift bins. Building upon our companion methodology paper, we apply a pipeline that combines the two-point function ξ ± with the mass aperture skewness statistic ⟨ M ap 3 ⟩ , which is an efficient compression of the full shear three-point function. We use a suite of simulated shear maps to obtain a joint covariance matrix. By jointly analyzing ξ ± and ⟨ M ap 3 ⟩ measured from DES Y3 data with a Λ CDM model, we find S 8 = 0.780 ± 0.015 and Ω m = 0.26 6 - 0.040 + 0.039 , yielding 111% of figure-of-merit improvement in the Ω m - S 8 plane relative to ξ ± alone, consistent with expectations from simulated likelihood analyses. With a w CDM model, we find S 8 = 0.74 9 - 0.026 + 0.027 and w 0 = - 1.39 ± 0.31 , which gives an improvement of 22% on the joint S 8 - w 0 constraint. Our results are consistent with w 0 = - 1 . Our new constraints are compared to CMB data from the Planck satellite, and we find that with the inclusion of ⟨ M ap 3 ⟩ the existing tension between the datasets is at the level of 2.3 σ . We show that the third-order statistic enables us to self-calibrate the mean photometric redshift uncertainty parameter of the highest redshift bin with little degradation in the figure of merit. Our results demonstrate the constraining power of higher-order lensing statistics and establish ⟨ M ap 3 ⟩ as a practical observable for joint analyses in current and future surveys.

Gomes, R. C. H. [University of Pennsylvania] (ORCI↗

DOE OSTI2019

Inferring fuel areal density from secondary neutron yields in laser-driven magnetized liner inertial fusion

A technique to infer the areal density ρR of compressed deuterium (D) in cylindrical implosions from the ratio of secondary D–T (deuterium–tritium) neutrons to primary D–D neutrons is described and evaluated. For ρR to be proportional to the ratio of D–T to D–D yield, the increase in the D–T fusion cross section with collisional slowing of the tritium must be small, requiring where TkeV is the electron temperature in keV. The technique is applied to results from laser-driven magnetized liner inertial fusion (MagLIF) targets on OMEGA, where ρR is certainly less than 4 mg/cm 2 . OMEGA MagLIF targets do not achieve a sufficiently high, radially integrated, axial magnetic field BR to confine the tritium, as occurs in Z MagLIF targets, because they are ~10× smaller in radius. The inferred areal densities show that fuel convergence is reduced by preheating, by an applied axial magnetic field, and by increasing the initial fuel density, which are key features of the MagLIF scheme. The results are compared with 1-D and 2-D magnetohydrodynamic simulations for nominal laser and target parameters, which predict areal densities 2× to 3× higher than the measurements.

Davies, J. R.↗

DOE OSTI2019

Surface Modification of High-Carbon Steel Using Fiber Laser and Its Thermal, Microstructural and Tribological Analysis

In this study, surface modification of high-carbon steel was carried out using 2 kW fiber laser and thermal, microstructural and tribological characterizations were performed. The process parameters selected for laser surface treatment were laser power (600-1500 W) and scan speed (3000-4500 mm/min). Infrared pyrometer was used to record the surface temperature during the process. The metallographic analysis was carried out using an optical microscope to find the depth and width of the laser-treated zone. Scanning electron microscopy and energy-dispersive spectroscopy were performed to reveal the microstructure and compositional changes taking place in the laser-treated zone. It was observed that the dendritic growth took place from the top surface toward the center of the laser-treated zone. The amount of dendritic growth can be related to the maximum surface temperature generated during the process. XRD analysis indicated the formation of some intermetallic compounds and phase shifts taking place in the laser-treated zone. Residual stress analysis was performed to analyze the amount of stress accumulation in the laser-treated zone. When the temperature cycle was analyzed, it was found that the melting of the steel resulted in the formation of a surface under compressive stress while the non-melt hardened zone developed a surface under tensile stress. The maximum Vickers microhardness value achieved was about 958.8 HV{sub 0.5} for 1500 W power and 3000 mm/min scan speed. Scratch test was performed on the laser-treated track, and it was found that the hardened zone showed better tribological properties with respect to the parent material. Finally, it was observed that the surface roughness value increased with higher heat input probably due to high rate of oxide formation as well as due to the presence of martensite in the laser-treated zone.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Insights into Engine Knock: Comparisons of Knock Metrics across Ranges of Intake Temperature and Pressure in the CFR Engine

Of late there has been a resurgence in studies investigating parameters that quantify combustion knock in both standardized platforms and modern spark-ignition engines. However, it is still unclear how metrics such as knock (octane) rating, knock onset, and knock intensity are related and how fuels behave according to these metrics across a range of conditions. As part of an ongoing study, the air supply system of a standard Cooperative Fuel Research (CFR) F1/F2 engine was modified to allow mild levels of intake air boosting while staying true to its intended purpose of being the standard device for American Society for Testing and Materials (ASTM)-specified knock rating or octane number tests. For instance, the carburation system and intake air heating manifold are not altered, but the engine was equipped with cylinder pressure transducers to enable both logging of the standard knockmeter readout and state-of-the-art indicated data. For this study, the engine was operated using primary reference fuel 90 (PRF90) at 600 rpm, first following the procedures of the ASTM D2699 research octane number test protocol in order to define the geometric compression ratio set point for standard knock number. Thereafter, compression ratio sweeps were conducted at intake temperatures ranging from 30 to 150°C and intake air boost extending from 0 to 0.3 bar above ambient. The resulting operating map provided a broad envelope of compressed in-cylinder conditions relevant to modern spark-ignition engines. Detailed analysis of the indicated data highlighted a poor correlation between established knock intensity metrics and the knockmeter reading, which is used to characterize a fuel’s octane number. It was further found that the auto-ignition characteristics of PRF90 could be perturbed by means of intake air boosting and heating without being captured by the knockmeter reading.

Rockstroh, Toby↗

NASA NTRS1993

Ulysses plasma observations in the Jovian magnetosheath

The solar wind plasma experiment aboard the Ulysses spacecraft, including separate ion and electron instruments, measured the plasma properties of the Jovian magnetosheath during the February 1992 encounter with Jupiter. Seven separate magnetosheath intervals were observed, as well as four bow shock crossings and numerous encounters with the magnetopause and its boundary layer. We present an overview of ion and electron bulk parameters and a sampling of distribution shapes for the magnetosheath and adjacent plasma regions. Plasma flows are generally appropriate for slowing and deflection of the solar wind flow about a relatively stationary obstacle, with the notable exception of the first inbound sheath transit, when an expanding magnetosphere resulted in sunward flow just above the magnetopause. The existence of a planetary depletion layer is suggested by trends in plasma density for some magnetopause encounters. The magnetopause boundary layer is characterized by a combination of sheathlike and magnetospheric distributions of both ions and electrons. The ion population in the sheath is observed to include a significant population of suprathermal protons. Electron distributions have a distinctive shape previously observed in the terrestrial magnetosheath, with fluxes parallel to the magnetic field dominating at thermal energies and perpendicular fluxes dominating at higher energies. Trends in electron temperature near the bow shock indicate that shock motion plays an important role in heating the electrons. In general, the plasma characteristics of the Jovian magnetosheath are quite similar to those in its terrestrial counterpart, but the compressible nature of the Jovian magnetosphere accentuates the importance of boundary motions.

Phillips, J. L.↗

DOE OSTI2025

CFD modeling of near-wall combustion and unburned methane prediction in natural gas spark ignition engines

Natural gas-powered engines play a critical role in gas drilling, compression, and transmission sectors, but methane (CH 4 ) from engine combustion slip can be significant over their lifespan, contributing to atmospheric pollution and signaling reduced engine efficiency. Here, to address this challenge, computational fluid dynamics (CFD) simulations offer valuable insights into the in-cylinder combustion process, enabling the optimization of combustion strategies and engine designs to minimize unburned CH 4 slip. This study aims to evaluate and improve combustion models for simulating the combustion process and predicting unburned CH 4 concentrations in natural gas spark-ignition (SI) engines, including engines that are part of combined reformer-engine systems. Specifically, the performance of two flamelet-based combustion models—the Extended Coherent Flame Model (ECFM) and the G-equation model—was assessed using experimental engine data collected under varying excess-air ratio (λ) conditions and fuel compositions, including natural gas and syngas blends. In addition, to enhance the predictive capabilities of the G-equation model, a flame-wall interaction (FWI) sub-model was integrated into its framework. The effects of its model parameters, such as quenching and influence distance, on combustion behavior and unburned methane predictions were analyzed in detail. The ECFM tended to predict delayed combustion phasing under diluted mixture conditions, resulting in overprediction of unburned CH 4 concentrations. In contrast, the G-equation model provided reasonable predictions of combustion pressure, while representing higher the CH 4 reduction rate across the operating condition compared to experimental data. Incorporating the FWI sub-model—with the quenching distance calculated based on a pressure-dependent relation (P -0.48 ) and a fixed influence distance of 1.5 mm—further improved the G-equation model’s accuracy in predicting CH 4 reduction rates without compromising its ability to simulate the combustion process.

Combustion model↗

NASA NTRS2010

Z-Pinch Pulsed Plasma Propulsion Technology Development

Fusion-based propulsion can enable fast interplanetary transportation. Magneto-inertial fusion (MIF) is an approach which has been shown to potentially lead to a low cost, small reactor for fusion break even. The Z-Pinch/dense plasma focus method is an MIF concept in which a column of gas is compressed to thermonuclear conditions by an axial current (I approximates 100 MA). Recent advancements in experiments and the theoretical understanding of this concept suggest favorable scaling of fusion power output yield as I(sup 4). This document presents a conceptual design of a Z-Pinch fusion propulsion system and a vehicle for human exploration. The purpose of this study is to apply Z-Pinch fusion principles to the design of a propulsion system for an interplanetary spacecraft. This study took four steps in service of that objective; these steps are identified below. 1. Z-Pinch Modeling and Analysis: There is a wealth of literature characterizing Z-Pinch physics and existing Z-Pinch physics models. In order to be useful in engineering analysis, simplified Z-Pinch fusion thermodynamic models are required to give propulsion engineers the quantity of plasma, plasma temperature, rate of expansion, etc. The study team developed these models in this study. 2. Propulsion Modeling and Analysis: While the Z-Pinch models characterize the fusion process itself, propulsion models calculate the parameters that characterize the propulsion system (thrust, specific impulse, etc.) The study team developed a Z-Pinch propulsion model and used it to determine the best values for pulse rate, amount of propellant per pulse, and mixture ratio of the D-T and liner materials as well as the resulting thrust and specific impulse of the system. 3. Mission Analysis: Several potential missions were studied. Trajectory analysis using data from the propulsion model was used to determine the duration of the propulsion burns, the amount of propellant expended to complete each mission considered. 4. Vehicle Design: To understand the applicability of Z-Pinch propulsion to interplanetary travel, it is necessary to design a concept vehicle that uses it -- the propulsion system significantly impacts the design of the electrical, thermal control, avionics and structural subsystems of a vehicle. The study team developed a conceptual design of an interplanetary vehicle that transports crew and cargo to Mars and back and can be reused for other missions. Several aspects of this vehicle are based on a previous crewed fusion vehicle study -- the Human Outer Planet Exploration (HOPE) Magnetized Target Fusion (MTF) vehicle. Portions of the vehicle design were used outright and others were modified from the MTF design in order to maintain comparability.

Polsgrove, Tara↗

NASA NTRS1994

The proton cyclotron instability and the anisotropy/B inverse correlation

Spacecraft observations in the strongly compressed subsolar magnetosheath show an inverse correlation between the proton temperature anistrophy (T(sub perpendicular to p)/T(sub parallel to p) greater than 1 where perpendicular to and parallel to denote directions perpendicular and parallel to the background magnetic field) and the parallel proton beta (beta(sub parallel to p). This manuscript uses one-dimensional hybrid simulations of the proton cyclotron anisotropy instability in homogeneous electron-proton plasmas to study this correlation which may represent a limited closure relation for fluid theories of anisotropic space plasmas. The emphasis is on driven simulation which increase the temperature anisotropy by periodically reducing the magnetic-field-aligned velocities of the protons. The late-time states from ensembles of both initial value and driven simulations yield very similar expressions for the proton anisotropy/beta(sub parallel to P) inverse correlation, and provide a basis for explaining differences between sheath observations from different spacecraft. The driven simulations also yield expressions for the maximum instability growth rate and the fluctuating field energy as functions of beta (sub parallel to p) and a parameter characterizing the anisotropy driver.

Gary, S. Peter↗