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DOE OSTI2025

Suppressing the sample variance of DESI-like galaxy clustering with fast simulations

Ongoing and upcoming galaxy redshift surveys, such as the Dark Energy Spectroscopic Instrument (DESI) survey, will observe vast regions of sky and a wide range of redshifts. In order to model the observations and address various systematic uncertainties, N-body simulations are routinely adopted, however, the number of large simulations with sufficiently high mass resolution is usually limited by available computing time. Therefore, achieving a simulation volume with the effective statistical errors significantly smaller than those of the observations becomes prohibitively expensive. In this study, we apply the Convergence Acceleration by Regression and Pooling (CARPool) method to mitigate the sample variance of the DESI-like galaxy clustering in the AbacusSummit simulations, with the assistance of the quasi-N-body simulations FastPM. Based on the halo occupation distribution (HOD) models, we construct different FastPM galaxy catalogs, including the luminous red galaxies (LRGs), emission line galaxies (ELGs), and quasars, with their number densities and two-point clustering statistics well matched to those of AbacusSummit. We also employ the same initial conditions between AbacusSummit and FastPM to achieve high cross-correlation, as it is useful in effectively suppressing the variance. Our method of reducing noise in clustering is equivalent to performing a simulation with volume larger by a factor of 5 and 4 for LRGs and ELGs, respectively. We also mitigate the standard deviation of the LRG bispectrum with the triangular configurations k 2 = 2k 1 = 0.2 h Mpc -1 by a factor of 1.6. With smaller sample variance on galaxy clustering, we are able to constrain the baryon acoustic oscillations (BAO) scale parameters to higher precision. The CARPool method will be beneficial to better constrain the theoretical systematics of BAO, redshift space distortions (RSD) and primordial non-Gaussianity (NG).

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

High-pressure neutron diffraction at ultra-low temperature

Neutron diffraction is a powerful tool in the study of quantum materials and associated emergent phenomena as it allows for direct detection of magnetic structure even at ultra-low temperatures. As pressure can drive systems across quantum critical points and tune emergent behaviors at the quantum scale, coupling neutron diffraction with extreme conditions of high pressure at (ultra-)low temperatures has been a key research target over decades. This has proven challenging as magnetic neutron diffraction typically requires large sample volumes due to flux limitations, whereas high-pressure studies require small sample volumes due to pressure limitations. Combining these two contradictory requirements poses many difficulties, but also brings opportunities in research and development. Here, we address these shortcomings through the use of a diamond anvil cell equipped with polycrystalline anvils with relatively large sample volumes coupled with the high neutron flux made available by the high-pressure diffractometer of the Spallation Neutron Source. This particular diamond anvil cell configuration has previously proven useful for single-crystal samples and is here coupled with the ultra-low temperatures of a dilution refrigerator for the first time. Our study on a single crystal of Yb 2 ⁢O 3 successfully collected magnetic neutron diffraction data at 5.3 GPa below 200 mK inside a dilution refrigerator. We have performed a detailed analysis of the magnetic diffraction data to investigate the magnetic structure under pressure and observed a subtle shift in the transition temperature. This development will open the door for future studies on magnetic materials with these much-desired coupled extremes of high pressure and ultra-low temperatures.

Wu, Yan [Oak Ridge National Laboratory (ORNL), Oak↗

NASA NTRS1976

Cosmic-ray transport theory and out-of-the-ecliptic exploration

The reasons for studying cosmic-ray transport theory are summarized and the fundamentally three-dimensional nature of the process is pointed out. It is shown that observations in the solar ecliptic plane cannot unambiguously test transport theories since the solutions to the transport equations depend critically on boundary conditions and variation of parameters such as diffusion tensor out of the ecliptic. Sample calculations (Fokker-Planck coefficient) are shown which illustrate the problem. It is concluded that out-of-the-ecliptic observations are essential to further test transport theory.

Jokipii, J. R.↗

NASA NTRS1992

Particle emission from artificial cometary materials

During KOSI (comet simulation) experiments, mineral-ice mixtures are observed in simulated space conditions. Emission of ice-/dust particles from the sample surface is observed by means of different devices. The particle trajectories are recorded with a video system. In the following analysis we extracted the parameters: particle count rate, spatial distribution of starting points on the sample surface, and elevation angle and particle velocity at distances up to 5 cm from the sample surface. Different kinds of detectors are mounted on a frame in front of the sample to register the emitted particles and to collect their dust residues. By means of these instruments the particle count rates, the particle sizes and the composition of the particles can be correlated. The results are related to the gas flux density and the temperature on the sample surface during the insolation period. The particle emission is interpreted in terms of phenomena on the sample surface, e.g., formation of a dust mantle.

Koelzer, Gabriele↗

NASA NTRS1999

Low Stretch Diffusion Flames Over a Solid Fuel

A unique new way to study low gravity flames in normal gravity has been developed. To study flame structure and extinction characteristics in low stretch environments, a normal gravity low-stretch diffusion flame is generated using a cylindrical PMMA sample of varying large radii. Foutch and T'ien used the radiative loss as well as a densimetric Froude number to characterize the blowoff (small Da) and quenching extinction (large Da) boundaries in stagnation-point diffusion flames under various convective conditions. An important conclusion of this study was that the shape and location of the extinction boundary, as well as a number of important flame characteristics, were almost identical for the buoyant, forced, and mixed convective environments they modeled. This theory indicates it should be possible to understand a material's burning characteristics in the low stretch environment of spacecraft (induced by fans and crew movements) by understanding its burning characteristics in an equivalent Earth-based stretch environment (induced by normal gravity buoyancy). Similarly, the material's burning characteristics in Lunar or Martian stretch environments (induced by partial gravity buoyancy) can be assessed. Equivalent stretch rates can be determined as a function of gravity, imposed flow, and geometry. A generalized expression for stretch rate which captures mixed convection includes both buoyant and forced stretch is defined as a = a(sub f) ((1 + (a(sub b))exp 2/(a(sub b))exp 2))exp 1/2. For purely buoyant flow, the equivalent stretch rate is a(sub b) = [(rho(exp e)-rho(exp *)/rho(sub e)][g/R](exp 1/2). For purely forced flow, the equivalent stretch rate is characterized by either a(sub f)= 2U(sub infinity)/R for a cylinder, or a(sub f)=U(sub jet)/d(sub jet) for a jet impinging on a planar surface. In these experiments, the buoyant stretch is varied through R, the radius of curvature, but the buoyant stretch could also be varied through g, the gravity level. In this way the effect of partial gravity, such as those found on the Moon (1/6 g) or Mars (1/3 g) can be captured in the definition of flame stretch.

Olson, S. L.↗

DOE OSTI2024

A Data-Driven Methodology for Contextual Unit Commitment Using Regression Residuals

Day after day, system operators are faced with the challenge of taking unit commitment (UC) decisions under uncertain net load conditions. The standard operating procedure for taking UC decisions begins by leveraging auxiliary data on covariates (such as the day of the week or latest weather information) to generate a point prediction for net load, which is used in solving a deterministic UC problem. Such an approach, however, is known to deliver a notoriously poor out-of-sample (OOS) performance, as it completely disregards the stochastic nature of net load. While stochastic programming models explicitly represent uncertainty, they mostly do so using a generic set of scenarios that neglect covariate observations, squandering useful auxiliary data that could be harnessed to glean insights into uncertainty. In this article, we discuss a contextual stochastic optimization approach to UC, which effectively exploits covariate observations while explicitly assessing uncertainty so as to boost the OOS performance of UC decisions. The key thrust of our approach is to leverage regression models, along with their empirical residuals, to set up and solve sample average approximation problems. Not only do we prove that our approach satisfies the requisite conditions for asymptotic optimality and consistency laid out in (Kannan et al., 2022), but we also assess its performance on several case studies conducted using real-world data collected in California ISO and New York ISO grids. In conclusion, results show that the proposed approach can significantly improve OOS performance compared to alternative methods proposed in the literature under varying dataset sizes.

Yurdakul, Ogun↗

NASA NTRS1993

Computation of nonequilibrium shock layers for the comet sample return vehicles

This paper contains computational results for the flow around the body of the 'Rosetta' spacecraft. The flow is computed for the predicted trajectory point of maximum heating, using a Navier-Stokes solver coupled to the chemical kinetics. The calculations are performed for catalytic and non-catalytic boundary conditions at the wall, and with a systematic grid sensitivity study. The calculations verify some of the assumptions made in an early study, and predict the location of peak convective heating.

Cambier, Jean-Luc↗

NASA NTRS2019

Numerical Investigation and Optimization of a Flushwall Injector for Scramjet Applications at Hypervelocity Flow Conditions

An investigation utilizing Reynolds-averaged simulations (RAS) was performed in order to find optimal designs for an interdigitated flushwall injector suitable for scramjet applications at hypervelocity conditions. The flight Mach number, duct height, spanwise width, and injection angle were the design variables selected to maximize two objective functions: the thrust potential and combustion efficiency. A Latin hypercube sampling design-of-experiments method was used to select design points for RAS. A methodology was developed that automated building geometries and generating grids for each design. The ensuing RAS analysis generated the performance database from which the two objective functions of interest were computed using a one-dimensional performance utility. The data were fitted using four surrogate models: an artificial neural network (ANN) model, a cubic polynomial, a quadratic polynomial, and a Kriging model. Variance-based decomposition showed that both objective functions were primarily driven by changes in the duct height. Multiobjective design optimization was performed for all four surrogate models via a genetic algorithm method. Optimal solutions were obtained at the upper and lower bounds of the flight Mach number range. The Kriging model obtained an optimal solution set that predicted high values for both objective functions. Additionally, three challenge points were selected to assess the designs on the Pareto fronts. Further sampling among the designs of the Pareto fronts are required in order to lower the errors and perform more accurate surrogate-based optimization. sed optimization.

Shenoy, Rajiv R.↗

NASA NTRS1993

Solidification of eutectic system alloys in space (M-19)

It is well known that in the liquid state eutectic alloys are theoretically homogeneous under 1 g conditions. However, the homogeneous solidified structure of this alloy is not obtained because thermal convection and non-equilibrium solidification occur. The present investigators have clarified the solidification mechanisms of the eutectic system alloys under 1 g conditions by using the in situ observation method; in particular, the primary crystals of the eutectic system alloys never nucleated in the liquid, but instead did so on the mold wall, and the crystals separated from the mold wall by fluid motion caused by thermal convection. They also found that the equiaxed eutectic grains (eutectic cells) are formed on the primary crystals. In this case, the leading phase of the eutectic must agree with the phase of the primary crystals. In space, no thermal convection occurs so that primary crystals should not move from the mold wall and should not appear inside the solidified structure. Therefore no equiaxed eutectic grains will be formed under microgravity conditions. Past space experiments concerning eutectic alloys were classified into two types of experiments: one with respect to the solidification mechanisms of the eutectic alloys and the other to the unidirectional solidification of this alloy. The former type of experiment has the problem that the solidified structures between microgravity and 1 g conditions show little difference. This is why the flight samples were prepared by the ordinary cast techniques on Earth. Therefore it is impossible to ascertain whether or not the nucleation and growth of primary crystals in the melt occur and if primary crystals influence the formation of the equiaxed eutectic grains. In this experiment, hypo- and hyper-eutectic aluminum copper alloys which are near eutectic point are used. The chemical compositions of the samples are Al-32.4mass%Cu (Hypo-eutectic) and Al-33.5mass%Cu (hyper-eutectic). Long rods for the samples are cast by the Ohno Continuous Casting Process and they show the unidirectionally solidified structure. Each flight and ground sample was made of these same rods. The dimensions of all samples are 4.5 mm in diameter and 23.5 mm in length. Each sample is put in a graphite capsule and then vacuum sealed in a double silica ampoule. Then the ampoule is put in the tantalum cartridge and sealed by electron beam welding. For onbard experiments, a Continuous Heating Furnance (CHF) will be used for melting and solidifying samples under microgravity conditions. Six flight samples will be used. Four samples are hypo-eutectic and two are hyper-eutectic alloys. The surface of the two hypo-eutectic alloy samples are covered with aluminum oxide film to prevent Marangoni convection expected under microgravity conditions. Each sample will be heated to 700 C and held at that temperature for 5 min. After that the samples will be allowed to cool to 500 C in the furnace and they will be taken out of the furnace for He gas cooling. The heating and cooling diagrams for the flight experiments are shown. After collecting the flight samples, the solidified structures of the samples will be examined and the mechanisms of eutectic solidification under microgravity conditions will be determined. It is likely that successful flight experiment results will lead to production of high quality eutectic alloys and eutectic composite materials in space.

Ohno, Atsumi↗

NASA NTRSDate not supplied

Unified Material-Environment Interaction Model for Binary UHTC Composites

A new model for the surface chemistry of zirconium and hafnium diborides containing silicon-carbide when exposed to high temperature conditions in air is formulated. Oxidation dynamics are simplified by considering the diffusion-limited equilibrium regime within the material at elevated temperatures. This model is first assessed against experimental mass-gain data taken from UHTC samples heated to high temperature in an oxygen environment. Then, further evaluations of the new model are conducted using hypersonic CFD simulations to analyze conditions experienced by HfB2-SiC in arc jet experiments conducted at NASA Ames Research Center. Measurements of stagnation point heat transfer and pressure are then used to calibrate the simulations. Results of coupled CFD-material response simulations are then compared to the surface temperatures measured during the Ames arc jet test. Results support the use of the proposed model while highlighting the need for improved gas-phase data on the additional constituents considered.

ultra high temperature ceramic↗

DOE OSTI2020

NSFnets (Navier-Stokes flow nets): Physics-informed neural networks for the incompressible Navier-Stokes equations

In the last 50 years there has been a tremendous progress in solving numerically the Navier-Stokes equations using finite differences, finite elements, spectral, and even meshless methods. Yet, in many real cases, we still cannot incorporate seamlessly (multi-fidelity) data into existing algorithms, and for industrial-complexity applications the mesh generation is time consuming and still an art. Moreover, solving ill-posed problems (e.g., lacking boundary conditions) or inverse problems is often prohibitively expensive and requires different formulations and new computer codes. Here, we employ physics-informed neural networks (PINNs), encoding the governing equations directly into the deep neural network via automatic differentiation, to overcome some of the aforementioned limitations for simulating incompressible laminar and turbulent flows. We develop the Navier-Stokes flow nets (NSFnets) by considering two different mathematical formulations of the Navier-Stokes equations: the velocity-pressure (VP) formulation and the vorticity-velocity (VV) formulation. Since this is a new approach, we first select some standard benchmark problems to assess the accuracy, convergence rate, computational cost and flexibility of NSFnets; analytical solutions and direct numerical simulation (DNS) databases provide proper initial and boundary conditions for the NSFnet simulations. The spatial and temporal coordinates are the inputs of the NSFnets, while the instantaneous velocity and pressure fields are the outputs for the VP-NSFnet, and the instantaneous velocity and vorticity fields are the outputs for the VV-NSFnet. This is unsupervised learning and, hence, no labeled data are required beyond boundary and initial conditions and the fluid properties. The residuals of the VP or VV governing equations, together with the initial and boundary conditions, are embedded into the loss function of the NSFnets. No data is provided for the pressure to the VP-NSFnet, which is a hidden state and is obtained via the incompressibility constraint without extra computational cost. Unlike the traditional numerical methods, NSFnets inherit the properties of neural networks (NNs), hence the total error is composed of the approximation, the optimization, and the generalization errors. Here, we empirically attempt to quantify these errors by varying the sampling (“residual”) points, the iterative solvers, and the size of the NN architecture. For the laminar flow solutions, we show that both the VP and the VV formulations are comparable in accuracy but their best performance corresponds to different NN architectures. The initial convergence rate is fast but the error eventually saturates to a plateau due to the dominance of the optimization error. For the turbulent channel flow, we show that NSFnets can sustain turbulence at , but due to expensive training we only consider part of the channel domain and enforce velocity boundary conditions on the subdomain boundaries provided by the DNS data base. We also perform a systematic study on the weights used in the loss function for balancing the data and physics components, and investigate a new way of computing the weights dynamically to accelerate training and enhance accuracy. In the last part, we demonstrate how NSFnets should be used in practice, namely for ill-posed problems with incomplete or noisy boundary conditions as well as for inverse problems. We obtain reasonably accurate solutions for such cases as well without the need to change the NSFnets and at the same computational cost as in the forward well-posed problems. As a result, we also present a simple example of transfer learning that will aid in accelerating the training of NSFnets for different parameter settings.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Efficient Quantum Gibbs Samplers with Kubo–Martin–Schwinger Detailed Balance Condition

Lindblad dynamics and other open-system dynamics provide a promising path towards efficient Gibbs sampling on quantum computers. In these proposals, the Lindbladian is obtained via an algorithmic construction akin to designing an artificial thermostat in classical Monte Carlo or molecular dynamics methods, rather than being treated as an approximation to weakly coupled system-bath unitary dynamics. Recently, Chen, Kastoryano, and Gilyén (arXiv:2311.09207) introduced the first efficiently implementable Lindbladian satisfying the Kubo–Martin–Schwinger (KMS) detailed balance condition, which ensures that the Gibbs state is a fixed point of the dynamics and is applicable to non-commuting Hamiltonians. This Gibbs sampler uses a continuously parameterized set of jump operators, and the energy resolution required for implementing each jump operator depends only logarithmically on the precision and the mixing time. In this work, we build upon the structural characterization of KMS detailed balanced Lindbladians by Fagnola and Umanità, and develop a family of efficient quantum Gibbs samplers using a finite set of jump operators (the number can be as few as one), akin to the classical Markov chain-based sampling algorithm. Compared to the existing works, our quantum Gibbs samplers have a comparable quantum simulation cost but with greater design flexibility and a much simpler implementation and error analysis. Moreover, it encompasses the construction of Chen, Kastoryano, and Gilyén as a special instance.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Harvest Initiated Volatile Organic Compound Emissions from In-Field Tall Wheatgrass

While crop and grassland usage continues to increase, the full diversity of plant-specific volatile organic compounds (VOCs) emitted from these ecosystems, including their implications for atmospheric chemistry and carbon cycling, remains poorly understood. It is particularly important to investigate VOCs in the context of potential biofuels: aside from the implications of largescale land use, harvest may shift both the flux and speciation of emitted VOCs. To this point, we evaluate the diversity of VOCs emitted both pre and postharvest from “Alkar” tall wheatgrass (Thinopyrum ponticum), a candidate biofuel that exhibits greater tolerance to frost and saline land compared to other grass varieties. Mature plants grown under field conditions (n = 6) were sampled for VOCs both pre- and postharvest (October 2022). Via hierarchical clustering of emitted VOCs from each plant, we observe distinct “volatilomes” (diversity of VOCs) specific to the pre- and postharvest conditions despite plant-to-plant variability. In total, 50 VOCs were found to be unique to the postharvest tall wheatgrass volatilome, and these unique VOCs constituted a significant portion (26%) of total postharvest signal. While green leaf volatiles (GLVs) dominate the speciation of postharvest emissions (e.g., 54% of unique postharvest VOC signal was due to 1-penten-3-ol), we demonstrate novel postharvest VOCs from tall wheatgrass that are under characterized in the context of carbon cycling and atmospheric chemistry (e.g., 3-octanone). Continuing evaluations will quantitatively investigate tall wheatgrass VOC fluxes, better informing the feasibility and environmental impact of tall wheatgrass as a biofuel.

09 BIOMASS FUELS↗

DOE OSTI2021

Roadmap for Advanced Power System Measurements

Conditions in the electric power grid are changing rapidly. Changes are driven, in particular, by the increased penetration of renewable resources in the generation mix. Part of the solution to dealing with the changing conditions is the better use of measurement systems, taking advantage of the better understanding of measurements that was heralded by digital technology. Another part of the solution is the communication of samples of the directly observable voltages and currents by means of continuous point-on-wave values. The increased bandwidth capability of such a system allows more complicated measurement models to be built at the point of use. Additional measurements and analyses can then be performed. This Roadmap hinges on these two aspects of measuring: improved measurements supported by high-bandwidth (raw data) communications. Following an introduction to the overall subject, the report explores the impact of what can be thought of as the digital revolution in measurement. In essence, that revolution has served to clarify ideas about measurement and is continuing to lead to improved processes. An extensive survey of the relevant literature was performed . Webinars were held to learn from the wider community of practitioners. Based on this information, a number of gaps were identified whose continued existence would hamper the solution of the challenges now facing measurement and communication in the power grid. The underlying value propositions are interoperability (presently not very satisfactory in many measurements); greater (and less challenging) adoption of distributed energy resources; and improved international competitiveness. Underlying all that, of course, is progress toward a more reliable and resilient power system. The identified gaps were addressed in four major thrusts: technology deployment and demonstration, education, instrumentation testing and standards, and analytical methods. For each of the thrusts, multiple goals are defined to guide the implementation. The thrusts were designed to close gaps and unlock high-value use cases. After discussing the literature review, gap analysis, high-value use cases, and research thrusts in chapters 2-5, the report culminates in chapter 6 with a roadmap that links each aspect together to form a unified plan. Developing a research portfolio aligned with this plan will ensure that advanced measurement systems are in place to support reliable operation of the power system as it modernizes.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Simple but tricky: Investigations of terephthalic acid purity obtained from mixed PET waste

In this study, we report for the first time, the basic depolymerization of mixed waste-polyethylene terephthalate (PET) by hydrolysis and subsequent terephthalic acid monomer recovery at high purity using benign reaction conditions. Several conditions were tested for depolymerization such as PET chips size, concentration of aqueous sodium hydroxide (20 or 30%), organic co-solvent (ethylene glycol or ethanol), temperature at which the reaction was run and duration of the heating. More importantly, several batches of PET were utilized as starting materials including a commercial PET, chopped PET obtained from clean bottles whose caps and labels were removed and the purity of the product from each condition was evaluated via nuclear magnetic resonance (1HNMR and 13CNMR), differential scanning calorimetry (DSC) and powder Xray diffraction (XRD). Unsurprisingly, the conversion of PET is dependent on the particle size varying from 100% conversion for fine powder to 73% conversion for (300 µm, mesh 6 – 20 or mesh 14-20). Ethanol appears to be more efficient as a co-solvent than ethylene glycol, with higher PET depolymerization conversions (94% versus 75-80%), shorter reaction times (2h versus 6h) and lower temperatures (80 °C versus 110 °C). The terephthalic acid (TPA) recovered appeared to have only subtle differences among the batches, most notably a pink color when the reaction was run in ethanol/base. The DSC of the compounds produced in ethylene glycol water appear to display a melting point (280-288 °C) while the samples prepared in ethanol as well as a commercial sample did not. Overall, the purity of the various TPA batches is comparable, and similar to commercial TPA, demonstrating the utility of the method to depolymerize realistic waste streams. The method is simple, demonstrated on multigram scale (15-30g) and allows for the complete removal of waste other than PET unaffected by alkaline conditions.

Cosimbescu, Lelia↗

DOE OSTI2023

The DESI One-Percent survey: exploring the Halo Occupation Distribution of Emission Line Galaxies with AbacusSummit simulations

The One-Percent survey of the Dark Energy Spectroscopic Instrument collected ~ 270k emission line galaxies (ELGs) at 0.8 < z < 1.6. The high completeness of the sample allowed the clustering to be measured down to scales never probed before, 0.04 Mpc/h in rp for the projected 2-point correlation function (2PCF) and 0.17 Mpc/h in galaxy pair separation s for the 2PCF monopole and quadrupole. The most striking feature of the measurements is a strong signal at the smallest scales, below 0.2 Mpc/h in rp and 1 Mpc/h in s. We analyse these data in the halo occupation distribution framework. We consider different distributions for central galaxies, a standard power law for satellites with no condition on the presence of a central galaxy and explore several extensions of these models. For all considered models, the mean halo mass of the sample is found to be log10 $\langle$Mh$\rangle$ ~ 11.9. We obtain a satellite mean occupation function which agrees with physically motivated ELG models only if we introduce central-satellite conformity, meaning that the satellite occupation is conditioned by the presence of central galaxies of the same type. To achieve in addition a good modelling of the clustering between 0.1 and 1 Mpc/h in rp, we allow for ELG positioning outside of the halo virial radius and find 0.5% of ELGs residing in the outskirts of halos. Furthermore, the satellite velocity dispersion inside halos is found to be ~ 30% larger than that of the halo dark matter particles. These are the main findings of our work. Here we investigate assembly bias as a function of halo concentration, local density or local density anisotropies and observe no significant change in our results. We split the data sample in two redshift bins and report no significant evolution with redshift. Lastly, changing the cosmology in the modelling impacts only slightly our results.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRSDate not supplied

High-Enthalpy Testing to Validate Simulation of an Aerosol Capture Probe

AERACEPT (Aerosol Rapid Analysis Combined Entry Probe/sonde Technology) is a developing technology enabling in-situ aerosol particle sampling and analysis in a small spacecraft mission envelope. It integrates a passive aerosol sample collection system into a probe’s thermal protection system (TPS) to remove the need for heat shield separation and active descent control (parachutes, gliders, etc.). AERACEPT is being validated against the requirements of the Nephele mission concept, which targets the middle and lower Venus cloud layers. The proposed technology employs 3D Carbon-Carbon (3D-CC) at the probe’s nose to withstand the extreme environments encountered in a Venus entry without producing pyrolysis gases that would contaminate the mission sample collection. Any shape change of this 3D-CC sample inlet will affect airflow through the sampling system, thereby impacting aerosol sample collection bias and efficiency. Accurate prediction of the nose’s material response during entry is there-fore of fundamental importance to the development and practical use of this technology. As a result, the AERACEPT project is planning a test campaign in the newly built PlasmatronX facility with a novel “Open Iso-Q” test article to validate state-of-the-art material response tools for a simulated Venus entry. The PlasmatronX is a 350 kW inductively-coupled plasma facility developed and run by the Center for Hypersonics and Entry Systems Studies at the University of Illinois at Urbana-Champaign. The facility can support ground testing for a variety of planetary destinations by simulating entry conditions in Nitrogen, Air, and Carbon Dioxide. To best simulate the Venus atmosphere and match flight-like recession, the planned AERACEPT test campaign will use Carbon Dioxide as its test gas. AERACEPT has designed two test articles for this campaign: 1) a standard test article whose curved surface approximates a constant applied heat flux (“Closed Iso-Q” model) and 2) a novel inlet test article with a through-hole at the stagnation point (“Open Iso-Q” model). Both article types consist of a 3D-CC sample bonded to a graphite fixture. All articles will be laser scanned before and after testing to estimate shape change and recession, and the “Closed Iso-Q” articles will be instrumented with thermocouples to provide temperature histories. The test article temperatures and inlet shape change will be compared against simulations run with the Porous material Analysis Toolbox based on OpenFOAM (PATO) to validate the AERACEPT 3D-CC material response model. Due to the high thermal conductivity of 3D-CC, multidimensional effects have a large influence on the test article temperature and the standard 1-D material response tools are not sufficient for test planning. The test campaign features (e.g. article design, run duration, heat fluxes) are therefore informed by a series of 3-D simulations using state-of-the-art material response tools such as PATO. The test campaign is scheduled for spring of 2024. Expected results include 1) Key drivers of selected test conditions (e.g. matching mission flight atmosphere & recession), 2) Simulation results that informed test article design, 3) Acquired test data such as recession measurements, temperature histories, and photos, and 4) Comparisons between test results and simulation predictions.

AERACEPT↗

NASA NTRSDate not supplied

High-Enthalpy Testing to Validate Simulation of an Aerosol Capture Probe

AERACEPT↗