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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Galileo PPR at Io: High Resolution Scans Taken in Conjunction with SSA and NIMS Data

The Galileo Photopolarimeter-Radiometer (PPR), when used in the radiometry mode which is most often used at Io, is a long-wavelength infrared single-aperture photometer. It is sensitive to temperatures from about 60 to several hundred K, and is thus useful for studying the volcanoes and background temperatures on Io. PPR can take raster scan images when it is the primary instrument being used (these data were discussed last year, see Rathbun et al., 2002). It can also take data in ride-along mode in conjunction with another remote sensing instrument (either SSI or NIMS) producing one-dimensional temperature scans. The best data of this type were taken during the close approach flybys during orbits I24, I25, I27, I31, I32, and I33 and include measurements of the volcanoes Pele, Prometheus, Pillan, Zamama, Tvashtar, Daedalus, Amarani, Gish Bar, Isum, Emakong, Tupan, and Tohil.

Rathbun, J. A.↗
NASA NTRS1994

(abstract) Galileo PPR Observations of Shoemaker-Levy 9

The Galileo spacecraft Photopolarimeter Radiometer (PPR), a hybrid visual/thermal IR instrument designed primarily to measure properties of the Jovian atmosphere, was employed for SL9 as a staring high-speed photometer at 945 and 678 nm, taking advantage of Galileo's direct view of the impact point.The PPR was able to acquire data at times when no other Galileo optical instruments could operate.

Galileo Jupiter Shoemaker-Levy 9 IR observations p↗
NASA NTRS2000

Modeling Io's Heat Flow: Constraints from Galileo PPR Data

We attempt to improve on previous Io heat flow estimates by using higher resolution data from Galileo Photopolarimeter Radiometer (PPR) and improved thermophysical models of the surface, including finite thermal inertia, the pedestal effect, and disk-resolved radiance.

Rathbun, J. A.↗
NASA NTRS2002

Recent Results from Galileo PPR at Io: Orbits I31 and I32

Recent Galileo PPR (Photo-Polarimeter Radiometer) results will be shown, including global day and nighttime maps, high latitude regional maps, and high-resolution scans across hotspots and from pole to pole. SO2 vapor pressure, global heatflow, and hotspot power outputs are estimated. Additional information is contained in the original extended abstract.

Rathbun, J. A.↗
NASA NTRS1995

Observing the Icy Jovian Satellites with the Galileo Photopolarimeter Radiometer Instrument

The Photopolarimeter/Radiometer (PPR) instrument aboard the Galileo spacecraft will go into orbit around Jupiter in December 1995. The 23 month tour offers PPR four Ganymede encounters, three Callisto encounters, and three Europa encounters with maximum PPR resolution varying from 0.5 km to 8 km and typical resolution of 200 km. In addition, there will be one Ganymede, one Callisto, and two Europa 'non-targeted' encounters giving maximum PPR resolution from 58 km to 200 km with a typical resolution of 300 km. There is a single Io encounter before Jupiter orbit insertion that will provide resolutions ranging from 400 km to 2.5 km, and numerous subsequent opportunities to observe Io with resolution as good as 600 km. The PPR will be used to study the polarization of reflected sunlight from each satellite over a wide range of phase angles. It will also map daytime and nighttime surface temperatures to look for spatial variations in thermophysical properties, study volcanic activity on Io, and look for possible endogenic thermal activity on Europa. These observation plans are presented.

Jovian↗
NASA NTRS1992

Galileo Photopolarimeter/Radiometer experiment

The Photopolarimeter/Radiometer (PPR) is a remote sensing instrument on the Galileo Orbiter designed to measure the degree of linear polarization and the intensity of reflected sunlight in ten spectral channels between 410 and 945 nm to determine the physical properties of Jovian clouds and aerosols, and to characterize the texture and microstructure of satellite surfaces. The PPR also measures thermal radiation in five spectral bands between 15 and 100 microns to sense the upper tropospheric temperature structure. Two additional channels which measure spectrally integrated solar and solar plus thermal radiation are used to determine the planetary radiation budget components. The PPR photopolarimetric measurements utilize previously flown technology for high-precision polarimetry using a calcite Wollaston prism and two silicon photodiodes to enable simultaneous detection of the two orthogonal polarization components. The PPR radiometry measurements are made with a lithium tantalate pyroelectric detector utilizing a unique arrangement of radiometric stops and a scene/space chopper blade to enable a warm instrument to sense accurately the much colder scene temperatures.

Russell, E. E.↗
DOE OSTI2022

Neutronics Modeling of the pulsed plasma rocket reactor using rattlesnake

In the pulsed plasma rocket (PPR) reactor, neutron induced fission processes are utilized to implement a series of pulsed micro-explosions of very high power and eject plasma as a propellant. More specifically, projectiles (bullets) composed of moderated uranium are sent through the chamber of an unmoderated uranium barrel. By inducing rapid fission within the bullets, a plasma can be generated with appropriate delivery of neutrons. This study aims to assess the neutronics performance of the PPR reactor during normal operations using the MOOSE-based Rattlesnake code through the evaluation of the impact of the movement of the fuel bullet and the rotation of control drums on the criticality of the system. The Monte Carlo (MC) code Serpent 2 was employed to generate material-based cross sections for use in Rattlesnake and the reference neutronics solution. Cubit was used to generate the mesh for the Rattlesnake model. Parametric studies were conducted to evaluate the best approaches for cross section and mesh generation to ensure accurate results from Rattlesnake. As part of the verification process, the eigenvalue results of the system at various fuel bullet positions were obtained using Rattlesnake and compared with the reference solutions. The acceptable differences show that the Rattlesnake model with appropriate cross section and mesh generation procedure is a sufficiently accurate approximation of the continuous energy (CE) MC model for micro-sized reactors like the PPR reactor. Next, the impact of the rotation of the control drums on the system criticality was evaluated using the verified model. It was shown that the high-fidelity simulation using the deterministic code Rattlesnake can produce sufficiently accurate results for the evaluation of the reactor's neutronics performance in different phases of the normal operation with acceptable computational cost.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Reducing Sample Size While Improving Equity in Vaccine Clinical Trials: A Machine Learning-Based Recruitment Methodology with Application to Improving Trials of Hepatitis C Virus Vaccines in People Who Inject Drugs

Despite the availability of direct-acting antivirals that cure individuals infected with the hepatitis C virus (HCV), developing a vaccine is critically needed in achieving HCV elimination. HCV vaccine trials have been performed in populations with high incidence of new HCV infection such as people who inject drugs (PWID). Developing strategies of optimal recruitment of PWID for HCV vaccine trials could reduce sample size, follow-up costs and disparities in enrollment. We investigate trial recruitment informed by machine learning and evaluate a strategy for HCV vaccine trials termed PREDICTEE—Predictive Recruitment and Enrichment method balancing Demographics and Incidence for Clinical Trial Equity and Efficiency. PREDICTEE utilizes a survival analysis model applied to trial candidates, considering their demographic and injection characteristics to predict the candidate’s probability of HCV infection during the trial. The decision to recruit considers both the candidate’s predicted incidence and demographic characteristics such as age, sex, and race. We evaluated PREDICTEE using in silico methods, in which we first generated a synthetic candidate pool and their respective HCV infection events using HepCEP, a validated agent-based simulation model of HCV transmission among PWID in metropolitan Chicago. We then compared PREDICTEE to conventional recruitment of high-risk PWID who share drugs or injection equipment in terms of sample size and recruitment equity, with the latter measured by participation-to-prevalence ratio (PPR) across age, sex, and race. Comparing conventional recruitment to PREDICTEE found a reduction in sample size from 802 (95%: 642–1010) to 278 (95%: 264–294) with PREDICTEE, while also reducing screening requirements by 30%. Simultaneously, PPR increased from 0.475 (95%: 0.356–0.568) to 0.754 (95%: 0.685–0.834). Even when targeting a dissimilar maximally balanced population in which achieving recruitment equity would be more difficult, PREDICTEE is able to reduce sample size from 802 (95%: 642–1010) to 304 (95%: 288–322) while improving PPR to 0.807 (95%: 0.792–0.821). PREDICTEE presents a promising strategy for HCV clinical trial recruitment, achieving sample size reduction while improving recruitment equity.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1994

Compute Server Performance Results

Parallel-vector supercomputers have been the workhorses of high performance computing. As expectations of future computing needs have risen faster than projected vector supercomputer performance, much work has been done investigating the feasibility of using Massively Parallel Processor systems as supercomputers. An even more recent development is the availability of high performance workstations which have the potential, when clustered together, to replace parallel-vector systems. We present a systematic comparison of floating point performance and price-performance for various compute server systems. A suite of highly vectorized programs was run on systems including traditional vector systems such as the Cray C90, and RISC workstations such as the IBM RS/6000 590 and the SGI R8000. The C90 system delivers 460 million floating point operations per second (FLOPS), the highest single processor rate of any vendor. However, if the price-performance ration (PPR) is considered to be most important, then the IBM and SGI processors are superior to the C90 processors. Even without code tuning, the IBM and SGI PPR's of 260 and 220 FLOPS per dollar exceed the C90 PPR of 160 FLOPS per dollar when running our highly vectorized suite,

Stockdale, I. E.↗
DOE OSTI2024

A Pyrrole Modified 3,4‐Propylenedioxythiophene Conjugated Polymer as Hole Transport Layer for Efficient and Stable Perovskite Solar Cells

Despite the outstanding electric properties and cost-effectiveness of poly(3,4-ethylenedioxythiophene) (PEDOT) and its derivatives, their performance as hole transport layer (HTL) materials in conventional perovskite solar cells (PSCs) has lagged behind that of widely used spirobifluorene-based molecules or poly(triaryl amine). This gap is mainly from their poor solubility and energy alignment mismatch. In this work, the design and synthesis of a pyrrole-modified HTL (PPr) based on 3,4-propylenedioxythiophene (ProDOT) are presented for efficient and stable PSCs. As a result of the superior defects passivation ability, excellent contact with perovskite, enhanced hole extraction, and high hydrophobicity, the unencapsulated PPr-based PSCs showed the peak PCE of 21.49% and outstanding moisture stability (over 4000 h). This work highlights the potential application of ProDOT-based materials as HTL for PSCs and underscores the importance of the rational design of PEDOT and its derivatives.

14 SOLAR ENERGY↗
DOE OSTI2023

Bayesian projection pursuit regression

In projection pursuit regression (PPR), a univariate response variable is approximated by the sum of $M$ “ridge functions,” which are flexible functions of one-dimensional projections of a multivariate input variable. Traditionally, optimization routines are used to choose the projection directions and ridge functions via a sequential algorithm, and $M$ is typically chosen via cross-validation. Here, we introduce a novel Bayesian version of PPR, which has the benefit of accurate uncertainty quantification. To infer appropriate projection directions and ridge functions, we apply novel adaptations of methods used for the single ridge function case ($M$=1), called the Bayesian Single Index Model; and use a Reversible Jump Markov chain Monte Carlo algorithm to infer the number of ridge functions $M$. We evaluate the predictive ability of our model in 20 simulated scenarios and for 23 real datasets, in a bake-off against an array of state-of-the-art regression methods. Finally, we generalize this methodology and demonstrate the ability to accurately model multivariate response variables. Its effective performance indicates that Bayesian Projection Pursuit Regression is a valuable addition to the existing regression toolbox.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Piecewise polyhedral formulations for a multilinear term

Herein, we present a mixed-integer linear programming (MILP) formulation of a piecewise, polyhedral relaxation (PPR) of a multilinear term using its convex-hull representation. Based on the PPR’s solution, we also present a MILP formulation whose solutions are feasible for nonconvex, multilinear equations. We then present computational results showing the effectiveness of proposed formulations on standard benchmark nonlinear programs (NLPs) with multilinear terms and compare with a traditional formulation that is built using recursive bilinear groupings of multilinear terms.

42 ENGINEERING↗
NASA NTRS1989

Planetary rover technology development requirements

Planetary surface (including lunar) mobility and sampling capability is required to support proposed future National Aeronautics and Space Administration (NASA) solar system exploration missions. The NASA Office of Aeronautics and Space Technology (OAST) is addressing some of these technology needs in its base research and development program, the Civil Space Technology Initiative (CSTI) and a new technology initiative entitled Pathfinder. The Pathfinder Planetary Rover (PPR) and Sample Acquisition, Analysis and Preservation (SAAP) programs will develop and validate the technologies needed to enable both robotic and piloted rovers on various planetary surfaces. The technology requirements for a planetary roving vehicle and the development plans of the PPR and SAAP programs are discussed.

Bedard, Roger J., Jr.↗
DOE OSTI2023

Projection pursuit adaptation on polynomial chaos expansions

Here, the present work addresses the issue of accurate stochastic approximations in high-dimensional parametric space using tools from uncertainty quantification (UQ). The basis adaptation method and its accelerated algorithm in polynomial chaos expansions (PCE) were recently proposed to construct low-dimensional approximations adapted to specific quantities of interest (QoI). The present paper addresses one difficulty with these adaptations, namely their reliance on quadrature point sampling, which limits the reusability of potentially expensive samples. Projection pursuit (PP) is a statistical tool to find the “interesting” projections in high-dimensional data and thus bypass the curse-of-dimensionality. In the present work, we combine the fundamental ideas of basis adaptation and projection pursuit regression (PPR) to propose a novel method to simultaneously learn the optimal low-dimensional spaces and PCE representation from given data. While this projection pursuit adaptation (PPA) can be entirely data-driven, the constructed approximation exhibits mean-square convergence to the solution of an underlying governing equation and thus captures the supports and probability distributions associated with the physics constraints. The proposed approach is demonstrated on a borehole problem and a structural dynamics problem, demonstrating the versatility of the method and its ability to discover low-dimensional manifolds with high accuracy with limited data. In addition, the method can learn surrogate models for different quantities of interest while reusing the same data set.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Auxetic two-dimensional transition metal selenides and halides

Abstract Auxetic two-dimensional (2D) materials provide a promising platform for biomedicine, sensors, and many other applications at the nanoscale. In this work, utilizing a hypothesis-based data-driven approache, we identify multiple materials with remarkable in-plane auxetic behavior in a family of buckled monolayer 2D materials. These materials are transition metal selenides and transition metal halides with the stoichiometry MX (M = V, Cr, Mn, Fe, Co, Cu, Zn, Ag, and X = Se, Cl, Br, I). First-principles calculations reveal that the desirable auxetic behavior of these 2D compounds originates from the interplay between the buckled 2D structure and the weak metal–metal interaction determined by their electronic structures. We observe that the Poisson’s ratio is sensitive to magnetic order and the amount of uniaxial stress applied. A transition from positive Poisson’s ratio (PPR) to negative Poisson’s ratio (NPR) for a subgroup of MX compounds under large uniaxial stress is predicted. The work provides a guideline for the future design of 2D auxetic materials at the nanoscale.

2d materials↗