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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 1,441 records · Page 80

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NASA NTRS2009

Roadmaps and Strategies for Crop Research for Bioregenerative Life Support Systems A Compilation of Findings from NASA’s Advanced Life Support Meetings

Extensive testing with plants for bioregenerative life support systems has been conducted by NASA for nearly 40 years, both through university grants and work at NASA field centers. During this time, numerous meetings were held to develop strategies and roadmaps for implementing bioregenerative life support systems. Findings from several of these meetings are summarized in this report. In nearly all cases, the recommendations included an active ground-based research program and integration tests with other life support subsystems, followed by eventual spaceflight testing. The most recent roadmap of NASA’s Exploration Life Support Crop Element suggests a sequence of first developing a modular vegetable production unit (VPU) to provide perishable foods to supplement the crew’s diet. A similar system could then be used on the lunar surface, with additional modules added as the lunar outpost expands. Eventually, these modules could be transferred to a dedicated pressurized logistics module (PLM) for crop production. Experience from the lunar tests could then be used to conduct a similar buildup for Mars missions, where in situ food production and bioregeneration would be important for achieving outpost autonomy. To date, most trade studies of bioregenerative life support systems indicate that reducing the costs associated with crop lighting systems are key, and use of light-emitting diodes (LEDs) or direct solar lighting offers promising options. Likewise, sustaining high yields and high harvest index (% edible biomass) will be important for minimizing costs, and this can be achieved by optimizing growth environments and through selecting, breeding, and genetically engineering crops suitable for space environments. Collectively, these strategies and roadmaps suggest that a combined approach of fundamental research, hardware (plant chamber) development, and operational testing is required to achieve reliable bioregenerative life support systems.

Bioregenerative↗

NASA NTRS2024

Examination of Perforate Facesheet Impedance Prediction Models

This study examines several perforate facesheet impedance prediction models. Each model is validated with impedances educed from acoustic pressure measurements acquired in the NASA Langley Research Center Normal Incidence Tube (NIT) and Grazing Flow Impedance Tube (GFIT). This measurement dataset includes results for 73 NIT samples acquired at sound pressure levels of 100, 120, and 140 dB, and for 9 GFIT samples acquired at SPLs of 120 and 140 dB and at mean flow speeds of Mach 0.0, 0.3, and 0.5. Multiple metrics are evaluated based on different potential applications of the selected perforate facesheet model. An optimizer is then used to modify one of these models to more accurately match the full measurement dataset.

acoustic↗

DOE OSTI2016

Learning planar Ising models

Inference and learning of graphical models are both well-studied problems in statistics and machine learning that have found many applications in science and engineering. However, exact inference is intractable in general graphical models, which suggests the problem of seeking the best approximation to a collection of random variables within some tractable family of graphical models. In this paper, we focus on the class of planar Ising models, for which exact inference is tractable using techniques of statistical physics. Based on these techniques and recent methods for planarity testing and planar embedding, we propose a greedy algorithm for learning the best planar Ising model to approximate an arbitrary collection of binary random variables (possibly from sample data). Given the set of all pairwise correlations among variables, we select a planar graph and optimal planar Ising model defined on this graph to best approximate that set of correlations. Finally, we demonstrate our method in simulations and for two applications: modeling senate voting records and identifying geo-chemical depth trends from Mars rover data.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Full-Spectrum-Analysis Isotope ID

FSAIsotopeID analyzes gamma ray spectra to identify radioactive isotopes (radionuclides). The algorithm fits the entire spectrum with combinations of pre-computed templates for a comprehensive set of radionuclides with varying thicknesses and compositions of shielding materials. The isotope identification algorithm is suitable for the analysis of spectra collected by gamma-ray sensors ranging from medium-resolution detectors, such a NaI, to high-resolution detectors, such as HPGe. In addition to analyzing static measurements, the isotope identification algorithm is applied for the radiation search applications. The search subroutine maintains a running background spectrum that is passed to the isotope identification algorithm, and it also selects temporal integration periods that optimize the responsiveness and sensitivity. Gain stabilization is supported for both types of applications.

Mitchell, Dean J.↗

DOE OSTI2017

Development of High Temperature Out-of-Pile Experiments for Testing Nuclear Thermal Propulsion Fuel Surrogates

Nuclear thermal propulsion (NTP) technology is designed to provide “in-space” vehicle propulsion by deriving thrust from a hydrogen working fluid that is heated from a nuclear reaction. Initial NTP fuel structures (primarily carbon/carbide based materials) developed by the Rover/NERVA program were designed to withstand temperatures exceeding 2400 K and remain intact after tens of firing cycles. Current programs responsible for development of this technology expect the fuels to withstand temperatures in excess of 2550K under a similar duty cycle. Experiments that subject fuels to these conditions are being developed to provide data and performance information for optimization and potential down-selection of the candidate materials. Initial tests will be designed for laboratory benchtop operation and will not expose surrogate specimens to the hydrogen working fluid or irradiation fields. The primary focus of these out-of-pile experiments will be to study thermal performance and thermal failure limits of the candidate specimen materials.

Howard, Richard↗

DOE OSTI2016

Full-duplex ultrasonic through-wall communication and power delivery system with frequency tracking

A method and apparatus provide simultaneous bi-directional communications through a barrier using a pair of piezoelectric transducers. Outside-to-inside transmission of differentially encoded binary data is only sampled at the inside when a known repeated bit in a Barker sequence is transmitted in the other direction. Differentially encoded data is translated based on the absolute value of differences between each signal envelope sample and the previous signal envelope sample. Inside-to-outside data is transmitted by varying an electrical load on the inside transducer to vary the proportion of a continuous wave signal it reflects. The reflected portion of the continuous wave changes the electrical impedance of the outside transducer and this change is measured and interpreted as binary data. Two frequency selection algorithms select minimally sufficient and then optimal frequencies for power and data transmission by a frequency stepping process.

Lawry, Tristan J.↗

DOE OSTI2023

Systems and methods for hierarchical multi-objective optimization

A method for optimizing objective functions can include selecting an objective function based at least on a hierarchy, applying parameters to the objective function to generate an output, responsive to the output not satisfying a tolerance condition, assigning a penalty to the set of parameters and evaluating a convergence condition using the set of parameters and the penalty, responsive to the output satisfying the tolerance condition, evaluating an additional objective function using the parameters in an order corresponding to the hierarchy or evaluating the convergence condition responsive to the selected objective function being a final objective function, modifying the set of parameters using a genetic algorithm responsive to the set of parameters not satisfying the convergence condition, and outputting the set of parameters responsive to the set of parameters satisfying the convergence condition.

Chan, Henry↗

DOE OSTI2024

Ensemble variational Fokker-Planck methods for data assimilation

Particle flow filters solve Bayesian inference problems by smoothly transforming a set of particles into samples from the posterior distribution. Particles move in state space under the flow of an McKean-Vlasov-Itˆo process. This work introduces the Variational Fokker-Planck (VFP) framework for data assimilation, a general approach that includes previously known particle flow filters as special cases. The McKean-Vlasov-Itˆo process that transforms particles is defined via an optimal drift that depends on the selected diffusion term. It is established that the underlying probability density - sampled by the ensemble of particles - converges to the Bayesian posterior probability density. For a finite number of particles the optimal drift contains a regularization term that nudges particles toward becoming independent random variables. Based on this analysis, we derive computationally-feasible approximate regularization approaches that penalize the mutual information between pairs of particles, and avoid particle collapse. Moreover, the diffusion plays a role akin to a particle rejuvenation approach that aims to alleviate particle collapse. The VFP framework is very flexible. Different assumptions on prior and intermediate probability distributions can be used to implement the optimal drift, and localization and covariance shrinkage can be applied to alleviate the curse of dimensionality. A robust implicit-explicit method is discussed for the efficient integration of stiff McKean- Vlasov-Itˆo processes. Here, the effectiveness of the VFP framework is demonstrated on three progressively more challenging test problems, namely the Lorenz ’63, Lorenz ’96 and the quasi-geostrophic equations.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Simplified Two-Stage Model Predictive Control for a Hybrid Multilevel Converter With Floating H-Bridge

This paper proposes a simplified two-stage model predictive control (ST-MPC) for a hybrid multilevel converter, which is an active-neutral-point-clamped converter with floating H-bridge (ANPC-H). The objective of the first stage is to select the voltage vector that has the optimal current tracking performance by using a novel geometrical positioning approach in the complex plane. The second stage selects the best switching state among all the available switching states that belong to the same voltage vector obtained in the first stage, to balance dc capacitor voltages and reduce the common mode voltage. The proposed ST-MPC can dramatically reduce the computational burden and ensure the best current tracking by the two-stage structure, such that the execution time is much shorter compared with the conventional MPC. In addition, the geometrical positioning approach in the first stage is generic and can be applicable for any multilevel converters with N-level output; thus, this ST-MPC can be applied for both sevenand nine-level operation of the hybrid ANPC-H converter under different dc voltage ratios. Both simulation results and experimental results obtained on a silicon carbide hybrid ANPC-H converter prototype validate the feasibility and effectiveness of the proposed ST-MPC strategy.

42 ENGINEERING↗

NASA NTRS1982

Nuclear electric propulsion mission to Neptune

A nuclear electric propulsion (NEP) mission to Neptune is studied. Results of trajectory and propulsion parameter optimization are presented which lead to a selection of key electric propulsion system parameters. Spiral earth escape and spiral capture modes are assumed in the optimization studies. Flight time vs payload for Space Transportation System (STS)/Centaur injection and Triton-aided orbit capture at Neptune are also briefly investigated as methods of improving mission performance. Radiation effects of the earth spiral phase are discussed. The effects of NEP technology on science payloads and mission and system designs are evaluated. NEP is shown to be a very flexible and high performing propulsion technology.

Nock, K. T.↗

NASA NTRS2023

Additive Manufacturing Process Development DOE for NASA HR-1 using Laser Blown Powder Directed Energy Deposition

NASA HR-1 is a Fe-Ni-Cr alloy that is used for high pressure hydrogen applications such as rocket engines, energy, and oil and gas. This investigation was focused on conducting a design of experiment program aimed at mapping the parameter process window for NASA HR-1 using the laser blown powder directed energy deposition (LP-DED) process. A two phased design of experiments (DOE), the first phase of the experiment was focused on optimizing single bead tracks while the second phase of the experiment was focused on optimizing bead overlap hatching in a multi pass bead build up. During the first phase of the deposition parameters, namely laser power, travel speed, and powder feed rate were varied. A down selection from the single bead parameter set was made and hatching experiments were conducted that focused on the overlap distance. In this paper the approach for conducting the DOE and results are discussed. The results focused on measurement of bead geometry, the as-built microstructural evolution, and porosity within the samples. The team at MSFC saw a variety of results across the process map created during the first phase of experimentation and were able to down select a parameter that created an optimal bead shape with a minimal amount of build porosity. It was determined that laser power and robot travel speed were the most sensitive parameters. The results from this investigation will inform future laser powder directed energy deposition parameter developments.

Parker Shake↗

DOE OSTI2026

Trends and limits of CO 2 capture in solid and liquid sorbents at standard conditions

Carbon capture and storage (CCS) plays a critical role in achieving climate change mitigation targets, offering a pathway to decarbonize power generation, industrial processes, and heat production while addressing atmospheric CO 2 removal. While CCS technologies are technically advanced, the widespread adoption of 100 % CO 2 capture capacities such as 1 mol of CO 2 /mol of material and 1 g CO 2 /g storage (targeted by the DARPA, Defense Sciences Office, USA Govt.) has raised questions about the feasibility of achieving higher capture capacities. In the context of limiting global warming to 1.5°C, reaching 100 % CO 2 capture capacity is increasingly necessary, with residual emissions requiring complementary carbon dioxide removal (CDR) technologies. This review exclusively focuses on the CO 2 capture capacities of various sorbents under standard conditions, using different evaluation metrics. This study explores the performance of solid and liquid sorbents under standard conditions, analyzing factors including surface area, pore structure, solvent type, and functionalization to identify materials optimized for industrial-scale CCS applications. Emerging sorbents, including ILs, MOFs, COFs, POPs, DES, RCC, hybrid materials, and reactive sorbents, offer significant potential for enhanced selectivity and energy-efficient regeneration. Through a systematic assessment of gravimetric, volumetric, and molar capacities, the study provides insights into material efficiencies and trade-offs, offering guidance on optimizing sorbent selection for specific applications. The research advances understanding of scalable CCS technologies, contributing to global efforts to achieve net-zero emissions and address the pressing challenge of climate change.

Absorption↗

DOE OSTI2019

Bayesian modeling of inconsistent plastic response due to material variability

The advent of fabrication techniques such as additive manufacturing has focused attention on the considerable variability of material response due to defects and other microstructural aspects. This variability motivates the development of an enhanced design methodology that incorporates inherent material variability to provide robust predictions of performance. In this work, we develop plasticity models capable of representing the distribution of mechanical responses observed in experiments using traditional plasticity models of the mean response and recently developed uncertainty quantification (UQ) techniques. To account for material response variability through variations in physical parameters, we adapt a recent Bayesian embedded modeling error calibration technique. We use Bayesian model selection to determine the most plausible of a variety of plasticity models and the optimal embedding of parameter variability. To expedite model selection, we develop an adaptive importance-sampling-based numerical integration scheme to compute the Bayesian model evidence. In conclusion, we demonstrate that the new framework provides predictive realizations that are superior to more traditional ones, and how these UQ techniques can be used in model selection and assessing the quality of calibrated physical parameters.

36 MATERIALS SCIENCE↗

DOE OSTI2016

SU-G-206-08: How Should Focal Spot Be Chosen for Optimized CT Imaging with Dose Modulation?

Purpose: To choose the preferred focal spot for achieving optimized CT image quality with balanced tube heating considerations. Methods: An anthropomorphic pelvic phantom was scanned using a GE Discovery CT750 HD at 120 and 140kVp, 0.8s rotation time, and pitch of 0.984. “Smart mA” was enabled to simulate a routine abdomen–pelvis CT scan. Permissible mA values at 120 and 140 kVp were obtained from the Serial Load Rating table (for mimicking a busy CT clinical operation) in the scanner Technical Reference Manual. At each kVp station and two Noise Index levels, the mA Upper Limit was set above/below the permissible mA values. Scanned mA values and focal spot (FS) used were obtained from the DICOM header of each image, and the FS-mA relationship was analyzed. For visual confirmation beyond recorded FS information, a CatPhan with a fat-ring attached for mimicking patient size/shape was scanned at 120kVp. A group of radiologists/physicists compared a pair of CatPhan images qualitatively. Lastly, a number of patient cases were evaluated to confirm the FS-mA relationship. Results: When preset Upper Limit values were above the permissible mA values, the Large FS (labeled 1.2) was used in scans, even if the maximum scanned mA values were much lower than the permissible values at both 120 and 140 kVp. Otherwise the Small FS (labeled 0.7) was used. Visual evaluation of the high contrast module of CatPhan and additional analysis of patient cases further confirmed that the preset Upper Limit determines which focal spot is to be used, not the actual maximum mA value to be scanned. Conclusion: Specific FS can be selected by setting up appropriate mA Upper Limit in a protocol. CT protocols could be optimized by selecting appropriate FS for improving patient image quality, especially benefiting the small size and pediatric patients.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2017

CYCLE MODELING AND OPTIMIZATION OF AN INTEGRALLY GEARED sCO2 COMPANDER

This paper presents the selection of a system configuration and off-design control method for an integrally geared compander based on cycle modeling and optimization. The goal of the cycle modeling was to determine a cycle configuration that would reach an efficiency of 50% at design conditions and to optimize off-design control to maintain high efficiencies. The compander is being developed for use in a concentrated solar power supercritical carbon dioxide power plant with expected turbine inlet temperatures of 705°C and utilizing dry cooling leading to compressor inlet temperature varying between 35°C and 55°C. The compander is unique as it consists of eight turbomachinery stages on four pinions all being driven by a single bull gear. The separate stages offer the opportunity to consider a variety of flow splits and cycle configurations including intercooling and multiple stages of reheat. Cycle modeling was conducted in two stages: on-design and off-design. On-design modeling was simulated with all components operating at their design point. This was used to compare the performance of different cycle configurations and design temperatures. Off-design modeling was then performed to investigate the temperature dependence of the cycle efficiency and power output and to develop a control strategy. Strategies considered and discussed include: turbine bypass, compressor recycle, inlet guide vanes, and inventory control. To determine the best operating conditions for each configuration and control strategy, a genetic algorithm was implemented to optimize the cycle performance across the range of operating temperatures being considered. The final selection of cycle configuration, design temperature and control strategy is also presented.

bennett, jeffrey↗

DOE OSTI2016

A comprehensive formulation for volumetric modulated arc therapy planning

Purpose: Volumetric modulated arc therapy (VMAT) is a widely employed radiation therapy technique, showing comparable dosimetry to static beam intensity modulated radiation therapy (IMRT) with reduced monitor units and treatment time. However, the current VMAT optimization has various greedy heuristics employed for an empirical solution, which jeopardizes plan consistency and quality. The authors introduce a novel direct aperture optimization method for VMAT to overcome these limitations. Methods: The comprehensive VMAT (comVMAT) planning was formulated as an optimization problem with an L2-norm fidelity term to penalize the difference between the optimized dose and the prescribed dose, as well as an anisotropic total variation term to promote piecewise continuity in the fluence maps, preparing it for direct aperture optimization. A level set function was used to describe the aperture shapes and the difference between aperture shapes at adjacent angles was penalized to control MLC motion range. A proximal-class optimization solver was adopted to solve the large scale optimization problem, and an alternating optimization strategy was implemented to solve the fluence intensity and aperture shapes simultaneously. Single arc comVMAT plans, utilizing 180 beams with 2° angular resolution, were generated for a glioblastoma multiforme case, a lung (LNG) case, and two head and neck cases—one with three PTVs (H&N{sub 3PTV}) and one with foue PTVs (H&N{sub 4PTV})—to test the efficacy. The plans were optimized using an alternating optimization strategy. The plans were compared against the clinical VMAT (clnVMAT) plans utilizing two overlapping coplanar arcs for treatment. Results: The optimization of the comVMAT plans had converged within 600 iterations of the block minimization algorithm. comVMAT plans were able to consistently reduce the dose to all organs-at-risk (OARs) as compared to the clnVMAT plans. On average, comVMAT plans reduced the max and mean OAR dose by 6.59% and 7.45%, respectively, of the prescription dose. Reductions in max dose and mean dose were as high as 14.5 Gy in the LNG case and 15.3 Gy in the H&N{sub 3PTV} case. PTV coverages measured by D95, D98, and D99 were within 0.25% of the prescription dose. By comprehensively optimizing all beams, the comVMAT optimizer gained the freedom to allow some selected beams to deliver higher intensities, yielding a dose distribution that resembles a static beam IMRT plan with beam orientation optimization. Conclusions: The novel nongreedy VMAT approach simultaneously optimizes all beams in an arc and then directly generates deliverable apertures. The single arc VMAT approach thus fully utilizes the digital Linac’s capability in dose rate and gantry rotation speed modulation. In practice, the new single VMAT algorithm generates plans superior to existing VMAT algorithms utilizing two arcs.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1986

CSTAR star catalogue development

The Continuous Stellar Tracking Attitude Reference (CSTAR) system is an in-house project for the Space Station to provide high accuracy, drift free attitude and angular rate information for the GN&C system. Constraints exist on the star catalogue incorporated in the system. These constraints include the following: mass memory allocated for catalogue storage, star tracker imaging sensitivity, the minimum resolvable separation angle between stars, the width of the field of view of the star tracker, and the desired number of stars to be tracked in a field of view. The Smithsonian Astrophysical Observatory (SAO) catalogue is the basis reference for this study. As it stands, the SAO does not meet the requirements of any of the above constraints. Star selection algorithms have been devised for catalogue optimization. Star distribution statistics have been obtained to aid in the development of these rules. VAX based software has been developed to implement the star selection algorithms. The software is modular and provides a design tool to tailor the catalogue to available star tracker technology. The SAO catalogue has been optimized for the requirements of the present CSTAR system.

Uhde-Lacovara, J. A.↗

DOE OSTI2019

Ideal isotropic auxetic networks from random networks

We design and create isotropically auxetic networks with Poisson's ratio close to −1 in experiments. To achieve this, we selectively prune bonds from disordered networks, and then optimize the properties of individual bonds and nodes.

Reid, Daniel R.↗