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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 955 records · Page 53

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NASA NTRS2000

Unsteady Phenomena During Operation of the SSME Fuel Flowmeter

This report describes a part of the analysis carried in support of the SSME (Space Shuttle Main Engine) Fuel Flowmeter redesign, addressing an intensely researched phenomenon known as "shifting" of the flowmeter constant value. It consists of a sudden change in the flowmeter indication, which occurs simultaneously with the onset of an oscillatory variation of the rotor speed. The change in the flowmeter indications does not correspond to a real change in the volumetric flow through the device. Several causes have been investigated in detail, in the past, without conclusive evidence towards a cause of this phenomenon. The present analysis addresses the flow physics through the flowmeter by assembling results from 3-D CFD (computational fluid dynamics) calculations, airfoil C(sub D)/C(sub L) performance curves and mass moment of inertia characteristics of the rotor into a synergistic calculation which simulates the unsteady regime of the flowmeter operation. The results show that the 4-bladed rotor interacts with the periodic flow pattern created behind the flow straightener upstream in a manner that generates a steady, periodic fluctuation in the rotor's speed. The amplitude of this fluctuation is significantly smaller than the 0.5% of mean speed threshold which constitutes a flight operational limit. When manufacturing errors occur, however, the fluctuations are amplified and can generate a significant apparent change in the flowmeter indication. Two types of possible fabrication errors-which can occur even for parts fabricated within the accepted tolerances for the blade airfoil-are presented, together with their effect on the flowmeter operation.

Marcu, Bogdan↗

NASA NTRS1996

An Experimental Study of Richtmyer-Meshkov Instability

Richtmyer-Meshkov (RM) instability occurs when a planar interface separating two fluids of different density is impulsively accelerated In the direction of its normal. It is one of the most fundamental of fluid instabilities and is of importance in fields ranging from astrophysics to materials processing. Because RM instability experiments are normally carried out in shock tubes, where the generation of a sharp well controlled interface between gases is difficult, there is a scarcity of good experimental results. The experiments presented here utilize a novel technique which circumvents many of the experimental difficulties that have previously limited the study of RM instability. In this system, the instability is generated by bouncing a thin rectangular tank containing two liquids off of a fixed spring. Results obtained from these experiments yield particularly well visualized images of the nonlinear development of the instability. However, because the run time in these experiments is limited, new experiments capable of achieving longer run times are planned.

Jacobs, Jeffrey W.↗

NASA NTRS2014

Aerodynamic Limits on Large Civil Tiltrotor Sizing and Efficiency

The NASA Large Civil Tiltrotor (2nd generation, or LCTR2) has been the reference design for avariety of NASA studies of design optimization, engine and gearbox technology, handling qualities, andother areas, with contributions from NASA Ames, Glenn and Langley Centers, plus academic and industrystudies. Ongoing work includes airfoil design, 3D blade optimization, engine technology studies, andwingrotor aerodynamic interference. The proposed paper will bring the design up to date with the latestresults of such studies, then explore the limits of what aerodynamic improvements might hope toaccomplish. The purpose is two-fold: 1) determine where future technology studies might have the greatestpayoff, and 2) establish a stronger basis of comparison for studies of other vehicle configurations andmissions.

Large Civil Tiltrotor↗

DOE OSTI2024

Characterizing PM 2.5 Emissions and Temporal Evolution of Organic Composition from Incense Burning in a California Residence

The chemical composition of incense-generated organic aerosol in residential indoor air has received limited attention in Western literature. In this study, we conducted incense burning experiments in a single-family California residence during vacancy. Here, we report the chemical composition of organic fine particulate matter (PM 2.5 ), associated emission factors (EFs), and gas-particle phase partitioning for indoor semivolatile organic compounds (SVOCs). Speciated organic PM 2.5 measurements were made using two-dimensional gas chromatography coupled with high-resolution time-of-flight mass spectrometry (GC×GC-HR-ToF-MS) and semivolatile thermal desorption aerosol gas chromatography (SV-TAG). Organic PM 2.5 EFs ranged from 7 to 31 mg g –1 for burned incense and were largely comprised of polar and oxygenated species, with high abundance of biomass-burning tracers such as levoglucosan. Differences in PM 2.5 EFs and chemical profiles were observed in relation to the type of incense burned. Nine indoor SVOCs considered to originate from sources other than incense combustion were enhanced during incense events. Time-resolved concentrations of these SVOCs correlated well with PM 2.5 mass (R 2 > 0.75), suggesting that low-volatility SVOCs such as bis(2-ethylhexyl)phthalate and butyl benzyl phthalate partitioned to incense-generated PM 2.5 . Both direct emissions and enhanced partitioning of low-volatility indoor SVOCs to incense-generated PM 2.5 can influence inhalation exposures during and after indoor incense use.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1992

RT-Syn: A real-time software system generator

This paper presents research into providing highly reusable and maintainable components by using automatic software synthesis techniques. This proposal uses domain knowledge combined with automatic software synthesis techniques to engineer large-scale mission-critical real-time software. The hypothesis centers on a software synthesis architecture that specifically incorporates application-specific (in this case real-time) knowledge. This architecture synthesizes complex system software to meet a behavioral specification and external interaction design constraints. Some examples of these external constraints are communication protocols, precisions, timing, and space limitations. The incorporation of application-specific knowledge facilitates the generation of mathematical software metrics which are used to narrow the design space, thereby making software synthesis tractable. Success has the potential to dramatically reduce mission-critical system life-cycle costs not only by reducing development time, but more importantly facilitating maintenance, modifications, and extensions of complex mission-critical software systems, which are currently dominating life cycle costs.

Setliff, Dorothy E.↗

NASA NTRS2000

Next-Generation Entry/Descent/Landing System for Mars Landers

Many important scientific objectives for Mars exploration require the ability to land safely at select sites. The 'first-generation' entry, descent, and landing (EDL) systems used in previous missions imposed limitations on target site selection due to the delivery accuracy achievable and those systems' inability to recognize and avoid hazardous terrain. This abstract outlines key capabilities of a proposed second-generation EDL system, currently under development by a consortium of NASA centers, Industry, and academic institutions.

Thurman, Sam W.↗

NASA NTRS2001

Entry System Design Considerations for Mars Landers

The objective for the next generation or Mars landers is to enable a safe landing at specific locations of scientific interest. The 1st generation entry, descent and landing systems, ex. Viking and Pathfinder, provided successful landing on Mars but by design were limited to large scale, 100s of km, landing sites with minimal local hazards. The 2 nd generation landers, or smart landers, will provide scientists with access to previously unachievable landing sites by providing precision landing to less than 10 km of a target landing site, with the ability to perform local hazard avoidance, and provide hazard tolerance. This 2nd generation EDL system can be utilized for a range of robotic missions with vehicles sized for science payloads from the small 25-70 kg, Viking, Pathfinder, Mars Polar Lander and Mars Exploration Rover-class, to the large robotic Mars Sample Return, 300 kg plus, science payloads. The 2nd generation system can also be extended to a 3nd generation EDL system with pinpoint landing, 10's of meters of landing accuracy, for more capable robotic or human missions. This paper will describe the design considerations for 2nd generation landers. These landers are currently being developed by a consortium of NASA centers, government agencies, industry and academic institutions. The extension of this system and additional considerations required for a 3nd generation human mission to Mars will be described.

Lockwood, Mary Kae↗

DOE OSTI2021

Geometrical-Based Generative Adversarial Network to Enhance Digital Rock Image Quality

X-ray microcomputed tomography (micro-CT) is a common tool for the study of porous media structures and properties. High-quality micro-CT data are required to accurately capture pore structures. Acquiring high-quality micro-CT data, however, is not always possible, owing to application limitations and experimental constraints. Therefore, we propose a geometrical-based generative adversarial network (GAN) to rapidly restore noisy micro-CT images to their clean counterparts. The training data and related ground-truth (GT) data are scanned for 7 min and 9.5 h, respectively. To evaluate the performance of the geometrical-based GAN, a 6003 voxel image that has never been used for training is reconstructed and compared with the corresponding GT image. Histogram matching and linear normalization are implemented to adjust the histogram of the reconstructed image to that of the GT image. A watershed-based segmentation method is then applied to delineate pore and solid phases. Lastly, we measure the Minkowski functionals and petrophysical properties, including absolute permeability, pore size distribution, drainage capillary pressure-saturation curve, and imbibition relative permeability, to estimate the physical accuracy of the denoised image. The results show that the proposed geometrical-based GAN can accurately restore noisy micro-CT data. By reducing the scanning time from 9.5 h to 7 min, the expenditure of collecting micro-CT can be decreased significantly. This is particularly important for applications where time-lapse images of a dynamic process are required, high-throughput imaging is necessary for real-time data analysis, or where the quantification of large sample volumes is required.

58 GEOSCIENCES↗

NASA NTRS2013

Band-limited Green's Functions for Quantitative Evaluation of Acoustic Emission Using the Finite Element Method

A method of numerically estimating dynamic Green's functions using the finite element method is proposed. These Green's functions are accurate in a limited frequency range dependent on the mesh size used to generate them. This range can often match or exceed the frequency sensitivity of the traditional acoustic emission sensors. An algorithm is also developed to characterize an acoustic emission source by obtaining information about its strength and temporal dependence. This information can then be used to reproduce the source in a finite element model for further analysis. Numerical examples are presented that demonstrate the ability of the band-limited Green's functions approach to determine the moment tensor coefficients of several reference signals to within seven percent, as well as accurately reproduce the source-time function.

Leser, William P.↗

DOE OSTI2024

Fueling the Future: The Emergence of Self-Powered Enzymatic Biofuel Cell Biosensors

Self-powered biosensors are innovative devices that can detect and analyze biological or chemical substances without the need for an external power source. These biosensors can convert energy from the surrounding environment or the analyte itself into electrical signals for sensing and data transmission. The self-powered nature of these biosensors offers several advantages, such as portability, autonomy, and reduced waste generation from disposable batteries. They find applications in various fields, including healthcare, environmental monitoring, food safety, and wearable devices. While self-powered biosensors are a promising technology, there are still challenges to address, such as improving energy efficiency, sensitivity, and stability to make them more practical and widely adopted. This review article focuses on exploring the evolving trends in self-powered biosensor design, outlining potential advantages and limitations. With a focal point on enzymatic biofuel cell power generation, this article describes various sensing mechanisms that employ the analyte as substrate or fuel for the biocatalyst’s ability to generate current. Technical aspects of biofuel cells are also examined. Research and development in the field of self-powered biosensors is ongoing, and this review describes promising areas for further exploration within the field, identifying underexplored areas that could benefit from further investigation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Structure of domain walls in chiral spin liquids

The chiral spin liquid is a canonical state of quantum spins combining topological and symmetry-breaking order, and possible experimental realizations have attracted growing interest. We examine the physics at interfaces between chiral spin liquid domains of opposite chirality. We show that a self-consistent mean-field description of spinons remains possible in the vicinity of a domain wall and use this to formulate a Ginzburg–Landau theory of the domain wall. The bulk of a chiral spin liquid contains gapped spinon excitations and gauge fluctuations, set by a finite spinon mass and a nonzero spinon Chern number. A third class of excitations consists of amplitude fluctuations of the spinon hoppings, which admit a geometric interpretation in terms of effective vielbein fields. These fluctuations are usually neglected because they are irrelevant for a homogeneous chiral spin liquid and are suppressed in standard large- N treatments. Going beyond the purely topological Chern–Simons limit, we incorporate these fluctuations into an effective field theoretic framework and show that they generate momentum-dependent corrections, including Chern–Simons-like linear terms and higher-order contributions, beyond the universal topological limit. We then analyze nontopological properties, including domain wall tension and edge velocity, and explain how they modify observables relative to the uniform case. These results connect measurable, nonuniversal quantities such as domain wall width, domain wall tension, and edge velocity to microscopic parameters and provide concrete targets for experiments.

domain walls↗

DOE OSTI2024

Grid-Forming Inverters: Project Demonstrations and Pilots

Power system operators around the world are pushing the limits of integrating inverter-based resources (IBRs) to very high levels, approaching 100% instantaneous penetration under certain operating conditions. This often applies to smaller power systems with very little or no ac interconnections to other neighboring regions or sometimes to fringes of large balancing areas, such as Denmark or Portugal, within the mainland European power system. These jurisdictions have identified the potential of grid-forming (GFM) technology as a key enabler to support the energy transition with very few or no synchronous generators online. Until recently, practical applications of GFM inverters were limited to microgrids and isolated grids and in smaller grid applications on the order of a few tens of megawatts (MW).

Australia↗

DOE OSTI2024

Utilization of Synthetic Near-Infrared Spectra via Generative Adversarial Network to Improve Wood Stiffness Prediction

Near-infrared (NIR) spectroscopy is widely used as a nondestructive evaluation (NDE) tool for predicting wood properties. When deploying NIR models, one faces challenges in ensuring representative training data, which large datasets can mitigate but often at a significant cost. Machine learning and deep learning NIR models are at an even greater disadvantage because they typically require higher sample sizes for training. In this study, NIR spectra were collected to predict the modulus of elasticity (MOE) of southern pine lumber (training set = 573 samples, testing set = 145 samples). To account for the limited size of the training data, this study employed a generative adversarial network (GAN) to generate synthetic NIR spectra. The training dataset was fed into a GAN to generate 313, 573, and 1000 synthetic spectra. The original and enhanced datasets were used to train artificial neural networks (ANNs), convolutional neural networks (CNNs), and light gradient boosting machines (LGBMs) for MOE prediction. Overall, results showed that data augmentation using GAN improved the coefficient of determination (R 2 ) by up to 7.02% and reduced the error of predictions by up to 4.29%. ANNs and CNNs benefited more from synthetic spectra than LGBMs, which only yielded slight improvement. All models showed optimal performance when 313 synthetic spectra were added to the original training data; further additions did not improve model performance because the quality of the datapoints generated by GAN beyond a certain threshold is poor, and one of the main reasons for this can be the size of the initial training data fed into the GAN. LGBMs showed superior performances than ANNs and CNNs on both the original and enhanced training datasets, which highlights the significance of selecting an appropriate machine learning or deep learning model for NIR spectral-data analysis. The results highlighted the positive impact of GAN on the predictive performance of models utilizing NIR spectroscopy as an NDE technique and monitoring tool for wood mechanical-property evaluation. Further studies should investigate the impact of the initial size of training data, the optimal number of generated synthetic spectra, and machine learning or deep learning models that could benefit more from data augmentation using GANs.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Improving neutrino oscillation measurements through event classification

Precise neutrino energy reconstruction is essential for next-generation long-baseline oscillation experiments, yet current methods remain limited by large uncertainties in neutrino-nucleus interaction modeling. Even so, it is well established that different interaction channels produce systematically varying amounts of missing energy and therefore yield different reconstruction performance–information that standard calorimetric approaches do not exploit. We introduce a strategy that incorporates this structure by classifying events according to their underlying interaction type prior to energy reconstruction. Using supervised machine-learning techniques trained on labeled generator events, we leverage intrinsic kinematic differences among quasielastic scattering, meson-exchange current, resonance production, and deep-inelastic scattering processes. A cross-generator testing framework demonstrates that this classification approach is robust to microphysics mismodeling and, when applied to a simulated DUNE 𝜈 𝜇 disappearance analysis, yields improved accuracy and sensitivity at the 10%–20% level. These results highlight a practical path toward reducing reconstruction-driven systematics in future oscillation measurements.

Ellis, Sebastian A. R. [King's College, London (Un↗

DOE OSTI2022

Two-step neutronics calculations with Shift and Griffin for advanced reactor systems

This research develops the initial coupling of the Shift Monte Carlo (MC) code and the Griffin reactor physics code for reactor analysis of non–light-water reactor systems. The novelty of this work is twofold. It is the first application of Shift to produce the multigroup cross sections needed for Griffin as applied to a non–light-water reactor system; and, the first investigation and analysis of characteristics of the Empire microreactor benchmark that should be considered for steady state and transient reactor physics calculations. This application uses the previously developed two-step neutronics analysis workflow to demonstrate this initial coupling. Here, we outline the two-step neutronics analysis workflow in which the Shift MC code is used to generate the multigroup cross sections and fluxes needed by the Griffin deterministic solver. Details on how these multigroup cross sections are generated using MC tallies are given, as well as the practicalities and limitations of the two-step neutronics workflow. The Empire microreactor benchmark was used to investigate and validate this coupling. Results using this benchmark show good agreement between Griffin calculations using Serpent-generated cross sections and Shift-generated cross sections. Analysis of the characteristics of this Empire benchmark show larger eigenvalue differences between heterogeneous and pin–homogenized solutions compared to those of traditional light-water reactor (LWR) designs, thus requiring super homogenization factor corrections for accurate eigenvalue and power distribution predictions.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS1992

Limitations on squeezing and formation of the superposition of two macroscopically distinguishable states at fundamental frequency in the process of second harmonic generation

The results of numerical simulations of quantum state evolution in the process of second harmonic generation (SHG) are discussed. It is shown that at a particular moment of time in the fundamental mode initially coherent state turns into a superposition of two macroscopically distinguished states. The question of whether this superposition exhibits quantum interference is analyzed.

Nikitin, S. P.↗

NASA NTRS2018

Evaluation of Multiple Flow Constrained Area Capacity Setting Methods for Collaborative Trajectory Options Program

The purpose of this study was to compare flow constrained area (FCA) capacity setting methods for Collaborative Trajectory Options Program (CTOP) as they pertain to the Integrated Demand Management (IDM) concept. IDM uses flow balancing to manage air traffic across multiple FCAs with a common downstream constraint, as well as constraints at the respective FCA locations. FCA capacity rates can be set manually, but generating capacities for multiple, interdependent FCAs could potentially over-burden a user. A new enhancement to CTOP called the FCA Balance Algorithm (FBA) was developed at NASA Ames Research Center to improve the process of allocating capacity across multiple flow constrained segments in the airspace. The FBA evaluates the predicted demand and capacity across multiple FCAs and dynamically generates capacity settings for the FCAs that best meet capacity limits for all identified constraints. In a human-in-the-loop simulation study, both manual and automated capacity setting methods were evaluated in terms of their overall feasibility using measures of system performance, human performance, and qualitative feedback. Subject matter experts were asked to use three different methods to allocate capacity to three FCAs, either (1) by manually setting capacity for every 60-minute time window, (2) by manually setting capacity for every 15-minute time window, or (3) by using the FBA capability to automatically generate capacity settings. Results showed no significant differences in terms of overall system performance, indicated by similar ground delay and airport throughput numbers between methods. However, differences in individual strategies afforded by the manual methods allowed some participants to achieve system-wide delay that was much lower than the average. The FBA was the fastest method of capacity setting, and it received the lowest subjective rating scores on physical task load, mental task load, task difficulty and task complexity out of the three methods. Finally, participants explained through qualitative feedback that there were many benefits to using the FBA, such as ease of use, accuracy, and low risk of human input error. Participants did not experience the same limitations with the FBA that they did with the manual methods, such as reduced accuracy in the 60-minute manual condition, or high complexity in the 15-minute/manual condition. These results suggest that the FBA automation enhancement to CTOP maintains system performance while improving human performance. Therefore, the FBA could be introduced as a way to mitigate operator workload while planning a CTOP.

NextGen↗

NASA NTRS2018

Evaluation of Multiple Flow Constrained Area Capacity Setting Methods for Collaborative Trajectory Options Program

NextGen↗