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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 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Tradeoffs When Considering Deep Reinforcement Learning for Contingency Management in Advanced Air Mobility

Air transportation is undergoing a rapid evolution globally with the introduction of Advanced Air Mobility (AAM) and with it comes novel challenges and opportunities for transforming aviation. As AAM operations introduce increasing heterogeneity in vehicle capabilities and density, increased levels of automation are likely necessary to achieve operational safety and efficiency goals. This paper focuses on one example where increased automation has been suggested. Autonomous operations will need contingency management systems that can monitor evolving risk across a span of interrelated (or interdependent) hazards and, if necessary, execute appropriate control interventions via supervised or automated decision making. Accommodating this complex environment may require automated functions (autonomy) that apply artificial intelligence (AI) techniques that can adapt and respond to a quickly changing environment. This paper explores the use of Deep Reinforcement Learning (DRL) which has shown promising performance in complex and high-dimensional environments where the objective can be constructed as a sequential decision-making problem. An extension of a prior formulation of the contingency management problem as a Markov Decision Process (MDP) is presented and uses a DRL framework to train agents that mitigate hazards present in the simulation environment. A comparison of these learning-based agents and classical techniques is presented in terms of their performance, verification difficulties, and development process.

machine learningautonomous systems; flight simulat↗
NASA NTRSDate not supplied

Tradeoffs When Considering Deep Reinforcement Learning for Contingency Management in Advanced Air Mobility

Air transportation is undergoing a rapid evolution globally with the introduction of Advanced Air Mobility (AAM) and with it comes novel challenges and opportunities for transforming aviation. As AAM operations introduce increasing heterogeneity in vehicle capabilities and density, increased levels of automation are likely necessary to achieve operational safety and efficiency goals. This paper focuses on one example where increased automation has been suggested. Autonomous operations will need contingency management systems that can monitor evolving risk across a span of interrelated (or interdependent) hazards and, if necessary, execute appropriate control interventions via supervised or automated decision making. Accommodating this complex environment may require automated functions (autonomy) that apply artificial intelligence (AI) techniques that can adapt and respond to a quickly changing environment. This paper explores the use of Deep Reinforcement Learning (DRL) which has shown promising performance in complex and high-dimensional environments where the objective can be constructed as a sequential decision-making problem. An extension of a prior formulation of the contingency management problem as a Markov Decision Process (MDP) is presented and uses a DRL framework to train agents that mitigate hazards present in the simulation environment. A comparison of these learning-based agents and classical techniques is presented in terms of their performance, verification difficulties, and development process.

machine learning↗
DOE OSTI2024

Theoretical design and performance of three-dimensional, pillared FeS 2 cathodes

Three-dimensional (3D) electrode design can provide improved capacities and rate capabilities over conventional two-dimensional electrodes by enhancing electrical and ionic transport. Here, expanding upon our previous modeling efforts for conversion chemistry lithium-ion batteries, we develop a pseudo-four-dimensional (P4D) approach that is subsequently used to investigate the design of a pillared FeS 2 electrode. The model considers transport in three dimensions with an additional “fourth” dimension corresponding to the solid-state lithium transport within the active material particles. Additionally, we allow for expansion of the active material during the conversion reaction to understand how internal stresses impact the electrochemical performance of the cell. By optimizing the model with respect to areal capacity, we are able to predict areal capacities up to 16.8 mAh/cm 2 for an areal current density of 1.78 mA/cm 2 and a 103% improvement for the three-dimensional electrodes over planar electrodes of equal volume. Despite the promising results, our simulations suggest that 3D design may be difficult for conversion cathode materials due to the large internal stresses that arise during conversion. Nevertheless, the model is robust and adaptable to other materials that may be more suitable for 3D electrodes due to a lesser change in volume during discharge.

Conversion cathode materials↗
DOE OSTI2021

Performance of a Hybrid HVAC-Integrated Thermal Storage Device

Thermal equipment in buildings is a primary contributor to peak loads on the electrical grid. Thermal energy storage is a cost-effective strategy to decouple electric use from thermal loads, thus reducing grid peak costs for building owners. One method for storing thermal energy in a building is to integrate a phase change material (PCM) directly into the heating, ventilation, and air conditioning system. These systems often require additional glycol loops, pumps, valves, and heat exchangers to couple the storage to the cooling system and building space, which increases the complexity and cost. This work will discuss an alternate approach where the storage is added directly into the heat pump evaporator. A detailed two-dimensional finite difference heat transfer model of a PCM-refrigerant-glycol heat exchanger was developed to simulate the performance of this component. The fluid stream was discretized along the flow direction to capture changes in the fluid properties and local heat transfer rates, and the phase change material was discretized in both the x and y directions to capture the movement of the melt front. The model was used to understand the impact of different material and geometric properties on the charge and discharge characteristics of the device. Finally, a Ragone framework analogous to that used for electrochemical batteries was used to maximize the energy density and round-trip efficiency of the device while supplying loads appropriate for space cooling in buildings.

buildings↗
NASA NTRS1992

Middeck zero-gravity dynamics experiment - Comparison of ground and flight test data

An analytic and experimental study of the changes in the modal parameters of space structural test articles from one- to zero-gravity is presented. Deployable, erectable, and rotary modules was assembled to form three one- and two-dimensional structures, in which variations in bracing wire and rotary joint preload could be introduced. The structures were modeled as if hanging from a suspension system in one gravity, and unconstrained, as if free floating in zero-gravity. The analysis is compared with ground experimental measurements, made on a spring/wire suspension system with a nominal plunge frequency of one Hertz, and with measurements made on the Shuttle middeck. The degree of change in linear modal parameters as well as the change in nonlinear nature of the response is examined. Trends in modal parameters are presented as a function of force amplitude, joint preload, and ambient gravity level.

Crawley, Edward F.↗
DOE OSTI2019

Impact of reduced dimensionality on the correlation length and magnetization dynamics of the spin chain cobaltite Ca 3 Co 2 O 6

We have recently applied the magnetic field and temperature dependence of magnetic entropy change as a probe of the magnetic states of a single crystal of Ca 3 Co 2 O 6 to establish a more comprehensive magnetic phase diagram for this exotic system. The results are consistent with the spin-density wave description of the ground state and indicate the suppression of the modulated state in favor of a ferrimagnetic up-up-down arrangement of the spin chains with the application of a moderate field. We demonstrate, in this study, that the features of the static magnetic phase diagram are preserved when the grain size of Ca 3 Co 2 O 6 is reduced to 440 nm (below the maximum c-axis correlation length of ~550 nm in Ca 3 Co 2 O 6 ), although the polycrystalline materials show a non-saturating behavior, rounded steps, and reduced magnetization when compared to the single crystal. Our new finding of the multiple low-temperature magnetization steps in the 440 nm sample, together with conflicting reports concerning such steps in nanostructured samples, suggests that correlations in the ab plane are more important than correlations along the c-axis in the appearance of the plateaus. The relaxation processes in the system are studied through the decay of remanent magnetization, ac susceptibility, and Argand diagrams. The introduction of grain boundaries in Ca 3 Co 2 O 6 weakens the slow-dynamic state, widens the low-temperature distribution of relaxation times, and lowers activation energies within the Arrhenius-like relaxation regime.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Scalar modular bootstrap and zeros of the Riemann zeta function

Using the technology of harmonic analysis, we derive a crossing equation that acts only on the scalar primary operators of any two-dimensional conformal field theory with U(1) c symmetry. From this crossing equation, we derive bounds on the scalar gap of all such theories. Rather remarkably, our crossing equation contains information about all nontrivial zeros of the Riemann zeta function. As a result, we rephrase the Riemann hypothesis purely as a statement about the asymptotic density of scalar operators in certain two-dimensional conformal field theories. We discuss generalizations to theories with only Virasoro symmetry.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Vertical full-colour micro-LEDs via 2D materials-based layer transfer

Micro-LEDs (µLEDs) have been explored for augmented and virtual reality display applications that require extremely high pixels per inch and luminance. However, conventional manufacturing processes based on the lateral assembly of red, green and blue (RGB) µLEDs have limitations in enhancing pixel density. Recent demonstrations of vertical µLED displays have attempted to address this issue by stacking freestanding RGB LED membranes and fabricating top-down, but minimization of the lateral dimensions of stacked µLEDs has been difficult. Here we report full-colour, vertically stacked µLEDs that achieve, to our knowledge, the highest array density (5,100 pixels per inch) and the smallest size (4 µm) reported to date. This is enabled by a two-dimensional materials-based layer transfer technique that allows the growth of RGB LEDs of near-submicron thickness on two-dimensional material-coated substrates via remote or van der Waals epitaxy, mechanical release and stacking of LEDs, followed by top-down fabrication. The smallest-ever stack height of around 9 µm is the key enabler for record high µLED array density. We also demonstrate vertical integration of blue µLEDs with silicon membrane transistors for active matrix operation. Furthermore, these results establish routes to creating full-colour µLED displays for augmented and virtual reality, while also offering a generalizable platform for broader classes of three-dimensional integrated devices.

42 ENGINEERING↗
NASA NTRS1987

Shuttle computational grid generation

The well known Karman-Trefftz conformal transformation, consisting of repeated applications of the same basic formula, were found to be quite successful to body, wing, and wing-body cross sections. This grid generation technique is extended to cross sections of more complex forms, and also more automatic. Computer programs were written for the selection of hinge points on cross section with angular shapes, the Karman-Trefftz tranformation of arbitrary shapes, and the special transform of hinge point on the imaginary axis. A feasibility study is performed for the future application of conformal mapping grid generation to complex three dimensional configurations. Examples such as Orbiter vehicle section and a few others were used.

Ing, Chang↗
NASA NTRS2005

Microscale out-of-plane anemometer

A microscale out-of-plane thermal sensor. A resistive heater is suspended over a substrate by supports raised with respect to the substrate to provide a clearance underneath the resistive heater for fluid flow. A preferred fabrication process for the thermal sensor uses surface micromachining and a three-dimensional assembly to raise the supports and lift the resistive heater over the substrate.

Liu, Chang↗
NASA NTRS2007

The Effect of Acoustic Disturbances on the Operation of the Space Shuttle Main Engine Fuel Flowmeter

The Space Shuttle Main Engine (SSME) uses a turbine fuel flowmeter (FFM) in its Low Pressure Fuel Duct (LPFD) to measure liquid hydrogen flowrates during engine operation. The flowmeter is required to provide accurate and robust measurements of flow rates ranging from 10000 to 18000 GPM in an environment contaminated by duct vibration and duct internal acoustic disturbances. Errors exceeding 0.5% can have a significant impact on engine operation and mission completion. The accuracy of each sensor is monitored during hot-fire engine tests on the ground. Flow meters which do not meet requirements are not flown. Among other parameters, the device is screened for a specific behavior in which a small shift in the flow rate reading is registered during a period in which the actual fuel flow as measured by a facility meter does not change. Such behavior has been observed over the years for specific builds of the FFM and must be avoided or limited in magnitude in flight. Various analyses of the recorded data have been made prior to this report in an effort to understand the cause of the phenomenon; however, no conclusive cause for the shift in the instrument behavior has been found. The present report proposes an explanation of the phenomenon based on interactions between acoustic pressure disturbances in the duct and the wakes produced by the FFM flow straightener. Physical insight into the effects of acoustic plane wave disturbances was obtained using a simple analytical model. Based on that model, a series of three-dimensional unsteady viscous flow computational fluid dynamics (CFD) simulations were performed using the MSFC PHANTOM turbomachinery code. The code was customized to allow the FFM rotor speed to change at every time step according to the instantaneous fluid forces on the rotor, that, in turn, are affected by acoustic plane pressure waves propagating through the device. The results of the simulations show the variation in the rotation rate of the flowmeter due to the interaction of the flow straightener wakes and the upstream propagating acoustic waves. A detailed analysis of the acoustic disturbance effects is presented along with an assessment of the impact on measurement accuracy.

Marcu, Bogdan↗
DOE OSTI2022

Data for Monitoring Fracture Saturation with Internal Transportable Seismic Sources and Twin Neural Networks

Seismic coda-wave analysis is a well-developed method for detecting subtle physical changes in complex media by measuring arrival times in the late-arriving energy from multiply-scattered or reflected waves. However, a challenge arises when multiply-scattered waves are not sufficiently separated in time from the direct arrivals to provide a clear coda wave train. Additional complications for monitoring changes in fracture systems arise when the signals originate from unsynchronized internal sources, such as natural induced seismicity, from acoustic emission, or from transportable intra-fracture sources (chattering dust), that generate uncontrolled signals that vary in arrival time, amplitude and frequency content. Here, we use a twin neural network (also known as a Siamese neural network) for dimensionality reduction to analyze signals from chattering dust to classify the fluid saturation state of a synthetic fracture system. The twin neural network with shared weights generates a low-dimensional representation of the data input by minimizing contrastive loss, serving as the input to a multiclass classifier that accurately classifies whether multiple fractures in a fracture system are fully saturated or partially saturated, or whether a change in saturation has occurred in different fractures in the system. These results show that information buried in unresolved codas from uncontrolled sources can be extracted using machine learning to monitor the evolution of fracture systems caused by physical and chemical processes even when the scattered and direct wave fields overlap.

58 GEOSCIENCES↗
NASA NTRS2002

Impact of left ventricular outflow tract area on systolic outflow velocity in hypertrophic cardiomyopathy: a real-time three-dimensional echocardiographic study

OBJECTIVES: The aim of this study was to use real-time three-dimensional echocardiography (3DE) to investigate the quantitative relation between minimal left ventricular (LV) outflow tract area (A(LVOT)) and maximal LV outflow tract (LVOT) velocity in patients with hypertrophic obstructive cardiomyopathy (HCM). BACKGROUND: In patients with HCM, LVOT velocity should change inversely with minimal A(LVOT) unless LVOT obstruction reduces the pumping capacity of the ventricle. METHODS: A total of 25 patients with HCM with systolic anterior motion (SAM) of the mitral valve leaflets underwent real-time 3DE. The smallest A(LVOT) during systole was measured using anatomically oriented two-dimensional "C-planes" within the pyramidal 3DE volume. Maximal velocity across LVOT was evaluated by two-dimensional Doppler echocardiography (2DE). For comparison with 3DE A(LVOT), the SAM-septal distance was determined by 2DE. RESULTS: Real-time 3DE provided unique information about the dynamic SAM-septal relation during systole, with A(LVOT) ranging from 0.6 to 5.2 cm(2) (mean: 2.2 +/- 1.4 cm(2)). Maximal velocity (v) correlated inversely with A(LVOT) (v = 496 A(LVOT)(-0.80), r = -0.95, p < 0.001), but the exponent (-0.80) was significantly different from -1.0 (95% confidence interval: -0.67 to -0.92), indicating a significant impact of small A(LVOT) on the peak LVOT flow rate. By comparison, the best correlation between velocity and 2DE SAM-septal distance was significantly (p < 0.01) poorer at -0.83, indicating the superiority of 3DE for assessing A(LVOT). CONCLUSIONS: Three-dimensional echocardiography-measured A(LVOT) provides an assessment of HCM geometry that is superior to 2DE methods. These data indicate that the peak LVOT flow rate appears to be significantly decreased by reduced A(LVOT). Real-time 3DE is a potentially valuable clinical tool for assessing patients with HCM.

NASA Discipline Cardiopulmonary↗
DOE OSTI2018

Formation of a Nanophase Wetting Layer and Metal Growth on a Semiconductor

Based on the data on the atomic density of a film and degree of its homogeneity during the formation of the interface between 3d transition metals (Cr, Co, Fe, or Cu) and silicon, a new concept of forming a contact between a reactive metal and a semiconductor has been justified. According to this concept, the low-temperature vapor-phase deposition of a metal onto a semiconductor is accompanied by the formation of a two-dimensional nanophase wetting layer of a metal or its mixture with silicon with a thickness of several monolayers, which significantly affects the interface formation and structure. This concept changes a perspective of forming a contact between a metal and a semiconductor substrate: it is necessary to take into account not only the formation of surface phases and clusters and/or the mixing process, but also the effect of elastic wetting of a substrate by the forming phases.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Nature-inspired lotus-shaped fins combined with hybrid nanoparticles and metal foam for high-performance latent heat thermal energy storage

Latent heat thermal energy storage (LHTES) systems play a critical role in renewable energy integration by providing high energy density and nearly isothermal operation during phase transitions. However, their performance is often limited by slow melting/charging rates, which motivates the search for enhanced heat transfer designs. This study investigates the melting behavior of RT-82 phase change material (PCM) using novel lotus-shaped fins combined with copper metal foam and conductive graphene nanoparticles and carbon nanotubes. A two-dimensional enthalpy-porosity model in ANSYS Fluent was developed to simulate the charging/melting process, capturing non-thermal equilibrium between the foam and PCM/nano-PCM. In this study, effects of fin geometry, nanoparticle concentration, and foam porosity on melting dynamics and cost-performance trade-offs were investigated. Results showed that natural convection accelerated melting by ~12% compared to conduction-only scenarios. Optimized lotus-shaped fins with higher fin density (T3F4 and T3F10) achieved up to 63% faster melting relative to sparse configurations. Graphene nanoparticles improved thermal conductivity, with a 6% volume fraction, by reducing melting time by ~6.9%, while their combination with 75% porosity foam achieved a maximum reduction in the melting time of ~51% compared to pure PCM. Cost-performance analysis identified T3F4 as the most balanced design, offering rapid thermal response without excessive material costs, while moderate-density designs like T3S6 provided economical alternatives with acceptable performance. These results highlight the performance enhancement that can be achieved by integrating bio-inspired fins, nanoparticles, and foams, into compact and efficient LHTES for solar heating, building thermal management, and industrial waste-heat recovery applications.

25 ENERGY STORAGE↗
DOE OSTI2021

Mapping Post-Climate Change Biogeographical Regions with Deep Latent Variable Models

Forecasting future changes to biodiversity due to shifts in climate is challenging due to nonlinear interactions between species as recorded in their presence/absence data. This work proposes using variational autoencoders with environmental covariates to identify low-dimensional structure in species’ joint co-occurrence patterns and leveraging this simplified representation to provide multivariate predictions of their habitat extent under future climate scenarios. We pursue a latent space clustering approach to map biogeographical regions of frequently co-occurring species and apply this methodology to a dataset from northern Belgium, generating predictive maps illustrating how these regions may expand or contract with changing temperature under a future climate scenario.

Krapu, Chris↗
DOE OSTI2025

Modeling supercritical CO2 injection induced rupture of a minor fault embedded in a poroelastic layered reservoir-caprock system

CO2 injection for geologic carbon sequestration involves hydromechanical processes that lead to changes in fluid pressure and stresses that can activate existing faults. This paper presents a new method and workflow of modeling fault activation considering more complex three-dimensional geometry of natural faults using the TOUGH-FLAC multiphase fluid flow and geomechanical simulator. In this method and workflow, FLAC3D mechanical interfaces and TOUGH3 finite volume elements are discretized using computer aided design and gridding software along with a tailored mesh translation routine. The method and workflow are demonstrated with a model of a curved minor fault embedded in a poro-elastic layered reservoir-caprock system. The model is used for a comprehensive sensitivity analysis of fault responses to fault length, injection mass rate, injection schedule, well-fault distance, and well locations versus fault location. Four metrics (CO2 plume, shear state of fault, pressure and stress path at fault monitoring points) are selected to assess CO2 migration, pressure change, and the reactivation of faults. The results reveal that CO2 can bypass around the tip of the minor impermeable fault, building up pressure and poro-elastic stress on both sides that tends to impede fault rupture. Our study shows the benefit of carefully designing the injection to achieve the targeted final storage volume, starting at a relatively low rate for considerable time, and then ramping up the injection rate to the full rate of injection. The initial low injection has two distinct benefits: (1) it allows for the formation of an extensive CO2 plume with a much higher mobility through a low viscosity that will result in a lower pressure for a given injection rate, and (2) it allows for gradual build-up of horizontal poro-elastic stress within the reservoir that will tend to impede activation of steeply dipping faults. The injection scenario starting at a low injection rate, denoted here as conservative injection, can significantly reduce the risk of fault activation as high fluid mobility and reservoir strengthening poro-elastic stress has been established long before reaching the peak injection rates. Moreover, simultaneous injection in two injection wells on both sides of fault can provide further reservoir strengthening through poro-elastic stress buildup acting on a fault under normal faulting stress regime. The findings presented in the paper can provide practical and effective guidance on long-term, safe, and reliable geological CO2 storage.

Cao, Meng↗