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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 505 records · Page 28

Cascade Storage and Delivery System for a Multi Mission Space Exploration Vehicle (MMSEV)

NASA is developing a Multi Mission Space Exploration Vehicle (MMSEV) for missions beyond Low Earth Orbit (LEO). The MMSEV is a pressurized vehicle used to extend the human exploration envelope for Lunar, Near Earth Object (NEO), and Deep Space missions. The Johnson Space Center is developing the Environmental Control and Life Support System (ECLSS) for the MMSEV. The MMSEV s intended use is to support longer sortie lengths with multiple Extra Vehicular Activities (EVAs) on a higher magnitude than any previous vehicle. This paper presents an analysis of a high pressure oxygen cascade storage and delivery system that will accommodate the crew during long duration Intra Vehicular Activity (IVA) and capable of multiple high pressure oxygen fills to the Portable Life Support System (PLSS) worn by the crew during EVAs. A cascade is a high pressure gas cylinder system used for the refilling of smaller compressed gas cylinders. Each of the large cylinders are filled by a compressor, but the cascade system allows small cylinders to be filled without the need of a compressor. In addition, the cascade system is useful as a "reservoir" to accommodate low pressure needs. A regression model was developed to provide the mechanism to size the cascade systems subject to constraints such as number of crew, extravehicular activity duration and frequency, and ullage gas requirements under contingency scenarios. The sizing routine employed a numerical integration scheme to determine gas compressibility changes during depressurization and compressibility effects were captured using the Soave-Redlich-Kwong (SRK) equation of state. A multi-dimensional nonlinear optimization routine was used to find the minimum cascade tank system mass that meets the mission requirements. The sizing algorithms developed in this analysis provide a powerful framework to assess cascade filling, compressor, and hybrid systems to design long duration vehicle ECLSS architecture. 1

Yagoda, Evan↗

Predicting Bone Mechanical State During Recovery After Long-Duration Skeletal Unloading Using QCT and Finite Element Modeling

During long-duration missions at the International Space Station, astronauts experience weightlessness leading to skeletal unloading. Unloading causes a lack of a mechanical stimulus that triggers bone cellular units to remove mass from the skeleton. A mathematical system of the cellular dynamics predicts theoretical changes to volume fractions and ash fraction in response to temporal variations in skeletal loading. No current model uses image technology to gather information about a skeletal site s initial properties to calculate bone remodeling changes and then to compare predicted bone strengths with the initial strength. The goal of this study is to use quantitative computed tomography (QCT) in conjunction with a computational model of the bone remodeling process to establish initial bone properties to predict changes in bone mechanics during bone loss and recovery with finite element (FE) modeling. Input parameters for the remodeling model include bone volume fraction and ash fraction, which are both computed from the QCT images. A non-destructive approach to measure ash fraction is also derived. Voxel-based finite element models (FEM) created from QCTs provide initial evaluation of bone strength. Bone volume fraction and ash fraction outputs from the computational model predict changes to the elastic modulus of bone via a two-parameter equation. The modulus captures the effect of bone remodeling and functions as the key to evaluate of changes in strength. Application of this time-dependent modulus to FEMs and composite beam theory enables an assessment of bone mechanics during recovery. Prediction of bone strength is not only important for astronauts, but is also pertinent to millions of patients with osteoporosis and low bone density.

Chang, Katarina L.↗

Electrochemistry-based Battery Modeling for Prognostics

Batteries are used in a wide variety of applications. In recent years, they have become popular as a source of power for electric vehicles such as cars, unmanned aerial vehicles, and commericial passenger aircraft. In such application domains, it becomes crucial to both monitor battery health and performance and to predict end of discharge (EOD) and end of useful life (EOL) events. To implement such technologies, it is crucial to understand how batteries work and to capture that knowledge in the form of models that can be used by monitoring, diagnosis, and prognosis algorithms. In this work, we develop electrochemistry-based models of lithium-ion batteries that capture the significant electrochemical processes, are computationally efficient, capture the effects of aging, and are of suitable accuracy for reliable EOD prediction in a variety of usage profiles. This paper reports on the progress of such a model, with results demonstrating the model validity and accurate EOD predictions.

battery↗

A Physics-Based Modeling Framework for Prognostic Studies

Prognostics and Health Management (PHM) methodologies have emerged as one of the key enablers for achieving efficient system level maintenance as part of a busy operations schedule, and lowering overall life cycle costs. PHM is also emerging as a high-priority issue in critical applications, where the focus is on conducting fundamental research in the field of integrated systems health management. The term diagnostics relates to the ability to detect and isolate faults or failures in a system. Prognostics on the other hand is the process of predicting health condition and remaining useful life based on current state, previous conditions and future operating conditions. PHM methods combine sensing, data collection, interpretation of environmental, operational, and performance related parameters to indicate systems health under its actual application conditions. The development of prognostics methodologies for the electronics field has become more important as more electrical systems are being used to replace traditional systems in several applications in the aeronautics, maritime, and automotive fields. The development of prognostics methods for electronics presents several challenges due to the great variety of components used in a system, a continuous development of new electronics technologies, and a general lack of understanding of how electronics fail. Similarly with electric unmanned aerial vehicles, electrichybrid cars, and commercial passenger aircraft, we are witnessing a drastic increase in the usage of batteries to power vehicles. However, for battery-powered vehicles to operate at maximum efficiency and reliability, it becomes crucial to both monitor battery health and performance and to predict end of discharge (EOD) and end of useful life (EOL) events. We develop an electrochemistry-based model of Li-ion batteries that capture the significant electrochemical processes, are computationally efficient, capture the effects of aging, and are of suitable accuracy for reliable EOD prediction in a variety of usage profiles.

Li-ion Batteries↗

A Wolf-Rayet-Like Progenitor of SN 2013cu from Spectral Observations of a Stellar Wind

The explosive fate of massive Wolf-Rayet stars (WRSs) is a key open question in stellar physics. An appealing option is that hydrogen- deficient WRSs are the progenitors of some hydrogen-poor supernova explosions of types IIb, Ib and Ic. A blue object, having luminosity and colours consistent with those of some WRSs, has recently been identified in pre-explosion images at the location of a supernova of type Ib, but has not yet been conclusively determined to have been the progenitor. Similar work has so far only resulted in non-detections. Comparison of early photometric observations of type Ic supernovae with theoretical models suggests that the progenitor stars had radii of less than 10(exp 12) centimetres, as expected for some WRSs. The signature of WRSs, their emission line spectra, cannot be probed by such studies. Here we report the detection of strong emission lines in a spectrum of type IIb supernova 2013cu (iPTF13ast) obtained approximately 15.5 hours after explosion (by 'flash spectroscopy', which captures the effects of the supernova explosion shock breakout flash on material surrounding the progenitor star).We identify Wolf-Rayet-like wind signatures, suggesting a progenitor of the WN(h) subclass (those WRSs with winds dominated by helium and nitrogen, with traces of hydrogen). The extent of this dense wind may indicate increased mass loss from the progenitor shortly before its explosion, consistent with recent theoretical predictions.

observations↗

Representing Extremes in Agricultural Models

AgMIP and related projects are conducting several activities to understand and improve crop model response to extreme events. This involves crop model studies as well as the generation of climate datasets and scenarios more capable of capturing extremes. Models are typically less responsive to extreme events than we observe, and miss several forms of extreme events. Models also can capture interactive effects between climate change and climate extremes. Additional work is needed to understand response of markets and economic systems to food shocks. AgMIP is planning a Coordinated Global and Regional Assessment of Climate Change Impacts on Agricultural Production and Food Security with an aim to inform the IPCC Sixth Assessment Report.

Agricultural systems↗

Variability of Phenology and Fluxes of Water and Carbon with Observed and Simulated Soil Moisture in the Ent Terrestrial Biosphere Model (Ent TBM Version 1.0.1.0.0)

The Ent Terrestrial Biosphere Model (Ent TBM) is a mixed-canopy dynamic global vegetation model developed specifically for coupling with land surface hydrology and general circulation models (GCMs). This study describes the leaf phenology submodel implemented in the Ent TBM version 1.0.1.0.0 coupled to the carbon allocation scheme of the Ecosystem Demography (ED) model. The phenology submodel adopts a combination of responses to temperature (growing degree days and frost hardening), soil moisture (linearity of stress with relative saturation) and radiation (light length). Growth of leaves, sapwood, fine roots, stem wood and coarse roots is updated on a daily basis. We evaluate the performance in reproducing observed leaf seasonal growth as well as water and carbon fluxes for four plant functional types at five Fluxnet sites, with both observed and prognostic hydrology, and observed and prognostic seasonal leaf area index. The phenology submodel is able to capture the timing and magnitude of leaf-out and senescence for temperate broadleaf deciduous forest (Harvard Forest and Morgan- Monroe State Forest, US), C3 annual grassland (Vaira Ranch, US) and California oak savanna (Tonzi Ranch, US). For evergreen needleleaf forest (Hyytiäla, Finland), the phenology submodel captures the effect of frost hardening of photosynthetic capacity on seasonal fluxes and leaf area. We address the importance of customizing parameter sets of vegetation soil moisture stress response to the particular land surface hydrology scheme. We identify model deficiencies that reveal important dynamics and parameter needs.

Soil moisture↗

Capturing Safety Requirements to Enable Effective Task Allocation Between Humans and Automaton in Increasingly Autonomous Systems

There is a current drive towards enabling the deployment of increasingly autonomous systems in the National Airspace System (NAS). However, shifting the traditional roles and responsibilities between humans and automation for safety critical tasks must be managed carefully, otherwise the current emergent safety properties of the NAS may be disrupted. In this paper, a verification activity to assess the emergent safety properties of a clearly defined, safety critical, operational scenario that possesses tasks that can be fluidly allocated between human and automated agents is conducted. Task allocation role sets were proposed for a human-automation team performing a contingency maneuver in a reduced crew context. A safety critical contingency procedure (engine out on takeoff) was modeled in the Soar cognitive architecture, then translated into the Hybrid Input Output formalism. Verification activities were then performed to determine whether or not the safety properties held over the increasingly autonomous system. The verification activities lead to the development of several key insights regarding the implicit assumptions on agent capability. It subsequently illustrated the usefulness of task annotations associated with specialized requirements (e.g., communication, timing etc.), and demonstrated the feasibility of this approach.

Neogi, Natasha A.↗

The Role of the Hall Effect in Global Structure and Dynamics of Planetary Magnetospheres: Ganymede as a Case Study

We present high-resolution Hall MHD simulations of Ganymede's magnetosphere demonstrating that Hall electric fields in ion-scale magnetic reconnection layers have significant global effects not captured in resistive MHD simulations. Consistent with local kinetic simulations of magnetic reconnection, our global simulations show the development of intense field-aligned currents along the magnetic separatrices. These currents extend all the way down to the moon's surface, where they may contribute to Ganymede's aurora. Within the magnetopause and magnetotail current sheets, Hall J x B forces accelerate ions to the local Alfven speed in the out-of-plane direction, producing a global system of ion drift belts that circulates Jovian magnetospheric plasma throughout Ganymede's magnetosphere. We discuss some observable consequences of these Hall-induced currents and ion drifts: the appearance of a sub-Jovian 'double magnetopause' structure, an Alfvenic ion jet extending across the upstream magnetopause, and an asymmetric pattern of magnetopause Kelvin-Helmholtz waves.

Magnetic Reconnection↗

Observations of Non-Spherical, Graphite-Epoxy Projectiles Impacting a Thermally-Insulated, Double-Wall Shield

The DebriSat hypervelocity impact experiment, performed at the Arnold Engineering Development Center (U.S.A.F. Arnold Air Force Base), is intended to update the catastrophic break-up models for modern satellites. To this end, the DebrisSat was built with many modern materials including structural panels of carbon-fiber, reinforced polymer (CFRP). Subsequent to the experiment, fragments of the DebrisSat have been extracted from porous, catcher panels used to gather the debris from the impact event. Thus far, one of the key observations from the collected fragments is that CFRP represents a large fraction of the fragments and that these fragments tend to be thin, flake-like structures or long, needle-like structures; whereas, debris with nearly equal dimensions is less prevalent. As current ballistic-limit models are all developed based upon spherical impacting particles, the experiment has pointed to a missing component in the current approach that must be considered. To begin to understand the implications of this observation, simulations like those shown in Fig. 1 have been performed using cylindrical structures at a representative orbital speed into an externally-insulated, double-wall shield that is representative of shielding of International-Space-Station-visiting vehicles. These simulations have been performed for normal impacts to the surface with three different angles-of-attack (AOA) to capture the effect on the shield performance. This paper documents the simulated shield and the models developed to study the effect of non-spherical fragments, as well as, derives the critical characteristics of CFRP impacting particles for the selected shield as shown in Fig. 2. To assist with the design of the updated debris models, this work summarizes the simulated results into a deployable form for evaluating the relative importance of fragment structures.

Miller, Joshua E.↗

Quantifying Spatiotemporal Variability of Glacier Algal Blooms and the Impact on Surface Albedo in Southwestern Greenland

Albedo reduction due to light-absorbing impurities can substantially enhance ice sheet surface melt by increasing surface absorption of solar energy. Glacier algae have been suggested to play a critical role in darkening the ablation zone in southwestern Greenland. It was very recently found that the Sentinel-3 Ocean and Land Colour Instrument (OLCI) band ratio R709 nm∕R673 nm can characterize the spatial patterns of glacier algal blooms. However, Sentinel-3 was launched in 2016, and current data are only available over three melting seasons (2016–2019). Here, we demonstrate the capability of the MEdium Resolution Imaging Spectrometer (MERIS) for mapping glacier algae from space and extend the quantification of glacier algal blooms over southwestern Greenland back to the period 2004–2011. Several band ratio indices (MERIS chlorophyll a indices and the impurity index) were computed and compared with each other. The results indicate that the MERIS two-band ratio index (2BDA) R709 nm∕R665 nm is very effective in capturing the spatial distribution and temporal dynamics of glacier algal growth on bare ice in July and August. We analyzed the interannual (2004–2011) and summer (July–August) trends of algal distribution and found significant seasonal and interannual increases in glacier algae close to the Jakobshavn Isbrae Glacier and along the middle dark zone between the altitudes of 1200 and 1400 m. Using broadband albedo data from the Moderate Resolution Imaging Spectroradiometer (MODIS), we quantified the impact of glacier algal growth on bare ice albedo, finding a significant correlation between algal development and albedo reduction over algae-abundant areas. Our analysis indicates the strong potential for the satellite algal index to be used to reduce bare ice albedo biases in regional climate model simulations.

surface albedo↗

Overview of Predictive Simulation Capability Development for Crater Evolution and Ejecta in Continuum/Rarefied Flows

As part of the Game Changing Development (GCD) Program, funded by NASA’s Space Technology Mission Directorate (STMD), the development of simulation capability for the prediction of extra-terrestrial Plume Surface Interaction (PSI) environments has been undertaken by the Fluid Dynamics Branch at NASA/MSFC. The Predictive Simulation Capability (PSC) Element is focused on creating simulation capability for the reliable and accurate prediction of PSI in Martian (~650 Pa) and Lunar (vacuum) ambient environments. In addition to the predictive simulation capability, the GCD Program also contains a companion Ground Testing Element for development of focused datasets for validation of predictive capability as well as a Flight-focused Instrumentation Element. The focus of this paper is to provide an overview and a brief status on one area of capability development through this GCD PSI project - capturing the effects of mixed continuum/rarefied flow on crater development and ejecta sheets. This includes both capability enhancements and maturation of the predictive tool, Loci/GGFS, into a production capable tool as well as validation of the tool against PSI data in Martian and Lunar environments. There are six newly developed capabilities that will be production ready by the end of the fiscal year. Newly developed capabilities must first be verified prior to being production ready, and this process includes capability demonstration, solution verification, and performance evaluation. An overview of the newly developed capabilities with respect to several test cases, including cratering simulations of the Apollo Lunar Module, will be presented. Several validation analyses have been performed to validate in Martian and more Lunar-like environments, including simulations of cratering from a subsonic flow test at Planetary Aeolian Lab (PAL) conducted in a Martian-like environment and pre-test cratering predictions of Physics Focused Ground Test (PFGT) tests planned to be performed in Martian-like and more Lunar-like environments. An overview of these validation analyses as it pertains to the capability development will be presented.

Andrew Weaver↗

Experimental Results and Interfacial Lift-off Model Predictions of Critical Heat Flux for Flow Boiling with Subcooled Inlet Conditions – In Preparation for Experiments Onboard the International Space Station

This study investigates critical heat flux (CHF) for subcooled flow boiling of n-Perfluorohexane based on results of pre-launch Earth-gravity Mission Sequence Tests (MSTs) of the Flow Boiling and Condensation Experiment (FBCE), which was launched to the International Space Station (ISS) in August 2021. CHF measurements were made in a rectangular channel having a 2.5 mm by 5 mm cross-section and a 114.6-mm long heated segment. Both single-sided and double-sided heating were tested in vertical upflow in Earth gravity for a variety of inlet conditions. The inlet subcooling was varied in the range of 0.4 – 32.0°C and encompassed both near-saturated and highly subcooled conditions. Experimental trends and high-speed video records were investigated to better understand the mechanism of CHF. Overall trends show CHF increases as flow rate and/or inlet subcooling are increased. Flow features from the events around CHF justify the applicability of the Interfacial Lift-off Model and the determination of limiting criteria for its application. The present experimental data are combined with prior databases for various flow orientations with respect to Earth gravity and microgravity data collected on parabolic flights. Predictions are made using the Interfacial Lift-off Model for this consolidated subcooled-inlet FBCE-CHF database. A heat utility ratio was included in the model to capture the effects of subcooling and corresponding thermodynamic non-equilibrium. An overall mean absolute error of 19.04% indicates good predictive capability of the model for both heating configurations, different gravity environments, and a wide range of inlet subcooling.

flow boiling↗

Overview of Predictive Simulation Capability Development for Crater Evolution and Ejecta in Continuum/Rarefied Flows

As part of the Game Changing Development (GCD) Program funded by NASA’s Space Technology Mission Directorate (STMD), the development of simulation capability for the prediction of extra-terrestrial plume surface interaction (PSI) environments has been undertaken by the Fluid Dynamics Branch at NASA/MSFC. The Predictive Simulation Capability (PSC) Element is focused on creating simulation capability for the reliable and accurate prediction of PSI in Martian (~650 Pa) and Lunar (vacuum) ambient environments. In this paper, an overview and brief status on one area of capability development through this GCD PSI project, capturing the effects of mixed continuum/rarefied flow on crater development and ejecta sheets, is presented with respect to capability enhancements, predictive tool maturation, and validation of the Loci/GGFS tool against PSI data in Martian and Lunar environments. Axisymmetric modeling, overset mesh/moving mesh, and multiple-species mixture modeling capabilities are verified against Loci/CHEM, and a demonstration of the capabilities is presented for the Apollo Lunar Module.

Andrew Weaver↗

A Quantum Algorithm to Simulate Open Quantum Systems

Given the advent of quantum algorithms for a wide array of problems in linear algebra and machine learning, it is important to develop general methods for the simulation of arbitrary (ie non-unitary) operators on quantum hardware. In this talk, we present a novel quantum algorithm based on the quantum singular value transformation (QSVT) to apply an arbitrary operator K to some input state and subsequently estimate the expectation value of some observable. Our construction then immediately yields a route to estimating observables of states undergoing open quantum dynamics, whose effect is captured by a set of non-unitary Kraus operators. Our algorithm succeeds deterministically given the Sz-Nagy dilation, and we provide details on the algorithm's query and gate complexity, numerical verification, and comparisons with prior methods.

Quantum computing↗

Sensitivity Study of Impact Risk Model Results to Thermal Radiation Damage Model for Large Objects

NASA’s Probabilistic Asteroid Impact Risk (PAIR) assessment model assesses the likelihood of potential damage for asteroid impact scenarios. Fast-running models are used to capture the effects of different hazards. This paper looks specifically at local ground damage hazards, including blast overpressure and thermal radiation damage, for large object impact scenarios. A sensitivity study is conducted to determine which parameters, and over what ranges, cause impact risks to become sensitive to thermal damage. Two additional thermal models with different approaches are used for comparison. The study determined the current thermal model is most sensitive to the luminous efficiency parameter that reflects the model’s uncertainty in the amount of energy contributing to the thermal radiation damage. This sensitivity was most apparent for the highest severity damage levels. Comparisons of the three models showed that in addition to sensitivities within the models, the impact risks are also sensitive to the choice of thermal model. The study results were applied to the 2023 PDC hypothetical asteroid impact scenario and parameter ranges of interest determined. At the serious damage level, luminous efficiencies above 0.006 showed a small chance of thermal playing an important role, while luminous efficiencies above 0.0008 led to thermal playing a significant role at the unsurvivable damage severity level. Study results are used to identify key areas where additional model refinement and better knowledge of asteroid properties may be important for improving damage estimates.

SMD↗

Sensitivity Study of Impact Risk Model Results to Thermal Radiation Damage Model for Large Objects

NASA’s Probabilistic Asteroid Impact Risk (PAIR) assessment model assesses the likelihood of potential damage for asteroid impact scenarios. Fast-running models are used to capture the effects of different hazards. This paper looks specifically at local ground damage hazards, including blast overpressure and thermal radiation damage, for large object impact scenarios. A sensitivity study is conducted to determine which parameters, and over what ranges, cause impact risks to become sensitive to thermal damage. Two additional thermal models with different approaches are used for comparison. The study determined the current thermal model is most sensitive to the luminous efficiency parameter that reflects the model’s uncertainty in the amount of energy contributing to the thermal radiation damage. This sensitivity was most apparent for the highest severity damage levels. Comparisons of the three models showed that in addition to sensitivities within the models, the impact risks are also sensitive to the choice of thermal model. The study results were applied to the 2023 Planetary Defense Conference hypothetical asteroid impact scenario and parameter ranges of interest determined. At the serious damage level, luminous efficiencies above 0.006 showed a small chance of thermal playing an important role, while luminous efficiencies above 0.0008 led to thermal playing a significant role at the unsurvivable damage severity level. Study results are used to identify key areas where additional model refinement and better knowledge of asteroid properties may be important for improving damage estimates.

SMD↗

Learjet 25D Jet Noise Flyover Measurements: Comparisons with Scale-Model Data

Continued interest in commercial supersonic flight has highlighted the need for accurate jet-noise predictions as jet noise is expected to be a dominant noise source for aircraft takeoff conditions. The current study compares the acoustic spectra obtained from a scale-model investigation to that from a Learjet 25D flyover test. Reasonable agreement was achieved between the scale-model and flight data in both peak level and frequency when the physical scale factor for the scale-model was increased by roughly 6%. The peak perceived noise levels (PNL) for the flight data were between 1.29 dB and 1.65 dB higher than those for the scale model. The roll-off of PNL with time for large emission angles was greater for the flight data than for the scale-model data. Using a distributed source model for shear-layer-refraction corrections to the scale-model data slightly improved comparisons to flight data at low frequencies for emission angles near 70° and between 110° and 130°. Distributed source models had no impact on the scale-model spectra near the peak jet-noise angle. Applying a stretching factor to the distributed source models to capture the effects of a flight stream had a very limited impact on the computed spectra.

Acoustics↗