Cryogenic Fluid Management Portfolio Project EXPL-05: NASA CFM Portfolio Project - 2023 Accomplishments and Highlights Progress on Flight Demos and Large CFM Demonstration (LCD)
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The CFM-ID 4.0 web server (https://cfmid.wishartlab.com) is an online tool for predicting, annotating and interpreting tandem mass (MS/MS) spectra of small molecules. It is specifically designed to assist researchers pursuing studies in metabolomics, exposomics and analytical chemistry. More specifically, CFM-ID 4.0 supports the: 1) prediction of electrospray ionization quadrupole time-of-flight tandem mass spectra (ESI-QTOF-MS/MS) for small molecules over multiple collision energies (10 eV, 20 eV, and 40 eV); 2) annotation of ESI-QTOF-MS/MS spectra given the structure of the compound; and 3) identification of a small molecule that generated a given ESI-QTOF-MS/MS spectrum at one or more collision energies. The CFM-ID 4.0 web server makes use of a substantially improved MS fragmentation algorithm, a much larger database of experimental and in silico predicted MS/MS spectra and improved scoring methods to offer more accurate MS/MS spectral prediction and MS/MS-based compound identification. Compared to earlier versions of CFM-ID, this new version has an MS/MS spectral prediction performance that is ~22% better and a compound identification accuracy that is ~35% better on a standard (CASMI 2016) testing dataset. CFM-ID 4.0 also features a neutral loss function that allows users to identify similar or substituent compounds where no match can be found using CFM-ID’s regular MS/MS-to-compound identification utility. Finally, the CFM-ID 4.0 web server now offers a much more refined user interface that is easier to use, supports molecular formula identification (from MS/MS data), provides more interactively viewable data (including proposed fragment ion structures) and displays MS mirror plots for comparing predicted with observed MS/MS spectra. These improvements should make CFM-ID 4.0 much more useful to the community and should make small molecule identification much easier, faster, and more accurate.
In the field of metabolomics, mass spectrometry (MS) is the method most commonly used for identifying and annotating metabolites. As this typically involves matching a given MS spectrum against an experimentally acquired reference spectral library, this approach is limited by the coverage and size of such libraries (which typically number in the thousands). These experimental libraries can be greatly extended by predicting the MS spectra of known chemical structures (which number in the millions) to create computational reference spectral libraries. To facilitate the generation of predicted spectral reference libraries we developed CFM-ID, a computer program that can accurately predict ESI-MS/MS spectrum for a given compound structure. CFM-ID is one of the best-performing methods for compound-to-mass-spectrum prediction, and also one of the top tools for in silico mass-spectrum-to-compound identification. This work improves CFM-ID’s ability to predict ESI-MS/MS spectra from compounds by: (1) learning parameters from features based on the molecular topology, (2) adding a new approach to ring cleavage that models such cleavage as a sequence of simple chemical bond dissociations and (3) expanding its hand-written rule-based predictor to cover more chemical classes, including acylcarnitines, acylcholines, flavonols, flavones, flavanones, and flavonoid glycosides. We demonstrate that this new version of CFM-ID (version 4.0) is significantly more accurate than previous CFM-ID versions, in terms of both EI-MS/MS spectral prediction and compound identification. CFM-ID 4.0 is available at http://cfmid4.wishartlab.com/ as a webservice and docker images can be downloaded at https://hub.docker.com/r/wishartlab/cfmid
Several technological capabilities must be developed to realize the vision of the Space Exploration Initiative (SEI). Cryogenic fluid management (CFM) is one technology area common to virtually every space transportation propulsion concept envisioned. The physics of storage, supply, transfer, and handling of subcritical cryogenic fluids in the reduced gravity environment of space present fundamental challenges. The CFM state of the art relative to future mission requirements is reviewed and associated technology challenges are outlined.
This paper presents an overview of the state-of-the-art two-phase CFD models that have been developed for various propellant tank storage and transfer operations in 1g, partial gravity and microgravity. The models are developed in the framework of the industry standard ANSYS/Fluent CFD code, the capabilities of which have been significantly enhanced and customized through incorporation of unique submodels via User Defined Functions (UDF)s to satisfy the requirements of its intended variable gravity Cryogenic Fluid Management (CFM) applications. These models/submodels have been validated against experimental data that cross spatial scales, fluid types, and gravity levels in order to properly anchor the models’ physical and numerical fidelity. The CFM application/processes that have been modeled include tank self-pressurization, tank autogenous pressurization, tank pressure control using both subcooled jet mixing and droplet spray injection mechanisms, tank chilldown/filling, tank drainage, tank slosh for both volatile and non-volatile fluids. The strength and shortcomings of the two-phase models for each application is highlighted and discussed briefly.
This paper presents an overview of the state-of-the-art two-phase CFD models that have been developed for various propellant tank storage and transfer operations in 1g, partial gravity, and microgravity. The models are developed in the framework of the industry standard ANSYS/Fluent CFD code, the capabilities of which have been significantly enhanced and customized through the incorporation of unique submodels via User Defined Functions (UDF)s to satisfy the requirements of its intended variable gravity Cryogenic Fluid Management (CFM) applications. These models/submodels have been validated against experimental data that cross spatial scales, fluid types, and gravity levels in order to properly anchor the models’ physical and numerical fidelity. The CFM application/processes that have been modeled include tank self-pressurization, tank autogenous pressurization, tank pressure control using both subcooled jet mixing and droplet spray injection mechanisms, tank chilldown/filling, tank drainage, tank slosh for both volatile and non-volatile fluids. The strength and shortcomings of the two-phase models for each application are highlighted and discussed briefly.
It is argued from the central limit theorem that the uncertainty in model predicted changes of the ozone column density is best represented by a normal probability density distribution. This conclusion is validated by comparison with a probability distribution generated by a Monte Carlo technique. In the case of the CFM-induced ozone depletion, and based on the estimated uncertainties in the reaction rate coefficients alone the relative mean standard deviation of this normal distribution is estimated to be 0.29.
The Multipurpose Hydrogen Test Bed (MHTB) Test Readiness Review (TRR), in preparation for upcoming thermodynamic vent system testing with LN2 (an LO2 simulant), was conducted on Aug 10 with no significant concerns or open action items. The 21 day test series, designed to evaluate the spray bar mixer/vent system concept suitability for zero-g operation began on August 19. The testing is progressing very well and results indicate that the Moog latching valve is more effective than the Castor solenoid valve in reducing pressure during the vent/mixing cycles. Testing with self-pressurization is expected to be completed on September 3 and testing with helium pressurization will be initiated on September 4 or 5. Additional activities during first half of August included coordination of Notification of Intent (NOI) to propose letters involving CFM in response to the HR&T BAA for Extramural Proposals.
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Examples of feedback among radiative, chemical and dynamical processes are discussed. The characteristics of the two dimensional (2-D) and three dimensional (3-D) models used in stratospheric ozone studies are discussed. The status of these multidimensional atmospheric photochemical models, their current capabilities and limitations, and possible impact on the chlorofluoromethane problem are presented. Requirements, techniques and problems of the parameterization of transport in 3-D models are described, the observational needs of multidimensional models are presented, and a summary is provided.
The development of a test bed tank and system for evaluating cryogenic fluid management technologies in a simulated upper stage liquid hydrogen tank is covered. The tank is 10 ft long and is 10 ft in diameter, and is an ASME certified tank constructed of 5083 aluminum. The tank is insulated with a combination of sprayed on foam insulation, covered by 45 layers of double aluminized mylar separated by dacron net. The mylar is applied by a continuous wrap system adapted from commercial applications, and incorporates variable spacing between the mylar to provide more space between those layers having a high delta temperature, which minimizes heat leak. It also incorporates a unique venting system which uses fewer large holes in the mylar rather than the multitude of small holes used conventionally. This significantly reduces radiation heat transfer. The test bed consists of an existing vacuum chamber at MSFC, the test bed tank and its thermal control system, and a thermal shroud (which may be heated) surrounding the tank. Provisions are made in the tank and chamber for inclusion of a variety of cryogenic fluid management experiments.
A very extensive set of gaseous- and particulate-emissions data from an in service commercial aircraft engine was obtained by a team of researchers from NASA, the Environmental Protection Agency, and the Department of Defense. The program was led and organized by Dr. Chowen Wey of the UEET Project Office at the NASA Glenn Research Center and was dubbed the Aircraft Particle Emissions eXperiment (APEX). Testing was done at the NASA Dryden Flight Research Center. The main object of APEX was to identify particulate emissions from commercial-aircraft engines.
Brief overview of cryogenic events including pressurization and modeling.
NASA, the US industry, and international partners are crafting frameworks to enable sustaining lunar missions. The ongoing programs, led by the agency, and prominent industry players, encompass plans for the sustained use of cryogenic propellants in lunar landers and in-space propellant refueling depots. NASA’s proactive funding initiatives have fueled the advancement of predictive computational models tailored to enhance the storage and transfer of cryogenic propellant. This paper aims to spotlight the latest advancements in this arena and delve into the collaborative efforts surrounding predictive model development within internal NASA programs as well as current and previous collaborations with industry and international partners. The paper presents an overview of recent advancements in cryogenic fluid management model development, along with their correlation with recent microgravity and large-scale cryogenic ground tests. The tests include key experiments such as the ISS Zero-Boil-Off Tank (ZBOT) series of experiments and the (Robotic Refueling Mission 3) RRM3 test during which liquid methane was stored on-orbit for an extended period of five months. The paper also highlights the anchoring of propellant tank pressurized drain tests involving sloshing that were conducted with liquid methane propellant during the Apollo/Saturn Era. Additionally, the paper discusses model anchoring against more recent sloshing tests carried out with liquid hydrogen propellant. Notable large-scale tests, such as a liquid oxygen propellant transfer test conducted by SpaceX were also used to help correlate a two-phase propellant transfer model using the valuable data measured during the test. The paper further showcases model correlations against a substantial oxygen liquefaction test undertaken by NASA to validate In-Situ-Resource-Utilization (ISRU) technologies that will prove pivotal for a sustained lunar presence.
Advancement in Cryogenic Fluid Management (CFM) Technologies is essential for achieving NASA's future long duration missions. Propulsion systems utilizing cryogens are necessary to achieve mission success. Current State Of the Art (SOA) CFM technologies enable cryogenic propellants to be stored for several hours. However, some envisioned mission architectures require cryogens to be stored for two years or longer. The fundamental roles of CFM technologies are long term storage of cryogens, propellant tank pressure control and propellant delivery. In the presence of heat, the cryogens will "boil-off" over time resulting in excessive pressure buildup, off-nominal propellant conditions, and propellant loss. To achieve long term storage and tank pressure control, the CFM elements will intercept and/or remove any heat from the propulsion system. All functions are required to perform both with and without the presence of a gravitational field. Which CFM technologies are required is a function of the cryogens used, mission architecture, vehicle design and propellant tank size. To enable NASA's crewed mission to the Martian surface, a total of seventeen CFM technologies have been identified to support an In-Space Stage and a Lander/Ascent Vehicle. Recognizing that FY2020 includes a Decision Point regarding the In-Space Stage Architecture, a set of CFM Technology Development Roadmaps have been created identifying the current Technology Readiness Level (TRL) of each element, current technology "gaps", and existing technology development efforts. The roadmaps include a methodical approach and schedule to achieve a flight demonstration in FY2023, hence maturing CFM technologies to TRL 7 for infusion into the In-Space Stage Preliminary Design.
The maturation of Cryogenic Fluid Management (CFM) Technologies is essential for achieving NASA's future long duration missions. Propulsion systems utilizing cryogens are necessary to achieve NASA's exploration missions to the moon, Mars, and beyond. Current State Of the Art (SOA) CFM technologies enable cryogenic propellants to be stored for several hours prior to their use. However, some envisioned mission architectures require that cryogens to be stored for two years or longer. The fundamental roles of CFM technologies are long term storage of cryogens, propellant tank pressure control and propellant delivery. In the presence of heat, the cryogens will "boil-off" over time resulting in excessive pressure buildup, off-nominal propellant conditions for engine consumption, and propellant loss. To achieve long term storage and tank pressure control, the CFM elements will intercept and/or remove any heat from the propulsion system. All functions are required to be performed both with and without the presence of a gravitational field. Which CFM technologies are required is a function of the cryogens used, mission architecture, vehicle design and propellant tank size. To enable NASA's crewed missions beyond Low Earth Orbit, a total of twenty-seven CFM technologies have been identified to support various In-Space Stages and Lander/Ascent Vehicles. A set of CFM Technology Development Roadmaps have been created identifying the current Technology Readiness Level (TRL) of each element, current technology "gaps", and existing technology development efforts. The roadmaps include a methodical approach and schedule to achieve a flight demonstration, hence maturing CFM technologies to TRL 6/7 for infusion into the NASA's exploration elements. Additionally, a survey of the aerospace industry was completed to understand their views on the various technologies and how they would be infused. This does not cover all possible technologies, but rather those that are of interest to NASA specifically.
Cooperative fault management (CFM) is designed herein to control different types of renewable energy resources cooperatively during electrical faults. This paper studies systems with a high penetration of photovoltaic (PV) energy and wind energy. First, CFM leverages power converters of PV farms to boost the ride-through capability of nearby doubly-fed induction generators (DFIGs). By controlling PV farms’ output voltages to change smoothly during both fault initiation and fault clearance, the widely used crowbar in DFIGs is less likely to be activated. Crowbar activation adversely makes DFIGs lose controllability and absorb reactive power. The second contribution is the development of a software-defined CFM controller and a controller in-the-loop demonstration of the real-time performance of this optimization-based CFM. CFM capitalizes on distributed optimization formulation to enable flexibility, plug-and-play, and privacy-preserving. Computation time, however, is a major concern for optimization-based dynamics control. Here, real-time controller-in-the-loop simulation results show optimization-based CFM can output reference values around 60 ms and is quick enough for dynamic control.
The Contributing Factor Map (CFM) is a visual representation of a taxonomy of factors influencing human health and performance in space. This presentation will give an overview of its development and its structure. It will describe various uses of the CFM that can support researchers working within the Human Research Program (HRP) Architecture of Evidence-Risk-Gap-Task-Deliverable. For example, during the Risk phase, the CFM can be used as a "menu" to help formulate a qualitative model of the factors contributing to specific consequences of concern. It provides a reference set of factors from across the operational, vehicle design, and human domains that otherwise might not be considered if approaching a risk from a specific domain perspective. Using the CFM as a reference can increase awareness of potential cross-disciplinary collaborations for overall risk mitigation. The CFM can also be used as a framework for identifying gaps in knowledge about a risk. This identification can support the subsequent development of gaps and tasks comprising the research plan aimed at risk mitigation. Examples of these types of applications of the CFM will be discussed and information on the support available to researchers in using it will be provided.