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At least 523 records · Page 29

Overview of the NASA Terrestrial Environments Support Role: Data and Applications

This presentation focuses on the terrestrial environment component of the Natural Environments Branch’s (NEB’s) support role and highlights the instrumentation and data sources used, how the data are quality controlled and archived, and the analyses and use-cases of these datasets. A detailed overview is provided about some individual data sources that are used by the branch, which includes a network of instruments (e.g., wind towers, balloons, and profilers) and models, such as the Earth Global Reference Atmospheric Model (Earth-GRAM). Additionally, the data archival and quality control processes that maintain the high-quality climatological datasets from these sources are discussed, as are the implemented and pending updates to this process. Examples of the different applications for these datasets are presented to showcase the analytical and operational capabilities of the NEB and demonstrate the culmination of the entire process. This includes the Range Reference Atmospheres created and maintained by the NEB, sea-state analyses for crewed return, certification of observation systems for space flight, and the day-of-launch support process. The NEB at NASA Marshall Space Flight Center (MSFC) supports the NASA Engineering Directorate (ED) and Exploration Systems Development Mission Directorate (ESDMD) by providing the necessary environmental constraints to facilitate the safe design and operation of assets required for space travel. This includes, but is not limited to, the environmental considerations for assets residing at the launch sites, temporarily stationed at a launch site, traversing the [extra-]terrestrial atmosphere and open space, and arriving at their destination. As such, the Terrestrial and Planetary Environments Team within the NEB is but a part of the whole, delegated to quantify the environment that assets may encounter whilst on Earth and within its atmosphere. However, nearly all ESDMD assets are subjected to terrestrial conditions, which cover a diverse range of meteorological regimes and extremes. The team also supports day-of-launch operations for the Space Launch System (SLS), providing real-time monitoring of the winds and thermodynamics along the launch path using an amalgamation of observed, remotely sensed, and modeled output.

Systems Engineering↗

Development of the Orion Life-Support Integration Facility (OLIF)

Testing the life support hardware of a vehicle that is going to take humans beyond low-Earth orbit (LEO) in conditions similar to space is crucial. The Orion Life-Support Integration Facility (OLIF) at NASA Johnson Space Center (JSC) was designed and built to test the Orion vehicle’s hardware and software as integrated systems to provide a complete Environmental Control and Life Support System (ECLSS) system-level qualification. The existing 11 Foot human rated vacuum chamber has been adapted to accommodate and integrate various qualification and flight like components of the Orion vehicle’s Air Revitalization System (ARS), Pressure Control System (PCS), Active Thermal Control System (ATCS) and the Orion Crew Survival System Suits (OCSS). The ultimate goal was to create an analog testbed that could safely support up to four test subjects in open “shirt-sleeve” or closed suit loop configurations and simulate Orion Cabin conditions. This integrated hardware/software ARS and PCS will help identify any technical issues that should be addressed prior to the Artemis-2 mission. This paper will discuss the history of Orion ECLSS hardware development testing in the 11 Foot Chamber, the challenge of integrating flight hardware and software control systems, and the capabilities that make it a unique, world class facility for NASA. It will provide an overview of past and future testing, and the lessons learned along the way.

Peter A Masi↗

Model implementation for dynamic computation of system cost for advanced life support

Life support system designs for long-duration space missions have a multitude of requirements drivers, such as mission objectives, political considerations, cost, crew wellness, inherent mission attributes, as well as many other influences. Evaluation of requirements satisfaction can be difficult, particularly at an early stage of mission design. Because launch cost is a critical factor and relatively easy to quantify, it is a point of focus in early mission design. The method used to determine launch cost influences the accuracy of the estimate. This paper discusses the appropriateness of dynamic mission simulation in estimating the launch cost of a life support system. This paper also provides an abbreviated example of a dynamic simulation life support model and possible ways in which such a model might be utilized for design improvement. c2004 COSPAR. Published by Elsevier Ltd. All rights reserved.

NASA Discipline Life Support Systems↗

The MELISSA pilot plant facility as as integration test-bed for advanced life support systems

The different advances in the Micro Ecological Life Support System Alternative project (MELISSA), fostered and coordinated by the European Space Agency, as well as in other associated technologies, are integrated and demonstrated in the MELISSA Pilot Plant laboratory. During the first period of operation, the definition of the different compartments at an individual basis has been achieved, and the complete facility is being re-designed to face a new period of integration of all these compartments. The final objective is to demonstrate the potentiality of biological systems such as MELISSA as life support systems. The facility will also serve as a test bed to study the robustness and stability of the continuous operation of a complex biological system. This includes testing of the associated instrumentation and control for a safe operation, characterization of the chemical and microbial safety of the system, as well as tracking the genetic stability of the microbial strains used. The new period is envisaged as a contribution to the further development of more complete biological life support systems for long-term manned missions, that should be better defined from the knowledge to be gained from this integration phase. This contribution summarizes the current status of the Pilot Plant and the planned steps for the new period. c2004 COSPAR. Published by Elsevier Ltd. All rights reserved.

Waste Management/instrumentation/methods↗

Basin-Scale Structural Features Database: Spatial Datasets to Support Carbon Storage Resource Assessments

Presentation slides on "Basin-Scale Structural Features Database: Spatial Datasets to Support Carbon Storage Resource Assessments" for CCUS 2025 Annual Meeting. The Basin-Scale Structural Features database contains a series of basin-scale spatial datasets representing structural features, including faults, fractures, folds, and earthquakes. Designed to support carbon storage feasibility and resources assessments for Carbon Capture and Storage (CCS) projects, the database leverages publicly available data resources from authoritative sources (e.g. US Geological Survey, State Geologic Surveys), and aims to help users better understand basin-scale structural features, as well as potential data gaps in areas with sparse information.

basin scale↗

Support size regulated ruthenium-sulfoacid-nitrogen sites intensify cellulose hydrogenolysis to 1,2-propylene glycol

Rational design of metal-acid-base multifunctional catalysts for upgrading cellulose to 1,2-propylene glycol (1,2-PG) is of great significance for building a sustainable world. However, it is time-consuming and tedious to regulate metal-acid-base sites to balance major reactions to render a high 1,2-PG yield. We herein report support size simultaneously regulated ruthenium-sulfoacid-nitrogen (Ru–SO 3 H–N) sites for cellulose hydrogenolysis to high yield 1,2-PG. Originated from the depolymerization and reassembly of zinc-1,3,5-benzenetricarboxylic acid (ZnBTC) fiber with zeolitic imidazolate framework (ZIF-8) in water, 2-methylimidazole infiltrated nanorod (ZnBTC(mIM)) with a varied aspect ratio was fabricated by varying the feed ratio of ZIF-8/ZnBTC. Upon being pyrolyzed, sulfonated and impregnated with Ru ions, the supported sites were tailored in terms of Ru single-atom/nanocluster ratio, SO 3 H acidity and N basicity. Further, the elaborately fabricated catalyst delivers 32.3% yield of 1,2-PG, corresponding to a high productivity of 67.71 mol h -1 g Ru -1 and a large turnover number of 34193, two and three orders of magnitude higher than those by using other Ru-containing catalytic systems for cellulose hydrogenolysis. The excellent performance can be attributed to optimized electronic and molecular structure of Ru–SO 3 H–N sites that can improve rate-determining cellulose hydrolysis/fructose hydrogenolysis, pivotal glucose isomerization with others to proceed at a matched rate. This study opens a new avenue to facilely tailor the metal-acid-base sites by rational design of size controlled supporting matrix.

1,2-Propylene glycol↗

Energy, power, and infrastructure demands from electrifying airport ground support equipment at United States airports

As the airline industry seeks to reduce costs and transition to clean energy, electric ground support equipment is emerging as a favorable option. The integration of electric ground support equipment into airport operations requires careful planning for vehicle deployment, charging infrastructure, and grid impacts. We develop a flexible, bottom-up modeling framework to assess energy and infrastructure needs across more than 300 U.S. airports. Our analysis estimates site-specific power and energy demand, equipment counts by type, charger requirements, and costs. Here we quantify the magnitude of new electrical loads created by the electrification of airport ground support equipment, finding that peak power demand at the largest airports can reach up to 20 megawatts, with annual electricity consumption approaching 51,000 megawatt-hours. We further show that behind-the-meter battery energy storage systems and solar photovoltaic systems can reduce peak load and lower total system costs by as much as 10 million dollars.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Optimization-Based Dynamic Voltage Support of Microgrids Using Energy Storage Systems

A microgrid network is characterized by a high R/X ratio, making the voltage more sensitive to active power changes compared to bulk power systems, where the voltage is regulated primarily by reactive power. Due to its sensitivity, voltage control approaches for microgrids should also consider the active power input coupling, making it very different from conventional power systems. Additionally, as the energy costs associated with active and reactive powers are different and the operational conditions of microgrids connected to active distribution systems vary over time, the ideal controller to provide voltage support must be flexible enough to handle these technical and operational constraints. This paper proposes a model predictive control approach to provide dynamic voltage support using energy storage systems. This approach uses a simplified predictive model of the system to solve the model predictive control problem. By proper selection of model predictive control weighting parameters, the quality of service provided can be adjusted to achieve the desired performance. A simulation study in MATLAB/Simulink validates the proposed approach for the Cordova, Alaska microgrid. Results show that the performance of the voltage support can be adjusted depending on the choice of weight and constraints of the controller.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Regenerative Life Support Systems Test Bed performance - Lettuce crop characterization

Two crops of lettuce (Lactuca sativa cv. Waldmann's Green) were grown in the Regenerative Life Support Systems (RLSS) Test Bed at NASA's Johnson Space Center. The RLSS Test Bed is an atmospherically closed, controlled environment facility for the evaluation of regenerative life support systems using higher plants. The chamber encloses 10.6 m 2 of growth area under cool-white fluorescent lamps. Lettuce was double seeded in 480 pots, each containing about 250 cm 3 of calcined-clay substrate. Each pot was irrigated with half-strength Hoagland's nutrient solution at an average total applied amount of 2.5 and 1.8 liters pot -1 , respectively, over each of the two 30-day crop tests. Average environmental and cultural conditions during both tests were 23°C air temperature, 72% relative humidity, 1000 ppm carbon dioxide (CO 2 ), 16h light/8h dark photoperiod, and 356 μmol m -2 s -1 photosynthetic photon flux. After 30 days from seeding, average yield (g pot -1 ) for the first and second crop tests were 72 and 49 edible (shoot) fresh mass, 3.65 and 2.56 edible dry mass, and 0.44 and 0.45 inedible (root) dry mass, respectively. Averaging over both crop tests, the test bed met the requirements of 2.1 person-days of oxygen production, 2.4 person days of CO 2 removal and 129 person days of potential potable water production. The satisfactory growth of both crops demonstrates the potential of lettuce for air revitalization and water production in a controlled ecological life support system. Differences in crop performance resulting from engineering system effects provides evidence of the resilience of biological systems.

Life support systems↗

Switching skeletons: hydrostatic support in molting crabs

Skeletal support systems are essential for support, movement, muscular antagonism, and locomotion. Crustaceans shed their rigid exoskeleton at each molt yet are still capable of forceful movement. We hypothesize that the soft water-inflated body of newly molted crabs may rely on a hydrostatic skeleton, similar to that of worms and polyps. We measured internal hydrostatic pressure and the force exerted during claw adduction and observed a strong correlation between force and hydrostatic pressure, consistent with hydrostatic skeletal support. This alternation between the two basic skeletal types may be widespread among arthropods.

Non-NASA Center↗

(abstract) Generic Modeling of a Life Support System for Process Technology Comparisons

This paper describes a simulation model called the Life Support Systems Analysis Simulation Tool (LiSSA-ST), the spreadsheet program called the Life Support Systems Analysis Trade Tool (LiSSA-TT), and the Generic Modular Flow Schematic (GMFS) modeling technique. Results of using the LiSSA-ST and the LiSSA-TT will be presented for comparing life support systems and process technology options for a Lunar Base and a Mars Exploration Mission.

life support system long-duration missions simulat↗

Diverse Redundant Systems for Reliable Space Life Support

Reliable life support systems are required for deep space missions. The probability of a fatal life support failure should be less than one in a thousand in a multi-year mission. It is far too expensive to develop a single system with such high reliability. Using three redundant units would require only that each have a failure probability of one in ten over the mission. Since the system development cost is inverse to the failure probability, this would cut cost by a factor of one hundred. Using replaceable subsystems instead of full systems would further cut cost. Using full sets of replaceable components improves reliability more than using complete systems as spares, since a set of components could repair many different failures instead of just one. Replaceable components would require more tools, space, and planning than full systems or replaceable subsystems. However, identical system redundancy cannot be relied on in practice. Common cause failures can disable all the identical redundant systems. Typical levels of common cause failures will defeat redundancy greater than two. Diverse redundant systems are required for reliable space life support. Three, four, or five diverse redundant systems could be needed for sufficient reliability. One system with lower level repair could be substituted for two diverse systems to save cost.

life support↗

Autonomous Task Management and Decision Support Tools

For some time aircraft manufacturers and researchers have been pursuing mechanisms for reducing crew workload and providing better decision support to the pilots, especially during non-normal situations. Some previous attempts to develop task managers or pilot decision support tools have not resulted in robust and fully functional systems. However, the increasing sophistication of sensors and automated reasoners, and the exponential surge in the amount of digital data that is now available create a ripe environment for the development of a robust, dynamic, task manager and decision support tool that is context sensitive and integrates information from a wide array of on-board and off aircraft sourcesa tool that monitors systems and the overall flight situation, anticipates information needs, prioritizes tasks appropriately, keeps pilots well informed, and is nimble and able to adapt to changing circumstances. This presentation will discuss the many significant challenges and issues associated with the development and functionality of such a system for use on the aircraft flight deck.

decision support↗

Need for Cost Optimization of Space Life Support Systems

As the nation plans manned missions that go far beyond Earth orbit to Mars, there is an urgent need for a robust, disciplined systems engineering methodology that can identify an optimized Environmental Control and Life Support (ECLSS) architecture for long duration deep space missions. But unlike the previously used Equivalent System Mass (ESM), the method must be inclusive of all driving parameters and emphasize the economic analysis of life support system design. The key parameter for this analysis is Life Cycle Cost (LCC). LCC takes into account the cost for development and qualification of the system, launch costs, operational costs, maintenance costs and all other relevant and associated costs. Additionally, an effective methodology must consider system technical performance, safety, reliability, maintainability, crew time, and other factors that could affect the overall merit of the life support system.

Costs↗

Autonomous, Context-Sensitive, Task Management Systems and Decision Support Tools I: Human-Autonomy Teaming Fundamentals and State of the Art

Recent advances in artificial intelligence, machine learning, data mining and extraction, and especially in sensor technology have resulted in the availability of a vast amount of digital data and information and the development of advanced automated reasoners. This creates the opportunity for the development of a robust dynamic task manager and decision support tool that is context sensitive and integrates information from a wide array of on-board and off aircraft sourcesa tool that monitors systems and the overall flight situation, anticipates information needs, prioritizes tasks appropriately, keeps pilots well informed, and is nimble and able to adapt to changing circumstances. This is the first of two companion reports exploring issues associated with autonomous, context-sensitive, task management and decision support tools. In the first report, we explore fundamental issues associated with the development of an integrated, dynamic, flight information and automation management system. We discuss human factors issues pertaining to information automation and review the current state of the art of pilot information management and decision support tools. We also explore how effective human-human team behavior and expectations could be extended to teams involving humans and automation or autonomous systems.

context-sensitive↗

Clinical Decision Support - Concepts of Operation

We are entering a new era in space exploration to return to the moon and explore Mars. These ambitious goals will require significant changes to in-flight and habitat medical care due to constraints on mass, volume, power, crew time and medical evacuation capabilities. These constraints make it absolutely necessary to develop transformative solutions using new technologies. The Exploration Medical Capability (ExMC) Element of the Human Research Program (HRP) pushes the boundary of space medical systems to advance the care of astronauts on future exploration missions beyond low Earth orbit by identifying and testing next-generation medical care and crew health maintenance technologies. The Clinical Decision Support (CDS) project addresses the gap Medical-701 within the Inflight Medical Conditions risk: Enhance medical capabilities within an exploration medical system. For long-duration, deep space missions, computational and data resources will play an important role in maintaining crew health, wellness and performance where the crew will need to be more self-reliant. The aim of the CDS project is to develop and provide recommended requirements for an in-vehicle CDSS that acts as an assistant for delivering optimal health and performance and medical care during exploration missions. The CDSS is envisioned as a software-based tool that will augment a crewmembers’ knowledge, skills and abilities to assist in decision-making and crew health and performance (CHP) management thus increasing CHP systems capabilities. The human interface will be context aware and lessen the cognitive load to assimilate and use information as well as combine large disparate data sets in such a manner that provides the crew with actionable insight to decisions related to crew medical, health and performance management. Crew autonomy will be provided through a CDS that presents knowledge and data in a context aware manner to augment a crew members’ knowledge, skills and abilities during the process of observation, orientation, decisions and action. The CDS project addresses the need for crew members to operate independently during long duration space exploration missions that require medical Levels of Care (LoC) V, the highest level specified by NASA-STD-3001 and described in more detail by the ExMC interpretation of LoC document (NASA/TM-2017-219290), where significant changes to in-flight and habitat medical care necessitate increasing crew autonomy in decision making and task performance. The CDS project will develop and test a series of iterative and increasingly more complex system prototypes. These annual demonstrations of the data system integration with the crew health and performance domain will inform exploration medical system requirements for an on-board Clinical Decision Support System (CDSS) through a series of use cases that guide CDS prototype functionality. CDS concepts are based on ExMC Concept of Operations documents (presented separately) and will highlight architecture extensibility to other more complex analyses and tests using core crew health and performance integrated data management, processing and visualization capabilities. This approach also establishes how externally developed analyses and approaches could be added to expand a clinical decision support system and thus highlight how a comprehensive system can be commercially and/or globally developed. The CDS project will build upon the concept of an integrated data management approach based on the Medical Data Architecture (MDA) project to more fully address challenges associated with in-flight and habitat medical, health and performance care due to constraints on mass, volume, power, crew time and medical evacuation capabilities required for medical LoC V. These requirements will be derived through systems engineering approaches and software prototype developments over the course of the multi-year CDS project to address crew health and performance decision-making and task performance, often autonomously executed by the crew, in a manner that is consistent with the appropriate medical level of care for the mission. This presentation will provide an overview of the vision for the CDS project and highlight the initial accomplishments in project planning, implementation and requirements identification in fiscal year 2020.

clinical decision support↗

Clinical Decision Support - Overview and Update

We are entering a new era in space exploration to return to the moon and explore Mars. These ambitious goals will require significant changes to in-flight and habitat medical care due to constraints on mass, volume, power, crew time and medical evacuation capabilities. These constraints make it absolutely necessary to develop transformative solutions using new technologies. The Exploration Medical Capability (ExMC) Element of the Human Research Program (HRP) pushes the boundary of space medical systems to advance the care of astronauts on future exploration missions beyond low Earth orbit by identifying and testing next-generation medical care and crew health maintenance technologies. The Clinical Decision Support (CDS) project addresses the gap Medical-701 within the Inflight Medical Conditions risk: Enhance medical capabilities within an exploration medical system. For long-duration, deep space missions, computational and data resources will play an important role in maintaining crew health, wellness and performance where the crew will need to be more self-reliant. The aim of the CDS project is to develop and provide recommended requirements for an in-vehicle CDSS that acts as an assistant for delivering optimal health and performance and medical care during exploration missions. The CDSS is envisioned as a software-based tool that will augment a crewmembers’ knowledge, skills and abilities to assist in decision-making and crew health and performance (CHP) management thus increasing CHP systems capabilities. The human interface will be context aware and lessen the cognitive load to assimilate and use information as well as combine large disparate data sets in such a manner that provides the crew with actionable insight to decisions related to crew medical, health and performance management. Crew autonomy will be provided through a CDS that presents knowledge and data in a context aware manner to augment a crew members’ knowledge, skills and abilities during the process of observation, orientation, decisions and action. The CDS project addresses the need for crew members to operate independently during long duration space exploration missions that require medical Levels of Care (LoC) V, the highest level specified by NASA-STD-3001 and described in more detail by the ExMC interpretation of LoC document (NASA/TM-2017-219290), where significant changes to in-flight and habitat medical care necessitate increasing crew autonomy in decision making and task performance. The CDS project will develop and test a series of iterative and increasingly more complex system prototypes. These annual demonstrations of the data system integration with the crew health and performance domain will inform exploration medical system requirements for an on-board Clinical Decision Support System (CDSS) through a series of use cases that guide CDS prototype functionality. CDS concepts are based on ExMC Concept of Operations documents (presented separately) and will highlight architecture extensibility to other more complex analyses and tests using core crew health and performance integrated data management, processing and visualization capabilities. This approach also establishes how externally developed analyses and approaches could be added to expand a clinical decision support system and thus highlight how a comprehensive system can be commercially and/or globally developed. The CDS project will build upon the concept of an integrated data management approach based on the Medical Data Architecture (MDA) project to more fully address challenges associated with in-flight and habitat medical, health and performance care due to constraints on mass, volume, power, crew time and medical evacuation capabilities required for medical LoC V. These requirements will be derived through systems engineering approaches and software prototype developments over the course of the multi-year CDS project to address crew health and performance decision-making and task performance, often autonomously executed by the crew, in a manner that is consistent with the appropriate medical level of care for the mission. This presentation will provide an overview of the vision for the CDS project and highlight the initial accomplishments in project planning, implementation and requirements identification in fiscal year 2020.

clinical decision support system↗

NASA Environmental Control and Life Support Technology Development for Exploration: 2020 to 2021 Overview

This paper provides an overview of NASA supported activities developing Environmental Control and Life Support (ECLSS) technologies in the following capability areas: life support, environmental monitoring, fire safety, and logistics. NASA has been refining technology needs for deep space missions including Gateway, lunar surface, Mars transit, and Mars surface missions. Validating technologies in relevant environments, both in low earth orbit (LEO) and ground tests is critical in understanding technology performance and long duration performance. On-orbit and ground tests inform NASA’s technology decisions to fill exploration gaps. NASA has multiple technology projects across the technology readiness spectrum with potential to fill or partially fill exploration gaps. For each capability area, this paper will describe select capability gaps, NASA technology project maturation over the past year, and how key performance parameters (KPPs) are being used to measure the degree of capability gap closure. KPPs are evolving but they still provide a useful measure in communicating progress and identifying development needs to fill exploration gaps. The intent is to provide a very high-level overview describing the strategic approach to gap closure and provide references to additional technical details, progress, and KPPs.

Life Support↗