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At least 235 records · Page 13

Gateway Integrated ECLSS Model Analysis of Intermodule Ventilation Failures

The Gateway Integrated ECLSS Model (GIEM) is a set of two independent models, made in Aspen Custom Modeler (ACM) and Thermal Desktop (TD), of the Gateway stack and each modules' associated environment control and life support system (ECLSS). The GIEM utilizes the 41-Node Metabolic Man (METMAN) to simulate crew inside the Gateway consuming O2 and producing CO2, H2O, and heat for the ECLSS to remove. The modules and visiting vehicles all have different levels of ECLSS capabilities and may rely on other modules and Intermodular Ventilation (IMV), which is used to exchange gas between the modules, to ensure the entire Gateway environment is controlled. If IMV were to fail or be turned off, some vehicles may have limited access to necessary ECLSS functions. This analysis focuses on evaluating O2, CO2, and H2O levels when crew are in vehicles without their own life support and IMV has failed to evaluate how long before the atmosphere is unsafe for the crew. This analysis uses the integrated nature of the GIEM to look at time to effect for O2 depletion and CO2 and H2O buildup when crew are working in vehicles that have been cut off from the ECLSS-active portion of the stack. This information is used to inform for how long crew can safely continue working in the ECLSS-inactive vehicles before experiencing a requirement violation or physical limitation and can be referenced when developing maintenance and emergency response concept of operations (ConOps).

Lawrence Barrett↗

Review of Integrated Noise Model (INM) Equations and Processes

The FAA's Integrated Noise Model (INM) relies on the methods of the SAE AIR-1845 'Procedure for the Calculation of Airplane Noise in the Vicinity of Airports' issued in 1986. Simplifying assumptions for aerodynamics and noise calculation were made in the SAE standard and the INM based on the limited computing power commonly available then. The key objectives of this study are 1) to test some of those assumptions against Boeing source data, and 2) to automate the manufacturer's methods of data development to enable the maintenance of a consistent INM database over time. These new automated tools were used to generate INM database submissions for six airplane types :737-700 (CFM56-7 24K), 767-400ER (CF6-80C2BF), 777-300 (Trent 892), 717-200 (BR7 15), 757-300 (RR535E4B), and the 737-800 (CFM56-7 26K).

Shepherd, Kevin P.↗

The Integrated Medical Model: Outcomes from Independent Review

In 2016, the Integrated Medical Model (IMM) v4.0 underwent an extensive external review in preparation for transition to an operational status. In order to insure impartiality of the review process, the Exploration Medical Capabilities Element of NASA's Human Research Program convened the review through the Systems Review Office at NASA Goddard Space Flight Center (GSFC). The review board convened by GSFC consisted of persons from both NASA and academia with expertise in the fields of statistics, epidemiology, modeling, software development, aerospace medicine, and project management (see Figure 1). The board reviewed software and code standards, as well as evidence pedigree associated with both the input and outcomes information. The board also assesses the models verification, validation, sensitivity to parameters and ability to answer operational questions. This talk will discuss the processes for designing the review, how the review progressed and the findings from the board, as well as summarize the IMM project responses to those findings. Overall, the board found that the IMM is scientifically sound, represents a necessary, comprehensive approach to identifying medical and environmental risks facing astronauts in long duration missions and is an excellent tool for communication between engineers and physicians. The board also found IMM and its customer(s) should convene an additional review of the IMM data sources and to develop a sustainable approach to augment, peer review, and maintain the information utilized in the IMM. The board found this is critically important because medical knowledge continues to evolve. Delivery of IMM v4.0 to the Crew Health and Safety (CHS) Program will occur in the 2017. Once delivered for operational decision support, IMM v4.0 will provide CHS with additional quantitative capability in to assess astronaut medical risks and required medical capabilities to help drive down overall mission risks.

medical equipment↗

The Integrated Medical Model: A Probabilistic Simulation Model for Predicting In-Flight Medical Risks

The Integrated Medical Model (IMM) is a probabilistic model that uses simulation to predict mission medical risk. Given a specific mission and crew scenario, medical events are simulated using Monte Carlo methodology to provide estimates of resource utilization, probability of evacuation, probability of loss of crew, and the amount of mission time lost due to illness. Mission and crew scenarios are defined by mission length, extravehicular activity (EVA) schedule, and crew characteristics including: sex, coronary artery calcium score, contacts, dental crowns, history of abdominal surgery, and EVA eligibility. The Integrated Medical Evidence Database (iMED) houses the model inputs for one hundred medical conditions using in-flight, analog, and terrestrial medical data. Inputs include incidence, event durations, resource utilization, and crew functional impairment. Severity of conditions is addressed by defining statistical distributions on the dichotomized best and worst-case scenarios for each condition. The outcome distributions for conditions are bounded by the treatment extremes of the fully treated scenario in which all required resources are available and the untreated scenario in which no required resources are available. Upon occurrence of a simulated medical event, treatment availability is assessed, and outcomes are generated depending on the status of the affected crewmember at the time of onset, including any pre-existing functional impairments or ongoing treatment of concurrent conditions. The main IMM outcomes, including probability of evacuation and loss of crew life, time lost due to medical events, and resource utilization, are useful in informing mission planning decisions. To date, the IMM has been used to assess mission-specific risks with and without certain crewmember characteristics, to determine the impact of eliminating certain resources from the mission medical kit, and to design medical kits that maximally benefit crew health while meeting mass and volume constraints.

Risk Analysis↗

Modeling the Effects of Artificial Drainage on Agriculture-dominated Watersheds using a Fully Distributed Integrated Hydrology Model: Datasets, scripts, model files

This model-data archive supports the research paper that demonstrates the integration of agricultural drainage features—specifically, narrow engineered ditches and tile drains—into a fully distributed, basin-scale integrated surface-subsurface hydrology model (ISSHM), Amanzi-ATS. The model employs innovative computational meshes aligned with agricultural ditches and incorporates the physically based Hooghoudt's drainage equation to simulate tile drainage, offering a novel strategy that enhances the accuracy of hydrological simulations.The archived dataset includes input parameters, model configurations, and select simulation outputs for the Amanzi-ATS model that successfully captured the streamflow patterns in the Portage River Watershed as validated by USGS gauge readings. Jupyter notebook for the preparation of model inputs and post-processing of outputs are also included. The model's predictive performance achieved a normalized Kling-Gupta Efficiency (KGE) of 0.81, surpassing SWAT without the necessity for site-specific calibration.The Amanzi-ATS model presented in this modeL-data archive allows for numerical experiments to explore the shifts in the flow structure under different drainage scenarios. As a tool for advancing the understanding of distributed hydrological responses and nutrient cycling, this archived model provides valuable insights for researchers, modelers, and decision-makers involved in watershed management and environmental modeling.The Watershed Workflow package is implemented in Python3. The Jupyter notebooks can be executed through multiple open-source tools, for example, Anaconda Jupyter Lab, VS Studio Code, etc. Other data files include CSV and HDF5 files, which can be read through Python scripts. The input files for the ATS model, open-source integrated hydrology, and transport model, are in XML format and can be edited in any commonly used text editors.

54 ENVIRONMENTAL SCIENCES↗

Autonomous, In-Flight Crew Health Risk Management for Exploration-Class Missions: Leveraging the Integrated Medical Model for the Exploration Medical System Demonstration Project

The Integrated Medical Model (IMM) captures organizational knowledge across the space medicine, training, operations, engineering, and research domains. IMM uses this knowledge in the context of a mission and crew profile to forecast risks to crew health and mission success. The IMM establishes a quantified, statistical relationship among medical conditions, risk factors, available medical resources, and crew health and mission outcomes. These relationships may provide an appropriate foundation for developing an in-flight medical decision support tool that helps optimize the use of medical resources and assists in overall crew health management by an autonomous crew with extremely limited interactions with ground support personnel and no chance of resupply.

Butler, D. J.↗

The Importance of Data Visualization: Incorporating Storytelling into the Scientific Presentation

From its inception in 2000, one of the primary tasks of the Biomedical Data Reduction Analysis (BDRA) group has been translation of large amounts of data into information that is relevant to the audience receiving it. BDRA helps translate data into an integrated model that supports both operational and research activities. This data integrated model and subsequent visual data presentations have contributed to BDRA's success in delivering the message (i.e., the story) that its customers have needed to communicate. This success has led to additional collaborations among groups that had previously not felt they had much in common until they worked together to develop solutions in an integrated fashion. As more emphasis is placed on working with "big data" and on showing how NASA's efforts contribute to the greater good of the American people and of the world, it becomes imperative to visualize the story of our data to communicate the greater message we need to share. METHODS To create and expand its data integrated model, BDRA has incorporated data from many different collaborating partner labs and other sources. Data are compiled from the repositories of the Lifetime Surveillance of Astronaut Health and the Life Sciences Data Archive, and from the individual laboratories at Johnson Space Center that support collection of data from medical testing, environmental monitoring, and countermeasures, as designated in the Medical Requirements Integration Documents. Ongoing communication with the participating collaborators is maintained to ensure that the message and story of the data are retained as data are translated into information and visual data presentations are delivered in different venues and to different audiences. RESULTS We will describe the importance of storytelling through an integrated model and of subsequent data visualizations in today's scientific presentations and discuss the collaborative methods used. We will illustrate the discussion with examples of graphs from BDRA's past work supporting operations and/or research efforts.

Babiak-Vazquez, A.↗

Model Formulations: Integrating Distributed Energy Resources (DER) using Advanced Unit Commitment Models and DER Aggregation Methodologies

A distribution energy resource aggregator (DERA) constitutes a group of distribution energy resources with small generation capacities which meet the threshold to participate in the electricity wholesale market. This document provides the proposed DERA model formulation that will be implemented in the SCUC simulation’s architecture for the SCUC-DER project. Different economical assessment methodologies have been developed to incorporated bids for individual distributed resources, which include solar cost dispatch and cost model, BESS opportunity cost offer algorithm, and price sensitive demand response model. Detailed methods are proposed to aggregate individual cost offers to a DERA cost curve to bid in SCUC market while three methods are proposed to simulate DER actual dispatch. Based on the DERA models in this document, the SCUC-DER project will be able to assess the impacts of DERA on the distribution system’s operation and reliability.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Modeling and Prediction of Wildfire Hazard in Southern California, Integration of Models with Imaging Spectrometry

Large urban wildfires throughout southern California have caused billions of dollars of damage and significant loss of life over the last few decades. Rapid urban growth along the wildland interface, high fuel loads and a potential increase in the frequency of large fires due to climatic change suggest that the problem will worsen in the future. Improved fire spread prediction and reduced uncertainty in assessing fire hazard would be significant, both economically and socially. Current problems in the modeling of fire spread include the role of plant community differences, spatial heterogeneity in fuels and spatio-temporal changes in fuels. In this research, we evaluated the potential of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Airborne Synthetic Aperture Radar (AIRSAR) data for providing improved maps of wildfire fuel properties. Analysis concentrated in two areas of Southern California, the Santa Monica Mountains and Santa Barbara Front Range. Wildfire fuel information can be divided into four basic categories: fuel type, fuel load (live green and woody biomass), fuel moisture and fuel condition (live vs senesced fuels). To map fuel type, AVIRIS data were used to map vegetation species using Multiple Endmember Spectral Mixture Analysis (MESMA) and Binary Decision Trees. Green live biomass and canopy moisture were mapped using AVIRIS through analysis of the 980 nm liquid water absorption feature and compared to alternate measures of moisture and field measurements. Woody biomass was mapped using L and P band cross polarimetric data acquired in 1998 and 1999. Fuel condition was mapped using spectral mixture analysis to map green vegetation (green leaves), nonphotosynthetic vegetation (NPV; stems, wood and litter), shade and soil. Summaries describing the potential of hyperspectral and SAR data for fuel mapping are provided by Roberts et al. and Dennison et al. To utilize remotely sensed data to assess fire hazard, fuel-type maps were translated into standard fuel models accessible to the FARSITE fire spread simulator. The FARSITE model and BEHAVE are considered industry standards for fire behavior analysis. Anderson level fuels map, generated using a binary decision tree classifier are available for multiple dates in the Santa Monica Mountains and at least one date for Santa Barbara. Fuel maps that will fill in the areas between Santa Barbara and the Santa Monica Mountains study sites are in progress, as part of a NASA Regional Earth Science Application Center, the Southern California Wildfire Hazard Center. Species-level maps, were supplied to fire managing agencies (Los Angeles County Fire, California Department of Forestry). Research results were published extensively in the refereed and non-refereed literature. Educational outreach included funding of several graduate students, undergraduate intern training and an article featured in the California Alliance for Minorities Program (CAMP) Quarterly Journal.

Roberts, Dar A.↗

An Integrated Biomechanical Model for Microgravity-Induced Visual Impairment

When gravitational unloading occurs upon entry to space, astronauts experience a major shift in the distribution of their bodily fluids, with a net headward movement. Measurements have shown that intraocular pressure spikes, and there is a strong suspicion that intracranial pressure also rises. Some astronauts in both short- and long-duration spaceflight develop visual acuity changes, which may or may not reverse upon return to earth gravity. To date, of the 36 U.S. astronauts who have participated in long-duration space missions on the International Space Station, 15 crew members have developed minor to severe visual decrements and anatomical changes. These ophthalmic changes include hyperopic shift, optic nerve distension, optic disc edema, globe flattening, choroidal folds, and elevated cerebrospinal fluid pressure. In order to understand the physical mechanisms behind these phenomena, NASA is developing an integrated model that appropriately captures whole-body fluids transport through lumped-parameter models for the cerebrospinal and cardiovascular systems. This data feeds into a finite element model for the ocular globe and retrobulbar subarachnoid space through time-dependent boundary conditions. Although tissue models and finite element representations of the corneo-scleral shell, retina, choroid and optic nerve head have been integrated to study pathological conditions such as glaucoma, the retrobulbar subarachnoid space behind the eye has received much less attention. This presentation will describe the development and scientific foundation of our holistic model.

Nelson, Emily S.↗

Integrated Medical Model Project - Overview and Summary of Historical Application

Introduction: The Integrated Medical Model (IMM) Project represents one aspect of NASA's Human Research Program (HRP) to quantitatively assess medical risks to astronauts for existing operational missions as well as missions associated with future exploration and commercial space flight ventures. The IMM takes a probabilistic approach to assessing the likelihood and specific outcomes of one hundred medical conditions within the envelope of accepted space flight standards of care over a selectable range of mission capabilities. A specially developed Integrated Medical Evidence Database (iMED) maintains evidence-based, organizational knowledge across a variety of data sources. Since becoming operational in 2011, version 3.0 of the IMM, the supporting iMED, and the expertise of the IMM project team have contributed to a wide range of decision and informational processes for the space medical and human research community. This presentation provides an overview of the IMM conceptual architecture and range of application through examples of actual space flight community questions posed to the IMM project. Methods: Figure 1 [see document] illustrates the IMM modeling system and scenario process. As illustrated, the IMM computational architecture is based on Probabilistic Risk Assessment techniques. Nineteen assumptions and limitations define the IMM application domain. Scenario definitions include crew medical attributes and mission specific details. The IMM forecasts probabilities of loss of crew life (LOCL), evacuation (EVAC), quality time lost during the mission, number of medical resources utilized and the number and type of medical events by combining scenario information with in-flight, analog, and terrestrial medical information stored in the iMED. In addition, the metrics provide the integrated information necessary to estimate optimized in-flight medical kit contents under constraints of mass and volume or acceptable level of mission risk. Results and Conclusions: Historically, IMM simulations support Science and Technology planning, Exploration mission planning, and ISS program operations by supplying simulation support, iMED data information, and subject matter expertise to Crew Health and Safety and the HRP. Upcoming release of IMM version 4.0 seeks to provide enhanced functionality to increase the quality of risk decisions made using the IMM through a more accurate representation of the real world system.

Myers, J.↗

The Application of Modeling and Simulation in Capacity Management within the ITIL Framework

Tightly integrating modeling and simulation techniques into Information Technology Infrastructure Library (ITIL) practices can be one of the driving factors behind a successful and cost-effective capacity management effort for any Information Technology (IT) system. ITIL is a best practices framework for managing IT infrastructure, development and operations. Translating ITIL theory into operational reality can be a challenge. This paper aims to highlight how to best integrate modeling and simulation into an ITIL implementation. For cases where the project team initially has difficulty gaining consensus on investing in modeling and simulation resources, a clear definition for M&S implementation into the ITIL framework, specifically its role in supporting Capacity Management, is critical to gaining the support required to garner these resources. This implementation should also help to clearly define M&S support to the overall system mission. This paper will describe the development of an integrated modeling approach and how best to tie M&S to definitive goals for evaluating system capacity and performance requirements. Specifically the paper will discuss best practices for implementing modeling and simulation into ITIL. These practices hinge on implementing integrated M&S methods that 1) encompass at least two or more predictive modeling techniques, 2) complement each one's respective strengths and weaknesses to support the validation of predicted results, and 3) are tied to the system's performance and workload monitoring efforts. How to structure two forms of modeling: statistical and simUlation in the development of "As Is" and "To Be" efforts will be used to exemplify the integrated M&S methods. The paper will show how these methods can better support the project's overall capacity management efforts.

Rahmani, Sonya↗

The Observed State of the Water Cycle in the Early Twenty-First Century

This study quantifies mean annual and monthly fluxes of Earth's water cycle over continents and ocean basins during the first decade of the millennium. To the extent possible, the flux estimates are based on satellite measurements first and data-integrating models second. A careful accounting of uncertainty in the estimates is included. It is applied within a routine that enforces multiple water and energy budget constraints simultaneously in a variational framework in order to produce objectively determined optimized flux estimates. In the majority of cases, the observed annual surface and atmospheric water budgets over the continents and oceans close with much less than 10% residual. Observed residuals and optimized uncertainty estimates are considerably larger for monthly surface and atmospheric water budget closure, often nearing or exceeding 20% in North America, Eurasia, Australia and neighboring islands, and the Arctic and South Atlantic Oceans. The residuals in South America and Africa tend to be smaller, possibly because cold land processes are negligible. Fluxes were poorly observed over the Arctic Ocean, certain seas, Antarctica, and the Australasian and Indonesian islands, leading to reliance on atmospheric analysis estimates. Many of the satellite systems that contributed data have been or will soon be lost or replaced. Models that integrate ground-based and remote observations will be critical for ameliorating gaps and discontinuities in the data records caused by these transitions. Continued development of such models is essential for maximizing the value of the observations. Next-generation observing systems are the best hope for significantly improving global water budget accounting.

Numerical analysis/modeling↗

Comparison of Integrated Analysis Methods for Two Model Scenarios

Integrated analysis methods have the potential to substantially decrease the time required for analysis modeling. Integration with computer aided design (CAD) software can also allow a model to be more accurate by facilitating import of exact design geometry. However, the integrated method utilized must sometimes be tailored to the specific modeling situation, in order to make the process most efficient. Two cases are presented here that illustrate different processes used for thermal analysis on two different models. These examples are used to illustrate how the requirements, available input, expected output, and tools available all affect the process selected by the analyst for the most efficient and effective analysis.

Amundsen, Ruth M.↗

The Integrated Medical Model

This slide presentation reviews the goals and approach for the Integrated Medical Model (IMM). The IMM is a software decision support tool that forecasts medical events during spaceflight and optimizes medical systems during simulations. It includes information on the software capabilities, program stakeholders, use history, and the software logic.

Butler, Douglas J.↗

A shared-world conceptual model for integrating space station life sciences telescience operations

Mental models of the Space Station and its ancillary facilities will be employed by users of the Space Station as they draw upon past experiences, perform tasks, and collectively plan for future activities. The operational environment of the Space Station will incorporate telescience, a new set of operational modes. To investigate properties of the operational environment, distributed users, and the mental models they employ to manipulate resources while conducting telescience, an integrating shared-world conceptual model of Space Station telescience is proposed. The model comprises distributed users and resources (active elements); agents who mediate interactions among these elements on the basis of intelligent processing of shared information; and telescience protocols which structure the interactions of agents as they engage in cooperative, responsive interactions on behalf of users and resources distributed in space and time. Examples from the life sciences are used to instantiate and refine the model's principles. Implications for transaction management and autonomy are discussed. Experiments employing the model are described which the authors intend to conduct using the Space Station Life Sciences Telescience Testbed currently under development at Ames Research Center.

Johnson, Vicki↗

Performance of an INTEGRAL spectrometer model

Model calculations for the INTEGRAL spectrometer (SPI) onboard the future INTErnational Gamma Ray Astrophysics Laboratory (INTEGAL) are presented, where the sensitivity for narrow lines is based on estimates of the background level and the detection efficiency. The instrumental background rates are explained as the sum of various components that depend on the cosmic ray intensity and the spectrometer characteristics, such as the mass distribution around the Ge detectors, the passive material, the characteristics of the detector system and the background reduction techniques. Extended background calculations were performed with Monte Carlo simulations and using semi-empirical and calculated neutron and proton cross sections. In order to improve the INTEGRAL spectrometer sensitivity, several designs and background reduction techniques were compared for an instrument with a fixed detector volume.

Jean, P.↗