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At least 793 records · Page 44

In-Situ Resource Utilization Modeling of a Lunar Water Processing System

A key element of achieving a sustained surface presence, such as defined in NASA’s Artemis plan, is In-Situ Resource Utilization (ISRU). ISRU is the practice of using local resources to provide mission consumables that reduce system launch mass requirements, and regenerate resources (chiefly, water and oxygen) for propulsion and life support supporting both Lunar and Martian missions. ISRU systems require multiple complex processes, such as excavation, chemical reactors, and electrolysis subsystems that must operate in harmony to optimize the overall system process from beginning to end. The Mission Analysis and Integration Tool (MAIT) was previously developed with MATLAB in FY22 to connect individual subsystem models into a customized, flexible framework for the purpose of technology downselect, optimization, and end-to-end process planning. Beginning in FY24, MAIT was leveraged and evolved using MATLAB/Simulink due to its ability to communicate with a vast number of other programming languages and makes up the backbone of data flow between inputs and outputs to the subsystem models. MAIT initially evaluated a suite of ISRU-related technologies, including the water processing Lunar Auger Dryer for ISRU (LADI) system with integrated upstream excavation and downstream electrolysis subsystems. With individual models consolidated, the MAIT tool generated over 60,000 cases during its parametric sweeps; these system iterations produced valuable insight into the optimal LADI geometry for minimizing energy demands, estimating carbothermal reactor and radiator mass relationships, and calculated the power dynamics of the electrolysis unit. Advanced efforts with advanced models will include examining multiple production targets to demonstrate the ability to scale ISRU technologies supporting the Space Technology Mission Directorate’s (STMD) commercialization strategy, and increase the MAIT software capability to handle a wide array of ISRU system models beyond the Lunar environment, e.g. production of propellant for a Martian lander.

Avery Carlson↗

In-Situ Resource Utilization Modeling of a Lunar Water Processing System

A key element of achieving a sustained surface presence, such as defined in NASA’s Artemis plan, is In-Situ Resource Utilization (ISRU). ISRU is the practice of using local resources to provide mission consumables that reduce system launch mass requirements, and regenerate resources (chiefly, water and oxygen) for propulsion and life support supporting both Lunar and Martian missions. ISRU systems require multiple complex processes, such as excavation, chemical reactors, and electrolysis subsystems that must operate in harmony to optimize the overall system process from beginning to end. The Mission Analysis and Integration Tool (MAIT) was previously developed with MATLAB in FY22 to connect individual subsystem models into a customized, flexible framework for the purpose of technology downselect, optimization, and end-to-end process planning. Beginning in FY24, MAIT was updated and became the capital program in the Systems Engineering and Integration (SE&I) ISRU Modeling and Analysis (SIMA) project. Prior work was leveraged and evolved using MATLAB/Simulink due to its ability to communicate with a vast number of other programming languages and makes up the backbone of data flow between inputs and outputs to the subsystem models. MAIT initially evaluated a suite of ISRU-related technologies, including the water processing Lunar Auger Dryer for ISRU (LADI) system with integrated upstream excavation and downstream electrolysis subsystems. With individual models consolidated, the MAIT tool generated over 5,000 cases during its first round of parametric sweeps on the water processing architecture at multiple production targets; the system analysis produced valuable insight into the optimal LADI geometry that minimized energy demands, estimated effects to cold trap size and radiator requirements, and calculated the power dynamics of the electrolysis unit and liquid oxygen storage volume. Additional efforts are being made to demonstrate the ability to scale ISRU technologies supporting the Space Technology Mission Directorate’s (STMD) commercialization strategy and increase the MAIT software capability. Work is ongoing to handle a wide array of ISRU system models beyond the Lunar environment, e.g. production of propellant for a Martian lander.

Avery Carlson↗

In-Situ Resource Utilization Modeling of a Lunar Water Processing System

A key element of achieving a sustained surface presence, such as defined in NASA’s Artemis plan, is In-Situ Resource Utilization (ISRU). ISRU is the practice of using local resources to provide mission consumables that reduce system launch mass requirements, and regenerate resources (chiefly, water and oxygen) for propulsion and life support supporting both Lunar and Martian missions. ISRU systems require multiple complex processes, such as excavation, chemical reactors, and electrolysis subsystems that must operate in harmony to optimize the overall system process from beginning to end. The Mission Analysis and Integration Tool (MAIT) was previously developed with MATLAB in FY22 to connect individual subsystem models into a customized, flexible framework for the purpose of technology downselect, optimization, and end-to-end process planning. Beginning in FY24, MAIT was updated and became the capital program in the Systems Engineering and Integration (SE&I) ISRU Modeling and Analysis (SIMA) project. Prior work was leveraged and evolved using MATLAB/Simulink due to its ability to communicate with a vast number of other programming languages and makes up the backbone of data flow between inputs and outputs to the subsystem models. MAIT initially evaluated a suite of ISRU-related technologies, including the water processing Lunar Auger Dryer for ISRU (LADI) system with integrated upstream excavation and downstream electrolysis subsystems. With individual models consolidated, the MAIT tool generated over 5,000 cases during its first round of parametric sweeps on the water processing architecture at multiple production targets; the system analysis produced valuable insight into the optimal LADI geometry that minimized energy demands, estimated effects to cold trap size and radiator requirements, and calculated the power dynamics of the electrolysis unit and liquid oxygen storage volume. Additional efforts are being made to demonstrate the ability to scale ISRU technologies supporting the Space Technology Mission Directorate’s (STMD) commercialization strategy and increase the MAIT software capability. Work is ongoing to handle a wide array of ISRU system models beyond the Lunar environment, e.g. production of propellant for a Martian lander.

Avery Carlson↗

ISS Operations Cost Reductions Through Automation of Real-Time Planning Tasks

In 2008 the Johnson Space Center s Mission Operations Directorate (MOD) management team challenged their organization to find ways to reduce the costs of International Space station (ISS) console operations in the Mission Control Center (MCC). Each MOD organization was asked to identify projects that would help them attain a goal of a 30% reduction in operating costs by 2012. The MOD Operations and Planning organization responded to this challenge by launching several software automation projects that would allow them to greatly improve ISS console operations and reduce staffing and operating costs. These projects to date have allowed the MOD Operations organization to remove one full time (7 x 24 x 365) ISS console position in 2010; with the plan of eliminating two full time ISS console support positions by 2012. This will account for an overall 10 EP reduction in staffing for the Operations and Planning organization. These automation projects focused on utilizing software to automate many administrative and often repetitive tasks involved with processing ISS planning and daily operations information. This information was exchanged between the ground flight control teams in Houston and around the globe, as well as with the ISS astronaut crew. These tasks ranged from managing mission plan changes from around the globe, to uploading and downloading information to and from the ISS crew, to even more complex tasks that required multiple decision points to process the data, track approvals and deliver it to the correct recipient across network and security boundaries. The software solutions leveraged several different technologies including customized web applications and implementation of industry standard web services architecture between several planning tools; as well as a engaging a previously research level technology (TRL 2-3) developed by Ames Research Center (ARC) that utilized an intelligent agent based system to manage and automate file traffic flow, archiving f data, and generating console logs. This technology called OCAMS (OCA (Orbital Communication System) Management System), is now considered TRL level 9 and is in daily use in the Mission Control Center in support of ISS operations. These solutions have not only allowed for improved efficiency on console; but since many of the previously manual data transfers are now automated, many of the human error prone steps have been removed, and the quality of the planning products has improved tremendously. This has also allowed our Planning Flight Controllers more time to focus on the abstract areas of the job, (like the complexities of planning a mission for 6 international crew members with a global planning team), instead of being burdened with the administrative tasks that took significant time each console shift to process. The resulting automation solutions have allowed the Operations and Planning organization to realize significant cost savings for the ISS program through 2020 and many of these solutions could be a viable

Hall, Timothy A.↗

International Space Station Evolution Data Book: Baseline Design - Volume 1

The International Space Station (ISS) will provide an Earth-orbiting facility that will accommodate engineering experiments as well as research in a microgravity environment for life and natural sciences. The ISS will distribute resource utilities and support permanent human habitation for conducting this research and experimentation in a safe and habitable environment. The objectives of the ISS program are to develop a world-class, international orbiting laboratory for conducting high-value scientific research for the benefit of humans on Earth; to provide access to the microgravity environment; to develop the ability to live and work in space for extended periods; and to provide a research test bed for developing advanced technology for human and robotic exploration of space. The current design and development of the ISS has been achieved through the outstanding efforts of many talented engineers, designers, technicians, and support personnel who have dedicated their time and hard work to producing a state-of-the-art Space Station. Despite these efforts, the current design of the ISS has limitations that have resulted from cost and technology issues. Regardless, the ISS must evolve during its operational lifetime to respond to changing user needs and long-term national and international goals. As technologies develop and user needs change, the ISS will be modified to meet these demands. The design and development of these modifications should begin now to prevent a significant lapse in time between the baseline design and the realization of future opportunities. For this effort to begin, an understanding of the baseline systems and current available opportunities for utilization needs to be achieved. Volume I of this document provides the consolidated overview of the ISS baseline systems. It also provides information on the current facilities available for pressurized and unpressurized payloads. Information on current plans for crew availability and utilization; resource timelines and margin summaries including power, thermal, and storage volumes; and an overview of the ISS cargo traffic and the vehicle traffic model is also included.

Jorgensen, Catherine A.↗

Analytical Modeling of Planetary Excavation for in Situ Resource Utilization

The space-faring capabilities of humans are dependent on the ability to interact with plan-etary surfaces safely and efficiently and utilize local re-sources. Since planetary regolith will be the primary feedstock for in situ resource utilization (ISRU) and infrastructure development activities [1,2], the site-specific geomechanical properties must be understood to optimize excavation operations [3]. Excavating planetary regolith is challenging due to its unique geomechanical properties, 1/6th G reduced gravity extreme conditions, and limited energy resources. Therefore, it is critical to develop technologies that reduce excavation force requirements and minimize tool path inefficiencies to save time and energy during planetary re-source acquisition and infrastructure development [3]. There have been several experimental investigations of methods to optimize planetary excavations [4,5], but none developed predictive capabilities. This abstract presents a simple analytical method that will be used to model laboratory and mission excavation data. Future work will build on the simple analytical method here to include high-fidelity numerical simulations of planetary excavation mechanics.

Regolith↗

Four-dimensional dose reconstruction through in vivo phase matching of cine images of electronic portal imaging device

Purpose: A method is proposed to reconstruct a four-dimensional (4D) dose distribution using phase matching of measured cine images to precalculated images of electronic portal imaging device (EPID). Methods: (1) A phantom, designed to simulate a tumor in lung (a polystyrene block with a 3 cm diameter embedded in cork), was placed on a sinusoidally moving platform with an amplitude of 1 cm and a period of 4 s. Ten-phase 4D computed tomography (CT) images of the phantom were acquired. A planning target volume (PTV) was created by adding a margin of 1 cm around the internal target volume of the tumor. (2) Three beams were designed, which included a static beam, a theoretical dynamic beam, and a planning-optimized dynamic beam (PODB). While the theoretical beam was made by manually programming a simplistic sliding leaf motion, the planning-optimized beam was obtained from treatment planning. From the three beams, three-dimensional (3D) doses on the phantom were calculated; 4D dose was calculated by means of the ten phase images (integrated over phases afterward); serving as “reference” images, phase-specific EPID dose images under the lung phantom were also calculated for each of the ten phases. (3) Cine EPID images were acquired while the beams were irradiated to the moving phantom. (4) Each cine image was phase-matched to a phase-specific CT image at which common irradiation occurred by intercomparing the cine image with the reference images. (5) Each cine image was used to reconstruct dose in the phase-matched CT image, and the reconstructed doses were summed over all phases. (6) The summation was compared with forwardly calculated 4D and 3D dose distributions. Accounting for realistic situations, intratreatment breathing irregularity was simulated by assuming an amplitude of 0.5 cm for the phantom during a portion of breathing trace in which the phase matching could not be performed. Intertreatment breathing irregularity between the time of treatment and the time of planning CT was considered by utilizing the same reduced amplitude when the phantom was irradiated. To examine the phase matching in a humanoid environment, the matching was also performed in a digital phantom (4D XCAT phantom). Results: For the static, the theoretical, and the planning-optimized dynamic beams, the 4D reconstructed doses showed agreement with the forwardly calculated 4D doses within the gamma pass rates of 92.7%, 100%, and 98.1%, respectively, at the isocenter plane given by 3%/3 mm criteria. Excellent agreement in dose volume histogram of PTV and lung-PTV was also found between the two 4D doses, while substantial differences were found between the 3D and the 4D doses. The significant breathing irregularities modeled in this study were found not to be noticeably affecting the reconstructed dose. The phase matching was performed equally well in a digital phantom. Conclusions: The method of retrospective phase determination of a moving object under irradiation provided successful 4D dose reconstruction. This method will provide accurate quality assurance and facilitate adaptive therapy when distinguishable objects such as well-defined tumors, diaphragm, and organs with markers (pancreas and liver) are covered by treatment beam apertures.

60 APPLIED LIFE SCIENCES↗

From conditional oughts to qualitative decision theory

The primary theme of this investigation is a decision theoretic account of conditional ought statements (e.g., 'You ought to do A, if C') that rectifies glaring deficiencies in classical deontic logic. The resulting account forms a sound basis for qualitative decision theory, thus providing a framework for qualitative planning under uncertainty. In particular, we show that adding causal relationships (in the form of a single graph) as part of an epistemic state is sufficient to facilitate the analysis of action sequences, their consequences, their interaction with observations, their expected utilities, and the synthesis of plans and strategies under uncertainty.

Pearl, Judea↗

Three-Dimensional Path Planning Software-Assisted Transjugular Intrahepatic Portosystemic Shunt: A Technical Modification

PurposeThis study was designed to report our results with a modified technique of three-dimensional (3D) path planning software assisted transjugular intrahepatic portosystemic shunt (TIPS).Methods3D path planning software was recently developed to facilitate TIPS creation by using two carbon dioxide portograms acquired at least 20° apart to generate a 3D path for overlay needle guidance. However, one shortcoming is that puncturing along the overlay would be technically impossible if the angle of the liver access set and the angle of the 3D path are not the same. To solve this problem, a prototype 3D path planning software was fitted with a utility to calculate the angle of the 3D path. Using this, we modified the angle of the liver access set accordingly during the procedure in ten patients.ResultsFailure for technical reasons occurred in three patients (unsuccessful wedged hepatic venography in two cases, software technical failure in one case). The procedure was successful in the remaining seven patients, and only one needle pass was required to obtain portal vein access in each case. The course of puncture was comparable to the 3D path in all patients. No procedure-related complication occurred following the procedures.ConclusionsAdjusting the angle of the liver access set to match the angle of the 3D path determined by the software appears to be a favorable modification to the technique of 3D path planning software assisted TIPS.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

SU-F-T-589: HybridArc Planning Criteria for Brain SRS

Purpose: To compare VMAT SRS plans, dynamic conformal arc (DCA) plans, and Brainlab iPlan’s capability of planning and delivering brain SRS plans by employing HybridArc. HybridArc utilizes both DCA and IMRT. Using HybridArc, the amount of DCA versus IMRT needs to be optimized. Methods: Four SRS patients with the aim of reducing brainstem dose were selected for this study. All patients were contoured in iPlan and transferred to Eclipse for VMAT planning. In iPlan, DCA plans were created for each case. Moreover, nine HybridArc plans with DCA-IMRT ratios between 9:1 through 1:9 were created with a single ring structure generated by subtracting 3 mm expansion of target from a 10 mm expansion of the target. Two static IMRT beams were used in each of the five DCA arcs for HybridArc. The dose was prescribed to DCA only and HybridArc plans and normalized so that the target volume (TV) receives 100% dose to 99.5% of the TV to achieve 120% ∼ 130% max dose within targets. Following metrics were compared: PITV, V12Gy, CGIc, CGIg, CGI, brainstem max dose, and total monitor units (MUs). Results: A brainstem max dose comparable with VMAT from 30% IMRT and less with 50% or more IMRT could be achieved. PITV decreased with increasing IMRT portion and begins to saturate past an IMRT portion of 30%. The CGIg index, which represents how fast the dose falls off, was better with HybridArc in all HybridArc plans. Total MUs increased with increasing IMRT but less than VMAT in all cases. Conclusion: Overall, a lower brainstem max dose and a lower V12Gy with fewer MUs can be achieved with HybridArc. Considering all factors, it would be best to use a DCA-IMRT ratio of either 7:3 or 6:4.

60 APPLIED LIFE SCIENCES↗

The Urban Energy-Water Nexus: Utility-Level Water Flows and Embedded Energy

There are limited open source data available for determining water production/treatment and required energy for cities across the United States. This database represents the culmination of a two-year effort to obtain data from cities across the United States via open records requests in order to determine the state of the U.S. urban energy-water nexus. Data were requested at the daily or monthly scale when available for 127 cities across the United States, represented by 253 distinct water and sewer districts. Data were requested from cities larger than 100,000 people and from each state. In the case of states that did not have cities that met these criteria, the largest cities in those states were selected. The resulting database represents a drinking water service population of 81.4 million and a wastewater service population of 86.2 million people. Average daily demands for the United States were calculated to be 560 liters per capita for drinking water and 500 liters per capita of wastewater. The embedded energy within each of these resources is 340 kWh/1000 m3 and 430 kWh/1000 m3, respectively. Drinking water data at the annual scale are available for production volume (89 cities) and for embedded energy (73 cities). Annual wastewater data are available for treated volume (104 cities) and embedded energy (90 cities). Monthly data are available for drinking water volume and embedded energy (73 and 56 cities) and wastewater volume and embedded energy (88 and 70 cities). Please see the two related papers for this metadata are included with this submission. Each folder name is a city that contributed data to the collection effort (City+State Abbreviation). Within each folder is a .csv file with drinking water and wastewater volume and energy data. A READ-ME file within each folder details the contents of the folder within any relevant information pertaining to data collection. Data are on the order of a monthly timescale when available, and yearly if not. Please cite the following papers when using the database: Chini, C.M. and Stillwell, A.S. (2017). The State of U.S. Urban Water: Data and the Energy-Water Nexus. Water Resources Research. 54(3). DOI: https://doi.org/10.1002/2017WR022265 Chini, C.M., and Stillwell, A. (2016). Where are all the data? The case for a comprehensive water and wastewater utility database. Journal of Water Resources Planning and Management. 143(3). DOI: 10.1061/(ASCE)WR.1943-5452.0000739

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Yerington Paiute Tribe Energy Plan Version 1

The Yerington Paiute Tribe has made energy management and planning a priority. The Tribal Council has recognized that energy is an important component of their goal of self-sufficiency. Recognizing energy development as a component of the Tribe’s natural resources provides for needed economic development.A number of priorities have been identified for energy development. These range from immediate housing needs such as weatherization and solar to interest in energy as economic development.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Quantifying the Level of Cross-State Renewable Energy Transactions (Presentation)

This presentation and associated spreadsheet examine the level of cross-state renewable energy transactions. Most state renewable portfolio standard (RPS) policies allow for out-of-state renewable energy or renewable energy certificates to count towards compliance. This analysis focuses on compliance for 2012 and provides stakeholders with an understanding of the extent to which RPSs are being met.

111(D)↗

Presidential Address: Building Our New Energy Future

Sheila J. Hayter, P.E., Presidential Member/Fellow ASHRAE and Distinguished Lecturer, is a group manager with the Integrated Applications Center at the Department of Energy's National Renewable Energy Laboratory (NREL) in Golden, Colo., where she has worked since 1992. She leads a team of experts who support international, federal, state, and local entities with the goal of significantly reducing nonrenewable energy consumption. As the ASHRAE president, this is her presidential speech.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Hosting Capacity Analysis for Utilities

NREL's dynamic hosting capacity analysis can help you better understand the thresholds at which new distributed photovoltaic (DPV) systems will trigger upgrades to the electrical distribution system. This fact sheet details NREL's analysis for utilities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Langley Research Center's Unitary Plan Wind Tunnel: Testing Capabilities and Recent Modernization Activities

Description, capabilities, initiatives, and utilization of the NASA Langley Research Center's Unitary Plan Wind Tunnel are presented. A brief overview of the facility's operational capabilities and testing techniques is provided. A recent Construction of Facilities (Car) project to improve facility productivity and efficiency through facility automation has been completed and is discussed. Several new and maturing thrusts are underway that include systematic efforts to provide credible assessment for data quality, modifications to the new automation control system for increased compatibility with the Modern Design of Experiments (MDOE) testing methodology, and process improvements for better test coordination, planning, and execution.

Micol, John R.↗