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DOE OSTI2020

Process-based balance of system cost modeling for offshore wind power plants in the United States

This paper describes the development of a process-based and open-source balance of system cost model that provides the capability to evaluate both existing and novel offshore wind technologies. Individual design and installation steps are represented with bottom-up engineering models that compute times and costs associated with the process; furthermore, operational constraints are assigned to each process so that delays caused by weather and presence of marine mammals may be accounted for in the overall project timeline. The model structure, assumptions, inputs, and results are vetted with industry partners and compared against actual projects for validation. Installation times show reasonable agreement with real data. Project cost sensitivities are investigated to compute the system-level impact of different design choices. First, individual vessel efficiencies are computed for varying numbers of installation vessels and weather time series to show the diminishing returns of more than two feeder barges. Then, array cable capital costs and installation times are determined for a representative project with different turbine sizes. These values quantify the cost-benefit tradeoffs and show a net-cost savings of decreasing numbers of turbines, increased turbine spacing, and fewer turbine terminations. These results demonstrate that the balance of system model features the accuracy, functionality, and accessibility to serve as the foundation for a wide range of analyses to identify cost reduction potentials for offshore wind energy in the United States.

17 WIND ENERGY↗

NASA NTRS1980

Retrieval techniques: LVLH and inertially stabilized payloads

Procedures and techniques are discussed for retrieving payloads that are inertially or local vertical/local horizontal (LVLH) stabilized. Selection of the retrieval profile to be used depends on several factors: (1) control authority of the payload, (2) payload sensitivity to primary reaction control system (PRCS) plumes, (3) whether the payload is inertially or LVLH stabilized, (4) location of the grapple fixture, and (5) orbiter propellant consumption. The general retrieval profiles recommended are a V-bar approach for payloads that are LVLH or gravity-gradient stabilized, and the V-bar approach with one or two phase flyaround for inertially stabilized payloads. Once the general type of profile has been selected, the detailed retrieval profile and timeline should consider the various guidelines, groundrules, and constraints associated with a particular payload or flight. Reaction control system (RCS) propellant requirements for the recommended profiles range from 200 to 1500 pounds, depending on such factors as braking techniques, flyaround maneuvers (if necessary), and stationkeeping operations. The time required to perform a retrieval (starting from 1000 feet) varies from 20 to 130 minutes, depending on the complexity of the profile. The goals of this project are to develop a profile which ensures mission success; to make the retrieval profiles simple; and to keep the pilot workload to a minimum by making use of the automatic features of the orbiter flight software whenever possible.

Yglesias, J. A.↗

NASA NTRS2008

Automated Planning and Scheduling for Orbital Express (151)

The challenging timeline for DARPA's Orbital Express mission demanded a flexible, responsive, and (above all) safe approach to mission planning. Because the mission was a technology demonstration, pertinent planning information was learned during actual mission execution. This information led to amendments to procedures, which led to changes in the mission plan. In general, we used the ASPEN planner scheduler to generate and validate the mission plans. We enhanced ASPEN to enable it to reason about uncertainty. We also developed a model generator that would read the text of a procedure and translate it into an ASPEN model. These technologies had a significant impact on the success of the Orbital Express mission.

autonomy↗

NASA NTRS2009

The Integrated Medical Model: A Risk Assessment and Decision Support Tool for Space Flight Medical Systems

The Integrated Medical Model (IMM) is a decision support tool that is useful to mission planners and medical system designers in assessing risks and designing medical systems for space flight missions. The IMM provides an evidence based approach for optimizing medical resources and minimizing risks within space flight operational constraints. The mathematical relationships among mission and crew profiles, medical condition incidence data, in-flight medical resources, potential crew functional impairments, and clinical end-states are established to determine probable mission outcomes. Stochastic computational methods are used to forecast probability distributions of crew health and medical resource utilization, as well as estimates of medical evacuation and loss of crew life. The IMM has been used in support of the International Space Station (ISS) medical kit redesign, the medical component of the ISS Probabilistic Risk Assessment, and the development of the Constellation Medical Conditions List. The IMM also will be used to refine medical requirements for the Constellation program. The IMM outputs for ISS and Constellation design reference missions will be presented to demonstrate the potential of the IMM in assessing risks, planning missions, and designing medical systems. The implementation of the IMM verification and validation plan will be reviewed. Additional planned capabilities of the IMM, including optimization techniques and the inclusion of a mission timeline, will be discussed. Given the space flight constraints of mass, volume, and crew medical training, the IMM is a valuable risk assessment and decision support tool for medical system design and mission planning.

Kerstman, Eric↗

DOE OSTI2024

2024 OES-Environmental 2024 State of the Science Report, Chapter 7: Education and Outreach around Environmental Effects of Marine Renewable Energy

The marine renewable energy (MRE) industry has faced many challenges in getting projects in the water. In many cases, this is due to long consenting timelines, and occasionally active public opposition, often related to concerns about environmental effects or potential conflicts with other uses of the ocean space. While these concerns are very real, some of them are based on misconceptions or lack of familiarity with MRE devices and how they function (Boudet et al. 2020; Karytsas & Theodoropoulou 2014), or uncertainty or misinformation regarding how MRE devices may affect the environment. These misconceptions are common challenges for other renewable energy sectors or other developments in the ocean (Caporale et al. 2020; Scott 2022; Wiersma & Devine-Wright 2014), though the details of device design, site-specific environmental effects, risk and benefit perceptions, and workforce development may be unique to MRE

16 TIDAL AND WAVE POWER↗

NASA NTRS2015

Pre-Mission Input Requirements to Enable Successful Sample Collection by a Remote Field/EVA Team

This paper is intended to evaluate the sample collection process with respect to sample characterization and decision making. In some cases, it may be sufficient to know whether a given outcrop or hand sample is the same as or different from previous sampling localities or samples. In other cases, it may be important to have more in-depth characterization of the sample, such as basic composition, mineralogy, and petrology, in order to effectively identify the best sample. Contextual field observations, in situ/handheld analysis, and backroom evaluation may all play a role in understanding field lithologies and their importance for return. For example, whether a rock is a breccia or a clast-laden impact melt may be difficult based on a single sample, but becomes clear as exploration of a field site puts it into context. The FINESSE (Field Investigations to Enable Solar System Science and Exploration) team is a new activity focused on a science and exploration field based research program aimed at generating strategic knowledge in preparation for the human and robotic exploration of the Moon, near-Earth asteroids (NEAs) and Phobos and Deimos. We used the FINESSE field excursion to the West Clearwater Lake Impact structure (WCIS) as an opportunity to test factors related to sampling decisions. In contract to other technology-driven NASA analog studies, The FINESSE WCIS activity is science-focused, and moreover, is sampling-focused, with the explicit intent to return the best samples for geochronology studies in the laboratory. This specific objective effectively reduces the number of variables in the goals of the field test and enables a more controlled investigation of the role of the crewmember in selecting samples. We formulated one hypothesis to test: that providing details regarding the analytical fate of the samples (e.g. geochronology, XRF/XRD, etc.) to the crew prior to their traverse will result in samples that are more likely to meet specific analytical objectives than samples collected in the absence of this premission information. We conducted three tests of this hypothesis. Our investigation was designed to document processes, tools and procedures for crew sampling of planetary targets. This is not meant to be a blind, controlled test of crew efficacy, but rather an effort to recognize the relevant variables that enter into sampling protocol and to develop recommendations for crew and backroom training in future endeavors. Methods: One of the primary FINESSE field deployment objectives was to collect impact melt rocks and impact melt-bearing breccias from a number of locations around the WCIS structure to enable high precision geochronology of the crater to be performed [1]. We conducted three tests at WCIS after two full days of team participation in field site activities, including using remote sensing data and geologic maps, hiking overland to become familiar with the terrain, and examining previously-collected samples from other islands. In addition, the team members shared their projects and techniques with the entire team. We chose our "crew members" as volunteers from the team, all of whom had had moderate training in geologic fieldwork and became familiar with the general field setting. The first two tests were short, focused tests of our hypothesis. Test A was to obtain hydrothermal vugs; Test B was to obtain impact melt and intrusive rock as well as the contact between the two to check for contact metamorphism and age differences. In both cases, the test director had prior knowledge of the site geology and had developed a study-specific objective for sampling prior to deployment. Prior to the field deployment, the crewmember was briefed on the sampling objective and the laboratory techniques that would be used on the samples. At the field sites (Fig. 2), the crewmember was given 30 minutes to survey a small section of outcrop (10-15 m) and acquire a suite of three samples. The crewmember talked through his process and the test director kept track of the timeline in verbal cues to the crewmember. At the conclusion, the team member conducting the scientific study appraised the samples and train of thought. Test C was a 90-minute EVA simulation using two crewmembers working out of line-of-sight in communication with a science backroom. The science objectives were determined by the science backroom team in advance using a Gigapan image of the outcrop (Fig. 1). The science team formulated hypotheses for the outcrop units and created sampling objectives for impact-melt lithologies; the science team turned these into a science plan, which they communicated to the crew in camp prior to crew deployment. As part of the science plan, the science team also discussed their sample needs in depth with the crewmembers, including laboratory methods, objectives, and samples sizes needed. During the deployment, the two crewmembers relayed real-time information to the science backroom by radio with no time delay. Both the crew and science team re-evaluated their hypotheses and science plans in real-time. Discussion: Upon evaluation, we found that the focused tests (Tests A and B) were successful in meeting their scientific objectives. The crewmember used their knowledge of how the samples were to be used in further study (technique, sample size, and scientific need) to focus on the sampling task. The crewmember was comfortable spending minimal time describing and mapping the outcrop. The crewmember used all available time to get a good sample. The larger test was unsuccessful in meeting the sampling objectives. When the crewmembers began describing the lithologies, it was quickly apparent that the lithologies were not as the backroom expected and had communicated to the crew. When the outcrop wasn't as expected, the crew members instinctively switched to field characterization mode, taking significant time to characterize and map the outcrop. One crew member admitted that he "kind of lost track" of the sampling strategy as he focused on the basic outcrop characterization. This is the logical first step in a field geology campaign, that a significant amount of time must be spent by the crew and backroom to understand the outcrop and its significance. Basic field characterization of an outcrop is a focused activity that takes significant time and training [2, 3]. Sampling of representational lithologies can be added to this activity for little cost [4]. However, we have shown that identification of unusual or specific samples for laboratory study also takes significant time and knowledge. We suggest that sampling of this type be considered a separate activity from field characterization, and that crewmembers be trained in sampling needs for different kinds of studies (representative lithologies vs. specialized samples) to acquire a mindset for sampling similar to field mapping. Sampling activities should be given a significant amount of specifically allocated time in scheduling EVA activities; and in the better case, that sampling be done as a second activity to a previously studied outcrop where both crew and backroom are comfortable with its context and characteristics. Our hypothesis posited that crewmember knowledge of how the samples would be used upon return would aid them in choosing relevant samples. Our testing bore this hypothesis out to some extent. We therefore recommend that crewmember training should include exposure to the laboratory techniques and analyses that will be used on the samples to foster this knowledge. There is also the potential for increasing crewmember contextual knowledge real-time in the field through the introduction of in situ geochemical technologies such as field portable XRF. The presence of field portable geochemical technology could enable the astronauts to interrogate the samples for K abundance real-time, ensuring they could collect valuable and dateable samples [5]. Though simulations such as these can teach us a fair bit about decision making processes and timeline building, one EVA participant noted that when he wasn't collecting "real" samples, he wasn't at his best. This effect suggests that higher-fidelity studies involving truly remote participants conducting actual scientific studies merit further attention to capture lessons for application to future crew situations.

sample collection↗

NASA NTRS2022

On the paragenetic modes of minerals: A mineral evolution perspective

A systematic survey of 57 different paragenetic modes distributed among 5659 mineral species reveals patterns in the diversity and distribution of minerals related to their evolving formational environments. The earliest minerals in stellar, nebular, asteroid, and primitive Earth contexts were dominated by relatively abundant chemical elements, notably H, C, O, Mg, Al, Si, S, Ca, Ti, Cr, and Fe. Significant mineral diversification subsequently occurred via two main processes, first through gradual selection and concentration of rarer elements by fluid-rock interactions (for example, in hydrothermal metal deposits, complex granite pegmatites, and agpaitic rocks), and then through near-surface biologically mediated oxidation and weathering. We find that 3349 mineral species (59.2%) are known from only one paragenetic context, whereas another 1372 species (24.2%) are associated with two paragenetic modes. Among the most genetically varied minerals are pyrite, albite, hornblende, corundum, magnetite, calcite, hematite, rutile, and baryte, each with 15 or more known modes of formation. Among the most common paragenetic modes of minerals are near-surface weathering/oxidation (1998 species), subsurface hydrothermal deposition (859 species), and condensation at volcanic fumaroles (459 species). In addition, many species are associated with compositionally extreme environments of highly differentiated igneous lithologies, including agpaitic rocks (726 species), complex granite pegmatites (564 species), and carbonatites and related carbonate-bearing magmas (291 species). Biological processes lead to at least 2707 mineral species, primarily as a consequence of oxidative weathering but also through coal-related and other taphonomic minerals (597 species), as well as anthropogenic minerals, for example as byproducts of mining (603 minerals). However, contrary to previous estimates, we find that only ~34% of mineral species form exclusively as a consequence of biological processes. By far the most significant factor in enhancing Earth’s mineral diversity has been its dynamic hydrological cycle. At least 4583 minerals—81% of all species—arise through water-rock interactions. A timeline for mineral-forming events suggests that much of Earth’s mineral diversity was established within the first 250 million years. If life is rare in the universe, then this view of a mineralogically diverse early Earth provides many more plausible reactive pathways over a longer timespan than previous models. If, however, life is a cosmic imperative that emerges on any mineral- and water-rich world, then these findings support the hypothesis that life on Earth developed rapidly in the early stages of planetary evolution

Robert M. Hazen↗

NASA NTRS1988

Hubble Space Telescope electrical power system model

This paper describes one of the most comprehensive models ever developed for a spacecraft electrical power system (EPS). The model was developed for the Hubble Space Telescope (HST) to evaluate vehicle power system performance and to assist in scheduling maintenance and refurbishment missions by providing data needed to forecast EPS power and energy margins for the mission phases being planned. The EPS model requires a specific mission phase description as the input driver and uses a high granularity database to produce a multi-orbit power system performance report. The EPS model accurately predicts the power system response to various mission timelines over the entire operational life of the spacecraft.

Baggett, Randy↗

NASA NTRS2003

Development of a Flexible Framework of Common Hypersonic Navier-Strokes Meshes for the Space Shuttle Orbiter

A flexible framework for the development of block structured volume grids for hypersonic Navier-Stokes flow simulations was developed for analysis of the Shuttle Orbiter Columbia. The development of the flexible framework, resulted in an ability to quickly generate meshes to directly correlate solutions contributed by participating groups on a common surface mesh, providing confidence for the extension of the envelope of solutions and damage scenarios. The framework draws on the experience of NASA Langely and NASA Ames Research Centers in structured grid generation, and consists of a grid generation process that is implemented through a division of responsibilities. The nominal division of labor consisted of NASA Johnson Space Center coordinating the damage scenarios to be analyzed by the Aerothermodynamics Columbia Accident Investigation (CAI) team, Ames developing the surface grids that described the computational volume about the orbiter, and Langely improving grid quality of Ames generated data and constructing the final volume grids. Distributing the work among the participants in the Aerothermodynamic CIA team resulted in significantly less time required to construct complete meshes than possible by any individual participant. The approach demonstrated that the One-NASA grid generation team could sustain the demand for new meshes to explore new damage scenarios within a aggressive timeline.

Alter, Stephen J.↗

NASA NTRSDate not supplied

An Optimization Approach to Support Science Decision Making for Lunar Surface Exploration

Introduction: Scientific exploration is one of the three pillars of NASA’s Moon2Mars architecture, with crew surface extra vehicular activities (EVA) serving a critical enabling function. Development of surface EVA operational planning and execution, specifically integrating science and flight control teams (FCT), is currently being explored through analog scenarios. This integration, exercised, for example, through the Joint EVA and Hu-man Surface Mobility Test Team (JETT), allows for science input on EVA activities in near real-time through a Science Evaluation Room (SER), or Arte-mis science backroom, which integrates with the broader FCT through the Science Officer. The SER works within the FCT to support dynamic EVA planning in response to changes in operational constraints as well as science opportunities and re-prioritization, increasing the mission science return and accelerating the accomplishment of the Moon2Mars science objectives. The SER works within the FCT to provide recommendations to traverse execution in near real-time. One challenge is the requirement to deliver SER inputs to the FCT on operationally relevant timelines. Failure to do so may result in suboptimal execution of science exploration EVAs or even loss of key science objectives. To close this gap, we present a network optimization tool to allow the SER to provide rapid input to the FCT in response to changes in operational constraints or science opportunities. Inputs are predicated on approved science objectives, and clear rationale must be provided to the FCT for any requested change. Accordingly, this tool incorporates the Science Traceability Matrix (STM), SER prioritization scheme, and station characterization and action planning with operational constraints such as duration, traverse speed, and distance to maximize science objectives based on SER priorities, consistent with FCT operational requirements. Method: As a proof of concept, we used an existing linear programing software package used to simulate optimal routes through cellular metabolism. We built a Demonstrative Model with three STM objectives and four stations on a region of the Moon. The objectives were given an arbitrary prioritization and mapped to the stations through four possible crew actions. (Figs. 1 and 2). This station to STM mapping is consistent with the method used by the JETT5 Science Team to develop analog surface EVA science planning. We used a grid system with the landing site at the origin and the four stations placed across the positive x,y quadrant. Actions were assigned to each station and the accomplishment of those actions resulted in a numerical “reward” based on the ability of that action to achieve science objectives. The aggregate reward from each individual STM objective contributes to a global score (Science Yield), weighted by its priority. Operational constraints included a requirement to start and end at the landing site, 5 minutes each for initial station characterization and “clean up,” and variable total EVA time, traverse rate (fixed to 0.5 meters per second in our example), and time to perform each action (10, 5, 7, and 15 min for actions 1, 2, 3, and 4, respectively). Additional constraints and variables will be added in the future (e.g., sample mass, number of stations, traverse route constraints, illumination). Optimization. We converted the connections (arcs) between these stations (nodes) into a mixed integer linear programming optimization problem (arcs = constraints, nodes = variables) with the objective to maximize Science Yield. For any action, the Science Yield is equal to the relevance of that action to an STM objective [3, 2, and 1 point(s) for High, Med., and Low relevance, respectively], multiplied by the STM Objective Priority [3, 2, and 1 point(s) for High, Med., and Low priority, respectively]. This resulted in a model that computes the optimal station and action combination to maximize the Science Yield. These weightings can be adjusted by the SER as desired. Results: We explored three test cases for the Demonstrative Model. First, we set the maximum EVA duration to 120 minutes and computed the optimal route (Fig. 3A). The model suggested per-forming Actions 1 and 2 at Station P01, followed by Actions 1 and 2 at Station P02, and finally Actions 1 and 3 at Station P04 before returning to the Landing Site. Second, we adjusted the STM Objective Priori-ty order and computed the new optimal route (Fig. 3B). Under this situation, the model suggested per-forming all Actions at Station P02 followed by all Actions at Station P03. The previous test cases were relevant to SER planning activities. Next, we explored providing mid-EVA replanning input to the FCT. Scenario: While executing the Route in Fig. 3A the crew finishes at Station P01 and FCT decides that the EVA needs to finish in 45 minutes back at the Landing Site. FCT asks SER to recommend changes to the plan to accommodate this operation-al change. Using the model and incorporating these new constraints (start at Station P01, max. time of 45 min), the model suggested performing Actions 2 and 4 at Station P03 (Fig. 4), requiring 41 minutes to complete and return to the Landing Site. Interestingly, Station 3 was not part of the original route. Using the model, we determined the EVA would need 66 minutes, instead of 45, in order for the original Station P04 to yield a larger Science Yield than Station P03. The parametrization and simulation was per-formed in less than a minute, demonstrating the operational relevance of the approach. Future Efforts: The results from the Demonstrative Model suggest this tool can accelerate SER decision making on operationally relevant timelines. Use in analog activities, such as JETT5 or follow-ons, which have over a dozen stations for a crew to explore and over a dozen actions per station, will provide needed validation of the utility of this tool for planning EVAs, replanning mid-EVA, or planning follow-on EVAs based on previous results. Further integration with FCT execution monitoring tools may provide additional efficiency gains, al-lowing rapid and iterative exploration of operation-al and science decision space by the FCT and SER.

Science Operations↗

NASA NTRS1995

Alternative Approach to Vehicle Element Processing

The National Space Transportation Policy (NSTP), describes the challenge facing today's aerospace industry. 'Assuring reliable and affordable access to space through U.S. space transportation capabilities is a fundamental goal of the U.S. space program'. Experience from the Space Shuttle Program (SSP) tells us that launch and mission operations are responsible for approximately 45 % of the cost of each shuttle mission. Reducing these costs is critical to NSTP goals in the next generation launch vehicle. Based on this, an innovative alternative approach to vehicle element processing was developed with an emphasis on reduced launch costs. State-of-the-art upgrades to the launch processing system (LPS) will enhance vehicle ground operations. To carry this one step further, these upgrade could be implemented at various vehicle element manufacturing sites to ensure system compatibility between the manufacturing facility and the launch site. Design center vehicle stand alone testing will ensure system integrity resulting in minimized checkout and testing at the launch site. This paper will addresses vehicle test requirements, timelines and ground checkout procedures which enable concept implementation.

Huether, Jacob E.↗

NASA NTRS2016

ACES M and S: Unmitigated Factorial Encounter Study on DAA/TCAS Interoperability

Realization of the expected proliferation of Unmanned Aircraft System (UAS) operations in the National Airspace System (NAS) depends on the development and validation of standards for UAS Detect and Avoid (DAA) Systems. The RTCA Special Committee 228 is charged with leading the development of draft Minimum Operational Performance Standards (MOPS) for UAS DAA Systems. NASA, as a participating member of RTCA SC-228 is committed to supporting the development and validation of draft requirements for DAA alerting and guidance systems. This presentation contains the results of two combinatorial encounter analysis studies using NASA's SAA Control fast-time simulation capability for this purpose. In these studies, encounters between two aircraft were simulated one at a time for the full factorial combination of encounter geometries (e.g., encounter angle, CPA offset) and aircraft performance (e.g., ownership and intruder ground speeds and vertical rates). The first study analyzes the relationships (e.g., timeline) between the different alerting-safety regions in the SC-228 MOPS (in order of increasing severity): 1) DAA warning alert, 2) well clear recovery (WCR) guidance, 3) DAA-Collision Avoidance (CA), and 4) TCAS RA. This study will focus primarily on encounter situations in which TCAS RA occurs prior to any of the other alerting-safety boundaries. In particular, this study will investigate whether using vertical distance or vertical distance at closest point of approach (i.e., vertical miss distance or VMD) is more appropriate for the definition of the DAA-CA region. In addition, cases where transitions between different regions skip an intermediate region will be analyzed. The second study in this presentation explores a proposal to use an altitude rate error threshold to determine if vertical maneuvers are acceptable for DAA WCR guidance against non-cooperative intruders. This study incorporates the radar from the Honeywell sensor model and examines a series of pairwise encounters between a non-cooperative intruder and a UAS ownship, with different combinations of intruder states and ownship performance levels. The study uses SAA Control as a simulation platform and pilot model, and Omnibands to provide DWC recovery guidance. Two simulation sets, one that allows vertical DWC recovery guidance and one that does not, are compared to determine if encounters with altitude rate errors above 250 feet-per-minute are more likely to have more severe losses of well clear, as determined by the Loss of Well-Clear Severity metric.

SaaControl↗

DOE OSTI2018

Translator Plan: A Coordinated Vision for Fiscal Years 2018-2020

In June of 2017, the Translator Group met to develop this coordinated three-year vision plan, incorporating key feedback and aligning to ARM’s mission priorities. This plan responds to a shift in how we determine our priorities, given the new needs of the ARM Facility. In the past, individual Translators have determined priorities in conversation with individual DOE Atmospheric System Research (ASR) working groups. To better support ARM’s Decadal Vision (https://www.arm.gov/publications/programdocs/doe-sc-arm-14-029.pdf), however, the Translator Group is instead developing a coordinated response to needs from our user community to better balance resources and skills among participants. This approach agrees with direction from ARM leadership and the ARM-ASR Coordination Team (AACT). To develop this plan the Translator Group reviewed feedback received from the User Executive Committee (UEC) and the Triennial Review, as well as priorities from ASR working groups and Principal Investigators (PIs), the LES ARM Symbiotic Simulation and Observation (LASSO) project, and new instrumentation and activities as described by the ARM Technical Director. In particular, we are responding to the advice that we were trying to do too much, and should focus on providing additional support to data quality, uncertainty assessment, a timeline for producing core VAPs from ARM Mobile Facility (AMF) campaigns, and supporting key aspects of the Decadal Vision.

value-added products, User Executive Committee, AR↗

NASA NTRS2013

Multifunction Habitat Workstation/OLED Development

This paper gives a general outline of both a multifunction habitat workstation and the research put into an Organic Light Emitting Diode (OLED) device. It first covers the tests that the OLED device will go through to become flight ready along with reasoning. Guidelines for building an apparatus to house the display and its components are given next, with the build of such following. The three tests the OLED goes through are presented (EMI, Thermal/Vac, Radiation) along with the data recovered. The second project of a multifunction workstation is then discussed in the same pattern. Reasoning for building such a workstation with telepresence in mind is offered. Build guidelines are presented first, with the build timeline following. Building the workstation will then be shown in great detail along with accompanying photos. Once the workstation has been discussed, the versatility of its functions are given. The paper concludes with future views and concepts that can added when the time or technology presents itself.

Schumacher, Shawn↗

DOE OSTI2022

Application Results on Early Exascale Hardware

This Exascale Computing Project (ECP) milestone report summarizes the status of 27 of the 31 ECP Applications Development (AD) subprojects at the end of FY21. In November and December of 2021, a comprehensive assessment of AD projects was conducted by the ECP leadership along with external subject matter experts (SMEs). (NNSA application projects are reviewed separately using the ASC milestone process.) The AD review committee—consisting of the AD lead, AD deputy, Level 3 (L3), and at least one external project SME—was tasked with evaluating each project’s progress relative to ECP project goals specified in the FY21 timeline. Key areas of focus were code maturity and performance on pre-exascale systems, an in-depth analysis of final key performance parameter (KPP) verification contracts, and future R&D priorities in the final year of ECP and beyond. As such, this report contains not only an accurate snapshot of each subproject’s current status but also represents a broad account of successes and challenges in porting large scientific applications to DOE’s next-generation high-performance computing architectures – the Frontier and Aurora systems.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2021

Practical Operational Readiness Gambits: Operations Training Simulations for the Curiosity Rover

The Mars Science Laboratory team had been puttingin effort to make a Training Venue to allow for parallel shadowtactical operations for trainees to actively work alongside theprime tactical operations personnel without affecting operations,since staffing constraints and shortened operations timelineswere straining the tactical process in supporting operationstrainees in the traditional way. The COVID- 19 Pandemic presentedfurther challenges in continuing on-console training forMSL operations trainees. The MSL operations team switched tofully remote operations, thus hampering the direct mentorshipa trainee would normally receive while on site at JPL. TheMars 2020 training team had developed a concept for roveroperations training simulations based on Johnson Space Center’sextensive simulations training program for astronauts andflight controllers. The MSL team borrowed this idea, and implementedthese training simulations which are called PracticalOperational Readiness Gambits (PORGs). The PORGs so farhave focused on the Science Planner and Rover Planner roles,which are two crucial roles in tactical operations that engagein key interactions throughout a shift. PORGs are based onactual sol scenarios that have occurred on Mars and follow thetactical operations process and timeline as closely as possible.However, unlike an operations shift, PORGs can slow down orpause to allow for more mentoring time. PORGs can focus onparticular skills to test the trainees on their understanding ofa concept. PORGs increase in complexity with each scenario toease the trainees into more typical tactical operations workloads.As more trainees join the MSL operations team, more roles arebeing incorporated into PORGs. There are plans to incorporatecertified operations personnel into PORGs to practice anomalyresponse situations. PORGs have become an essential part of theMSL operations training program and will continue even afterthe return to on-site operations at JPL.

Gajeway, Jocelyn↗

DOE OSTI2015

Investigation of injury/illness data at a nuclear facility. Part II

At Los Alamos National Laboratory (LANL), there are several nuclear facilities, accelerator facilities, radiological facilities, explosives sites, moderate- and high-hazard non-nuclear facilities, biosciences laboratory, etc. The Plutonium Science and Manufacturing Directorate (ADPSM) provides special nuclear material research, process development, technology demonstration, and manufacturing capabilities. ADPSM manages the LANL Plutonium Facility. Within the Radiological Control Area at TA-55 (PF-4), chemical and metallurgical operations with plutonium and other hazardous materials are performed. LANL Health and Safety Programs investigate injury and illness data. In this study, statistically significant trends have been identified and compared for LANL, ADPSM, and PF-4 injury/illness cases. A previously described output metric is used to measures LANL management progress towards meeting its operational safety objectives and goals. Timelines are used to determine trends in Injury/Illness types. Pareto Charts are used to prioritize causal factors. The data generated from analysis of Injury/Illness data have helped identify and reduce the number of corresponding causal factors.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2000

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.↗