Using Complexity Metrics to Support Sustainability of Computational Science and Engineering Software
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The Common Habitat is a large habitat developed as an alternative architecture study, not part of the current NASA baseline, that uses the SLS core stage liquid oxygen tank as its primary structure. It has a gravity-independent internal architecture, such that identical units can be used on the lunar surface, Mars surface, and in microgravity. In developing the habitat, two key architectural questions emerged. Should the internal layout use a vertical or horizontal orientation of the tank? Should the crew size be four or eight? This led to the design of four variants: a four-crew horizontal, four-crew vertical, eight-crew horizontal, and eight-crew vertical. The four-crew variants use a shortened version of the tank while the eight-crew variants use the entire tank. The primary consideration applied for down-selection is the crew experience living and working in the habitat, inclusive of crew productivity, well-being, and survivability. Based on this consideration, a series of seven assessments were performed to compare the variants. This analysis was performed as an unfunded, volunteer activity leveraging civil servants across multiple field centers, most with expertise working in various Artemis teams. Additionally, the evaluation was limited to the use of CAD models, images, and spreadsheet data, with no resources available for mockups or Virtual Reality. A logistics analysis developed a standard logistics module and then estimated how much stowage could be carried onboard each Common Habitat and how many logistics modules are required by each variant for a given mission duration. It also considered the amounts of water to be stored in each variant. A functional analysis identified and compared the living and working functions across the habitats, ranking them relative to each other. A crew time assessment first estimated the total crew time, building a weekly crew timeline for both four and eight-person crews. It then allocated time to activities linked to living and working functions, comparing how much time was available for each function in each variant. A science productivity assessment developed a relative metric using crew time, science stowage, and assumed rates of experiment consumables use to analytically compare the four variants. It also comparatively ranked the habitats with respect to a number of subjective parameters and a workstation acceptability rating. A maintenance capacity assessment identified and compared eleven generic maintenance capabilities across the variants and also ranked them for their predicted ability to complete twelve fabrication, maintenance, and repair scenarios. A contingency responsiveness analysis examined twelve serious in-flight contingencies. For each scenario, the number of crew needed to respond were predicted and acceptability of various aspects of contingency response were evaluated, comparing the variants against each other. Finally, in a habitability assessment, 120 habitability characteristics reflecting 13 major categories were evaluated for each habitat. These results were compared to identify the most acceptable habitat in each category. Ultimately, the data favored the horizontal orientation over the vertical and an eight-person crew over four. Implications of selecting this variant are discussed, including specific architectural challenges that result from the use of the full tank.
The Common Habitat is a large habitat that uses the Space Launch System core stage liquid oxygen tank as its primary structure. It has a gravity-independent internal architecture, such that identical units can be used on the lunar surface, Mars surface, and in microgravity. In developing the habitat, two key architectural questions emerged. Should the internal layout use a vertical or horizontal orientation of the tank? Should the crew size be four or eight? This led to the design of four variants: a four-crew horizontal, four-crew vertical, eight-crew horizontal, and eight-crew vertical. The primary consideration applied for down-selection was the crew experience living and working in the habitat, inclusive of crew productivity, well-being, and survivability. Based on this consideration, a series of seven assessments was performed to compare the four variants. A stowage assessment developed a standard logistics module and then considered the amounts of water to be stored in each variant. It then estimated how much stowage could be carried onboard each Common Habitat and how many logistics modules are required by each variant for a given mission duration. A functional analysis identified and compared the living and working functions across the four habitat, ranking them relative to each other. A crew time assessment first estimated the total crew time, building a weekly crew timeline for both four and eight-person crews. It then allocated time to activities linked to living and working functions, comparing how much time was available for each function in each variant. A science productivity assessment developed a relative metric using crew time, science stowage, and assumed rates of experiment consumables use to analytically compare the four variants. It also comparatively ranked the habitats with respect to a number of subjective parameters and a workstation acceptability rating. A maintenance capacity assessment identified and compared eleven generic maintenance capabilities across the four variants and also ranked the variants for their predicted ability to complete twelve fabrication, maintenance, and repair scenarios. A contingency responsiveness analysis examined twelve serious in-flight contingencies. For each scenario, the number of crew needed to respond was predicted and acceptability of various aspects of contingency response was evaluated, comparing the four variants against each other. Finally, in a habitability assessment, 120 habitability characteristics reflecting 13 major categories were evaluated for each habitat. These results were compared to identify the most acceptable habitat in each category. Ultimately, the data was shown to favor the horizontal orientation over the vertical and an eight-person crew over four. Implications of selecting this variant are discussed, including specific architectural challenges that result from the use of the full SLS liquid oxygen tank.
Developing decision-relevant science for adaptation requires the identification of climatic parameters that are both actionable for practitioners as well as tractable for modelers. In many sectors, these decision-relevant climatic metrics and the approaches that enable their identification remain largely unknown. “Co-production” of science with scientists and decision-makers is one potential way to identify these metrics, but there is little research describing specific and successful co-production approaches. This paper examines the negotiations and outcomes from Project Hyperion, wherein scientists and water managers jointly developed decision-relevant climatic metrics for adaptive water management. We identify successful co-production strategies by analyzing the project’s numerous back-and-forth engagements and tracing the evolution of the science during these engagements. We found that effective mediation between scientists and managers needed dedicated “boundary spanners” with significant modeling expertise. Translating practitioners’ information needs into tractable climatic metrics required direct and indirect methods of eliciting knowledge. We identified four indirect methods that were particularly salient for extracting tacitly held knowledge and enabling shared learning: developing a hierarchical framework linking management issues with metrics, starting discussions from the planning challenges, collaboratively exploring the planning relevance of new scientific capabilities, and using analogies of other “good” metrics. The decision-relevant metrics we developed provide insights into advancing adaptation-relevant climate science in the water sector. The co-production strategies we identified can be used to design and implement productive scientist–decision-maker interactions. Overall, the approaches and metrics we developed can help climate science to expand in new and more use-inspired directions.
ASTRO2010 Decadal Survey stated that an advanced large-aperture ultraviolet, optical, near-infrared (UVOIR) telescope is required to enable the next generation of compelling astrophysics and exoplanet science; and, that present technology is not mature enough to affordably build and launch any potential UVOIR mission concept. AMTD is the start of a multiyear effort to develop, demonstrate and mature critical technologies to TRL-6 by 2018 so that a viable flight mission can be proposed to the 2020 Decadal Review. AMTD builds on the state of art (SOA) defined by over 30 years of monolithic & segmented ground & space-telescope mirror technology to mature six key technologies: (1) Large-Aperture, Low Areal Density, High Stiffness Mirror Substrates: Both (4 to 8 m) monolithic and (8 to 16 m) segmented primary mirrors require larger, thicker, and stiffer substrates. (2) Support System: Large-aperture mirrors require large support systems to ensure that they survive launch and deploy on orbit in a stress-free and undistorted shape. (3) Mid/High Spatial Frequency Figure Error: Very smooth mirror is critical for producing high-quality point spread function (PSF) for high contrast imaging. (4) Segment Edges: The quality of segment edges impacts PSF for high-contrast imaging applications, contributes to stray light noise, and affects total collecting aperture. (5) Segment to Segment Gap Phasing: Segment phasing is critical for producing high-quality temporally-stable PSF. (6) Integrated Model Validation: On-orbit performance is driven by mechanical & thermal stability. Compliance cannot be 100% tested, but relies on modeling. AMTD is pursuing multiple design paths to provide the science community with options to enable either large aperture monolithic or segmented mirrors with clear engineering metrics traceable to science requirements.
ASTRO2010 Decadal Survey stated that an advanced large-aperture ultraviolet, optical, near-infrared (UVOIR) telescope is required to enable the next generation of compelling astrophysics and exoplanet science; and, that present technology is not mature enough to affordably build and launch any potential UVOIR mission concept. AMTD is a multiyear effort to develop, demonstrate and mature critical technologies to TRL-6 by 2018 so that a viable flight mission can be proposed to the 2020 Decadal Review. AMTD builds on the state of art (SOA) defined by over 30 years of monolithic & segmented ground & space-telescope mirror technology to mature six key technologies: center dotLarge-Aperture, Low Areal Density, High Stiffness Mirror Substrates: Both (4 to 8 m) monolithic and (8 to 16 m) segmented telescopes require larger and stiffer mirrors. center dotSupport System: Large-aperture mirrors require large support systems to ensure that they survive launch, deploy on orbit, and maintain a stable, undistorted shape. center dotMid/High Spatial Frequency Figure Error: Very smooth mirror is critical for producing high-quality point spread function (PSF) for high contrast imaging. center dotSegment Edges: The quality of segment edges impacts PSF for high-contrast imaging applications, contributes to stray light noise, and affects total collecting aperture. center dotSegment to Segment Gap Phasing: Segment phasing is critical for producing high-quality temporally-stable PSF. center dotIntegrated Model Validation: On-orbit performance is driven by mechanical & thermal stability. Compliance cannot be 100% tested, but relies on modeling. Because we cannot predict the future, AMTD is pursuing multiple design paths to provide the science community with options to enable either large aperture monolithic or segmented mirrors with clear engineering metrics traceable to science requirements
Defining design alternatives constitutes one of the critical initial steps of the systems engineering process. Once these design alternatives have been identified, assessing which alternatives best satisfy the project’s objectives can prove to be challenging when dealing with complex decision frameworks. Complex systems often involve the participation of different interest groups, who have different value systems and are focused on distinct aspects of the project. For example, design alternatives might be assessed predominantly for their technical merit by one group of stakeholders, while a different group might be more inclined to assess the design alternatives primarily based on programmatic values. MESCAL (Monitoring the Evolving State of Clouds and Aerosol Layers) is an ongoing NASA / CNES (Centre National d’Etudes Spatiales) joint study for an active remote sensing Earth observing satellite. Several design alternatives have been identified and the assessment of these alternatives requires consideration of a variety of factors. This paper presents the approach that was used to support a global assessment of the MESCAL design alternatives. A mapping of the interactions between mission, instrument, and science requirements was modeled to support the assessment of the trade space. In addition, a set of metrics was developed to structure the assessment that was conducted. Finally, this paper also discusses the general applicability of these metrics to other science mission concepts in the formulation phase.
ASTRO2010 Decadal stated that an advanced large-aperture ultraviolet, optical, near-infrared (UVOIR) telescope is required to enable the next generation of compelling astrophysics and exoplanet science; and, that present technology is not mature enough to affordably build and launch any potential UVOIR mission concept. AMTD builds on the state of art (SOA) defined by over 30 years of monolithic & segmented ground & space-telescope mirror technology to mature six key technologies. AMTD is deliberately pursuing multiple design paths to provide the science community with op-tions to enable either large aperture monolithic or segmented mirrors with clear engineering metrics traceable to science requirements.
Distributed Space Missions (DSMs) are gaining momentum in their application to earth observation missions owing to their unique ability to increase observation sampling in multiple dimensions. DSM design is a complex problem with many design variables, multiple objectives determining performance and cost and emergent, often unexpected, behaviors. There are very few open-access tools available to explore the tradespace of variables, minimize cost and maximize performance for pre-defined science goals, and therefore select the most optimal design. This paper presents a software tool that can multiple DSM architectures based on pre-defined design variable ranges and size those architectures in terms of predefined science and cost metrics. The tool will help a user select Pareto optimal DSM designs based on design of experiments techniques. The tool will be applied to some earth observation examples to demonstrate its applicability in making some key decisions between different performance metrics and cost metrics early in the design lifecycle.
The Magnetospheric Multiscale Mission (MMS) is a NASA mission intended to make fundamental advancements in our understanding of the Earth's Magnetosphere. There are three processes that MMS is intended to study including magnetic recon- nection, charged particle acceleration, and turbulence. There are four phases of the MMS mission and each phase is designed to study a particular region of the Earth's magnetosphere. The mission is composed of a formation of four spacecraft that are nominally in a regular tetrahedron formation. In this work, we present optimal orbit designs for Phase I and II. This entails designing optimal reference orbits so that the spacecraft dwell-time in the region of interest is a maximum. This is non-trivial because the Earth's magnetosphere is dynamic and its shape and position are not constant in inertial space. Optimal orbit design for MMS also entails designing the formation so that the relative motion of the four spacecraft yields the greatest science return. We develop performance metrics that are related to the science return, and use Sequential Quadratic Programming (SQP) to determine optimal relative motion solutions. We also ensure that practical constraints such as maximum eclipse time and minimum inter-spacecraft separation distances are not violated.
The Deep Atmosphere Venus Investigation of Noble gases, Chemistry, and Imaging(DAVINCI) mission is currently scheduled to launch in June 2029 to explore Venus via two flybys and a probe descent scheduled for June 2031. The goals of this mission is to study the origin, evolution, and current state of Venus, especially the deep Venusian atmosphere using an atmospheric probe named Zephyr. The Zephyr will take key measurements in the deep atmosphere of Venus and be the first probe to take high-resolution aerial photographs of a mountainous tesserae surface as it descends over the Alpha Regio highlands region, which has the oldest surfaces of Venus. The Zephyr’s descent trajectory, which determines the flight over the Alpha Regio, is crucial to meet the science objectives of the DAVINCI mission. To ensure the success of the DAVINCI mission, the Entry, Descent, and Landing (EDL) modeling has undergone several developments to track its trajectory, its uncertainties, and calculate metrics on the science data that can be transmitted. This paper will cover these developments and the current status of the EDL modeling.
The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will image billions of astronomical objects in the wide–fast–deep primary survey and in a set of minisurveys including intensive observations of a group of deep drilling fields (DDFs). The DDFs are a critical piece of three key aspects of the LSST Dark Energy Science Collaboration (DESC) cosmological measurements: they provide a required calibration for photometric redshifts (photo- z ) and weak gravitational lensing (WL) measurements and they directly contribute to cosmological constraints from the most distant Type Ia supernovae (SNe Ia). We present a set of cohesive DDF strategies fulfilling science requirements relevant to DESC and following the guidelines of the Survey Cadence Optimization Committee. We propose a method to estimate the observing strategy parameters and we perform simulations of the corresponding surveys. We define a set of metrics for each science case to assess the performance of the proposed observing strategies. We show that the most promising results are achieved with deep rolling surveys characterized by two sets of fields: ultradeep fields ( z ≲ 1.1) observed at a high cadence with a large number of visits over a limited number of seasons, and deep fields ( z ≲ 0.7), observed with a cadence of ~3 nights for 10 yr. These encouraging results should be confirmed with realistic simulations using the LSST scheduler. A DDF budget of ~8.5% is required to design observing strategies satisfying all the cosmological requirements. A lower DDF budget leads to surveys that either do not fulfill the photo- z /WL requirements or are not optimal for SN Ia cosmology.
METRIC is a robotic science laboratory that can determine the mineralogy, elemental chemistry, micromorphology, and thermophysical properties of planetary regolith. The METRIC suite comprises METRIC XRD/F, an X-ray diffraction/X-ray fluorescence instrument that can determine the mineralogy and elemental chemistry of regolith samples; METRIC XCT, a micro X-ray computed tomography instrument that can be used to evaluate grain/crystallite sizes and textures; METRIC IRS, an imaging spectrometer mounted on a rover that can determine mineralogy and thermophysical properties at the landing site; and a pneumatic sample collection, processing, distribution system developed by Honeybee Robotics. The payload elements could be deployed on a static lander or a rover. Data returned from the METRIC payload would inform origin, formation, and evolution of rocky planetary bodies. METRIC XRD/F draws on heritage from the CheMin instrument on the Mars Science Laboratory (MSL) Curiosity rover [1], with a few important improvements. Like CheMin, METRIC XRD/F operates in transmission geometry and uses piezoelectric actuators on sample cells in a tuning fork geometry to induce convective grain motion of the regolith to create a randomly oriented powder. MSL CheMin uses an energy-sensitive CCD to collect XRD patterns and XRF spectra simultaneously from the same sample cell, resulting in qualitative XRF data. METRIC XRD/F uses two different sample cells, one optimized for XRD and one optimized for XRF, and a silicon drift detector to detect fluoresced X-rays. This improvement to the XRF capabilities provides quantitative geochemical data of major elements down to Z = 11 and allows for the detection of minor and trace elements that are critical for evaluating geologic evolution of the Moon (e.g., P and Th). Modest improvements to the XRD geometry and hardware allow for better angular resolution and the ability to distinguish between members of the pyroxene group. METRIC XCT uses the same geometry and much of the same hardware as METRIC XRD/F, where a CCD would capture images of a regolith sample in a 3 mm diameter sample tube that is rotated 360° in steps <1°. Image brightness can be used to infer compositional data, where brighter materials indicate a higher Z, much like scanning electron microscopy. Data from METRIC XCT complement those from METRIC XRD/F. Particle size, shape, and texture can provide petrologic and provenance information, whereas vesicle size and morphology in volcanic or impact melt lithologies can inform cooling rates. METRIC IRS is a hyperspectral thermal imager that can be mounted to a lander or rover to provide mineralogical data from the broader landing site and help determine whether the samples analyzed by METRIC XRD/F and XCT are representative. The METRIC IRS spectral range (8–14 μm) and resolution (10.8 cm-1) allow for quantitative mineralogy from modelling Reststrahlen bands of major rock-forming minerals (e.g., silicates, phosphates). Radiance cubes can be processed and modelled with an onboard high-performance computer to determine mineral abundances of plagioclase, high-Ca pyroxene, pigeonite, orthopyroxene, olivine, and glass. Regolith samples can be acquired, processed, and delivered to the X-ray instruments via multiple sample handling systems, but the pneumatic sampling systems developed by Honeybee Robotics [e.g., 2] are best suited for relatively low-cost missions that are being competed for the Moon (e.g., NASA’s Payloads and Research Investigations for the Surface of the Moon program). There are pneumatic sampling systems that collect surface material and other systems that pneumatically drill up to ~1 m below the surface, providing material that has not been space weathered and has not been affected by the lander’s exhaust. [1] Blake, D. F., Vaniman, D., Achilles, C., Anderson, R., Bish, D., et al. (2012). Space Sci. Rev. 170, 341-478. https://doi.org/10.1007/s11214-012-9905-1. [2] Zacny, K., Betts, B., Hedlund, M., Long, P., Gramlich, M., Tura, K., Chu, P., Jacob, A., Garcia, A. (2014). IEEE Aerospace Conference, 3-7 March 2014, Big Sky, MT, U.S.A.
The Magnetospheric Multiscale Mission (MMS) is a NASA mission intended to make fundamental advancements in our understanding of the Earth s magnetosphere. There are three processes that MMS is intended to study including magnetic reconnection, charged particle acceleration, and turbulence. There are four phases of the MMS mission and each phase is designed to study a particular region of the Earth's magnetosphere. The mission is composed of a formation of four spacecraft that are nominally in a regular tetrahedron formation. In this work, we present optimal orbit designs for Phase I and II. This entails designing reference orbits such that the spacecraft dwell-time in the region of interest is a maximum. This is non-trivial because the Earth's magnetosphere is dynamic and its shape and position are not constant in inertial space. Optimal orbit design for MMS also entails designing the formation so that the relative motion of the four spacecraft yields the greatest science return. We develop performance metrics that are directly related to the science return, and use Sequential Quadratic Programming (SQP) to determine optimal relative motion solutions. While designing for optimal science return, we also consider practical constraints such as maximum eclipse time and minimum inter-spacecraft separation distances. Data are presented that illustrates how long we can ensure that the formation remains in the relevant region of the Earth's magnetosphere. We also draw general conclusions about where in the orbit acceptable tetrahedron configurations can be provided and for how long.
The NSF-DOE Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) requires calibration products that provide uniform, stable, and accurate photometric and astrometric performance across the 3.2 gigapixel focal plane and throughout the 10-year survey. This paper details the algorithms and workflows used to produce instrument calibrations and remove instrumental artifacts for Data Preview 2 (DP2)---the first end-to-end processing demonstration using on-sky data with the LSST Camera (LSSTCam). We describe the verification, acceptance, and certification framework used to assess calibration quality and quantify residual systematics. We show baseline metrics on calibrated science images to evaluate the robustness of the calibration and instrument signature removal (ISR) data processing pipelines for DP2. Finally, we summarize the known limitations observed in DP2 production and outline expected algorithmic improvements for the first public LSST data release (Data Release~1, DR1).
One of the most interesting and challenging aspects of formation guidance law design is the coupling of the orbit design and the science return. The analyst s role is more complicated than simply to design the formation geometry and evolution. He or she is also involved in designing a significant portion of the science instrument itself. The effectiveness of the formation as a science instrument is intimately coupled with the relative geoniet,ry and evolution of the collection of spacecraft. Therefore, the science return can be maximized by optimizing the orbit design according to a performance metric relevant to the science mission goals. In this work, we present a simple method for optimal formation guidance that is applicable to missions whose performance metric, requirements, and constraints can be cast as functions that are explicitly dependent upon the orbit states and spacecraft relative positions and velocities. We present a general form for the cost and constraint functions, and derive their semi-analytic gradients with respect to the formation initial conditions. The gradients are broken down into two types. The first type are gradients of the mission specific performance metric with respect to formation geometry. The second type are derivatives of the formation geometry with respect to the orbit initial conditions. The fact that these two types of derivatives appear separately allows us to derive and implement a general framework that requires minimal modification to be applied to different missions or mission phases. To illustrate the applicability of the approach, we conclude with applications to twc missims: the Magnetospheric Mu!tiscale mission (MMS), a,nd the TJaser Interferometer Space Antenna (LISA).
One of the most interesting and challenging aspects of formation guidance law design is the coupling of the orbit design and the science return. The analyst's role is more complicated than simply to design the formation geometry and evolution. He or she is also involved in designing a significant portion of the science instrument itself. The effectiveness of the formation as a science instrument is intimately coupled with the relative geometry and evolution of the collection of spacecraft. Therefore, the science return can be maximized by optimizing the orbit design according to a performance metric relevant to the science mission goals. In this work, we present a simple method for optimal formation guidance that is applicable to missions whose performance metric, requirements, and constraints can be cast as functions that are explicitly dependent upon the orbit states and spacecraft relative positions and velocities. We present a general form for the cost and constraint functions, and derive their semi-analytic gradients with respect to the formation initial conditions. The gradients are broken down into two types. The first type are gradients of the mission specific performance metric with respect to formation geometry. The second type are derivatives of the formation geometry with respect to the orbit initial conditions. The fact that these two types of derivatives appear separately allows us to derive and implement a general framework that requires minimal modification to be applied to different missions or mission phases. To illustrate the applicability of the approach, we conclude with applications to two missions: the Magnetospheric Multiscale mission (MMS) , and the Laser Interferometer Space Antenna (LISA).
Materials science is a central component of early-stage research and development of virtually all clean energy technologies. But as much as material breakthroughs often hold the key to high efficiencies, long lifetimes, and high stability in eventual devices, early-stage choices about material types, structures, and processing can also serve to lock in long-term social and equity impacts of deployed energy technologies. Thus, to achieve a just and sustainable energy transition, tools to assess the energy justice impacts of early-stage materials research are critical. Here, we discuss development of the Justice Underpinning Science and Technology Research (JUST-R) metrics framework - a suite of metrics targeted at early-stage researchers to assess energy justice considerations in their work. The framework is evaluated for its appeal to researchers and effectiveness at promoting integration of energy justice into research through case studies, which reveal its ability to broaden researcher perspectives and key avenues for future improvement.