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In this project, Building America team Building Science Corporation researched some of the ramifications of using exterior, vapor permeable insulation on retrofit walls with vapor permeable cavity insulation. Retrofit strategies are a key factor in reducing exterior building stock consumption.
Moisture management of high-R walls is important to ensure optimal performance. This case study, developed by Building America team Building Science Corporation, focuses on how eight high-R walls handle the three main sources of moisture—construction moisture, air leakage condensation, and bulk water leaks.
In this project, the Building Science Corporation team studied a historic brick building in Lawrence, Massachusetts, which is being renovated into 10 condominium units and adding insulation to the interior side of walls of such masonry buildings.
This case study by the U.S. Department of Energy’s Building America research team Building Science Corporation is a test implementation of an unvented tile roof assembly in a hot-humid climate (Orlando, Florida; zone 2A), insulated with air-permeable insulation (netted and blown fiberglass).
The FINESSE (Field Investigations to Enable Solar System Science and Exploration) team, part of the Solar System Exploration Virtual Institute (SSERVI), is a field-based research program aimed at generating strategic knowledge in preparation for human and robotic exploration of the Moon, near-Earth asteroids, Phobos and Deimos, and beyond. 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. We used the FINESSE field excursion to the West Clearwater Lake Impact structure (WCIS) as an opportunity to test factors related to sampling decisions. We examined the in situ sample characterization and real-time decision-making process of the astronauts, with a guiding hypothesis that pre-mission training that included detailed background information on the analytical fate of a sample would better enable future astronauts to select samples that would best meet science requirements. We conducted three tests of this hypothesis over several days in the field. Our investigation was designed to document processes, tools and procedures for crew sampling of planetary targets. This was not meant to be a blind, controlled test of crew efficacy, but rather an effort to explicitly recognize the relevant variables that enter into sampling protocol and to be able to develop recommendations for crew and backroom training in future endeavors.
During the week of July 23, 2001, a workshop called 'Japan 2001 Science, Creativity and the Young Mind' took place at Bristol University in Bristol, England. Coordinated under the direction of Dr. Eric Albone, Clifton Scientific Trust, it brought together 60 British and Japanese students and provided them with a forum for learning and interacting. We at the NASA Glenn Research Center (GRC) in Cleveland, Ohio, had the good fortune to participate with six of those students and their team leaders in a Space Science Workshop. The Space Science Team was led by two Bristol University people from the Earth Sciences Department - Carsten Riedel and Stuart Stansfield - under the direction of Professor Steve Sparks, FRS. The Team was assisted by Lawrence Williams, Director of Studies, Holy Cross School, UK. Funding was provided by the Daiwa Anglo-Japanese Foundation, the Great Britain Sasakawa Foundation, and Japan 2001. This report is a compilation of correspondence via e-mail that took place before, during, and immediately after the workshop. A final report from the students on their findings is now in production and will be made available from Clifton Scientific Trust.
Operating a one-ton rover on the surface of Mars requires more than just a joystick and an experiment. With 10 science instruments, 17 cameras, a radioisotope thermoelectric generator and lasers, Curiosity is the largest and most complex rover NASA has sent to Mars. Combined with a 1 way light time of 4 to 20 minutes and a distributed international science and engineering team, it takes a lot of work to operate this mega-rover. The Mars Science Lab's operations team has developed an organization and process that maximizes science return and safety of the spacecraft. These are the voyages of the rover Curiosity, its 2 year mission, to determine the habitability of Gale Crater, to understand the role of water, to study the climate and geology of Mars.
Astrobiology missions to ocean worlds in our solar system must overcome both scientific and technological challenges due to extreme temperature and radiation conditions, long communication times, and limited bandwidth. While such tools could not replace ground-based analysis by science and engineering teams, machine learning algorithms could enhance the science return of these missions through development of autonomous science capabilities. Examples of science autonomy include onboard data analysis and subsequent instrument optimization, data prioritization (for transmission), and real-time decision-making based on data analysis. Similar advances could be made to develop streamlined data processing software for rapid ground-based analyses. Here we discuss several ways machine learning and autonomy could be used for astrobiology missions, including landing site selection, prioritization and targeting of samples, classification of “features” (e.g., proposed biosignatures) and novelties (uncharacterized, “new” features, which may be of most interest to agnostic astrobiological investigations), and data transmission.
The Human Exploration Science Office (KX) provides leadership for NASA's Imagery Integration (Integration 2) Team, an affiliation of experts in the use of engineering-class imagery intended to monitor the performance of launch vehicles and crewed spacecraft in flight. Typical engineering imagery assessments include studying and characterizing the liftoff and ascent debris environments; launch vehicle and propulsion element performance; in-flight activities; and entry, landing, and recovery operations. Integration 2 support has been provided not only for U.S. Government spaceflight (e.g., Space Shuttle, Ares I-X) but also for commercial launch providers, such as Space Exploration Technologies Corporation (SpaceX) and Orbital Sciences Corporation, servicing the International Space Station. The NASA Integration 2 Team is composed of imagery integration specialists from JSC, the Marshall Space Flight Center (MSFC), and the Kennedy Space Center (KSC), who have access to a vast pool of experience and capabilities related to program integration, deployment and management of imagery assets, imagery data management, and photogrammetric analysis. The Integration 2 team is currently providing integration services to commercial demonstration flights, Exploration Flight Test-1 (EFT-1), and the Space Launch System (SLS)-based Exploration Missions (EM)-1 and EM-2. EM-2 will be the first attempt to fly a piloted mission with the Orion spacecraft. The Integration 2 Team provides the customer (both commercial and Government) with access to a wide array of imagery options - ground-based, airborne, seaborne, or vehicle-based - that are available through the Government and commercial vendors. The team guides the customer in assembling the appropriate complement of imagery acquisition assets at the customer's facilities, minimizing costs associated with market research and the risk of purchasing inadequate assets. The NASA Integration 2 capability simplifies the process of securing one-of-a-kind imagery assets and skill sets, such as ground-based fixed and tracking cameras, crew-in the-loop imaging applications, and the integration of custom or commercial-off-the-shelf sensors onboard spacecraft. For spaceflight applications, the Integration 2 Team leverages modeling, analytical, and scientific resources along with decades of experience and lessons learned to assist the customer in optimizing engineering imagery acquisition and management schemes for any phase of flight - launch, ascent, on-orbit, descent, and landing. The Integration 2 Team guides the customer in using NASA's world-class imagery analysis teams, which specialize in overcoming inherent challenges associated with spaceflight imagery sets. Precision motion tracking, two-dimensional (2D) and three-dimensional (3D) photogrammetry, image stabilization, 3D modeling of imagery data, lighting assessment, and vehicle fiducial marking assessments are available. During a mission or test, the Integration 2 Team provides oversight of imagery operations to verify fulfillment of imagery requirements. The team oversees the collection, screening, and analysis of imagery to build a set of imagery findings. It integrates and corroborates the imagery findings with other mission data sets, generating executive summaries to support time-critical mission decisions.
The Desert Research and Technology Studies (D-RATS) 2011 field test involved the planning and execution of a series of exploration scenarios under operational conditions similar to those that would be expected during a human exploration mission to a near-Earth asteroid (NEA). The focus was on understanding the operations tempo during simulated NEA exploration and the implications of communications latency and limited data bandwidth. Anchoring technologies and sampling techniques were not evaluated due to the immaturity of those technologies and the inability to meaningfully test them at D-RATS. Reduced gravity analogs and simulations are being used to fully evaluate Multi-Mission Space Exploration Vehicle (MMSEV) and extravehicular (EVA) operations and interactions in near-weightlessness at a NEA as part of NASA s integrated analogs program. Hypotheses were tested by planning and performing a series of 1-day simulated exploration excursions comparing test conditions all of which involved a single Deep Space Habitat (DSH) and either zero, one, or two MMSEVs; three or four crewmembers; one of two different communications bandwidths; and a 100-second roundtrip communications latency between the field site and Houston. Excursions were executed at the Black Point Lava Flow test site with a Mission Control Center and Science Support Room at Johnson Space Center (JSC) being operated with 100-second roundtrip communication latency to the field. Crews were composed of astronauts and professional field geologists and teams of Mission Operations, Science, and Education & Public Outreach (EPO) experts also supported the mission simulations each day. Data were collected separately from the Crew, Mission Operations, Science, and EPO teams to assess the test conditions from multiple perspectives. For the operations tested, data indicates practically significant benefits may be realized by including at least one MMSEV and by including 4 versus 3 crewmembers in the NEA exploration architecture as measured by increased Scientific Data Quality, EVA Exploration Time, Capability Assessment Ratings, and Overall Acceptability ratings by Crew, Mission Operations, Science, and Education & Public Outreach teams. A combination of text and voice was used to effectively communicate over the 100-second roundtrip communications latency and increased communication bandwidth yielded a small but practically significant improvement in Overall Acceptability as rated by the Science team, although the impact of bandwidth on scientific strategic planning was not assessed. No effect of increased bandwidth was observed with respect to Crew, Mission Operations, or EPO team ratings of Overall Acceptability.
During the week of July 23, 2001, a workshop called the Japan 2001 Science, Creativity and the Young Mind took place at Bristol University in Bristol, England. Coordinated by the Clifton Scientific Trust, it brought together 60 British and Japanese students and provided them with a forum for learning and interacting. All the students were chosen from geographical areas of social deprivation, where university education is not seen as a natural progression for students. One of the aims of the workshop was to give the combined group a new view of themselves as potential scientists and an ambition to succeed at the highest level. Members of the Glenn Research Center's Learning Technologies Project participated with six of the students and their team leaders as a Space Science Team. Four interactive videoconferencing sessions were held between the NASA Glenn Research Center and Bristol University on four consecutive days. During the sessions, students raised questions concerning various theories about the probable formation of volcanoes on Mars. Of specific interest was if the great Tharsis volcanoes might be the result of an ancient collision of planetary proportions, or if plate tectonic movement, evidence for which was recently discovered by NASA's Mars Global Surveyor Spacecraft, might account for them.
The Mars Exploration Rover Opportunity has recently completed a two year campaign studying Victoria Crater. The campaign culminated in a close approach of Cape Verde in order to acquire high resolution imagery of the exposed stratigraphy in the cliff face. The close approach to Cape Verde provided significant challenges for every subsystem of the rover as the rover needed to traverse difficult, uncharacterised terrain and approach a cliff face with the potential of blocking out solar energy and communications with Earth. In this paper we describe the strategic analyses performed by the science and engineering teams so that we could successfully achieve the science objectives while keeping the rover safe.
In 2001, NASA Goddard Space Flight Center's Laboratory for Terrestrial Physics started the construction of a science Investigator-led Processing System (SIPS) for processing data from the Ozone Monitoring Instrument (OMI) which will launch on the Aura platform in mid 2004. The Ozone Monitoring Instrument (OMI) is a contribution of the Netherlands Agency for Aerospace Programs (NIVR) in collaboration with the Finnish Meteorological Institute (FMI) to the Earth Observing System (EOS) Aura mission. It will continue the Total Ozone Monitoring System (TOMS) record for total ozone and other atmospheric parameters related to ozone chemistry and climate. OMI measurements will be highly synergistic with the other instruments on the EOS Aura platform. The LTP previously developed the Moderate Resolution Imaging Spectrometer (MODIS) Data Processing System (MODAPS), which has been in full operations since the launches of the Terra and Aqua spacecrafts in December, 1999 and May, 2002 respectively. During that time, it has continually evolved to better support the needs of the MODIS team. We now run multiple instances of the system managing faster than real time reprocessings of the data as well as continuing forward processing. The new OMI Data Processing System (OMIDAPS) was adapted from the MODAPS. It will ingest raw data from the satellite ground station and process it to produce calibrated, geolocated higher level data products. These data products will be transmitted to the Goddard Distributed Active Archive Center (GDAAC) instance of the Earth Observing System (EOS) Data and Information System (EOSDIS) for long term archive and distribution to the public. The OMIDAPS will also provide data distribution to the OMI Science Team for quality assessment, algorithm improvement, calibration, etc. We have taken advantage of lessons learned from the MODIS experience and software already developed for MODIS. We made some changes in the hardware system organization, database and software to adapt the system for OMI. We replaced the fundamental database system, Sybase, with an Open Source RDBMS called PostgreSQL, and based the entire OMIDAPS on a cluster of Linux based commodity computers rather than the large SGI servers that MODAPS uses. Rather than relying on a central I/O server host, the new system distributes its data archive among multiple server hosts in the cluster. OMI is also customizing the graphical user interfaces and reporting structure to more closely meet the needs of the OMI Science Team. Prior to 2003, simulated OMI data and the science algorithms were not ready for production testing. We initially constructed a prototype system and tested using a 25 year dataset of Total Ozone Mapping Spectrometer (TOMS) and Solar Backscatter Ultraviolet Instrument (SBUV) data. This prototype system provided a platform to support the adaptation of the algorithms for OMI, and provided reprocessing of the historical data aiding in its analysis. In a recent reanalysis of the TOMS data, the OMIDAPS processed 108,000 full orbits of data through 4 processing steps per orbit, producing about 800,000 files (400 GiB) of level 2 and greater data files. More recently we have installed two instances of the OMIDAPS for integration and testing of OM1 science processes as they get delivered from the Science Team. A Test instance of the OMIDAPS has also supported a series of "Interface Confidence Tests" (ICTs) and End-to-End Ground System tests to ensure the launch readiness of the system. This paper will discuss the high-level hardware, software, and database organization of the OMIDAPS and how it builds on the MODAPS heritage system. It will also provide an overview of the testing and implementation of the production OMIDAPS.
The Jet Propulsion Laboratory Innovation Foundry has established a new approach for exploring, developing, and evaluating early concepts with a group called the Architecture Team. The Architecture Team combines innovative collaborative methods and facilitated sessions with subject matter experts and analysis tools to help mature mission concepts. Science, implementation, and programmatic elements are all considered during an A-Team study. In these studies, Concept Maturity Levels are used to group methods. These levels include idea generation and capture (Concept Maturity Level 1), initial feasibility assessment (Concept Maturity Level 2), and trade space exploration (Concept Maturity Level 3). Methods used for exploring the science objectives, feasibility, and scope will be described including the use of a new technique for understanding the most compelling science, called a Science Return Diagram. In the process of developing the Science Return Diagram, gradients in the science trade space are uncovered along with their implications for implementation and mission architecture. Special attention is paid toward developing complete investigations, establishing a series of logical claims that lead to the natural selection of a measurement approach. Over 20 science-focused A-Team studies have used these techniques to help science teams refine their mission objectives, make implementation decisions, and reveal the mission concept's most compelling science. This article will describe the A-Team process for exploring the mission concept's science trade space and the Science Return Diagram technique.
The FINESSE (Field Investigations to Enable Solar System Science and Exploration) team of NASA's Solar System Exploration Research Virtual Institute (SSERVI) is 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, and the moons of Mars. The FINESSE science program is infused with leading edge exploration concepts since "science enables exploration and exploration enables science." The FINESSE education and public outreach program leverages the team's field investigations and educational partnerships to share the excitement of lunar, Near Earth Asteroid, and martian moon science and exploration locally, nationally, and internationally. The FINESSE education plan is in line with all of NASA's Science Mission Directorate science education objectives, particularly to enable STEM (science, technology, engineering, and mathematics) education and leverage efforts through partnerships.
A long-term approach to achieving equity in the energy efficiency industry is to increase the overall diversity of the professionals who work in the field. Building science professionals have a direct impact on energy efficiency policy and programs, as many become leaders within the industry. Buildings are used every day by almost all members of U.S. society, so diversity in building science professionals is critical to better understanding the behaviors and needs of the full spectrum of building occupants. Many groups of people, including minorities and women, are underrepresented in the industry. The industry needs to attract a wide range of current college and university students to careers in building science, so that many perspectives are included in the clean energy transition. The JUMP into STEM student competition addresses this need by inspiring students from diverse backgrounds to use creative ideation to solve real-world building science problems. Student teams - comprising an interdisciplinary mix of majors and underrepresented groups in science, technology, engineering, and math (STEM) - respond to one of three buildings-related challenges. Diversity is encouraged through challenge design, competition guidelines, and evaluation criteria for the submission. Winners of the competition are awarded paid building science internships, a gateway to a career in this field. The competition has an advisory panel of diversity experts and a professor team that includes representation from minority-serving institutions. This paper presents the JUMP into STEM approach to fostering diversity and creative ideation on technical challenges and discusses outcomes from the 2019 and 2020 competitions.
During the post-launch SMAP calibration and validation (Cal/Val) phase there are two objectives for each science data product team: 1) calibrate, verify, and improve the performance of the science algorithm, and 2) validate the accuracy of the science data product as specified in the science requirements and according to the Cal/Val schedule. This report provides an assessment of the SMAP Level 4 Surface and Root Zone Soil Moisture Passive (L4_SM) product specifically for the product's public Version 2 validated release scheduled for 29 April 2016. The assessment of the Version 2 L4_SM data product includes comparisons of SMAP L4_SM soil moisture estimates with in situ soil moisture observations from core validation sites and sparse networks. The assessment further includes a global evaluation of the internal diagnostics from the ensemble-based data assimilation system that is used to generate the L4_SM product. This evaluation focuses on the statistics of the observation-minus-forecast (O-F) residuals and the analysis increments. Together, the core validation site comparisons and the statistics of the assimilation diagnostics are considered primary validation methodologies for the L4_SM product. Comparisons against in situ measurements from regional-scale sparse networks are considered a secondary validation methodology because such in situ measurements are subject to up-scaling errors from the point-scale to the grid cell scale of the data product. Based on the limited set of core validation sites, the wide geographic range of the sparse network sites, and the global assessment of the assimilation diagnostics, the assessment presented here meets the criteria established by the Committee on Earth Observing Satellites for Stage 2 validation and supports the validated release of the data. An analysis of the time average surface and root zone soil moisture shows that the global pattern of arid and humid regions are captured by the L4_SM estimates. Results from the core validation site comparisons indicate that "Version 2" of the L4_SM data product meets the self-imposed L4_SM accuracy requirement, which is formulated in terms of the ubRMSE: the RMSE (Root Mean Square Error) after removal of the long-term mean difference. The overall ubRMSE of the 3-hourly L4_SM surface soil moisture at the 9 km scale is 0.035 cubic meters per cubic meter requirement. The corresponding ubRMSE for L4_SM root zone soil moisture is 0.024 cubic meters per cubic meter requirement. Both of these metrics are comfortably below the 0.04 cubic meters per cubic meter requirement. The L4_SM estimates are an improvement over estimates from a model-only SMAP Nature Run version 4 (NRv4), which demonstrates the beneficial impact of the SMAP brightness temperature data. L4_SM surface soil moisture estimates are consistently more skillful than NRv4 estimates, although not by a statistically significant margin. The lack of statistical significance is not surprising given the limited data record available to date. Root zone soil moisture estimates from L4_SM and NRv4 have similar skill. Results from comparisons of the L4_SM product to in situ measurements from nearly 400 sparse network sites corroborate the core validation site results. The instantaneous soil moisture and soil temperature analysis increments are within a reasonable range and result in spatially smooth soil moisture analyses. The O-F residuals exhibit only small biases on the order of 1-3 degrees Kelvin between the (re-scaled) SMAP brightness temperature observations and the L4_SM model forecast, which indicates that the assimilation system is largely unbiased. The spatially averaged time series standard deviation of the O-F residuals is 5.9 degrees Kelvin, which reduces to 4.0 degrees Kelvin for the observation-minus-analysis (O-A) residuals, reflecting the impact of the SMAP observations on the L4_SM system. Averaged globally, the time series standard deviation of the normalized O-F residuals is close to unity, which would suggest that the magnitude of the modeled errors approximately reflects that of the actual errors. The assessment report also notes several limitations of the "Version 2" L4_SM data product and science algorithm calibration that will be addressed in future releases. Regionally, the time series standard deviation of the normalized O-F residuals deviates considerably from unity, which indicates that the L4_SM assimilation algorithm either over- or under-estimates the actual errors that are present in the system. Planned improvements include revised land model parameters, revised error parameters for the land model and the assimilated SMAP observations, and revised surface meteorological forcing data for the operational period and underlying climatological data. Moreover, a refined analysis of the impact of SMAP observations will be facilitated by the construction of additional variants of the model-only reference data. Nevertheless, the “Version 2” validated release of the L4_SM product is sufficiently mature and of adequate quality for distribution to and use by the larger science and application communities.
The Stratospheric Aerosol and Gas Experiment III on the International Space Station (SAGE III/ISS) was delivered to the International Space Station (ISS) on 23 February 2017. The SAGE III/ISS payload was robotically installed external to the ISS and began acquiring science measurements on 17 March 2017. The SAGE III/ISS instrument retrieves vertical profiles of atmospheric ozone, multi-wavelength aerosol extinctions, and other gaseous species. This paper will focus on the improvements made to the operations of the SAGE III/ISS payload. A key focus of the operations team following commissioning was to create robust tools that aid in the operations of the payload. A close collaboration with the SAGE III/ISS ground systems team allowed for the development of web-based tools to continuously monitor the health of the payload. The mission operations team also worked with the SAGE III/ISS science team to gain a better sense of how the instrument works to maximize the quality and quantity of the science data collected. Another unique aspect of the SAGE III/ISS payload, that will be discussed, is the challenges of operating a hosted payload on the ISS; an active platform that has frequent attitude maneuvers, dockings, and EVAs. This active environment increases the need for the SAGE III/ISS operations team command to the payload. Through coordination and teamwork, SAGE III/ISS mission has developed an operations team, tool, and procedures that have successfully managed the payload around ISS activities and recovered from multiple instrument upsets. This has led the SAGE III/ISS payload to successfully surpass the acquisition metrics set forth prior to launch, allowing for the continued contribution to studying the atmospheric composition of the stratosphere and how it plays a role in Earth’s climate.