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At least 361 records · Page 20

The Lunar Regolith Terrain (LRT) Field: A New Lunar Surface Planetary Analog Facility at NASA Marshall Space Flight Center (MSFC)

Introduction: NASA is moving toward a new age of exploration and resource utilization of the lunar surface. Challenges related to exploration, resource utilization, and construction at the Lunar South Pole will require advanced technology and well-designed mission concepts and operations. NASA Marshall Space Flight Center (MSFC) has added new capabilities to support surface mobility and construction activities to meet industry, academia, and NASA research and development goals for lunar applications. The Lunar Regolith Terrain (LRT) field is a new, large-area, lunar regolith simulant planetary analog testing ground for users interested in surface mobility and lunar construction activities. The LRT complements NASA MSFC’s other lunar environment testing facilities such as the Lunar Surface Simulator (V20 dirty vacuum chamber), the Lunar Environment Testing System (LETS), among many others. Lunar Regolith Terrain (LTR) Description: The Lunar Regolith Terrain field is an outdoor planetary analog environment facility located on base at MSFC. The lunar regolith simulant is JSC-1A feedstock material (volcanic cinder sand sourced from Meriam Crater, Flagstaff, AZ). The field contains more than 500 tons of lunar regolith simulant confined within a 125 ft x 125 ft (38 m x 38 m) area. The field is placed ~ 50% over paved parking lot and ~ 50% over a natural ground. Currently, the depth of regolith ranges between ~ 5 in - ~ 4 ft (~ 13cm – 1.2m) but can be modified to suit user needs. The lunar regolith simulant that makes up the field has representative geotechnical, geochemical, and optical properties of lunar mare basalt. An area within the LRT of lunar highlands terrain simulant is planned. Additional Features of the LRT: The LRT was designed to allow rapid modification of the terrain’s topography obstacles in the field. The terrain can be reshaped to suit specific testing requirements that may require flat expanses, steep hills, or heavily cratered and rocky landscapes. Large rocky obstacles in Fig. 1 are artificial landscape boulders (faux-rocks) that can be easily placed by users or removed entirely. Areas of the field also contain buried fiducials, large sheets, bar stock, and pipes of various composition and dimensions to allow for possible ground penetrating radar and shallow seismic studies. Rapid modification capabilities will also allow for burial of additional user-specific materials to enable in-situ resource utilization detection (e.g., burial of hydrogen sources for neutron detection or other materials). The field is also equipped with on-site office space with an air-conditioned and heated trailer with 120/240V power and lighting. The site has Wi-Fi and Cellular signal coverage. Direct radio frequency communication with the Huntsville Operations Support Center (HOSC) is in development. Additional on-site workspace and secure equipment storage is available in adjacent buildings. Accessibility to the field is straightforward with on-site parking and access for delivery of instruments, payloads, and additional equipment. Community Availability: The LRTF provides an accessible planetary analog surface environment for surface mobility testing, autonomous roving operations, developing advanced navigation techniques and operations development. Interested parties can contact the abstract authors for additional details, tours, and scheduling.

Lunar Regolith↗

Spatial and Seasonal Patterns of the Mosquito Community in Central Oklahoma

Mosquitoes (Culicidae) are ubiquitous flying insects that function as vectors for several viruses that cause disease in humans. Mosquito abundance and diversity are influenced by landscape features and environmental factors such as temperature and precipitation and vary across seasons and years. The range and phenology of many mosquito species that vector viruses relevant to human health are changing. We sampled mosquito communities in central Oklahoma for four years at thirteen sites, collecting over 25,000 mosquitoes; among these, we identified 27 different species, including several that transmit human pathogens and were collected in suburban backyards. Community composition differed across the landscape and changed from early season to late season and year to year. This effort to describe mosquito communities in Oklahoma is a first step toward assessing and predicting arbovirus risk, an ongoing and dynamic public health challenge.

David Hoekman↗

Marshall Space Flight Center: Lunar Regolith Terrain (LRT)

Introduction: NASA is moving toward a new age of exploration and resource utilization of the lunar surface. Challenges related to exploration, resource utilization, and construction at the Lunar South Pole will require advanced technology and well-designed mission concepts and operations. NASA Marshall Space Flight Center (MSFC) has added new capabilities to support surface mobility and construction activities to meet industry, academia, and NASA research and development goals for lunar applications. The Lunar Regolith Terrain (LRT) field is a new, large-area, lunar regolith simulant planetary analog testing ground for users interested in surface mobility and lunar construction activities. The LRT complements NASA MSFC’s other lunar environment testing facilities such as the Lunar Surface Simulator (V20 dirty vacuum chamber), the Lunar Environment Testing System (LETS), among many others. Lunar Regolith Terrain (LTR) Description: The Lunar Regolith Terrain field is an outdoor planetary analog environment facility located on base at MSFC. The lunar regolith simulant is JSC-1A feedstock material (volcanic cinder sand sourced from Meriam Crater, Flagstaff, AZ). The field contains more than 500 tons of lunar regolith simulant confined within a 125 ft x 125 ft (38 m x 38 m) area. The field is placed ~ 50% over paved parking lot and ~ 50% over a natural ground. Currently, the depth of regolith ranges between ~ 5 in - ~ 4 ft (~ 13cm – 1.2m) but can be modified to suit user needs. The lunar regolith simulant that makes up the field has representative geotechnical, geochemical, and optical properties of lunar mare basalt. An area within the LRT of lunar highlands terrain simulant is planned. Additional Features of the LRT: The LRT was designed to allow rapid modification of the terrain’s topography obstacles in the field. The terrain can be reshaped to suit specific testing requirements that may require flat expanses, steep hills, or heavily cratered and rocky landscapes. Large rocky obstacles in Fig. 1 are artificial landscape boulders (faux-rocks) that can be easily placed by users or removed entirely. Areas of the field also contain buried fiducials, large sheets, bar stock, and pipes of various composition and dimensions to allow for possible ground penetrating radar and shallow seismic studies. Rapid modification capabilities will also allow for burial of additional user-specific materials to enable in-situ resource utilization detection (e.g., burial of hydrogen sources for neutron detection or other materials). The field is also equipped with on-site office space with an air-conditioned and heated trailer with 120/240V power and lighting. The site has Wi-Fi and Cellular signal coverage. Direct radio frequency communication with the Huntsville Operations Support Center (HOSC) is in development. Additional on-site workspace and secure equipment storage is available in adjacent buildings. Accessibility to the field is straightforward with on-site parking and access for delivery of instruments, payloads, and additional equipment. Community Availability: The LRTF provides an accessible planetary analog surface environment for surface mobility testing, autonomous roving operations, developing advanced navigation techniques and operations development. Interested parties can contact the abstract authors for additional details, tours, and scheduling.

Lunar Regolith↗

Size and Structure of the Sequence Space of Repeat Proteins

The coding space of protein sequences is shaped by evolutionary constraints set by requirements of function and stability. We show that the coding space of a given protein family— the total number of sequences in that family—can be estimated using models of maximum entropy trained on multiple sequence alignments of naturally occurring amino acid sequences. We analyzed and calculated the size of three abundant repeat proteins families, whose members are large proteins made of many repetitions of conserved portions of *30 amino acids. While amino acid conservation at each position of the alignment explains most of the reduction of diversity relative to completely random sequences, we found that correlations between amino acid usage at different positions significantly impact that diversity. We quantified the impact of different types of correlations, functional and evolutionary, on sequence diversity. Analysis of the detailed structure of the coding space of the families revealed a rugged landscape, with many local energy minima of varying sizes with a hierarchical structure, reminiscent of frustrated energy landscapes of spin glass in physics. This clustered structure indicates a multiplicity of subtypes within each family and suggests new strategies for protein design.

Jacopo Marchi↗

Marshall Space Flight Center: Lunar Regolith Terrain (LRT)

Introduction: NASA is moving toward a new age of exploration and resource utilization of the lunar surface. Challenges related to exploration, resource utilization, and construction at the Lunar South Pole will require advanced technology and well-designed mission concepts and operations. NASA Marshall Space Flight Center (MSFC) has added new capabilities to support surface mobility and construction activities to meet industry, academia, and NASA research and development goals for lunar applications. The Lunar Regolith Terrain (LRT) field is a new, large-area, lunar regolith simulant planetary analog testing ground for users interested in surface mobility and lunar construction activities. The LRT complements NASA MSFC’s other lunar environment testing facilities such as the Lunar Surface Simulator (V20 dirty vacuum chamber), the Lunar Environment Testing System (LETS), among many others. Lunar Regolith Terrain (LTR) Description: The Lunar Regolith Terrain field is an outdoor planetary analog environment facility located on base at MSFC. The lunar regolith simulant is JSC-1A feedstock material (volcanic cinder sand sourced from Meriam Crater, Flagstaff, AZ). The field contains more than 500 tons of lunar regolith simulant confined within a 125 ft x 125 ft (38 m x 38 m) area. The field is placed ~ 50% over paved parking lot and ~ 50% over a natural ground. Currently, the depth of regolith ranges between ~ 5 in - ~ 4 ft (~ 13cm – 1.2m) but can be modified to suit user needs. The lunar regolith simulant that makes up the field has representative geotechnical, geochemical, and optical properties of lunar mare basalt. An area within the LRT of lunar highlands terrain simulant is planned. Additional Features of the LRT: The LRT was designed to allow rapid modification of the terrain’s topography obstacles in the field. The terrain can be reshaped to suit specific testing requirements that may require flat expanses, steep hills, or heavily cratered and rocky landscapes. Large rocky obstacles in Fig. 1 are artificial landscape boulders (faux-rocks) that can be easily placed by users or removed entirely. Areas of the field also contain buried fiducials, large sheets, bar stock, and pipes of various composition and dimensions to allow for possible ground penetrating radar and shallow seismic studies. Rapid modification capabilities will also allow for burial of additional user-specific materials to enable in-situ resource utilization detection (e.g., burial of hydrogen sources for neutron detection or other materials). The field is also equipped with on-site office space with an air-conditioned and heated trailer with 120/240V power and lighting. The site has Wi-Fi and Cellular signal coverage. Direct radio frequency communication with the Huntsville Operations Support Center (HOSC) is in development. Additional on-site workspace and secure equipment storage is available in adjacent buildings. Accessibility to the field is straightforward with on-site parking and access for delivery of instruments, payloads, and additional equipment. Community Availability: The LRTF provides an accessible planetary analog surface environment for surface mobility testing, autonomous roving operations, developing advanced navigation techniques and operations development. Interested parties can contact the abstract authors for additional details, tours, and scheduling.

Lunar Regolith↗

Patterns and Controls on Island-Wide Aboveground Biomass Accumulation in Second-Growth Forests of Puerto Rico

Understanding the heterogeneity of biomass accumulation in second-growth tropical forests following land use abandonment is important for informing ecosystem carbon models and forest restoration efforts. There is an urgent need for a broad sample of second-growth forests to enhance our knowledge of carbon accumulation in human-dominated landscapes, especially for older forests. Puerto Rico has predominantly second-growth forests, ranging in age from approximately 25 to more than 80 years. We used an island-wide sample of airborne lidar from the NASA Goddard Lidar, Hyperspectral, and Thermal (G-LiHT) Airborne Imager collected on March 2017, forest inventory data, and data on forest age, precipitation, soils, and land use to estimate aboveground biomass stocks in moist and wet, second-growth tropical forests. Biomass accumulation rates in Puerto Rico were lower, on average, than in other Neotropical forests. Median biomass across >16,700 ha of older second-growth forests was 105 Mg ha−1, and sampled biomass rarely surpassed 250 Mg ha−1. Differences in biomass by age were large and persistent across different substrates and land uses, with a plateau in the pattern of island-wide biomass accumulation after about 33 years. A spatial regression model showed that multiple factors were related to biomass accumulation, including time since abandonment, geologic substrate, past land use as coffee or pasture, precipitation, topographic wetness index, and slope. Our findings have important consequences for the total carbon storage and expected climate mitigation benefits of large-scale reforestation efforts, and highlight the value of airborne lidar for quantifying biomass variability in complex tropical landscapes.

Sebastián Martinuzzi↗

Creating Gridded Fire Probability Maps using NASA Data

Fire is a nationally and globally significant process that strongly affects human–dominated and wild landscapes. Even though fire can be devastating, wildland fire is a natural and integral force on our landscapes, providing value by decreasing fuels at the Wildland Urban Interface (WUI) to promote safe communities. However, uncontained wildfires can devastate communities, threaten our health, and result in substantial economic losses. There has been greater than a $50B increase in wildfire insurance claims from 2017-2021, which has been exacerbated by climate change. Our partners at Kettle reinsurance are focused on building a smarter reinsurance model for protecting today’s globalized world from the catastrophic effects of climate change. Our objective is to develop the world's first grid-based wildfire probability product using multiple sources of satellite data to determine whether a ‘conflagration' (fire larger than 999+ acres) has ‘breached’ a grid cell. This will substantially decrease the time it takes for homeowners to receive payouts, from over a year to a couple months. Working with our partners at Kettle reinsurance, we use multiple satellites and ancillary data to weigh the likelihood of fire, based on a number of sources that verify a fire burning in a grid cell and the level of confidence in the data source. For example, Sentinel-2 vegetation-change indices have a higher level of confidence than VIIRS (Visible Infrared Imaging Radiometer Suite) active-fire detection data; and VIIRS active-fire detection data have a higher-level of confidence than MODIS (Moderate Resolution Imaging Spectroradiometer) active-fire detection data. The first iteration has been developed for responding to wildfires in California, with the possibility to expand nationwide and globally.

Emily Gargulinski↗

Northeast Alaska Climate: Using Earth Observations to Evaluate Snow Variability through a Climatological Analysis to Support Ecological Monitoring in Northeast Alaska

Alaska is experiencing climate change at an unprecedented rate, with temperatures increasing twice as fast as the national average. The resulting changes to the landscape and ecosystems are significant, including shorter winters, declining snow depth, thawing permafrost, and rapidly receding glaciers. These changes are not only exacerbating the negative impacts of oil exploration but also affecting the food security of indigenous communities that rely on hunting as a subsistence food source. With the US Fish and Wildlife Service managing a potential tundra travel season for the first time in its history, adequate data on historic snow variables is essential to protect the unique habitat of the area. This project used NASA satellite and assimilation system data to inform and improve the current understanding of snow patterns in the Arctic National Wildlife Refuge and the National Petroleum Reserve – Alaska. The DEVELOP team used MODIS Normalized Difference Snow Index data to determine snow season duration, snow change frequency, and the first and last days of snow. The team also utilized the 2.1 Global Land Data Assimilation System and Daymet V4 products to study climatological trends in snow depth and snow water equivalent, respectively, across the study areas. The results of this study give users the capacity to visualize maps of multiple snow variables to monitor changes in snow conditions and proactively prepare for the ecological, cultural, and landscape impacts that changes in snow variability will cause in the future.

Remote Sensing↗

Gender Diversity in Heliophysics

Science is conducted by people. When those people do not feel safe in their workplace, they will struggle to produce quality science. The American scientific community has traditionally been dominated by cisgender white men–cisgender meaning that their gender aligns with the one assigned to them at birth. Individuals who are not part of this dominant demographic group have historically been excluded from scientific debate. However, the demographic landscape is changing rapidly [e.g., Jones (2022)], and organizations must ensure early career scientists of all identities feel accepted so they can achieve their goals in the field. Heliophysics describes the confluence and interaction of historically delineated scientific disciplines, including plasma, solar, and space physics. The scientific architecture of our field is founded on collaboration between people with diverse interests, backgrounds, skill sets, and ways of approaching problems. It should follow that the cohort of heliophysicists is at least as diverse as our research problems. A framing often referred to as “the business case” for diversity holds that perspectives different than our own enrich the ways in which we solve problems and communicates the positive outcomes for diverse working groups Starck et al. (2021). However, this rationale is insufficient in scope and uncompassionate in motivation; the safety of marginalized individuals is just as important as the achievements of a group. From the expectations that marginalized people outperform in order to prove themselves to the tokenization of their inclusion in an otherwise normative space, the “business case” for diversity is often harmful to historically marginalized individuals Haacker et al. (2022). The primary motivation for a diverse constituency of heliophysicists ought to be equity. Only by accepting the authentic selves of our fellow heliophysicists can we create an environment in which they have the mental and emotional safety necessary to do their best work. This white paper focuses on a particular axis of identity which the authors believe lacks visibility within heliophysics: gender expansion. It begins with definitions, explains the current landscape, and suggests actions toward a better future. The authors seek to shed light on these issues so that we can work together as a community to create a more inclusive, safe, and welcoming space for people of all identities.

M. Kenny↗

Global Carbon Consumption Database for Wildland Fire

Fire plays a significant role on both national and global scales, profoundly impacting landscapes shaped by human activity as well as those left wild. Even though fire can be devastating, wildland fire is a natural and integral force on our landscapes. Fires can also serve to reduce fuels to mitigate wildfire risk and maintain healthy ecosystem functions. However, the smoke produced by fires, regardless of their size or purpose, can pose adverse effects on human health when inhaled downwind. Understanding the influence of smoke on air quality and human well-being necessitates the quantification of emissions that fires release into the atmosphere. In response to this need, we have established a comprehensive global consumption database directly linked to distinct fuels within various fire danger categories. This database, featuring a spatial resolution of approximately 300 meters, builds upon the foundations of the Pettinari, M. Lucrecia (2015) Global Fuelbed database, a global fuel map with standardized Fuel Characteristic Classification System (FCCS) biomass parameters. Consumption is broken down into five Fire Danger categories (Low, Moderate, High, Very High, Extreme), for both ‘new’ and ‘residual’ burning scenarios. We define ‘residual burned area’ as area burning in a region that has burned on a previous day for the same fire season, and ‘new burned area’ as area burning in a region that has not recently burned. This product serves as a valuable tool when used in conjunction with burned area data to rapidly estimate the carbon consumed and released into the atmosphere. Previously, we developed a similar emissions method utilizing satellite information, in conjunction with the FCCS 30-meter United States fuelbed dataset. We implemented this approach on fires, documented during the 2019 Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) campaign to estimate daily carbon emissions. Our emissions estimates were rigorously compared against in-situ measurements of CO2, CO, and black carbon aerosols, revealing a robust agreement between the two datasets.

Emily Gargulinski↗

CONUS and Global Carbon Consumption Database for Wildland Fire

Fire plays a significant role on both national and global scales, profoundly impacting landscapes shaped by human activity as well as wildlands. Even though fire can be devastating, wildland fire is a natural and integral force on our landscapes. Fires can also serve to reduce fuels to mitigate wildfire risk and maintain healthy ecosystem functions. However, the smoke produced by fires, regardless of their size or purpose, can pose adverse effects on human health when inhaled downwind. Understanding the influence of smoke on air quality and human well-being necessitates the quantification of emissions that fires release into the atmosphere. In response to this need, we have developed a carbon consumption database for the Continental United States (CONUS) and are developing a global carbon consumption database, both of which are directly link to distinct fuels within various fire danger categories. Fuel Characteristic Classification System (FCCS) fuels are used to parameterize biomass, and consumption is broken down into five Fire Danger categories (Low, Moderate, High, Very High, Extreme), for both ‘new’ and ‘residual’ burning scenarios. Residual burned area is defined as burning in areas that have recently burned. We implemented the FCCS 30-meter CONUS fuelbed dataset during the 2019 Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) campaign to estimate daily carbon emissions. Our emissions estimates were rigorously compared against in-situ measurements of CO2, CO, and black carbon aerosols, revealing a robust agreement between the two datasets. The 300-meter global database builds upon the foundations of the Pettinari, M. Lucrecia (2015) Global Fuelbed database, a global fuel map with standardized FCCS biomass parameters. These products can serve as valuable tools when used in conjunction with burned area data to rapidly and accurately estimate carbon consumed and released into the atmosphere.

FCCS↗

Physics-Guided Deep Learning for Complex System Health Management and Decision Making

The landscape of complex engineered systems is rapidly evolving, from smart manufacturing facilities to next-generation transportation vehicles. As these systems become increasingly sophisticated and interconnected, the need for advanced health management systems grows ever more critical. These systems must go beyond simple monitoring, actively predicting potential failures before they occur. This paradigm shift from fixed maintenance schedules to condition-based predictions is key to optimizing system performance, enhancing safety, and paving the way for autonomous decision-making across various industries. Whether in industrial processes, energy systems, or advanced transportation, the ability to anticipate and prevent failures is becoming a cornerstone of operational excellence. To accurately predict the future health of any complex system, knowledge of its current health state and future operational conditions is essential. Recent advancements in data-driven algorithms have generated growing interest in artificial intelligence for industrial applications. However, the limitations of pure data-driven methods, particularly in industries where data acquisition is costly and limited, have become apparent. This has led to a focus on blending physics with data-driven algorithms, mitigating the drawbacks of both approaches while emphasizing their respective advantages. This research proposes a novel framework for integrating physics-based performance models with deep learning algorithms for the prognostics of complex safety-critical systems. In this approach, physics-based models serve as a blueprint, capturing fundamental system behaviors, while deep learning algorithms, leveraging real-world sensor data, fill in gaps and identify subtle patterns indicative of potential problems. This hybrid methodology, utilizing techniques such as Physics-Informed Neural Networks (PINNs), offers a powerful solution for predicting system health. By fusing domain knowledge with data-driven insights, this approach promises more accurate, adaptable, and reliable models for health prediction. The resulting framework is versatile, applicable across various sectors including aerospace, manufacturing, and energy systems, ultimately contributing to safer, more efficient operations in our increasingly complex technological landscape.

Diagnostics↗

Automated Knowledge Discovery from Simulators

In this paper, we explore one aspect of knowledge discovery from simulators, the landscape characterization problem, where the aim is to identify regions in the input/ parameter/model space that lead to a particular output behavior. Large-scale numerical simulators are in widespread use by scientists and engineers across a range of government agencies, academia, and industry; in many cases, simulators provide the only means to examine processes that are infeasible or impossible to study otherwise. However, the cost of simulation studies can be quite high, both in terms of the time and computational resources required to conduct the trials and the manpower needed to sift through the resulting output. Thus, there is strong motivation to develop automated methods that enable more efficient knowledge extraction.

landscapes↗

Frustration in Fuzzy Protein Complexes Leads to Interaction Versatility

Disordered proteins frequently serve as interaction hubs involving a constrained variety of partners. Complexes with different partners frequently exhibit distinct binding modes, involving regions that remain disordered in the bound state. While the conformational properties of disordered proteins are well-characterized in their free states, less is known about the molecular mechanisms by which specificity can be achieved not with one but with multiple partners. Using the energy landscape theory concept of protein frustration, we demonstrate that complexes of disordered proteins exhibit a high degree of local frustration, especially at the binding interface. These suboptimal interactions lead to the possibility of multiple bound substates, each displaying distinct frustration patterns, which are differently populated in complexes with different partners. These results explain how specificity of disordered proteins can be achieved without a single common bound conformation and how the conflict between different interactions can be used to control the binding to multiple partners.

Chemical specificity↗

INTERNATIONAL COOPERATION IN SPACE

In the community of nations there exists today a deep and wide abyss separating one important and powerful group of nations from another. The political and philosophical differences which constitute this abyss are very real and very fundamental, and they are not likely to disappear during this century. There are smaller canyons in the landscape as well, some more permanent than others. However, it is possible to build bridges of culture, science, and cooperative effort of many kinds across these canyons so that men of good will from one side may mingle freely with those from the other side, and for a little while, at least, be as one people. Scientists have been helping to build bridges like this for a long time. Especially prominent in this sort of activity has been the International Council of Scientific Unions (ICSU) which was the mother hen, so to speak, of the International Geophysical Year. At present, problems of international cooperation in space research are the concern of a Special Committee of the International Council of Scientific Unions, known as COSPAR (Committee on Space Research).

SPACE EXPLORATION↗

Radar as a tool for regional investigations

Radar is considered as a means for delimiting associations of physical and cultural phenomena by outlining image variation in tone, texture, pattern, and shape. Classification and description of landscape types are discussed. The imagery used for the study covers a portion of the Asheville Basin in North Carolina, extending from Hot Springs to an area southeast of Hendersonville. Eleven regions are discussed.

Nunnally, N. R.↗