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At least 1,081 records · Page 60

A Regression Method for Comparing Launch Zone Ranges Derived From Different Sources

In modern fighter aircraft air-to-air missile launch acceptable ranges (LARs) are provided to the pilot for his launch decision. These LARs are calculated in the avionic software, using very simple algebraic equations and algorithms, that attempt to model complex missile behavior. Frequently these algorithms are revised to reflect inaccuracies discovered, when comparisons are made with missile six degree-of-freedom (6-DOF) simulations. The process of modifying this software has become expensive. In the past, these simple LAR generators were modified based only on subjective judgmental approach, with little regard to the missile range design limits. With reduced budgets a more rational methodology should be taken to assess whether or not simple fighter LAR generators need to be modified. Any LAR generator can produce large amounts of range (minimum and maximum) data over the board engagement limits of modem fighter and air-to-air missiles. This infinite population lends itself to some statistical methodology to access simple LAR accuracy and the need for software modification. The methodology should produce statistical parameters for use in the decision making process of modifying a simple fighter LAR generator. This paper presents a regression method, based on a missile range design limit philosophy. Acceptance criteria from the regression method are given that provide simple statistical parameters to aid in this decision making process.

Flight Testing↗

Mapping Application for Penguin Populations and Projected Dynamics (MAPPPD): Data and Tools for Dynamic Management and Decision Support

The Mapping Application for Penguin Populations and Projected Dynamics (MAPPPD) is a web-based, open access, decision-support tool designed to assist scientists, non-governmental organizations and policy-makers working to meet the management objectives as set forth by the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) and other components of the Antarctic Treaty System (ATS) (that is, Consultative Meetings and the ATS Committee on Environmental Protection). MAPPPD was designed specifically to complement existing efforts such as the CCAMLR Ecosystem Monitoring Program (CEMP) and the ATS site guidelines for visitors. The database underlying MAPPPD includes all publicly available (published and unpublished) count data on emperor, gentoo, Adelie) and chinstrap penguins in Antarctica. Penguin population models are used to assimilate available data into estimates of abundance for each site and year.Results are easily aggregated across multiple sites to obtain abundance estimates over any user-defined area of interest. A front end web interface located at www.penguinmap.com provides free and ready access to the most recent count and modelled data, and can act as a facilitator for data transfer between scientists and Antarctic stakeholders to help inform management decisions for the continent.

Humphries, G. R. W.↗

Integration of the Total Lightning Jump Algorithm into Current Operational Warning Environment Conceptual Models

The purpose of the total lightning jump algorithm (LJA) is to provide forecasters with an additional tool to identify potentially hazardous thunderstorms, yielding increased confidence in decisions within the operational warning environment. The LJA was first developed to objectively indentify rapid increases in total lightning (also termed "lightning jumps") that occur prior to the observance of severe and hazardous weather (Williams et al. 1999, Schultz et al. 2009, Gatlin and Goodman 2010, Schultz et al. 2011). However, a physical and framework leading up to and through the time of a lightning jump is still lacking within the literature. Many studies infer that there is a large increase in the updraft prior to or during the jump, but are not specific on what properties of the updraft are indeed increasing (e.g., maximum updraft speed vs volume or both) likely because these properties were not specifically observed. Therefore, the purpose of this work is to physically associate lightning jump occurrence to polarimetric and multi-Doppler radar measured thunderstorm intensity metrics and severe weather occurrence, thus providing a conceptual model that can be used to adapt the LJA to current operations.

Schultz, C. J.↗

Surface Water and Flood Extent Mapping, Monitoring, and Modeling Products and Services for the SERVIR Regions

SERVIR is a joint NASA - US Agency for International Development (USAID) project to improve environmental decision-making using Earth observations and geospatial technologies. A common need identified among SERVIR regions has been improved information for disaster risk reduction and in specific surface water and flood extent mapping, monitoring and forecasting. Of the 70 SERVIR products (active, complete, and in development), 4 are related to surface water and flood extent mapping, monitoring or forecasting. Visit http://www.servircatalog.net for more product details.

environment↗

The Crop Evaluation Research for Environmental Strategies (CERES) Remote Sensing 2008 Project Activities

In recent years, the use of Plant Incorporated Protectant (PIP) corn by American producers has been increasing dramatically. PIP corn contains genetically inserted traits that produce toxins in the plant that provide narrowly targeted protection against specific insect pests. The plant producing t oxms can offer significant reductions in the application of broad -spectrum pesticides that have ecological and human health consequences. PIP corn as a percentage of total corn acreage planted in the US is expected to continue to increase as these protective traits are "stacked" with other desirable traits by seed companies, and producers are seeing considerable increases in corn yield as a result. The introduction of corn as a bio-fuel source for ethanol has increased production by over 6 million hectares in 2007. The United States Environmental Protection Agency (USEPA), which is responsible for the registration of PIP crops under the Federal Insecticide, Fungicide and Rodenticide Act, views the use of PIP corn as positive. Broad spectrum pesticide use has declined since the PIP traits have been introduced. As the agricultural landscape sees a higher percentage of corn acres using the PIP technology, the risk of the targeted insect pest populations developing resistance to the toxins, thereby rendering the in will increase as well. This result would negate the effectiveness of the PIP corn traits and could reduce production of a US field corn crop valued at $33 billion dollars in 2006 and place US food and now energy security at risk. Concerns over insect pest resistance development to PIP traits have led the USEPA to team with NASA and the Institute for Technology Development (ITD) to develop geo-spatial technologies designed to proactively monitor the corn production landscape for insect pest infestation and possible resistance development. USEPA resistance management simulation models are combined with NASA remote sensi ng products to monitor the corn landscape for resistance development. The two agencies have entered into an agreement which could potentially lead to the development of next generation NASA sensors that will more specifically address the requirements of the USEPA's resistance development strategy and offer opportunities to study the ever changing ecosystem complexities. The USEPA/NASA/ITD team has developed a broad research project entitled CERES (Crop Evaluation Research for Environmental Strategies). CERES is a research effort leading to decision support system tools that are designed to integrate multi-resolution NASA remote sensing data products and USEPA geo -spatial models to monitor the potential for insect pest resistance development from the regional to the landscape and then to the field level.

Casas, Joseph C.↗

The Porous Microstructure Analysis (PuMA) software

The open-source Porous Microstructure Analysis (PuMA) software was implemented to offer an efficient framework for determining material characteristics from 3D microstructures. Its development was inspired by progress in X-ray microtomography, an imaging technology that captures the internal structure of materials in 3D, and even in a 4D temporal context. Over recent years, this method has transformed the domain of materials science due to its capability to non-destructively examine material microstructures while presenting digital data about their geometrical details. It has provided insights into materials relevant to several NASA missions, including heatshields, parachute fabrics, meteorites, and other advanced composites. PuMA, in its current version 3, delivers an array of features, spanning from basic geometric insights of a microstructure to intricate anisotropic thermo-elastic and chemical behavior. Specifically, the software evaluates morphological attributes (specific surface area, volume fractions, mean intercept lengths, orientation) and physical characteristics (conductivity, elasticity, permeability, and tortuosity). Additionally, it can model material degradation processes, such as oxidation and surface chemistry interactions. The software can generate synthetic microstructures, from straightforward geometrical designs to intricate woven and non-woven geometries. Coupling material generation and characterization enable parametric studies and sensitivity analysis to optimize the microstructural performance and inform design decisions and reliability assessment based on uncertainty quantification. A recent addition to PuMA includes the TomoSAM plugin, devised to incorporate the cutting-edge Segment Anything Model (SAM). SAM is a promptable deep learning model that can identify objects and create image masks in a zero-shot manner, based only on a few user clicks. The synergy between these tools aids in the segmentation of complex 3D datasets from tomography or other imaging techniques, which would otherwise require a laborious manual segmentation process.

Tomography↗

The Porous Microstructure Analysis (PuMA) software

The open-source Porous Microstructure Analysis (PuMA) software was created to offer an efficient framework for determining material properties from 3D microstructures. Its development was inspired by progress in X-ray microtomography, an imaging technology that captures the internal structure of materials in 3D, and even in a 4D temporal context. Over recent years, this method has transformed the domain of materials science due to its capability to non-destructively examine material microstructures while presenting digital data about their geometrical details. It has provided insights into materials relevant to several NASA missions, including heatshields, parachute fabrics, meteorites, and other advanced composites. PuMA, in its current version 3, delivers an array of features, spanning from basic geometric insights of a microstructure to intricate anisotropic thermo-elastic and chemical behavior. Specifically, the software evaluates morphological attributes (specific surface area, volume fractions, mean intercept lengths, orientation) and physical characteristics (conductivity, elasticity, permeability, and tortuosity). Additionally, it can model material degradation processes, such as oxidation and surface chemistry interactions. The software can generate synthetic microstructures, from straightforward geometrical designs to intricate woven and non-woven geometries. Coupling material generation and characterization enables parametric studies and sensitivity analysis to optimize the microstructural performance and inform design decisions and reliability assessment based on uncertainty quantification. A recent addition to PuMA includes the TomoSAM plugin, devised to incorporate the cutting-edge Segment Anything Model (SAM) into our image segmentation workflow. SAM is a promptable deep learning model that can identify objects and create image masks in a zero-shot manner, based only on a few user clicks. The synergy between these tools aids in the segmentation of complex 3D datasets from tomography and other imaging techniques, which would otherwise require a laborious manual segmentation process.

Tomography↗

Multi-Parent Clustering Algorithms from Stochastic Grammar Data Models

We introduce a statistical data model and an associated optimization-based clustering algorithm which allows data vectors to belong to zero, one or several "parent" clusters. For each data vector the algorithm makes a discrete decision among these alternatives. Thus, a recursive version of this algorithm would place data clusters in a Directed Acyclic Graph rather than a tree. We test the algorithm with synthetic data generated according to the statistical data model. We also illustrate the algorithm using real data from large-scale gene expression assays.

Mjoisness, Eric↗

Constraints, Approach and Present Status for Selecting the Mars Surveyor 2001 Landing Site

There are many similarities between the Mars Surveyor '01 (MS '01) landing site selection process and that of Mars Pathfinder. The selection process includes two parallel activities in which engineers define and refine the capabilities of the spacecraft through design, testing and modeling and scientists define a set of landing site constraints based on the spacecraft design and landing scenario. As for Pathfinder, the safety of the site is without question the single most important factor, for the simple reason that failure to land safely yields no science and exposes the mission and program to considerable risk. The selection process must be thorough, defensible and capable of surviving multiple withering reviews similar to the Pathfinder decision. On Pathfinder, this was accomplished by attempting to understand the surface properties of sites using available remote sensing data sets and models based on them. Science objectives are factored into the selection process only after the safety of the site is validated. Finally, as for Pathfinder, the selection process is being done in an open environment with multiple opportunities for community involvement including open workshops, with education and outreach opportunities.

Golombek, M.↗

Applications of Remote Sensing for Land Use Planning Scenarios with Suitability Analysis

In regions undergoing rapid urbanization, such as West Africa, land use planning (LUP) is vital to accommodate growing population and manage natural resources. Suitability analysis modeling is a widely used tool in LUP to determine the extent to which a land area is suitable for a designated purpose, but there is a gap in the integration of remote sensing time series data into land use decisions. The goal of this study was to incorporate remote sensing time series information with suitability analyses to inform LUP decisions in urban areas. In the study area of Kumasi, Ghana, land cover trends and land surface temperature (LST) from 2000 to 2019 were used to understand climate change trends. Suitability analyses determined the fitness of land areas for predetermined uses. These background processes informed a genetic algorithm to project plausible futures for three land use scenarios. One scenario represented current land use planning practices for addressing population growth, another scenario prioritized minimizing climate change impacts while also accommodating population growth, and the final scenario focused on both of these climate and population goals in addition to high density urban development. Each of these scenarios was successful in achieving population accommodation and respective climate change mitigation goals. The results for these scenarios provide insight into plausible land use distributions in 2050 based on different planning approaches. The genetic algorithm was able to effectively develop results for each scenario through the integration of remotely sensed trends and suitability models, providing a novel approach to land use decision-making.

remote sensing time series↗

Constraints, Approach, and Status of Mars Surveyor 2001 Landing Site Selection

There are many similarities between the Mars Surveyor '01 (MS '01) landing site selection process and that of Mars Pathfinder. The selection process includes two parallel activities in which engineers define and refine the capabilities of the spacecraft through design, testing and modeling and scientists define a set of landing site constraints based on the spacecraft design and landing scenario. As for Pathfinder, the safety of the site is without question the single most important factor, for the simple reason that failure to land safely yields no science and exposes the mission and program to considerable risk. The selection process must be thorough and defensible and capable of surviving multiple withering reviews similar to the Pathfinder decision. On Pathfinder, this was accomplished by attempting to understand the surface properties of sites using available remote sensing data sets and models based on them. Science objectives are factored into the selection process only after the safety of the site is validated. Finally, as for Pathfinder, the selection process is being done in an open environment with multiple opportunities for community involvement including open workshops, with education and outreach opportunities. Additional information is contained in the original extended abstract.

Golombek, M.↗

Constraints and Approach for Selecting the Mars Surveyor '01 Landing Site

There are many similarities between the Mars Surveyor '01 (MS '01) landing site selection process and that of Mars Pathfinder. The selection process includes two parallel activities in which engineers define and refine the capabilities of the spacecraft through design, testing and modeling and scientists define a set of landing site constraints based on the spacecraft design and landing scenario. As for Pathfinder, the safety of the site is without question the single most important factor, for the simple reason that failure to land safely yields no science and exposes the mission and program to considerable risk. The selection process must be thorough and defensible and capable of surviving multiple withering reviews similar to the Pathfinder decision. On Pathfinder, this was accomplished by attempting to understand the surface properties of sites using available remote sensing data sets and models based on them. Science objectives are factored into the selection process only after the safety of the site is validated. Finally, as for Pathfinder, the selection process is being done in an open environment with multiple opportunities for community involvement including open workshops, with education and outreach opportunities.

Golombek, M.↗

Integration of Weather Data into Airspace and Traffic Operations Simulation (ATOS) for Trajectory- Based Operations Research

Explicit integration of aviation weather forecasts with the National Airspace System (NAS) structure is needed to improve the development and execution of operationally effective weather impact mitigation plans and has become increasingly important due to NAS congestion and associated increases in delay. This article considers several contemporary weather-air traffic management (ATM) integration applications: the use of probabilistic forecasts of visibility at San Francisco, the Route Availability Planning Tool to facilitate departures from the New York airports during thunderstorms, the estimation of en route capacity in convective weather, and the application of mixed-integer optimization techniques to air traffic management when the en route and terminal capacities are varying with time because of convective weather impacts. Our operational experience at San Francisco and New York coupled with very promising initial results of traffic flow optimizations suggests that weather-ATM integrated systems warrant significant research and development investment. However, they will need to be refined through rapid prototyping at facilities with supportive operational users We have discussed key elements of an emerging aviation weather research area: the explicit integration of aviation weather forecasts with NAS structure to improve the effectiveness and timeliness of weather impact mitigation plans. Our insights are based on operational experiences with Lincoln Laboratory-developed integrated weather sensing and processing systems, and derivative early prototypes of explicit ATM decision support tools such as the RAPT in New York City. The technical components of this effort involve improving meteorological forecast skill, tailoring the forecast outputs to the problem of estimating airspace impacts, developing models to quantify airspace impacts, and prototyping automated tools that assist in the development of objective broad-area ATM strategies, given probabilistic weather forecasts. Lincoln Laboratory studies and prototype demonstrations in this area are helping to define the weather-assimilated decision-making system that is envisioned as a key capability for the multi-agency Next Generation Air Transportation System [1]. The Laboratory's work in this area has involved continuing, operations-based evolution of both weather forecasts and models for weather impacts on the NAS. Our experience has been that the development of usable ATM technologies that address weather impacts must proceed via rapid prototyping at facilities whose users are highly motivated to participate in system evolution.

Peters, Mark↗

Advancing Precipitation Estimation, Prediction, and Impact Studies

Precipitation exhibits a large variability over a wide range of space and time scales: from seconds to years and decades in time; from the millimeter scale of microphysical processes to regional and global scales in space. It also exhibits a large variability in magnitude and frequency, from low extremes resulting in prolonged droughts to high extremes resulting in devastating floods. Improving precipitation estimation and prediction has great societal impact for decision support in water resources management, infrastructure protection and design under accelerating climate extremes, quantifying water and energy balances at the regional to global scales, and predicting hurricanes, tornadoes, floods and droughts that affect the economy and security around the world (e.g., Blunden and Arndt, 2019). Yet, despite significant advances in observations and physical understanding, precipitation still remains one of the most challenging variables to model and predict at local, regional and global scales with significant implications for our ability to quantify water and energy cycle dynamics, inform decision making, and predict hydro-geomorphic hazards in response to precipitation extremes (e.g. Maggioni and Massari, 2019).

Efi Foufoula-Georgiou↗

Utilization of remotely-sensed data in the management of inland wetlands

The author has identified the following significant results. ERTS-1 data and aerial photography are proving to be a useful tool for the inventory and management of inland wetlands. Two examples of the application of remotely-sensed data to specific wetland management needs or requirements are discussed. Studies of the Great Dismal Swamp are utilizing ERTS-1 imagery and color IR photography in: (1) study area selection; (2) field inspection; (3) vegetation mapping; (4) identification of drainage characteristics and moisture regime; (5) location of intensive study areas; and (6) detection of change. Thematic extractions of ERTS-1 data made using the United States Geological Survey's Autographic Theme Extraction System are aiding analyses of swamp hydrologic regime and providing information pertinent to quick recognition and inventory of wetlands from ERTS-1. DCP'S in south Florida wetlands provide near-real time data for water resources managers. Data relayed by satellite can be entered into models to provide predictive data and water storage information for long-term and short-term decision making.

Carter, V.↗

Artificial intelligence approach to planning the robotic assembly of large tetrahedral truss structures

An assembly planner for tetrahedral truss structures is presented. To overcome the difficulties due to the large number of parts, the planner exploits the simplicity and uniformity of the shapes of the parts and the regularity of their interconnection. The planning automation is based on the computational formalism known as production system. The global data base consists of a hexagonal grid representation of the truss structure. This representation captures the regularity of tetrahedral truss structures and their multiple hierarchies. It maps into quadratic grids and can be implemented in a computer by using a two-dimensional array data structure. By maintaining the multiple hierarchies explicitly in the model, the choice of a particular hierarchy is only made when needed, thus allowing a more informed decision. Furthermore, testing the preconditions of the production rules is simple because the patterned way in which the struts are interconnected is incorporated into the topology of the hexagonal grid. A directed graph representation of assembly sequences allows the use of both graph search and backtracking control strategies.

Homemdemello, Luiz S.↗

Computing in space: Issues and answers

Future plans for space exploration call for scientific instruments whose data is increasingly voluminous, far exceeding constraints set by telemetry rates, and therefore, an increased role for spaceborne computing. Three issues that greatly influence the realization of spaceborne computing systems are addressed. The first involves the identification of those research problems which are unique to space computing. Resources must be expended on these problems if efforts are to add value to, and have impact on, the technology of computing in space. The second addresses the transfer of new technology from the research laboratory to use in space. What can be done to expedite this process and shrink the technology gap that separates Earth and space based systems must be assessed. The third issue involves the user's point of view of what is required of new space computing systems. That is, what are the driving forces that most influence customers' decisions to use or not use new technology? Issues of design environment for spaceborne computers, tools for modeling and evaluation of flight systems, and validation of space flight hardware and software are also discussed.

Davidson, John M.↗

A Model for NASA-KSC's Privatization Transition

This paper describes a model for government agencies that are considering privatization of all or part of their functions. Privatization encompasses the transitioning of government functions from government run to contractor run. The model developed in this paper is used to analyze the National Aeronautics and Space Administration's (NASA) decision to privatize space shuttle operations at the Kennedy Space Center (KSC). Several specific recommendations are given to KSC as they attempt to operationalize this privatization decision at the Center and to transition to a new relationship with their contractors.

Lavelle, Jerome P.↗