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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Space and Earth Science Data Compression Workshop

The workshop explored opportunities for data compression to enhance the collection and analysis of space and Earth science data. The focus was on scientists' data requirements, as well as constraints imposed by the data collection, transmission, distribution, and archival systems. The workshop consisted of several invited papers; two described information systems for space and Earth science data, four depicted analysis scenarios for extracting information of scientific interest from data collected by Earth orbiting and deep space platforms, and a final one was a general tutorial on image data compression.

Tilton, James C.↗
NASA NTRS2009

Recent Advances in Techniques for Hyperspectral Image Processing

Imaging spectroscopy, also known as hyperspectral imaging, has been transformed in less than 30 years from being a sparse research tool into a commodity product available to a broad user community. Currently, there is a need for standardized data processing techniques able to take into account the special properties of hyperspectral data. In this paper, we provide a seminal view on recent advances in techniques for hyperspectral image processing. Our main focus is on the design of techniques able to deal with the highdimensional nature of the data, and to integrate the spatial and spectral information. Performance of the discussed techniques is evaluated in different analysis scenarios. To satisfy time-critical constraints in specific applications, we also develop efficient parallel implementations of some of the discussed algorithms. Combined, these parts provide an excellent snapshot of the state-of-the-art in those areas, and offer a thoughtful perspective on future potentials and emerging challenges in the design of robust hyperspectral imaging algorithms

Plaza, Antonio↗
NASA NTRS2013

Putting Integrated Systems Health Management Capabilities to Work: Development of an Advanced Caution and Warning System for Next-Generation Crewed Spacecraft Missions

Integrated System Health Management (ISHM) technologies have advanced to the point where they can provide significant automated assistance with real-time fault detection, diagnosis, guided troubleshooting, and failure consequence assessment. To exploit these capabilities in actual operational environments, however, ISHM information must be integrated into operational concepts and associated information displays in ways that enable human operators to process and understand the ISHM system information rapidly and effectively. In this paper, we explore these design issues in the context of an advanced caution and warning system (ACAWS) for next-generation crewed spacecraft missions. User interface concepts for depicting failure diagnoses, failure effects, redundancy loss, "what-if" failure analysis scenarios, and resolution of ambiguity groups are discussed and illustrated.

integrated system management↗
NASA NTRS2016

Evaluating the Impact of Data Placement to Spark and SciDB with an Earth Science Use Case

We investigate the impact of data placement for two Big Data technologies, Spark and SciDB, with a use case from Earth Science where data arrays are multidimensional. Simultaneously, this investigation provides an opportunity to evaluate the performance of the technologies involved. Two datastores, HDFS and Cassandra, are used with Spark for our comparison. It is found that Spark with Cassandra performs better than with HDFS, but SciDB performs better yet than Spark with either datastore. The investigation also underscores the value of having data aligned for the most common analysis scenarios in advance on a shared nothing architecture. Otherwise, repartitioning needs to be carried out on the fly, degrading overall performance.

Spark↗
NASA NTRS2017

Precision Projector Laboratory: Detector Characterization with an Astronomical Emulation Testbed

As astronomical observations benefit from improved sensitivity, the effectiveness of scientific programs is becoming limited by systematics that often originate in poorly understood image sensor behavior. Traditional, bottom-up detector characterization methods provide one way to model underlying detector physics, and generate ever more faithful numerical simulations, but this approach is vulnerable to preconceptions and over-simplification. The alternative top-down approach is laboratory emulation, which enables observation, calibration, and analysis scenarios to be tested without relying on a complete understanding of the underlying physics. This complements detector characterization and simulation efforts by testing their validity. We describe a laboratory facility and experimental testbed that supports the emulation of a wide range of mission concepts such as gravitational weak lensing measurements by WFIRST and high precision spectrophotometry of transiting exoplanets by JWST. An Offner relay projects readily customizable "scenes" (e.g. stars, galaxies, spectra) with very low optical aberration over the full area of a typical optical or near infrared image sensor. f/8 and slower focal ratios may be selected, spanning those of most proposed space missions and approximating the point spread function (PSF) size of seeing limited ground based surveys. Diffraction limited PSFs are projected over a wide field of view and wavelength range to deliver highly predictable image patterns down to sub-pixel scales with stable intensity and fine motion control. The testbed enables realistic validation of detector performance on science-like images, which aids mission design and survey strategy, as well as targeted investigations of various detector effects.

Seshadri, Suresh↗
NASA NTRS2021

A New Approach to Evaluate and Reduce Uncertainty of Model-Based Biodiversity Projections for Conservation Policy Formulation

Biodiversity projections with uncertainty estimates under different climate, land-use, and policy scenarios are essential to setting and achieving international targets to mitigate biodiversity loss. Evaluating and improving biodiversity predictions to better inform policy decisions remains a central conservation goal and challenge. A comprehensive strategy to evaluate and reduce uncertainty of model outputs against observed measurements and multiple models would help to produce more robust biodiversity predictions. We propose an approach that integrates biodiversity models and emerging remote sensing and in-situ data streams to evaluate and reduce uncertainty with the goal of improving policy-relevant biodiversity predictions. In this article, we describe a multivariate approach to directly and indirectly evaluate and constrain model uncertainty, demonstrate a proof of concept of this approach, embed the concept within the broader context of model evaluation and scenario analysis for conservation policy, and highlight lessons from other modeling communities.

Bonnie J E Myers↗
NASA NTRS2022

Coevolution of Machine Learning and Process-Based Modelling to Revolutionize Earth and Environmental Sciences: A Perspective

Machine learning (ML) applications in Earth and environmental sciences (EES) have gained incredible momentum in recent years. However, these ML applications have largely evolved in ‘isolation’ from the mechanistic, process-based modelling (PBM) paradigms, which have historically been the cornerstone of scientific discovery and policy support. In this perspective, we assert that the cultural barriers between the ML and PBM communities limit the potential of ML, and even its ‘hybridization’ with PBM, for EES applications. Fundamental, but often ignored, differences between ML and PBM are discussed as well as their strengths and weaknesses in light of three overarching modelling objectives in EES, (1) nowcasting and prediction, (2) scenario analysis, and (3) diagnostic learning. The paper ponders over a ‘coevolutionary’ approach to model building, shifting away from a borrowing to a co-creation culture, to develop a generation of models that leverage the unique strengths of ML such as scalability to big data and high-dimensional mapping, while remaining faithful to process-based knowledge base and principles of model explainability and interpretability, and therefore, falsifiability.

Saman Razavi↗
NASA NTRS2024

Assessing Effects of Climate and Technology Uncertainties in Large Natural Resource Allocation Problems

The productivity of the world's natural resources is critically dependent on a variety of highly uncertain factors, which obscure individual investors and governments that seek to make long-term, sometimes irreversible, investments in their exploration and utilization. These dynamic considerations are poorly represented in disaggregated resource models, as incorporating uncertainty into large-dimensional problems presents a challenging computational task. In this paper, we apply the SCEQ algorithm (Cai and Judd, 2023) to solve a large-scale dynamic stochastic global land resource use problem with stochastic crop yields due to adverse climate impacts and limits on further technological progress. For the same model parameters and bounded shocks, the range of land conversion is considerably smaller for the dynamic stochastic model than for deterministic scenario analysis.

numerical methods↗
NASA NTRSDate not supplied

A Comparative Assessment of Evolvable Martian ISRU Propellant Production for Future Human Missions

In 2022, NASA released its “Moon to Mars Strategy and Objectives Development” document, containing top-level goals and objectives designed to create a blueprint for sustained human presence and exploration throughout the solar system. One objective in this “blueprint” calls for the demonstration of “…Mars ISRU capabilities to support an initial human Mars exploration campaign.” NASA is looking at both the benefits and liens of this concept, as one of several trade space aspects under consideration, for inclusion in the overall architecture of the human exploration of Mars. This paper summarizes results from a series of Martian ISRU-focused trade studies from 2023 and 2024. These studies cover five different approaches to providing propellants for returning crew and equipment from the surface of Mars, using several different combinations of propellants delivered (from Earth) and produced from Martian feedstock material. For comparison purposes, the same ISRU infrastructure elements were used across all options wherever possible. The equipment mass, power, operational complexity, and time needed to produce some or all of these propellants have been quantified and compared when used in a common mission scenario. Analysis results for each option are discussed. Performance parameters for these options are compared side-by-side and observations made, including the positive and negative aspects of each case. The possibility of evolving from a simpler ISRU case to more complex cases that would potentially lead to more sustainable operations are also discussed. While no single case emerged as “better” in all aspects when compared to the others, there are distinct advantages and disadvantages that did emerge when comparing the results generated from a common set of assumptions for all cases. Consequently, specific mission objectives may determine which of these advantages or disadvantages are important for choosing among the cases that could benefit any particular mission or campaign.

Mars↗
NASA NTRSDate not supplied

A Comparative Assessment of Evolvable Martian ISRU Propellant Production for Future Human Missions

In 2022, NASA released its “Moon to Mars Strategy and Objectives Development” document, containing top-level goals and objectives designed to create a blueprint for sustained human presence and exploration throughout the solar system. One objective in this “blueprint” calls for the demonstration of “…Mars ISRU capabilities to support an initial human Mars exploration campaign.” NASA is looking at both the benefits and liens of this concept, as one of several trade space aspects under consideration, for inclusion in the overall architecture of the human exploration of Mars. This paper summarizes results from a series of Martian ISRU-focused trade studies from 2023 and 2024. These studies cover five different approaches to providing propellants for returning crew and equipment from the surface of Mars, using several different combinations of propellants delivered (from Earth) and produced from Martian feedstock material. For comparison purposes, the same ISRU infrastructure elements were used across all options wherever possible. The equipment mass, power, operational complexity, and time needed to produce some or all of these propellants have been quantified and compared when used in a common mission scenario. Analysis results for each option are discussed. Performance parameters for these options are compared side-by-side and observations made, including the positive and negative aspects of each case. The possibility of evolving from a simpler ISRU case to more complex cases that would potentially lead to more sustainable operations are also discussed. While no single case emerged as “better” in all aspects when compared to the others, there are distinct advantages and disadvantages that did emerge when comparing the results generated from a common set of assumptions for all cases. Consequently, specific mission objectives may determine which of these advantages or disadvantages are important for choosing among the cases that could benefit any particular mission or campaign.

Propellant↗
NASA NTRS2024

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↗
NASA NTRS2004

Space mission scenario development and performance analysis tool

This paper discusses a new and innovative approach for a rapid spacecraft multi-disciplinary performance analysis using a tool called the Mission Scenario Development Workbench (MSDW). To meet the needs of new classes of space missions, analysis tools with proven models were developed and integrated into a framework to enable rapid trades and analyses between spacecraft designs and operational scenarios during the formulation phase of a mission. Generally speaking, spacecraft resources are highly constrained on deep space missions and this approach makes it possible to maximize the use of existing resources to attain the best possible science return. This approach also has the potential benefit of reducing the risk of costly design changes made later in the design cycle necessary to meet the mission requirements by understanding system design sensitivities early and adding appropriate margins. This paper will describe the approach used by the Mars Science Laboratory Project to accomplish this result.

performance analysis↗
NASA NTRS2008

Strategic Analysis Overview

NASA s Constellation Program employs a strategic analysis methodology in providing an integrated analysis capability of Lunar exploration scenarios and to support strategic decision-making regarding those scenarios. The strategic analysis methodology integrates the assessment of the major contributors to strategic objective satisfaction performance, affordability, and risk and captures the linkages and feedbacks between all three components. Strategic analysis supports strategic decision making by senior management through comparable analysis of alternative strategies, provision of a consistent set of high level value metrics, and the enabling of cost-benefit analysis. The tools developed to implement the strategic analysis methodology are not element design and sizing tools. Rather, these models evaluate strategic performance using predefined elements, imported into a library from expert-driven design/sizing tools or expert analysis. Specific components of the strategic analysis tool set include scenario definition, requirements generation, mission manifesting, scenario lifecycle costing, crew time analysis, objective satisfaction benefit, risk analysis, and probabilistic evaluation. Results from all components of strategic analysis are evaluated a set of pre-defined figures of merit (FOMs). These FOMs capture the high-level strategic characteristics of all scenarios and facilitate direct comparison of options. The strategic analysis methodology that is described in this paper has previously been applied to the Space Shuttle and International Space Station Programs and is now being used to support the development of the baseline Constellation Program lunar architecture. This paper will present an overview of the strategic analysis methodology and will present sample results from the application of the strategic analysis methodology to the Constellation Program lunar architecture.

Cirillo, William M.↗
NASA NTRS2015

Modeling and Analysis of Realistic Fire Scenarios in Spacecraft

An accidental fire inside a spacecraft is an unlikely, but very real emergency situation that can easily have dire consequences. While much has been learned over the past 25+ years of dedicated research on flame behavior in microgravity, a quantitative understanding of the initiation, spread, detection and extinguishment of a realistic fire aboard a spacecraft is lacking. Virtually all combustion experiments in microgravity have been small-scale, by necessity (hardware limitations in ground-based facilities and safety concerns in space-based facilities). Large-scale, realistic fire experiments are unlikely for the foreseeable future (unlike in terrestrial situations). Therefore, NASA will have to rely on scale modeling, extrapolation of small-scale experiments and detailed numerical modeling to provide the data necessary for vehicle and safety system design. This paper presents the results of parallel efforts to better model the initiation, spread, detection and extinguishment of fires aboard spacecraft. The first is a detailed numerical model using the freely available Fire Dynamics Simulator (FDS). FDS is a CFD code that numerically solves a large eddy simulation form of the Navier-Stokes equations. FDS provides a detailed treatment of the smoke and energy transport from a fire. The simulations provide a wealth of information, but are computationally intensive and not suitable for parametric studies where the detailed treatment of the mass and energy transport are unnecessary. The second path extends a model previously documented at ICES meetings that attempted to predict maximum survivable fires aboard space-craft. This one-dimensional model implies the heat and mass transfer as well as toxic species production from a fire. These simplifications result in a code that is faster and more suitable for parametric studies (having already been used to help in the hatch design of the Multi-Purpose Crew Vehicle, MPCV).

life support↗
NASA NTRS2015

Exploring NASA Human Spaceflight and Pioneering Scenarios

The life cycle cost analysis of space exploration scenarios is explored via a merger of (1) scenario planning, separating context and (2) modeling and analysis of specific content. Numerous scenarios are presented, leading to cross-cutting recommendations addressing life cycle costs, productivity, and approaches applicable to any scenarios. Approaches address technical and non-technical factors.

cost modeling estimation↗
NASA NTRS2015

Exploring NASA Human Spaceflight and Pioneering Scenarios

The life cycle cost analysis of space exploration scenarios is explored via a merger of (1) scenario planning, separating context and (2) modeling and analysis of specific content. Numerous scenarios are presented, leading to cross-cutting recommendations addressing life cycle costs, productivity, and approaches applicable to any scenarios. Approaches address technical and non-technical factors.

space systems life cycle costs↗
NASA NTRS1991

MisTec: A software application for supporting space exploration scenario options and technology development analysis and planning

The structure and composition of a new, emerging software application, which models and analyzes space exploration scenario options for feasibility based on technology development projections is presented. The software application consists of four main components: a scenario generator for designing and inputting scenario options and constraints; a processor which performs algorithmic coupling and options analyses of mission activity requirements and technology capabilities; a results display which graphically and textually shows coupling and options analysis results; and a data/knowledge base which contains information on a variety of mission activities and (power and propulsion) technology system capabilities. The general long-range study process used by NASA to support recent studies is briefly introduced to provide the primary basis for comparison for discussing the potential advantages to be gained from developing and applying this king of application. A hypothetical example of a scenario option to facilitate the best conceptual understanding of what the application is, how it works, or the operating methodology, and when it might be applied is presented.

Horsham, Gary A. P.↗