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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 NTRS1992

Challenges of space medical operations and life sciences management

The Kennedy Space Center (KSC) has been the premier launch and landing site for America's space program since the early 1960s. Visitors are cognizant of space vehicles, processing facilities and launch pads which are treasured national resources. However, most are unaware of the unique organization which supports launch and landing activities and manages the center's occupational medicine, environmental health, ecological and environmental monitoring functions, as well as human and plant research programs. Management of this multifaceted organization can be complex because funding its different functions comes from a number of sources. Additionally the diverse disciplines of personnel present a special challenge in maintaining professional competencies while assuring efficiency in cyclical operations. This article explains the organization's structure and reviews some of its accomplishments.

Haddad, S. G.↗
NASA NTRS1993

Data management system performance modeling

This paper discusses analytical techniques that have been used to gain a better understanding of the Space Station Freedom's (SSF's) Data Management System (DMS). The DMS is a complex, distributed, real-time computer system that has been redesigned numerous times. The implications of these redesigns have not been fully analyzed. This paper discusses the advantages and disadvantages for static analytical techniques such as Rate Monotonic Analysis (RMA) and also provides a rationale for dynamic modeling. Factors such as system architecture, processor utilization, bus architecture, queuing, etc. are well suited for analysis with a dynamic model. The significance of performance measures for a real-time system are discussed.

Kiser, Larry M.↗
NASA NTRS1993

DMS augmented monitoring and diganosis application (DMS AMDA) prototype

The Data Management System Augmented Monitoring and Diagnosis Application (DMS AMDA) is currently under development at NASA Ames Research Center (ARC). It will provide automated monitoring and diagnosis capabilities for the Space Station Freedom (SSF) Data Management System (DMS) in the Control Center Complex (CCC) at NASA Johnson Space Center. Several advanced automation applications are under development for use in the CCC for other SSF subsystems. The DMS AMDA, however, is the first application to utilize digraph failure analysis techniques and the Extended Realtime FEAT (ERF) application as the core of its diagnostic system design, since the other projects were begun before the digraph tools were available. Model-based diagnosis and expert systems techniques will provide additional capabilities and augment ERF where appropriate. Utilization of system knowledge captured in the design phase of a system in digraphs should result in both a cost savings and a technical advantage during implementation of the diagnostic software. This paper addresses both the programmatic and technical considerations of this approach, and describes the software design and initial prototyping effort.

Patterson-Hine, F. A.↗
NASA NTRS1994

Using CLIPS to represent knowledge in a VR simulation

Virtual reality (VR) is an exciting use of advanced hardware and software technologies to achieve an immersive simulation. Until recently, the majority of virtual environments were merely 'fly-throughs' in which a user could freely explore a 3-dimensional world or a visualized dataset. Now that the underlying technologies are reaching a level of maturity, programmers are seeking ways to increase the complexity and interactivity of immersive simulations. In most cases, interactivity in a virtual environment can be specified in the form 'whenever such-and-such happens to object X, it reacts in the following manner.' CLIPS and COOL provide a simple and elegant framework for representing this knowledge-base in an efficient manner that can be extended incrementally. The complexity of a detailed simulation becomes more manageable when the control flow is governed by CLIPS' rule-based inference engine as opposed to by traditional procedural mechanisms. Examples in this paper will illustrate an effective way to represent VR information in CLIPS, and to tie this knowledge base to the input and output C routines of a typical virtual environment.

Engelberg, Mark L.↗
NASA NTRS1997

A Comparison of Two Control Display Unit Concepts on Flight Management System Training

One of the biggest challenges for a pilot in the transition to a 'glass' cockpit is understanding the flight management system (FMS). Because of both the complex nature of the FMS and the pilot-FMS interface, a large portion of transition training is devoted to the FMS. The current study examined the impact of the primary pilot-FMS interface, the control display unit (CDU), on FMS training. Based on the hypothesis that the interface design could have a significant impact on training, an FMS simulation with two separate interfaces was developed. One interface was similar to a current-generation design, and the other was a multiwindows CDU based on graphical user interface techniques. For both application and evaluation reasons, constraints were applied to the graphical CDU design to maintain as much similarity as possible with the conventional CDU. This preliminary experiment was conducted to evaluate the interface effects on training. Sixteen pilots with no FMS experience were used in a between-subjects test. A time-compressed, airline-type FMS training environment was simulated. The subjects were trained to a fixed-time criterion, and performance was measured in a final, full-mission simulation context. This paper describes the technical approach, simulation implementation, and experimental results of this effort.

Abbott, Terence S.↗
NASA NTRS2002

Spatial Metadata for Global Change Investigations Using Remote Sensing

Satellite and aircraft-borne remote sensors have gathered petabytes of data over the past 30+ years. These images are an important resource for establishing cause and effect relationships between human-induced land cover changes and alterations in climate and other biophysical patterns at local to global scales. However, the spatial, temporal, and spectral characteristics of these datasets vary, thus complicating long-term studies involving several types of imagery. As the geographical and temporal coverage, the spectral and spatial resolution, and the number of individual sensors increase, the sheer volume and complexity of available data sets will complicate management and use of the rapidly growing archive of earth imagery. Mining this vast data resource for images that provide the necessary information for climate change studies becomes more difficult as more sensors are launched and more imagery is obtained.

Emerson, Charles W.↗
NASA NTRS2003

Reference architecture for space data systems

Architectures for terrestrial data systems that are built and managed by a single organization are inherently complex. In order to understand any large-scale system architecture, and to judge its applicability for its nominal task, a description of the system must be produced that exposes a number of distinct viewpoints. Within the CCSDS Architecture Working Group we have adapted the Reference Model for Open Distributed Processing to describe large, multi-national, space data systems.

CCSDS space communication reference architecture s↗
NASA NTRS2007

Reducing a Knowledge-Base Search Space When Data Are Missing

This software addresses the problem of how to efficiently execute a knowledge base in the presence of missing data. Computationally, this is an exponentially expensive operation that without heuristics generates a search space of 1 + 2n possible scenarios, where n is the number of rules in the knowledge base. Even for a knowledge base of the most modest size, say 16 rules, it would produce 65,537 possible scenarios. The purpose of this software is to reduce the complexity of this operation to a more manageable size. The problem that this system solves is to develop an automated approach that can reason in the presence of missing data. This is a meta-reasoning capability that repeatedly calls a diagnostic engine/model to provide prognoses and prognosis tracking. In the big picture, the scenario generator takes as its input the current state of a system, including probabilistic information from Data Forecasting. Using model-based reasoning techniques, it returns an ordered list of fault scenarios that could be generated from the current state, i.e., the plausible future failure modes of the system as it presently stands. The scenario generator models a Potential Fault Scenario (PFS) as a black box, the input of which is a set of states tagged with priorities and the output of which is one or more potential fault scenarios tagged by a confidence factor. The results from the system are used by a model-based diagnostician to predict the future health of the monitored system.

James, Mark↗
NASA NTRS2015

Integrated Surface Power Strategy for Mars

A National Aeronautics and Space Administration (NASA) study team evaluated surface power needs for a conceptual crewed 500-day Mars mission. This study had four goals: 1. Determine estimated surface power needed to support the reference mission; 2. Explore alternatives to minimize landed power system mass; 3. Explore alternatives to minimize Mars Lander power self-sufficiency burden; and 4. Explore alternatives to minimize power system handling and surface transportation mass. The study team concluded that Mars Ascent Vehicle (MAV) oxygen propellant production drives the overall surface power needed for the reference mission. Switching to multiple, small Kilopower fission systems can potentially save four to eight metric tons of landed mass, as compared to a single, large Fission Surface Power (FSP) concept. Breaking the power system up into modular packages creates new operational opportunities, with benefits ranging from reduced lander self-sufficiency for power, to extending the exploration distance from a single landing site. Although a large FSP trades well for operational complexity, a modular approach potentially allows Program Managers more flexibility to absorb late mission changes with less schedule or mass risk, better supports small precursor missions, and allows a program to slowly build up mission capability over time. A number of Kilopower disadvantages-and mitigation strategies-were also explored.

Rucker, Michelle↗
NASA NTRS2018

A Fast Monte Carlo Method for Model-Based Prognostics Based on Stochastic Calculus

This work proposes a fast Monte Carlo method to solve differential equations utilized in model-based prognostics. The methodology is derived from the theory of stochastic calculus, and the goal of such a method is to speed up the estimation of the probability density functions describing the independent variable evolution over time. In the prognostic scenarios presented in this paper, the stochastic differential equations describe variables directly or indirectly related to the degradation of a monitored system. The method allows the estimation of the probability density functions by solving the deterministic equation and approximating the stochastic integrals using samples of the model noise. By so doing, the prognostic problem is solved without the Monte Carlo simulation based on Euler's forward method, which is typically the most time consuming task of the prediction stage. Three different prognostic scenarios are presented as proof of concept: (i) life prediction of electrolytic capacitors, (ii) remaining time to discharge of Lithium-ion batteries, and (iii) prognostic of cracked structures under fatigue loading. The paper shows how the method produces probability density functions that are statistically indistinguishable from the distributions estimated with Euler's forward Monte Carlo simulation. However, the proposed solution is orders of magnitude faster when computing the time-to-failure distribution of the monitored system. The approach may enable complex real-time prognostics and health management solutions with limited computing power.

Corbetta, M.↗
NASA NTRS2019

A Fast Monte Carlo Method for Model-Based Prognostics Based on Stochastic Calculus

This work proposes a fast Monte Carlo method to solve differential equations utilized in model-based prognostics. The methodology is derived from the theory of stochastic calculus, and the goal of such a method is to speed up the estimation of the probability density functions describing the independent variable evolution over time. In the prognostic scenarios presented in this paper, the stochastic differential equations describe variables directly or indirectly related to the degradation of a monitored system. The method allows the estimation of the probability density functions by solving the deterministic equation and approximating the stochastic integrals using samples of the model noise. By so doing, the prognostic problem is solved without the Monte Carlo simulation based on Euler's forward method, which is typically the most time consuming task of the prediction stage. Three different prognostic scenarios are presented as proof of concept: (i) life prediction of electrolytic capacitors, (ii) remaining time to discharge of Lithium-ion batteries, and (iii) prognostic of cracked structures under fatigue loading. The paper shows how the method produces probability density functions that are statistically indistinguishable from the distributions estimated with Euler's forward Monte Carlo simulation. However, the proposed solution is orders of magnitude faster when computing the time-to-failure distribution of the monitored system. The approach may enable complex real-time prognostics and health management solutions with limited computing power.

stochastic calculus↗
NASA NTRS2015

3D Photocatalytic Air Processor for Dramatic Reduction of Life Support Mass and Complexity

To dramatically reduce the cost and risk of CO2 management systems in future extended missions, we have conducted preliminary studies on the materials and device development for advanced "artificial photosynthesis" reaction systems termed the High Tortuosity PhotoElectroChemical (HTPEC) system. Our Phase I studies have demonstrated that HTPEC operates in much the same way a tree would function, namely directly contacting the cabin air with a photocatalyst in the presence of light and water (as humidity) to immediately conduct the process of CO2 reduction to O2 and useful, "tunable" carbon products. This eliminates many of the inefficiencies associated with current ISS CO2 management systems. We have laid the solid foundation for Phase II work to employ novel and efficient reactor geometries, lighting approaches, 3D manufacturing methods and in-house grown novel catalytic materials.The primary objective of the proposed work is to demonstrate the scientific and engineering foundation for light-activated, compact devices capable of converting CO2 to O2 and mission-relevant carbon compounds. The proposed HTPEC CO2 management system will demonstrate a novel pathway with high efficiency and reliability in a compact, lightweight reactor architecture. The proposed HTPEC air processing concept can be developed in multiple architectures, such as centralized processing as well as "artificial leaves" distributed throughout the cabin that utilize pre-existing cabin ventilation (wind). Additionally, HTPEC can be deployed with spectrally tunable collection channels for selectable product generation. HTPEC employs light as its only energy source to remove and convert waste CO2 using a non-toxic composite catalyst.We have demonstrated in the Phase I studies the production, tunability and robustness of the novel composite catalysts following the preliminary work in the Chen laboratory. Additionally, we have designed, fabricated and tested all components of HTPEC device with active materials, including flow modeling to optimize flow mixing and pressure drop as well as the production of ethylene and other larger hydrocarbons. To best determine how this technology could be implemented, we also performed system integration optimization and trade studies. This includes parameters such as mass, volume, power in relation to selected mission configurations, CO2 delivery methods and light source/delivery approaches.

Artificial Photosynthesis↗
NASA NTRS2021

Bias Correction of Hydrologic Projections Strongly Impacts Inferred Climate Vulnerabilities in Institutionally Complex Water Systems

Water-resources planners use regional water management models (WMMs) to identify vulnerabilities to climate change. Frequently, dynamically downscaled climate inputs are used in conjunction with land-surface models (LSMs) to provide hydrologic streamflow projections, which serve as critical inputs for WMMs. Here, we show how even modest projection errors can strongly affect assessments of water availability and financial stability for irrigation districts in California. Specifically, our results highlight that LSM errors in projections of flood and drought extremes are highly interactive across timescales, path-dependent, and can be amplified when modeling infrastructure systems (e.g., misrepresenting banked groundwater). Common strategies for reducing errors in deterministic LSM hydrologic projections (e.g., bias correction) can themselves strongly distort projected climate vulnerabilities and misrepresent their inferred financial consequences. Overall, our results indicate a need to move beyond standard deterministic climate projection and error management frameworks that are dependent on single simulated climate change scenario outcomes.

Keyvan Malek↗
DOE OSTI2012

HERCULES: A Pattern Driven Code Transformation System

New parallel computers are emerging, but developing efficient scientific code for them remains difficult. A scientist must manage not only the science-domain complexity but also the performance-optimization complexity. HERCULES is a code transformation system designed to help the scientist to separate the two concerns, which improves code maintenance, and facilitates performance optimization. The system combines three technologies, code patterns, transformation scripts and compiler plugins, to provide the scientist with an environment to quickly implement code transformations that suit his needs. Unlike existing code optimization tools, HERCULES is unique in its focus on user-level accessibility. In this paper we discuss the design, implementation and an initial evaluation of HERCULES.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2014

Consensus Standardization of Slurry Simulant Development Process to Reduce Design Risk Within the DOE Complex

A critical responsibility of DOE’s Office of Environmental Management is the design, construction, and operation of equipment and facilities to process legacy radioactive waste slurries for safe, long-term disposal. The accomplishment of this mission requires the extensive use of physical and chemical simulants to represent the hazardous radioactive waste. Development and characterization of simulants can often be difficult to compare or utilize as questions exist as to the basis, techniques, or consistency associated with reported parameters. In addition, controversy has existed in the interpretation and application of the characterization data for the wastes that the simulants are intended to represent.

design↗
DOE OSTI2012

A Practical Approach to a Closed Nuclear Fuel Cycle and Sustained Nuclear Energy - 12383

Recent systems analysis studies at Oak Ridge National Laboratory (ORNL) have shown that sufficient information is available from previous research and development (R and D), industrial experience, and current studies to make rational decisions on a practical approach to a closed nuclear fuel cycle in the United States. These studies show that a near-term decision is needed to recycle used nuclear fuel (UNF) in the United States, to encourage public recognition that a practical solution to disposal of nuclear energy wastes, primarily UNF, is achievable, and to ensure a focus on essential near-term actions and future R and D. Recognition of the importance of time factors is essential, including the multi-decade time period required to implement industrial-scale fuel recycle at the capacity needed, and the effects of radioactive decay on proliferation resistance, recycling complexity, radioactive emissions, and high-level-waste storage, disposal form development, and eventual emplacement in a geologic repository. Analysis of time factors led to identification of the benefits of processing older fuel and an 'optimum decay storage time'. Further benefits of focused R and D can ensure more complete recycling of UNF components and minimize wastes requiring disposal. Analysis of recycling costs and nonproliferation requirements, which are often cited as reasons for delaying a decision to recycle, shows that (1) the differences in costs of nuclear energy with open or closed fuel cycles are insignificant and (2) nonproliferation requirements can be met by a combination of 'safeguards-by-design' co-location of back-end fuel cycle facilities, and applied engineered safeguards and monitoring. The study shows why different methods of separating and recycling used fuel components do not have a significant effect on nonproliferation requirements and can be selected on other bases, such as process efficiency, maturity, and cost-effectiveness. Finally, the study concludes that continued storage of UNF without a decision to recycle is not a solution to the problem of nuclear waste disposal, but can be a deterrent to public confidence in nuclear energy. In summary, our studies have shown, in contrast to findings of the more prominent studies, that today we do have sufficient knowledge to make informed choices for the values and essential methods of UNF recycling, based on previous research, industrial experience, and current analyses. We have shown the significant importance of time factors, including the benefits of an optimum decay storage time on deploying effective nonproliferation safeguards, enabling reduced recycling complexity and environmental emissions, and optimizing waste management and disposal. Together with the multi-decade time required to implement industrial-scale UNF recycle at the capacity needed to match generation rate, our conclusion is that a near-term decision to recycle as many UNF components as possible is vitally needed. Further indecision and procrastination can lead to a loss of public confidence and favorable perception of nuclear energy. With no near-term decision, the path forward for UNF disposal will remain uncertain, with many diverse technologies being considered and no possible focus on a practical solution to the problem. However, a near-term decision to recycle UNF fuel and to take advantage of processing UNF and surface storing HLW, together with development and incorporation of more-complete recycling of UNF components, can provide the focus needed for a practical solution to the problem of nuclear waste disposal. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗