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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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NASA NTRSDate not supplied

Variability in Modelled Airborne Dust Mineralogy Derived from Global Soil Composition Uncertainties

Dust aerosols consist on a variety of minerals with different physic and chemical properties. As such, they interact with short and long wave radiation, potentially form clouds, act as nutrients modulating biogeochemical cycles, or influence atmospheric chemistry, differently. Most current state-of-the-art Earth System Models (ESMs) neglect the complexity in dust composition, mainly due to computational constraints, but also to the existing uncertainties in the size resolved composition of parent soils, the resulting distribution of minerals in airborne dust, and the scarcity of observations to constrain them. Within this work, we assess the variability of global dust composition due to uncertainties in the characterization of the parent soil mineralogy. To that end, we consider two available global soil mineralogy atlases, developed by Claquin et al. (1999) –C1999- and Journet et al. (2014) –J2014-, which represent respectively 8 and 12 relevant minerals for climate (namely: illite, smectite/montmorillonite, kaolinite, calcite, gypsum, hematite, quartz, and feldspars in C1999, and those plus chlorite, vermiculite, goethite, and mica in J2014). Thanks to a recently developed feature of the MONARCH atmospheric-chemistry model, we are able to explicitly resolve the minerals’ atmospheric cycle. Therefore, we define two global experiments to assess changes on airborne dust composition attributed to the soil mineralogy assumptions and provide a measure of their variability. We also perform a preliminary evaluation of the global mineralogy results against available observations of mineral fractions in surface dust concentration. Our results will inform the climate modelling community about the potential variability in dust composition, an aspect that will gain relevance as ESMs continue growing in complexity and new processes to better characterize aerosols’ forcing or biogeochemical cycles are added. Further observational constraints, such as those that will derive from the EMIT NASA mission on soil composition or the FRAGMENT experimental campaigns on airborne dust characterization, will be key in the near future to improve our understanding of the impact of dust mineralogy on fundamental climate features.

Dust aerosols↗
NASA NTRS1990

Dynamic control of robotic welding - On-going research

Two major challenges exist for the development of dynamic control systems: first, the control system must be resourceful enough to provide problem-solving capabilities in unforeseen circumstances; second, it must be rapid enough to respond to dynamic environments. Most conventional control systems do not have the ability to 'step back' and problem-solve, especially in environments with incomplete and uncertain models and data. Orthogonally, commercially available AI systems usually do not respond at the rates required to support 'real-time' control. Hence, control systems are not available that respond to complex dynamic environments within appropriate time constraints. This paper describes work on an AI-based control system designed to address these challenges. A prototype system has been used, in a simulated environment, to control the robotic welding of aerospace components. This AI-based control system has demonstrated the ability to flexibly control a complex process within required time constraints by incorporating higher level reasoning and the ability to deal with uncertainty. Further work is in progress to expand the system's problem-solving capabilities.

Ruokangas, Corinne C.↗
NASA NTRS1998

Space Shuttle Main Engine Quantitative Risk Assessment: Illustrating Modeling of a Complex System with a New QRA Software Package

During 1997, a team from Hernandez Engineering, MSFC, Rocketdyne, Thiokol, Pratt & Whitney, and USBI completed the first phase of a two year Quantitative Risk Assessment (QRA) of the Space Shuttle. The models for the Shuttle systems were entered and analyzed by a new QRA software package. This system, termed the Quantitative Risk Assessment System(QRAS), was designed by NASA and programmed by the University of Maryland. The software is a groundbreaking PC-based risk assessment package that allows the user to model complex systems in a hierarchical fashion. Features of the software include the ability to easily select quantifications of failure modes, draw Event Sequence Diagrams(ESDs) interactively, perform uncertainty and sensitivity analysis, and document the modeling. This paper illustrates both the approach used in modeling and the particular features of the software package. The software is general and can be used in a QRA of any complex engineered system. The author is the project lead for the modeling of the Space Shuttle Main Engines (SSMEs), and this paper focuses on the modeling completed for the SSMEs during 1997. In particular, the groundrules for the study, the databases used, the way in which ESDs were used to model catastrophic failure of the SSMES, the methods used to quantify the failure rates, and how QRAS was used in the modeling effort are discussed. Groundrules were necessary to limit the scope of such a complex study, especially with regard to a liquid rocket engine such as the SSME, which can be shut down after ignition either on the pad or in flight. The SSME was divided into its constituent components and subsystems. These were ranked on the basis of the possibility of being upgraded and risk of catastrophic failure. Once this was done the Shuttle program Hazard Analysis and Failure Modes and Effects Analysis (FMEA) were used to create a list of potential failure modes to be modeled. The groundrules and other criteria were used to screen out the many failure modes that did not contribute significantly to the catastrophic risk. The Hazard Analysis and FMEA for the SSME were also used to build ESDs that show the chain of events leading from the failure mode occurence to one of the following end states: catastrophic failure, engine shutdown, or siccessful operation( successful with respect to the failure mode under consideration).

Smart, Christian↗
NASA NTRSDate not supplied

Space-borne Doppler Weather Radar Modeling for Radar Design Evaluation

A model has been developed to predict the reflectivity and Doppler performance of a spaceborne weather radar for atmospheric aerosol and cloud monitoring. The goal is to predict radar sensitivity, resolution, uncertainties and other key performance metrics vs. radar design parameters and hardware nonidealities. Analytical formulas are readily available to predict key performance metrics of a space-borne radar system as a function of design parameters such as antenna size, spacecraft velocity, transmit power, and receive noise figure. Effects of some system nonidealities such as antenna pointing errors, power amplifier nonlinearity and phase noise can be estimated using idealized methods. These analytical formulas use idealized forms of the antenna radiation pattern and weather statistics to predict system performance. However, it is desirable to have a more physical model based on discretized weather volumes in which the particle size distribution, Doppler distribution, and other parameters can be varied to study how the radar hardware design parameters and nonidealities affect the measurement of the weather reflectivity and Doppler characteristics. This would allow the radar designers to have more insight into what is being measured and the hardware parameters and errors that need to be carefully controlled to achieve best radar performance, as well as potential methods to calibrate the system or correct errors. This presentation will demonstrate some proof-of-concept Ka-band simulations where the discretized model agrees with the analytical formulas for a simple case where the elements in the discretized weather volume are defined by a constant reflectivity and simple velocity vectors. In particular, the system sensitivity and Doppler uncertainty are evaluated by analytical formulas as well as the discretized model. Future work will expand on this to include more complex weather scenarios and the addition of system nonidealities.

Sara Tucker↗
NASA NTRS2021

Reduced Complexity Model Intercomparison Project Phase 2: Synthesizing Earth System Knowledge for Probabilistic Climate Projections

Over the last decades, climate science has evolved rapidly across multiple expert domains. Our best tools to capture state-of-the-art knowledge in an internally self-consistent modelling framework are the increasingly complex fully coupled Earth System Models (ESMs). However, computational limitations and the structural rigidity of ESMs mean that the full range of uncertainties across multiple domains are difficult to capture with ESMs alone. The tools of choice are instead more computationally efficient reduced complexity models (RCMs), which are structurally flexible and can span the response dynamics across a range of domain-specific models and ESM experiments. Here we present Phase 2 of the Reduced Complexity Model Intercomparison Project (RCMIP Phase 2), the first comprehensive intercomparison of RCMs that are probabilistically calibrated with key benchmark ranges from specialized research communities. Unsurprisingly, but crucially, we find that models which have been constrained to reflect the key benchmarks better reflect the key benchmarks. Under the low-emissions SSP1-1.9 scenario, across the RCMs, median peak warming projections range from 1.3 to 1.7°C (relative to 1850-1900, using an observationally-based historical warming estimate of 0.8°C between 1850-1900 and 1995-2014). Further developing methodologies to constrain these projection uncertainties seems paramount given the international community's goal to contain warming to below 1.5°C above pre-industrial in the long-term. Our findings suggest that users of RCMs should carefully evaluate their RCM, specifically its skill against key benchmarks and consider the need to include projections benchmarks either from ESM results or other assessments to reduce divergence in future projections.

Climate↗
NASA NTRS2010

Energy Management of the Multi-Mission Space Exploration Vehicle Using a Goal-Oriented Control System

Safe human exploration in space missions requires careful management of limited resources such as breathable air and stored electrical energy. Daily activities for astronauts must be carefully planned with respect to such resources, and usage must be monitored as activities proceed to ensure that they can be completed while maintaining safe resource margins. Such planning and monitoring can be complex because they depend on models of resource usage, the activities being planned, and uncertainties. This paper describes a system - and the technology behind it - for energy management of the NASA-Johnson Space Center's Multi-Mission Space Exploration Vehicles (SEV), that provides, in an onboard advisory mode, situational awareness to astronauts and real-time guidance to mission operators. This new capability was evaluated during this year's Desert RATS (Research and Technology Studies) planetary exploration analog test in Arizona. This software aided ground operators and crew members in modifying the day s activities based on the real-time execution of the plan and on energy data received from the rovers.

Braman, Julia M. B.↗
NASA NTRS2008

Sensitivity of Polar Stratospheric Ozone Loss to Uncertainties in Chemical Reaction Kinetics

Several recent observational and laboratory studies of processes involved in polar stratospheric ozone loss have prompted a reexamination of aspects of our understanding for this key indicator of global change. To a large extent, our confidence in understanding and projecting changes in polar and global ozone is based on our ability to simulate these processes in numerical models of chemistry and transport. The fidelity of the models is assessed in comparison with a wide range of observations. These models depend on laboratory-measured kinetic reaction rates and photolysis cross sections to simulate molecular interactions. A typical stratospheric chemistry mechanism has on the order of 50- 100 species undergoing over a hundred intermolecular reactions and several tens of photolysis reactions. The rates of all of these reactions are subject to uncertainty, some substantial. Given the complexity of the models, however, it is difficult to quantify uncertainties in many aspects of system. In this study we use a simple box-model scenario for Antarctic ozone to estimate the uncertainty in loss attributable to known reaction kinetic uncertainties. Following the method of earlier work, rates and uncertainties from the latest laboratory evaluations are applied in random combinations. We determine the key reactions and rates contributing the largest potential errors and compare the results to observations to evaluate which combinations are consistent with atmospheric data. Implications for our theoretical and practical understanding of polar ozone loss will be assessed.

Kawa, S. Randolph↗
NASA NTRS1996

Integrated Aeropropulsion Control System Design

%T Integrated Aeropropulsion Control System Design%A C-F. Lin%A Francis X. Hurley%A Jie Huang%A F. Y. Hadaegh%J International Conference on Control and Information(psi)995%C Hong Kong%D June 1995%K aeropropulsion, control, system%U http://jpltrs.jpl.nasa.gov/1995/95-0658.pdfAn integrated intelligent control approach is proposed to design a high performance control system for aeropropulsion systems based on advanced sensor processing, nonlinear control and neural fuzzy control integration. Our approach features the following innovations:??e complexity and uncertainty issues are addressed via the distributed parallel processing, learning, and online reoptimization properties of neural networks.??e nonlinear dynamics and the severe coupling can be naturally incorporated into the design framework.??e knowledge base and decision making logic furnished by fuzzy systems leads to a human intelligence enhanced control scheme.In addition, fault tolerance, health monitoring and reconfigurable control strategies will be accommodated by this approach to ensure stability, graceful degradation and reoptimization in the case of failures, malfunctions and damage.!.

aeropropulsion control systems↗
NASA NTRS2006

Integrated Vehicle Health Management (IVHM) for Aerospace Systems

To achieve NASA's ambitious Integrated Space Transportation Program objectives, aerospace systems will implement a variety of new concept in health management. System level integration of IVHM technologies for real-time control and system maintenance will have significant impact on system safety and lifecycle costs. IVHM technologies will enhance the safety and success of complex missions despite component failures, degraded performance, operator errors, and environment uncertainty. IVHM also has the potential to reduce, or even eliminate many of the costly inspections and operations activities required by current and future aerospace systems. This presentation will describe the array of NASA programs participating in the development of IVHM technologies for NASA missions. Future vehicle systems will use models of the system, its environment, and other intelligent agents with which they may interact. IVHM will be incorporated into future mission planners, reasoning engines, and adaptive control systems that can recommend or execute commands enabling the system to respond intelligently in real time. In the past, software errors and/or faulty sensors have been identified as significant contributors to mission failures. This presentation will also address the development and utilization of highly dependable sohare and sensor technologies, which are key components to ensure the reliability of IVHM systems.

Baroth, Edmund C.↗
NASA NTRS2013

Development of Large-Scale Spacecraft Fire Safety Experiments

The status is presented of a spacecraft fire safety research project that is under development to reduce the uncertainty and risk in the design of spacecraft fire safety systems by testing at nearly full scale in low-gravity. Future crewed missions are expected to be more complex and longer in duration than previous exploration missions outside of low-earth orbit. This will increase the challenge of ensuring a fire-safe environment for the crew throughout the mission. Based on our fundamental uncertainty of the behavior of fires in low-gravity, the need for realistic scale testing at reduced gravity has been demonstrated. To address this gap in knowledge, a project has been established under the NASA Advanced Exploration Systems Program under the Human Exploration and Operations Mission directorate with the goal of substantially advancing our understanding of the spacecraft fire safety risk. Associated with the project is an international topical team of fire experts from other space agencies who conduct research that is integrated into the overall experiment design. The experiments are under development to be conducted in an Orbital Science Corporation Cygnus vehicle after it has undocked from the ISS. Although the experiment will need to meet rigorous safety requirements to ensure the carrier vehicle does not sustain damage, the absence of a crew removes the need for strict containment of combustion products. The tests will be fully automated with the data downlinked at the conclusion of the test before the Cygnus vehicle reenters the atmosphere. A computer modeling effort will complement the experimental effort. The international topical team is collaborating with the NASA team in the definition of the experiment requirements and performing supporting analysis, experimentation and technology development. The status of the overall experiment and the associated international technology development efforts are summarized.

Life Support↗
NASA NTRS2009

A Distributed Prognostic Health Management Architecture

This paper introduces a generic distributed prognostic health management (PHM) architecture with specific application to the electrical power systems domain. Current state-of-the-art PHM systems are mostly centralized in nature, where all the processing is reliant on a single processor. This can lead to loss of functionality in case of a crash of the central processor or monitor. Furthermore, with increases in the volume of sensor data as well as the complexity of algorithms, traditional centralized systems become unsuitable for successful deployment, and efficient distributed architectures are required. A distributed architecture though, is not effective unless there is an algorithmic framework to take advantage of its unique abilities. The health management paradigm envisaged here incorporates a heterogeneous set of system components monitored by a varied suite of sensors and a particle filtering (PF) framework that has the power and the flexibility to adapt to the different diagnostic and prognostic needs. Both the diagnostic and prognostic tasks are formulated as a particle filtering problem in order to explicitly represent and manage uncertainties; however, typically the complexity of the prognostic routine is higher than the computational power of one computational element ( CE). Individual CEs run diagnostic routines until the system variable being monitored crosses beyond a nominal threshold, upon which it coordinates with other networked CEs to run the prognostic routine in a distributed fashion. Implementation results from a network of distributed embedded devices monitoring a prototypical aircraft electrical power system are presented, where the CEs are Sun Microsystems Small Programmable Object Technology (SPOT) devices.

Bhaskar, Saha↗
NASA NTRS1997

The Problem of Size in Robust Design

To facilitate the effective solution of multidisciplinary, multiobjective complex design problems, a departure from the traditional parametric design analysis and single objective optimization approaches is necessary in the preliminary stages of design. A necessary tradeoff becomes one of efficiency vs. accuracy as approximate models are sought to allow fast analysis and effective exploration of a preliminary design space. In this paper we apply a general robust design approach for efficient and comprehensive preliminary design to a large complex system: a high speed civil transport (HSCT) aircraft. Specifically, we investigate the HSCT wing configuration design, incorporating life cycle economic uncertainties to identify economically robust solutions. The approach is built on the foundation of statistical experimentation and modeling techniques and robust design principles, and is specialized through incorporation of the compromise Decision Support Problem for multiobjective design. For large problems however, as in the HSCT example, this robust design approach developed for efficient and comprehensive design breaks down with the problem of size - combinatorial explosion in experimentation and model building with number of variables -and both efficiency and accuracy are sacrificed. Our focus in this paper is on identifying and discussing the implications and open issues associated with the problem of size for the preliminary design of large complex systems.

Koch, Patrick N.↗
NASA NTRS2016

Space Launch System Booster Separation Aerodynamic Database Development and Uncertainty Quantification

The development of the aerodynamic database for the Space Launch System (SLS) booster separation environment has presented many challenges because of the complex physics of the ow around three independent bodies due to proximity e ects and jet inter- actions from the booster separation motors and the core stage engines. This aerodynamic environment is dicult to simulate in a wind tunnel experiment and also dicult to simu- late with computational uid dynamics. The database is further complicated by the high dimensionality of the independent variable space, which includes the orientation of the core stage, the relative positions and orientations of the solid rocket boosters, and the thrust lev- els of the various engines. Moreover, the clearance between the core stage and the boosters during the separation event is sensitive to the aerodynamic uncertainties of the database. This paper will present the development process for Version 3 of the SLS booster separa- tion aerodynamic database and the statistics-based uncertainty quanti cation process for the database.

Chan, David T.↗
NASA NTRS1978

Quantum nondemolition measurements of harmonic oscillators

Measuring systems to determine the real component of the complex amplitude of a harmonic oscillator are described. This amplitude is constant in the absence of driving forces, and the uncertainty principle accounts for the fact that only the real component can be measured precisely and continuously ('quantum nondemolition measurement'). Application of the measuring systems to the detection of gravitational waves is considered.

Thorne, K. S.↗
NASA NTRSDate not supplied

The Big Plunge at Venus: The DAVINCI Descent Phase

DAVINCI (Deep Atmosphere Venus Investigation of Noble gases, Chemistry, and Imaging) was selected as one of two new Discovery missions in summer of 2021 with the primary goals to study how the Venus atmosphere formed and changed over time. DAVINCI does this by making in situ measurements of the atmosphere, taking images below the cloud layer during the descent phase, and imaging the surface and clouds during two flyby science opportunities. The Descent Sphere is neither designed nor required to land on the surface so all critical science data must be taken and transmitted to a relay spacecraft prior to impact. This architecture drives the mission to a carefully-crafted concept of operations; deployments, instrument operations, and communications are choreographed to ensure the right data is gathered at the right altitude given the uncertainties in the trajectory and timeline. A complex flow of analyses and tests throughout development will validate the system’s ability to execute the mission goals. In the end DAVINCI will be ready for its one hour of descent time to meet its driving science goals.

DAVINCI↗
NASA NTRSDate not supplied

The Big Plunge at Venus: The DAVINCI Descent Phase

DAVINCI (Deep Atmosphere Venus Investigation of Noble gases, Chemistry, and Imaging) was selected as one of two new Discovery missions in summer of 2021 with the primary goals are to study how the Venus atmosphere formed and changed over time. DAVINCI does this by making in situ measurements of the atmosphere and taking images below the cloud layer during the descent phase. The probe is neither designed nor required to land on the surface so all critical science data must be taken and transmitted to a relay spacecraft prior to impact. This architecture drives the mission to a carefully-crafted concept of operations; deployments, instrument operations, and communications are choreographed to ensure the right data is gathered at the right altitude given the uncertainties in the trajectory and timeline. A complex flow of analyses and tests throughout development will validate the system’s ability to execute the mission goals. In the end, DAVINCI will be ready for the one opportunity at one hour of descent time to meet its driving science goals.

DAVINCI↗
NASA NTRS2009

Synthesis and Control of Flexible Systems with Component-Level Uncertainties

An efficient and computationally robust method for synthesis of component dynamics is developed. The method defines the interface forces/moments as feasible vectors in transformed coordinates to ensure that connectivity requirements of the combined structure are met. The synthesized system is then defined in a transformed set of feasible coordinates. The simplicity of form is exploited to effectively deal with modeling parametric and non-parametric uncertainties at the substructure level. Uncertainty models of reasonable size and complexity are synthesized for the combined structure from those in the substructure models. In particular, we address frequency and damping uncertainties at the component level. The approach first considers the robustness of synthesized flexible systems. It is then extended to deal with non-synthesized dynamic models with component-level uncertainties by projecting uncertainties to the system level. A numerical example is given to demonstrate the feasibility of the proposed approach.

Maghami, Peiman G.↗
NASA NTRS2010

World, We Have Problems: Simulation for Large Complex, Risky Projects, and Events

Prior to a spacewalk during the NASA STS/129 mission in November 2009, Columbia Broadcasting System (CBS) correspondent William Harwood reported astronauts, "were awakened again", as they had been the day previously. Fearing something not properly connected was causing a leak, the crew, both on the ground and in space, stopped and checked everything. The alarm proved false. The crew did complete its work ahead of schedule, but the incident reminds us that correctly connecting hundreds and thousands of entities, subsystems and systems, finding leaks, loosening stuck valves, and adding replacements to very large complex systems over time does not occur magically. Everywhere major projects present similar pressures. Lives are at - risk. Responsibility is heavy. Large natural and human-created disasters introduce parallel difficulties as people work across boundaries their countries, disciplines, languages, and cultures with known immediate dangers as well as the unexpected. NASA has long accepted that when humans have to go where humans cannot go that simulation is the sole solution. The Agency uses simulation to achieve consensus, reduce ambiguity and uncertainty, understand problems, make decisions, support design, do planning and troubleshooting, as well as for operations, training, testing, and evaluation. Simulation is at the heart of all such complex systems, products, projects, programs, and events. Difficult, hazardous short and, especially, long-term activities have a persistent need for simulation from the first insight into a possibly workable idea or answer until the final report perhaps beyond our lifetime is put in the archive. With simulation we create a common mental model, try-out breakdowns of machinery or teamwork, and find opportunity for improvement. Lifecycle simulation proves to be increasingly important as risks and consequences intensify. Across the world, disasters are increasing. We anticipate more of them, as the results of global warming prove more and more ominous-glaciers melting in Bolivia, floods in Saudi Arabia, the Maldives sinking and salt rising along the Nile. Fear grows about potential asteroid crashes and nightly television images raise awareness of victims of floods, hurricanes, cyclones and typhoons, fire, tornado, tsunami, bombings, landslides, and cross-boundary criminality. The Red Cross says that disasters impact 250 million people each year. That means that 700,000 people are having a very bad day today. Modeling and simulation is and must be part of the solution.

Elfrey, Priscilla↗