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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 NTRS2012

Life Cycle of Midlatitude Deep Convective Systems in a Lagrangian Framework

Deep Convective Systems (DCSs) consist of intense convective cores (CC), large stratiform rain (SR) regions, and extensive non-precipitating anvil clouds (AC). This study focuses on the evolution of these three components and the factors that affect convective AC production. An automated satellite tracking method is used in conjunction with a recently developed multi-sensor hybrid classification to analyze the evolution of DCS structure in a Lagrangian framework over the central United States. Composite analysis from 4221 tracked DCSs during two warm seasons (May-August, 2010-2011) shows that maximum system size correlates with lifetime, and longer-lived DCSs have more extensive SR and AC. Maximum SR and AC area lag behind peak convective intensity and the lag increases linearly from approximately 1-hour for short-lived systems to more than 3-hours for long-lived ones. The increased lag, which depends on the convective environment, suggests that changes in the overall diabatic heating structure associated with the transition from CC to SR and AC could prolong the system lifetime by sustaining stratiform cloud development. Longer-lasting systems are associated with up to 60% higher mid-tropospheric relative humidity and up to 40% stronger middle to upper tropospheric wind shear. Regression analysis shows that the areal coverage of thick AC is strongly correlated with the size of CC, updraft strength, and SR area. Ambient upper tropospheric wind speed and wind shear also play an important role for convective AC production where for systems with large AC (radius greater than 120-km) they are 24% and 20% higher, respectively, than those with small AC (radius=20 km).

Feng, Zhe↗
NASA NTRS2014

An Overview of Current Capabilities and Research Activities in the Airspace Operations Laboratory at NASA Ames Research Center

The Airspace Operations Laboratory at NASA Ames conducts research to provide a better understanding of roles, responsibilities, and requirements for human operators and automation in future air traffic management (ATM) systems. The research encompasses developing, evaluating, and integrating operational concepts and technologies for near-, mid-, and far-term air traffic operations. Current research threads include efficient arrival operations, function allocation in separation assurance and efficient airspace and trajectory management. The AOL has developed powerful air traffic simulation capabilities, most notably the Multi Aircraft Control System (MACS) that is used for many air traffic control simulations at NASA and its partners in government, academia and industry. Several additional NASA technologies have been integrated with the AOL's primary simulation capabilities where appropriate. Using this environment, large and small-scale system-level evaluations can be conducted to help make near-term improvements and transition NASA technologies to the FAA, such as the technologies developed under NASA's Air Traffic Management Demonstration-1 (ATD-1). The AOL's rapid prototyping and flexible simulation capabilities have proven a highly effective environment to progress the initiation of trajectory-based operations and support the mid-term implementation of NextGen. Fundamental questions about accuracy requirements have been investigated as well as realworld problems on how to improve operations in some of the most complex airspaces in the US. This includes using advanced trajectory-based operations and prototype tools for coordinating arrivals to converging runways at Newark airport and coordinating departures and arrivals in the San Francisco and the New York metro areas. Looking beyond NextGen, the AOL has started exploring hybrid human/automation control strategies as well as highly autonomous operations in the air traffic control domain. Initial results indicate improved capacity, low operator workload, good situation awareness and acceptability for controllers teaming with autonomous air traffic systems. While much research and development needs to be conducted to make such concepts a reality, these approaches have the potential to truly transform the airspace system towards increased mobility, safe and efficient growth in global operations and enabling many of the new vehicles and operations that are expected over the next decades. This paper describes how the AOL currently contributes to the ongoing air transportation transformation.

simulation↗
NASA NTRS2020

Assembly and Integration Process of the High-Density Detector Array Readout Modules for the Simons Observatory

The Simons Observatory will measure the cosmic microwave background tempera-ture and polarization using a suite of new telescopes in the Atacama Desert in Chile. The Simons Observatory will use dichroic transition edge sensor (TES) bolometer arrays spanning six frequency bands from 27 to 280 GHz. The Simons Observa-tory will pioneer the use of a densely packed multiplexing architecture based on the microwave SQUID multiplexer ( 𝜇mux), housing ∼2000 microwave resonators, each coupled to a TES. The Simons Observatory aims to multiplex each array of ∼2000 detectors with a single pair of coaxial cables and requires a multiplexing factor of ∼1000 . The Simons Observatory cryogenic readout system is called the universal microwave multiplexing module (UMM). The UMM couples to both horn and lenslet-coupled detector arrays and is integrated into the universal focal-plane module (UFM) after being independently characterized. We present processes we have developed for highly repeatable and automated integration methods of UMMs, which will be needed for the production of the 49 UFMs required for the first stage of the Simons Observatory.

CMB↗
NASA NTRS2006

Control Software for Advanced Video Guidance Sensor

Embedded software has been developed specifically for controlling an Advanced Video Guidance Sensor (AVGS). A Video Guidance Sensor is an optoelectronic system that provides guidance for automated docking of two vehicles. Such a system includes pulsed laser diodes and a video camera, the output of which is digitized. From the positions of digitized target images and known geometric relationships, the relative position and orientation of the vehicles are computed. The present software consists of two subprograms running in two processors that are parts of the AVGS. The subprogram in the first processor receives commands from an external source, checks the commands for correctness, performs commanded non-image-data-processing control functions, and sends image data processing parts of commands to the second processor. The subprogram in the second processor processes image data as commanded. Upon power-up, the software performs basic tests of functionality, then effects a transition to a standby mode. When a command is received, the software goes into one of several operational modes (e.g. acquisition or tracking). The software then returns, to the external source, the data appropriate to the command.

Howard, Richard T.↗
NASA NTRS2017

A Comparison of the SOCIT and DebriSat Experiments

This paper explores the differences between, and shares the lessons learned from, two hypervelocity impact experiments critical to the update of orbital debris environment models. The procedures and processes of the fourth Satellite Orbital Debris Characterization Impact Test (SOCIT) were analyzed and related to the ongoing DebriSat experiment. SOCIT was the first hypervelocity impact test designed specifically for satellites in Low Earth Orbit (LEO). It targeted a 1960's U.S. Navy satellite, from which data was obtained to update pre-existing NASA and DOD breakup models. DebriSat is a comprehensive update to these satellite breakup models- necessary since the material composition and design of satellites have evolved from the time of SOCIT. Specifically, DebriSat utilized carbon fiber, a composite not commonly used in satellites during the construction of the US Navy Transit satellite used in SOCIT. Although DebriSat is an ongoing activity, multiple points of difference are drawn between the two projects. Significantly, the hypervelocity tests were conducted with two distinct satellite models and test configurations, including projectile and chamber layout. While both hypervelocity tests utilized soft catch systems to minimize fragment damage to its post-impact shape, SOCIT only covered 65% of the projected area surrounding the satellite, whereas, DebriSat was completely surrounded cross-range and downrange by the foam panels to more completely collect fragments. Furthermore, utilizing lessons learned from SOCIT, DebriSat's post-impact processing varies in methodology (i.e., fragment collection, measurement, and characterization). For example, fragment sizes were manually determined during the SOCIT experiment, while DebriSat utilizes automated imaging systems for measuring fragments, maximizing repeatability while minimizing the potential for human error. In addition to exploring these variations in methodologies and processes, this paper also presents the challenges DebriSat has encountered thus far and how they were addressed. Accomplishing DebriSat's goal of collecting 90% of the debris, which constitutes well over 100,000 fragments, required addressing many challenges stemming from the very large number of fragments. One of these challenges arose in identifying the foam-embedded fragments. DebriSat addressed this by X-raying all of the panels once the loose debris were removed, and applying a detection algorithm developed in-house to automate the embedded fragment identification process. It is easy to see how the amount of data being compiled would be outstanding. Creating an efficient way to catalog each fragment, as well as archiving the data for reproducibility also posed a great challenge for DebriSat. Barcodes to label each fragment were introduced with the foresight that once the characterization process began, the datasheet for each fragment would have to be accessed again quickly and efficiently. The DebriSat experiment has benefited significantly by leveraging lessons learned from the SOCIT experiment along with the technological advancements that have occurred during the time between the experiments. The two experiments represent two ages of satellite technology and, together, demonstrate the continuous efforts to improve the experimental techniques for fragmentation debris characterization.

Ausay, Erick↗
NASA NTRS2007

Objective Lightning Probability Forecasting for Kennedy Space Center and Cape Canaveral Air Force Station, Phase II

This report describes the work done by the Applied Meteorology Unit (AMU) to update the lightning probability forecast equations developed in Phase I. In the time since the Phase I equations were developed, new ideas regarding certain predictors were formulated and a desire to make the tool more automated was expressed by 45 WS forecasters. Five modifications were made to the data: 1) increased the period of record from 15 to 17 years, 2) modified the valid area to match the lighting warning areas, 3) added the 1000 UTC CCAFS sounding to the other soundings in determining the flow regime, 4) used a different smoothing function for the daily climatology, and 5) determined the optimal relative humidity (RH) layer to use as a predictor. The new equations outperformed the Phase I equations in several tests, and improved the skill of the forecast over the Phase I equations by 8%. A graphical user interface (GUI) was created in the Meteorological Interactive Data Display System (MIDDS) that gathers the predictor values for the equations automatically. The GUI was transitioned to operations in May 2007 for the 2007 warm season.

Lambert, Winifred↗
NASA NTRS1994

Automated Test Environment for a Real-Time Control System

An automated environment with hardware-in-the-loop has been developed by Rocketdyne Huntsville for test of a real-time control system. The target system of application is the man-rated real-time system which controls the Space Shuttle Main Engines (SSME). The primary use of the environment is software verification and validation, but it is also useful for evaluation and analysis of SSME avionics hardware and mathematical engine models. It provides a test bed for the integration of software and hardware. The principles and skills upon which it operates may be applied to other target systems, such as those requiring hardware-in-the-loop simulation and control system development. Potential applications are in problem domains demanding highly reliable software systems requiring testing to formal requirements and verifying successful transition to/from off-nominal system states.

Hall, Ronald O.↗
NASA NTRS2010

Automated Detection of Oscillating Regions in the Solar Atmosphere

Recently observed oscillations in the solar atmosphere have been interpreted and modeled as magnetohydrodynamic wave modes. This has allowed for the estimation of parameters that are otherwise hard to derive, such as the coronal magnetic-field strength. This work crucially relies on the initial detection of the oscillations, which is commonly done manually. The volume of Solar Dynamics Observatory (SDO) data will make manual detection inefficient for detecting all of the oscillating regions. An algorithm is presented that automates the detection of areas of the solar atmosphere that support spatially extended oscillations. The algorithm identifies areas in the solar atmosphere whose oscillation content is described by a single, dominant oscillation within a user-defined frequency range. The method is based on Bayesian spectral analysis of time series and image filtering. A Bayesian approach sidesteps the need for an a-priori noise estimate to calculate rejection criteria for the observed signal, and it also provides estimates of oscillation frequency, amplitude, and noise, and the error in all of these quantities, in a self-consistent way. The algorithm also introduces the notion of quality measures to those regions for which a positive detection is claimed, allowing for simple post-detection discrimination by the user. The algorithm is demonstrated on two Transition Region and Coronal Explorer (TRACE) datasets, and comments regarding its suitability for oscillation detection in SDO are made.

Ireland, J.↗
NASA NTRS2014

Aggregation Tool to Create Curated Data albums to Support Disaster Recovery and Response

Despite advances in science and technology of prediction and simulation of natural hazards, losses incurred due to natural disasters keep growing every year. Natural disasters cause more economic losses as compared to anthropogenic disasters. Economic losses due to natural hazards are estimated to be around $6-$10 billion dollars annually for the U.S. and this number keeps increasing every year. This increase has been attributed to population growth and migration to more hazard prone locations such as coasts. As this trend continues, in concert with shifts in weather patterns caused by climate change, it is anticipated that losses associated with natural disasters will keep growing substantially. One of challenges disaster response and recovery analysts face is to quickly find, access and utilize a vast variety of relevant geospatial data collected by different federal agencies such as DoD, NASA, NOAA, EPA, USGS etc. Some examples of these data sets include high spatio-temporal resolution multi/hyperspectral satellite imagery, model prediction outputs from weather models, latest radar scans, measurements from an array of sensor networks such as Integrated Ocean Observing System etc. More often analysts may be familiar with limited, but specific datasets and are often unaware of or unfamiliar with a large quantity of other useful resources. Finding airborne or satellite data useful to a natural disaster event often requires a time consuming search through web pages and data archives. Additional information related to damages, deaths, and injuries requires extensive online searches for news reports and official report summaries. An analyst must also sift through vast amounts of potentially useful digital information captured by the general public such as geo-tagged photos, videos and real time damage updates within twitter feeds. Collecting and aggregating these information fragments can provide useful information in assessing damage in real time and help direct recovery efforts. The search process for the analyst could be made much more efficient and productive if a tool could go beyond a typical search engine and provide not just links to web sites but actual links to specific data relevant to the natural disaster, parse unstructured reports for useful information nuggets, as well as gather other related reports, summaries, news stories, and images. This presentation will describe a semantic aggregation tool developed to address similar problem for Earth Science researchers. This tool provides automated curation, and creates "Data Albums" to support case studies. The generated "Data Albums" are compiled collections of information related to a specific science topic or event, containing links to relevant data files (granules) from different instruments; tools and services for visualization and analysis; information about the event contained in news reports, and images or videos to supplement research analysis. An ontology-based relevancy-ranking algorithm drives the curation of relevant data sets for a given event. This tool is now being used to generate a catalog of Hurricane Case Studies at Global Hydrology Resource Center (GHRC), one of NASA's Distribute Active Archive Centers. Another instance of the Data Albums tool is currently being created in collaboration with NASA/MSFC's SPoRT Center, which conducts research on unique NASA products and capabilities that can be transitioned to the operational community to solve forecast problems. This new instance focuses on severe weather to support SPoRT researchers in their model evaluation studies

Ramachandran, Rahul↗
NASA NTRS2014

Q-Thruster Breadboard Campaign Project

Dr. Harold "Sonny" White has developed the physics theory basis for utilizing the quantum vacuum to produce thrust. The engineering implementation of the theory is known as Q-thrusters. During FY13, three test campaigns were conducted that conclusively demonstrated tangible evidence of Q-thruster physics with measurable thrust bringing the TRL up from TRL 2 to early TRL 3. This project will continue with the development of the technology to a breadboard level by leveraging the most recent NASA/industry test hardware. This project will replace the manual tuning process used in the 2013 test campaign with an automated Radio Frequency (RF) Phase Lock Loop system (precursor to flight-like implementation), and will redesign the signal ports to minimize RF leakage (improves efficiency). This project will build on the 2013 test campaign using the above improvements on the test implementation to get ready for subsequent Independent Verification and Validation testing at Glenn Research Center (GRC) and Jet Propulsion Laboratory (JPL) in FY 2015. Q-thruster technology has a much higher thrust to power than current forms of electric propulsion (~7x Hall thrusters), and can significantly reduce the total power required for either Solar Electric Propulsion (SEP) or Nuclear Electric Propulsion (NEP). Also, due to the high thrust and high specific impulse, Q-thruster technology will greatly relax the specific mass requirements for in-space nuclear reactor systems. Q-thrusters can reduce transit times for a power-constrained architecture.

White, Harold↗
NASA NTRS1992

Automation life-cycle cost model

The problem domain being addressed by this contractual effort can be summarized by the following list: Automation and Robotics (A&R) technologies appear to be viable alternatives to current, manual operations; Life-cycle cost models are typically judged with suspicion due to implicit assumptions and little associated documentation; and Uncertainty is a reality for increasingly complex problems and few models explicitly account for its affect on the solution space. The objectives for this effort range from the near-term (1-2 years) to far-term (3-5 years). In the near-term, the envisioned capabilities of the modeling tool are annotated. In addition, a framework is defined and developed in the Decision Modelling System (DEMOS) environment. Our approach is summarized as follows: Assess desirable capabilities (structure into near- and far-term); Identify useful existing models/data; Identify parameters for utility analysis; Define tool framework; Encode scenario thread for model validation; and Provide transition path for tool development. This report contains all relevant, technical progress made on this contractual effort.

Gathmann, Thomas P.↗
NASA NTRS1998

X-33/RLV System Health Management/Vehicle Health Management

To reduce operations costs, Reusable Launch Vehicles (RLVS) must include highly reliable robust subsystems which are designed for simple repair access with a simplified servicing infrastructure, and which incorporate expedited decision-making about faults and anomalies. A key component for the Single Stage To Orbit (SSTO) RLV system used to meet these objectives is System Health Management (SHM). SHM incorporates Vehicle Health Management (VHM), ground processing associated with the vehicle fleet (GVHM), and Ground Infrastructure Health Management (GIHM). The primary objective of SHM is to provide an automated and paperless health decision, maintenance, and logistics system. Sanders, a Lockheed Martin Company, is leading the design, development, and integration of the SHM system for RLV and for X-33 (a sub-scale, sub-orbit Advanced Technology Demonstrator). Many critical technologies are necessary to make SHM (and more specifically VHM) practical, reliable, and cost effective. This paper will present the X-33 SHM design which forms the baseline for the RLV SHM, and it will discuss applications of advanced technologies to future RLVs. In addition, this paper will describe a Virtual Design Environment (VDE) which is being developed for RLV. This VDE will allow for system design engineering, as well as program management teams, to accurately and efficiently evaluate system designs, analyze the behavior of current systems, and predict the feasibility of making smooth and cost-efficient transitions from older technologies to newer ones. The RLV SHM design methodology will reduce program costs, decrease total program life-cycle time, and ultimately increase mission success.

Mouyos, William↗
NASA NTRS2014

Development and Implementation of Dynamic Scripts to Execute Cycled WRF/GSI Forecasts

Automating the coupling of data assimilation (DA) and modeling systems is a unique challenge in the numerical weather prediction (NWP) research community. In recent years, the Development Testbed Center (DTC) has released well-documented tools such as the Weather Research and Forecasting (WRF) model and the Gridpoint Statistical Interpolation (GSI) DA system that can be easily downloaded, installed, and run by researchers on their local systems. However, developing a coupled system in which the various preprocessing, DA, model, and postprocessing capabilities are all integrated can be labor-intensive if one has little experience with any of these individual systems. Additionally, operational modeling entities generally have specific coupling methodologies that can take time to understand and develop code to implement properly. To better enable collaborating researchers to perform modeling and DA experiments with GSI, the Short-term Prediction Research and Transition (SPoRT) Center has developed a set of Perl scripts that couple GSI and WRF in a cycling methodology consistent with the use of real-time, regional observation data from the National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center (EMC). Because Perl is open source, the code can be easily downloaded and executed regardless of the user's native shell environment. This paper will provide a description of this open-source code and descriptions of a number of the use cases that have been performed by SPoRT collaborators using the scripts on different computing systems.

Zavodsky, Bradley↗
NASA NTRS1992

Fault detection using a two-model test for changes in the parameters of an autoregressive time series

This article describes an investigation of a statistical hypothesis testing method for detecting changes in the characteristics of an observed time series. The work is motivated by the need for practical automated methods for on-line monitoring of Deep Space Network (DSN) equipment to detect failures and changes in behavior. In particular, on-line monitoring of the motor current in a DSN 34-m beam waveguide (BWG) antenna is used as an example. The algorithm is based on a measure of the information theoretic distance between two autoregressive models: one estimated with data from a dynamic reference window and one estimated with data from a sliding reference window. The Hinkley cumulative sum stopping rule is utilized to detect a change in the mean of this distance measure, corresponding to the detection of a change in the underlying process. The basic theory behind this two-model test is presented, and the problem of practical implementation is addressed, examining windowing methods, model estimation, and detection parameter assignment. Results from the five fault-transition simulations are presented to show the possible limitations of the detection method, and suggestions for future implementation are given.

Scholtz, P.↗
NASA NTRS1994

A genetic technique for planning a control sequence to navigate the state space with a quasi-minimum-cost output trajectory for a non-linear multi-dimnensional system

There are many multi-stage optimization problems that are not easily solved through any known direct method when the stages are coupled. For instance, we have investigated the problem of planning a vehicle's control sequence to negotiate obstacles and reach a goal in minimum time. The vehicle has a known mass, and the controlling forces have finite limits. We have developed a technique that finds admissible control trajectories which tend to minimize the vehicle's transit time through the obstacle field. The immediate applications is that of a space robot which must rapidly traverse around 2-or-3 dimensional structures via application of a rotating thruster or non-rotating on-off for such vehicles is located at the Marshall Space Flight Center in Huntsville Alabama. However, it appears that the development method is applicable to a general set of optimization problems in which the cost function and the multi-dimensional multi-state system can be any nonlinear functions, which are continuous in the operating regions. Other applications included the planning of optimal navigation pathways through a transversability graph; the planning of control input for under-water maneuvering vehicles which have complex control state-space relationships; the planning of control sequences for milling and manufacturing robots; the planning of control and trajectories for automated delivery vehicles; and the optimization and athletic training in slalom sports.

Hein, C.↗
NASA NTRS1996

Medical and surgical applications of space biosensor technology

Researchers in space life sciences are rapidly approaching a technology impasse. Many of the critical questions on the impact of spaceflight on living systems simply cannot be answered with the limited available technologies. Research subjects, particularly small animal models like the rat, must be allowed to function relatively untended and unrestrained for long periods to fully reflect the impact of microgravity and spaceflight on their behavior and physiology. These requirements preclude the use of present hard-wired instrumentation techniques and limited data acquisition systems. Implantable sensors and miniaturized biotelemetry are the only means of capturing the fundamental and critical data. This same biosensor and biotelemetry technology has direct application to Earth-based medicine and surgery. Continuous, on-line data acquisition and improved measurement capabilities combined with the ease and flexibility offered by automated, wireless, and portable instruments and data systems, should provide a boon to the health care industry. Playing a key role in this technology revolution is the Sensors 2000! (S2K!) Program at NASA Ames Research Center. S2K!, in collaboration with space life sciences researchers and managers, provides an integrated capability for sensor technology development and applications, including advanced biosensor technology development, spaceflight hardware development, and technology transfer and commercialization. S2K! is presently collaborating on several spaceflight projects with dual-use medical applications. One prime example is a collaboration with the Fetal Treatment Center (FTC) at the University of California at San Francisco. The goal is to develop and apply implantable chemical sensor and biotelemetry technology to continuously monitor fetal patients during extra-uterine surgery, replacement into the womb, through birth and beyond. Once validated for ground use, the method will be transitioned to spaceflight applications to remotely monitor key biochemical parameters in flight animals. Successful application of NASA implantable biosensor and biotelemetry technologies should accelerate the advancement of this and other modern medical procedures while furthering the exploration of life in space.

NASA Discipline General Space Life Sciences↗
NASA NTRS2000

Performance Optimization of a Rotor Alone Nacelle for Acoustic Fan Testing

This paper describes the techniques, equipment, and results from the optimization of a two-axis traverse actuation system used to maintain concentricity between a sting-mounted fan and a wall-mounted nacelle in the 9 x 15 (9 Foot by 15 Foot Test Section) Low Speed Wind Tunnel (LSWT) at the NASA Glenn Research Center (GRC). The Rotor Alone Nacelle (RAN) system, developed at GRC by the Engineering Design and Analysis Division (EDAD) and the Acoustics Branch, used nacelle-mounted lasers and an automated control system to maintain concentricity as thermal and thrust operating loads displace the fan relative to the nacelle. This effort was critical to ensuring rig/facility safety and experimental consistency of the acoustic data from a statorless, externally supported nacelle configuration. Although the tip clearances were originally predicted to be about 0.020 in. at maximum rotor (fan) operating speed, proximity probe measurements showed that the nominal clearance was less than 0.004 in. As a result, the system was optimized through control-loop modifications, active laser cooling, data filtering and averaging, and the development of strict operational procedures. The resultant concentricity error of RAN was reduced to +/- 0.0031 in. in the Y-direction (horizontal) and +0.0035 in./-0.001 3 in. in the Z-direction (vertical), as determined by error analysis and experimental results. Based on the success of this project, the RAN system will be transitioned to other wind tunnel research programs at NASA GRC.

Cunningham, C. C.↗
NASA NTRS2005

Knowledge Representation Standards and Interchange Formats for Causal Graphs

In many domains, automated reasoning tools must represent graphs of causally linked events. These include fault-tree analysis, probabilistic risk assessment (PRA), planning, procedures, medical reasoning about disease progression, and functional architectures. Each of these fields has its own requirements for the representation of causation, events, actors and conditions. The representations include ontologies of function and cause, data dictionaries for causal dependency, failure and hazard, and interchange formats between some existing tools. In none of the domains has a generally accepted interchange format emerged. The paper makes progress towards interoperability across the wide range of causal analysis methodologies. We survey existing practice and emerging interchange formats in each of these fields. Setting forth a set of terms and concepts that are broadly shared across the domains, we examine the several ways in which current practice represents them. Some phenomena are difficult to represent or to analyze in several domains. These include mode transitions, reachability analysis, positive and negative feedback loops, conditions correlated but not causally linked and bimodal probability distributions. We work through examples and contrast the differing methods for addressing them. We detail recent work in knowledge interchange formats for causal trees in aerospace analysis applications in early design, safety and reliability. Several examples are discussed, with a particular focus on reachability analysis and mode transitions. We generalize the aerospace analysis work across the several other domains. We also recommend features and capabilities for the next generation of causal knowledge representation standards.

Throop, David R.↗