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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 sources NASA NTRS DOE OSTI

NASA NTRS2002

Sounding-Diagnosed Convective Environments and Preliminary Energy Budgets Diagnosed during the TRMM Field Campaigns

An overview of mean convective thermodynamic and wind profiles for the Tropical Rainfall Measuring Mission (TRMM) Large Scale Biosphere-Atmosphere Experiment (LBA) and Kwajalein Experiment (KWAJEX) field campaigns will be presented, highlighting the diverse continental and marine tropical environments in which rain clouds and mesoscale convective systems evolved. An assessment of ongoing sounding quality control procedures will be shown. Additionally, we will present preliminary budgets of sensible heat source (Q1) and apparent moisture sink (Q2), which have been diagnosed from the various sounding networks.

Halverson, Jeffrey B.↗

NASA NTRS1978

Diagnosable systems for intermittent faults

The fault diagnosis capabilities of systems composed of interconnected units capable of testing each other are studied for the case of systems with intermittent faults. A central role is played by the concept of t(i)-fault diagnosability. A system is said to be t(i)-fault diagnosable when it is such that if no more than t(i) units are intermittently faulty then a fault-free unit will never be diagnosed as faulty and the diagnosis at any time is at worst incomplete. Necessary and sufficient conditions for t(i)-fault diagnosability are proved, and bounds for t(i) are established. The conditions are in general more restrictive than those for permanent-fault diagnosability. For intermittent faults there is only one testing strategy (repetitive testing), and consequently only one type of intermittent-fault diagnosable system.

Mallela, S.↗

NASA NTRS1986

Short-term numerical precipitation forecasts initialized using a diagnosed divergent-wind component

Use of the diagnosed-divergence initialization procedure of Tarbell et al. (1979) to predict the hourly rainfall data used in short-term precipitation forecasts is examined experimentally. Data simulations using a mesoscale model and balanced and internally consistent data were conducted; the physical and numerical characteristics of the mesoscale model are described. The real experiment used rainfall data from April 25-26, 1979 to investigate the capabilities of the initialization procedure to improve short-term precipitation forecasts. The derivation of the diagnosed-divergent wind using a mesoscale omega equation which includes the effects of latent heating is discussed. The diagnosed-divergence initialization forecasts are compared to nondivergence or observed-divergence initializations. It is observed that the diagnosed-divergence initializations provide better rainfall data than the other initializations.

Salmon, Ellen M.↗

NASA NTRS2012

Improving Multiple Fault Diagnosability using Possible Conflicts

Multiple fault diagnosis is a difficult problem for dynamic systems. Due to fault masking, compensation, and relative time of fault occurrence, multiple faults can manifest in many different ways as observable fault signature sequences. This decreases diagnosability of multiple faults, and therefore leads to a loss in effectiveness of the fault isolation step. We develop a qualitative, event-based, multiple fault isolation framework, and derive several notions of multiple fault diagnosability. We show that using Possible Conflicts, a model decomposition technique that decouples faults from residuals, we can significantly improve the diagnosability of multiple faults compared to an approach using a single global model. We demonstrate these concepts and provide results using a multi-tank system as a case study.

multiple faults↗

NASA NTRS2003

Practical Formal Verification of Diagnosability of Large Models via Symbolic Model Checking

This document reports on the activities carried out during a four-week visit of Roberto Cavada at the NASA Ames Research Center. The main goal was to test the practical applicability of the framework proposed, where a diagnosability problem is reduced to a Symbolic Model Checking problem. Section 2 contains a brief explanation of major techniques currently used in Symbolic Model Checking, and how these techniques can be tuned in order to obtain good performances when using Model Checking tools. Diagnosability is performed on large and structured models of real plants. Section 3 describes how these plants are modeled, and how models can be simplified to improve the performance of Symbolic Model Checkers. Section 4 reports scalability results. Three test cases are briefly presented, and several parameters and techniques have been applied on those test cases in order to produce comparison tables. Furthermore, comparison between several Model Checkers is reported. Section 5 summarizes the application of diagnosability verification to a real application. Several properties have been tested, and results have been highlighted. Finally, section 6 draws some conclusions, and outlines future lines of research.

Cavada, Roberto↗

DOE OSTI2025

Comparison of Expert Vocabulary Usage Patterns Between Mental Health and Nonmental Health Clinicians When Diagnosing Pediatric Anxiety Disorders

Objective: To compare the utilization patterns of expert vocabulary (EVo) in diagnosing pediatric anxiety between mental health and non-mental health clinical notes from electronic health records to understand the role of Evo in informing classification and decision-making in anxiety diagnoses. Study design: We conducted a retrospective study using a cohort less than age 25 from Cincinnati Children's Hospital including 897 685 patients with 61 586 446 notes. We analyzed EVo, collected from mental health clinicians, in both mental and nonmental health notes. We compared classification accuracy using EVo-based patient-level embedding from all clinical notes, mental-health notes, and nonmental health notes for 2 tasks: 1) pre-vs postdiagnosis anxiety patients, and 2) prediagnosis anxiety vs nonanxiety patients. Results: EVo usage was highest in prediagnosis anxiety, lower in nonanxiety, and lowest in post-diagnosis. Classification models using EVo features from all, mental-health, and non-mental health notes showed similar F1 scores for prediagnosis anxiety (0.70 ± 0.2 for 2 categories). For anxiety vs nonanxiety classification, all clinical and nonmental health notes had better F1 scores than mental-health notes (above 0.90 for 3 categories). There was a notable difference in class-wise performance across both tasks. Conclusions: There are significant differences in anxiety EVo use between mental health and nonmental health clinicians. Despite less anxiety-specific terminology, non-mental health notes still captured key aspects of patient presentations, emphasizing the importance of including all clinicians' notes in analysis. EVo's utility for anxiety classification is most effective in prediagnostic phases, suggesting the need for a dedicated diagnostic lexicon and further study before incorporating EVo into classification models.

feature engineering↗

DOE OSTI2025

Technical note: Recommendations for diagnosing cloud feedbacks and rapid cloud adjustments using cloud radiative kernels

Abstract. The cloud radiative kernel method is a popular approach to quantify cloud feedbacks and rapid cloud adjustments to increased CO2 concentrations and to partition contributions from changes in cloud amount, altitude, and optical depth. However, because this method relies on cloud property histograms derived from passive satellite sensors or produced by passive satellite simulators in models, changes in obscuration of lower-level clouds by upper-level clouds can cause apparent low-cloud feedbacks and adjustments, even in the absence of changes in lower-level cloud properties. Here, we provide a methodology for properly diagnosing the impact of changing obscuration on cloud feedbacks and adjustments and quantify these effects across climate models. Averaged globally and across global climate models, properly accounting for obscuration leads to weaker positive feedbacks from lower-level clouds and stronger positive feedbacks from upper-level clouds while simultaneously removing a mostly artificial anti-correlation between them. Given that the methodology for diagnosing cloud feedbacks and adjustments using cloud radiative kernels has evolved over several papers, and obscuration effects have only occasionally been considered in recent papers, this paper serves to establish recommended best practices and to provide a corresponding code base for community use.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1985

Global scale diagnoses of FGGE data

Descriptive global scale diagnoses of the First Global Atmospheric Research Experiment SOP-1 analyses were made and compared against controlled, real data integrations of the Goddard Laboratory of Atmospheric Science (GLAS) general circulation model (GCM) as well as other data sets. The effects of critical latitudes were studied; the influence of tropical wind data and latent heating upon the GLAS GCM was diagnosed; planetary wave structure on various time scales from the diurnal to the monthly was studied; and the GLAS analyses were compared with other analyses. Short term controlled GLAS GCM integrations show that: (1) the inclusion of tropical wind data in real data integrations has an important influence in the mid-latitude prediction in both hemispheres; and (2) the tropical divergent wind reacts almost immediately to alteration of the tropical latent heating. The presence or absence of zonally averaged easterlies depends strongly upon the presence of tropical latent heating.

Paegle, J.↗

NASA NTRS1987

The stratosphere - Climatologies of the radiative heating and cooling rates and the diabatically diagnosed net circulation fields

Stratospheric solar, IR, and net radiative heating are calculated on a monthly basis using solar and IR radiative codes and satellite derived distributions of ozone, water vapor, and temperature. Divergence-free, zonally averaged, advective fields are diagnosed using the calculated diabatic heating; associated stream functions are derived. The stratospheric transport of inert tracers is studied. Analysis of the diagnosed advective fields reveal that: (1) entry into the mid- to upper stratosphere of tropospheric air is mainly from altitude regions of + or - 10 deg at the equatorial tropopause; (2) at latitudes poleward of + or - 15 deg, tracers transported from the troposphere into the stratosphere are transported toward the pole and then downward and out of the stratosphere; and (3) the presence of net cooling cells in the lower stratospheric polar regions is important. The interannual variability of the diabatic circulation is estimated using heating and advection fields derived from LIMS data.

Callis, Linwood B.↗

NASA NTRS1988

Diagnosing faults in autonomous robot plan execution

A major requirement for an autonomous robot is the capability to diagnose faults during plan execution in an uncertain environment. Many diagnostic researches concentrate only on hardware failures within an autonomous robot. Taking a different approach, the implementation of a Telerobot Diagnostic System that addresses, in addition to the hardware failures, failures caused by unexpected event changes in the environment or failures due to plan errors, is described. One feature of the system is the utilization of task-plan knowledge and context information to deduce fault symptoms. This forward deduction provides valuable information on past activities and the current expectations of a robotic event, both of which can guide the plan-execution inference process. The inference process adopts a model-based technique to recreate the plan-execution process and to confirm fault-source hypotheses. This technique allows the system to diagnose multiple faults due to either unexpected plan failures or hardware errors. This research initiates a major effort to investigate relationships between hardware faults and plan errors, relationships which were not addressed in the past. The results of this research will provide a clear understanding of how to generate a better task planner for an autonomous robot and how to recover the robot from faults in a critical environment.

Lam, Raymond K.↗

NASA NTRS1988

MOORE: A prototype expert system for diagnosing spacecraft problems

MOORE is a rule-based, prototype expert system that assists in diagnosing operational Tracking and Data Relay Satellite (TDRS) problems. It is intended to assist spacecraft engineers at the TDRS ground terminal in trouble shooting problems that are not readily solved with routine procedures, and without expert counsel. An additional goal of the prototype system is to develop in-house expert system and knowledge engineering skills. The prototype system diagnoses antenna pointing and earth pointing problems that may occur within the TDRS Attitude Control System (ACS). Plans include expansion to fault isolation of problems in the most critical subsystems of the TDRS spacecraft. Long term benefits are anticipated with use of an expert system during future TDRS programs with increased mission support time, reduced problem solving time, and retained expert knowledge and experience. Phase 2 of the project is intended to provide NASA the necessary expertise and capability to define requirements, evaluate proposals, and monitor the development progress of a highly competent expert system for NASA's Tracking Data Relay Satellite. Phase 2 also envisions addressing two unexplored applications for expert systems, spacecraft integration and tests (I and T) and support to launch activities. The concept, goals, domain, tools, knowledge acquisition, developmental approach, and design of the expert system. It will explain how NASA obtained the knowledge and capability to develop the system in-house without assistance from outside consultants. Future plans will also be presented.

Howlin, Katherine↗

NASA NTRS1990

A study on diagnosability of space station ECLSS

The use is demonstrated of the Multigraph Architecture (MGA) for studies on the Environment Control and Life Support System (ECLSS). The objective was the following: (1) to create an updated set of models of the Potable Water Subsystem (PWS) by using the graphical model building tools of the Multigraph Programming Environment (MPE); (2) to derive a real time alarm simulator from the models; and (3) to demonstrate the effects of sensor allocation on the diagnosability of the PWS. This work may serve as a preliminary study for the detailed analysis of the sensor allocation and diagnosability problems in the ECLSS.

Padalkar, S.↗

NASA NTRS1989

Diagnosing faults in autonomous robot plan execution

Lam, Raymond K.↗

NASA NTRS1989

Jet streak circulations associated with a moderate snowfall event as diagnosed from NGM model output

The existence, evolution, and interaction of vertical circulations associated with upper-level jet streaks during a moderate snowfall event are diagnosed using a nested grid model (NGM). The event itself is overviewed, and the diagnosis of transverse circulations utilizing NGM output is discussed. Focus is placed on the identification of the horizontal and vertical components of the circulation, the temporal evolution of the circulation, and the comparison of the circulation from successive model forecasts. A preliminary analysis of the model data indicates that the horizontal and vertical branches of the circulations can be diagnosed from the model output, and the horizontal and vertical components of the circulations may be identified and followed during an individual forecast cycle.

Kocin, Paul J.↗

NASA NTRS1990

Diagnosing multiple faults in SSM/PMAD

Multiple fault diagnosis for SSM/PMAD (space station module/power management and distribution) using the knowledge management design system as applied to the SSM/PMAD domain (KNOMAD-SSM/PMAD) is discussed. KNOMAD-SSM/PMAD provides a powerful facility for knowledge representation and reasoning which has been used to build the second generation of FRAMES (fault recovery and management expert system). FRAMES now handles the diagnosis of multiple faults and provides support for a more powerful interface for user interaction during autonomous operation. There are two types of multiple fault diagnosis handled in FRAMES. The first diagnoses hard faults, soft faults, and incipient faults simultaneously. The second diagnoses multiple hard faults which occur in close proximity in time to one another. Multiple fault diagnosis in FRAMES is performed using a rule-based approach. This rule-based approach, enabled by the KNOMAD-SSM/PMAD system, has proven to be powerful. Levels of autonomy are discussed, focusing on the approach taken in FRAMES for providing at least three levels of autonomy: complete autonomy, partial autonomy, and complete manual mode.

Riedesel, Joel↗

NASA NTRS1991

Psychiatric diagnoses in a group of astronaut applicants

Between 1959 and 1987, the psychiatric evaluation of astronaut candidates evolved from a 30-h intensive examination evaluating applicants for psychopathology, and studying their performance under stress, to a 2-h clinical interview whose structure and contents were determined by the individual examiner. Evaluations done during these years applied both psychiatric (or, 'select-out') criteria and psychological (or, 'select-in') criteria. In an attempt to more rigorously define the psychiatric, 'select-out' component, a standardized, semistructured clinical interview was developed to identify the presence or history of psychiatric disorders listed in the Diagnostic and Statistical Manual of Mental Disorders, 3rd Ed. ('DSM-III'). A total of 117 astronaut applicants underwent this clinical interview as part of a comprehensive medical evaluation during a recent astronaut selection. Of the 117 applicants, 9 (7.7 percent) met DSM-III criteria for a variety of Axis I and Axis II diagnoses, including V-code diagnoses.

Santy, Patricia A.↗

NASA NTRS1991

GTEX: An expert system for diagnosing faults in satellite ground stations

A proof of concept expert system called Ground Terminal Expert (GTEX) was developed at The University of Akron in collaboration with NASA Lewis Research Center. The objective of GTEX is to aid in diagnosing data faults occurring with a digital ground terminal. This strategy can also be applied to the Very Small Aperture Terminal (VSAT) technology. An expert system which detects and diagnoses faults would enhance the performance of the VSAT by improving reliability and reducing maintenance time. GTEX is capable of detecting faults, isolating the cause and recommending appropriate actions. Isolation of faults is completed to board-level modules. A graphical user interface provides control and a medium where data can be requested and cryptic information logically displayed. Interaction with GTEX consists of user responses and input from data files. The use of data files provides a method of simulating dynamic interaction between the digital ground terminal and the expert system. GTEX as described is capable of both improving reliability and reducing the time required for necessary maintenance.

Schlegelmilch, Richard F.↗

NASA NTRS1994

Diagnosing anomalies of spacecraft for space maintenance and servicing

Very often servicing of satellites is necessary to replace components which are responsible for anomalous behavior of satellite operations due to adverse interactions with the natural space environment. A major difficulty with this diagnosis is that those responsible for diagnosing these anomalies do not have the tools to assess the role of the space environment causing the anomaly. To address this issue, we have under development a new rule-based, expert system for diagnosing spacecraft anomalies. The knowledge base consists of over two-hundred rules and provides links to historical and environmental databases. Environmental causes considered are bulk charging, single event upsets (SEU), surface charging, and total radiation dose. The system's driver translates forward chaining rules into a backward chaining sequence, prompting the user for information pertinent to the causes considered. When the user selects the novice mode, the system automatically gives detailed explanations and descriptions of terms and reasoning as the session progresses, in a sense teaching the user. As such it is an effective tutoring tool. The use of heuristics frees the user from searching through large amounts of irrelevant information and allows the user to input partial information (varying degrees of confidence in an answer) or 'unknown' to any question. The system is available on-line and uses C Language Integrated Production System (CLIPS), an expert shell developed by the NASA Johnson Space Center AI Laboratory in Houston.

Lauriente, Michael↗