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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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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Planning and Monitoring Multi-Job Type Swarm Search and Service Missions

To transition from control theory to real applications, it is important to study missions such as Swarm Search and Service (SSS) where vehicles are not only required to search an area, but also service all jobs that they find. In SSS missions, each type of job requires a group of vehicles to break off from the swarm for a given amount of time to service it. The required number of vehicles and the service rate are unique to each job type. Once a job has been completed, the vehicles are able to return to the swarm for use elsewhere. If not, enough vehicles are present in the swarm at the time that the job is identified, that job is dropped without being serviced. In SSS missions that occur in open environments, the arrival rate of jobs varies dynamically as vehicles move in and out of the swarm to service jobs. Human operators are tasked with effectively planning and managing these complex missions. This paper presents a user study that seeks to test the efficacy and ease-of-use of a prediction model known as the Hybrid Model as an aid in planning and monitoring tasks. Results show that the novel computational model aid allows operators to more effectively choose the necessary swarm size to handle expected mission workload, as well as, maintain sufficient situation awareness to evaluate the performance of the swarm during missions.

swarm search and service↗
DOE OSTI2022

Infrared-Fused Vision-Based Thermoregulation Performance Estimation for Personal Thermal Comfort-Driven HVAC System Controls

Thermal comfort is one of the primary factors influencing occupant health, well-being, and productivity in buildings. Existing thermal comfort systems require occupants to frequently communicate their comfort vote via a survey which is impractical as a long-term solution. Here, we present a novel thermal infrared-fused computer vision sensing method to capture thermoregulation performance in a non-intrusive and non-invasive manner. In this method, we align thermal and visible images, detect facial segments (i.e., nose, eyes, face boundary), and accordingly read the temperatures from the appropriate coordinates in the thermal image. We focus on the human face since it is often clearly visible to cameras and is not merged into a hot background (unlike hands). We use a regularized Gaussian Mixture model to track the thermoregulation changes over time and apply a heuristic algorithm to extract hot and cold indices. We present a personalized and a generalized comfort modeling method, selected based on the availability of the occupant historical indices measurements in a neutral environment, and use the time-series of the hot and cold indices to define corrections to HVAC system operations in the form of setpoint constraints. To evaluate the efficacy of our proposed approach in responding to thermal stimuli, we designed a series of controlled experiments to simulate exposure to cold and hot environments. While applying personalized modeling showed an acceptable average accuracy of 91.3%, the generalized model’s average accuracy was only 65.2%. This shows the importance of having access to physiological records in modeling and assessing comfort. We also found that individual differences should be considered in selecting the cooling and heating rates when some knowledge of the occupant’s overall thermal preference is available.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRSDate not supplied

Differential Equation Approximation Using Gradient-Boosted Quantile Regression

The operation of cyber-physical-human (CPH) systems is subject to various epistemic and aleatory uncertainties. Overall trustworthiness of CPH systems relies on the trustworthiness of its components and their interactions. It is important that computational models comprising the cyber component of CPH provide predictions accompanied by a measure of confidence in model outcomes. Uncertainty quantification (UQ) and propagation are especially important in safety critical CPH systems. Gradient-boosted trees is a modeling approach capable both of learning the dynamics of a system and performing UQ. In this paper, we devise a method for using gradient boosting to learn the dynamics of a second order differential equation and estimate uncertainty at the same time. We do this by creating a custom loss function that trains the model to approximate the second derivative of a noisy time series, and to penalize based on a parameter that corresponds to the desired quantile. The resulting gradient boosting model can simulate stochastic trajectories of the system given a single starting point, that is, it can estimate both the expected trajectory and its uncertainty. We show that the uncertainty estimation is well calibrated and that the model can learn the dynamics even in the presence of noise. We demonstrate the approach on a simple cartpole system.

Autonomous systems↗
NASA NTRS1993

Probabilistic simulation of the human factor in structural reliability

A formal approach is described in an attempt to computationally simulate the probable ranges of uncertainties of the human factor in structural probabilistic assessments. A multi-factor interaction equation (MFIE) model has been adopted for this purpose. Human factors such as marital status, professional status, home life, job satisfaction, work load and health, are considered to demonstrate the concept. Parametric studies in conjunction with judgment are used to select reasonable values for the participating factors (primitive variables). Suitability of the MFIE in the subsequently probabilistic sensitivity studies are performed to assess the validity of the whole approach. Results obtained show that the uncertainties for no error range from five to thirty percent for the most optimistic case.

Chamis, C. C.↗
NASA NTRS1996

Downsizing Visualization Platforms: From Crays to Indigos and Beyond

Despite its increasingly negative connotation in other domains, "downsizing" is a positive trend as it applies to the computer hardware necessary to perform scientific visualization. In this talk, we will consider how the visualization of a particular data set, the Digital Terrain Model (DTM) derived from the Viking Orbiter imagery, has been realized in three distinct projects over the past decade. These examples serve to demonstrate how the vast improvements in computational performance both decrease the cost of such visualization efforts, and permit an increasing level of interactivity. We then consider how even today's graphical systems require the visualization designer to make intelligent choices and trade-offs in database rendering. Finally, we discuss how insights from an understanding of human visual perception can guide these design decisions, and suggest new options for visualization hardware and software.

Kaiser, Mary K.↗
NASA NTRS2008

Engineering America's Current and Future Space Transportation Systems: 50 Years of Systems Engineering Innovation for Sustainable Exploration

Over the past 50 years, the National Aeronautics and Space Administration (NASA) has delivered space transportation solutions for America's complex missions, ranging from scientific payloads that expand knowledge, such as the Hubble Space Telescope, to astronauts and lunar rovers destined for voyages to the Moon. Currently, the venerable Space Shuttle, which has been in service since 1981, provides the United States' (U.S.) capability for both crew and heavy cargo to low-Earth orbit to' construct the International Space Station, before the Shuttle is retired in 2010. In the next decade, NASA will replace this system with a duo of launch vehicles: the Ares I Crew Launch Vehicle and the Ares V Cargo Launch Vehicle (Figure 1). The goals for this new system include increased safety and reliability coupled with lower operations costs that promote sustainable space exploration for decades to come. The Ares I will loft the Orion Crew Exploration Vehicle, while the heavy-lift Ares V will carry the Altair Lunar Lander and the equipment and supplies needed to construct a lunar outpost for a new generation of human and robotic space pioneers. This paper will provide details of the in-house systems engineering and vehicle integration work now being performed for the Ares I and planned for the Ares V. It will give an overview of the Ares I system-level test activities, such as the ground vibration testing that will be conducted in the Marshall Center's Dynamic Test Stand to verify the integrated vehicle stack's structural integrity and to validate computer modeling and simulation (Figure 2), as well as the main propulsion test article analysis to be conducted in the Static Test Stand. These activities also will help prove and refine mission concepts of operation, while supporting the spectrum of design and development work being performed by Marshall's Engineering Directorate, ranging from launch vehicles and lunar rovers to scientific spacecraft and associated experiments. Ultimately, fielding a robust space transportation solution that will carry international explorers and essential payloads will pave the way for a new century of scientific discovery beyond planet Earth.

Dmbacher, Daniel L.↗
DOE OSTI2019

Scalable Representation Learning for Long-Term Augmented Reality-Based Information Delivery in Collaborative Human-Robot Perception

Augmented reality (AR)-based information delivery has been attracting an increasing attention in the past few years to improve com- munication in human-robot teaming. In the long-term use of AR systems for collaborative human-robot perception, one of the biggest challenges is to perform place and scene matching under long-term environmental changes, such as dramatic variations in lighting, weather and vegetation across di erent times of the day, months, and seasons. To address this challenge, we introduce a novel representation learning approach that learns a scalable long-term representation model that can be used for place and scene matching in various long-term conditions. Our approach is formulated as a regularized optimization problem, which selects the most representative scene templates in di erent scenarios to construct a scalable representation of the same place that can exhibit signi cant long-term environment changes. Our approach adaptively learns to select a small subset of the templates to construct the representation model, based on a user-de ned representativeness threshold, which makes the learned model highly scalable to the long-term variations in real-world applications. To solve the formulated optimization problem, a new algo- rithmic solver is designed, which is theoretically guaranteed to converge to the global optima. Experiments are conducted using two large-scale benchmark datasets, which have demonstrated the superior performance of our approach for long-term place and scene matching.

42 ENGINEERING↗
DOE OSTI2025

Report of the 2025 Workshop on Next-Generation Ecosystems for Scientific Computing: Harnessing Community, Software, and AI for Cross-Disciplinary Team Science

This report summarizes insights from the 2025 Workshop on Next-Generation Ecosystems for Scientific Computing: Harnessing Community, Software, and AI for Cross-Disciplinary Team Science, which convened more than 40 experts from national laboratories, academia, industry, and community organizations to chart a path toward more powerful, sustainable, and collaborative scientific software ecosystems. To address urgent challenges at the intersection of high-performance computing (HPC), AI, and scientific software, participants envisioned agile, robust ecosystems built through socio-technical co-design—the intentional integration of social and technical components as interdependent parts of a unified strategy. This approach combines advances in AI, HPC, and software with new models for cross-disciplinary collaboration, training, and workforce development. Key recommendations include building modular, trustworthy AI-enabled scientific software systems; enabling scientific teams to integrate AI systems into their workflows while preserving human creativity, trust, and scientific rigor; and creating innovative training pipelines that keep pace with rapid technological change. Pilot projects were identified as near-term catalysts, with initial priorities focused on hybrid AI/HPC infrastructure, cross-disciplinary collaboration and pedagogy, responsible AI guidelines, and prototyping of public-private partnerships. This report presents a vision of next-generation ecosystems for scientific computing where AI, software, hardware, and human expertise are interwoven to drive discovery, expand access, strengthen the workforce, and accelerate scientific progress.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1995

Model-based VQ for image data archival, retrieval and distribution

An ideal image compression technique for image data archival, retrieval and distribution would be one with the asymmetrical computational requirements of Vector Quantization (VQ), but without the complications arising from VQ codebooks. Codebook generation and maintenance are stumbling blocks which have limited the use of VQ as a practical image compression algorithm. Model-based VQ (MVQ), a variant of VQ described here, has the computational properties of VQ but does not require explicit codebooks. The codebooks are internally generated using mean removed error and Human Visual System (HVS) models. The error model assumed is the Laplacian distribution with mean, lambda-computed from a sample of the input image. A Laplacian distribution with mean, lambda, is generated with uniform random number generator. These random numbers are grouped into vectors. These vectors are further conditioned to make them perceptually meaningful by filtering the DCT coefficients from each vector. The DCT coefficients are filtered by multiplying by a weight matrix that is found to be optimal for human perception. The inverse DCT is performed to produce the conditioned vectors for the codebook. The only image dependent parameter used in the generation of codebook is the mean, lambda, that is included in the coded file to repeat the codebook generation process for decoding.

Manohar, Mareboyana↗
NASA NTRS2011

Impact of Water Withdrawals from Groundwater and Surface Water on Continental Water Storage Variations

Humans have strongly impacted the global water cycle, not only water flows but also water storage. We have performed a first global-scale analysis of the impact of water withdrawals on water storage variations, using the global water resources and use model WaterGAP. This required estimation of fractions of total water withdrawals from groundwater, considering five water use sectors. According to our assessment, the source of 35% of the water withdrawn worldwide (4300 cubic km/yr during 1998-2002) is groundwater. Groundwater contributes 42%, 36% and 27% of water used for irrigation, households and manufacturing, respectively, while we assume that only surface water is used for livestock and for cooling of thermal power plants. Consumptive water use was 1400 cubic km/yr during 1998-2002. It is the sum of the net abstraction of 250 cubic km/yr of groundwater (taking into account evapotranspiration and return flows of withdrawn surface water and groundwater) and the net abstraction of 1150 km3/yr of surface water. Computed net abstractions indicate, for the first time at the global scale, where and when human water withdrawals decrease or increase groundwater or surface water storage. In regions with extensive surface water irrigation, such as Southern China, net abstractions from groundwater are negative, i.e. groundwater is recharged by irrigation. The opposite is true for areas dominated by groundwater irrigation, such as in the High Plains aquifer of the central USA, where net abstraction of surface water is negative because return flow of withdrawn groundwater recharges the surface water compartments. In intensively irrigated areas, the amplitude of seasonal total water storage variations is generally increased due to human water use; however, in some areas, it is decreased. For the High Plains aquifer and the whole Mississippi basin, modeled groundwater and total water storage variations were compared with estimates of groundwater storage variations based on groundwater table observations, and with estimates of total water storage variations from the GRACE satellites mission. Due to the difficulty in estimating area-averaged seasonal groundwater storage variations from point observations of groundwater levels, it is uncertain whether WaterGAP underestimates actual variations or not. We conclude that WaterGAP possibly overestimates water withdrawals in the High Plains aquifer where impact of human water use on water storage is readily discernible based on WaterGAP calculations and groundwater observations. No final conclusion can be drawn regarding the possibility of monitoring water withdrawals in the High Plains aquifer using GRACE. For the less intensively irrigated Mississippi basin, observed and modeled seasonal groundwater storage reveals a discernible impact of water withdrawals in the basin, but this is not the case for total water storage such that water withdrawals at the scale of the whole Mississippi basin cannot be monitored by GRACE.

Doell, Petra↗
DOE OSTI2021

Automatic identification and quantification of dense microcracks in high-performance fiber-reinforced cementitious composites through deep learning-based computer vision

Highlights: • A method is presented to detect, locate, quantify, and visualize dense microcracks in HPFRCC. • Quantification of dense microcracks is realized using deep learning method for the first time. • The presented method uses deep learning models that are trained using a realistic dataset size. • The presented method has a high computation efficiency for identifying and quantifying cracks. • The presented method provides crack width with errors up to 50 μm and a R{sup 2} value of 0.984. High-performance fiber-reinforced cementitious composites (HPFRCCs) feature high mechanical strengths, crack resistance, and durability. Under excessive loading, HPFRCCs demonstrate dense microcracks that are difficult to identify using existing methods. This study presents a computer vision method for identification, quantification, and visualization of microcracks in HPFRCCs based on deep learning. The presented method integrates multiple deep learning models and computer vision techniques in a hierarchical architecture. The crack pattern (e.g., number, width, and spacing of cracks) are automatically determined from pictures without human intervention. This study shows that the presented method achieves an accuracy of 0.992 for crack detection and an accuracy finer than 50 μm (R{sup 2} > 0.984) for quantification of crack width when deep learning models are trained using only 200 pictures of HPFRCCs and 200 pictures of conventional concrete with incorporation of data augmentation. The presented method is expected to be also applicable to other materials featuring complex cracks.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Computed Tomography Radiomics Predicts HPV Status and Local Tumor Control After Definitive Radiochemotherapy in Head and Neck Squamous Cell Carcinoma

Purpose: This study aimed to predict local tumor control (LC) after radiochemotherapy of head and neck squamous cell carcinoma (HNSCC) and human papillomavirus (HPV) status using computed tomography (CT) radiomics. Methods and Materials: HNSCC patients treated with definitive radiochemotherapy were included in the retrospective study approved by the local ethical commission (93 and 56 patients in the training and validation cohorts, respectively). Three hundred seventeen CT radiomic features, including those based on shape, intensity, texture, and wavelet transform, were calculated in the primary tumor region. Cox and logistic regression models were built to predict LC and HPV status, respectively. The best-performing features in the univariable analysis were included in the multivariable analysis after the exclusion of redundant features. The quality of the models was assessed using the concordance index (CI) for modeling of LC and receiver operating characteristics area under the curve (AUC) for HPV status prediction. The radiomics LC model was compared to a model incorporating clinical parameters (tumor stage, volume, and HPV status) and a mixed model. Results: A radiomic signature comprising 3 features was significantly associated with LC (CI{sub training} = 0.75 and CI{sub validation} = 0.78), showing that tumors with a more heterogeneous CT density distribution are at risk for decreased LC. The addition of clinical parameters to the radiomics model slightly improved the model in the training cohort but not in the validation cohort. Another radiomic signature showed good performance in HPV status prediction (AUC{sub training} = 0.85 and AUC{sub validation} = 0.78) and indicated that HPV-positive tumors have a more homogenous CT density distribution. Conclusions: Heterogeneity of HNSCC tumor density, quantified by CT radiomics, is associated with LC after radiochemotherapy and HPV status.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

Assessment of cardiac single-photon emission computed tomography performance using a scanning linear observer

Purpose: Single-photon emission computed tomography (SPECT) is widely used to detect myocardial ischemia and myocardial infarction. It is important to assess and compare different SPECT system designs in order to achieve the highest detectability of cardiac defects. Methods: Whitaker et al.'s study ['Estimating random signal parameters from noisy images with nuisance parameters: linear and scanning-linear methods,' Opt. Express 16(11), 8150-8173 (2008)] on the scanning linear observer (SLO) shows that the SLO can be used to estimate the location and size of signals. One major advantage of the SLO is that it can be used with projection data rather than with reconstruction data. Thus, this observer model assesses the overall hardware performance independent of any reconstruction algorithm. In addition, the computation time of image quality studies is significantly reduced. In this study, three systems based on the design of the GE cadmium zinc telluride-based dedicated cardiac SPECT camera Discovery 530c were assessed. This design, which is officially named the Alcyone Technology: Discovery NM 530c, was commercialized in August, 2009. The three systems, GE27, GE19, and GE13, contain 27, 19, and 13 detectors, respectively. Clinically, a human heart can be virtually segmented into three coronary artery territories: the left-anterior descending artery, left-circumflex artery, and right coronary artery. One of the most important functions of a cardiac SPECT system is to produce images from which a radiologist can accurately predict in which territory the defect exists [http://www.asnc.org/media/PDFs/PPReporting081511.pdf, Guideline from American Society of Nuclear Cardiology]. A good estimation of the extent of the defect from the projection images is also very helpful for determining the seriousness of the myocardial ischemia. In this study, both the location and extent of defects were estimated by the SLO, and the system performance was assessed by localization receiver operating characteristic (LROC) [P. Khurd and G. Gindi, 'Decision strategies maximizing the area under the LROC curve,' Proc. SPIE 5749, 150-161 (2005)] or estimation receiver operating characteristic (EROC) [E. Clarkson, 'Estimation receiver operating characteristic curve and ideal observers for combined detection/estimation tasks,' J. Opt. Soc. Am. A 24, B91-B98 (2007)] curves. Results: The area under the LROC/EROC curve (AULC/AUEC) and the true positive fraction (TPF) at a specific false positive fraction (FPF) can be treated as the figures of merit. For radii estimation with a 1 mm tolerance, the AUEC values of the GE27, GE19, and GE13 systems are 0.8545, 0.8488, and 0.8329, and the TPF at FPF = 5% are 77.1%, 76.46%, and 73.55%, respectively. The assessment of all three systems revealed that the GE19 system yields estimated information and cardiac defect detectability very close to those of the GE27 system while using eight fewer detectors. Thus, 30% of the expensive detector units can be removed with confidence. Conclusions: As the results show, a combination of the SLO and LROC/EROC curves can determine the configuration that yields the most relevant estimation/detection information. Thus, this is a useful method for assessing cardiac SPECT systems.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

CrossMP: Enabling Cross-Modality Translation between Single-Cell RNA-Seq and Single-Cell ATAC-Seq through Web-Based Portal

In recent years, there has been a growing interest in profiling multiomic modalities within individual cells simultaneously. One such example is integrating combined single-cell RNA sequencing (scRNA-seq) data and single-cell transposase-accessible chromatin sequencing (scATAC-seq) data. Integrated analysis of diverse modalities has helped researchers make more accurate predictions and gain a more comprehensive understanding than with single-modality analysis. However, generating such multimodal data is technically challenging and expensive, leading to limited availability of single-cell co-assay data. Here, we propose a model for cross-modal prediction between the transcriptome and chromatin profiles in single cells. Our model is based on a deep neural network architecture that learns the latent representations from the source modality and then predicts the target modality. It demonstrates reliable performance in accurately translating between these modalities across multiple paired human scATAC-seq and scRNA-seq datasets. Additionally, we developed CrossMP, a web-based portal allowing researchers to upload their single-cell modality data through an interactive web interface and predict the other type of modality data, using high-performance computing resources plugged at the backend.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1979

A rationale for human operator pulsive control behavior

When performing tracking tasks which involve demanding controlled elements such as those with K/s-squared dynamics, the human operator often develops discrete or pulsive control outputs. A dual-loop model of the human operator is discussed, the dominant adaptive feature of which is the explicit appearance of an internal model of the manipulator-controlled element dynamics in an inner feedback loop. Using this model, a rationale for pulsive control behavior is offered which is based upon the assumption that the human attempts to reduce the computational burden associated with time integration of sensory inputs. It is shown that such time integration is a natural consequence of having an internal representation of the K/s-squared-controlled element dynamics in the dual-loop model. A digital simulation is discussed in which a modified form of the dual-loop model is shown to be capable of producing pulsive control behavior qualitively comparable to that obtained in experiment.

Hess, R. A.↗
DOE OSTI2020

COVID-19 Joint Pandemic Modeling and Analysis Platform

The non-pharmaceutical intervention to reduce the impact and spread of COVID-19 requires the development of policies and guidance through a collaborative effort among government, academia, medicine, and citizens. To operationalize this effort, we have developed an all-encompassing situational awareness platform that can process multi-modal and multi-source data allowing informed decision making. Besides, showing the current spread of infection, the platform also captures the impact of human dynamics on the infection spread, location, and availability of critical infrastructure, prediction, and high-performance computing driven simulation. The platform is extensible, allowing third-party integration and services to consume the curated data and analytics in near real-time. We believe the platform will augment critical decision making for reducing the impact and spread of the pandemic.

Thakur, Gautam↗
DOE OSTI2019

Phonetic acquisition in cortical dynamics, a computational approach

Many computational theories have been developed to improve artificial phonetic classification performance from linguistic auditory streams. However, less attention has been given to psycholinguistic data and neurophysiological features recently found in cortical tissue. We focus on a context in which basic linguistic units-such as phonemes-are extracted and robustly classified by humans and other animals from complex acoustic streams in speech data. We are especially motivated by the fact that 8-month-old human infants can accomplish segmentation of words from fluent audio streams based exclusively on the statistical relationships between neighboring speech sounds without any kind of supervision. In this paper, we introduce a biologically inspired and fully unsupervised neurocomputational approach that incorporates key neurophysiological and anatomical cortical properties, including columnar organization, spontaneous micro-columnar formation, adaptation to contextual activations and Sparse Distributed Representations (SDRs) produced by means of partial N-Methyl-D-aspartic acid (NMDA) depolarization. Its feature abstraction capabilities show promising phonetic invariance and generalization attributes. Our model improves the performance of a Support Vector Machine (SVM) classifier for monosyllabic, disyllabic and trisyllabic word classification tasks in the presence of environmental disturbances such as white noise, reverberation, and pitch and voice variations. Furthermore, our approach emphasizes potential self-organizing cortical principles achieving improvement without any kind of optimization guidance which could minimize hypothetical loss functions by means of-for example-backpropagation. Thus, our computational model outperforms multiresolution spectro-temporal auditory feature representations using only the statistical sequential structure immerse in the phonotactic rules of the input stream.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1990

Fault diagnosis

The objective of the research in this area of fault management is to develop and implement a decision aiding concept for diagnosing faults, especially faults which are difficult for pilots to identify, and to develop methods for presenting the diagnosis information to the flight crew in a timely and comprehensible manner. The requirements for the diagnosis concept were identified by interviewing pilots, analyzing actual incident and accident cases, and examining psychology literature on how humans perform diagnosis. The diagnosis decision aiding concept developed based on those requirements takes abnormal sensor readings as input, as identified by a fault monitor. Based on these abnormal sensor readings, the diagnosis concept identifies the cause or source of the fault and all components affected by the fault. This concept was implemented for diagnosis of aircraft propulsion and hydraulic subsystems in a computer program called Draphys (Diagnostic Reasoning About Physical Systems). Draphys is unique in two important ways. First, it uses models of both functional and physical relationships in the subsystems. Using both models enables the diagnostic reasoning to identify the fault propagation as the faulted system continues to operate, and to diagnose physical damage. Draphys also reasons about behavior of the faulted system over time, to eliminate possibilities as more information becomes available, and to update the system status as more components are affected by the fault. The crew interface research is examining display issues associated with presenting diagnosis information to the flight crew. One study examined issues for presenting system status information. One lesson learned from that study was that pilots found fault situations to be more complex if they involved multiple subsystems. Another was pilots could identify the faulted systems more quickly if the system status was presented in pictorial or text format. Another study is currently under way to examine pilot mental models of the aircraft subsystems and their use in diagnosis tasks. Future research plans include piloted simulation evaluation of the diagnosis decision aiding concepts and crew interface issues. Information is given in viewgraph form.

Abbott, Kathy↗