Search NASA⌕ Search

SEARCH · Search NASA

Results for “DECISION ELEMENT”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 253 records · Page 14

Dynamic IT Security Database and Analytics for Launch Control Systems Software

During the Summer 2020 session, I worked with intern Destani S. Van Arsdalen of EGS Software. Together, we co-created a tool to aid the dynamic investigation, updated over time,of the security compliance of LCS COTS and open source software. We originally planned touse spreadsheet software for management and analysis, but through this exploratoryproject, chose to use Python and JSON after receiving feedback on our project’s current anddesired capabilities at that time.At first, the project was solely designed to help on-board new COTS software, based on aquestionnaire that could be filled out for each software package. This, combined with usingthe spreadsheet application’s web-query capabilities to fetch information from the NVD,allowed presentation and analytics cells to automatically populate as elements of themanually-filled questionnaire changed. While this system was promising, we decided tochange technologies for a few reasons. In the spreadsheet, single cells could not hold complexdata like arrays and objects. The automatic population of cells and dynamic updates made itdifficult to manage and add new features. And finally, it had limited extensibility sinceadding new software required significant understanding of how both the spreadsheet wasconstructed, and the more obscure, proprietary scripting languages packaged with it.The pivot to a standard computer science database language of JSON, aided by thescripting capabilities of Python, greatly helped to improve the project’s functionality. First,and most importantly, the script’s import and analysis of database data is easilyreproducible. Additional data analysis can be modularly added without requiringmodification of the script and is capable of routine scheduling. The revised process can besplit into three parts. First, the conversion of LCS asset and software documentation into theJSON hierarchical database format. Second, the merging of this database with the NVD,forming a new data structure, using CPEs of the CVE object as a linking element betweenthem. And third, the automatically performed analytics and analysis of the combined data,in a modular and extensible format, to produce better informed business decisions. The outputted graphs, for example, are automatically generated by the Python script inconnection with the combined database. This allows updated graphs and any analytics to be re-rendered automatically following updates to the LCS’s initial asset documentation. Afinal report can then be programmatically and easily constructed from these sources to allow fully reproducible metrics for heavily evidenced risk management decisions.

it↗

Gateway Program Progress and Overview

This paper provides an overview and status of the Gateway, which will be a small, human-tended space station in orbit around the Moon. The National Aeronautics and Space Administration (NASA) leads the Program and serves as the integrator of the spaceflight capabilities and contributions of U.S. commercial partners and international partners to develop the Gateway. Gateway is the cornerstone of sustainable deep space human exploration and is an essential element of the infrastructure necessary for the execution of the Artemis missions to the Moon. This paper will outline the current planned configuration and deployment of the station, describing the concept of operations and how Gateway supports both lunar surface missions and also serves as the springboard for exploration deeper in space. Calendar year 2022 will see the accomplishments of major milestones such as over twenty systems preliminary design reviews (PDRs), a Program-wide PDR-informed synchronization review, and NASA Key Decision Point marking the evolution of the program as a whole from the formulation phase and into implementation. This paper will provide a progress update for each major component of the Gateway: The Power and Propulsion Element; the Habitation and Logistics Outpost (HALO); Deep Space Logistics; the International Habitation module; the European System Providing Refueling, Infrastructure, and Telecommunications (ESPRIT), which includes a Refueler Module and the HALO Lunar Communications System; External Robotics System; and an Airlock with both science and crew capabilities. For each component, the paper will describe the current maturity of the modules, acquisition strategy, contracts, and if applicable, international partnership status. This paper will also outline the integration function the Gateway Program Office performs at the NASA Johnson Space Center, including the multilateral governance structure and cross-program interfaces across Artemis.

Gateway↗

Advancements in Constitutive Model Calibration: Leveraging the Power of Full‐Field DIC Measurements and In Situ Load Path Selection for Reliable Parameter Inference

Accurate material characterization and model calibration are essential for computationally supported high-consequence engineering decisions. Historically, characterization and calibration methods (1) use simplified test specimen geometries and global data, (2) cannot guarantee that sufficient characterization data are collected for a specific model of interest, (3) use deterministic methods that provide best-fit parameter values with no uncertainty quantification, and (4) are sequential, inflexible, and time-consuming. This work brings together several recent advancements into an improved workflow called interlaced characterization and calibration (ICC) that advances the state-of-the-art in constitutive model calibration. The ICC paradigm (1) employs tools to efficiently use full-field data to calibrate high-fidelity material models, (2) aligns the data needed with the data collected by adopting an optimal experimental design protocol, (3) quantifies parameter uncertainty through Bayesian inference and (4) incorporates these advancements into a quasi real-time feedback loop. The ICC framework is demonstrated here on the calibration of a material model using simulated full-field data for an aluminium cruciform specimen being deformed biaxially. The cruciform is actively driven through the myopically preferred load path using Bayesian optimal experimental design, which selects load steps that yield the maximum expected information gain (EIG). Principal component analysis (PCA) is performed on the model predictions of full-field displacements, and fast surrogate models are built to approximate the input-output relationships of the expensive finite element model. Furthermore, the tools developed and demonstrated here show that high-fidelity constitutive models can be efficiently and reliably calibrated with quantified uncertainty, thus supporting credible decision-making and potentially increasing the agility of solid mechanics modelling by enabling utilization of computational simulations at earlier stages of the design cycle.

Bayesian optimal experimental design↗

Outline of a new approach to the analysis of complex systems and decision processes.

Development of a conceptual framework for dealing with systems which are too complex or too ill-defined to admit of precise quantitative analysis. The approach outlined is based on the premise that the key elements in human thinking are not numbers, but labels of fuzzy sets - i.e., classes of objects in which the transition from membership to nonmembership is gradual rather than abrupt. The approach in question has three main distinguishing features - namely, the use of so-called 'linguistic' variables in place of or in addition to numerical variables, the characterization of simple relations between variables by conditional fuzzy statements, and the characterization of complex relations by fuzzy algorithms.

Zadeh, L. A.↗

Machine learning for fundamental spectroscopic and thermodynamic data of actinides and lanthanides

Accurately modeling optical spectra with absolute radiometric intensities is vital for nuclear forensics applications that depend on characterizing optical emissions from energetic nuclear phenomena. This requires precise knowledge of the individual atomic transition probabilities, known as Einstein A-coefficients, for each emission line. Obtaining these values theoretically or experimentally is often impractical due to the complex electronic structures and the number of transitions involved in atoms relevant to nuclear applications. In this study, we explore the use of machine learning to predict the Einstein A coefficients for atomic transitions. Seven models were evaluated that ranged from deep learning to decision tree algorithms, and found that gradient boosting performed best, specifically the Extreme Gradient Boosting (XGB) architecture, achieving a precision of 86% across transitions of 36 elements. Furthermore, the model was cross-validated using published transition probabilities reported in the literature and applied to estimate Pu plasma temperatures from a previous experiment conducted at Savannah River National Laboratory.

Atomic spectroscopy↗

The U.S. Agrivoltaic Shading Tool: A National-Scale Interface for Modeling Light and Shade Patterns in Ten Common Agrivoltaic Configurations

Agrivoltaic systems are dual-use configurations that co-locate agriculture and photovoltaic (PV) infrastructure and require careful design to balance crop performance and energy generation. A critical element of agrivoltaic design is the spatial and temporal distribution of irradiance and shade within and around PV arrays. To support research, planning, and stakeholder decision-making, we introduce the U.S. Agrivoltaic Shading Tool, a novel web-based application that delivers high-resolution irradiance and photosynthetically active radiation (PAR) modeling for ten standardized PV configurations across the conterminous United States. The tool leverages the National Laboratory of the Rockies (NLR) System Advisor Model (SAM) to perform detailed irradiance simulations, using meteorological data from the National Solar Radiation Database (NSRDB). Outputs include seasonal, monthly, weekly, and diurnal patterns of available sunlight, amount of shade, irradiance, and PAR at ground level within agrivoltaic system footprints. For a user's selected location, these results are visualized through interactive visualizations, heatmaps, and time-series plots, designed to be accessible to both technical and non-technical users. In addition to facilitating rapid spatial exploration of agrivoltaic light environments, the tool will offer seamless integration with the InSPIRE Agrivoltaics Design and Analysis Model (ADAM). This optional workflow will allow users to port selected site and configuration parameters into a more advanced modeling environment for further customization of structural layouts, crop-system compatibility, power generation, and technoeconomic performance. Finally, to promote open science, the entire dataset will be hosted and available for open access through the OpenEI platform. By standardizing and disseminating high-quality irradiance data and design tools, the U.S. Agrivoltaic Shading Tool supports a wide range of users, including researchers, landowners, energy developers, and policymakers, in evaluating the agronomic and energetic feasibility of agrivoltaic systems across the United States.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

SCAR program overview

The objectives, program elements, and distribution of research effort in the NASA AST/SCAR Program since its inception in July of 1972 are discussed. The data needed to make rational decisions in the consideration of future military and civil supersonic aircraft were the main directive.

Mclean, F. E.↗

MIDAS, prototype Multivariate Interactive Digital Analysis System for large area earth resources surveys. Volume 1: System description

A third-generation, fast, low cost, multispectral recognition system (MIDAS) able to keep pace with the large quantity and high rates of data acquisition from large regions with present and projected sensots is described. The program can process a complete ERTS frame in forty seconds and provide a color map of sixteen constituent categories in a few minutes. A principle objective of the MIDAS program is to provide a system well interfaced with the human operator and thus to obtain large overall reductions in turn-around time and significant gains in throughput. The hardware and software generated in the overall program is described. The system contains a midi-computer to control the various high speed processing elements in the data path, a preprocessor to condition data, and a classifier which implements an all digital prototype multivariate Gaussian maximum likelihood or a Bayesian decision algorithm. Sufficient software was developed to perform signature extraction, control the preprocessor, compute classifier coefficients, control the classifier operation, operate the color display and printer, and diagnose operation.

Christenson, D.↗

A Reliable Earth Return System for Safe Recovery of Mars Samples

The objective of a Mars sample return mission is to bring selected Mars surface materials to Earth. Numerous approaches for the Earth-return segment have been analyzed including propulsive or aerocapture return to low-Earth orbit followed by Space Shuttle rendezvous and direct entry. Of these approaches, ballistic entry of a small capsule terminating in a ground landing has been shown to be the lowest risk strategy. Over the past two years, significant work has been performed towards development of a robust direct entry vehicle for Mars sample return. In June 1999, the NASA Planetary Protection Officer provided initial guidance to the former Mars Sample Return Project. The sample return phase of the mission was assigned a restricted Earth return planetary protection classification. The draft mission requirement states that the total mean probability of release of unsterilized Mars material into the Earth;s biosphere must be less than 1.0E-06 (1 in a million). This strict requirement drives the approach and design of the Earth return system. To meet this requirement, selection of the Earth return strategy and development of the Earth return system must be guided by risk, not performance, based decisions. An initial Probabilistic Risk Assessment (PRA) was performed to address the direct entry Earth return system containment assurance reliability and to identify high-risk elements of this system. The results of this PRA identified risk elements that include thermal protection system performance during entry, spin-eject orientation and aerodynamic stability during entry, structural integrity under atmospheric deceleration and impact loads, and tracking/recovery of this system. This initial probabilistic risk quantification demonstrates that, with the proper development program, a prototypical direct entry design can satisfy the containment assurance reliability requirement. Through the current Mars Sample Return Advanced Technology Development effort, an extensive design, analysis, and test program is presently proceeding with the aim of reducing the containment assurance risk of this system. This technology development effort, guided by a continuing PRA, focuses on key risk areas of a direct entry Earth return system including: the thermal protection system, impact dynamics, structural performance, aerodynamic stability, and ground recovery. This development program will culminate in a system validation flight test, 1-2 years prior to launch of the flight system. This flight test would include the launch, entry, and recovery of a full-scale Earth return system, as a scientific validation of the key risk elements to verify nominal design performance. The results of the initial PRA suggested several dominant failure sequences that can be validated in a flight test. These include: demonstrating the thermal protection system reliability and performance during entry, demonstrating the spin-eject orientation and aero-dynamic stability during entry, demonstrating the structural integrity under atmospheric deceleration and impact loads, and demonstrating tracking and recovery of the Earth return system. This single test will directly address over 50% of the total containment assurance risk elements. This presentation will begin by presenting the relative risk of various Earth return strategies. The results of the initial probabilistic risk assessment will be presented followed by a discussion of the development accomplishments and plans for demonstration of a highly reliable direct entry Earth return system.

Braun, R.↗

Performance and Mass Modeling Subtleties in Closed-Brayton-Cycle Space Power Systems

A number of potential NASA missions could benefit from closed-Brayton-cycle (CBC) power conversion systems. The human and robotic mission power applications include spacecraft, surface base, and rover scenarios. Modeling of CBC subsystems allows system engineers, mission planners and project managers to make informed decisions regarding power conversion system characteristics and capabilities. To promote thorough modeling efforts, a critical review of CBC modeling techniques is presented. Analysis of critical modeling elements, component influences and cycle sensitivities is conducted. The analysis leads to quantitative results addressing projections on converter efficiency and overall power conversion system mass. Even moderate modeling errors are shown to easily over-predict converter efficiencies by 30 percent and underestimate mass estimates by 20 percent. Both static and dynamic modeling regimes are evaluated. Key considerations in determining model fidelity requirements are discussed. Conclusions and recommendations are presented that directly address ongoing modeling efforts in solar and nuclear space power systems.

Barrett, Michael J.↗

Performance and Mass Modeling Subtleties in Closed-Brayton-Cycle Space Power Systems

A number of potential NASA missions could benefit from closed-Brayton-cycle (CBC) power conversion systems. The human and robotic mission power applications include spacecraft, surface base, and rover scenarios. Modeling of CBC subsystems allows system engineers, mission planners and project managers to make informed decisions regarding power conversion system characteristics and capabilities. To promote thorough modeling efforts, a critical review of CBC modeling techniques is presented. Analysis of critical modeling elements, component influences and cycle sensitivities is conducted. The analysis leads to quantitative results addressing projections on converter efficiency and overall power conversion system mass. Even moderate modeling errors are shown to easily over-predict converter efficiencies by 30% and underestimate mass estimates by 20%. Both static and dynamic modeling regimes are evaluated. Key considerations in determining model fidelity requirements are discussed. Conclusions and recommendations are presented that directly address ongoing modeling efforts in solar and nuclear space power systems.

Barrett, Michael J.↗

Integrated Design Results for the MSR SRC Mars Ascent Vehicle

The primary mission of the NASA Mars Sample Return (MSR) Campaign is to return samples of the Martian surface to Earth for scientific study. As part of this campaign, NASA is developing a Mars Ascent Vehicle (MAV). This vehicle must survive an approximate two year journey to the Martian surface as a payload aboard a separate lander spacecraft. After residing on the surface for another year, the MAV will carry a payload of samples into orbit. From there, following ejection from the MAV, the samples will rendezvous with an Earth return spacecraft for capture, and ultimately, return to Earth.The design of the MAV represents a number of unique challenges, as no launch vehicle has ever left the surface of a planet other than Earth. Although conceptual designs for a MAV have been in various levels of development since the 1970s, none have achieved the level of fidelity and support that exists in the current MSR-MAV design. Early MSR-MAV concept studies examined multiple methods of propulsion, ultimately deciding that a Two Stage to Orbit (TSTO) solid propulsion vehicle would provide the most capable performance in a Martian environment. Following this key architecture decision, the vehicle design was further matured to a Solid-Solid Guided-Guided (SSGG) architecture for NASA Key Decision Point A (KDP-A). Although the SSGG design was able to meet all mission constraints, concerns were raised regarding limited mass margin on other elements of the MSR campaign at such an early phase. A design challenge was issued to reduce MAV total mass by as much as possible. It was ultimately determined that by moving a number of components of the vehicle second stage to the first stage, the overall vehicle mass could be reduced significantly. The new design featured a much smaller and completely unguided second stage. This paper describes the resultant Solid-Solid Guided-Unguided (SSGU) MAV design concept developed as part of the Systems Requirement Cycle (SRC). This design was developed primarily by NASA Marshall Space Flight Center (MSFC), in association with NASA Jet Propulsion Laboratory (JPL) and NASA Langley Research Center (LaRC). The TSTO vehicle includes one solid rocket motor per stage. As the vehicle second stage is unguided, it features spin-stabilization to maintain vehicle stability during flight. An electromechanically actuated Thrust Vector Control (TVC) and a monopropellant Reaction Control System (RCS) is employed for active guidance on the first stage. The vehicle is designed to deliver up to 0.47kg of Martian samples to a Mars circular orbit of 380km at 27° inclination. Due to the extremely unique design constraints of this mission, and a recent transition to a Risk Class A posture, the MAV team was compelled to devise unconventional solutions to the vehicle design. The detailed design and analysis of these subsystems and the vehicle as a whole are discussed in this paper relative to all of the engineering disciplines involved.

MSR↗

Integrated Design Results for the MSR SRC Mars Ascent Vehicle

The primary mission of the NASA Mars Sample Return (MSR) Campaign is to return samples of the Martian surface to Earth for scientific study. As part of this campaign, NASA is developing a Mars Ascent Vehicle (MAV). This vehicle must survive an approximate two-year journey to the Martian surface as a payload aboard a separate lander spacecraft. After residing on the surface for another year, the MAV will carry a payload of samples into orbit. From there, following ejection from the MAV, the samples will rendezvous with an Earth return spacecraft for capture, and ultimately, return to Earth. The design of the MAV represents a number of unique challenges, as no launch vehicle has ever left the surface of a planet other than Earth. Although conceptual designs for a MAV have been in various levels of development since the 1970s, none have achieved the level of fidelity and support that exists in the current MSR-MAV design. Early MSR-MAV concept studies examined multiple methods of propulsion, ultimately deciding that a Two-Stage-to-Orbit (TSTO) solid propulsion vehicle would provide the most capable performance in a Martian environment. Following this key architecture decision, the vehicle design was further matured to a Solid-Solid Guided-Guided (SSGG) architecture for NASA Key Decision Point A (KDP-A). Although the SSGG design was able to meet all mission constraints, concerns were raised regarding limited mass margin on other elements of the MSR campaign at such an early phase. A design challenge was issued to reduce MAV total mass by as much as possible. It was ultimately determined that by moving a number of components of the vehicle second stage to the first stage, the overall vehicle mass could be reduced significantly. The new design features a much smaller and completely unguided second stage. This paper describes the resultant Solid-Solid Guided-Unguided (SSGU) MAV design concept developed as part of the Systems Requirement Cycle (SRC). This design was developed primarily by NASA Marshall Space Flight Center (MSFC), in association with NASA Jet Propulsion Laboratory (JPL) and NASA Langley Research Center (LaRC). The TSTO vehicle includes one solid rocket motor per stage. As the vehicle second stage is unguided, it features spin-stabilization to maintain vehicle stability during flight. An electromechanically actuated Thrust Vector Control (TVC) system and a monopropellant Reaction Control System (RCS) are employed for active guidance on the first stage. The vehicle is designed to deliver up to 0.47kg of Martian samples to a Mars circular orbit of 380km at 27° inclination. Due to the extremely unique design constraints of this mission, and a recent transition to a Risk Class A posture, the MAV team was compelled to devise unconventional solutions to the vehicle design. The detailed design and analysis of these subsystems and the vehicle as a whole are discussed in this paper relative to all of the engineering disciplines involved.

MAV↗

Data‐Driven Insights into Rare Earth Mineralization: Machine Learning Applications Using Functional Material Synthesis Data

Understanding rare‐earth element (REE) mineralization mechanisms is essential for developing efficient separation strategies. Although the geochemical pathways that generate REE deposits are qualitatively known, quantitative links between specific conditions and mineralization outcomes remain limited. Herein, the repurpose laboratory REE hydrothermal synthesis data—originally collected for functional‐materials fabrication—as a surrogate for studying mineralization with data‐driven methods. The compiled 1,200+ hydrothermal reaction records and trained three machine‐learning models—K‐nearest neighbors (KNN), random forest (RF), and extreme gradient boosting (XGB)—to predict product elements and phases from precursors, additives, reaction conditions, and engineered features. Validation shows XGB achieves the highest accuracy. Feature importance indicates thermodynamic properties of cations and anions dominate model decisions. Correlations reveal positive relationships among precursor concentration, reaction time, pH, and temperature, consistent with classical crystallization behavior. XGB‐based regressors are built to predict crystallization temperature and pH from precursor/product attributes. Performance is strongest when similar training examples exist, while accuracy declines for underrepresented reactions, notably REE carbonates and heavy‐REE systems. Overall, the study shows that functional‐materials datasets can illuminate REE mineralization and provide priors for exploration and processing. Expanding datasets with less‐studied chemistries and conditions will improve generality and support deposit discovery and more efficient REE recovery.

feature importance analysis↗

The Value of a Spaceflight Clinical Decision Support System for Earth-Independent Medical Operations

As NASA prepares for crewed lunar missions over the next several years, plans are also underway to journey farther into deep space. Deep space exploration will require a paradigm shift in astronaut medical support toward progressively earth-independent medical operations (EIMO). The Exploration Medical Capability (ExMC) element of NASA’s Human Research Program (HRP) is investigating the feasibility and value of advanced capabilities to promote and enhance EIMO. Currently, astronauts rely on real-time communication with ground-based medical providers. However, as the distance from Earth increases, so do communication delays and disruptions. Moreover, resupply and evacuation will become increasingly complex, if not impossible, on deep space missions. In contrast to today’s missions in low earth orbit (LEO), where most medical expertise and decision-making are ground-based, an exploration crew will need to autonomously detect, diagnose, treat, and prevent medical events. Due to the sheer amount of pre-mission training required to execute a human spaceflight mission, there is often little time to devote exclusively to medical training. One potential solution is to augment the long duration exploration crew’s knowledge, skills, and abilities with a clinical decision support system (CDSS). An analysis of preliminary data indicates the potential benefits of a CDSS to mission outcomes when augmenting cognitive and procedural performance of an autonomous crew performing medical operations, and we provide an illustrative scenario of how such a CDSS might function.

Brian K. Russell↗

Principles and Options for Designing Battery Energy Storage Zoning Ordinances

Deployment of battery energy storage (BESS) systems, both standalone and as part of hybrid systems paired with generation, has rapidly increased in the United States in recent years as utilities and communities have deployed storage to improve electric grid reliability and act as a cost-effective alternative to larger grid infrastructure. The modular nature of BESS technologies means systems may be built near other existing land uses, creating the potential for conflicts with neighboring landowners that can be managed and mitigated through zoning and permitting requirements established by local jurisdictions. While many cities and counties have adopted ordinances specific to BESS into their local zoning codes, these ordinances vary significantly in their requirements and level of detail. Meanwhile, many other jurisdictions, including those home to proposed or existing BESS projects, lack any specific language related to BESS in their zoning codes. Local planning and zoning officials have limited capacity and may lack the familiarity with BESS technologies needed to develop ordinances or otherwise make reasonable zoning decisions that balance safety, community impacts, and other goals. The resulting uncertainty at the local zoning level has led developers to withdraw projects in some areas and has spurred moratoria or bans on energy storage projects in others. This report intends to provide practical resources for practitioners interested in reasonable and effective local regulation of battery energy storage. It does not present a model zoning ordinance, but rather is intended to complement model ordinances developed by others by providing additional context and analysis regarding the structure of energy storage zoning ordinances and the decision points for local officials. Zoning ordinances at the city, town, and county level across the U.S. were surveyed alongside two template model ordinances to identify common elements and options for regulating the zoning and siting of BESS. Common elements identified and analyzed include definitions and general requirements, including cutoffs or tiers used to apply regulations to different system sizes and the permitted zones where jurisdictions allow BESS to be sited; visual, noise, and aesthetic requirements, including property line setbacks, fencing and visual screening, noise, and lighting requirements; and safety and planning requirements, such as site plans, decommissioning plans or funds, and requirements for access by emergency services. The report also summarizes some of the more unique regulations, including those that place additional restrictions on BESS at the local level.

25 ENERGY STORAGE↗

Deep space telecommunications, navigation, and information management - Support of the Space Exploration Initiative

The principal challenges in providing effective deep space navigation, telecommunications, and information management architectures and designs for Mars exploration support are presented. The fundamental objectives are to provide the mission with the means to monitor and control mission elements, obtain science, navigation, and engineering data, compute state vectors and navigate, and to move these data efficiently and automatically between mission nodes for timely analysis and decision making. New requirements are summarized, and related issues and challenges including the robust connectivity for manned and robotic links, are identified. Enabling strategies are discussed, and candidate architectures and driving technologies are described.

Hall, Justin R.↗

Pilots' Information Needs and Strategies for Operating in Icing Conditions

Pilot current use of icing information, pilot encounters and strategies for dealing with in-flight aircraft structural icing situations, and desired attributes of new icing information systems were investigated through a survey of pilots of several operational categories. The survey identified important information elements and fiequently used information paths for obtaining icing-related information. Free- response questions solicited descriptions of significant , icing encounters, and probed key icing-related decision and information criteria. Results indicated the information needs for the horizontal and vertical location of icing conditions and the identification of icing-free zones.

Vigeant-Langlois, Laurence N.↗