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At least 811 records · Page 45

Studies of lightning data in conjunction with geostationary satellite data

Since January, work has been proceeding on the first phase of this project: the creation of an extensive real-time lightning data base accessible via the Space Science and Engineering Center McIdas system. The purpose of this endeavor is two-fold: to enhance the availability and ease of access to lightning data among the various networks, governmental and research agencies; and to test the feasiblity and desirability of such efforts in succeeding years. The final steps in the creation of the necessary communications links, hardware, and software are in the process of being completed. Operations ground rules for access among the various users have been discussed and are being refined. While the research planned for the last year of the project will rely for the most part on archived, quality-controlled data from the various networks, the real-time data will provide a valuable first-look at potentially interesting case studies. For this purpose, tools are being developed on McIdas for display and analysis of the data as they become available. In conjunction with concurrent GOES real-time imagery, strike locations can be plotted, gridded and contoured, or displayed in various statistical formats including frequency distributions, histograms, and scatter plots. The user may also perform these functions in relation to arbitrarily defined areas on the satellite image. By mid-May these preparations for the access and analysis of real-time lightning data are expected to be complete.

Auvine, B.↗

Remote measurement of in-plane diffusivity components in plates

A method of determining thermal diffusivity in thin plates is presented. The method, using infrared images of evolving thermal patterns previously injected with a laser, is noncontacting, one-sided, and remote. It does not require independent estimates of either the emissivity of the sample or the sample thickness. With a line-segment pattern for thermal input, it yields the inplane components of the diffusivity tensor in anisotropic materials and also the rate of heat loss to the environment of the plate. Two methods of data analysis are presented, one corresponding to a heating line of general cross section and the other considering a Gaussian cross section, thereby saving considerable computer time. Both methods produce a statistical evaluation of measurement quality as well as estimates of diffusivity and loss rate. Results are shown for plates of metals and graphite-epoxy composite materials. Principal components and orientation for the diffusivity tensor are obtained in the anisotropic graphite-epoxy sample.

Welch, Christopher S.↗

A simulation study of the flight dynamics of elastic aircraft. Volume 1: Experiment, results and analysis

The simulation experiment described addresses the effects of structural flexibility on the dynamic characteristics of a generic family of aircraft. The simulation was performed using the NASA Langley VMS simulation facility. The vehicle models were obtained as part of this research. The simulation results include complete response data and subjective pilot ratings and comments and so allow a variety of analyses. The subjective ratings and analysis of the time histories indicate that increased flexibility can lead to increased tracking errors, degraded handling qualities, and changes in the frequency content of the pilot inputs. These results, furthermore, are significantly affected by the visual cues available to the pilot.

Waszak, Martin R.↗

A simulation study of the flight dynamics of elastic aircraft. Volume 2: Data

The simulation experiment described addresses the effects of structural flexibility on the dynamic characteristics of a generic family of aircraft. The simulation was performed using the NASA Langley VMS simulation facility. The vehicle models were obtained as part of this research project. The simulation results include complete response data and subjective pilot ratings and comments and so allow a variety of analyses. The subjective ratings and analysis of the time histories indicate that increased flexibility can lead to increased tracking errors, degraded handling qualities, and changes in the frequency content of the pilot inputs. These results, furthermore, are significantly affected by the visual cues available to the pilot.

Waszak, Martin R.↗

Antenna pattern study

Prediction of antenna radiation patterns has long been an important function in the design of command, communication, and tracking systems for rocket vehicles and spacecraft. An acceptable degree of assurance that a radio link will provide the required quality of data or certainty of correct command execution must be acquired by some means if the system is to be certified as reliable. Two methods have been used to perform this function: (1) Theoretical analysis, based on the known properties of basic antenna element types and their behavior in the presence of conductive structures of simple shape, and (2) Measurement of the patterns on scale models of the spacecraft or rocket vehicle on which the antenna is located. Both of these methods are ordinarily employed in the antenna design process.

Harper, Warren↗

The Pacor 2 expert system: A case-based reasoning approach to troubleshooting

The Packet Processor 2 (Pacor 2) Data Capture Facility (DCF) acquires, captures, and performs level-zero processing of packet telemetry for spaceflight missions that adhere to communication services recommendations established by the Consultative Committee for Space Data Systems (CCSDS). A major goal of this project is to reduce life-cycle costs. One way to achieve this goal is to increase automation. Through automation, using expert systems, and other technologies, staffing requirements will remain static, which will enable the same number of analysts to support more missions. Analysts provide packet telemetry data evaluation and analysis services for all data received. Data that passes this evaluation is forwarded to the Data Distribution Facility (DDF) and released to scientists. Through troubleshooting, data that fails this evaluation is dumped and analyzed to determine if its quality can be improved before it is released. This paper describes a proof-of-concept prototype that troubleshoots data quality problems. The Pacor 2 expert system prototype uses the case-based reasoning (CBR) approach to development, an alternative to a rule-based approach. Because Pacor 2 is not operational, the prototype has been developed using cases that describe existing troubleshooting experience from currently operating missions. Through CBR, this experience will be available to analysts when Pacor 2 becomes operational. As Pacor 2 unique experience is gained, analysts will update the case base. In essence, analysts are training the system as they learn. Once the system has learned the cases most likely to recur, it can serve as an aide to inexperienced analysts, a refresher to experienced analysts for infrequently occurring problems, or a training tool for new analysts. The Expert System Development Methodology (ESDM) is being used to guide development.

Sary, Charisse↗

Aerosol Source Attributions and Source-Receptor Relationships Across the Northern Hemisphere

Emissions and long-range transport of air pollution pose major concerns on air quality and climate change. To better assess the impact of intercontinental transport of air pollution on regional and global air quality, ecosystems, and near-term climate change, the UN Task Force on Hemispheric Transport of Air Pollution (HTAP) is organizing a phase II activity (HTAP2) that includes global and regional model experiments and data analysis, focusing on ozone and aerosols. This study presents the initial results of HTAP2 global aerosol modeling experiments. We will (a) evaluate the model results with surface and aircraft measurements, (b) examine the relative contributions of regional emission and extra-regional source on surface PM concentrations and column aerosol optical depth (AOD) over several NH pollution and dust source regions and the Arctic, and (c) quantify the source-receptor relationships in the pollution regions that reflect the sensitivity of regional aerosol amount to the regional and extra-regional emission reductions.

HTAP2↗

PALMO: An OVERFLOW Machine Learning Airfoil Performance Database

The OVERFLOW Machine Learning Airfoil Performance (PALMO) database has been created to enable robust modeling of airfoil performance in a variety of applications. The database uses OVERFLOW simulation data second-order accurate in time and fourth-order accurate in space with Spalart-Allmaras turbulence closure. The foundation of the in-development PALMO database is the airfoil base cube. Each base cube includes simulation data parametrized over a range of Mach numbers, Reynolds numbers, and angles-of-attack. This first release of the database includes the NACA 4-series airfoils, with parametrization in airfoil thickness and camber from an NACA 0006 to an NACA 4424. In total, 52,480 NACA 4-series calculations were run on the NASA High-End Compute Capability (HECC) supercomputer and the corresponding airfoil performance coefficients are embedded in the Appendix of this document for public distribution. This provides high-order-accurate simulation data covering a wide range of aerospace design applications, which enables users to develop OVERFLOW-quality airfoil performance look-up tables without additional high-performance computing. In addition to engineering design and analysis of aerospace vehicles, PALMO is well suited to be a benchmark dataset for the development and testing of machine learning methods in aerospace engineering. Downstream surrogate models enable OVERFLOW- quality airfoil performance predictions for any arbitrary combination of camber, thickness, Mach number, Reynolds number, and angle-of-attack within the bounds of the database.

Database↗

The Suomi National Polar-Orbiting Partnership (SNPP): Continuing NASA Research and Applications

The Suomi National Polar-orbiting Partnership (SNPP) satellite was successfully launched into a polar orbit on October 28, 2011 carrying 5 remote sensing instruments designed to provide data to improve weather forecasts and to increase understanding of long-term climate change. SNPP provides operational continuity of satellite-based observations for NOAA's Polar-orbiting Operational Environmental Satellites (POES) and continues the long-term record of climate quality observations established by NASA's Earth Observing System (EOS) satellites. In the 2003 to 2011 pre-launch timeframe, NASA's SNPP Science Team assessed the adequacy of the operational Raw Data Records (RDRs), Sensor Data Records (SDRs), and Environmental Data Records (EDRs) from the SNPP instruments for use in NASA Earth Science research, examined the operational algorithms used to produce those data records, and proposed a path forward for the production of climate quality products from SNPP. In order to perform these tasks, a distributed data system, the NASA Science Data Segment (SDS), ingested RDRs, SDRs, and EDRs from the NOAA Archive and Distribution and Interface Data Processing Segments, ADS and IDPS, respectively. The SDS also obtained operational algorithms for evaluation purposes from the NOAA Government Resource for Algorithm Verification, Independent Testing and Evaluation (GRAVITE). Within the NASA SDS, five Product Evaluation and Test Elements (PEATEs) received, ingested, and stored data and performed NASA's data processing, evaluation, and analysis activities. The distributed nature of this data distribution system was established by physically housing each PEATE within one of five Climate Analysis Research Systems (CARS) located at either at a NASA or a university institution. The CARS were organized around 5 key EDRs directly in support of the following NASA Earth Science focus areas: atmospheric sounding, ocean, land, ozone, and atmospheric composition products. The PEATES provided the system level interface with members of the NASA SNPP Science Team and other science investigators within each CARS. A sixth Earth Radiation Budget CARS was established at NASA Langley Research Center (NASA LaRC) to support instrument performance, data evaluation, and analysis for the SNPP Clouds and the Earth's Radiant Budget Energy System (CERES) instrument. Following the 2011 launch of SNPP, spacecraft commissioning, and instrument activation, the NASA SNPP Science Team evaluated the operational RDRs, SDRs, and EDRs produced by the NOAA ADS and IDPS. A key part in that evaluation was the NASA Science Team's independent processing of operational RDRs and SDRs to EDRs using the latest NASA science algorithms. The NASA science evaluation was completed in the December 2012 to April 2014 timeframe with the release of a series of NASA Science Team Discipline Reports. In summary, these reports indicated that the RDRs produced by the SNPP instruments were of sufficiently high quality to be used to create data products suitable for NASA Earth System science and applications. However, the quality of the SDRs and EDRs were found to vary greatly when considering suitability for NASA science. The need for improvements in operational algorithms, adoption of different algorithmic approaches, greater monitoring of on-orbit instrument calibration, greater attention to data product validation, and data reprocessing were prominent findings in the reports. In response to these findings, NASA, in late 2013, directed the NASA SNPP Science Team to use SNPP instrument data to develop data products of sufficiently high quality to enable the continuation of EOS time series data records and to develop innovative, practical applications of SNPP data. This direction necessitated a transition of the SDS data system from its pre-launch assessment mode to one of full data processing and production. To do this, the PEATES, which served as NASA's data product testing environment during the prelaunch and early on-orbit periods, were transitioned to Science Investigator-led Processing Systems (SIPS). The distributed data architecture was maintained in this new system by locating the SIPS at the same institutions at which the CARS and PEATES were located. The SIPS acquire raw SNPP instrument Level 0 (i.e. RDR) data over the full SNPP mission from the NOAA ADS and IDPS through the NASA SDS Data Distribution and Depository Element (SD3E). The SIPS process those data into NASA Level 1, Level 2, and global, gridded Level 3 standard products using peer-reviewed algorithms provided by members of the NASA Science Team. The SIPS work with the NASA SNPP Science Team in obtaining enhanced, refined, or alternate real-time algorithms to support the capabilities of the Direct Readout Laboratory (DRL). All data products, algorithm source codes, coefficients, and auxiliary data used in product generation are archived in an assigned NASA Distributed Active Archive Center (DAAC).

remote sensing↗

The Impact of Traffic Prioritization on Deep Space Network Mission Traffic

A select number of missions supported by NASA's Deep Space Network (DSN) are demanding very high data rates. For example, the Kepler Mission was launched March 7, 2009 and at that time required the highest data rate of any NASA mission, with maximum rates of 4.33 Mb/s being provided via Ka band downlinks. The James Webb Space Telescope will require a maximum 28 Mb/s science downlink data rate also using Ka band links; as of this writing the launch is scheduled for a June 2014 launch. The Lunar Reconnaissance Orbiter, launched June 18, 2009, has demonstrated data rates at 100 Mb/s at lunar-Earth distances using NASA's Near Earth Network (NEN) and K-band. As further advances are made in high data rate space telecommunications, particularly with emerging optical systems, it is expected that large surges in demand on the supporting ground systems will ensue. A performance analysis of the impact of high variance in demand has been conducted using our Multi-mission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE) simulation tool. A comparison is made regarding the incorporation of Quality of Service (QoS) mechanisms and the resulting ground-to-ground Wide Area Network (WAN) bandwidth necessary to meet latency requirements across different user missions. It is shown that substantial reduction in WAN bandwidth may be realized through QoS techniques when low data rate users with low-latency needs are mixed with high data rate users having delay-tolerant traffic.

prioritization↗

The Impact of Traffic Prioritization on Deep Space Network Mission Traffic

A select number of missions supported by NASA's Deep Space Network (DSN) are demanding very high data rates. For example, the Kepler Mission was launched March 7, 2009 and at that time required the highest data rate of any NASA mission, with maximum rates of 4.33 Mb/s being provided via Ka band downlinks. The James Webb Space Telescope will require a maximum 28 Mb/s science downlink data rate also using Ka band links; as of this writing the launch is scheduled for a June 2014 launch. The Lunar Reconnaissance Orbiter, launched June 18, 2009, has demonstrated data rates at 100 Mb/s at lunar-Earth distances using NASA's Near Earth Network (NEN) and K-band. As further advances are made in high data rate space telecommunications, particularly with emerging optical systems, it is expected that large surges in demand on the supporting ground systems will ensue. A performance analysis of the impact of high variance in demand has been conducted using our Multi-mission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE) simulation tool. A comparison is made regarding the incorporation of Quality of Service (QoS) mechanisms and the resulting ground-to-ground Wide Area Network (WAN) bandwidth necessary to meet latency requirements across different user missions. It is shown that substantial reduction in WAN bandwidth may be realized through QoS techniques when low data rate users with low-latency needs are mixed with high data rate users having delay-tolerant traffic.

quality of service↗

Engineering and Scientific Applications: Using MatLab(Registered Trademark) for Data Processing and Visualization

MatLab(R) (MATrix LABoratory) is a numerical computation and simulation tool that is used by thousands Scientists and Engineers in many cou ntries. MatLab does purely numerical calculations, which can be used as a glorified calculator or interpreter programming language; its re al strength is in matrix manipulations. Computer algebra functionalities are achieved within the MatLab environment using "symbolic" toolbo x. This feature is similar to computer algebra programs, provided by Maple or Mathematica to calculate with mathematical equations using s ymbolic operations. MatLab in its interpreter programming language fo rm (command interface) is similar with well known programming languag es such as C/C++, support data structures and cell arrays to define c lasses in object oriented programming. As such, MatLab is equipped with most ofthe essential constructs of a higher programming language. M atLab is packaged with an editor and debugging functionality useful t o perform analysis of large MatLab programs and find errors. We belie ve there are many ways to approach real-world problems; prescribed methods to ensure foregoing solutions are incorporated in design and ana lysis of data processing and visualization can benefit engineers and scientist in gaining wider insight in actual implementation of their perspective experiments. This presentation will focus on data processing and visualizations aspects of engineering and scientific applicati ons. Specifically, it will discuss methods and techniques to perform intermediate-level data processing covering engineering and scientifi c problems. MatLab programming techniques including reading various data files formats to produce customized publication-quality graphics, importing engineering and/or scientific data, organizing data in tabu lar format, exporting data to be used by other software programs such as Microsoft Excel, data presentation and visualization will be discussed. The presentation will emphasize creating practIcal scripts (pro grams) that extend the basic features of MatLab TOPICS mclude (1) Ma trix and vector analysis and manipulations (2) Mathematical functions (3) Symbolic calculations & functions (4) Import/export data files (5) Program lOgic and flow control (6) Writing function and passing parameters (7) Test application programs

Sen, Syamal K.↗

Maximizing Science Return from Future Rodent Experiments on the International Space Station (ISS): Tissue Preservation

To better understand how mammals adapt to long duration habitation in space, a system for performing rodent experiments on the ISS is under development; Rodent Research-1 is the first flight and will include validation of both on-orbit animal support and tissue preservation. To evaluate plans for on-orbit sample dissection and preservation, we simulated conditions for euthanasia, tissue dissection, and prolonged sample storage on the ISS, and we also developed methods for post-flight dissection and recovery of high quality RNA from multiple tissues following prolonged storage in situ for future science. Mouse livers and spleens were harvested under conditions that simulated nominal, on-orbit euthanasia and dissection operations including storage at -80 C for 4 months. The RNA recovered was of high quality (RNA Integrity Number, RIN(is) greater than 8) and quantity, and the liver enzyme contents and activities (catalase, glutathione reductase, GAPDH) were similar to positive controls, which were collected under standard laboratory conditions. We also assessed the impact of possible delayed on-orbit dissection scenarios (off-nominal) by dissecting and preserving the spleen (RNAlater) and liver (fast-freezing) at various time points post-euthanasia (from 5 min up to 105 min). The RNA recovered was of high quality (spleen, RIN (is) greater than 8; liver, RIN (is) greater than 6) and liver enzyme activities were similar to positive controls at all time points, although an apparent decline in select enzyme activities was evident at the latest time (105 min). Additionally, various tissues were harvested from either intact or partially dissected, frozen carcasses after storage for approximately 2 months; most of the tissues (brain, heart, kidney, eye, adrenal glands and muscle) were of acceptable RNA quality for science return, whereas some tissues (small intestine, bone marrow and bones) were not. These data demonstrate: 1) The protocols developed for future flight experiments will support science return despite delayed preservation post-euthanasia or prolonged storage, and 2) Many additional tissues for gene expression analysis can be obtained by dissection following prolonged storage of the tissue in situ at -80 C. These findings have relevance both to high value, ground-based experiments when sample collection capability is severely constrained, and to all future spaceflight experiments that entail on-orbit sample recovery by the ISS crew.

tissues↗

Integrating Flight Dynamics & Control Analysis and Simulation in Rotorcraft Conceptual Design

The development of a toolset, SIMPLI-FLYD ('SIMPLIfied FLight dynamics for conceptual Design') is described. SIMPLI-FLYD is a collection of tools that perform flight dynamics and control modeling and analysis of rotorcraft conceptual designs including a capability to evaluate the designs in an X-Plane-based real-time simulation. The establishment of this framework is now facilitating the exploration of this new capability, in terms of modeling fidelity and data requirements, and the investigation of which stability and control and handling qualities requirements are appropriate for conceptual design. Illustrative design variation studies for single main rotor and tiltrotor vehicle configurations show sensitivity of the stability and control characteristics and an approach to highlight potential weight savings by identifying over-design.

Integrating Flight Dynamics↗

NASA Feedback to DLA Land & Maritime Moratorium on Wafer Fab Audits

On September 29, 2017 the Defense Logistics Agency (DLA), Land and Maritime, announced that on September 1, 2017 they had begun a moratorium on the auditing of wafer fabrication facilities (fabs) used in the production of semiconductor die for military (MIL) qualified integrated circuits and discrete semiconductors (transistors and diodes). The announcement said the moratorium would last for six months initially and would apply to all wafer fabs qualified to MIL-PRF-19500 (discretes) and MIL-PRF-38535 (ICs) located, onshore or offshore. The stated rationale behind this action was to give DLA time to evaluate the risk of modifying current surveillance practices across 70+ Federal Stock Classes (FSC) under the jurisdiction of the DLA Qualifying Activity (VQ). The objective was to free up the resources used in these audits so they could be redirected towards audits of other commodities which were under resourced, notably connectors. In the announcement letter, DLA-VQ requested data from the community to assist with decisions on wafer fab re-audit cycle modifications. NASA used available information on current and historical audit schedules to gather such data and analyzed it to provide an in-depth understanding of the impact of locations, part types, in-house or out-of-house fabs on those schedules over time. This presentation provides the results of NASA's data analysis and suggest some changes to auditing practices that could increase efficient use of resources without significant increases in risk.

fab audits↗

Interpreting forest and grassland biome productivity utilizing nested scales of image resolution and biogeographical analysis

Data acquisition, initial site characterization, image and geographic information methods available, and brief evaluations of first-year for NASA's Thematic Mapper (TM) working group are presented. The TM and other spectral data are examined in order to relate local, intensive ecosystem research findings to estimates of carbon cycling rates over wide geographic regions. The effort is to span environments ranging from dry to moist climates and from good to poor site quality using the TM capability, with and without the inclusion of geographic information system (GIS) data, and thus to interpret the local spatial pattern of factors conditioning biomass or productivity. Twenty-eight TM data sets were acquired, archived, and evaluated. The ERDAS image processing and GIS system were installed on the microcomputer (PC-AT) and its capabilities are being investigated. The TM coverage of seven study areas were exported via ELAS software on the Prime to the ERDAS system. Statistical analysis procedures to be used on the spectral data are being identified.

Iverson, L. R.↗

Examination of L-Band Brightness Temperature Forecasts in the SMAP Level-4 Soil Moisture Analysis

The NASA Soil Moisture Active Passive (SMAP) mission [4] has been providing L-band (1.4 GHz) passive microwave brightness temperature (Tb) observations since April 2015. By assimilating the Tb observations into the NASA Catchment land surface model [5] using a spatially distributed ensemble Kalman filter, the NASA Global Modeling and Assimilation Office generates the SMAP Level-4 Soil Moisture (L4_SM) product, which provides global, 3-hourly, 9-km resolution estimates of surface (0-5 cm) and root-zone (0-100 cm) soil moisture with ~2.5-day latency for use in research and applications [6]. The L4_SM product also includes estimates of soil temperature, land surface fluxes, and assimilation diagnostics such as the model forecast and observed Tb values [7]. The output from the L4_SM system is routinely monitored by the L4_SM team. Such monitoring provides valuable information; instances of unusually large Tb observation-minus-forecast (O-F) residuals can indicate events during which soil moisture conditions are poorly described in the land modeling system [7,8]. For example, repeated occurrences of very large Tb O-F values in central Australia were traced back to deficiencies in the gauge-based precipitation product used in the land modeling system through L4_SM Version 5; this discovery prompted the use, beginning in Version 6, of satellite- and gauge-based precipitation observations outside of North America [9]. Recently, a statistical analysis of the Tb O-F residuals revealed systematic errors in the “tau-omega” L-band radiative transfer model that converts the land-model simulated soil moisture and temperature into the forecast Tb prior to the L4_SM analysis. The L4_SM analysis is built on the ensemble Kalman filter and assumes unbiased forecast errors. The presence of systematic Tb forecast errors could thus adversely impact the quality of the analyzed soil moisture. In this paper, we examine the Tb O-F residuals of the latest Version 7 L4_SM data (Science Version ID Vv7030 and Vv7032) [10,11,12]. In the L4_SM Version 7 algorithm, key parameters of the L-band radiative transfer model, including soil roughness, scattering albedo, and a (seasonally varying) climatology of vegetation opacity, are obtained from the SMAP Level-2 Radiometer retrieval product (Version 5) [1]. Additionally, we also use ground measurements of surface soil moisture and soil temperature from the SMAP core validation sites as in situ reference of soil conditions [2,3]. As part of the L4_SM system calibration, the seasonally-varying bias between the model forecast Tb and the observed values is removed prior to the assimilation of the SMAP Tb observations [7]. That is, the L4_SM system is designed to only correct errors in synoptic-scale and interannual variations from the long-term mean seasonal cycle while maintaining the model’s (potentially erroneous) climatology. The Tb O-F residuals examined here are thus computed using SMAP Tb observations after they are rescaled to the mean seasonal cycle of Tb from the modeling system without SMAP data assimilation. Consequently, the long-term average of the Tb O-F residuals has a global mean of only 0.13 K and locally small values, ranging from -1 to 3 K. Despite the small time-average values of the Tb O-F residuals, the model forecast Tb was nevertheless found to exhibit undesirable systematic errors. At some locations, the time-average Tb O-F values strongly depend on surface soil moisture (SM). At the Yanco SMAP core validation site, for example, the Tb O-F residuals typically range from 5 to 15 K under dry soil moisture conditions (SM < 0.15 m3 m-3) yet are predominantly negative under wet soil moisture conditions (SM > 0.25 m3 m-3), with values ranging from 0 to -40 K. This results in soil moisture analysis increments that persistently make the soil drier under dry SM conditions and persistently make the soil wetter under wet SM conditions, suggesting an error in the dynamic range of the simulated Tb, soil moisture or soil temperature. In this paper, we describe the higher-order systematic Tb forecast errors in more detail, examine their impact on the L4_SM product quality, and explore potential avenues to further improve the L4_SM algorithm.

Rolf Reichle↗

A pilot modeling technique for handling-qualities research

A brief survey of the more dominant analysis techniques used in closed-loop handling-qualities research is presented. These techniques are shown to rely on so-called classical and modern analytical models of the human pilot which have their foundation in the analysis and design principles of feedback control. The optimal control model of the human pilot is discussed in some detail and a novel approach to the a priori selection of pertinent model parameters is discussed. Frequency domain and tracking performance data from 10 pilot-in-the-loop simulation experiments involving 3 different tasks are used to demonstrate the parameter selection technique. Finally, the utility of this modeling approach in handling-qualities research is discussed.

Hess, R. A.↗