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Evaluating real-world hazards associated with perception subsystems is critical in enhancing the performance of autonomous vehicles. The reliability of autonomous vehicles perception subsystems are paramount for safe and efficient operation. While current studies employ different metrics to evaluate perception subsystem failures in autonomous vehicles, there still exists a gap in the development and emphasis on engineering requirements. To address this gap, this study proposes the establishment of engineering requirements that specifically target real-world hazards and resilience factors important to AV operation, using High-Definition Maps, Global Navigation Satellite System, and weather sensors. The findings include the need for engineering requirements to establish clear criteria for a high-definition maps functionality in the presence of erroneous perception subsystem inputs which enhances the overall safety and reliability of the autonomous vehicles.

The Current Icing Product (CIP; Bernstein et al. 2005) and Forecast Icing Product (FIP; Wolff et al. 2009) were originally developed by the United States’ National Center for Atmospheric Research (NCAR) under sponsorship of the Federal Aviation Administration (FAA) in the mid 2000’s and provide operational icing guidance to users through the NOAA Aviation Weather Center (AWC). The current operational version of FIP uses the Rapid Refresh (RAP; Benjamin et al. 2016) numerical weather prediction (NWP) model to provide hourly forecasts of Icing Probability, Icing Severity, and Supercooled Large Drop (SLD) Potential. Forecasts are provided out to 18 hours over the Contiguous United States (CONUS) at 15 flight levels between 1,000 ft and FL290, inclusive, and at a 13-km horizontal resolution.

Future compliance to FAA 14 CFR Part 25 and EASA CS-25 Appendix O conditions has required icing wind tunnels to expand their cloud simulation envelope, and demonstrate accurate calibration of liquid water content and droplet particle size distributions under these conditions. This has led to a renewed community interest in the accuracy of these calibrations, and the potential inter-facility bias due to the choice of instrumentation and processing methods. This article provides a comparison of the response of various hot-wire liquid water content instruments under Appendix C and supercooled large droplet conditions, after an independent similar analysis at other wind tunnel facilities. The instruments are being used, or are under consideration for use, by facilities collaborating in the ICE GENESIS program.

A new optical array imaging probe, called the 1D2D probe, has been developed by Science Engineering Associates, with features added to improve the real-time and post-analysis measurements of particle spectra, particularly in the Supercooled Large Droplet size range. The probe uses optical fibers and avalanche photodiodes to achieve a very high frequency response, and a Field-Programmable Gate Array that performs real-time particle rejection and processing of accepted particles with negligible inter-particle dead time. The probe records monochromatic two-dimensional images, while also recording the number of individual particle pixels at a second grey scale level. The probe implements flexible features to filter recording of highly out of focus particles to improve the accuracy of particle size determination, or to reject small particles to improve the statistics of measurements of larger particles.

Modern vehicles use automated driving assistance systems (ADAS) products to automate certain aspects of driving, which improves operational safety. In the U.S. in 2020, 38,824 fatalities occurred due to automotive accidents, and typically about 25% of these are associated with inclement weather. ADAS features have been shown to reduce potential collisions by up to 21%, thus reducing overall accidents. But ADAS typically utilize camera sensors that rely on lane visibility and the absence of obstructions in order to function, rendering them ineffective in inclement weather. To address this research gap, we propose a new technique to estimate snow coverage so that existing and new ADAS features can be used during inclement weather. In this study, we use a single camera sensor and historical weather data to estimate snow coverage on the road. Camera data was collected over 6 miles of arterial roadways in Kalamazoo, MI.

NASA and the FAA conducted two flight campaigns to quantify onboard weather radar measurements with in-situ measurements of high concentrations of ice crystals found in deep convective storms. The ultimate goal of this research was to improve the understanding of high ice water content (HIWC) and develop onboard weather radar processing techniques to detect regions of HIWC ahead of an aircraft to enable tactical avoidance of the potentially hazardous conditions. Both HIWC RADAR campaigns utilized the NASA DC-8 Airborne Science Laboratory equipped with a Honeywell RDR-4000 weather radar and in-situ microphysical instruments to characterize the ice crystal clouds. The purpose of this paper is to summarize how these campaigns were conducted and highlight key results. The first campaign was conducted in August 2015 with a base of operations in Ft. Lauderdale, Florida.

High Ice Water Content (HIWC) has been identified as a primary causal factor in numerous engine events over the past two decades. Previous attempts to develop a remote detection process utilizing modern commercial radars have failed to produce reliable results. This paper discusses the reasons for previous failures and describes a new technique that has shown very encouraging accuracy and range performance without the need for any modifications to industry’s current radar design(s). The performance of this new process was evaluated during the joint NASA/FAA HIWC RADAR II Flight Campaign in August of 2018. Results from that evaluation are discussed, along with the potential for commercial application, and development of minimum operational performance standards for future radar products.

In the last several years, the aviation industry has improved its understanding of jet engine events related to the ingestion of ice crystal particles. Ice crystal icing has caused powerloss and compressor damage events (henceforth referred to as “engine events”) during flights of large transport aircraft, commuter aircraft and business jets. A database has been created at Boeing to aid in analysis and study of these engine events. This paper will examine trends in the engine event database to better understand the weather which is associated with events. The event database will be evaluated for a number of criteria, such as the global location of the event, at what time of day the event occurred, in what season the event occurred, and whether there were local meteorological influences at play. A large proportion of the engine events occur in tropical convection over the ocean.

Advancements in numerical weather prediction (NWP) models continue to enhance the quality of in-flight icing forecasts and diagnoses. When diagnosing current in-flight icing conditions, observational datasets are combined with NWP model output to form a more accurate representation of those conditions. Surface observations are heavily relied upon to identify cloud coverage and cloud base height above observing stations. One of the major challenges of using these point-based or otherwise limited observations of cloud properties is extending the influence of the observation to nearby points on the model grid. An alternate solution to the current method for incorporating these point-based observations into the in-flight icing diagnoses was developed. The basis for the new method is rooted in a concept borrowed from signal and image processing known as dithering.

The National Aeronautics and Space Administration (NASA) is interested in characterizing the responses of THOR (test device for human occupant restraint) anthropometric test device (ATD) to representative loading acceleration pulse s. Test conditions were selected both for their applicability to anticipated NASA landing scenarios, and for comparison to human volunteer data previously collected by the United States Air Force (USAF). THOR impact testing was conducted in the fore-to-aft frontal (-x) and in the upward spinal (-z) directions with peak sled accelerations ranging from 8 to 12 G and rise times of 40, 70, and 100ms. Each test condition was paired with historical huma n data sets under similar test conditions that were also conducted on the Horizontal Impulse Accelerator (HIA). A correlation score was calculated for each THOR to human comparison using CORA (CORrelation and Analysis) software.

The objective of this work is to better understand freezing fog/drizzle conditions using observations collected during the Fog Remote Sensing and Modeling project (FRAM-S) that took place at St. John's International Airport, St. John's, NL, Canada. This location was ~1 km away from the Atlantic Ocean coast. During the project, the following measurements at one minute resolution were collected: precipitation rate (PR) and amount, fog/drizzle microphysics, 3D wind speed (Uh) and turbulence (Uh'), visibility (Vis), IR and SW radiative fluxes, temperature (T) and relative humidity (RH), and aerosol observations. The reflectivity and microphysical parameters obtained from the Metek Inc. MRR (Microwave Rain Radar) were also used in the analysis. The measurements were then used to obtain freezing fog/drizzle microphysical characteristics and their relation to visibility.

A large database is being created from icing flight programs completed by aircraft manufacturers for certification and by the NASA-Glenn Research Center for basic research. Although not yet complete, this database already provides an excellent opportunity to study aircraft icing conditions sampled in a wide variety of environments across eastern Canada and most of the United States, including Alaska. In this study, the focus is a comparison of conditions found within boundary-layer stratocumulus icing clouds over the Great Lakes, Pacific Northwest and Alaskan Interior. The clouds will be characterized in terms of temperature, liquid water content, median volumetric diameter, and drop concentration. Critical factors driving these parameters will be discussed.

In the continental United States east of the Rocky Mountains cold fronts are quite common in wintertime due to the many cyclones moving through this region, and icing conditions in the vicinity of cold fronts are a major contributor to the overall occurrence of icing in the atmosphere. The conditions examined in this study will be those behind the cold front. Icing there is often found in stratocumulus clouds that form due to destabilization of the boundary layer through cold air advection and an inversion formed by subsidence aloft which caps their growth. Moist adiabatic lapse rates, small drop sizes, high drop concentrations, and moderate to high liquid water contents depending on the cloud depth often characterize these clouds.

Cloud properties retrieved from satellite data are used to diagnose aircraft icing threat in single layer and multilayered ice-over-liquid clouds. The algorithms are being applied in real time to the Geostationary Operational Environmental Satellite (GOES) data over the CONUS with multilayer data available over the eastern CONUS. METEOSAT data are also used to retrieve icing conditions over western Europe. The icing algorithm's methodology and validation are discussed along with future enhancements and plans. The icing risk product is available in image and digital formats on NASA Langley ‘s Cloud and Radiation Products web site, http://www-angler.larc.nasa.gov.

This study presents an evaluation of in-flight icing severity forecasts produced for the eastern United States for the winter 09/10 using the German ADWICE icing forecasting system. An instance of the underlying COSMO-EU 7km model was run over the eastern CONUS to produce four months worth of NWP data for the ADWICE algorithm. The generated icing fields were then verified using pilot reports (PIREPS) as “truth” data. In order to be able to characterize ADWICE performance over this non-native domain against a known quantity for this part of the world, a comparative verification was performed with the American FIP icing product over 1.5 months of data, using a unified set of observation PIREPS and forecast times. Subsequently, ADWICE forecasts were verified over the whole time period and analyzed with respect to seasonal, regional or altitude variations.

An experimental research effort was begun to develop a database of airplane aerodynamic characteristics with simulated ice accretion over a large range of incidence and sideslip angles. Wind-tunnel testing was performed at the NASA Langley 12-ft Low-Speed Wind Tunnel using a 3.5% scale model of the NASA Langley Generic Transport Model. Aerodynamic data were acquired from a six-component force and moment balance in static-model sweeps from α = -5 to 85 deg. and β = -45 to 45 deg. at a Reynolds number of 0.24x10⁶ and Mach number of 0.06. The 3.5% scale GTM was tested in both the clean configuration and with full-span artificial ice shapes attached to the leading edges of the wing, horizontal and vertical tail. Aerodynamic results for the clean airplane configuration compared favorably with similar experiments carried out on a 5.5% scale GTM.

The Current Icing Product (CIP) provides an hourly diagnosis of the severity of icing occurring based on multiple data sources. Pilot reports (PIREPs) and surface observations (METARs), as well as satellite, numerical weather prediction (NWP) model, radar, and lightning data are all utilized within the algorithm. The accurate identification of cloud base is a large factor in the algorithm's determination of icing severity. Current methods employ the METAR observation of ceiling to identify the cloud base over a specified area within the CIP domain. The temperature from the Rapid Update Cycle (RUC) NWP model at the height of the observed METAR ceiling can be utilized as a proxy for the amount of condensate in the cloud. The likelihood of a large amount of condensate in the identified cloud increases with increasing cloud base temperature. As the amount of liquid water diagnosed by CIP severity increases, so does the estimated icing severity.

Solar proton events (SPEs) represent the single-most significant source of acute radiation exposure during space missions. Historically, an exponential in rigidity (particle momentum) fit has been used to express the SPE energy spectrum using GOES data up to 100 MeV. More recently, researchers have found that a Weibull fit better represents the energy spectrum up to 1000 MeV (1 GeV). In addition, the availability of SPE data extending up to several GeV has been incorporated in analyses to obtain a more complete and accurate energy spectrum representation. In this paper we discuss the major SPEs that have occurred over the past five solar cycles (~50+ years) in detail - in particular, Aug 1972 and Sept & Oct 1989 SPEs. Using a high-energy particle transport/dose code, radiation exposure estimates are presented for various thicknesses of aluminum. The effects on humans and spacecraft systems are also discussed in detail.

Recently a new emphasis has been placed on engineering applications of space radiation analyses and thus a systematic effort of Verification, Validation and Uncertainty Quantification (VV&UQ) of the tools commonly used for radiation analysis for vehicle design and mission planning has begun. There are two sources of uncertainty in geometric discretization addressed in this paper that need to be quantified in order to understand the total uncertainty in estimating space radiation exposures. One source of uncertainty is in ray tracing, as the number of rays increase the associated uncertainty decreases, but the computational expense increases. Thus, a cost benefit analysis optimizing computational time versus uncertainty is needed and is addressed in this paper. The second source of uncertainty results from the interpolation over the dose vs. depth curves that is needed to determine the radiation exposure.

Not only is the common dream of frequent personal flight travel going unfulfilled, the current generation of General Aviation (GA) is facing tremendous challenges that threaten to relegate the Single Engine Piston (SEP) aircraft market to a footnote in the history of U.S. aviation. A case is made that this crisis stems from a generally low utility coupled to a high cost that makes the SEP aircraft of relatively low transportation value and beyond the means of many. The roots of this low value are examined in a broad sense, and a Next Generation NASA Advanced GA Concept is presented that attacks those elements addressable by synergistic aircraft design.