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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.

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.

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 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.

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.

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.

The Mars Reconnaissance Orbiter (MRO) launched on August 12, 2005 and began aerobraking at Mars in March 2006. In order to save propellant, MRO used aerobraking to modify the initial orbit at Mars. The spacecraft passed through the atmosphere briefly on each orbit; during each pass the spacecraft was slowed by atmospheric drag, thus lowering the orbit apoapsis. The largest area on the spacecraft, most affected by aeroheating, was the solar arrays. A thermal analysis of the solar arrays was conducted at NASA Langley Research Center to simulate their performance throughout the entire roughly 6-month period of aerobraking. A companion paper describes the development of this thermal model. This model has been correlated against many sets of flight data. Several maneuvers were performed during the cruise to Mars, such as thruster calibrations, which involve large abrupt changes in the spacecraft orientation relative to the sun.

The Mars Reconnaissance Orbiter (MRO) launched on August 12, 2005 and started aerobraking at Mars in March 2006. During the spacecraft's design phase, thermal models of the solar panels and instruments were developed to determine which components would be the most limiting thermally during aerobraking. Having determined the most limiting components, (from a temperature limit standpoint), thermal limits in terms of heat rate were established. Advanced thermal modeling techniques were developed utilizing Thermal Desktop and Patran Thermal. Heat transfer coefficients were calculated using a Direct Simulation Monte Carlo technique. Analysis established that the solar panels were the most limiting components during the aerobraking phase of the mission.

To meet the challenge of future deep space programs an accurate and efficient engineering code for analyzing the shielding requirements against high-energy galactic heavy radiations is needed. Such engineering design codes require establishing validation processes using laboratory ion beams and space flight measurements in realistic geometries. In consequence, a new version of the HZETRN code capable of simulating HZE ions with either laboratory or space boundary conditions is currently under development. The new code, GRNTRN, is based on a Green's function approach to the solution of Boltzmann's transport equation and like its predecessor is deterministic in nature. Code validation in the laboratory environment is addressed by showing that GRNTRN accurately predicts energy loss spectra as measured by solid-state detectors in ion beam experiments.

On January 14, 2004 President George W Bush outlined a new vision for NASA that has humans venturing back to the moon by 2020. With this ambitious goal, new tools and models have been developed to help define and predict the amount of space radiation astronauts will be exposed to during transit and habitation on the moon. A representative scenario is used that includes a trajectory from LEO to a Lunar Base, and simplified CAD models for the transit and habitat structures. For this study galactic cosmic rays, solar proton events, and trapped electron and proton environments are simulated using new dynamic environment models to generate energetic electron, and light and heavy ion fluences. Detailed calculations are presented to assess the human exposure for transit segments and surface stays.

Meeting radiation protection requirements during EVA is predominantly an operational issue with some potential considerations for temporary shelter. The issue of spacesuit shielding is mainly guided by the potential of accidental exposure when operational and temporary shelter considerations fail to maintain exposures within operational limits. In this case, very high exposure levels are possible which could result in observable health effects and even be life threatening. Under these assumptions, potential spacesuit radiation exposures have been studied using known historical solar particle events to gain insight on the usefulness of modification of spacesuit design in which the control of skin exposure is a critical design issue and reduction of blood forming organ exposure is desirable.

This paper describes the effort and accomplishments for developing flexible fabrics with high thermal conductivity (FFHTC) for spacesuits to improve thermal performance, lower weight and reduce complexity. Commercial and additional space exploration applications that require substantial performance enhancements in removal and transport of heat away from equipment as well as from the human body can benefit from this technology. Improvements in thermal conductivity were achieved through the use of modified polymers containing thermally conductive additives. The objective of the FFHTC effort is to significantly improve the thermal conductivity of the liquid cooled ventilation garment by improving the thermal conductivity of the subcomponents (i.e., fabric and plastic tubes).

A new Green’s function code (GRNTRN) capable of simulating HZE ions with either laboratory or space boundary conditions is currently under development. The computational model consists of combinations of physical perturbation expansions based on the scales of atomic interaction, multiple scattering, and nuclear reactive processes with use of the Neumann-asymptotic expansions with non-perturbative corrections. The code contains energy loss due to straggling, nuclear attenuation, nuclear fragmentation with energy dispersion and downshifts. Recent publications have focused on code validation in the laboratory environment and have shown that the code predicts energy loss spectra accurately as measured by solid-state detectors in ion beam experiments. In this paper emphasis is placed on code validation with space boundary conditions.

A new method is developed for calculating the low energy neutron flux in a space environment which is protected from galactic cosmic rays (GCR) and solar particle events (SPE) by shielding materials. Our calculations are compared with low energy neutron flux flight data recorded on four different STS low earth orbit missions. We also compare our neutron flux calculations with the low energy neutron flux data recorded by MIR. The low energy neutron flux calculations can be described as a deterministic method for solving the Boltzmann equation for the light ion flux associated with a given environment. Existing Monte Carlo neutron flux simulations associated with the MIR and ISS space stations are also compared with our deterministic method for calculating neutron flux.