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A research program was conducted to evaluate the effectiveness of icing tunnel hybrid model design. A hybrid design is where the full-scale leading edge of a wing section is maintained only to a certain percentage of the local chord, while the aft section of the model is redesigned into a shortened or truncated planform. An initial study was conducted in 2020 where the ice shape geometries on a full-chord length version of the swept CRM65 wing model were compared to those from the hybrid version of CRM65 that were obtained in the NASA Icing Research Tunnel in 2015. The results were reported in a 2021 paper. For most test conditions, the overall size and shape of the ice shapes compared well. However, the ice shapes from the full-chord model were generally slightly smaller than those from the hybrid model.

Modifications have been implemented in the GlennICE software to accommodate a non-inertial reference frame. GlennICE accepts a flow solution from an external flow solver. It then introduces particles and tracks them through the flow field in a Lagrangian manner. Centrifugal and Coriolis terms were added to the GlennICE software to account for relative frame simulations. The objective of the present paper is twofold. First, to check that the new terms are implemented correctly and that the code still behaves as expected with respect to convergence. And second, to provide some initial insight into an upcoming propeller experiment in the NASA Icing Research Tunnel. The paper presents a description of the code modifications. In addition, results are presented for two operating conditions, and three particle sizes. Each case was simulated with four different grid densities to assess grid dependence.

The Icing Research Tunnel at NASA Glenn follows the recommended practice for calibration outlined in SAE’s ARP5905. The calibration team has followed the schedule of a full calibration every five years with a check calibration done every six months following. The liquid water content of the IRT has maintained stability within the stated specifications of variation within +/- 10% of the curve fit equation generated from calibration data. Using past measurements and data trends, IRT characterization engineers wanted to develop methods for the ability to know when data were not within variation. Trends can be observed in the liquid water content measurement process by constructing statistical process control charts. This paper describes data processing procedures for the Multi-Element Sensor in the IRT, including collision efficiency corrections, canonical correlation analysis, process for rejection of data, and construction of control charts.

When examining the literature on the adhesion strength of impact ice, there have been a wide range of methodologies tried to measure the required stresses to induce interfacial delamination. Utilizing the Icing Research Tunnel at the NASA Glenn Research Center to generate the impact ice required for this work, several different mechanical tests have been and are being developed to determine the stresses along the interface between ice and coupon. This set of tests includes the technical mature modified lap joint test which has been used to conduct ice adhesion studies through a wide sweep of icing conditions. To conduct in situ ice adhesion measurements inside of the Icing Research Tunnel, several new experiments are currently being developed to make ice adhesion measurements during and immediately after ice accretion.

A process of using machine learning to segment impact ice microstructure is presented and analyzed. The microstructure of impact ice has been shown to correlate with the adhesion strength of ice. Machine vision techniques are explored as a method of decreasing analysis time. The segmentation was conducted with the goal of obtaining average grain size estimations. The model was trained on a set of micrographs of impact ice grown at NASA Glenn’s Icing Research Tunnel. The model leveraged a model pre-trained on a large set of micrographs of various materials as a starting point. Post-processing of the segmented images was done to connect broken boundaries. An automatic method of determining grain size following an ASTM standard was implemented. Segmentation results using different training sets as well as different encoder and decoder pairs are presented. Calculated sizes are compared to manual grain size measurement methods.

Numerical solutions have been generated which simulate flow inside an aircraft engine flying at altitude through an ice crystal cloud. The geometry used for this study is the Honeywell Uncertified Research Engine (HURE) which was recently tested in the NASA Propulsion Systems Laboratory (PSL) in January 2018. The simulations were carried out at predicted operating points with a potential risk of ice accretion. The extent of the simulation is from upstream of the engine inlet to downstream past the strut in the core and bypass. The flow solution is produced using GlennHT, a NASA in-house code. A mixing plane approximation is used upstream and downstream of the fan. The use of the mixing plane allows for steady state solutions in the relative frame. The flow solution is then passed on to LEWICE3D for particle trajectory, impact and breakup prediction. The LEWICE3D code also uses a mixing plane approximation at the boundaries upstream and downstream of the fan.

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.

Artificial ice shapes of various geometric fidelity were tested on a wing model based on the Common Research Model. Low Reynolds number tests were conducted at Wichita State University’s Walter H. Beech Memorial Wind Tunnel utilizing an 8.9% scale model, and high Reynolds number tests were conducted at ONERA’s F1 wind tunnel utilizing a 13.3% scale model. Several identical geometrically-scaled ice shapes were tested at both facilities, and the results were compared at overlapping Reynolds and Mach numbers. This was to ensure that the results and trends observed at low Reynolds number could be applied and continued to high, near-flight Reynolds number. The data from Wichita State University and ONERA F1 agreed well at matched Reynolds and Mach numbers. The lift and pitching moment curves agreed very well for most configurations.

Understanding the aerodynamic impact of swept-wing ice accretions is a crucial component of the design of modern aircraft. Computer-simulation tools are commonly used to approximate ice shapes, so the necessary level of detail or fidelity of those simulated ice shapes must be understood relative to high-fidelity representations of the ice. Previous tests were performed in the NASA Icing Research Tunnel to acquire high-fidelity ice shapes. From this database, full-span artificial ice shapes were designed and manufactured for both an 8.9%-scale and 13.3%-scale semispan wing model of the CRM65 which has been established as the full-scale baseline for this swept-wing project. These models were tested in the Walter H. Beech wind tunnel at Wichita State University and at the ONERA F1 facility, respectively. The data collected in the Wichita St.

The influence of freestream static temperature on roughness temporal evolution and spatial variation was investigated in the Icing Research Tunnel (IRT) at NASA Glenn Research Center. A 53.34 cm (21-in.) NACA 0012 airfoil model and a 152.4 cm (60-in.) HAARP-II business jet airfoil model were exposed to Appendix C clouds for fixed exposure times and thus fixed ice accumulation parameter. For the base conditions, the static temperature was varied to produce different stagnation point freezing fractions. The resulting ice shapes were then scanned using a ROMER Absolute Arm system and analyzed using the self-organizing map approach of McClain and Kreeger. The ice accretion prediction program LEWICE was further used to aid in interrogations of the ice accretion point clouds by using the predicted surface variations of local collection efficiency.

This paper introduces a data driven model for predicting airport arrival capacity with 2-8 hour look-ahead forecast data. The model is suitable for air traffic flow management by explicitly investigating the impact of convective weather on airport arrival meter fix throughput. Estimation of the arrival airport capacity under arrival meter fix flow constraints due to severe weather is an important part of Air Traffic Management (ATM). Airport arrival capacity can be reduced if one or more airport arrival meter fixes are partially or completely blocked by convective weather. When the predicted airport arrival demands exceed the predicted available airport’s arrival capacity for a sustained period, Ground Delay Program (GDP) operations will be triggered by ATM system.

The blade crossing event of a coaxial counter-rotating rotor is a potential source of noise and impulsive blade loads. Blade crossings occur many times during each rotor revolution. In previous research by the authors, this phenomenon was analyzed by simulating two airfoils passing each other at specified speeds and vertical separation distances, using the compressible Navier-Stokes solver OVERFLOW. The simulations explored mutual aerodynamic interactions associated with thickness, circulation, and compressibility effects. Results revealed the complex nature of the aerodynamic impulses generated by upper/lower airfoil interactions. In this paper, the coaxial rotor system is simulated using two trains of airfoils, vertically offset, and traveling in opposite directions. The simulation represents multiple blade crossings in a rotor revolution by specifying horizontal distances between each airfoil in the train based on the circumferential distance between blade tips.

Many studies have been performed to quantify the formation and evolution of roughness on ice shapes created in Appendix C icing conditions, which exhibits supercooled liquid droplets ranging from 1-50 µm. For example Anderson and Shin (1997), Anderson et al. (1998), and Shin (1994) represent early studies of ice roughness during short-duration icing events measured in the Icing Research Tunnel at the NASA Glenn Research Center. In the historical literature, image analysis techniques were employed to characterize the roughness. Using multiple images of the roughness elements, these studies of roughness focused on extracting parametric representations of ice roughness elements. While the image analysis approach enabled many insights into icing physics, recent improvements in laser scanning approaches have revolutionized the process of ice accretion shape characterization.

When the demand for either a region of airspace or an airport approaches or exceeds the available capacity, miles-in-trail (MIT) restrictions are the most frequently issued traffic management initiatives (TMIs) that are used to mitigate these imbalances. Miles-in-trail operations require aircraft in a traffic stream to meet a specific inter-aircraft separation in exchange for maintaining a safe and orderly flow within the stream. This stream of aircraft can be departing an airport, over a common fix, through a sector, on a specific route or arriving at an airport. This study begins by providing a high-level overview of the distribution and causes of arrival MIT restrictions for the top ten airports in the United States. This is followed by an in-depth analysis of the frequency, duration and cause of MIT restrictions impacting the Hartsfield-Jackson Atlanta International Airport (ATL) from 2009 through 2011.

The term Integrated Vehicle Health Management (IVHM) describes a set of capabilities that enable sustainable and safe operation of components and subsystems within aerospace platforms. However, very little guidance exists for the systems engineering aspects of design with IVHM in mind. It is probably because of this that designers have to use knowledge picked up exclusively by experience rather than by established process. This motivated a group of leading IVHM practitioners within the aerospace industry under the aegis of SAE's HM-1 technical committee to author a document that hopes to give working engineers and program managers clear guidance on all the elements of IVHM that they need to consider before designing a system. This proposed recommended practice (ARP6883 [1]) will describe all the steps of requirements generation and management as it applies to IVHM systems, and demonstrate these with a “real-world” example related to designing a landing gear system.

A review of the research accomplished in 2009 in the System-Level Design, Analysis and Simulation Tools (SLDAST) of the NASA's Airspace Systems Program is presented. This research thrust focuses on the integrated system-level assessment of component level innovations, concepts and technologies of the Next Generation Air Traffic System (NextGen) under research in the ASP program to enable the development of revolutionary improvements and modernization of the National Airspace System. The review includes the accomplishments on baseline research and the advancements on design studies and system-level assessment, including the cluster analysis as an annualization standard of the air traffic in the U.S. National Airspace, and the ACES-Air MIDAS integration for human-in-the-loop analyzes within the NAS air traffic simulation.

From November 2010 until May of 2011, NASA's Icing Remote Sensing System was positioned at Platteville, Colorado between the National Science Foundation's S-Pol radar and Colorado State University's CHILL radar (collectively known as FRONT, or ‘Front Range Observational Network Testbed’). This location was also underneath the flight-path of aircraft arriving and departing from Denver's International Airport, which allowed for comparison to pilot reports of in-flight icing. This work outlines how the NASA Icing Remote Sensing System's derived liquid water content and in-flight icing hazard profiles can be used to provide in-flight icing verification and validation during icing and non-icing scenarios with the purpose of comparing these times to profiles of polarized moment data from the two nearby research radars.

Ice accretions that have formed inside gas turbine engines as a result of flight in clouds of high concentrations of ice crystals in the atmosphere have recently been identified as an aviation safety hazard. NASA's Aviation Safety Program (AvSP) has made plans to conduct research in this area to address the hazard. This paper gives an overview of NASA's engine ice-crystal icing research project plans. Included are the rationale, approach, and details of various aspects of NASA's research.

JSC-1A lunar simulant has been applied to AZ93 and AgFEP thermal control surfaces on aluminum substrates in a simulated lunar environment. The temperature of these surfaces was monitored as they were heated with a solar simulator using varying angles of incidence and cooled in a 30 K coldbox. Thermal modeling was used to determine the solar absorptivity (a) and infrared emissivity (e) of the thermal control surfaces in both their clean and dusted states. It was found that even a sub-monolayer of dust can significantly raise the α of either type of surface. A full monolayer can increase the α/ε ratio by a factor of 3–4 over a clean surface. Little angular dependence of the α of pristine thermal control surfaces for both AZ93 and AgFEP was observed, at least until 30° from the surface. The dusted surfaces showed the most angular dependence of α when the incidence angle was in the range of 25° to 35°.