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Develop advanced nonlinear signal analysis topographical mapping system

The SSME has been undergoing extensive flight certification and developmental testing, which involves some 250 health monitoring measurements. Under the severe temperature pressure, and dynamic environments sustained during operation, numerous major component failures have occurred, resulting in extensive engine hardware damage and scheduling losses. To enhance SSME safety and reliability, detailed analysis and evaluation of the measurements signal are mandatory to assess its dynamic characteristics and operational condition. Efficient and reliable signal detection techniques will reduce catastrophic system failure risks and expedite the evaluation of both flight and ground test data, and thereby reduce launch turn-around time. The basic objective of this contract are threefold: (1) Develop and validate a hierarchy of innovative signal analysis techniques for nonlinear and nonstationary time-frequency analysis. Performance evaluation will be carried out through detailed analysis of extensive SSME static firing and flight data. These techniques will be incorporated into a fully automated system. (2) Develop an advanced nonlinear signal analysis topographical mapping system (ATMS) to generate a Compressed SSME TOPO Data Base (CSTDB). This ATMS system will convert tremendous amounts of complex vibration signals from the entire SSME test history into a bank of succinct image-like patterns while retaining all respective phase information. A high compression ratio can be achieved to allow the minimal storage requirement, while providing fast signature retrieval, pattern comparison, and identification capabilities. (3) Integrate the nonlinear correlation techniques into the CSTDB data base with compatible TOPO input data format. Such integrated ATMS system will provide the large test archives necessary for a quick signature comparison. This study will provide timely assessment of SSME component operational status, identify probable causes of malfunction, and indicate feasible engineering solutions. The final result of this program will yield an ATMS system of nonlinear and nonstationary spectral analysis software package integrated with the Compressed SSME TOPO Data Base (CSTDB) on the same platform. This system will allow NASA engineers to retrieve any unique defect signatures and trends associated with different failure modes and anomalous phenomena over the entire SSME test history across turbo pump families.

Jong, Jen-Yi↗

Acquisition and use of Orlando, Florida and Continental Airbus radar flight test data

Westinghouse is developing a lookdown pulse Doppler radar for production as the sensor and processor of a forward looking hazardous windshear detection and avoidance system. A data collection prototype of that product was ready for flight testing in Orlando to encounter low level windshear in corroboration with the FAA-Terminal Doppler Weather Radar (TDWR). Airborne real-time processing and display of the hazard factor were demonstrated with TDWR facilitated intercepts and penetrations of over 80 microbursts in a three day period, including microbursts with hazard factors in excess of .16 (with 500 ft. PIREP altitude loss) and the hazard factor display at 6 n.mi. of a visually transparent ('dry') microburst with TDWR corroborated outflow reflectivities of +5 dBz. Range gated Doppler spectrum data was recorded for subsequent development and refinement of hazard factor detection and urban clutter rejection algorithms. Following Orlando, the data collection radar was supplemental type certified for in revenue service on a Continental Airlines Airbus in an automatic and non-interferring basis with its ARINC 708 radar to allow Westinghouse to confirm its understanding of commercial aircraft installation, interface realities, and urban airport clutter. A number of software upgrades, all of which were verified at the Receiver-Transmitter-Processor (RTP) hardware bench with Orlando microburst data to produce desired advanced warning hazard factor detection, included some preliminary loads with automatic (sliding window average hazard factor) detection and annunciation recording. The current (14-APR-92) configured software is free from false and/or nuisance alerts (CAUTIONS, WARNINGS, etc.) for all take-off and landing approaches, under 2500 ft. altitude to weight-on-wheels, into all encountered airports, including Newark (NJ), LAX, Denver, Houston, Cleveland, etc. Using the Orlando data collected on hazardous microbursts, Westinghouse has developed a lookdown pulse Doppler radar product with signal and data processing algorithms which detect realistic microburst hazards and has demonstrated those algorithms produce no false alerts (or nuisance alerts) in urban airport ground moving vehicle (GMTI) and/or clutter environments.

Eide, Michael C.↗

An approach to the design and implementation of spacecraft attitude control systems

Over 39 years and a long list of missions, the guidance, navigation, and control (GN&C) groups at the Goddard Space Flight Center have gradually developed approaches to the design and implementation of successful spacecraft attitude control systems. With the recent creation of the Guidance, Navigation, and Control Center at Goddard, there is a desire to document some of these design practices to help to ensure their consistent application in the future. In this paper, we will discuss the beginnings of this effort, drawing primarily on the experience of one of the past attitude control system (ACS) groups at Goddard (what was formerly known as Code 712, the Guidance, Navigation, and Control Branch). We will discuss the analysis and design methods and criteria used, including guidelines for linear and nonlinear analysis, as well as the use of low- and high-fidelity simulation for system design and verification of performance. Descriptions of typical ACS sensor and actuator hardware will be shown, and typical sensor/actuator suites for a variety of mission types detailed. A description of the software and hardware test effort will be given, along with an attempt to make some qualitative estimates on how much effort is involved. The spacecraft and GN&C subsystem review cycles will be discussed, giving an outline of what design reviews are typically held and what information should be presented at each stage. Finally, we will point out some of the lessons learned at Goddard.

ODonnell, James R., Jr.↗

An Approach to the Design and Implementation of Spacecraft Attitude Control Systems

Over 39 years and a long list of missions, the guidance, navigation, and control (GN&C) groups at the Goddard Space Flight Center have gradually developed approaches to the design and implementation of successful spacecraft attitude control systems. With the recent creation of the Guidance, Navigation, and Control Center at Goddard, there is a desire to document some of these design practices to help to ensure their consistent application in the future. In this paper, we will discuss the beginnings of this effort, drawing primarily on the experience of one of the past attitude control system (ACS) groups at Goddard (what was formerly known as Code 712, the Guidance, Navigation, and Control Branch). We will discuss the analysis and design methods and criteria used, including guidelines for linear and nonlinear analysis, as well as the use of low- and high-fidelity simulation for system design and verification of performance. Descriptions of typical ACS sensor and actuator hardware will be shown, and typical sensor/actuator suites for a variety of mission types detailed. A description of the software and hardware test effort will be given, along with an attempt to make some qualitative estimates on how much effort is involved. The spacecraft and GN&C subsystem review cycles will be discussed, giving an outline of what design reviews are typically held and .what information should be presented at each stage. Finally, we will point out some of the lessons learned at Goddard.

ODonnell, James R., Jr.↗

Development of Advanced Verification and Validation Procedures and Tools for the Certification of Learning Systems in Aerospace Applications

Adaptive control technologies that incorporate learning algorithms have been proposed to enable automatic flight control and vehicle recovery, autonomous flight, and to maintain vehicle performance in the face of unknown, changing, or poorly defined operating environments. In order for adaptive control systems to be used in safety-critical aerospace applications, they must be proven to be highly safe and reliable. Rigorous methods for adaptive software verification and validation must be developed to ensure that control system software failures will not occur. Of central importance in this regard is the need to establish reliable methods that guarantee convergent learning, rapid convergence (learning) rate, and algorithm stability. This paper presents the major problems of adaptive control systems that use learning to improve performance. The paper then presents the major procedures and tools presently developed or currently being developed to enable the verification, validation, and ultimate certification of these adaptive control systems. These technologies include the application of automated program analysis methods, techniques to improve the learning process, analytical methods to verify stability, methods to automatically synthesize code, simulation and test methods, and tools to provide on-line software assurance.

Jacklin, Stephen↗

In-Depth Modeling and Simulation Analysis of Artemis Missions Using the Impact Probabilistic Risk Assessment Tool

BACKGROUND The Artemis campaign is a Moon exploration program with a series of six planned missions, five of which will be crewed. These five crewed missions will contain a single mission segment (space flight), or multiple mission segments involving space flight (Orion), lunar landing (LTV) and/or space habitat (Gateway). Each crewed segment faces the risk of unique medical conditions, necessitating medical sets/kits tailored to those specificities. To support and enable a data-driven and evidence-based decision-making process through out a mission’s life cycle, a software tool called IMPACT was developed. Using probabilistic risk assessment (PRA) methodologies, IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces) is a novel tool built for analyzing the possibility of encountering complex medical risks during space flight, and for identifying the medical resources and capabilities needed to treat those potential at-risk medical conditions. IMPACT achieves this by performing hundreds of thousands of Monte Carlo simulations of missions to build aggregate pictures of medical risk. During an extended simulation modeling phase, IMPACT generated analytical results for medical risks, and the medical resources and capabilities to address those risks, for every segment of every crewed Artemis mission. This presentation will highlight the reliability, consistency and validity of IMPACT’s computational modeling techniques and will showcase the library of analytical outcomes generated for the Artemis missions. OVERVIEW During the early stages of IMPACT’s design, architecture and technical requirements collection, “scenarios” (use cases) - achievement goals required for acceptance testing, were identified by stakeholders. IMPACT successfully completed the scenario testing requirements and undertook an extensive operational run phase utilizing a wide range of input combinations with a goal of delivering a cohesive, trustworthy, reliable, vast, and diverse body of evidence. The intent of these modeling runs was to validate consistency in output, ensure solidity of executable operations and to streamline processes by identifying areas requiring efficiency improvements. Using the many missions of Artemis, IMPACT ran variations of operational runs to assess the output for acceptable, as well as unusual characteristics. This rigorous long-term “shakedown” analysis was implemented to help build a collective body of evidence to aid in securing a high level of confidence, reliability, and validity in the output, whether from the applicational components of IMPACT, or the entirety of the operational process. ANTICIPATED ANALYSIS AND CONCLUSION This presentation will discuss the various categories of input criteria; the comparisons in the application of these input criteria to various Artemis missions; the preparation and collection of the body of evidence, and reliability of the computational modeling techniques. This paper serves as an initial analytical overview of IMPACT’s probabilistic risk assessment (PRA) medical risk outputs covering Artemis missions and is not intended to be deemed the official medical response for the Artemis campaign.

Crew Composition↗

California coast nearshore processes study

The author has identified the following significant results. Remote sensor aircraft flights took place simultaneously with ERTS-1 overpasses at the San Francisco, Monterey Bay, and Santa Barbara test cells. The cameras and scanners used were configured for detecting suspended sediment and for maximum water penetration. The Ektachrome/Wratten 12 photographs which were intentionally overexposed 1-1/2 stops were found to show the most extensive sediment transport detail. Minus blue/K 2 photographs illustrate nearshore underwater bottom detail including the head of the Mugu submarine canyon. The EMSIDE 9 channel scanner was employed to classify and differentiate suspended sediment, oil, kelp, and other materials found in the nearshore area. Processing of bulk ERTS-1 computer compatible tapes was utilized to enhance and analyze nearshore sediments. This technique was most successful in enhancing subtle nearshore features found to be faint or invisible on prints made from the supplied negatives. In addition to this continuing computer process, an effort was initiated to interface density values from the bulk tapes into contouring and mapping software.

Pirie, D. M.↗

Comparisons of Kinematics and Dynamics Simulation Software Tools

Kinematic and dynamic analyses for moving bodies are essential to system engineers and designers in the process of design and validations. 3D visualization and motion simulation plus finite element analysis (FEA) give engineers a better way to present ideas and results. Marshall Space Flight Center (MSFC) system engineering researchers are currently using IGRIP from DELMIA Inc. as a kinematic simulation tool for discrete bodies motion simulations. Although IGRIP is an excellent tool for kinematic simulation with some dynamic analysis capabilities in robotic control, explorations of other alternatives with more powerful dynamic analysis and FEA capabilities are necessary. Kinematics analysis will only examine the displacement, velocity, and acceleration of the mechanism without considering effects from masses of components. With dynamic analysis and FEA, effects such as the forces or torques at the joint due to mass and inertia of components can be identified. With keen market competition, ALGOR Mechanical Event Simulation (MES), MSC visualNastran 4D, Unigraphics Motion+, and Pro/MECHANICA were chosen for explorations. In this study, comparisons between software tools were presented in terms of following categories: graphical user interface (GUI), import capability, tutorial availability, ease of use, kinematic simulation capability, dynamic simulation capability, FEA capability, graphical output, technical support, and cost. Propulsion Test Article (PTA) with Fastrac engine model exported from IGRIP and an office chair mechanism were used as examples for simulations.

Yeu-Sheng Paul Shiue↗

Java Architecture for Detect and Avoid Extensibility and Modeling

Unmanned aircraft will equip with a detect-and-avoid (DAA) system that enables them to comply with the requirement to "see and avoid" other aircraft, an important layer in the overall set of procedural, strategic and tactical separation methods designed to prevent mid-air collisions. This paper describes a capability called Java Architecture for Detect and Avoid Extensibility and Modeling (JADEM), developed to prototype and help evaluate various DAA technological requirements by providing a flexible and extensible software platform that models all major detect-and-avoid functions. Figure 1 illustrates JADEM's architecture. The surveillance module can be actual equipment on the unmanned aircraft or simulators that model the process by which sensors on-board detect other aircraft and provide track data to the traffic display. The track evaluation function evaluates each detected aircraft and decides whether to provide an alert to the pilot and its severity. Guidance is a combination of intruder track information, alerting, and avoidance/advisory algorithms behind the tools shown on the traffic display to aid the pilot in determining a maneuver to avoid a loss of well clear. All these functions are designed with a common interface and configurable implementation, which is critical in exploring DAA requirements. To date, JADEM has been utilized in three computer simulations of the National Airspace System, three pilot-in-the-loop experiments using a total of 37 professional UAS pilots, and two flight tests using NASA's Predator-B unmanned aircraft, named Ikhana. The data collected has directly informed the quantitative separation standard for "well clear", safety case, requirements development, and the operational environment for the DAA minimum operational performance standards. This work was performed by the Separation Assurance/Sense and Avoid Interoperability team under NASA's UAS Integration in the NAS project.

unmanned aircraft systems↗

Surface and Airborne Monitoring Technology for Detecting Geologic Leakage in a CO 2 -Enhanced Oil Recovery Pilot, Anadarko Basin, Texas

Surface and airborne gas monitoring programs are becoming an important part of environmental protection in areas favorable for subsurface storage of carbon dioxide. Understanding structural architecture and its effects on the flux of fluids, specifically CO 2 and CH 4 , in the shallow subsurface and atmosphere is helping design and implement next generation monitoring technologies, including unmanned aerial vehicles (UAVs). An important aspect of this research is using subsurface fracture data to inform the design of flight pathways for UAVs in the Farnsworth Oil Unit of the Anadarko Basin. The target zone for CO 2 storage and enhanced oil recovery in the Farnsworth Oil Unit is in the upper Morrow sandstone at subsurface depths greater than 2,000 m. Field study reveals that sandstone and chert in the High Plains Aquifer contain numerous joints that provide crucial insight into aquifer architecture and subsurface flow pathways. Properties of more than 1,700 joints were measured in the field and in high-resolution satellite images. Two distinctive joint systems interpreted as a conjugate pair were identified in the study area. Joint spacing follows a log-normal statistical scaling rule. These fractures appear to be the product of an E-NE regional compressive stress and may have a significant effect on flow in the High Plains Aquifer system. Based on the results of this research, design of UAV flight paths should be oblique to fractures in a way that maximizes the likelihood of CO 2 and CH 4 flux from of systematic joints and cross joints. Detection of leaks either from subsurface seal failures or surface equipment problems is important to insure that stored CO 2 is not being lost to the atmosphere. In the case of surface leaks, costs go up and injection efficiency goes down. Surface leaks are often short term caused by seal leaks, pop off valves, or other equipment failure modes. In either case, CO 2 is released to the atmosphere. This projects primary goal was to explore the use of low cost sensors coupled with the appropriate hardware and software to produce a low cost system capable of detecting both long and short term leaks. In addition, an aerial system was designed to measure the CO 2 and CH 4 distributions above the surface. Both the ground and UAV based systems were designed, tested and deployed in the Farnsworth field.

02 PETROLEUM↗

Software breadboard study

The overall goal of this study was to develop new concepts and technology for the Comet Rendezvous Asteroid Flyby (CRAF), Cassini, and other future deep space missions which maximally conform to the Functional Specification for the NASA X-Band Transponder (NXT), FM513778 (preliminary, revised July 26, 1988). The study is composed of two tasks. The first task was to investigate a new digital signal processing technique which involves the processing of 1-bit samples and has the potential for significant size, mass, power, and electrical performance improvements over conventional analog approaches. The entire X-band receiver tracking loop was simulated on a digital computer using a high-level programming language. Simulations on this 'software breadboard' showed the technique to be well-behaved and a good approximation to its analog predecessor from threshold to strong signal levels in terms of tracking-loop performance, command signal-to-noise ratio and ranging signal-to-noise ratio. The successful completion of this task paves the way for building a hardware breadboard, the recommended next step in confirming this approach is ready for incorporation into flight hardware. The second task in this study was to investigate another technique which provides considerable simplification in the synthesis of the receiver first LO over conventional phase-locked multiplier schemes and in this approach, provides down-conversion for an S-band emergency receive mode without the need of an additional LO. The objective of this study was to develop methodology and models to predict the conversion loss, input RF bandwidth, and output RF bandwidth of a series GaAs FET sampling mixer and to breadboard and test a circuit design suitable for the X and S-band down-conversion applications.

Nuckolls, C.↗

Mars 2020 Entry, Descent, and Landing System Software Implementation

On February 18th, 2021, the Mars 2020 project's Perseverance Rover successfully touched down on the Martian surface after nearly eight years of development. The Mars 2020 Entry, Descent, and Landing (EDL) System largely leveraged heritage from the Mars Science Laboratory (MSL) EDL System while employing targeted technological advancements. The landing process is autonomously directed by a software behavior implemented in the rover's primary flight computer called the EDL Timeline that assumes control of the vehicle six days before atmospheric entry. This paper first walks through the basics of the EDL Timeline mechanics and how the behavior is designed to account for internal system variations and environmental unknowns. It then summarizes the interactions between the EDL timeline and other high-level system behaviors like spacecraft mode transitions and system fault protection, focusing on the complications that arise when passing spacecraft control between executive functions. Although the MSL-inherited EDL System is reliable and capable, targeted updates and a thorough verification and validation program were required for Mars 2020. This paper discusses changes made to close vulnerabilities discovered during both MSL and Mars 2020 development cycles, landing system capability enhancements that were enabling for Mars 2020's mission, and how these updates were integrated with the heritage system. It then describes how both analysis and testing campaigns were utilized to verify and validate all aspects of EDL and system behaviors that run during the six days before landing, as well as the operational workarounds that were needed to address problems found during the development and commissioning process. Finally, this paper imparts lessons learned from Mars 2020 EDL development, implementation, and operations, emphasizing how systems designed to conduct time-critical mission events with low margin of error can be improved in the future.

Stehura, Aaron↗

Human Thermal Model Evaluation Using the JSC Human Thermal Database

The human thermal database developed at the Johnson Space Center (JSC) is used to evaluate a set of widely used human thermal models. This database will facilitate a more accurate evaluation of human thermoregulatory response using in a variety of situations, including those situations that might otherwise prove too dangerous for actual testing--such as extreme hot or cold splashdown conditions. This set includes the Wissler human thermal model, a model that has been widely used to predict the human thermoregulatory response to a variety of cold and hot environments. These models are statistically compared to the current database, which contains experiments of human subjects primarily in air from a literature survey ranging between 1953 and 2004 and from a suited experiment recently performed by the authors, for a quantitative study of relative strength and predictive quality of the models. Human thermal modeling has considerable long term utility to human space flight. Such models provide a tool to predict crew survivability in support of vehicle design and to evaluate crew response in untested environments. It is to the benefit of any such model not only to collect relevant experimental data to correlate it against, but also to maintain an experimental standard or benchmark for future development in a readily and rapidly searchable and software accessible format. The Human thermal database project is intended to do just so; to collect relevant data from literature and experimentation and to store the data in a database structure for immediate and future use as a benchmark to judge human thermal models against, in identifying model strengths and weakness, to support model development and improve correlation, and to statistically quantify a model s predictive quality.

Cognata, T.↗

Flight Deck Surface Trajectory-Based Operations (STBO): A Four-Dimensional Trajectory (4DT) Simulation

Within human factors there is burgeoning interest in the Human-Autonomy Teaming (HAT) concept as away to address the challenges of interacting with complex, increasingly autonomous systems. The HAT concept comes out of an aspiration to interact with increasingly autonomous automation as a team member, rather than simply use automation as a tool. The authors, and others, have proposed core tenets for HAT that include bi-directional communication, automation and system transparency, and advanced coordination between human and automated teammates via predefined, dynamic task sequences known as plays (Shively et al., 2017). It is believed that, with proper implementation, HAT should foster appropriate teamwork, thus increasing trust and reliance on the system, which in turn will reduce workload, increase situation awareness, and improve performance. To this end, HAT has been demonstrated and/or studied in multiple applications including search and rescue operations (Nourbakhsh et al., 2005), healthcare and medicine (Tsui Yanco, 2007), autonomous vehicles (Parasuraman, Barnes, Cosenzo, Mulgund, 2007), photography (Lachter, Brandt, Sadler, Shively, in press), and aviation (Shively et al., in press). The current paper presents one such effort to apply HAT. It details the design of a R-HAT Agent developed as part of a NASA Research Agreement awarded to Human-Autonomy Teaming Solutions Inc. (HATS Inc), and developed in collaboration with the Human-Autonomy Teaming Laboratory at NASA Ames Research Center. The role of this Agent is to mediate interaction between the automation and the human operator of an advanced ground dispatch station, with this mediation based upon previously mentioned core tenets for HAT and the many lessons learned from the HAT research literature. This dispatch station was developed to support a NASA project investigating a concept called Reduced Crew Operations (RCO; Lachter, Brandt, Battiste, Matessa, Johnson, in press). Part of the RCO concept involves a ground operator providing enhanced support to a large number of aircraft with a single pilot on the flight deck. When assisted by the Agent, operators can monitor and support or manage a large number of aircraft and use plays to respond in real-time to complicated, workload-intensive events (e.g., an airport closure). A play is a plan that encapsulates goals, tasks, and a task allocation strategy appropriate for a particular situation. In the current implementation, when a play is initiated by a user, the Agent determines what tasks need to be done and has the ability to autonomously execute them (e.g., determining diversion options and uplinking new routes to aircraft) when it is safe and appropriate. The R-HAT Agent has been designed to both support end users and research in RCO and HAT. Additionally, the Agent and its underlying architecture were developed with generalizability in mind as a modular piece of software applicable outside of RCO aviation in domains such as those mentioned above. This paper will also discuss future further development and testing of the R-HAT Agent.

Bakowski, Deborah L.↗

3D Material Response of the MSL Heatshield Using NuSil-Coated PICA

The Mars Science Laboratory (MSL) Entry, Descent and Landing Instrumentation (MEDLI) collected in-flight data largely used by the ablation community to verify and validate physics-based models for the response of the Phenolic Impregnated Carbon Ablator (PICA) material [1-4]. MEDLI data were recently used to guide the development of NASA’s high-fidelity material response models for PICA implemented in the Porous material Analysis Toolbox based on OpenFOAM (PATO) software [5-6]. A follow-up instrumentation suite, MEDLI2, was used for the Mars 2020 mission [7] after the large scientific impact of MEDLI. Recent analyses performed as part of MEDLI2 development drew the attention to significant effects of a protective coating to the aerothermal response of PICA. NuSil, a silicone-based overcoat sprayed onto the MSL heatshield, including the MEDLI plugs, as contamination control, is currently neglected in PICA ablation models. To mitigate the spread of phenolic dust from PICA, NuSil was applied to the entire MSL and Mars 2020 heatshields, including the MEDLI and MEDLI2 plugs. Ground testing of PICA-NuSil (PICA-N) models exhibited surface temperature jumps due to oxide scale formation and subsequent NuSil burn- off. It is therefore critical to include a model for the aerothermal response of the coating in ongoing code development and validation efforts. Figure 1 illustrates the PICA-N model implemented in PATO with a test case that shows a temperature jump and a change of recession rate at the wall after 20 seconds of simulation when the NuSil coating was fully removed.

Aerospace↗

Identification of serum biomarkers for occupational medicamentosa-like dermatitis induced by trichloroethylene using mass spectrometry

Occupational medicamentosa-like dermatitis induced by trichloroethylene (OMLDT) is an autoimmune disease and it has become a serious occupational health hazard. In the present study, we collected fasting blood samples from patients with OMLDT (n = 18) and healthy volunteers (n = 33) to explore serum peptidome patterns. Peptides in sera were purified using weak cation exchange magnetic beads (MB-WCX), and analyzed by matrix-assisted laser desorption ionization time-of-flight-mass spectrometry (MALDI-TOF-MS) and ClinProTools bioinformatics software. The intensities of thirty protein/peptide peaks were significantly different between the healthy control and OMLDT patients. A pattern of three peaks (m/z 2106.3, 2134.5, and 3263.67) was selected for supervised neural network (SNN) model building to separate the OMLDT patients from the healthy controls with a sensitivity of 95.5% and a specificity of 73.8%. Furthermore, two peptide peaks of m/z 4091.61 and 4281.69 were identified as fragments of ATP-binding cassette transporter family A member 12 (ABCA12), and cationic trypsinogen (PRRS1), respectively. Our findings not only show that specific proteomic fingerprints in the sera of OMLDT patients can be served as a differentiated tool of OMLDT patients with high sensitivity and high specificity, but also reveal the novel correlation between OMLDT with ABC transports and PRRS1, which will be of potential value for clinical and mechanistic studies of OMLDT. - Highlights: • Identify 30 differential protein/peptide peaks between OMLDT and healthy control • The test sensitivity and test specificity were 95.5% and 73.8%, respectively. • ABCA12 and PRSS1 were identified as potential biomarkers in OMLDT patients.

60 APPLIED LIFE SCIENCES↗

Hybrid Solid Oxide Fuel Cell/Gas Turbine Model Development for Electric Aviation

A thermodynamic model was developed and validated to analyze a high-performance solid oxide fuel cell and gas turbine (SOFC-GT) hybrid power system for electric aviation. This study used a process simulation software package (ProMax) to study the role of SOFC design and operation on the feasibility and performance of the hybrid system. Standard modules, including compressor, turbine, heat exchanger, reforming reactor, and combustor were used from the ProMax tool suite while a custom module was created to simulate the SOFC stack. The model used an SOFC test data set as an input. Additional SOFC stack performance effects, such as pressure, temperature, and utilization of air and fuel, were added from open source data. System performance predictors were SOFC specific power, fuel-to-electricity conversion efficiency, and hybrid system efficiency. Using these input data and predictors, a static thermodynamic performance model was created that can be modified for different system configurations and operating conditions. Prior to creating the final aircraft performance model, initial demonstration models were developed to validate output results. We used the NASA SOFC model as a benchmark, which was created with their Numerical Propulsion System Simulator (NPSS) software framework. Our output results matched within 1% of both the NASA model and open source SOFC performance data. With confidence gained in the accuracy of this model, a 1-MW SOFC-GT hybrid power system was constructed for an aircraft propulsion concept. Overall hybrid system efficiencies of > 75% FTE were observed during standard 36,000 feet cruise flight conditions.

30 DIRECT ENERGY CONVERSION↗

Evaluation of Droplet Splashing Algorithm in LEWICE 3.0

The Icing Branch at NASA Glenn Research has developed a computer program to simulate ice formation on the leading edge of an aircraft wing during flight through cold, moist air. As part of the branch's current research, members have developed software known as LEWICE. This program is capable of predicting the formation of ice under designated weather conditions. The success of LEWICE is an asset to airplane manufacturers, ice protection system manufacturers, and the airline industry. Simulations of ice formation conducted in the tunnel and in flight is costly and time consuming. However, the danger of in-flight icing continues to be a concern for both commercial and military pilots. The LEWICE software is a step towards inexpensive and time efficient prediction of ice collection. In the most recent version of the program, LEWICE contains an algorithm for droplet splashing. Droplet splashing is a natural occurrence that causes accumulation of ice on aircraft surfaces. At impingement water droplets lose a portion of their mass to splashing. With part of each droplet joining the airflow and failing to freeze, early versions of LEWICE without the splashing algorithm over-predicted the collection of ice on the leading edge. The objective of my project was to determine whether the revised version of LEWICE accurately reflected the ice collection data obtained from the Icing Research Tunnel (IRT). The experimental data from the IRT was collected by Mark Potapczuk in January, March and July of 2001 and April and December of 2002. Experimental data points were the result of ice tracings conducted shortly after testing in the tunnel. Run sheets, which included a record of velocity, temperature, liquid water content and droplet diameter, served as the input of the LEWICE computer program. Parameters identical to the tunnel conditions were used to run LEWICE 2.0 and LEWICE 3.0. The results from IRT and versions of LEWICE were compared graphically. After entering the raw experimental data and computer output into a spread sheet, I mapped each ice formation onto a clean airfoil. The LEWICE output provided the data points to graphically depict ice formations developed by the program. weather conditions of runs conducted in January 2001, it was evident that the splashing algorithm of LEWICE 3.0 predicts ice formations more accurately than LEWICE 2.0. Especially at conditions with droplet size between 80 and 160 microns, the splashing algorithm of the new LEWICE version compensated for the loss of droplet mass as a result of splashing. In contrast, LEWICE 2.0 consistently over-predicted the mass of the ice in conditions with droplet size exceeding 80 microns. This evidence confirms that changes made to algorithms of LEWICE 3.0 have increased the accuracy of predicting ice collection.

Homenko, Hilary N.↗