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A sample environmental control and life support model performance analysis using the environmental analysis routines library is presented. An example of a complete model set up and execution is provided. The particular model was synthesized to utilize all of the component performance routines and most of the program options.
An emerging new mission for aeronautics is Urban Air Mobility (UAM), a concept for air transportation around metropolitan areas with passenger-carrying operations. UAM vehicles must be capable of vertical take-off and landing, and this requirement presents unique technical challenges for electric and hybrid-based vertical take-off and landing (eVTOL). A critical challenge for UAM market growth is to gain public acceptance for being as safe as - or safer than - commercial air travel and automotive transportation. There is a lack of data for propulsion systems, components, and the associated thermal management systems for UAM eVTOL propulsion systems. The new mission, new propulsion system concepts, safety criticality of propulsion component performance during vertical take-off and lift operations, and lack of data presents many research challenges and opportunities. NASA has developed and published UAM vehicle concept studies. For a subset of the said concept vehicles, NASA has contracted for a study to identify failure modes and hazards associated with the propulsion systems of the concept vehicles and to perform functional hazard analyses (FHA) and failure modes and effects criticality analyses (FMECA) for each. From the completed study results, it was recommended for NASA to support research toward developing electric/hybrid-electric propulsion components with improved reliability and to explore powertrain architectures that can take advantage of higher reliability components to achieve inherent air-vehicle safety. NASA has started a research effort for UAM propulsion with a focus toward improving safety and reliability. Recent results and research strategy will be discussed toward the goals by means of: 1) improving individual component reliability through advanced materials and design methods, 2) improving the thermal management system, and 3) designing propulsion system architectures to provide inherent UAM vehicle safety.
The Nuclear Thermal Rocket Element Environmental Simulator (NTREES) was designed to perform non-nuclear testing of nuclear thermal rocket (NTR) fuel elements and materials. NTREES can simulate the thermal hydraulic environment within an NTR and has been leveraged to provide critical information on component performance and material compatibility. NTREES has the ability to expose test articles to pressurized Hydrogen gas up to 1000 psig and 225 g/s. NTREES tests are operated in a deoxygenated environment of Nitrogen or Argon pressurized up to 1000 psig. NTREES simulates fission heat through induction heating powered by a 1.2 MW AC power supply, and NTREES has recorded temperatures exceeding 3700K. To perform hot Hydrogen exposure tests on materials more rapidly and earlier in the fuel development process, NTREES must be able to test small material samples on the order of 1 square inch in volume, individual fuel assembly subcomponents, and particle materials. To meet these needs, multiple testing rigs have been developed to immerse test specimens in hot Hydrogen, with each "immersion rig" varying in its capability of sample type and performance range in order to meet the broadest range of testing needs. Herein is a discussion of a selection of these “immersion rigs.”
In this talk we shall discuss algorithms and CAD tools for the design and analysis of structures for high performance applications using advanced composite materials. An extensive mathematical theory for optimal structural (e.g., shape) design was developed over the past thirty years. Aspects of this theory have been used in the design of components for hypersonic vehicles and thermal diffusion systems based on homogeneous materials. Enhancement of the design methods to include optimization of the microstructure of the component is a significant innovation which can lead to major enhancements in component performance. Our work is focused on the adaptation of existing theories of optimal structural design (e.g., optimal shape design) to treat the design of structures using advanced composite materials (e.g., fiber reinforced, resin matrix materials). In this talk we shall discuss models and algorithms for the design of simple structures from composite materials, focussing on a problem in thermal management. We shall also discuss methods for the integration of active structural controls into the design process.
Electrified aircraft powertrains contain multiple tightly coupled subsystems, making them much more complex than traditional aircraft propulsion systems, both in terms of integration and control. Electrification enables aircraft to have multiple distributed thrust-producing fans that the flight control system can utilize for enhanced maneuverability, further increasing the control complexity. The SUbsonic Single Aft eNgine (SUSAN) Electrofan is a NASA concept aircraft that leverages this technology. SUSAN is a series/parallel partial hybrid electric single-aisle transport aircraft that takes advantage of its electrified powertrain to provide fuel burn and emissions benefits when compared to the state-of-the-art. Achieving these benefits requires an appropriately designed control architecture that coordinates the various powertrain and flight control subsystems. As such, the SUSAN aircraft is designed with a high level of automation, allowing it to properly manage coupled subsystems and react rapidly to failures and anomalies. To do this effectively, algorithms that perform component health management, fault detection, isolation, and accommodation, and continuous optimization, must be developed, tested, validated, and implemented. This paper describes a piloted evaluation of such an algorithm in scenarios with multiple fan failures, performed in a flight simulator, demonstrating failure recovery and continued safe operation up to the limits of the powertrain. These scenarios are subsequently related to certification requirements.
Electrified aircraft powertrains contain multiple tightly coupled subsystems, making them much more complex than traditional aircraft propulsion systems, both in terms of integration and control. Electrification enables aircraft to have multiple distributed thrust-producing fans that the flight control system can utilize for enhanced maneuverability, further increasing the control complexity. The SUbsonic Single Aft eNgine (SUSAN) Electrofan is a NASA concept aircraft that leverages this technology. SUSAN is a series/parallel partial hybrid electric single-aisle transport aircraft that takes advantage of its electrified powertrain to provide fuel burn and emissions benefits when compared to the state-of-the-art. Achieving these benefits requires an appropriately designed control architecture that coordinates the various powertrain and flight control subsystems. As such, the SUSAN aircraft is designed with a high level of automation, allowing it to properly manage coupled subsystems and react rapidly to failures and anomalies. To do this effectively, algorithms that perform component health management, fault detection, isolation, and accommodation, and continuous optimization, must be developed, tested, validated, and implemented. This paper describes a piloted evaluation of such an algorithm in scenarios with multiple fan failures, performed in a flight simulator, demonstrating failure recovery and continued safe operation up to the limits of the powertrain. These scenarios are subsequently related to certification requirements.
Electrified aircraft powertrains contain multiple tightly coupled subsystems, making them much more complex than traditional aircraft propulsion systems, both in terms of integration and control. Electrification enables aircraft to have multiple distributed thrust-producing fans that the flight control system can utilize for enhanced maneuverability, further increasing the control complexity. The SUbsonic Single Aft eNgine (SUSAN) Electrofan is a NASA concept aircraft that leverages this technology. SUSAN is a series/parallel partial hybrid electric single-aisle transport aircraft that takes advantage of its electrified powertrain to provide fuel burn and emissions benefits when compared to the state-of-the-art. Achieving these benefits requires an appropriately designed control architecture that coordinates the various powertrain and flight control subsystems. As such, the SUSAN aircraft is designed with a high level of automation, allowing it to properly manage coupled subsystems and react rapidly to failures and anomalies. To do this effectively, algorithms that perform component health management, fault detection, isolation, and accommodation, and continuous optimization, must be developed, tested, validated, and implemented. This paper describes a piloted evaluation of such an algorithm in scenarios with multiple fan failures, performed in a flight simulator, demonstrating failure recovery and continued safe operation up to the limits of the powertrain. These scenarios are subsequently related to certification requirements.
The SpaceCubeX project is motivated by the need for high performance, modular, and scalable on-board processing to help scientists answer critical 21st century questions about global climate change, air quality, ocean health, and ecosystem dynamics, while adding new capabilities such as low-latency data products for extreme event warnings. These goals translate into on-board processing throughput requirements that are on the order of 100-1,000 more than those of previous Earth Science missions for standard processing, compression, storage, and downlink operations. To study possible future architectures to achieve these performance requirements, the SpaceCubeX project provides an evolvable testbed and framework that enables a focused design space exploration of candidate hybrid CPU/FPGA/DSP processing architectures. The framework includes ArchGen, an architecture generator tool populated with candidate architecture components, performance models, and IP cores, that allows an end user to specify the type, number, and connectivity of a hybrid architecture. The framework requires minimal extensions to integrate new processors, such as the anticipated High Performance Spaceflight Computer (HPSC), reducing time to initiate benchmarking by months. To evaluate the framework, we leverage a wide suite of high performance embedded computing benchmarks and Earth science scenarios to ensure robust architecture characterization. We report on our projects Year 1 efforts and demonstrate the capabilities across four simulation testbed models, a baseline SpaceCube 2.0 system, a dual ARM A9 processor system, a hybrid quad ARM A53 and FPGA system, and a hybrid quad ARM A53 and DSP system.
The development of a microstrip-based L-band Dicke radiometer with the long-term stability required for future ocean salinity measurements to an accuracy of 0.1 psu is presented. This will require the L-band radiometer requirements and configuration to achieve this objective. System configuration and component performance have been evaluated with radiometer test beds at both JPL and GSFC. The GSFC testbed uses a cryogenic chamber that al-lows long-term characterization at radiometric temperatures in the range of 70 - 120 K. The research has addressed several areas including component characterization as a function of temperature and bias, system linearity, optimum noise diode injection calibration and precision temperature control of components. A breadboard radiometer, utilizing microstrip-based technologies, has been built to demonstrate this long-term stability. This system is partially polarimetric providing V, H, -45 and +45 signals. Test results are compared to current and future ocean salinity radiometer requirements to show that the desire performance is possible.
Utilizing the Arcam electron beam melting powder bed process, fuel nozzles designed by GTI and not manufacturable by traditional manufacturing techniques were produced. The fuel nozzles resulted in a 50% reduction in emissions and efficiency improvement. The goal of this project was to assess the cost and performance benefits of utilizing selected Additive Manufacturing (AM) approaches to fabricate an advanced premix nozzle for use in commercial burner applications that can only be manufactured by advanced AM methods, and which offers the potential for increased component performance.
Ti6Al4V alloy has been widely used in many fields, such as aerospace and medicine, due to its excellent biocompatibility and mechanical properties. Most high-performance components made of Ti6Al4V alloy usually need to be polished to produce their specific functional requirements. However, due to the material properties of Ti6Al4V, its polishing process still requires significant development. Therefore, this study aimed to investigate the performance of polishing Ti6Al4V by using tools with different rigidities. Two kinds of bonnet tool were used, namely a pure rubber (PR) bonnet and a semirigid (SR) bonnet. The characterization of material removal and surface integrity after polishing was conducted through a series of experiments on a 6-DOF robotic polishing device. The results demonstrate that both bonnet tools successfully produce nanometric level surface roughness. Moreover, the material removal rate of the SR bonnet tool is significantly higher than that of the PR bonnet, which is consistent with the material removal characteristics of glass polishing in previous research. In addition, the presented analysis on key polishing parameters and surface integrity lays the theoretical foundation for the polishing process of titanium alloy in different application fields.
Development of new materials and predictive capabilities of component performance hinges on the ability to accurately digitize "as-built" geometries. X-ray computed tomography (CT) offers a non-destructive method of capturing these details but current methodologies are unable to produce the required fidelity for critical component certification. This project focused on discovering the limitations of existing CT reconstruction algorithms and exploring machine learning (ML) methodologies to overcome these limitations. We found that existing CT reconstruction methods are insufficient for Sandia's critical component certification process and that ML algorithms are a viable path forward to improving the quality of CT images.
A traditional F110-type turbofan engine model was extended to include a ventral nozzle and two thrust-augmenting ejectors for Short Take-Off Vertical Landing (STOVL) aircraft applications. Development of the real-time F110/STOVL simulation required special attention to the modeling approach to component performance maps, the low pressure turbine exit mixing region, and the tailpipe dynamic approximation. Simulation validation derives by comparing output from the ADSIM simulation with the output for a validated F110/STOVL General Electric Aircraft Engines FORTRAN deck. General Electric substantiated basic engine component characteristics through factory testing and full scale ejector data.
Data were obtained in an altitude test chamber for a range of altitudes from 20,000 to 58,000 feet at a flight Mach number of 0.9, and for several flight Mach numbers at an altitude of 45,000 feet. Data approximating sea-level operation are also included. Engine component performance data are presented in addition to windmilling, exhaust-nozzle, and ejector performance.
The development of a microstrip-based L-band Dicke radiometer with the long-term stability required for future ocean salinity measurements to an accuracy of 0.1 psu is presented. This measurement requires the L-band radiometers to have calibration stabilities of less than or equal to 0.05 K over 2 days. This research has focused on determining the optimum radiometer requirements and configuration to achieve this objective. System configuration and component performance have been evaluated with radiometer test beds at both JPL and GSFC. The GSFC testbed uses a cryogenic chamber that allows long-term characterization at radiometric temperatures in the range of 70 - 120 K. The research has addressed several areas including component characterization as a function of temperature and DC bias, system linearity, optimum noise diode injection calibration, and precision temperature control of components. A breadboard radiometer, utilizing microstrip-based technologies, has been built to demonstrate this long-term stability.
The Personal Computer Transport Analysis Program (PCTAP) is C++ software used for analysis of thermal fluid systems. The program predicts thermal fluid system and component transients. The output consists of temperatures, flow rates, pressures, delta pressures, tank quantities, and gas quantities in the air, along with air scrubbing component performance. PCTAP s solution process assumes that the tubes in the system are well insulated so that only the heat transfer between fluid and tube wall and between adjacent tubes is modeled. The system described in the model file is broken down into its individual components; i.e., tubes, cold plates, heat exchangers, etc. A solution vector is built from the components and a flow is then simulated with fluid being transferred from one component to the next. The solution vector of components in the model file is built at the initiation of the run. This solution vector is simply a list of components in the order of their inlet dependency on other components. The component parameters are updated in the order in which they appear in the list at every time step. Once the solution vectors have been determined, PCTAP cycles through the components in the solution vector, executing their outlet function for each time-step increment.
Abstract The tightest constraints on the tensor-to-scalar ratio r can only be obtained after removing a substantial fraction of the lensing B -mode sample variance. The planned Cosmic Microwave Background (CMB)-S4 experiment ( cmb-s4.org ) will remove the lensing B -mode signal internally by reconstructing the gravitational lenses from high-resolution observations. We document here a first lensing reconstruction pipeline able to achieve this optimally for arbitrary sky coverage. We make it part of a map-based framework to test CMB-S4 delensing performance and its constraining power on r , including inhomogeneous noise and two non-Gaussian Galactic polarized foreground models. The framework performs component separation of the high-resolution maps, followed by the construction of lensing B -mode templates, which are then included in a parametric small-aperture map cross-spectra-based likelihood for r . We find that the lensing reconstruction and framework achieve the expected performance, compatible with the target σ ( r ) ≃ 5 · 10 −4 in the absence of a tensor signal, after an effective removal of 92%–93% of the lensing B -mode variance, depending on the simulation set. The code for the lensing reconstruction can also be used for cross-correlation studies with large-scale structures, lensing spectrum reconstruction, cluster lensing, or other CMB lensing-related purposes. As part of our tests, we also demonstrate the joint optimal reconstruction of the lensing potential with the lensing curl potential mode at second order in the density fluctuations.
The measurement of fast neutron fluxes is important in many areas of nuclear technology. It affects the stability of the reactor structural components, performance of fuel, and also the fuel manner. The experiments performed at the LR-0 reactor were in the past focused on the measurement of neutron field far from the core, in reactor pressure vessel simulator or in biological shielding simulator. In the present the measurement in closer regions to core became more important, especially measurements in structural components like reactor baffle. This importance increases with both reactor power increase and also long term operation. Other important task is an increasing need for the measurement close to the fuel. The spectra near the fuel are aimed due to the planned measurements with the FLIBE salt, in FHR / MSR research, where one of the task is the measurement of the neutron spectra in it. In both types of experiments there is strong demand for high working count rate. The high count rate is caused mainly by high gamma background and by high fluxes. The fluxes in core or in its vicinity are relatively high to ensure safe reactor operation. This request is met in the digital spectroscopic apparatus. All experiments were realized in the LR-0 reactor. It is an extremely flexible light water zero-power research reactor, operated by the Research Center Rez (Czech Republic). (authors)