SEARCH · Engineering Papers
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Viewgraphs on Enabler 1 and 2 engine system design modeling and comparisons are presented. The objective of this research was to define a near-term solid-core nuclear thermal propulsion (NTP) engine system scaling database. A unified set of performance, weight, and size scaling data are identified and documented. Results should be useful to meet initial mission and concept design study requirements.
In engineering practice, model-based design requires not only a good process-based model, but also a good description of stochastic disturbances and measurement errors to learn credible parameter values from observations. However, typical methods use Gaussian error models, which often cannot describe the complex temporal patterns of residuals. Consequently, this results in overconfidence in the identified parameters and, in turn, optimistic reactor designs. Here, we assess the strengths and weaknesses of a method to statistically describe these patterns with autocorrelated error models. This method produces increased widths of the credible prediction intervals following the inclusion of the bias term, in turn leading to more conservative design choices. However, we also show that the augmented error model is not a universal tool, as its application cannot guarantee the desired reliability of the resulting wastewater reactor design.
An engineering model of microbursts was developed as an aid to possible future flight simulation in wind shear. Planetary boundary layer and high altitude turbulence were also modeled.
Since the Second European Conference on Space Debris in 1997, the Orbital Debris Program Office at the NASA Johnson Space Center has undertaken a major effort to update and improve the principal software tools employed to model the space debris environment and to evaluate mission risks. NASA's orbital debris engineering model, ORDEM, represents the current and near-term Earth orbital debris population from the largest spacecraft to the smallest debris in a manner which permits spacecraft engineers and experimenters to estimate the frequency and velocity with which a satellite may be struck by debris of different sizes. Using expanded databases and a new program design, ORDEM2000 provides a more accurate environment definition combined with a much broader array of output products in comparison with its predecessor, ORDEM96. Studies of the potential long-term space debris environment are now conducted with EVOLVE 4.0, which incorporates significant advances in debris characterization and breakup modeling. An adjunct to EVOLVE 4.0, GEO EVOLVE has been created to examine debris issues near the geosynchronous orbital regime. In support of NASA Safety Standard 1740.14, which establishes debris mitigation guidelines for all NASA space programs, a set of evaluation tools called the Debris Assessment Software (DAS) is specifically designed for program offices to determine whether they are in compliance with NASA debris mitigation guidelines. DAS 1.5 has recently been released with improved WINDOWS compatibility and graphics functions. DAS 2.0 will incorporate guideline changes in a forthcoming revision to NASA Safety Standard 1740.14. Whereas DAS contains a simplified model to calculate possible risks associated with satellite reentries, NASA's higher fidelity Object Reentry Survival Analysis Tool (ORSAT) has been upgraded to Version 5.0. With the growing awareness of the potential risks posed by uncontrolled satellite reentries to people and property on Earth, the application of both DAS and ORSAT has increased markedly in the past two years.
As wind turbines continue to grow ever larger to reduce the cost of energy, their blades follow suit, with the largest commercial offshore blades extending past 100 m. Massive blades such as these raise key transportation and manufacturing challenges, especially for land-based turbines. Segmented blades are one solution and are garnering increased industry and research interest. In this work, a detailed mechanical joint model is integrated into the Wind-Plant Integrated System Design and Engineering Model (WISDEM ® ), which will facilitate future segmented blade research and optimization. WISDEM is used to design a wind turbine with 100-m segmented blades. This wind turbine design is compared to other machines with 100-m monolithic blades designed for rail-transportability. The designs are compared in terms of blade mass and cost, turbine capital cost, annual energy production, and levelized cost of energy, with monolithic designs being the lightest and most economical. However, this result may vary by wind plant location. A variety of segmentation joint types exist, and they will inevitably vary in parameters such as cost, spanwise location, and physical characteristics. This work examines the sensitivity of wind turbine design drivers and annual energy production to a variety of the aforementioned parameters, using the open-source wind turbine design codes OpenFAST and WISDEM, finding that joint mass, stiffness, and location can have significant effects on design drivers.
INL engineers developed a special purpose software framework designed to establish real-time connections between multiple running Unity instances. The framework is developed in Unity, a game engine development platform. This framework programmatically attaches functions to engineering models, enabling users to interact with, observe, and make changes to virtual models. These interactions are broadcasted through websocket connections, and received by other engineers in real-time.
The genesis for this systematic literature review was to search for industry case studies that could inform a decision of whether or not to support the change process, investment, training, and tools needed to implement an MBSE approach across the engineering enterprise. The question asked was, how the change from a document - based systems engineering approach (DBSE) to a model-based systems engineering approach (MBSE) is justified? The methodology employed for this systematic literature review was to conduct a document search of electronically published case studies by authors from the defense, space, and complex systems product engineering industries. The 67 case studies without metrics mainly attributed success to completeness, consistency, and communication of requirements. The 21 case studies with metrics on cost and schedule primarily attributed success to the ability of an MBSE approach to improve defect prevention strategies. The primary conclusion is that there is a significant advantage to project performance by applying an MBSE approach. An MBSE approach made the engineering processes on a complex system development effort more efficient by improving requirements completeness, consistency, and communication. These were seen in engineering processes involved in requirements management, concept exploration, design reuse, test and qualification, Verification and Validation, and margins analyses. An MBSE approach was most effective at improving defect prevention strategies. The approach was found to enhance the capability to find defects early in the system development life cycle (SDLC), when they could be fixed with less impact and prevented rework in later phases, thus mitigating risks to cost, schedule, and mission. However, if a program only employed an MBSE approach for requirements management, advantages from finding defects early could not be leveraged in later phases, where the savings in cost and schedule from rework prevention is realized. Significant performance success was achieved when the systems engineer (SE) held a leadership role over engineering process es. A number of the case studies addressed a general lack of skilled MBSE engineers as a major hindrance to implementing an MBSE approach successfully.
At redshift z = 0.03, the recently discovered SN 2017egm is the nearest Type I superluminous supernova (SLSN) to date and first near the center of a massive spiral galaxy (NGC 3191). Using SDSS spectra of NGC 3191, we find a metallicity ∼2 Z{sub ⊙} at the nucleus and ∼1.3 Z{sub ⊙} for a star-forming region at a radial offset similar to SN 2017egm. Archival radio-to-UV photometry reveals a star formation rate of ∼15 M{sub ⊙} yr{sup −1} (with ∼70% dust obscured), which can account for a Swift X-ray detection and a stellar mass of ∼10{sup 10.7} M{sub ⊙}. We model the early UV–optical light curves with a magnetar central-engine model, using the Bayesian light curve fitting tool MOSFiT. The fits indicate an ejecta mass of 2–4 M{sub ⊙}, a spin period of 4–6 ms, a magnetic field of (0.7--1.7)×10{sup 14} G, and a kinetic energy of 1--2×10{sup 51} erg. These parameters are consistent with the overall distributions for SLSNe, modeled by Nicholl et al., although the derived mass and spin are toward the low end, possibly indicating an enhanced loss of mass and angular momentum before explosion. This has two implications: (i) SLSNe can occur at solar metallicity, although with a low fraction of ∼10%, and (ii) metallicity has at most a modest effect on their properties. Both conclusions are in line with results for long gamma-ray bursts. Assuming a monotonic rise gives an explosion date of MJD 57889 ± 1. However, a short-lived excess in the data relative to the best-fitting models may indicate an early-time “bump.” If confirmed, SN 2017egm would be the first SLSN with a spectrum during the bump phase; this shows the same O ii lines seen at maximum light, which may be an important clue for explaining these bumps.
The NEXT propulsion system is an advanced ion propulsion system presently under development that is oriented towards robotic exploration of the solar system using solar electric power. The subsystem includes an ion engine, power processing unit, feed system components, and thruster gimbal. The Prototype Model engine PM1 was subjected to qualification-level environmental testing in 2006 to demonstrate compatibility with environments representative of anticipated mission requirements. Although the testing was largely successful, several issues were identified including the fragmentation of potting cement on the discharge and neutralizer cathode heater terminations during vibration which led to abbreviated thermal testing, and generation of particulate contamination from manufacturing processes and engine materials. The engine was reworked to address most of these findings, renamed PM1R, and the environmental test sequence was repeated. Thruster functional testing was performed before and after the vibration and thermal-vacuum tests. Random vibration testing, conducted with the thruster mated to the breadboard gimbal, was executed at 10.0 Grms for 2 min in each of three axes. Thermal-vacuum testing included three thermal cycles from 120 to 215 C with hot engine re-starts. Thruster performance was nominal throughout the test program, with minor variations in a few engine operating parameters likely caused by facility effects. There were no significant changes in engine performance as characterized by engine operating parameters, ion optics performance measurements, and beam current density measurements, indicating no significant changes to the hardware as a result of the environmental testing. The NEXT PM1R engine and the breadboard gimbal were found to be well-designed against environmental requirements based on the results reported herein. The redesigned cathode heater terminations successfully survived the vibration environments. Based on the results of this test program and confidence in the engineering solutions available for the remaining findings of the first test program, specifically the particulate contamination, the hardware environmental qualification program can proceed with confidence
An overview is provided of the Human Performance Modeling (HPM) element within the NASA Aviation Safety Program (AvSP). Two separate model development tracks for performance modeling of real-world aviation environments are described: the first focuses on the advancement of cognitive modeling tools for system design, while the second centers on a prescriptive engineering model of activity tracking for error detection and analysis. A progressive implementation strategy for both tracks is discussed in which increasingly more complex, safety-relevant applications are undertaken to extend the state-of-the-art, as well as to reveal potential human-system vulnerabilities in the aviation domain. Of particular interest is the ability to predict the precursors to error and to assess potential mitigation strategies associated with the operational use of future flight deck technologies.
An examination of the Hubble Space Telescope (HST) Wide Field Planetary Camera 2 (WFPC-2) radiator assembly was conducted at NASA Goddard Space Flight Center (GSFC) during the summer of 2009. Immediately apparent was a distinct biasing of the largest 45 impact features towards one side of the radiator, in contrast to an approximately uniform distribution of smaller impacts. Such a distribution may be a consequence of the HST s attitude history and pointing requirements for the cold radiator, or of environmental effects, such as an anisotropic distribution of the responsible population in that size regime. Understanding the size-dependent spatial distribution of impact features is essential to the general analysis of these features. We have obtained from GSFC a 15 minute temporal resolution record of the state vector (Earth Centered Inertial position and velocity) and HST attitude, consisting of the orientation of the velocity and HST-sun vectors in HST body coordinates. This paper reviews the actual state vector and attitude history of the radiator in the context of the randomly tumbling plate assumption and assesses the statistical likelihood (or collection efficiency) of the radiator for the micrometeoroid and orbital debris environments. The NASA Marshall Space Flight Center s Meteoroid Environment Model is used to assess the micrometeoroid component. The NASA Orbital Debris Engineering Model (ORDEM) is used to model the orbital debris component. Modeling results are compared with observations of the impact feature spatial distribution, and the relative contribution of each environmental component are examined in detail.
The Green Propellant Infusion Mission (GPIM) is sponsored by NASA's Space Technology Mission Directorate (STMD) Technology Demonstration Mission (TDM) office. The goal of GPIM is to advance the technology readiness level of a green propulsion system, specifically, one using the monopropellant, AF-M315E, by demonstrating ground handling, spacecraft processing, and on-orbit operations. One of the risks identified for GPIM is potential contamination of sensitive spacecraft surfaces from the effluents in the plumes of AF-M315E thrusters. NASA Glenn Research Center (GRC) is conducting activities to characterize the effects of AF-M315E plume impingement and deposition. GRC has established individual plume models of the 22-N and 1-N thrusters that will be used on the GPIM spacecraft. The models describe the pressure, temperature, density, Mach number, and species concentration of the AF-M315E thruster exhaust plumes. The models are being used to assess the impingement effects of the AF-M315E thrusters on the GPIM spacecraft. The model simulations will be correlated with plume measurement data from Laboratory and Engineering Model 22-N, AF-M315E thrusters. The thrusters will be tested in a small rocket, altitude facility at NASA GRC. The GRC thruster testing will be conducted at duty cycles representatives of the planned GPIM maneuvers. A suite of laser-based diagnostics, including Raman spectroscopy, Rayleigh spectroscopy, Schlieren imaging, and physical probes will be used to acquire plume measurements of AFM315E thrusters. Plume data will include temperature, velocity, relative density, and species concentration. The plume measurement data will be compared to the corresponding simulations of the plume model. The GRC effort will establish a data set of AF-M315E plume measurements and a plume model that can be used for future AF-M315E applications.
The Green Propellant Infusion Mission (GPIM) is sponsored by NASA's Space Technology Mission Directorate (STMD) Technology Demonstration Mission (TDM) office. The goal of GPIM is to advance the technology readiness level of a green propulsion system, specifically, one using the monopropellant, AF-M315E, by demonstrating ground handling, spacecraft processing, and on-orbit operations. One of the risks identified for GPIM is potential contamination of sensitive spacecraft surfaces from the effluents in the plumes of AF-M315E thrusters. NASA Glenn Research Center (GRC) is conducting activities to characterize the effects of AF-M315E plume impingement and deposition. GRC has established individual plume models of the 22-N and 1-N thrusters that will be used on the GPIM spacecraft. The model simulations will be correlated with plume measurement data from Laboratory and Engineering Model 22-N, AF-M315E thrusters. The thrusters are currently being tested in a small rocket, altitude facility at NASA GRC. A suite of diagnostics, including Raman spectroscopy, Rayleigh spectroscopy, and Schlieren imaging are being used to acquire plume measurements of AF-M315E thrusters. Plume data will include temperature, velocity, relative density, and species concentration. The plume measurement data will be compared to the corresponding simulations of the plume model. The GRC effort will establish a data set of AF-M315E plume measurements and a plume model that can be used for future AF-M315E applications.
We describe our pilot study development of an Assurance Case arguing the robustness of a spacecraft demonstration of optical communication. Our Assurance Case addresses the concern that optical communication may be interrupted by the presence of cloud cover, threatening the success of the demonstration. Central to our Assurance Case is its use of a model of atmospheric attenuation to support a key portion of the robustness argument. The conclusion for the demonstration is that its schedule slack plus ability to store data for transmission later accommodates occasional weather-caused atmospheric attenuation.We indicate how the overall structure of the Assurance Case derives from the Objectives Hierarchy set forth in the NASA Reliability and Maintainability standard. We then present the portions of the Assurance Case that argue (1) the atmospheric attenuation model is sufficiently accurate, (2) application of the model shows the desired robustness of the demonstration, and (3) all the model assumptions are satisfied in its application. Lastly, we suggest how an engineering model of the demonstration system and its use could inform the development of the Assurance Case encompassing additional plausible hazards.
Explore the source record for details and available documents.
This paper presents the first blind prediction stage of the Tidal Turbine Benchmarking Project being conducted and funded by the UK's EPSRC and Supergen ORE Hub. In this first stage, only steady flow conditions, at low and elevated turbulence (3.1%) levels, were considered. Prior to the blind prediction stage, a large laboratory scale experiment was conducted in which a highly instrumented 1.6m diameter tidal rotor was towed through a large towing tank in well-defined flow conditions with and without an upstream turbulence grid. Details of the test campaign and rotor design were released as part of this community blind prediction exercise. Participants were invited to use a range of engineering modelling approaches to simulate the performance and loads of the turbine. 26 submissions were received from 12 groups from across academia and industry using solution techniques ranging from blade resolved computational fluid dynamics through actuator line, boundary integral element methods, vortex methods to engineering Blade Element Momentum methods. The comparisons between experiments and blind predictions were extremely positive helping to provide validation and uncertainty estimates for the models, but also validating the experimental tests themselves. The exercise demonstrated that the experimental turbine data provides a robust data set against which researchers and design engineers can test their models and implementations to ensure robustness in their processes, helping to reduce uncertainty and provide increased confidence in engineering processes. Furthermore, the data set provides the basis by which modellers can evaluate and refine approaches.
Black holes (BHs) hide themselves behind various astronomical phenomena and their properties, i.e., mass and spin, are usually difficult to constrain. One leading candidate for the central engine model of gamma-ray bursts (GRBs) invokes a stellar mass BH and a neutrino-dominated accretion flow (NDAF), with the relativistic jet launched due to neutrino-anti-neutrino annihilations. Such a model gives rise to a matter-dominated fireball, and is suitable to interpret GRBs with a dominant thermal component with a photospheric origin. We propose a method to constrain BH mass and spin within the framework of this model and apply the method to the thermally dominant GRB 101219B, whose initial jet launching radius, r {sub 0}, is constrained from the data. Using our numerical model of NDAF jets, we estimate the following constraints on the central BH: mass M {sub BH} ∼ 5–9 M {sub ⊙}, spin parameter a {sub *} ≳ 0.6, and disk mass 3 M {sub ⊙} ≲ M {sub disk} ≲ 4 M {sub ⊙}. Our results also suggest that the NDAF model is a competitive candidate for the central engine of GRBs with a strong thermal component.
Furthermore, there are many applications in science and engineering modeling where an accurate representation of a complex model geometry in the form of a mesh is important. In applications of flow and transport in subsurface porous media, this is manifest in models that must capture complex geologic stratigraphy, structure (faults, folds, erosion, deposition) and infrastructure (tunnels, boreholes, excavations). Model setup, defined as the activities of geometry definition, mesh generation (creation, optimization, modification, refine, de-refine, smooth), assigning material properties, initial conditions and boundary conditions requires specialized software tools to automate and streamline the process. In addition, some model setup tools will provide more utility if they are designed to interface with and meet the needs of a particular flow and transport software suite. A control volume discretization that uses a two point flux approximation is for example most accurate when the underlying control volumes are 2D or 3D Voronoi tessellations. In this paper we will present the coupling of LaGriT, a mesh generation and model setup software suite and TOUGH2 to model subsurface flow problems and we show an example of how LaGriT can be used as a model setup tool for the generation of a Voronoi mesh for the simulation program TOUGH2. To generate the MESH file for TOUGH2 from the LaGriT output a standalone module Lagrit2Tough2 was developed, which is presented here and will be included in a future release of LaGriT. Here in this paper an alternative method to generate a Voronoi mesh for TOUGH2 with LaGriT is presented and thanks to the modular and command based structure of LaGriT this method is well suited to generating a mesh for complex models.