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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.
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Several modifications made to enhance utility of HBEAR, computer program for analysis and design of hydrostatic bearings. Modifications make program applicable to more realistic cases and reduce time and effort necessary to arrive at a suitable design. Uses search technique to iterate on size of orifice to obtain required pressure ratio.
This paper describes the process of integrating available environment models into a single package that calculates the radiation environment for any earth orbit quickly and accurately with the only input being initial orbit parameters, launch date and length of mission, and units of output. The radiation dose is calculated for particles penetrating varying aluminum shielding thicknesses and incident upon several materials inside. Included also are modifications that have been made to the codes that account for the decrease of the magnetic field with time, which allows the use of data taken in the past to accurately predict a future environment. The complete package has relatively short run times, 20 minutes per mission on a Micro VAX II, allowing multiple iterations for application to mission design and planning.
The state-of-art power semiconductor devices require a thorough understanding of the thermal behavior for these devices. Traditional thermal analysis have (1) failed to account for the thermo-electrical interaction which is significant for power semiconductor devices operating at high temperature, and (2) failed to account for the thermal interactions among all the levels involved in, from the entire device to the gate micro-structure. Furthermore there is a lack of quantitative studies of the thermal breakdown phenomenon which is one of the major failure mechanisms for power electronics. This research work is directed towards addressing. Using a coupled thermal and electrical simulation, in which the drift-diffusion equations for the semiconductor and the energy equation for temperature are solved simultaneously, the thermo-electrical interactions at the micron scale of various junction structures are thoroughly investigated. The optimization of gate structure designs and doping designs is then addressed. An iterative numerical procedure which incorporates the thermal analysis at the device, chip and junction levels of the power device is proposed for the first time and utilized in a BJT power semiconductor device. In this procedure, interactions of different levels are fully considered. The thermal stability issue is studied both analytically and numerically in this research work in order to understand the mechanism for thermal breakdown.
Within the scope of the Multi-purpose Crew Restraints for Long Duration Spaceflights project, funded by Code U, it was proposed to conduct a series of evaluations on the ground and on the KC-135 to investigate the human factors issues concerning confined/unique workstations, such as the design of crew restraints. The usability of multiple crew restraints was evaluated for use with the Life Sciences Glovebox (LSG) and for performing general purpose tasks. The purpose of the KC-135 microgravity evaluation was to: (1) to investigate the usability and effectiveness of the concepts developed, (2) to gather recommendations for further development of the concepts, and (3) to verify the validity of the existing requirements. Some designs had already been tested during a March KC-135 evaluation, and testing revealed the need for modifications/enhancements. This flight was designed to test the new iterations, as well as some new concepts. This flight also involved higher fidelity tasks in the LSG, and the addition of load cells on the gloveports.
A technique for the optimization of stability constrained geometrically nonlinear shallow trusses with snap through behavior is demonstrated using the arc length method and a strain energy density approach within a discrete finite element formulation. The optimization method uses an iterative scheme that evaluates the design variables' performance and then updates them according to a recursive formula controlled by the arc length method. A minimum weight design is achieved when a uniform nonlinear strain energy density is found in all members. This minimal condition places the design load just below the critical limit load causing snap through of the structure. The optimization scheme is programmed into a nonlinear finite element algorithm to find the large strain energy at critical limit loads. Examples of highly nonlinear trusses found in literature are presented to verify the method.
The Iterator Perl Module provides a general-purpose framework for constructing iterator objects within Perl, and a standard API for interacting with those objects. Iterators are an object-oriented design pattern where a description of a series of values is used in a constructor. Subsequent queries can request values in that series. These Perl modules build on the standard Iterator framework and provide iterators for some other types of values. Iterator::DateTime constructs iterators from DateTime objects or Date::Parse descriptions and ICal/RFC 2445 style re-currence descriptions. It supports a variety of input parameters, including a start to the sequence, an end to the sequence, an Ical/RFC 2445 recurrence describing the frequency of the values in the series, and a format description that can refine the presentation manner of the DateTime. Iterator::String constructs iterators from string representations. This module is useful in contexts where the API consists of supplying a string and getting back an iterator where the specific iteration desired is opaque to the caller. It is of particular value to the Iterator::Hash module which provides nested iterations. Iterator::Hash constructs iterators from Perl hashes that can include multiple iterators. The constructed iterators will return all the permutations of the iterations of the hash by nested iteration of embedded iterators. A hash simply includes a set of keys mapped to values. It is a very common data structure used throughout Perl programming. The Iterator:: Hash module allows a hash to include strings defining iterators (parsed and dispatched with Iterator::String) that are used to construct an overall series of hash values.
COBRA-AHS is a package of advanced software for analysis of rigid or flexible shaft systems supported by rolling-element bearings operating at high speeds under complex mechanical and thermal loads. These loads can include centrifugal and thermal loads generated by motions of bearing components. COBRA-AHS offers several improvements over prior commercial bearing-analysis programs: It includes innovative probabilistic fatigue-life-estimating software that provides for computation of three-dimensional stress fields and incorporates stress-based (in contradistinction to prior load-based) mathematical models of fatigue life. It interacts automatically with the ANSYS finite-element code to generate finite-element models for estimating distributions of temperature and temperature-induced changes in dimensions in iterative thermal/dimensional analyses: thus, for example, it can be used to predict changes in clearances and thermal lockup. COBRA-AHS provides an improved graphical user interface that facilitates the iterative cycle of analysis and design by providing analysis results quickly in graphical form, enabling the user to control interactive runs without leaving the program environment, and facilitating transfer of plots and printed results for inclusion in design reports. Additional features include roller-edge stress prediction and influence of shaft and housing distortion on bearing performance.
Terrain Identify specifics such as slope, rockiness, traction parameters Identify what part of ISRU needs each Physical Geotechnical Hardness, density, cohesion, etc. Identify what part of ISRU needs each (e.g., excavation needs to know hardness, density; soil processing needs to know density, cohesion; etc.)Mineral Identify specifics Identify what part of ISRU needs each Volatile Identify specifics Identify what part of ISRU needs each Atmosphere Identify specifics Identify what part of ISRU needs each Environment Identify specifics Identify what part of ISRU needs each Resource Characterization What: Develop an instrument suite to locate and evaluate the physical, mineral, and volatile resources at the lunar poles Neutron Spectrometer Near Infrared (IR) to locate subsurface hydrogen surface water Near IR for mineral identification Auger drill for sample removal down to 1 m Oven with Gas Chromatograph Mass Spectrometer to quantify volatiles present ISRU relevance: Water volatile resource characterization and subsurface material access removal Site Evaluation Resource Mapping What: Develop and utilize new data products and tools for evaluating potential exploration sites for selection and overlay mission data to map terrain, environment, and resource information e.g., New techniques applied to generate Digital Elevation Map (DEMs) at native scale of images (1mpxl)ISRU relevance: Resource mapping and estimation with terrain and environment information is needed for extraction planning Mission Planning and Operations What: Develop and utilize tools and procedures for planning mission operations and real time changes Planning tools include detailed engineering models (e.g., power and data) of surface segment systems allows evaluation of designs ISRU relevance: Allows for iterative engineering as a function of environment and hardware performance.
The National Aeronautics and Space Administration (NASA) has evolved multiple spacesuit systems for performing extravehicular activity (EVA) or space walks. These spacesuit systems include the Apollo Extravehicular Mobility Unit (EMU), Space Shuttle and International Space Station (ISS) EMU, and Exploration EMU (xEMU). Each spacesuit system is like the other for functionality. However, each spacesuit system is different in configuration based on the technology infused into the system associated with the purpose of the mission. Each spacesuit system is made up of many components and the integrate environment targeted for operations leads to an integrated system that is complex. Since Apollo, NASA has invested in multiple technologies that make up these spacesuit systems in different iterations. The Apollo EMU was designed in the 1960’s with a focus to facilitate the first human to walk on the moon. The Space Shuttle EMU was designed in the 1970’s for reusable microgravity operations that began in the early 1980’s. The Space Shuttle EMU was enhanced to facilitate extended operation on the ISS. Over the last 15 years, NASA has been designing, developing, and testing a new spacesuit system, the xEMU which is considered a design, verification, and test unit. NASA is planning to land the first woman and first person of color on the Moon. NASA recently engaged industry through a new contractual arrangement to provide EVA services needed to return to the Moon and to continue operations on the ISS. Spacesuit systems are complex. Understanding the requirements, operational environment, the necessary technologies, and the integrated spacesuit system are paramount. In addition, understanding the technology infusion process to meet the mission objectives is critical. This paper will review the spacesuit systems for EVA and several component functions within the spacesuits, along with a system comparison of those technologies from Apollo to xEMU.
This paper details a translation of a first order quadratic program (QP) solver from MATLAB to C. NASA could use this QP solver to generate online flight path trajectories for powered descent vehicles during landing. Over 12 weeks, the team designed, implemented, and tested two iterations of the QP solver for accuracy and runtime on 104 benchmark QP tests. The final iteration was 541.07% faster than the first, handling most tests in under one second. Additionally, it solved four more QP tests for N≥1383, and all outputs for cost and D_x matched the MATLAB reference values.
The Deep Underground Neutrino Experiment and Long-Baseline Neutrino Facility (DUNE-LBNF) are under development at Fermilab since early 2010s [1]. At present, the work is being performed towards a comprehensive review conducted by US Department of Energy (DOE)-the Critical Decision 2 (CD-2)-that is planned to take place in the middle of 2022. The primary scientific objectives of DUNE are to carry out a comprehensive investigation of neutrino oscillations to test CP violation in the lepton sector, determine the ordering of the neutrino masses, and to test the three-neutrino paradigm (electron, muon and tau neutrino). The LBNF will provide a 120-GeV proton beam on a neutrino production target utilizing a new 800-MeV superconducting Linac which is expected to be completed in 2027 [2]. The neutrino beamline, which utilizes a target and horn systems, decay pipe, hadron absorber and other systems, is a core component of the LBNF. At present-as a result of numerous iterations-there exists an optimized design with a 1.5-m graphite target and focusing system consisting of three horns. Further optimization energy deposition and radiological calculations are performed towards CD-2 and beyond. This paper describes results of the most recent MARS15 [3] optimization studies.
During large scale algal biomass cultivation, it is difficult to reliably control relative composition to target levels. Rapid determination of chemical composition is feasible by using near infrared (NIR) spectral data. We sought to build and improve on reliable high-throughput screening prediction method based on partial least squares regression (PLSR) by the application of artificial neural networks (ANN) and associated optimization strategies. The algal biomass sample set was designed and created in an iterative process of culturing in physiologically diverse conditions at the GAI field site, followed by compositional analyses at NREL. The workflow allowed us to identify gaps in compositional space for informing the subsequent cultivation and sampling efforts and generated a high quality set of 210 unique samples with chemical analysis results, spectral scanning data, and cultivation metadata. We observed a significant improvement in the performance of carbohydrate content predictions using an optimized ANN model compared to PLSR, with > 16% reduction in mean absolute percent error (MAPE) when tested on the same set of reserved data. The optimized ANN models for FAME and protein prediction performed exceptionally well with 5.99% and 5.09% MAPE, respectively. Application of these methods to detection and quantification of minor biomass constituents that are relevant to certain product streams has shown positive preliminary results, opening the possibility for extensions to the outputs of this powerful data type. All models are accompanied by prediction uncertainties and unsupervised spectral outlier detection to alert an operator to unreliable spectral data. These tools can be deployed for rapid determination of algal culture status, and cultivation and biomass quality improvement.
The development of novel instrumentation requires an iterative cycle with three stages: design, prototyping, and testing. Recent advancements in simulation and nanofabrication techniques have significantly accelerated the design and prototyping phases. Nonetheless, detector characterization continues to be a major bottleneck in device development. During the testing phase, a significant time investment is required to characterize the device in different operating conditions and find optimal operating parameters. The total effort spent on characterization and parameter optimization can occupy a year or more of an expert's time. In this work, we present a novel technique for automated sensor calibration that aims to accelerate the testing stage of the development cycle. This technique leverages closed-loop Bayesian optimization (BO), using real-time measurements to guide parameter selection and identify optimal operating states. We demonstrate the method with a novel low-noise CCD, showing that the machine learning-driven tool can efficiently characterize and optimize operation of the sensor in a couple of days without supervision of a device expert.
A Documented Safety Analysis (DSA) is a Department of Energy (DOE) construct that defines the extent to which a nuclear facility can be operated safely. It includes a description of hazards, safe boundaries, and hazard controls. The authors assert that a Digital Safety Analysis (DgSA) is far superior to a legacy DSA for several reasons: • The underling database is structured such that it is possible to perform a comprehensive design review and safety analysis by iterating systematically across a hierarchy of linked objects versus a redundant and spotty review by entities of various abilities under unknown resource and schedule constraints. • The analysis of a new design can discover elements that are similar to elements in previous designs. The discovery of similarities is made possible by using the same structure for the underlying database for each new DgSA. The “prior learning” from previous designs is then applied automatically to new designs. • Outputs from the DgSA are from a single source to ensure consistency among various views of the same information. After the DgSA is released, the continued use of a single source implements a configuration management program to ensure consistency between the design basis, the design, the built system, and system procedures. • The development of the DgSA is agile in that any change in a linked object triggers an analysis of impacts on other linked objects and updates of linked objects are made accordingly. After the DgSA is released, the continued maintenance of these links and objects automates the “unreviewed safety question” process.
The US is among seven partner nations in a collaborative effort to design, build, and demonstrate fusion’s ability to be a large-scale carbon free energy source. Each country has its own Domestic Agencies (DA) that contribute directly to the ITER project. US ITER, which is a DOE Office of Science project managed by Oak Ridge National Laboratory, is developing world class engineering solutions to the design, construction, and assembly of the burning plasma experiment that can demonstrate the scientific and technological feasibility of fusion. US ITER’s scope includes completing the preliminary and final design, qualifying materials and processes for manufacture and testing, executing manufacturing, and delivering the Fueling Pellet Injection System (FPIS) to the ITER site for assembly. The US-ITER FPIS system is designed to inject cryogenically frozen pellets of deuterium-tritium (D-T) into the plasma. The FPIS has two main functions: 1. Provide a steady supply of deuterium and tritium fuel, 2. Mitigating the impact of edge localized modes on the plasma facing components. The FPIS will have the capability to reside in three port cells within a tritium second barrier containment cask. Each pellet cask contains three flight tubes linking with penetrations on the torus cryopump housing and vacuum vessel (VV): two for the magnetic high field side (HFS) pellet injection and one for the magnetic low field side (LFS) pellet injection. This paper presents results of the thermal-structural analyses of the FPIS flight tube structural components when subjected to various loads such as electromagnetic (EM) loads, nuclear heating, seismic, and operational, and dynamic shock events. The resulting temperatures and stresses under combined conditions have been found to satisfy the design criteria to ensure safe and reliable operation of the FPIS flight tubes within the vacuum vessel.
The first evidence of widespread chaotic plasma dynamics relevant to the onset of disruptive tearing modes is found in DIII-D tokamak discharges. This evidence is obtained by calculating positive maximal Lyapunov exponents from Mirnov signals using the Rosenstein algorithm, implying the chaotic growth and/or rotation of magnetohydrodynamic modes in DIII-D [Luxon, Nucl. Fusion 42, 614 (2002)] plasmas. Such chaotic dynamics offer an explanation for the random tearing mode onset times previously observed in ITER baseline scenario discharges. Further, the Lyapunov timescales associated with this chaos could inhibit reliable prediction of tearing mode onset beyond the angular momentum confinement timescale; this constraint should inform the design of plasma control systems on ITER.
As electric propulsion technology has improved and mission requirements have changed, a series of Ion Propulsion Module (IPM) design concepts have evolved. The most recent iteration occurred in the NASA-sponsored Halley Comet Rendezvous Mission (HCRM) study of ion drive. Spacecraft system design considerations introduced by the integration of such an IPM as the primary propulsion source are described with reference to the synthesis of the HCRM spacecraft and spacecraft design considerations for other interplanetary applications. IPM interactions with the system (especially telecommunications and science) are found to be manageable. The spacecraft design developed for the HCRM indicates the interface simplicity between the IPM and the spacecraft. Methods are shown for readily applying this IPM to a variety of planetary missions. Methods are also described for the IPM to provide up to 5 kW to the spacecraft for increasing the mission science return
Delivery of Orbital Replacement Units (ORUs) to on-orbit destinations such a the International Space Station (ISS) and the Hubble Space Telescope is an important component of the space program. ORUs are integrated on orbit with space assets to maintain and upgrade functionality. For ORUs comprised of sensitive equipment, the dynamic launch environment drives design and testing requirements, and high frequency random vibrations are generally the cause for failure. Vibration isolation can mitigate the structure-borne vibration environment during launch, and hardware has been developed that can provide a reduced environment for current and future launch environments. Random vibration testing of one ORU to equivalent Space Shuttle launch levels revealed that its qualification and acceptance requirements were exceeded. An isolation system was designed to mitigate the structure-borne launch vibration environment. To protect this ORU, the random vibration levels at 50 Hz must be attenuated by a factor of two and those at higher frequencies even more. Design load factors for Shuttle launch are high, so a metallic load path is needed to maintain strength margins. Isolation system design was performed using a finite element model of the ORU on its carrier with representative disturbance inputs. Iterations on the modelled to an optimized design based on flight proven SoftRide MultiFlex isolators. Component testing has been performed on prototype isolators to validate analytical predictions.