Search NASA⌕ Search

SEARCH · Search NASA

Results for “selection methodology”

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.

At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Design of Quasi-Terminator Orbits near Primitive Bodies

Quasi-terminator orbits are a class of quasi-periodic orbits around a primitive body that exist in the vicinity of the well-known terminator orbits. The inherent stability of quasi-terminator trajectories and their wide variety of viewing geometries make them a very compelling option for primitive body mapping missions. In this paper, we discuss orbit design methodologies for selection of an appropriate quasi-terminator orbit that would meet the needs of a specific mission. Convergence of these orbits in an eccentric, higher-fidelity model is also discussed with an example case at Bennu, the target of the upcoming NASA's OSIRIS-REx mission.

mapping↗
NASA NTRS2018

Building Reliable Printed Circuit Boards - the Lessons Learned

"Printed circuit boards (PCBs) are the baseline for electronics manufacturing upon which electronic components are mounted and formed into electronic systems. PCBs are used in a variety of electronic circuits from simple one-transistor amplifiers to large super computers. A PCB serves three main functions: 1) it provides the necessary mechanical support for the components in the circuit 2) it provides the necessary electrical interconnections, and 3) it bears some form of legend which identifies the components it carries. The failure modes on the PCBs can be categorized in a hierarchical structure, in which the mechanisms and causes are site or location dependant. This one day workshop will discuss a variety of failure mechanisms that effect the functionality of PCBs. These mechanisms can be related to how PCB materials are selected, PCBs are designed, manufactured, tested and used in the field conditions. The workshop will begin with an overview of PCB manufacturing, materials and processes. With the help of examples and case studies, a wide range of failure mechanisms will be discussed, case studies are focused on digital circuits, however some failures in analog, double sided boards are also presented. The workshop then provides the guideline for selection of methodologies for identifying potential failure mechanisms based on the failure history and how a systematic root cause failure analysis of the PCB can result in prevention of future issues."

Sood, Bhanu↗
NASA NTRSDate not supplied

Effect of Geometric Granularity on the Noise Signature of a Full-Scale Large Civil Transport Nose Landing Gear

Results from a comprehensive simulation campaign focused on characterizing the air-frame noise signature of a full-scale Boeing 777-300ER nose landing gear are presented. The as-flown, installed nose gear geometry was used to assess how accurately the selected computational methodology can predict far-field noise before extending the simulation approach to the complete B777-300ER aircraft in landing configuration. To facilitate direct comparisons with experimental data, the simulations were conducted for conditions matching those recorded for a flyby of the same aircraft over the ground-based phased microphone array used during the 2005 Quiet Technology Demonstrator II test. The far-field acoustic footprint of the nose landing gear was computed via a Ffowcs-Williams and Hawkings integral approach, with pressures on the model solid surface or flow quantities on a permeable data surface enclosing the gear used as input. A grid refinement study performed for the baseline gear con-figuration to establish the convergence behavior of the far-field spectrum indicated that the sound pressure levels had converged at frequencies slightly beyond 5 kHz for the finest spatial resolution attempted. To ascertain the effects of geometric granularity on far-field noise, simulations of a defeatured version of the nose gear were undertaken. Comparisons with fully-dressed gear results indicated that finer geometric details add 2–4 dB to the sound pressure levels at mid- to high-frequencies (800 Hz to 5 kHz), suggesting that for accurate noise prediction such details cannot be neglected.

airframe noise↗
NASA NTRS2022

Event Report for The Ethical Artificial Intelligence Quantification Workshop

Artificial Intelligence (AI) is a powerful emerging technology area which requires special attention to using it ethically. AI ethics is still an emerging field, and the partners for this workshop and report seek to move AI ethics discussion ahead by experimenting with ways to measure AI ethics criteria. The following document describes the outcomes and learnings from The Ethical Artificial Intelligence Quantification Workshop held at the National Institute for Aerospace (NIA), Hampton, Virginia on May 12th, 2022. The purpose of the workshop was for participants to evaluate and experiment-with the methodology and process presented by AIEthics.World in cooperation with Intel Corporation. The meeting participants learned about the Ethical AI Certification and Maturity Model™ and applied the methodology to selected notional AI systems. The workshop facilitated the evaluation of the maturity of the AI system according to ethical considerations relevant to NASA, NIA and other participants. The workshop consisted of three main phases. The first phase focused on understanding and summarizing NASA’s ethical approaches, mission and values based on published documentation, discussions and individual insights & opinions of participants. This information was prioritized, weighted, ordered, and quantified in phase two, to formulate an alignment between human values (ethics) and their applicability to AI systems during all lifecycle phases. The first two phases were summarized as a form of ethical genealogy for artificial intelligence, specific to NASA’s ethical approaches. In the third and last phase of the workshop the participants evaluated notional examples of artificial intelligence to qualify and quantify its ability to adhere to the organizational ethics approaches, using the Ethical AI Certification and Maturity Model™. The workshop uses the concept of genealogy, in the traditional sense: the study and traceability of lines of ancestors in the process of evolutionary development from earlier forms. However, as it is applied to an Ethical AI definition, it is providing the insights to the necessary and mandatory traceability of content, data, metrics, telemetry, elements, and structures which are used in the AI’s lifecycle to foster and measure AI ethics in all steps of its lifecycle. The Ethical Artificial Intelligence Quantification Workshop provided NASA with the opportunity to apply the Ethical AI Certification and Maturity Model™, in combination with existing and well-known decision-making and quality control methods to identify the metrics and measurements for an Ethical AI and assess its ethical condition and quality aligned with NASA ethics approaches. The result of the workshop is the capacity for NASA to apply the maturity model assessment to its AI Systems as desired and if necessary, publish the ability of these AI Systems to adhere to the organizational ethical goals. AI ethics frameworks need to be customized for each application domain, for example, individual NASA Mission Directorates. General principles that work in one area such as AI/Machine Learning-based text analysis (the ethics of information-extraction) may need to be adapted for another such as sense-and-avoid decision-making in a flight environment. The workshop was conducted among approximately twenty NASA subject matter experts, so the elements noted above should be considered examples, not definitive NASA ethical AI principles, genealogy, etc. Generating a definitive AI ethics framework for an organization as diverse as NASA would require far more discussion, debate, review, etc. However, the workshop provided valuable insight into mechanisms and processes for quantifying AI ethical qualities.

Artificial Intelligence↗
NASA NTRSDate not supplied

Development of a Test Article to Demonstrate the Long Duration Storage of Liquid Hydrogen via a Two-Stage Active Cooling Approach

A NASA team is developing a test article for the purpose of demonstrating the long duration storage of liquid hydrogen utilizing passive Cryogenic Fluid Management and cryocoolers via a two-stage active cooling approach. Funded by NASA’s Technology Demonstration Mission Program and managed by the Cryogenic Fluid Management Portfolio Project, the team is leveraging demonstrations conducted under pervious NASA activities to develop a fully integrated test article that will demonstrate the zero boil-off storage of liquid hydrogen. This paper discusses the previous activities being leveraged from NASA’s Cryogenic Propellant Storage and Transfer project, the test article design and build, hardware and instrumentation selections, control methodology, and the planned primary and secondary test objectives. The test article assembly and demonstration are both to be conducted in the East Test Area at NASA Marshall Space Flight Center and are currently scheduled for Fiscal Year 2024.

Active Cooling↗
DOE OSTI2019

Assessment of Pre-Irradiation SiC CMC Joint Performance in Representative Cladding Geometries

Silicon carbide fiber reinforced, silicon carbide matrix composites (SiC-SiC) offer strength at high temperatures, corrosion resistance, and stability during irradiation, and are being developed by General Atomics as cladding for accident tolerant fuel (ATF) applications and advanced reactor concepts. Advanced joining techniques capable of withstanding harsh reactor environments are key to enable GA’s SiGAtm SiC-SiC composite. The objective of this work is to obtain joint-specific material properties for assemblies in representative planar and cladding geometries that will allow for the generation of a material properties database and more accurate simulation of SiC joint behavior across arange of temperatures and irradiation conditions. To support this, three different joint formulations are being assessed for mechanical and thermal performance pre and post irradiation in the High Flux Isotope Reactor (HIFR) at ORNL. GA has previously identified its hybrid SiC (HSiC) joint as the most promising and best suited joining approach for cladding applications [1]. Additionally, oxide and transeutectic phase (TEP) joints are being investigated to make the material property database more comprehensive as these joints have previously shown strength resilience under irradiation in planar geometries [2]. The thermal and mechanical data obtained in this work will address vital knowledge gaps, enabling more accurate modeling of joints in SiC-based components for accelerated material qualification.The scope of work presented here focuses on the mechanical and thermal performance of the joint material prior to irradiation in HFIR. Endplug push-out (EPPO) testing to determine joint strength in tube geometries, and shear strength testing for planar geometries have provided a benchmark for pre-irradiation mechanical performance. These results show that all three selected joint methodologies result in cladding joints capable of withstanding the expected joint stresses in a LWR reactor environment [3]. This has been accompanied by He leak testing of the joint regions on tube specimens to assess the suitability of each joint methodology for cladding applications. Here, only the HSiC formulation consistently met critical leak rate requirements suggesting that other joining strategies require additional development. Finally, pre-irradiation thermal testing has been completed to establish a baseline for comparison after irradiation. Subsequent irradiation of these joints types in HFIR will provide further detail on joint material properties and their appropriateness for nuclear applications.

Gonderman, Sean↗
DOE OSTI2021

Economic and Environmental Assessment of Biological Conversions of Agile BioFoundry (ABF) Bio-Derived Chemicals

Bio-derived chemicals are an essential part of the growing bioeconomy. They possess the potential to boost a new domestic bioproduct industry, improve the sustainability of integrated biomanufacturing, and reduce U.S. dependence on fossil energy. The Agile BioFoundry (ABF) consortium, a Department of Energy (DOE)-sponsored collaboration, is investigating biobased pathways to produce advantaged products including advanced biofuels, fuel intermediates, and bioproducts. ABF is integrating advanced computational tools for biological engineering, process design and data analysis, and economic/sustainability modeling tools into a comprehensive and dynamic platform for biomanufacturing of microbes and using them to produce key metabolic intermediates or beachhead molecules which may be derivatized into several distinct bioproducts of industrial interest. In this presentation, we first discuss a methodology to select a single exemplar product molecule to represent each beachhead pathway based on similarities with other end-molecule options (yields/titers/rates, fermentation operation mode, oxygen requirements, general separations challenges, etc.), in order to maintain a reasonable number of cases for rigorous process simulation. We then use techno-economic analysis (TEA) and life-cycle analysis (LCA) to highlight sensitivities and trends around economic performance and environmental footprint, reflecting examples for two selected ABF technology pathways to bio-derived chemicals: 1) adipic acid production via muconic acid fermentation from mixed sugars with Pseudomonas putida and 2) cineole via geranyl diphosphate with Rhodosporidium toruloides. We present multi-variable scan plots highlighting key drivers on costs and greenhouse gas emissions in order to identify the parameter space in which each pathway could ultimately achieve economic and environmental sustainability meeting or exceeding commodity product benchmarks, thus prioritizing future R&D focus areas.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2017

Analysing lessons from experience as part of a project to prepare/train teams to manage potentially stressful crisis situations - 164

Following the presentation of the methodology for making use of Operating Experience (OE) data, implemented as part of a study on preparing teams to manage potentially stressful crisis situations, this paper discusses and enhances the 'Implementing a Learning Organisation (ILO)' model, the aim of which is to organise operating experience for learning purposes. By way of introduction, we first present this model, which is divided into four fields of investigation for organising an OE mechanism to support learning, to pose the question we aim to answer in this paper: how does the field relating to the use of OE in the ILO model help us to turn the experience acquired to good account? With this in mind, we then present the different stages of the methodology for making use of OE. The first stage involves defining the area under examination in line with current best practices. This definition is then used in the second stage, as a basis for developing a framework to guide the analysis of OE. Finally, the third stage of the methodology involves selecting the OE data to be analysed. The findings obtained in the chosen case are then presented and several points are discussed based on this experience. These relate to the following: the acquisition of knowledge on current working situations enabled by OE; the stored data analysis method; and the conditions facilitating the use of OE. (authors)

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1982

Development of test methodology for dynamic mechanical analysis instrumentation

Dynamic mechanical analysis instrumentation was used for the development of specific test methodology in the determination of engineering parameters of selected materials, esp. plastics and elastomers, over a broad range of temperature with selected environment. The methodology for routine procedures was established with specific attention given to sample geometry, sample size, and mounting techniques. The basic software of the duPont 1090 thermal analyzer was used for data reduction which simplify the theoretical interpretation. Clamps were developed which allowed 'relative' damping during the cure cycle to be measured for the fiber-glass supported resin. The correlation of fracture energy 'toughness' (or impact strength) with the low temperature (glassy) relaxation responses for a 'rubber-modified' epoxy system was negative in result because the low-temperature dispersion mode (-80 C) of the modifier coincided with that of the epoxy matrix, making quantitative comparison unrealistic.

Allen, V. R.↗
DOE OSTI2019

Embedded Sensor Development in Metallic Structures for the Transformational Challenge Reactor

The ability to make minimally intrusive measurements of process conditions has tremendous potential for improving system performance and control in applications such as nuclear power generation. Towards this end, emerging and evolving advanced manufacturing methods, such as additive manufacturing, present new opportunities for more seamlessly integrating sensing with structure. This technical report summarizes the progress of work performed to assess the feasibility of embedding commercial off-the-shelf (COTS) sensors in a metallic reactor core using advanced manufacturing methods. The progress of four research and development tasks are documented: 1) A survey of COTS sensors for nuclear applications that are candidates for embedded fabrication, 2) Development of a conceptual framework for investigating the feasibility of sensor embedment, 3) Definition of structural geometries and other characteristics that will represent compelling proof-of-concept, and 4) Preliminary prototyping of embedded sensors. For the purposes of this initial study, nuclear grade K-type thermocouples were selected for investigation of embedment methodologies. This sensor was selected as an initial candidate because it represents one of the simplest sensor configurations that can provide useful process information. A selective laser melting (SLM) additive manufacturing process was used to fabricate structures with complexity representative of the core design of the transformational challenge reactor (TCR) and methods were developed to embed a thermocouple with a complex two-dimensional routing path. There are many challenges associated with embedding sensors during the additive manufacturing process including securing the sensor in the structure, relocating the part in the additive machine if using a “pick and place” sensor placement method, mitigating the potential for powder contamination, optimizing energy deposition parameters to build as closely as possible around the sensor path and improve structural integrity of the part, and tuning energy deposition to mitigate thermally induced warpage of the sensor and part as well as potential for damaging the sensing device. Preliminary results indicate that it is feasible to integrate the sensor while minimally compromising the structural integrity of the part and preserving sensor performance. This first phase of this work focused on developing a workflow for embedding sensors and controlling energy deposition during the additive manufacturing process to better understand the build characteristics around the sensor. Future work will perform more in-depth characterization of prototype parts using X-ray computed tomography and scanning electron microscopy to better understand fabricated structures, performance testing of embedded sensors in high temperature environments, adding new embedded measurement modalities, embedding devices with dissimilar materials in contact with additive powders, and the development of methods for embedding sensors with three-dimensional routing paths.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

High-Penetration Photovoltaic Planning Methodologies

The main objective of this report is to provide an overview of select U.S. utility methodologies for performing high-penetration photovoltaic (HPPV) system planning and impact studies. This report covers the Federal Energy Regulatory Commission's orders related to photovoltaic (PV) power system interconnection, particularly the interconnection processes for the Large Generation Interconnection Procedures and Small Generation Interconnection Procedures. In addition, it includes U.S. state interconnection standards and procedures. The procedures used by these regulatory bodies consider the impacts of HPPV power plants on the networks. Technical interconnection requirements for HPPV voltage regulation include aspects of power monitoring, grounding, synchronization, connection to the overall distribution system, back-feeds, disconnecting means, abnormal operating conditions, and power quality. This report provides a summary of mitigation strategies to minimize the impact of HPPV. Recommendations and revisions to the standards may take place as the penetration level of renewables on the grid increases and new technologies develop in future years.

14 SOLAR ENERGY↗
NASA NTRS1992

Methodology development for evaluation of selective-fidelity rotorcraft simulation

This paper addressed the initial step toward the goal of establishing performance and handling qualities acceptance criteria for realtime rotorcraft simulators through a planned research effort to quantify the system capabilities of 'selective fidelity' simulators. Within this framework the simulator is then classified based on the required task. The simulator is evaluated by separating the various subsystems (visual, motion, etc.) and applying corresponding fidelity constants based on the specific task. This methodology not only provides an assessment technique, but also provides a technique to determine the required levels of subsystem fidelity for a specific task.

Lewis, William D.↗
DOE OSTI2013

Information Gain Based Dimensionality Selection for Classifying Text Documents

Selecting the optimal dimensions for various knowledge extraction applications is an essential component of data mining. Dimensionality selection techniques are utilized in classification applications to increase the classification accuracy and reduce the computational complexity. In text classification, where the dimensionality of the dataset is extremely high, dimensionality selection is even more important. This paper presents a novel, genetic algorithm based methodology, for dimensionality selection in text mining applications that utilizes information gain. The presented methodology uses information gain of each dimension to change the mutation probability of chromosomes dynamically. Since the information gain is calculated a priori, the computational complexity is not affected. The presented method was tested on a specific text classification problem and compared with conventional genetic algorithm based dimensionality selection. The results show an improvement of 3% in the true positives and 1.6% in the true negatives over conventional dimensionality selection methods.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

Rocket-powered single-stage vehicle configuration selection and design

A reusable rocket-powered, single-stage launch vehicle has been designed as a part of NASA's Advanced Manned Launch System (AMLS) study to examine options for a next-generation manned space transportation system. The configuration selection process utilized a response surface methodology for multidisciplinary optimization. The methodology was utilized to determine the minimum dry weight entry vehicle to meet constraints on landing velocity and on subsonic, supersonic, and hypersonic trim and stability. Once the optimum configuration was determined, a multidisciplinary conceptual vehicle design was performed. This paper presents the results of the configuration selection methodology and summarizes the overall conceptual design process with special attention given to the individual disciplines of weights/ sizing, structures/materials, configuration, flight mechanics, aerodynamics, aeroheating, propulsion, and operations.

Stanley, Douglas O.↗
DOE OSTI2014

Fukushima Daiichi Unit 1 Uncertainty Analysis -- Preliminary Selection of Uncertain Parameters and Analysis Methodology

Sandia National Laboratories (SNL) plans to conduct uncertainty analyses (UA) on the Fukushima Daiichi unit (1F1) plant with the MELCOR code. The model to be used was developed for a previous accident reconstruction investigation jointly sponsored by the US Department of Energy (DOE) and Nuclear Regulatory Commission (NRC). However, that study only examined a handful of various model inputs and boundary conditions, and the predictions yielded only fair agreement with plant data and current release estimates. The goal of this uncertainty study is to perform a focused evaluation of uncertainty in core melt progression behavior and its effect on key figures-of-merit (e.g., hydrogen production, vessel lower head failure, etc.). In preparation for the SNL Fukushima UA work, a scoping study has been completed to identify important core melt progression parameters for the uncertainty analysis. The study also lays out a preliminary UA methodology.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Contextualizing Non-Powered Dam Site Selection for Archimedes Screw Turbines: A Methodology for Responsible Archimedes Screw Turbine Conversion at Existing Dams

Non-powered dams represent 97% of dams in the United States and their energy generation potential has not been fully realized. The use of an Archimedes screw turbine to generate power at non-powered dams offers a dual benefit; producing electricity, and acting as downstream fish passage, helping to reconnect previously separated ecosystems. In this study, we assess the technical, environmental, social, and economic feasibility of generating power at non-powered U.S. dam sites using Archimedes screw turbines by integrating mechanical constraints, social impact metrics, proximity to infrastructure, and environmental sensitivity data. Results account for future precipitation predictions and show, between 2024 and 2050, the number of sites where Archimedes screw turbines are viable decreases by one site, but overall generation capacity increases due to increased flow rates across persisting locations. Our analysis identified 82 non-powered dam sites with a mean generation capacity of 49 kW that meet the mechanical requirements for Archimedes screw turbine technology in 2024. Our analysis presents a framework for considering social, environmental, and economic impacts of specific turbine technologies to convert non-powered dams to generate power.

Archimedes screw turbine↗