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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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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

Unsteady transonic aerodynamic and aeroelastic calculations about airfoils and wings

The development and application of transonic small disturbance codes for computing two dimensional flows, using the code ATRAN2, and for computing three dimensional flows, using the code ATRAN3S, are described. Calculated and experimental results are compared for unsteady flows about airfoils and wings, including several of the cases from the AGARD Standard Aeroelastic Configurations. In two dimensions, the results include AGARD priority cases for the NACA 64A006, NACA 64A010, NACA 0012, and MBB-A3 airfoils. In three dimensions, the results include flows about the F-5 wing, a typical wing, and the AGARD rectangular wings. Viscous corrections are included in some calculations, including those for the AGARD rectangular wing. For several cases, the aerodynamic and aeroelastic calculations are compared with experimental results.

Goorjian, P. M.↗
NASA NTRS1985

Unsteady transonic aerodynamic and aeroelastic calculations about airfoils and wings

The development and application of transonic small disturbance codes for computing two dimensional flows, using the code ATRAN2, and for computing three dimensional flows, using the code ATRAN3S, are described. Calculated and experimental results are compared for unsteady flows about airfoils and wings, including several of the cases from the AGARD Standard Aeroelastic Configurations. In two dimensions, the results include AGARD priority cases for the NACA 54A006, NACA 64A010, NACA 0012, and MBB-A3 airfoils. In three dimensions, the results include flow about the F-5 wing, a typical wing, and the AGARD rectangular wings. Viscous corrections are included in some calculations, including those for the AGARD rectangular wing. For several cases, the aerodynamic and aeroelastic calculations are compared with experimental results.

Goorjian, P. M.↗
NASA NTRS2023

Leveraging Automated Fiber Placement Computer Aided Process Planning Framework for Defect Validation and Dynamic Layup Strategies

Process planning represents an essential stage of the Automated Fiber Placement (AFP) workflow. It develops useful and efficient machine processes based upon the working material, composite design, and manufacturing resources. The current state of process planning requires a high degree of interaction from the process planner and could greatly benefit from increased automation. Therefore, a list of key steps and functions are created to identify the more difficult and time-consuming phases of process planning. Additionally, a set of metrics must exist by which to evaluate the effectiveness of the manufactured laminate from the machine code created during the Process Planning stage. Layup strategies, in addition to dog ears, stagger shifts, steering constraints, and starting points, represented the group of functions labeled as process optimization and ranked the highest in terms of priority for automation. The laminates resulting from the selected parameters are evaluated through the occurrences of principal defect metrics such as fiber gaps, overlaps, angle deviation and steering violations. This document presents an automated software solution to the layup strategy and starting point selection phase of process planning. A series of ply scenarios are generated with variations of these ply parameters and evaluated according to a set of metrics entered by the Process Planner. These metrics are generated through use of the Analytical Hierarchy Process (AHP), where relative importance between each of the fiber features are defined. The ply scenarios are selected which reduce the overall fiber feature scores based on the defects the Process Planner wishes to minimize.

HiCAM↗
NASA NTRS2023

Python Based Plume Dynamics Estimation Tool (PyPDET) Rapid Plume Strike Analysis for RPOD Maneuvers in Deep Space Operations

I worked as a NASA Intern during the Summer 2023 term in the DS-00 division under the supervision of my mentor, Dr. Jonathan Pitt. Our goal was to build on our previous work from 2022 to develop a plume strike estimation tool using a prescribed physics methodology and model plume impingement effects while considering the dynamics of a rendezvous, operations, proximity, and docking (RPOD) maneuver. This tool supports previously configured CFD-DSMC calculations by allowing for rapid analysis of initial designs using a low-fidelity source flow model. Engineers can then use the high-fidelity CFD-DSMC tool to consolidate results as they work towards finalizing a design. This year’s project was focused on developing a software application that other engineers would be using in their analysis. Thus, the user’s experience was considered in the development of this application. Proper documentation, testability, and modularity of the codebase was our priority. For example, the project included auto documentation procedures to start building towards a User Manual, while also including dedicated demonstration cases for more explicit communication of functionality. Also, this project included a framework for testing the source code for future developments. Additionally, care was taken to develop the code using an Object-Oriented Programming approach. Thus, allowing for a modular extensibility of functionality in anticipation of future developments. The core work of this project was developing an algorithm that would transform the visiting vehicle and associated thruster data according to the kinematics described in the jet firing history. It would then calculate the estimated plume strikes on two of the target vehicles and write data accordingly into a VTK file. Summer work is to conclude by developing and presenting a PowerPoint slide deck at the intern exit briefing on August 11 th , 2023. Once the model for simple plume strike calculations is developed and tested there are several avenues to explore to continue development of this tool. These are also discussed in this report.

Plume Impingement↗
DOE OSTI2025

FluxRETAP: a REaction TArget Prioritization genome-scale modeling technique for selecting genetic targets

MOTIVATION: Metabolic engineering is rapidly evolving as a result of new advances in synthetic biology tools and automation platforms that enable high throughput strain construction, as well as the development of machine learning tools (ML) for biology. However, selecting genetic engineering targets that effectively guide the metabolic engineering process is still challenging. ML can provide predictive power for synthetic biology, but current technical limitations prevent the independent use of ML approaches without previous biological knowledge. RESULTS: Here, we present FluxRETAP, a simple and computationally inexpensive method that leverages the prior mechanistic knowledge embedded in genome-scale models for suggesting targets for genetic overexpression, downregulation or deletion, with the final goal of increasing the production of a desired metabolite. This method can provide a list of desirable engineering targets that can be combined with current ML pipelines. FluxRETAP captured 100% of reaction targets experimentally verified to improve Escherichia coli isoprenol production, 50% of targets that experimentally improved taxadiene production in E. coli and ∼60% of genetic targets from a verified minimal constrained cut-set in Pseudomonas putida, while providing additional high priority targets that could be tested. Overall, FluxRETAP is an efficient algorithm for identifying a prioritized list of testable genetic and reaction targets. AVAILABILITY AND IMPLEMENTATION: FluxRETAP is implemented in python and released under the creative commons license. The implementation and code are freely available at: https://github.com/JBEI/FluxRETAP.

Czajka, Jeffrey J↗
NASA NTRS2005

Impact of Lunar Dust on the Exploration Initiative

From the Apollo era it is known that dust on the Moon can cause serious problems for exploration activities. Such problems include adhering to clothing and equipment, reducing external visibility on landings, and causing difficulty to breathing and vision within the spacecraft. An important step in dealing with dust-related problems is to understand how dust grains behave in the lunar environment. All astronauts who walked on the Moon reported difficulties with lunar dust. Eugene Cernan, commander of Apollo 17, stated that one of the most aggravating, restricting facets of lunar surface exploration is the dust and its adherence to everything no matter what kind of material, whether it be skin, suit material, metal, no matter what it be and it's restrictive friction-like action to everything it gets on. Dust has also been highlighted as a priority by the Mars Exploration Program Assessment Group (MEPAG): 1A. Characterize both aeolian dust and particulates that would be kicked up from the martian regolith by surface operations of a human mission with fidelity sufficient to establish credible engineering simulation labs and/or software codes on Earth. We shall briefly describe the properties of lunar dust and its impact on the Apollo astronauts, and then summarize three main problems areas for understanding its behavior: Dust Adhesion and Abrasion, Surface Electric Fields and Dust Transport. These issues are all inter-related and must be well understood in order to minimize the impact of dust on lunar surface exploration.

Stubbs, T. J.↗
DOE OSTI2025

JACC.shared: Leveraging HPC Metaprogramming and Performance Portability for Computations That Use Shared Memory GPUs

In this work, we present JACC.shared, a new feature of Julia for ACCelerators (JACC), which is the performanceportable and metaprogramming model of the just-in-time and LLVM-based Julia language. This new feature allows JACC applications to leverage the high-performance computing (HPC) capabilities of high-bandwidth, on-chip GPU memory. Historically, exploiting high-bandwidth, shared-memory GPUs has not been a priority for high-level programming solutions. JACC.shared covers that gap for the first time, thereby providing a highlevel, portable, and easy-to-use solution for programmers to exploit this memory and supporting all current major accelerator architectures. Well-known HPC and AI workloads, such as multi/hyperspectral imaging and AI convolutions, have been used to evaluate JACC.shared on two exascale GPU architectures hosted by some of the most powerful US Department of Energy supercomputers: Perlmutter (NVIDIA A100) and Frontier (AMD MI250X). The performance evaluation reports speedup of up to 3.5× by adding only one line of code to the base codes, thus providing important accelerators in a simple, portable, and transparent way and elevating the programming productivity and performance-portability capabilities for Julia/JACC HPC, AI, and scientific applications.

Valero Lara, Pedro [ORNL] (ORCID:0000000214794310)↗
DOE OSTI2026

Facilitating Data Collection of Maintenance Events to Populate the Hydrogen Component Reliability Database (HyCReD)

The Hydrogen Component Reliability Database (HyCReD) is a collaborative project between the National Renewable Energy Laboratory, the University of Maryland, and hydrogen stakeholders to improve safety and reliability for hydrogen facilities by implementing component reliability data taxonomies that support hydrogen infrastructure failure rate analysis. The project aims to quantify failure rates of hydrogen components through high-quality data collection and analysis on root causes and maintenance needed. HyCReD provides a common database for cataloging hydrogen component failures which exists for reliability research in many other mature industries [2]. The database fills a gap for the hydrogen community by providing a scientifically rigorous approach to quantitative risk assessment (QRA), prognostic health management (PHM), and reliability-centered maintenance (RCM) analysis. High level results will be aggregated and anonymized to protect company sensitive information; detailed results will be used to help address issues of hydrogen components. These advanced analytics will support accelerated deployment of hydrogen infrastructure by enabling better: design and safety of projects (safety codes and standards development), infrastructure reliability and cost (component failure rates, maintenance protocols), and component R&D needs (robust supply chain). A key to a successful HyCReD implementation is facilitating the ease of reporting and data quality in the database that can be used for analysis. Maintenance data was a previously identified gap in initial efforts to populate and validate the database taxonomies [3]. Collection of maintenance data will be instrumental in identifying failure modes and rates, identifying incipient component failures or reduced performance, cataloging best practices for maintenance routines and methods for prognostic health management, and quantifying the risk and effect of different failure modes. Several key priorities are identified for streamlined data collection to achieve quality and detailed failure data: Applicability, Ease of Use, Accessibility, and Information Security. The HyCReD team has now begun deployment of the database to several companies and groups that have signed non-disclosure agreements to facilitate the data collection of failures in industry hydrogen refueling station infrastructure. This paper will provide an update into the process of HyCReD deployment including the development of a coding guide for facility personnel to reference and ensure data quality and consistency from one station to another as well as implementation of contextually dependent data fields of system taxonomy and formatted entries to provide ease of use. The goal is to communicate the lessons learned from the roll-out to technicians and engineers in the field, and the addition of need for high level of security to protect all stakeholders.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2013

Uncertainty Determination for Aeroheating in Uranus and Saturn Probe Entries by the Monte Carlo Method

The 2013-2022 Decaedal survey for planetary exploration has identified probe missions to Uranus and Saturn as high priorities. This work endeavors to examine the uncertainty for determining aeroheating in such entry environments. Representative entry trajectories are constructed using the TRAJ software. Flowfields at selected points on the trajectories are then computed using the Data Parallel Line Relaxation (DPLR) Computational Fluid Dynamics Code. A Monte Carlo study is performed on the DPLR input parameters to determine the uncertainty in the predicted aeroheating, and correlation coefficients are examined to identify which input parameters show the most influence on the uncertainty. A review of the present best practices for input parameters (e.g. transport coefficient and vibrational relaxation time) is also conducted. It is found that the 2(sigma) - uncertainty for heating on Uranus entry is no more than 2.1%, assuming an equilibrium catalytic wall, with the uncertainty being determined primarily by diffusion and H(sub 2) recombination rate within the boundary layer. However, if the wall is assumed to be partially or non-catalytic, this uncertainty may increase to as large as 18%. The catalytic wall model can contribute over 3x change in heat flux and a 20% variation in film coefficient. Therefore, coupled material response/fluid dynamic models are recommended for this problem. It was also found that much of this variability is artificially suppressed when a constant Schmidt number approach is implemented. Because the boundary layer is reacting, it is necessary to employ self-consistent effective binary diffusion to obtain a correct thermal transport solution. For Saturn entries, the 2(sigma) - uncertainty for convective heating was less than 3.7%. The major uncertainty driver was dependent on shock temperature/velocity, changing from boundary layer thermal conductivity to diffusivity and then to shock layer ionization rate as velocity increases. While radiative heating for Uranus entry was negligible, the nominal solution for Saturn computed up to 20% radiative heating at the highest velocity examined. The radiative heating followed a non-normal distribution, with up to a 3x variation in magnitude. This uncertainty is driven by the H(sub 2) dissociation rate, as H(sub 2) that persists in the hot non-equilibrium zone contributes significantly to radiation.

Palmer, Grant↗
NASA NTRSDate not supplied

Combustion and Emissions Analysis of Alternatives

NASA’s Aeronautics Research Mission Directorate requested an analysis of alternatives (AoA) study on the following three competencies in 2020: subsonic transport acoustics, combustion and emissions, and aircraft icing. This presentation will address details specific to the combustion and emissions analysis of alternatives study. The basic process used for during the AoA study in shown in Figure 1. Figure 1. Flow chart of the Analysis of Alternative process used in this study. The combustion study team was multidisciplinary, including a wide range perspectives and areas of expertise. Inputs were collected from within NASA and a wide range of external stakeholders, including aircraft engine companies, aircraft airframe companies and other government agencies. Eight future realities for aviation were developed in preparation for the applying the AoA process, such as future realities with increased or decrease airline traffic, greater emissions stringency, or a revolution in energy infrastructure (such as hydrogen usage). Based on the inputs collected, over seventy technical elements applicable to combustion and emissions research were developed. To rank the importance of these technical elements for each future reality, a set of evaluation criterion were developed that can be generally characterized as environmental impacts, technologies enabling reduced fuel burn, and elements requiring significant NASA involvement or having significant industry pull. Using in-house codes to apply the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) methodology, as well performing consistency checks and other analysis by the study team, a ranked set of technical elements was generated. Several research needs were identified and analyzed to determine the highest priorities for potential research by NASA in the combustion and emissions area. Results from the study will be presented.

combustion↗
NASA NTRS1994

Constraint based scheduling for the Goddard Space Flight Center distributed Active Archive Center's data archive and distribution system

The Goddard Space Flight Center (GSFC) Distributed Active Archive Center (DAAC) has been operational since October 1, 1993. Its mission is to support the Earth Observing System (EOS) by providing rapid access to EOS data and analysis products, and to test Earth Observing System Data and Information System (EOSDIS) design concepts. One of the challenges is to ensure quick and easy retrieval of any data archived within the DAAC's Data Archive and Distributed System (DADS). Over the 15-year life of EOS project, an estimated several Petabytes (10(exp 15)) of data will be permanently stored. Accessing that amount of information is a formidable task that will require innovative approaches. As a precursor of the full EOS system, the GSFC DAAC with a few Terabits of storage, has implemented a prototype of a constraint-based task and resource scheduler to improve the performance of the DADS. This Honeywell Task and Resource Scheduler (HTRS), developed by Honeywell Technology Center in cooperation the Information Science and Technology Branch/935, the Code X Operations Technology Program, and the GSFC DAAC, makes better use of limited resources, prevents backlog of data, provides information about resources bottlenecks and performance characteristics. The prototype which is developed concurrently with the GSFC Version 0 (V0) DADS, models DADS activities such as ingestion and distribution with priority, precedence, resource requirements (disk and network bandwidth) and temporal constraints. HTRS supports schedule updates, insertions, and retrieval of task information via an Application Program Interface (API). The prototype has demonstrated with a few examples, the substantial advantages of using HTRS over scheduling algorithms such as a First In First Out (FIFO) queue. The kernel scheduling engine for HTRS, called Kronos, has been successfully applied to several other domains such as space shuttle mission scheduling, demand flow manufacturing, and avionics communications scheduling.

Short, Nick, Jr.↗
DOE OSTI2024

Systematic and objective evaluation of Earth system models: PCMDI Metrics Package (PMP) version 3

Systematic, routine, and comprehensive evaluation of Earth system models (ESMs) facilitates benchmarking improvement across model generations and identifying the strengths and weaknesses of different model configurations. By gauging the consistency between models and observations, this endeavor is becoming increasingly necessary to objectively synthesize the thousands of simulations contributed to the Coupled Model Intercomparison Project (CMIP) to date. The Program for Climate Model Diagnosis and Intercomparison (PCMDI) Metrics Package (PMP) is an open-source Python software package that provides quick-look objective comparisons of ESMs with one another and with observations. The comparisons include metrics of large- to global-scale climatologies, tropical inter-annual and intra-seasonal variability modes such as the El Niño–Southern Oscillation (ENSO) and Madden–Julian Oscillation (MJO), extratropical modes of variability, regional monsoons, cloud radiative feedbacks, and high-frequency characteristics of simulated precipitation, including its extremes. The PMP comparison results are produced using all model simulations contributed to CMIP6 and earlier CMIP phases. An important objective of the PMP is to document the performance of ESMs participating in the recent phases of CMIP, together with providing version-controlled information for all datasets, software packages, and analysis codes being used in the evaluation process. Among other purposes, this also enables modeling groups to assess performance changes during the ESM development cycle in the context of the error distribution of the multi-model ensemble. Quantitative model evaluation provided by the PMP can assist modelers in their development priorities. In this paper, we provide an overview of the PMP, including its latest capabilities, and discuss its future direction.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2021

Demystification of Processes that Effect Prioritization of Space Radiation Element Research

In an effort to demystify how research funding priorities are established , the Space Radiation Element will present an introduction to the Human Space Risk Board (HSRB) framework that is that used to inform Human System Risk and can be found at https://humanresearchroadmap.nasa.gov/Risks/. These risks are based on the consequences of hazards (space radiation, altered gravity, isolation & confinement, distance from earth and hostile/closed environment) a human body is exposed to during spaceflight. The HSRB regularly evaluates risks to humans in space which includes updating the knowledge base to reflect emerging research, the development of effective countermeasures, and evolving operational approaches toward addressing those risks. To increase understanding and clarity, this talk will step through how risks (with the focus on Risk of Radiation Carcinogenesis) are assigned a rating (and color code) based on design reference missions, likelihood, and consequence. Further, The Space Radiation Element will discuss how risks, including the magnitude/rating, required technical deliverables, and expected products from current research efforts affect our element strategy and prioritization of research. In addition, navigation of the publicly available www.nasa.gov/hrp, will be demonstrated to inform principal investigators where this information can be readily accessed. Our primary objectives for this presentation/demonstration are to demystify The Space Radiation Element’s internal processes and to educate researchers concerning publicly available documents that can be used to better align their proposed objectives with Element priorities.

J A Zawaski↗
NASA NTRS2013

Electrical Impedance Tomography Technology: 2013 Center Innovation Fund Final Report

Electrical impedance tomography is a medical noninvasive imaging technology which has advantages over other medical imaging technologies for medically safe long term real time internal imaging monitoring applications in human patients. The technology is much more compact, portable, low power and potentially more low cost compared to other medical image technologies, making it very well suited for medical aerospace and spaceflight applications. EIT technology’s main drawback has been low image resolution, and consequently improving EIT resolution is the primary research goal, as well as increasing imaging speed for real time animation imaging. In a relatively short time the BERL group has brought together design plans, technical resources and has built and tested hardware with the purpose of improving EIT imaging technology. EIT prototype system development plans and system designs have been made to target needed EIT technical improvement in electronic and computer hardware as well as EIT software technology. New hardware design and fabrication resources and technologies have been brought together through resourceful use of existing equipment and software at BERL, and a significant advance has been made in custom electronic hardware prototyping capabilities in collaboration with EFAL, for mutual benefit for both NASA KSC laboratories. BERL has gained significant EIT software capability and tested EIT imaging algorithm code through collaboration with an internationally recognized EIT software development and research forum. A new custom workstation has been developed, built and tested using internal resources, equipment and expertise, that includes a new state-of-the-art massively parallel technology that is commercially available. Custom prototype hardware has been designed and tested, a high priority electronic design, key to improving electronic performance and image quality, has been researched and tested in four designs, with a summary of test results of the selected design illustrated here. The selected design performance exceeds the developed EIT design hardware specifications.

Michael R Lapointe↗
NASA NTRS1984

Chemical application of diffusion quantum Monte Carlo

The diffusion quantum Monte Carlo (QMC) method gives a stochastic solution to the Schroedinger equation. This approach is receiving increasing attention in chemical applications as a result of its high accuracy. However, reducing statistical uncertainty remains a priority because chemical effects are often obtained as small differences of large numbers. As an example, the single-triplet splitting of the energy of the methylene molecule CH sub 2 is given. The QMC algorithm was implemented on the CYBER 205, first as a direct transcription of the algorithm running on the VAX 11/780, and second by explicitly writing vector code for all loops longer than a crossover length C. The speed of the codes relative to one another as a function of C, and relative to the VAX, are discussed. The computational time dependence obtained versus the number of basis functions is discussed and this is compared with that obtained from traditional quantum chemistry codes and that obtained from traditional computer architectures.

Reynolds, P. J.↗
NASA NTRSDate not supplied

Where IMERG Goes Next: Version 08 and Beyond

With the Version 07 (V07) Integrated Multi-satellitE Retrievals for GPM (IMERG) algorithm finalized and production initiated, the focus turns to enhancements for Version 08. These include innovations not included in V07 due to time constraints, plus issues revealed by the initial V07 products. One high priority is to evaluate and revise the schemes in V07 that rectify temporal artifacts caused by the time interpolation that fills the gaps between the various passive microwave (PMW) sensor overpasses. A second priority is to improve the homogeneity between the TRMM and GPM eras by characterizing differences between the two eras, determining the causes of these differences, and applying corrections as feasible, perhaps by enforcing spatial scale consistency (an overarching issue). Certainly, we must account for GPROF and the Combined Radar-Radiometer Algorithm converting to Machine Learning schemes in V08. Other priority topics include additional automated quality control for artifacts in the IR brightness temperatures and PMW precipitation fields, revisions to the specification algorithm for the probability of liquid precipitation, and accommodating new PMW sensors, which include the next generation of small-sats. We also consider the post-V08 landscape; the final GPM reprocessing will be restricted to fixing known code or algorithmic errors. Nonetheless, there are several data sources on the horizon to consider, including more small-sat PMW radiometers, AVHRR-based precipitation estimates (most useful in high latitudes), and the ISCCP-Next Generation and GEO-Ring projects that could provide easy access to multiple geosynchronous satellite channels and enable significantly improved algorithms compared to GEO-IR alone.

George J. Huffman↗
NASA NTRS1994

Formal Methods Demonstration Project for Space Applications

Requirements and design specifications are a high priority candidate for better software engineering techniques. Most hazardous software safety errors found during system integration and test of two NASA spacecraft were the result of requirements discrepancies or interface specifications. The highest density of major defects found through the use of software inspections was during the requirements phase. This was seven times higher than the density of major defects found in code inspections. Requirements errors are between 10 and 100 times more costly to fix at later phases of the software lifecycle than at the requirements phase itself. One study found that early lifecycle errors are the most likely to lead to catastrophic failures.

critical↗
NASA NTRS1989

A real-time expert system for self-repairing flight control

An integrated environment for specifying, prototyping, and implementing a self-repairing flight-control (SRFC) strategy is described. At an interactive workstation, the user can select paradigms such as rule-based expert systems, state-transition diagrams, and signal-flow graphs and hierarchically nest them, assign timing and priority attributes, establish blackboard-type communication, and specify concurrent execution on single or multiple processors. High-fidelity nonlinear simulations of aircraft and SRFC systems can be performed off-line, with the possibility of changing SRFC rules, inference strategies, and other heuristics to correct for control deficiencies. Finally, the off-line-generated SRFC can be transformed into highly optimized application-specific real-time C-language code. An application of this environment to the design of aircraft fault detection, isolation, and accommodation algorithms is presented in detail.

Gaither, S. A.↗