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At least 1,441 records · Page 80

MSD CoP Webinar: AI and Extreme Events - Overcoming Data Challenges for Improved Characterization of Climate Extremes

Context: This webinar was hosted by the MultiSector Dynamics Community of Practice (MSD CoP; https://multisectordynamics.org). Abstract: Artificial Intelligence (AI) models require large volumes of data for training and testing. Data requirements present challenges for using AI to explore extreme events with limited observational data. This webinar will showcase two innovative methods developed by part of the European Climate Intelligence (CLINT) project to overcome data challenges and harness AI to improve our understanding of climate extremes. Dr. Ascenso will present his research on data augmentation methods to improve estimates of tropical cyclones using satellite data. His presentation will review established methods for data augmentation and explore opportunities and challenges for using generative AI to generate images of extreme, life-threatening tropical cyclones. Next, Dr. Plesiat will present his research on deep learning techniques to overcome limited observational data sets. His presentation will illustrate deep learning methods to develop AI reconstructions of four climate indices across Europe. Presenters : Dr. Guido Ascenso (post-doctoral researcher, Politecnico di Milano); Dr. Étienne Plésiat (German Climate Computing Centre - DKRZ) Moderator(s): Stefano Galelli (MSD CoP WG Co-Lead), David Gold (MSD CoP WG Co-Lead), Jillian Sturtevant (MSD CoP WG Communications Officer), Matteo Giuliani (Politecnico di Milano, MSD CoP WG Member, Moderator and Organizer) This webinar was held on: October 11, 2024 from 11AM - 1PM ET

AI↗

Damping characterization in large structures

This research project has as its main goal the development of methods for selecting the damping characteristics of components of a large structure or multibody system, in such a way as to produce some desired system damping characteristics. The main need for such an analytical device is in the simulation of the dynamics of multibody systems consisting, at least partially, of flexible components. The reason for this need is that all existing simulation codes for multibody systems require component-by-component characterization of complex systems, whereas requirements (including damping) often appear at the overall system level. The main goal was met in large part by the development of a method that will in fact synthesize component damping matrices from a given system damping matrix. The restrictions to the method are that the desired system damping matrix must be diagonal (which is almost always the case) and that interbody connections must be by simple hinges. In addition to the technical outcome, this project contributed positively to the educational and research infrastructure of Tuskegee University - a Historically Black Institution.

Eke, Fidelis O.↗

Projection algorithm for state preparation on quantum computers

We present an efficient method to prepare states of a many-body system on quantum hardware, first isolating individual quantum numbers and then using time evolution to isolate the energy. Our method in its simplest form requires only one additional auxiliary qubit. The total time evolved for an accurate solution is proportional to the ratio of the spectrum range of the trial state to the gap to the lowest excited state, a substantial improvement over other projection algorithms, and the accuracy increases exponentially with the time evolved. Isolating the quantum numbers is efficient because of the known eigenvalues and increases the gap thus shortening the propagation time required. The success rate of the algorithm, or the probability of producing the desired state, is a simple function of measurement times and phases and is dominated by the square overlap of the original state to the desired state. We present examples from the nuclear shell model and the Heisenberg model. In conclusion, we compare this algorithm to previous algorithms for short evolution times and discuss potential further improvements.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

TPSAS-NF1676L-32030-DND

Composite structures are often difficult to inspect due to the anisotropic nature of the material systems and the range of flaws and defects that can arise in the manufacturing process. NASA?s Advanced Composites Project, a public-private partnership between government, universities and industry, seeks to address improved methods, tools, and protocols to reduce the development and certification timeline for composite materials and structures. The rapid inspection of composites is one of the three focused research areas of the project. One deliverable of the project is to develop an NDE Methods and Capabilities Handbook. This Handbook provides a publically available guidance document that facilitates the selection of appropriate NDE techniques and provides recommended protocols for detecting and characterizing common flaw types in solid laminate polymer matrix composite (PMC) structures. The Handbook will reduce the time required to develop qualified inspection processes for composite aircraft structures during the development, certification, and manufacturing phases by providing a reference that helps minimize trial and error and provides guidance on best practices, techniques, and settings, for specific flaw types and geometries. The Handbook will include an NDE Guidance Matrix that provides an applicability rating for NDE techniques as they apply to given flaw types. NDE techniques will include, but is not limited to ultrasound, laser based ultrasound, infrared thermography, and x-ray CT. Flaw types will include, but are not limited to porosity, delamination, voids, AFP defects and impact damage. The Handbook will contain details that support the applicability rating including, but not limited to, specimen details, inspection parameters, data analysis techniques, inspection efficiency (speed & cost), and limitations. This presentation will describe key Handbook activities with examples of the techniques and flaw types examined by the Advanced Composite Consortium members.

Patricia A Howell↗

An improved method of Nusselt number calculation

A novel method for calculating the Nusselt number, Nu, in a steady-state Rayleigh-Benard convection problem is presented, in which calculations are done for a square box with constant temperature, free-slip boundary conditions at the top and bottom, and a reflection symmetry along the side walls. The element heat flux is obtained by averaging over the entire element; element heat fluxes are then projected to the adjacent nodes. Compared with previous methods, the approach reduces the calculated depth variation in horizontally averaged flux by more than a factor of 10 and shows more rapid convergence of Nu as a function of grid size.

Ho-Liu, Phyllis↗

Advanced Interactive Display Formats for Terminal Area Traffic Control

This research project deals with an on-line dynamic method for automated viewing parameter management in perspective displays. Perspective images are optimized such that a human observer will perceive relevant spatial geometrical features with minimal errors. In order to compute the errors at which observers reconstruct spatial features from perspective images, a visual spatial-perception model was formulated. The model was employed as the basis of an optimization scheme aimed at seeking the optimal projection parameter setting. These ideas are implemented in the context of an air traffic control (ATC) application. A concept, referred to as an active display system, was developed. This system uses heuristic rules to identify relevant geometrical features of the three-dimensional air traffic situation. Agile, on-line optimization was achieved by a specially developed and custom-tailored genetic algorithm (GA), which was to deal with the multi-modal characteristics of the objective function and exploit its time-evolving nature.

Grunwald, Arthur J.↗

Advanced Interactive Display Formats for Terminal Area Traffic Control

This research project deals with an on-line dynamic method for automated viewing parameter management in perspective displays. Perspective images are optimized such that a human observer will perceive relevant spatial geometrical features with minimal errors. In order to compute the errors at which observers reconstruct spatial features from perspective images, a visual spatial-perception model was formulated. The model was employed as the basis of an optimization scheme aimed at seeking the optimal projection parameter setting. These ideas are implemented in the context of an air traffic control (ATC) application. A concept, referred to as an active display system, was developed. This system uses heuristic rules to identify relevant geometrical features of the three-dimensional air traffic situation. Agile, on-line optimization was achieved by a specially developed and custom-tailored genetic algorithm (GA), which was to deal with the multi-modal characteristics of the objective function and exploit its time-evolving nature.

Grunwald, Arthur J.↗

A Non-Invasive Approach for Elucidating the Spatial Distribution of In Situ Stress in Deep Subsurface Geologic Formations Considered for CO 2 Storage (Task 5 Report Field Scale Stress Modeling)

This report describes research accomplishments achieved with funding provided through Department of Energy (DOE) Contract DE-FE0031686, for the project “A Non-Invasive Approach for Elucidating the Spatial Distribution of In Situ Stress in Deep Subsurface Geologic Formations Considered for CO 2 Storage.” The purpose of this DOE funding is to develop non-invasive methods to obtain important information about subsurface stresses. The overall research goal of the project was to develop and improve methods for determining the spatial distribution of stresses, including magnitude and orientation of the three principal stress components in the subsurface, based on new methods that extract stress information from seismic data combined with well measurements, extended with well tests and logs, and unified in a numerical model that permits computation of the full stress tensor throughout the domains under investigation.

58 GEOSCIENCES↗

Monitoring Areal Snow Cover Using NASA Satellite Imagery

The objective of this project is to develop products and tools to assist in the hydrologic modeling process, including tools to help prepare inputs for hydrologic models and improved methods for the visualization of streamflow forecasts. In addition, this project will facilitate the use of NASA satellite imagery (primarily snow cover imagery) by other federal and state agencies with operational streamflow forecasting responsibilities. A GIS software toolkit for monitoring areal snow cover extent and producing streamflow forecasts is being developed. This toolkit will be packaged as multiple extensions for ArcGIS 9.x and an opensource GIS software package. The toolkit will provide users with a means for ingesting NASA EOS satellite imagery (snow cover analysis), preparing hydrologic model inputs, and visualizing streamflow forecasts. Primary products include a software tool for predicting the presence of snow under clouds in satellite images; a software tool for producing gridded temperature and precipitation forecasts; and a suite of tools for visualizing hydrologic model forecasting results. The toolkit will be an expert system designed for operational users that need to generate accurate streamflow forecasts in a timely manner. The Remote Sensing of Snow Cover Toolbar will ingest snow cover imagery from multiple sources, including the MODIS Operational Snowcover Data and convert them to gridded datasets that can be readily used. Statistical techniques will then be applied to the gridded snow cover data to predict the presence of snow under cloud cover. The toolbar has the ability to ingest both binary and fractional snow cover data. Binary mapping techniques use a set of thresholds to determine whether a pixel contains snow or no snow. Fractional mapping techniques provide information regarding the percentage of each pixel that is covered with snow. After the imagery has been ingested, physiographic data is attached to each cell in the snow cover image. This data can be obtained from a digital elevation model (DEM) for the area of interest.

Harshburger, Brian J.↗

Alternating Direction Decomposition with Strong Bounding and Convexification (ADDSBC) for Solving Security Constrained AC Unit Commitment Problems

This project aims to develop efficient and robust computational methods for solving the security-constrained unit commitment and alternating current optimal power flow problem (SC-UC-ACOPF). The SC-UC-ACOPF problem is at the center of the short-term operation of the U.S. Power Grid. It is solved every week, every day, and every 10 minutes to plan for the optimal action of electricity generation and consumption by minimizing the generation cost and maintaining power system reliability against potential disruptions of equipment failures. In mathematical terms, SC-UC-ACOPF is a challenging large-scale mixed-integer nonlinear optimization model. This means that the decisions involve both discrete variables, e.g. the turning on and off of generators and switching of transmission lines and transformers, and continuous decisions, e.g. the amount of energy generated by each generator and the power flows in the power grid. The physics of the power flow is described by nonlinear equations involving real and reactive power and bus voltages. Another key feature is the large number of contingencies, i.e. the system needs to stay reliable in face of failure of any one equipment, such as transmission lines and generators. The U.S. power grids are extremely complicated and large scale with more than 5,000 generators, 50,000 buses, and 100,000 high-voltage transmission lines, making the SC-UC-ACOPF a very large-scale computation challenge. The research developed in this project aims to solve the SC-UC-ACOPF problems in the three timescales, i.e. weekly, daily, and every 10-min. The proposed computational methods are built on a principled algorithmic approach of decomposition and penalization. More specifically, the algorithm develops spatial and temporal decomposition by exploiting the strong temporal coupling and weak spatial coupling of the UC problem and the complementary feature, i.e. weak temporal coupling and strong spatial coupling of the ACOPF problem. The algorithm also leverages recent progresses in strong convex relaxation of ACOPF. A unique feature of the proposed approach is that it generates a valid, global upper bound on the optimal maximum profit. In this way, a global optimality gap is available to measure the quality of the solution. To further speed up computation, the research team has developed a plethora of effective heuristics to strengthen the iterative penalty-based decomposition framework. For instance, a heuristic is developed to construct inner approximations of the time coupling constraints within the time decoupled problems. Contingencies are pre-screened and low-rank matrix computation is exploited to find the almost unique solution to each contingency. A novel heuristic for line switching is proposed and tested with positive impacts on instances where line switching is beneficial. Taking a systematic approach and carefully handling every detail of the problem pays off. The TIM-GO’s performance throughout the trials and the final event was stellar. TIM-GO garnered the second highest total prize money and is ranked in the top three positions across all categories of comparison.

97 MATHEMATICS AND COMPUTING↗

Advanced Methods for Aircraft Engine Thrust and Noise Benefits: Nozzle-Inlet Flow Analysis

In this project on the first stage (2000-Ol), we continued to develop the previous joint research between the Fluid Mechanics and Acoustics Laboratory (FM&AL) at Hampton University (HU) and the Jet Noise Team (JNT) at the NASA Langley Research Center (NASA LaRC). At the second stage (2001-03), FM&AL team concentrated its efforts on solving of problems of interest to Glenn Research Center (NASA GRC), especially in the field of propulsion system enhancement. The NASA GRC R&D Directorate and LaRC Hyper-X Program specialists in a hypersonic technology jointly with the FM&AL staff conducted research on a wide region of problems in the propulsion field as well as in experimental testing and theoretical and numerical simulation analyses for advanced aircraft and rocket engines. The last year the Hampton University School of Engineering & Technology was awarded the NASA grant, for creation of the Aeropropulsion Center, and the FM&AL is a key team of the project fulfillment responsible for research in Aeropropulsion and Acoustics (Pillar I). This work is supported by joint research between the NASA GRC/ FM&AL and the Institute of Mechanics at Moscow State University (IMMSU) in Russia under a CRDF grant. The main areas of current scientific interest of the FM&AL include an investigation of the proposed and patented advanced methods for aircraft engine thrust and noise benefits. This is the main subject of our other projects, of which one is presented. The last year we concentrated our efforts to analyze three main problems: (a) new effective methods fuel injection into the flow stream in air-breathing engines; (b) new re-circulation method for mixing, heat transfer and combustion enhancement in propulsion systems and domestic industry application; (c) covexity flow The research is focused on a wide regime of problems in the propulsion field as well as in experimental testing and theoretical and numerical simulation analyses for advanced aircraft and rocket engines (see, for example, Figures 4). The FM&AL Team uses analytical methods, numerical simulations and experimental tests at the Hampton University campus, NASA and IM/MSU.

Morgan, Morris H., III↗

Solar Thermochemical Ammonia Production (STAP) (Final Report)

Ammonia (NH 3 ) is an energy-dense chemical and a vital component of fertilizer. In addition, it is a carbon-neutral liquid fuel and a potential candidate for thermochemical energy storage for high-temperature concentrating solar power (CSP). Currently, NH 3 synthesis occurs via the Haber-Bosch process, which requires high pressures (15-25 MPa) and medium to high temperatures (400-500 °C). N 2 and H 2 are essential feedstocks for this NH 3 production process. H 2 is generally derived from methane via steam reforming; N 2 is sourced from air, after oxygen removal via combustion of hydrocarbons. Both processes consume hydrocarbons, resulting in the release of CO 2 . In addition, hydrocarbon fuels are burned to produce the heat and mechanical energy required to perform the NH 3 reaction, further increasing CO 2 emissions. Overall, the production of ammonia via the Haber-Bosch (H-B) process is responsible for up to 1.4% of the world’s carbon emissions. The development of a renewable pathway to NH 3 synthesis, which utilizes concentrated solar irradiation as a process heat instead of fossil fuels and operates under low or ambient pressure, will result in a decrease (or elimination) of greenhouse gas emissions as well as avoid the cost, complexity, and safety issues inherent in high-pressure processes. Most current efforts to “green” ammonia production involve either electrolysis or simply replacing the energy source for H-B with renewable electricity, but otherwise leaving the process intact. The effort proposed here would create a new paradigm for the synthesis of NH 3 utilizing solar-thermal heat, water, and air as feedstocks, providing a truly green method of production. The overall objective of the STAP (Solar Thermal Ammonia Production) project was to develop a solar thermochemical looping technology to produce and store nitrogen (N 2 ) from air for the subsequent production of ammonia (NH 3 ) via an advanced two-stage process. The goal is a cost-effective and energy efficient technology for the renewable N 2 production and synthesis of NH 3 from H 2 (produced from H 2 O) and air using solar-thermal energy from concentrating sunlight, under pressures an order of magnitude lower than H-B NH 3 production. Our process involves two looping cycles, which do not require catalysts and can be recycled. Over the course of the STAP project, we (1) developed and deeply characterized oxide materials for N 2 separation; (2) developed a method for the synthesis of metal nitrides, producing a series of quaternary compounds that have been heretofore unreported; (3) modeled, designed, and fabricated bench-scale tube and on-sun reactors for the N 2 production step and demonstrated the ability to separate N 2 over multiple cycles in the tube reactor; (4) designed and fabricated a bench-scale Ammonia Synthesis Reactor (ASR) and demonstrated the proof of concept of NH 3 synthesis via a novel looping process using metal nitrides over multiple cycles; and (5) completed a systems- and technoeconomic analysis showing the feasibility of ammonia production on a larger scale via the STAP process. The development of renewable, low-cost NH 3 will be of great interest to the chemicals industry, particularly agricultural sectors. The CSP industry should be both an important customer and potential end-user of this technology, as it affords the capability of synthesizing a promising thermochemical storage material on-site. Since the NH 3 synthesis step also requires H 2 , there will exist a symbiotic relationship between this technology and solar-thermochemical water-splitting applications. Green ammonia synthesis will result in the decarbonization of a hydrocarbon-intensive industry, helping to meet the Administration goal of industrial decarbonization by 2050. The resulting decrease in CO 2 and related pollutants will improve health and well-being of society, particularly for those living in the vicinity of commercial production plants.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Specification and Design of Electrical Flight System Architectures with SysML

Modern space flight systems are required to perform more complex functions than previous generations to support space missions. This demand is driving the trend to deploy more electronics to realize system functionality. The traditional approach for the specification, design, and deployment of electrical system architectures in space flight systems includes the use of informal definitions and descriptions that are often embedded within loosely coupled but highly interdependent design documents. Traditional methods become inefficient to cope with increasing system complexity, evolving requirements, and the ability to meet project budget and time constraints. Thus, there is a need for more rigorous methods to capture the relevant information about the electrical system architecture as the design evolves. In this work, we propose a model-centric approach to support the specification and design of electrical flight system architectures using the System Modeling Language (SysML). In our approach, we develop a domain specific language for specifying electrical system architectures, and we propose a design flow for the specification and design of electrical interfaces. Our approach is applied to a practical flight system.

specifications↗

Using Project Accounting to Report the Full Impact of Combined Heat and Power Projects

Well-applied combined heat and power (CHP) is the most efficient method of generating electricity and useful thermal energy, producing substantially less emissions per MWhe compared to other combustion-based power generation technologies. This report explains how to apply the Greenhouse Gas Protocol for Project Accounting (Project Protocol) to quantify and report reductions in emissions resulting from onsite CHP projects that reduces electricity generated on the grid. Use of the Project Protocol captures the full emissions reduction impact realized from CHP systems, including impacts outside the boundaries of the host facility.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Development, Implementation and Application of Micromechanical Analysis Tools for Advanced High Temperature Composites

This document contains the final report to the NASA Glenn Research Center (GRC) for the research project entitled Development, Implementation, and Application of Micromechanical Analysis Tools for Advanced High-Temperature Composites. The research supporting this initiative has been conducted by Dr. Brett A. Bednarcyk, a Senior Scientist at OM in Brookpark, Ohio from the period of August 1998 to March 2005. Most of the work summarized herein involved development, implementation, and application of enhancements and new capabilities for NASA GRC's Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC) software package. When the project began, this software was at a low TRL (3-4) and at release version 2.0. Due to this project, the TRL of MAC/GMC has been raised to 7 and two new versions (3.0 and 4.0) have been released. The most important accomplishments with respect to MAC/GMC are: (1) A multi-scale framework has been built around the software, enabling coupled design and analysis from the global structure scale down to the micro fiber-matrix scale; (2) The software has been expanded to analyze smart materials; (3) State-of-the-art micromechanics theories have been implemented and validated within the code; (4) The damage, failure, and lifing capabilities of the code have been expanded from a very limited state to a vast degree of functionality and utility; and (5) The user flexibility of the code has been significantly enhanced. MAC/GMC is now the premier code for design and analysis of advanced composite and smart materials. It is a candidate for the 2005 NASA Software of the Year Award. The work completed over the course of the project is summarized below on a year by year basis. All publications resulting from the project are listed at the end of this report.

Source record↗

Seoul National University AGN Monitoring Project. I. Strategy and Sample

While the reverberation mapping technique is the best available method for measuring black hole mass in active galactic nuclei (AGNs) beyond the local volume, this method has been mainly applied to relatively low-to-moderate luminosity AGNs at low redshift. We present the strategy of the Seoul National University AGN Monitoring Project, which aims at measuring the time delay of the H line emission with respect to AGN continuum, using a sample of relatively high luminosity AGNs out to redshift z ∼ 0.5. We present simulated cross correlation results based on a number of mock light curves, in order to optimally determine monitoring duration and cadence. We describe our campaign strategy based on the simulation results and the availability of observing facilities. We present the sample selection, and the properties of the selected 100 AGNs, including the optical luminosity, expected time lag, black hole mass, and Eddington ratio.

Jong-Hak Woo↗

Data-driven surrogates for high dimensional models using Gaussian process regression on the Grassmann manifold

This paper introduces a surrogate modeling scheme based on Grassmannian manifold learning to be used for cost-efficient predictions of high-dimensional stochastic systems. The method exploits subspace-structured features of each solution by projecting it onto a Grassmann manifold. This point-wise linear dimensionality reduction harnesses the structural information to assess the similarity between solutions at different points in the input parameter space. The method utilizes a solution clustering approach in order to identify regions of the parameter space over which solutions are sufficiently similarly such that they can be interpolated on the Grassmannian. In this clustering, the reduced-order solutions are partitioned into disjoint clusters on the Grassmann manifold using the eigen-structure of properly defined Grassmannian kernels and, the Karcher mean of each cluster is estimated. Then, the points in each cluster are projected onto the tangent space with origin at the corresponding Karcher mean using the exponential mapping. For each cluster, a Gaussian process regression model is trained that maps the input parameters of the system to the reduced solution points of the corresponding cluster projected onto the tangent space. Using this Gaussian process model, the full-field solution can be efficiently predicted at any new point in the parameter space. In certain cases, the solution clusters will span disjoint regions of the parameter space. In such cases, for each of the solution clusters we utilize a second, density-based spatial clustering to group their corresponding input parameter points in the Euclidean space. The proposed method is applied to two numerical examples. Here, the first is a nonlinear stochastic ordinary differential equation with uncertain initial conditions where the surrogate is used to predict the time history solution. The second involves modeling of plastic deformation in a model amorphous solid using the Shear Transformation Zone theory of plasticity, where the proposed surrogate is used to predict the full strain field of a material specimen under large shear strains.

42 ENGINEERING↗

Interface Consistency: Phase I Results & Phase II Status

Future exploration missions will rely on designing and developing vehicles and complex systems from within NASA and through multiple external commercial partners to meet mission goals. Despite existing consistency-related agency requirements, NASA’s approach to commercial spaceflight development encourages providers’ flexibility and innovation. This strategy is resulting in significant design diversity across Artemis vehicles. Design best practices and guidelines champion interface consistency to promote mental model development and knowledge transfer. However, research investigating the benefits of consistency is mixed, and little is known about its role in complex systems. Determining the level of risk that system diversity presents is difficult, as there is no established method for quantifying the degree of consistency within and across interfaces, nor is there information about the differential impacts of different types of inconsistency. Phase I of this project (Characterization and Measurement) served as a starting point to better understand the construct of consistency, its application, and the range of studies and methods for measuring it. The project team created a taxonomy of consistency to apply to interfaces as a framework to guide the development of tools to assess intersystem consistency. Checklist and cognitive walkthrough methods were developed for use by human factors (HF) and human-computer interaction (HCI) experts. The Intersystem Consistency Scale (ICS) was developed for interface evaluations with crew. A pilot study evaluated the methods’ ability to distinguish differences between Artemis-like prototype pairs exhibiting either high or low design consistency. In addition, click errors and time on task were collected within the ICS (crew-like) group. Results from our exploratory analysis and lessons learned from the pilot study will be discussed. The project team will also present the status of Phase II (Risk Assessment, Standards and Guidelines). This includes incorporating feedback to redesign the assessment tools, and inputs from displays and training Subject Matter Experts to update tasks and prototype designs. The team will present the risk assessment study design to identify the types and levels of inconsistency that pose the greatest risk to performance. Plans to apply these results toward agency standards and guideline recommendations will also be discussed.

Human-Computer Interaction↗