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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 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Communicating the Threat of a Tropical Cyclone to the Eastern Range

The 45th Weather Squadron (45 WS) has developed a tool to help visualize the Wind Speed Probability product from the National Hurricane Center (NHC) and to help communicate that information to space launch customers and decision makers at the 45th Space Wing (45 SW) and Kennedy Space Center (KSC) located in east central Florida. This paper reviews previous work and presents the new visualization tool, including initial feedback as well as the pros and cons. The NHC began issuing their Wind Speed Probability product for tropical cyclones publicly in 2006. The 45 WS uses this product to provide a threat assessment to 45 SW and KSC leadership for risk evaluations with an approaching tropical cyclone. Although the wind speed probabilities convey the uncertainty of a tropical cyclone well, communicating this information to customers is a challenge. The 45 WS continually strives to provide the wind speed probability information to customers in a context which clearly communicates the threat of a tropical cyclone. First, an intern from the Florida Institute of Technology (FIT) Atmospheric Sciences department, sponsored by Scitor Corporation, independently evaluated the NHC wind speed probability product. This work was later extended into a M.S. thesis at FIT, partially funded by Scitor Corporation and KSC. A second thesis at FIT further extended the evaluation partially funded by KSC. Using this analysis, the 45 WS categorized the probabilities into five probability interpretation categories: Very Low, Low, Moderate, High, and Very High. These probability interpretation categories convert the forecast probability and forecast interval into easily understood categories that are consistent across all ranges of probabilities and forecast intervals. As a follow-on project, KSC funded a summer intern to evaluate the human factors of the probability interpretation categories, which ultimately refined some of the thresholds. The 45 WS created a visualization tool to express the timing and risk for multiple locations in a single graphic. Preliminary results on an on-going project by FIT will be included in this paper. This project is developing a new method of assigning the probability interpretation categories and updating the evaluation of the performance of the NHC wind speed probability analysis.

Winters, Katherine A.↗
NASA NTRSDate not supplied

Distributed Visual Sensing and Fusion for Advanced Air Mobility

Surveillance solutions for Advanced and Urban Air Mobility frameworks are a key factor to enable safe operations of highly automated aircraft in the civil airspace. To design solutions suitable for all types of aircraft, non-cooperative sensors can be used, though many challenges arise when the small dimensions of the vehicles and their proximity to the ground during low-altitude missions are considered. A distributed sensing concept can be efficiently applied to address these challenges by exploiting multiple sensors within a surveillance network. This paper proposes a strategy to fuse the information collected by three ground-fixed cameras within a network of multiple distributed sensors and is tested with during experimental flight tests. The solution exploits standalone tracking estimates of each camera within a fusion center that performs triangulation and three-dimensional tracking. This approach is tested in a scenario involving two small UAVs flying at low altitude. The paper deals with the challenges of associating the two objects from independent and unrelated tracks to achieve robust triangulation, which produces meter-level mean errors with respect to GNSS-based ground truth.

Federica Vitiello↗
DOE OSTI2022

A portable fiber optic sensor for the luminescent sensing of cobalt ions using carbon dots

Cobalt is critical to energy-relevant technologies, and demand for cobalt will increase significantly with growing global adoption of renewables. However, supply chain stability is threatened by economic and geopolitical factors, incentivizing domestic cobalt production from alternative resources such as coal, coal utilization byproducts (e.g., ash, acid mine drainage) and electronic waste. Rapid, inexpensive, and portable characterization techniques are needed to reduce production costs associated with cobalt prospecting and process monitoring. Here, in this research, we develop a compact, portable fiber optic luminescent probe for cobalt using phosphorus and nitrogen co-doped carbon dots as the sensing material. The carbon dot emission overlaps well with the cobalt absorption band at ~510 nm, leading to a selective decrease in emission as a function of cobalt concentration. The system responds nearly instantly to the presence of cobalt, with detection limits of 0.7 and 3.5 ppm in water and pH 1.68 buffer, respectively, providing comparable performance to a commercial spectrometer at a significantly lower cost. Moreover, the sensor is selective for cobalt in the presence of 13 of the most common metal ions encountered in coal utilization byproducts and is responsive to cobalt when spiked into an acid mine drainage leachate sample, highlighting the sensor's potential for real-world deployment in challenging matrices. In addition, integrating the carbon dots with a filter paper substrate produced ‘test strip’ sensors that exhibited a selective and sensitive visual response to cobalt using a handheld UV lamp. Taken together, the sensing system represents a significant step forward in the development of low-cost practical sensors for high-value metals in complex streams.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Development of a Digital Twin for Hydrogen Dispersion and Safety Assessment in an Electrolyzer Based Hydrogen Production Facility

Digital twin models are virtual representations of physical systems that use real-time data to simulate and optimize performance. This study presents the development and initial implementation of a digital twin (DT) for the electrolyzer-based hydrogen production facility at NREL's Advanced Research on Integrated Energy Systems (ARIES), focused on enhancing safety and optimizing sensor placement through physics-based simulations and metadata integration. The DT incorporates detailed facility-specific information, including component layout, leak locations, and controlled release parameters, to model hydrogen dispersion under varying environmental conditions. Using steady-state computational fluid dynamics (CFD) simulations informed by real meteorological data, such as wind speed, direction, and vertical wind profiles, the DT enables visualization of hydrogen plume behavior and spatial concentration distributions. Comparative analysis between high and low wind speed scenarios illustrates the significant influence of wind dynamics on plume shape and extent, with horizontal momentum dominating dispersion at higher speeds, while buoyancy effects become more prominent under low wind conditions. These simulations generate a rich dataset embedded within the DT, allowing users to assess potential leak outcomes and identify optimal sensor locations based on concentration thresholds. The model supports scenario-based analysis to guide safety strategies and equipment deployment for open-area hydrogen infrastructure. The digital twin thus serves as a dynamic platform for virtual prototyping, providing predictive insight into hydrogen behavior and enhancing risk-informed decision-making. This initial phase establishes a validated foundation for future integration of transient, uncontrolled leak scenarios and real-time sensor feedback, positioning the DT as a critical tool for safety design, operational planning, and adaptive monitoring in hydrogen systems. Overall, the approach demonstrates the value of combining environmental data with digital simulations to inform safer and more efficient deployment of hydrogen technologies.

08 HYDROGEN↗
NASA NTRS1974

The effect of simulator dynamics on pilot response

The effects of visual display dynamics on the altitude tracking performance of a subject in a fixed base flight simulator are considered. The subject, flying the linearized longitudinal equations of motion, attempts to maintain the same altitude as two airplanes positioned three hundred feet ahead, as in level formation flying. The horizon together with the two leading aircraft are represented symbolically on a CRT display. The subject's aircraft is disturbed by atmospheric turbulence. The data indicate a relationship between the bandwidth of the display dynamics and the short period characteristics of the simulated airplane. For an airplane with a relatively fast pitch response the presence of altitude display dynamics, with a bandwidth as high as five times the short period natural frequency, causes significant degradation of altitude tracking performance.

Weener, E. F.↗
NASA NTRS2003

A Probabilistic Approach to Technology Identification, Evaluation, and Selection for Affordable Transport Concepts

Most grant goals were accomplished over the course of the grant, albeit only partial success was achieved in applying ASDL s existing advanced design methods to HAVOC. The limited success in applying ASDL's advanced design methods occurred due to: fundamental 20 of 197 limitations in the RSM metamodeling process used; the highly computationally intensive nature of HAVOC as compared to many other advanced system synthesis and sizing codes; and the highly curved nature of low I(sub sp) rocket system spaces. These challenges encountered during the grant led to ongoing efforts in more efficient and robust sequential metamodeling/surrogate optimization based advanced design methods which are expected to overcome all of the challenges encountered with RSM during the grant. Other achievements over the course of the grant included the documentation of the existing HAVOC cost module and formulation of new cost estimation relationships in support of APS analysis of 3rd Gen RLV. Further achievements beyond the scope of the grant as originally defined were also achieved such as HAVOC code and portability improvements, historical propulsion performance and reliability regression relationships, and new visualization routines to vacilitate visualization of HAVOC DOE case file results.

Source record↗
NASA NTRS2002

Stimulus-response compatibility and psychological refractory period effects: implications for response selection

The purpose of this paper was to provide insight into the nature of response selection by reviewing the literature on stimulus-response compatibility (SRC) effects and the psychological refractory period (PRP) effect individually and jointly. The empirical findings and theoretical explanations of SRC effects that have been studied within a single-task context suggest that there are two response-selection routes-automatic activation and intentional translation. In contrast, all major PRP models reviewed in this paper have treated response selection as a single processing stage. In particular, the response-selection bottleneck (RSB) model assumes that the processing of Task 1 and Task 2 comprises two separate streams and that the PRP effect is due to a bottleneck located at response selection. Yet, considerable evidence from studies of SRC in the PRP paradigm shows that the processing of the two tasks is more interactive than is suggested by the RSB model and by most other models of the PRP effect. The major implication drawn from the studies of SRC effects in the PRP context is that response activation is a distinct process from final response selection. Response activation is based on both long-term and short-term task-defined S-R associations and occurs automatically and in parallel for the two tasks. The final response selection is an intentional act required even for highly compatible and practiced tasks and is restricted to processing one task at a time. Investigations of SRC effects and response-selection variables in dual-task contexts should be conducted more systematically because they provide significant insight into the nature of response-selection mechanisms.

Review Literature↗
NASA NTRS1991

Dynamic stall effects and applications to high performance aircraft

Recent research conducted at the NASA Langley Research Center on the effects of large amplitude pitching motions on the aerodynamic characteristics of modern fighter aircraft configurations is highlighted. Wind tunnel tests were conducted on simple flat-plate wings to gain understanding of the complex flow phenomena during unsteady motions at high angles of attack. Studies then progressed to a representative modern fighter configuration. Using a computer controlled dynamic apparatus, tests were conducted to investigate effects of pitch rate and motion time history and to determine the persistence of unsteady effects. Data were also obtained in sideslip and with control surface deflections to investigate dynamic effects on lateral stability and available control power. Force and moment data were obtained using a 6-component internal strain-gage balance. To aid in the interpretation of the results, flow visualization using a laser light-sheet system was also obtained. Results of these tests are discussed, along with their implications on the maneuverability of future advanced airplanes designed to operate in the highly dynamic, high angle-of-attack environment.

Brandon, Jay M.↗
NASA NTRS2019

Cloud Giovanni: Reining in Costs and Improving Performance with Analytical Data Stores Using Scalable Serverless Architecture

Giovanni is the Geospatial Interactive Online Visualization ANd aNalysis Infrastructure developed at NASA GES DISC which provides a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science data. It receives large number of user requests each day for a variety of analysis and visualization services, which leads to the big data challenge of serving gradually increasing large data volumes with diverse statistical algorithms. We hereby propose a multi-dimensional accumulation method which provides fast and cost-efficient cloud analysis for diverse services including both area averaging and time averaging. This method involves the weighted volume integration over multiple variable dimensions (time and space), and is implemented in AWS using Athena providing serverless and highly scalable data analysis. Compared to the standard method, this approach dramatically reduced the computational time by order of magnitude with a minimal AWS cost incurred. For example, for a benchmark of 10-year area averaging over the 1x1 degree daily variable, the computational time was reduced from minutes to seconds, and the Athena cost is only $5 for 100,000 requests.

Zhang, Hailiang↗
DOE OSTI2017

A Unit Testing Framework for Scientific Legacy Code

Large-scale scientific applications play important roles in supporting research. However, it is often very expensive and time-consuming to make changes to, maintain and evolve the scientific code due to its complexity and poor programming skills of researchers. Therefore, in order to visualize scientific code architecture to optimize software design, understand undocumented source code, and analyze software flow and functionality, we first introduce a unit testing framework (UTF). Then, because such infrastructure's performance is very crucial in practical use since the scientific legacy applications simulate instances in a long period of time, we improve the UTF by applying Message Passing based Parallelization and parallel I/O operations. Furthermore, due to the scientific code has enormous state data and the I/O capacity on the server is limited, we apply in situ data analysis method to encounter fewer resource limitations, and adopt signal processing to greatly reduce data transfer. Last, we demonstrated the correctness and high-efficiency of our framework for legacy Earth model on Titan supercomputer.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

A Comprehensive Analysis of Energy and Daylighting Impact of Window Shading Systems and Control Strategies on Commercial Buildings in the United States

Commercial buildings consume approximately 1.9 EJ of energy in the United States, 50% of which is for heating, cooling, and lighting applications. It is estimated that windows contribute up to 34% of the energy used for heating and cooling. However, window retrofits are not often undertaken to increase energy efficiency because of the high cost and disruptive nature of window installation. Highly efficient window technologies would also need shading devices for glare prevention and visual comfort. An automated window shading system with an appropriate control strategy is a technology that can reduce energy demand, maintain occupant comfort, and enhance the aesthetics and privacy of the built environment. However, the benefits of the automated shades currently used by the shading industry are not well studied. The topic merits an analysis that will help building owners, designers and engineers, and utilities make informed decisions using knowledge of the impact of this technology on energy consumption, peak demand, daylighting, and occupant comfort. This study uses integrated daylight and whole-building energy simulation to evaluate the performance of various control strategies that the shading industry uses in commercial office buildings. The analysis was performed for three different vintages of medium office buildings at six different locations in United States. The results obtained show the control strategies enabled cooling energy savings of up to 40% using exterior shading, and lighting energy savings of up to 25%. The control strategies described can help building engineers and researchers explore different control methods used to control shading in actual buildings but rarely discussed in the literature. This information will give researchers the opportunity to investigate potential improvements in current technologies and their performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Edge ML for CAN bus intrusion detection in AVs

Autonomous Vehicles (AVs) are revolutionizing transportation, but their reliance on interconnected cyber-physical systems exposes them to unprecedented cybersecurity risks. This study addresses the critical challenge of detecting real-time cyber intrusions in self-driving vehicles by leveraging a dataset from the Udacity self-driving car project. We simulate four high-impact attack vectors, Denial of Service (DoS), spoofing, replay, and fuzzy attacks, by injecting noise into spatial features (e.g., bounding box coordinates) to replicate adversarial scenarios. We develop and evaluate two lightweight neural network architectures (NN-1 and NN-2) alongside a logistic regression baseline (LG-1) for intrusion detection. The models achieve exceptional performance, with NN-2 attaining an AUC score of 93.15% and 93.15% accuracy, demonstrating their suitability for edge deployment in AV environments. Through explainable AI techniques, we uncover unique forensic fingerprints of each attack type, such as spatial corruption in fuzzy attacks and temporal anomalies in replay attacks, offering actionable insights for feature engineering and proactive defense. Visual analytics, including confusion matrices, ROC curves, and feature importance plots, validate the models' robustness and interpretability. This research sets a new benchmark for AV cybersecurity, delivering a scalable, field-ready toolkit for Original Equipment Manufacturers (OEMs) and policymakers. By aligning intrusion fingerprints with SAE J3061 automotive security standards, we provide a pathway for integrating machine learning into safety-critical AV systems. Our findings underscore the urgent need for security-by-design AI, ensuring that AVs not only drive autonomously but also defend autonomously. This work bridges the gap between theoretical cybersecurity and life-preserving engineering, offering a leap toward safer, more secure autonomous transportation.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1987

Planform effects on the supersonic aerodynamics of multibody configurations

An experimental and theoretical investigation of the effect of planform on the supersonic aerodynamics of low-fineness-ratio multibody configurations was conducted. Longitudinal and lateral-directional aerodynamic and flow visualization data were obtained on three multibody configurations. The data indicated that planform has a small effect on the zero lift drag of a multibody configuration. The longitudinal data obtained at lifting conditions showed a sensitivity to planform shape. Lateral-directional data obtained for all configurations did not uncover any unusual stability traits for this class of configuration. A comparison study was also made between the planform effects observed on single-body and multibody configurations. Results from this study indicate that the multibody concept appears to offer a mechanism for employing a low-sweep wing with no significant increase in zero-lift drag but still retaining high-performance characteristics at high-lift conditions. Evaluation of the linear-theory prediction methods revealed a general inability of the methods to predict the characteristics of low-fineness-ratio geometries.

Mcmillin, Naomi↗
NASA NTRS1998

BioSIGHT: Interactive Visualization Modules for Science Education

Redefining science education to harness emerging integrated media technologies with innovative pedagogical goals represents a unique challenge. The Integrated Media Systems Center (IMSC) is the only engineering research center in the area of multimedia and creative technologies sponsored by the National Science Foundation. The research program at IMSC is focused on developing advanced technologies that address human-computer interfaces, database management, and high-speed network capabilities. The BioSIGHT project at is a demonstration technology project in the area of education that seeks to address how such emerging multimedia technologies can make an impact on science education. The scope of this project will help solidify NASA's commitment for the development of innovative educational resources that promotes science literacy for our students and the general population as well. These issues must be addressed as NASA marches toward the goal of enabling human space exploration that requires an understanding of life sciences in space. The IMSC BioSIGHT lab was established with the purpose of developing a novel methodology that will map a high school biology curriculum into a series of interactive visualization modules that can be easily incorporated into a space biology curriculum. Fundamental concepts in general biology must be mastered in order to allow a better understanding and application for space biology. Interactive visualization is a powerful component that can capture the students' imagination, facilitate their assimilation of complex ideas, and help them develop integrated views of biology. These modules will augment the role of the teacher and will establish the value of student-centered interactivity, both in an individual setting as well as in a collaborative learning environment. Students will be able to interact with the content material, explore new challenges, and perform virtual laboratory simulations. The BioSIGHT effort is truly cross-disciplinary in nature and requires expertise from many areas including Biology, Computer Science Electrical Engineering, Education, and the Cognitive Sciences. The BioSIGHT team includes a scientific illustrator, educational software designer, computer programmers as well as IMSC graduate and undergraduate students.

Wong, Wee Ling↗
NASA NTRS2018

Internship in Augmented and Virtual Reality - Rapid Model Import Tool

The integration of virtual and augmented reality, sometimes called mixed reality, is an emerging technology which will likely skyrocket overnight much in the way smartphones did a decade ago. Kennedy Space Center's Augmented and Virtual Reality (AVR) Lab is developing a Rapid Model Import Tool (RMIT) to create a quick and efficient way to bring NASA's complex engineering 3D models into virtual and augmented environments. The long-term objective is to create a tool that will ultimately benefit KSC engineers. Its various uses within NASA can potentially span from astronaut training, to marketing, to public outreach, to name a few. Unity is a prolific cross-platform game engine that allows users to build high quality 2D and 3D games for desktop, mobile, web, and game console platforms. It is perhaps also the most widely used software for virtual reality game development. At the AVR lab, we are looking at alternative uses of Unity to build tools for NASA engineers to perform design, development, testing, and training on spacecraft, rocket delivery systems, ground support equipment, and facilities at KSC. As an intern for the RMIT project, I am charged with the task of performing research on Unity-compatible file types to develop an efficient, affordable, preservative process to bring models from CATIA 3D engineering software into the Unity environment. With a tool called the NASA Enterprise Visualization Application (NEVA), developed by the Boeing Design Visualization group at KSC, we are able to easily convert CATIA's design models to. DAE (also known as COLLADA) and .OBJ file formats. I first reduce the polygon count of the model within CATIA itself, make any necessary tweaks to reduce the model further, and then export using NEVA. The .OBJ or. DAE files that I am left with are then converted by another intern to a Unity-compatible file format using a custom Python script. I have generated extensive documentation of this process in a NEVA User Guide. By the end of this semester, we will have built a solid framework for RMIT based on a thorough understanding of virtual reality specifications and file requirements, allowing future software development teams to go forward with development on the custom tool.

Leap Motion↗
DOE OSTI2021

macroMS: Image-Guided Analysis of Random Objects by Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry

Mass spectrometry imaging is well-suited to characterizing sample surfaces for their chemical content in a spatially resolved manner. However, when the surface contains small objects with significant empty spaces between them, more efficient approaches to sample acquisition are possible. Image-guided mass spectrometry (MS) enables high-throughput analysis of a diverse range of sample types, such as microbial colonies, liquid microdroplets, and others, by recognizing and analyzing selected location targets in an image. Here, we describe an imaging protocol and macroMS, an online software suite that can be used to enhance MS measurements of macroscopic samples that are imaged by a camera or a flatbed scanner. Furthermore, the web-based tool enables users to find and filter targets from the optical images, correct optical distortion issues for improved spatial location of selected targets, input the custom geometry files into an MS device to acquire spectra at the selected locations, and finally, perform limited data analysis and use visualization tools to aid locating samples containing compounds of interest. Using the macroMS suite, an enzyme mutant library of Saccharomyces cerevisiae and nL droplet arrays of Escherichia coli and Pseudomonas fluorescens have been assayed at a rate of ~2 s/sample.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Defect-driven selective metal oxidation at atomic scale

Nanoscale materials modified by crystal defects exhibit significantly different behaviours upon chemical reactions such as oxidation, catalysis, lithiation and epitaxial growth. However, unveiling the exact defect-controlled reaction dynamics (e.g. oxidation) at atomic scale remains a challenge for applications. Here, using in situ high-resolution transmission electron microscopy and first-principles calculations, we reveal the dynamics of a general site-selective oxidation behaviour in nanotwinned silver and palladium driven by individual stacking-faults and twin boundaries. The coherent planar defects crossing the surface exhibit the highest oxygen binding energies, leading to preferential nucleation of oxides at these intersections. Planar-fault mediated diffusion of oxygen atoms is shown to catalyse subsequent layer-by-layer inward oxide growth via atomic steps migrating on the oxide-metal interface. These findings provide an atomistic visualization of the complex reaction dynamics controlled by planar defects in metallic nanostructures, which could enable the modification of physiochemical performances in nanomaterials through defect engineering.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Designing Unmanned Aerial Survey Monitoring Program to Assess Floating Litter Contamination

Monitoring marine contamination by floating litter can be particularly challenging since debris are continuously moving over a large spatial extent pushed by currents, waves, and winds. Floating litter contamination have mostly relied on opportunistic surveys from vessels, modeling and, more recently, remote sensing with spectral analysis. This study explores how a low-cost commercial unmanned aircraft system equipped with a high-resolution RGB camera can be used as an alternative to conduct floating litter surveys in coastal waters or from vessels. The study compares different processing and analytical strategies and discusses operational constraints. Collected UAS images were analyzed using three different approaches: (i) manual counting (MC), using visual inspection and image annotation with object counts as a baseline; (ii) pixel-based detection, an automated color analysis process to assess overall contamination; and (iii) machine learning (ML), automated object detection and identification using state-of-the-art convolutional neural network (CNNs). Our findings illustrate that MC still remains the most precise method for classifying different floating objects. ML still has a heterogeneous performance in correctly identifying different classes of floating litter; however, it demonstrates promising results in detecting floating items, which can be leveraged to scale up monitoring efforts and be used in automated analysis of large sets of imagery to assess relative floating litter contamination.

Almeida, Sílvia (ORCID:0000000320636826)↗