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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 1,549 records · Page 86
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

On the Modeling of Urban Air Mobility Vehicle Takeoff and Landing Operations in the FAA Aviation Environmental Design Tool

Urban air mobility (UAM) vehicles are anticipated to operate in close proximity to the public. A possible barrier to the introduction of UAM vehicles as a transit solution is their community noise impact, particularly around vertiports. The Federal Aviation Administration Aviation Environmental Design Tool (AEDT) is the mandated tool to assess aircraft noise and other environmental impacts due to federal actions at civilian airports, vertiports, or in U.S. airspace for commercial flight operations. However, AEDT was designed to model fixed-wing aircraft and conventional helicopter operations, not UAM vehicles. Prior work by the authors showed significant differences in noise contours of UAM departures and approaches when modeling operations as fixed-wing and helicopter types in AEDT. This paper identifies the sources of those differences. Additionally, a NASA time-marching simulation tool is used to generate noise exposure predictions for equivalent operations to help identify differences associated with the noise model implemented in AEDT and offer possible changes to assess UAM community noise impact more consistently with simulation-based modeling.

aeroacoustics↗
NASA NTRSDate not supplied

Aviary: An Open-Source Multidisciplinary Design, Analysis, and Optimization Tool for Modeling Aircraft with Analytic Gradients

Aviary is an open-source aircraft design, analysis, and optimization tool built on OpenMDAO and leveraging the legacy tools of FLOPS and GASP. This presentation will introduce the basics of Aviary, more details for which can be found in the paper. Specifically, this presentation will discuss an overview of why new aircraft design tools are necessary and how Aviary meets those needs, the structure and subsystems of Aviary, and the validation and interface that Aviary provides.

optimization↗
NASA NTRS2024

Valkyrie Robot Capability Demonstration: Autonomous Grab of Body Stored Hand-Tool

A video that provides an automated tool grasp industrial scenario for the NASA Valkyrie Robot from the NASA Dexterous Robotics Team. The scenario is where the Valkyrie uses externally mounted sensors and tools to investigate a room for objects of interest and removes any hazards. This video highlights the tool pick component of the full demonstration. Video run time is 3 min. 28 sec, in color with no sound.

Valkyrie↗
NASA NTRSDate not supplied

AI-Enhanced Computational Tools for Entry Systems Modeling

To advance the understanding of complex atmospheric entry phenomena, NASA’s Entry Systems Modeling (ESM) team [1] has developed high-fidelity computational tools addressing multiscale challenges, from material microstructures to full-scale heatshield response. This abstract highlights a subset of ESM tools, focusing on AI integration to enhance workflows and predictive modeling. - PuMA [2] computes effective material properties from high-resolution micro-CT scans, supporting TPS analysis for NASA missions. - TomoSAM [3] automates 3D tomography dataset segmentation for PuMA using the Segment Anything Model, reducing manual effort and improving accuracy. - PATO [4] models porous reactive materials under extreme conditions, with advancements such as unified solvers, mechanical erosion, and TPS coatings for NASA missions. - arcjetCV [5] employs deep learning to analyze arc jet test footage, measuring recession rates, shape changes, and shock standoff distances, bridging simulations, and experiments to reveal TPS ablation behavior. - ARCHeS [6] simulates arc heater plasma flows, modeling turbulence, radiation, and electromagnetic interactions to optimize arc heater performance, validate TPS under extreme conditions, and serve as a foundation for developing digital twins of arc heater facilities. - SPARTA [7] simulates rarefied hypersonic flows and gas-surface interactions for planetary entry missions, leveraging GPU architectures for scalable and efficient aerothermal and ablation analyses. AI-driven solutions, such as deep learning segmentation, have streamlined workflows in ESM tools and still hold significant potential to further accelerate processes and enhance automation in entry systems modeling. [1] Haskins, J.B. (2023), [2] Ferguson, J.C. (2018), [3] Meurisse, J.B.E. (2018), [4] Semeraro, F. (2023), [5] Quintart, A. (2024) [6] Meurisse, J.B.E. (2022), [7] Plimpton, S.J. (2019)

Predictive Modeling↗
NASA NTRSDate not supplied

Performance Risk Model (PRisM) Proof-of-Concept: An Operational Decision Support Tool to Predict Crew Performance in Space from Available Performance Tests

The Crew Health and Performance-Probabilistic Risk Assessment (CHP-PRA) team at NASA Glenn Research Center has developed a range of tools to evaluate astronaut health during spaceflight and to optimize the medical set required for missions. Among these, the Performance Risk Model (PRisM) represents a novel advancement, extending CHP-PRA’s focus beyond medical systems into the domain of human performance. Such tool could be pivotal in optimizing astronaut capabilities during space travel, thereby enhancing overall mission success. PRisM leverages data from well-established performance assessments conducted during previous crewed space missions and Earth analogs to strategically predict outcomes for planned tasks, even when direct performance testing has not been conducted for those specific tasks. To evaluate performance, PRisM references the various metrics outlined in NASA-STD-3001 and employs a methodology to integrate different performance scales. This framework analyzes the contribution of various human system task categories (HSTCs) to task execution and compares these contributions to the HSTCs’ involvement in other known tests. The model further employs a Monte Carlo simulation to sample performance scores from their distribution in operationally relevant tests such as those in Mulavara et al. (2018) and, by leveraging similarities in HSTC involvement, transfers this knowledge to actual mission tasks, such as those outlined in the "Human Exploration of Mars: Preliminary List of Crew Tasks”. The current PRisM proof-of-concept includes analyses of the impact of exercise and specific medications on astronauts’ performance, with provisions to incorporate additional countermeasures as data becomes available. Furthermore, the tool is customizable to include any system necessary to fully encompass the domain of human systems and can be adapted to evaluate performance for any spaceflight activities as requested by operational stakeholders. PRisM has the potential to assist the Human Research Program in exploring the capabilities trade space for optimized crew performance.

performance modeling↗
DOE OSTI2012

Strengthened IAEA Safeguards-Imagery Analysis: Geospatial Tools for Nonproliferation Analysis

This slide presentation focuses on the growing role and importance of imagery analysis for IAEA safeguards applications and how commercial satellite imagery, together with the newly available geospatial tools, can be used to promote 'all-source synergy.' As additional sources of openly available information, satellite imagery in conjunction with the geospatial tools can be used to significantly augment and enhance existing information gathering techniques, procedures, and analyses in the remote detection and assessment of nonproliferation relevant activities, facilities, and programs. Foremost of the geospatial tools are the 'Digital Virtual Globes' (i.e., GoogleEarth, Virtual Earth, etc.) that are far better than previously used simple 2-D plan-view line drawings for visualization of known and suspected facilities of interest which can be critical to: (1) Site familiarization and true geospatial context awareness; (2) Pre-inspection planning; (3) Onsite orientation and navigation; (4) Post-inspection reporting; (5) Site monitoring over time for changes; (6) Verification of states site declarations and for input to State Evaluation reports; and (7) A common basis for discussions among all interested parties (Member States). Additionally, as an 'open-source', such virtual globes can also provide a new, essentially free, means to conduct broad area search for undeclared nuclear sites and activities - either alleged through open source leads; identified on internet BLOGS and WIKI Layers, with input from a 'free' cadre of global browsers and/or by knowledgeable local citizens (a.k.a.: 'crowdsourcing'), that can include ground photos and maps; or by other initiatives based on existing information and in-house country knowledge. They also provide a means to acquire ground photography taken by locals, hobbyists, and tourists of the surrounding locales that can be useful in identifying and discriminating between relevant and non-relevant facilities and their associated infrastructure. The digital globes also provide highly accurate terrain mapping for better geospatial context and allow detailed 3-D perspectives of all sites or areas of interest. 3-D modeling software (i.e., Google's SketchUp6 newly available in 2007) when used in conjunction with these digital globes can significantly enhance individual building characterization and visualization (including interiors), allowing for better assessments including walk-arounds or fly-arounds and perhaps better decision making on multiple levels (e.g., the best placement for International Atomic Energy Agency (IAEA) video monitoring cameras).

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2013

Use of SCALE Continuous-Energy Monte Carlo Tools for Eigenvalue Sensitivity Coefficient Calculations

The TSUNAMI code within the SCALE code system makes use of eigenvalue sensitivity coefficients for an extensive number of criticality safety applications, such as quantifying the data-induced uncertainty in the eigenvalue of critical systems, assessing the neutronic similarity between different critical systems, and guiding nuclear data adjustment studies. The need to model geometrically complex systems with improved fidelity and the desire to extend TSUNAMI analysis to advanced applications has motivated the development of a methodology for calculating sensitivity coefficients in continuous-energy (CE) Monte Carlo applications. The CLUTCH and Iterated Fission Probability (IFP) eigenvalue sensitivity methods were recently implemented in the CE KENO framework to generate the capability for TSUNAMI-3D to perform eigenvalue sensitivity calculations in continuous-energy applications. This work explores the improvements in accuracy that can be gained in eigenvalue and eigenvalue sensitivity calculations through the use of the SCALE CE KENO and CE TSUNAMI continuous-energy Monte Carlo tools as compared to multigroup tools. The CE KENO and CE TSUNAMI tools were used to analyze two difficult models of critical benchmarks, and produced eigenvalue and eigenvalue sensitivity coefficient results that showed a marked improvement in accuracy. The CLUTCH sensitivity method in particular excelled in terms of efficiency and computational memory requirements.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Development of a Groundwater Transport Simulation Tool for Remedial Process Optimization

The groundwater remedy for hexavalent chromium at the Hanford Site includes operation of five large pump-and-treat systems along the Columbia River. The systems at the 100-HR-3 and 100-KR-4 groundwater operable units treat a total of about 9,840 liters per minute (2,600 gallons per minute) of groundwater to remove hexavalent chromium, and cover an area of nearly 26 square kilometers (10 square miles). The pump-and-treat systems result in large scale manipulation of groundwater flow direction, velocities, and most importantly, the contaminant plumes. Tracking of the plumes and predicting needed system modifications is part of the remedial process optimization, and is a continual process with the goal of reducing costs and shortening the timeframe to achieve the cleanup goals. While most of the initial system evaluations are conducted by assessing performance (e.g., reduction in contaminant concentration in groundwater and changes in inferred plume size), changes to the well field are often recommended. To determine the placement for new wells, well realignments, and modifications to pumping rates, it is important to be able to predict resultant plume changes. In smaller systems, it may be effective to make small scale changes periodically and adjust modifications based on groundwater monitoring results. Due to the expansive nature of the remediation systems at Hanford, however, additional tools were needed to predict the plume reactions to system changes. A computer simulation tool was developed to support pumping rate recommendations for optimization of large pump-and-treat groundwater remedy systems. This tool, called the Pumping Optimization Model, or POM, is based on a 1-layer derivation of a multi-layer contaminant transport model using MODFLOW and MT3D.

Ivarson, Kristine A.↗
DOE OSTI2014

Tools for Large-Scale Mobile Malware Analysis

Analyzing mobile applications for malicious behavior is an important area of re- search, and is made di cult, in part, by the increasingly large number of appli- cations available for the major operating systems. There are currently over 1.2 million apps available in both the Google Play and Apple App stores (the respec- tive o cial marketplaces for the Android and iOS operating systems)[1, 2]. Our research provides two large-scale analysis tools to aid in the detection and analysis of mobile malware. The rst tool we present, Andlantis, is a scalable dynamic analysis system capa- ble of processing over 3000 Android applications per hour. Traditionally, Android dynamic analysis techniques have been relatively limited in scale due to the compu- tational resources required to emulate the full Android system to achieve accurate execution. Andlantis is the most scalable Android dynamic analysis framework to date, and is able to collect valuable forensic data, which helps reverse-engineers and malware researchers identify and understand anomalous application behavior. We discuss the results of running 1261 malware samples through the system, and provide examples of malware analysis performed with the resulting data. While techniques exist to perform static analysis on a large number of appli- cations, large-scale analysis of iOS applications has been relatively small scale due to the closed nature of the iOS ecosystem, and the di culty of acquiring appli- cations for analysis. The second tool we present, iClone, addresses the challenges associated with iOS research in order to detect application clones within a dataset of over 20,000 iOS applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Tools for Simulation and Benchmark Generation at Exascale

The path to exascale high-performance computing (HPC) poses several challenges related to power, performance, resilience, productivity, programmability, data movement, and data management. Investigating the performance of parallel applications at scale on future architectures and the performance impact of different architecture choices is an important component of HPC hardware/software co-design. Simulations using models of future HPC systems and communication traces from applications running on existing HPC systems can offer an insight into the performance of future architectures. This work targets technology developed for scalable application tracing of communication events and memory profiles, but can be extended to other areas, such as I/O, control flow, and data flow. It further focuses on extreme-scale simulation of millions of Message Passing Interface (MPI) ranks using a lightweight parallel discrete event simulation (PDES) toolkit for performance evaluation. Instead of simply replaying a trace within a simulation, the approach is to generate a benchmark from it and to run this benchmark within a simulation using models to reflect the performance characteristics of future-generation HPC systems. This provides a number of benefits, such as eliminating the data intensive trace replay and enabling simulations at different scales. The presented work utilizes the ScalaTrace tool to generate scalable trace files, the ScalaBenchGen tool to generate the benchmark, and the xSim tool to run the benchmark within a simulation.

Lagadapati, Mahesh↗
DOE OSTI2014

Klonos: A Similarity Analysis Based Tool for Software Porting

The Klonos is a compiler-based tool that can help users for scientific application porting. The tool is based on the similarity analysis with the help of the OpenUH compiler (a branch of Open64 compiler). This tool combines syntactic and cost-model-provided metrics clusters, which aggregate similar subroutines that can be ported similarity. The generated porting plan, which allows programmers and compilers to reuse porting experience as much as possible during the porting process.

and Oscar Hernandez, Wei Ding↗
DOE OSTI2016

Friction stir weld tools having fine grain structure

Tools for friction stir welding can be made with fewer process steps, lower cost techniques, and/or lower cost ingredients than other state-of-the-art processes by utilizing improved compositions and processes of fabrication. Furthermore, the tools resulting from the improved compositions and processes of fabrication can exhibit better distribution and homogeneity of chemical constituents, greater strength, and/or increased durability. In one example, a friction stir weld tool includes tungsten and rhenium and is characterized by carbide and oxide dispersoids, by carbide particulates, and by grains that comprise a solid solution of the tungsten and rhenium. The grains do not exceed 10 micrometers in diameter.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Materials Flows Through Industry Tool to Track Supply Chain Energy Demand

In evaluating next-generation materials and processes, the supply chain can have a large impact on the life cycle energy impacts. The Materials Flow through Industry (MFI) tool was developed for the Department of Energy's Advanced Manufacturing Office to be able to evaluate the energy impacts of the U.S. supply chain. The tool allows users to perform process comparisons, material substitutions, and grid modifications, and to see the effects of implementing sector efficiency potentials (Masanet, et al. 2009). This paper reviews the methodology of the tool and provides results around specific scenarios.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2015

LESSONS FROM NUCLEAR ENERGY: BUILDING SNOW AND AVALANCHE SIMULATION TOOLS USING A COMMON OPEN-SOURCE FRAMEWORK

The Department of Energy (DOE) is currently investing millions of dollars annually into various modeling and simulation tools for all aspects of nuclear energy. An important part of this effort includes developing applications based on the open-source Multiphysics Object Oriented Simulation Environment (MOOSE; mooseframework.org) from Idaho National Laboratory (INL). Through the DOE and outside collaborators, MOOSE includes a large set of physics modules, including phase field, level set, heat conduction, tensor mechanics, Navier-Stokes, and porous media, among others. The phase-field module, in particular, is well-suited for micro-structure evolution simulations, including solidification, as shown in the figure. It was also used, in conjunction with the heat conduction module, to build a multiscale snow model (Pika) as presented at the 2014 International Snow Science Workshop (Slaughter et al., 2014). The snow science community should learn from the nuclear industry, and harness the enormous effort underway to build simulation tools that are open, modular, and share a common framework. In particular, MOOSE-based multi-physics solvers are inherently parallel, dimension agnostic, adaptive in time and space, fully-coupled, and capable of interacting with other applications. The snow science community must build on existing tools to enable collaboration between researchers and practitioners throughout the world, and advance the state-of-the-art in line with other scientific research efforts.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

INVESTIGATION OF IN-AUTOCLAVE ADDITIVE MANUFACTURING COMPOSITE TOOLING

The autoclave is a crucial piece of equipment for fabricating Tier 1 polymer composite aerospace structural components with very low void content (i.e. < 5 %). The essential component in this composite manufacturing process is the rigid mold that defines the final shape of the fabricated composite component. The Big Area Additive Manufacturing (BAAM) system located at Oak Ridge National Laboratory s (ORNL) Manufacturing Demonstration Facility (MDF) has been used to manufacture a new generation of in-autoclave tools that can be used to fabricate various aerospace composite parts. Different tools made form Polyphenylene sulfide (PPS) with 50 % by weight carbon fiber and Polyphenylsulfone (PPSU) with 25 % carbon fiber are investigated in this study. The behavior of the printed tools under different temperature ramp rates for the autoclave cycles was observed and analyzed.

Kunc, Vlastimil↗
DOE OSTI2017

Can We Practically Bring Physics-based Modeling Into Operational Analytics Tools?

We present that analytics software is increasingly used to improve and maintain operational efficiency in commercial buildings. Energy managers, owners, and operators are using a diversity of commercial offerings often referred to as Energy Information Systems, Fault Detection and Diagnostic (FDD) systems, or more broadly Energy Management and Information Systems, to cost-effectively enable savings on the order of ten to twenty percent. Most of these systems use data from meters and sensors, with rule-based and/or data-driven models to characterize system and building behavior. In contrast, physics-based modeling uses first-principles and engineering models (e.g., efficiency curves) to characterize system and building behavior. Historically, these physics-based approaches have been used in the design phase of the building life cycle or in retrofit analyses. Researchers have begun exploring the benefits of integrating physics-based models with operational data analytics tools, bridging the gap between design and operations. In this paper, we detail the development and operator use of a software tool that uses hybrid data-driven and physics-based approaches to cooling plant FDD and optimization. Specifically, we describe the system architecture, models, and FDD and optimization algorithms; advantages and disadvantages with respect to purely data-driven approaches; and practical implications for scaling and replicating these techniques. Finally, we conclude with an evaluation of the future potential for such tools and future research opportunities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗