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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Study of Aircraft Structural Response and Occupant Loading During a Ditching Event Utilizing LS-DYNA Simulation

In this study, the capability of finite element model (FEM) analysis to assess aircraft structural response and occupant injury risk during aircraft water ditching conditions was evaluated. A FEM of the Fokker F28 aircraft, previously validated against full-scale crash test data, was simulated in a realistic water impact environment utilizing recorded conditions from the ditching of US Airways Flight 1549 into the Hudson River. The FEM of the F28 aircraft, was developed from a NASTRAN loads model provided by the vehicle manufacturer, calibrated using component fuselage drop-tests, and validated through test-analysis comparisons from a full-scale crash test of the F28 onto soil. Simulation results are presented in several categories: vehicle kinematics, structural accelerations, damage, occupant responses, and injury risk predictions. Results were consistent with the general outcomes of Flight 1549, indicating that the developed vehicle FEM, validated against land impact test data, may provide an effective tool for evaluating water ditching events.

Jacob Putnam↗
NASA NTRS1975

Vector thrust induced lift effects for several ejector exhaust locations on a V/STOL wind tunnel model at forward speed

The results and analysis of aerodynamic force data obtained from a small scale model of a V/STOL research vehicle in a low speed wind tunnel are presented. The analysis of the data includes the evaluation of aerodynamic-propulsive lift performance when operating twin ejector nozzles with thrust deflected. Three different types of thrust deflector systems were examined: 90 deg downward deflected nozzle, 90 deg slotted nozzle with boundary layer control, and an externally blown flap configuration. Several nozzle locations were tested, including over and underwing positions. The interference lift of the nacelle and model due to jet exhaust thrust is compared and results show that 90 deg turned nozzles located over the wing (near the trailing edge) produce the largest interference lift increment for an untrimmed aircraft, and that the slotted nozzle located under the wing near the trailing edge (in conjunction with a BLC flap) gives a comparable interference lift in the trimmed condition. The externally blown flap nozzle produced the least interference lift and significantly less total lift due to jet thrust effects.

Sharon, A. D.↗
DOE OSTI2021

DISTRIBUTION TRANSFORMER ASSET MONITORING ON THE GRID EDGE USING SMART SENSOR DATA

As new loads such as rooftop photovoltaics, electric vehicles and other distributed energy resources become commonplace on the distribution grid, the stress on already aging assets begins to escalate. This increased loading and changing dynamics can exacerbate failure rates. While traditional monitoring efforts focus on transmission and generation assets, utilities are now beginning to pay close attention to distribution assets in order to increase reliability indices and reduce cost from unexpected outages. This research develops low-cost and scalable methods to monitoring the health of a critical distribution grid asset: the service transformer. Existing methods in literature are either invasive and thus difficult to implement or require the device to be tested offline in an expensive lab setting. Data from the ubiquitous smart meter as well as a novel Bluetooth based transformer monitor are leveraged to automatically notify the utility of deteriorating or damaged transformers. Voltage, temperature, and vibration are some of the signals measured and analyzed by the proposed algorithms to predict transformer failures. Furthermore, these algorithms are designed to keep the implementation and processing costs low by taking advantage of edge computing where possible.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Analyzing Residential Charging Demand for Light-Duty Electric Vehicles in Colorado

The past decade has witnessed a remarkable surge in adoption of electric vehicles (EVs). The momentum is expected to continue with strong support from governments and industry. Rapid EV adoption will add significant electricity demand, making it critical to plan for and manage EV charging to avoid causing additional stress and non-negligible risks to the already-aging power grid. To help power grid operators understand the impacts of residential EV charging and identify risk factors, this study presents a data-driven charging demand analysis for light-duty vehicles. This study considers two real-world grid service regions in Colorado and merges multiple data sources and state-of-the-art tools that characterize EV adoption projections, vehicle travel patterns, seasonal variations, residential charging accessibility, ambient temperature impact, EV charging behaviors, grid utility customers, vehicle registration, and household-level EV charging demand distribution. We characterize potential residential charging demand in 2030 for two regions within the state of Colorado: Boulder and Aurora regions. We project that EVs will be 26% of the light-duty vehicle population in Boulder and 16% in Aurora areas. Charging demand is characterized for ten power grid feeders (five for each study region). Across the ten feeders, peak total EV charging powers during wintertime range from less than 1 MW to more than 4 MW.

ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2010

Ares I-X Flight Evaluation Tasks in Support of Ares I Development

NASA s Constellation Program successfully launched the Ares I-X Flight Test Vehicle on October 28, 2009. The Ares I-X flight was a development flight test that offered a unique opportunity for early engineering data to impact the design and development of the Ares I crew launch vehicle. As the primary customer for flight data from the Ares I-X mission, the Ares Projects Office established a set of 33 flight evaluation tasks to correlate fight results with prospective design assumptions and models. Included within these tasks were direct comparisons of flight data with pre-flight predictions and post-flight assessments utilizing models and modeling techniques being applied to design and develop Ares I. A discussion of the similarities and differences in those comparisons and the need for discipline-level model updates based upon those comparisons form the substance of this paper. The benefits of development flight testing were made evident by implementing these tasks that used Ares I-X data to partially validate tools and methodologies in technical disciplines that will ultimately influence the design and development of Ares I and future launch vehicles. The areas in which partial validation from the flight test was most significant included flight control system algorithms to predict liftoff clearance, ascent, and stage separation; structural models from rollout to separation; thermal models that have been updated based on these data; pyroshock attenuation; and the ability to predict complex flow fields during time-varying conditions including plume interactions.

Huebner, Lawrence D.↗
NASA NTRS2008

Technical Progress on the Ares I-X Flight Test

Ares I-X will be NASA's first test flight for a new human-rated launch vehicle since 1981, and the team is well on its way toward completing the vehicle's design and hardware fabrication for an April 2009 launch. This uncrewed suborbital development test flight gives NASA its first opportunities to: gather critical data about the flight dynamics of the integrated launch vehicle; understand how to control its roll during flight; better characterize the stage separation environments during future flight; and demonstrate the first stage recovery system. The Ares I-X Flight Test Vehicle (FTV) incorporates a mix of flight and mockup hardware. It is powered by a four-segment solid rocket booster, and will be modified to include a fifth, spacer segment; the upper stage, Orion crew exploration vehicle, and launch abort system are simulator hardware to make the FTV aerodynamically similar to the same size, shape, and weight of Ares I. The Ares IX first stage includes an existing Shuttle solid rocket motor and thrust vector control system controlled by an Ascent Thrust Vector Controller (ATVC) designed and built by Honeywell International. The avionics system will be tested in a dedicated System Integration Laboratory located at Lockheed Martin Space Systems (LMSS) in Denver, Colorado. The Upper Stage Simulator (USS) is made up of cylindrical segments that will be stacked and integrated at Kennedy Space Center (KSC) for launch. Glenn Research Center is already building these segments, along with their internal access structures. The active Roll Control System (RoCS) includes two thruster units harvested from Peacekeeper missiles. Duty cycle testing for RoCS was conducted, and fuel tanking and detanking tests will occur at KSC in early 2008. This important flight will provide valuable experience for the ground operations team in integrating, stacking, and launching Ares I. Data from Ares I-X will ensure the safety and reliability of America's newest launch vehicle.

Davis, S.R.↗
NASA NTRS2011

Error Estimate of the Ares I Vehicle Longitudinal Aerodynamic Characteristics Based on Turbulent Navier-Stokes Analysis

Numerical predictions of the longitudinal aerodynamic characteristics for the Ares I class of vehicles, along with the associated error estimate derived from an iterative convergence grid refinement, are presented. Computational results are based on the unstructured grid, Reynolds-averaged Navier-Stokes flow solver USM3D, with an assumption that the flow is fully turbulent over the entire vehicle. This effort was designed to complement the prior computational activities conducted over the past five years in support of the Ares I Project with the emphasis on the vehicle s last design cycle designated as the A106 configuration. Due to a lack of flight data for this particular design s outer mold line, the initial vehicle s aerodynamic predictions and the associated error estimates were first assessed and validated against the available experimental data at representative wind tunnel flow conditions pertinent to the ascent phase of the trajectory without including any propulsion effects. Subsequently, the established procedures were then applied to obtain the longitudinal aerodynamic predictions at the selected flight flow conditions. Sample computed results and the correlations with the experimental measurements are presented. In addition, the present analysis includes the relevant data to highlight the balance between the prediction accuracy against the grid size and, thus, the corresponding computer resource requirements for the computations at both wind tunnel and flight flow conditions. NOTE: Some details have been removed from selected plots and figures in compliance with the sensitive but unclassified (SBU) restrictions. However, the content still conveys the merits of the technical approach and the relevant results.

Aerodynamic characteristics↗
NASA NTRS1979

Space shuttle plume/simulation application

An analysis of pressure and strain-gage data from space shuttle wind tunnel test IA119 and IA138 was performed to define the influence on aerodynamic characteristics resulting from the main propulsion system and solid rocket booster plumes. Aerodynamic characteristics of each of the elements, the components and total vehicle of the space shuttle vehicle during ascent flight was considered. Pressure data were obtained over the aft portions of the space shuttle wind tunnel model in addition to wing and elevon gage data.

Boyle, W.↗
NASA NTRS2019

Reconstruction of Schiaparelli and Comars Flight Data

ESA recently flew an entry, descent, and landing demonstrator module called Schiaparelli that entered the atmosphere of Mars on the 19th of October, 2016. The instrumentation suite included heatshield and backshell pressure transducers and thermocouples (known as AMELIA) and backshell radiation and direct heatflux-sensing sensors (known as COMARS and ICOTOM). Due to the failed landing of Schiaparelli, only a subset of the flight data was transmitted before and after plasma black-out. The goal of this paper is to present comparisons of the flight data with calculations from NASA simulation tools, DPLR/NEQAIR and LAURA/HARA. DPLR and LAURA are used to calculate the flowfield around the vehicle and surface properties, such as pressure and convective heating. The flowfield data are passed to NEQAIR and HARA to calculate the radiative heat flux. Comparisons will be made to the COMARS total heat flux, radiative heat flux and pressure measurements. Results will also be shown against the reconstructed heat flux which was calculated from an inverse analysis of the AMELIA thermocouple data performed by Astrium. Preliminary calculations are presented in this abstract. The aerodynamics of the vehicle and certain as yet unexplained features of the inverse analysis and forebody data will be investigated.

Schiaparelli↗
NASA NTRS2008

Ares I-X Flight Test--The Future Begins Here

In less than one year, the National Aeronautics and Space Administration (NASA) will launch the Ares I-X mission. This will be the first flight of the Ares I crew launch vehicle, which, together with the Ares V cargo launch vehicle, will send humans to the Moon and beyond. Personnel from the Ares I-X Mission Management Office (MMO) are finalizing designs and fabricating vehicle hardware for a 2009 launch. Ares I-X will be a suborbital development flight test that will gather critical data about the flight dynamics of the integrated launch vehicle stack; understand how to control its roll during flight; better characterize the severe stage separation environments that the upper stage engine will experience during future flights; and demonstrate the first stage recovery system. NASA also will modify the launch infrastructure and ground and mission operations. The Ares I-X Flight Test Vehicle (FTV) will incorporate flight and mockup hardware similar in mass and weight to the operational vehicle. It will be powered by a four-segment Solid Rocket Booster (SRB), which is currently in Shuttle inventory, and will include a fifth spacer segment and new forward structures to make the booster approximately the same size and weight as the five-segment SRB. The Ares I-X flight profile will closely approximate the flight conditions that the Ares I will experience through Mach 4.5, up to approximately 130,000 feet (39,600 meters (m)) and through maximum dynamic pressure ('Max Q') of approximately 800 pounds per square foot (38.3 kilopascals (kPa)). Data from the Ares I-X flight will support the Ares I Critical Design Review (CDR), scheduled for 2010. Work continues on Ares I-X design and hardware fabrication. All of the individual elements are undergoing CDRs, followed by a two-part integrated vehicle CDR in March and July 2008. The various hardware elements are on schedule to begin deliveries to Kennedy Space Center (KSC) in early September 2008. Ares I-X is the first step in the long journey to the Moon and farther destinations. This suborbital test will be NASA's first flight of a new human-rated launch vehicle in more than a generation. This promises to be an exciting time for NASA and the nation, as we reach for new goals in space exploration. A visual presentation is included.

Davis, Stephan R.↗
DOE OSTI2023

Domain-aware Control-oriented Neural Models for Autonomous Underwater Vehicles

Conventional physics-based modeling is a time-consuming bottleneck in control design for complex nonlinear systems like autonomous underwater vehicles (AUVs). In contrast, purely data-driven models, require a large number of observations and lack operational guarantees for safety-critical systems. Data-driven models leveraging available partially characterized dynamics have potential to provide reliable systems models in a typical data-limited scenario for high value complex systems, thereby avoiding months of expensive expert modeling time. In this work we explore this middle-ground between expert-modeled and pure data-driven modeling. We present control-oriented parametric models with varying levels of domain-awareness that exploit known system structure and prior physics knowledge to create constrained deep neural dynamical system models. We employ universal differential equations to construct data-driven blackbox and graybox representations of the AUV dynamics. In addition, we explore a hybrid formulation that explicitly models the residual error related to imperfect graybox models. We compare the prediction performance of the learned models for different distributions of initial conditions and control inputs to assess their suitability for control.

Shaw Cortez, Wenceslao E.↗
DOE OSTI2024

Effect of adaptive cruise control on fuel consumption in real-world driving conditions

This paper presents a comprehensive analysis of the impact of adaptive cruise control on energy consumption in real-world driving conditions based on a natural experiment: a large-scale observational dataset of driving data from a diverse fleet of vehicles and drivers. The analysis is conducted at two different fidelity levels: (1) a macroscopic trip-level benefit estimate that compares trips with and without cruise control in a counterfactual way using statistical methods, and (2) a situation-based comparison achieved through the segmentation of trips into distinct driving situations such as acceleration, braking, cruising, and other maneuvers. The results of this research show that the effect of cruise control on energy consumption varies across different driving situations and levels of analysis. In a macroscopic trip-level analysis, cruise control engagement is associated with a slight increase in fuel consumption across the fleet. As revealed later by the situation-based analysis, this result can be attributed to the negative impact of cruise control on energy consumption in cruising mode, which is the most common driving situation. However, the situation-based comparison demonstrates that cruise control can provide fuel consumption benefits in situations involving acceleration and braking, particularly when a preceding vehicle is present. The study also emphasizes the importance of controlling for various factors that can influence both fuel consumption and the likelihood of cruise control engagement to properly evaluate its effects.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Delving into the depths of NGC 3783 with XRISM II. Cross-calibration of X-ray instruments used in the large, multi-mission observational campaign

Context. Accurate X-ray spectroscopic measurements are fundamental for deriving basic physical parameters of the most abundant baryon components in the Universe. The plethora of X-ray observatories currently operational enables a panchromatic view of the high-energy emission of celestial sources. However, uncertainties in the energy-dependent calibration of the instrument transfer functions (e.g. the effective area, energy redistribution, or gain) can limit - and historically, did limit - the accuracy of X-ray spectroscopic measurements. Aims. We revised the status of the cross-calibration among the scientific payload on board four operation missions: Chandra, NuSTAR, XMM-Newton, and the recently launched XRISM. XRISM carries the micro-calorimeter Resolve, which yields the best energy resolution at energies ≥2 keV. For this purpose, we used the data from a 10-day-long observational campaign targeting the nearby active galactic nucleus NGC 3783, carried out in July 2024. Methods. We present a novel model-independent method for assessing the cross-calibration status that is based on a multi-node spline of the spectra with the highest-resolving power (XRISM/Resolve in our campaign). We also estimated the impact of the intrinsic variability of NGC 3783 on the cross-calibration status due to the different time coverages of participating observatories and performed an empirical reassessment of the Resolve throughput at low energies. Results. Based on this analysis, we derived a set of energy-dependent correction factors of the observed responses, enabling a statistically robust analysis of the whole spectral dataset. They will be employed in subsequent papers describing the astrophysical results of the campaign. Aims. We revised the status of the cross-calibration among the scientific payload on board four operation missions: Chandra, NuSTAR, XMM-Newton, and the recently launched XRISM. XRISM carries the micro-calorimeter Resolve, which yields the best energy resolution at energies ≥2 keV. For this purpose, we used the data from a 10-day-long observational campaign targeting the nearby active galactic nucleus NGC 3783, carried out in July 2024. Methods. We present a novel model-independent method for assessing the cross-calibration status that is based on a multi-node spline of the spectra with the highest-resolving power (XRISM/Resolve in our campaign). We also estimated the impact of the intrinsic variability of NGC 3783 on the cross-calibration status due to the different time coverages of participating observatories and performed an empirical reassessment of the Resolve throughput at low energies. Results. Based on this analysis, we derived a set of energy-dependent correction factors of the observed responses, enabling a statistically robust analysis of the whole spectral dataset. They will be employed in subsequent papers describing the astrophysical results of the campaign.

Active Galactic Nuclei, individual: NGC 3783↗
DOE OSTI2024

Estimation of Forest Aboveground Biomass from Derivatives of Vegetation-Structure Profiles

Several studies have found that the vertical Fourier transform of lidar, interferometric Synthetic Aperture Radar (SAR), and stereo photogrammetric profiles at empirically-determined spatial frequencies enables high-performance forest aboveground biomass (AGB) estimation. Linear combinations of real and imaginary parts of Fourier transforms of Tomographic (multi-baseline) SAR (TomoSAR) profiles, from Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) airborne data, generate ~20%-precision estimates of AGB in the Saskatchewan area of Canada. We found that this 20% precision can be improved to ~15%, a factor of 30% improvement in root mean square error (RMSE) if, in addition to using Fourier transforms of the profile itself, we use Fourier transforms of the spatial, vertical derivative of the profile. The formulation of this "derivative" algorithm is the subject of this paper.

Treuhaft, Robert↗
DOE OSTI2024

Simulations of Sparse Static Detector Networks for City-Scale Radiological/Nuclear Detection

Sparse static detector networks in urban environments can be used in efforts to detect illicit radioactive sources, such as stolen nuclear material or radioactive "dirty bombs." We use detailed simulations to evaluate multiple configurations of detector networks and their ability to detect sources moving through a $6\times 6$ km 2 area of downtown Chicago. A detector network's probability of detecting a source increases with detector density but can also be increased with strategic node placement. Here, we show that the ability to fuse correlated data from a source-carrying vehicle passing by multiple detectors can significantly contribute to the overall detection probability. In this article, we distinguish static sensor deployments operated as networks able to correlate signals between sensors, from deployments operated as arrays where each sensor is operated individually. In particular, we show that additional visual attributes of source-carrying vehicles, such as vehicle color and make, can greatly improve the ability of a detector network to detect illicit sources.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2025

PDF Entity Annotation Tool (PEAT)

While different text mining approaches – including the use of Artificial Intelligence (AI) and other machine based methods - continue to expand at a rapid pace, the tools used by researchers to create the labeled datasets required for training, modeling, and evaluation remain rudimentary. Labeled datasets contain the target attributes the machine is going to learn; for example, training an algorithm to delineate between images of a car or truck would generally require a set of images with a quantitative description of the underlying features of each vehicle type. Development of labeled textual data that can be used to build natural language machine learning models for scientific literature is not currently integrated into existing manual workflows used by domain experts. Published literature is rich with important information, such as different types of embedded text, plots, and tables that can all be used as inputs to train ML/natural language processing (NLP) models, when extracted and prepared in machine readable formats. Currently, both normalized data extraction of use to domain experts and extraction to support development of ML/NLP models are labor intensive and cumbersome manual processes. Automatic extraction of data and information from formats such as PDFs that are optimized for layout and human readability, not machine readability. The PDF (Portable Document Format) Entity Annotation Tool (PEAT) was developed with the goal of allowing users to annotate publications within their current print format, while also allowing those annotations to be captured in a machine-readable format. One of the main issues with traditional annotation tools is that they require transforming the PDF into plain text to facilitate the annotation process. While doing so lessens the technical challenges of annotating data, the user loses all structure and provenance that was inherent in the underlying PDF. Also, textual data extraction from PDFs can be an error prone process. Challenges include identifying sequential blocks of text and a multitude of document formats (multiple columns, font encodings, etc.). As a result of these challenges, using existing tools for development of NLP/ML models directly from PDFs is difficult because the generated outputs are not interoperable. We created a system that allows annotations to be completed on the original PDF document structure, with no plain text extraction. The result is an application that allows for easier and more accurate annotations. In addition, by including a feature that grants the user the ability to easily create a schema, we have developed a system that can be used to annotate text for different domain-centric schemas of relevance to subject matter experts. Different knowledge domains require distinct schemas and annotation tags to support machine learning.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

FY2019 Technology Integration Annual Progress Report

The 2019 Technology Integration Annual Progress Report covers 30 multi-year projects funded by the Vehicle Technologies Office. The report includes information on 23 competitively awarded projects, ranging from safety training and design for maintenance facilities housing gaseous fuel vehicles, to electric vehicle community partner programs, to truck platooning with advanced driver assistance systems. It also includes seven projects conducted by several of VTO’s National Laboratory partners, Argonne National Laboratory, Oak Ridge National Laboratory and the National Renewable Energy Laboratory. These projects range from a Technical Assistance project for business, industry, government and individuals, to the EcoCar Advanced Vehicle Technology Competition, and the Fuel Economy Information Project.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

FY2020 Technology Integration Annual Progress Report

The 2020 Technology Integration Annual Progress Report covers 46 multi-year projects funded by the Vehicle Technologies Office. The report includes information on competitively awarded projects, ranging from rural shared mobility demonstration projects to medium- and heavy-duty electric vehicle deployment to statewide alternative fuel resiliency planning. It also includes projects conducted by several of the Vehicle Technologies Office’s (VTO) National Laboratory partners, Argonne National Laboratory, Oak Ridge National Laboratory and the National Renewable Energy Laboratory. These projects range from a Technical Assistance project for business, industry, government and individuals, to the EcoCar Advanced Vehicle Technology Competition, and the Fuel Economy Information Project.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗