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At least 577 records · Page 32

Estimation of Supersonic Stage Separation Aerodynamics of Winged-Body Launch Vehicles Using Response Surface Methods

A collection of statistical and mathematical techniques referred to as response surface methodology was used to estimate the longitudinal stage separation aerodynamic characteristics of a generic, bimese, winged multi-stage launch vehicle configuration using data obtained on small-scale models at supersonic speeds in the NASA Langley Research Center Unitary Plan Wind Tunnel. The simulated Mach 3 staging was dominated by multiple shock wave interactions between the orbiter and booster vehicles throughout the relative spatial locations of interest. This motivated a partitioning of the overall inference space into several contiguous regions within which the separation aerodynamics were presumed to be well-behaved and estimable using cuboidal and spherical central composite designs capable of fitting full second-order response functions. The primary goal was to approximate the underlying overall aerodynamic response surfaces of the booster vehicle in belly-to-belly proximity to the orbiter vehicle using relatively simple, lower-order polynomial functions that were piecewise-continuous across the full independent variable ranges of interest. The quality of fit and prediction capabilities of the empirical models were assessed in detail, and the issue of subspace boundary discontinuities was addressed. The potential benefits of augmenting the central composite designs to full third order using computer-generated D-optimality criteria were also evaluated. The usefulness of central composite designs, the subspace sizing, and the practicality of fitting low-order response functions over a partitioned inference space dominated by highly nonlinear and possibly discontinuous shock-induced aerodynamics are discussed.

Erickson, Gary E.↗

Analysis of the March 30, 2011 Hail Event at Shuttle Launch Pad 39A

The Kennedy Space Center (KSC) Hail Monitor System, a joint effort of the NASA KSC Physics Lab and the KSC Engineering Services Contract (ESC) Applied Technology Lab, was first deployed for operational testing in the fall of 2006. Volunteers from the Community Collaborative Rain, Hail, and Snow Network (CoCoRaHS) in conjunction with Colorado State University have been instrumental in validation testing using duplicate hail monitor systems at sites in the hail prone high plains of Colorado. The KSC Hail Monitor System (HMS), consisting of three stations positioned approximately 500 ft from the launch pad and forming an approximate equilateral triangle, as shown in Figure 1, was first deployed to Pad 39B for support of STS-115. Two months later, the HMS was deployed to Pad 39A for support of STS-116. During support of STS-117 in late February 2007, an unusually intense (for Florida standards) hail event occurred in the immediate vicinity of the exposed space shuttle and launch pad. Hail data of this event was collected by the HMS and analyzed. Support of STS-118 revealed another important application of the hail monitor system. Ground Instrumentation personnel check the hail monitors daily when a vehicle is on the launch pad, with special attention after any storm suspected of containing hail. If no hail is recorded by the HMS, the vehicle and pad inspection team has no need to conduct a thorough inspection of the vehicle immediately following a storm. On the afternoon of July 13, 2007, hail on the ground was reported by observers at the Vertical Assembly Building (VAB) and Launch Control Center (LCC), about three miles west of Pad 39A, as well as at several other locations at KSC. The HMS showed no impact detections, indicating that the shuttle had not been damaged by any of the numerous hail events which occurred on that day.

Lane, John E.↗

A Distributed Simulation-to-Flight Framework to Support Investigating Trust/Trustworthiness in Multi-Agent Systems

As autonomous systems continue to grow both in use and complexity, the necessity for robust and extensible simulation-to-flight frameworks is paramount for establishing an effective architecture for autonomous systems. Hardware test flights are time-consuming and cost prohibitive during early system design and development. Simulation environments can be useful tools to accelerate algorithm development and testing. However, transitions from simulation to flight (sim-to-flight) can be challenging, unless systems are designed with this transition in mind and with the necessary capabilities built into the architecture and framework. One of the objectives of Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR) was to design and develop a distributed mixed-reality simulation environment to begin establishing a basis for certification of autonomous systems via research into trust and trustworthiness. ATTRACTOR’s objective was to construct computational concepts of trustworthiness and justifiable trust in multi-agent autonomous teams, to inform future certification of safety-critical and time-critical autonomous systems in aviation. In this paper, we present an autonomous systems architecture and development framework paired with a persistent distributed modeling and simulation (ModSim) environment for test and evaluation of autonomous systems. They were designed under ATTRACTOR in order to measure and establish trustworthiness and trust in single-and multi-agent human-machine systems whether these machines are fixed-wing general aviation, rotary-wing Unmanned Aerial Vehicles (UAVs), ground rovers, or even spacecraft. The Autonomous Entity Operational Network (AEON) framework enables autonomous system development with an easily extensible collection of libraries and plug-n-play nodes facilitated by the Data Distribution Service (DDS) communication protocol standard. The Baseline Environment for Autonomous Modeling (BEAM) simulation environment is a distributed mixed-reality Unity™-based environment built around the same DDS communication paradigm allowing for easy integration with AEON-based autonomous applications, enabling sim-to-flight with minimal configuration changes. Using AEON and BEAM, source code that runs in simulation ports directly to hardware and has successfully flown in the National Airspace System (NAS) at NASA LaRC many times over the lifetime of ATTRACTOR.

Benjamin N Kelley↗

Variability Analysis of FMVSS-121 Air Brake Systems: 60-mi/hr Service Brake System Performance Data for Truck Tractors

In support of the Federal Motor Carrier Safety Administration’s (FMCSA’s) ongoing interest in connected and automated commercial vehicles, this report summarizes analyses conducted to quantify variability in stopping distance tests conducted on commercial truck tractors. The data used were retrieved from tests performed under the controlled conditions specified for FMVSS-121 air brake system compliance testing. The report explores factors affecting the variability of the service brake stopping distance as defined by 49 CFR 571.121, S5.3.1 Stopping Distance—trucks and buses stopping distance. Variables examined in this analysis include brake type, weight, wheelbase, and tractor antilock braking system (ABS). This analysis uses existing test data collected between 2010 and 2019. Several of the examined parameters affected both tractor stopping distance and stopping distance variability. First, the average stopping distance for disc/disc brakes was shorter than either drum/drum or disc/drum brakes, but brake type did not have a statistically significant effect on stopping distance variability. Second, tractors with a gross vehicle weight rating (GVWR) of 45,000-50,000 lb had shorter stopping distances than any other examined weight category. Weight was found to have a significant effect on stopping distance variability; the 50,000-55,000-lb GVWR range had more variability than both the next lower (45,000-50,000 lb) and next higher (55,000-60,000 lb) range.

Lascurain, Mary Beth↗

Data Resources to Empower Your Fleet

This presentation is on how data collection and analytics can shape fleet electrification plans and help to overcome behavioral barriers.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗

A multi-level load shape clustering and disaggregation approach to characterize patterns of energy consumption behavior

This study presents representative electrical load shapes, disaggregated to the end-use level, for over 5000 customer clusters across California’s residential, commercial, industrial and agricultural sectors. We developed a novel, multi-level load shape clustering approach for residential and commercial sectors leveraging interval meter data for over 350,000 California utility customers collected as a part of the Phase 4 California Demand Response (DR) Potential Study. The clustering approach allowed us to identify typical consumption patterns and categorize customers based on their daily load shape displayed throughout the year. For example, we were able to identify customers with particular energy technologies such as electric vehicles and rooftop solar, as well as building occupancy types such as restaurants, grocery stores and even unoccupied buildings, based solely on whole-building interval data. We then combined the load shape-based clusters with other customer information including building type, climate, geographical area, total consumption and low-income status, to create a set of customer clusters based on both demographics and usage patterns. Total cluster electricity demand was then disaggregated into a wide variety of end-uses using weather normalization and other publicly available end-use load shape datasets. The resulting disaggregated cluster load shapes will be released in anonymized form as part of the Phase 4 DR Potential Study. They will have wide-ranging applications in energy research and policy analysis, including estimation of energy efficiency (EE) and DR potential on the end-use level, time-dependent valuation of EE savings, building stock modeling, and developing customer targeting strategies for EE and DR programs.

Murthy, Samanvitha↗

Vehicle Tracking System using Nanotechnology Satellites and Tags

This paper describes a joint project to design, develop, and deploy a satellite based tracking system incorporating micro-nanotechnology components. The system consists of a constellation of 'nanosats', a satellite command station and data collection sites, and a large number of low-cost electronic 'tags'. Both government and commercial applications are envisioned for the satellite based tracking system. The projected low price for the tracking service is made possible by the lightweight nanosats and inexpensive electronic tags which use high production volume single chip transceivers and microprocessor devices. The nanosat consists of a five inch aluminum cube with body mounted solar panels (GaAs solar cells) on all six faces. A UHF turnstile antenna and a simple, spring release mechanism complete the external configuration of the spacecraft.

Lorenzini, Dino A.↗

Descriptor: Infrastructure Perception and Control: Multi-Sensor Object Tracking Dataset (IPC-MSOT)

Traffic intersections are crucial and challenging nodes in transportation networks where multiple lanes of vehicles and pedestrians converge. Traffic accidents often occur at traffic intersections, including a large proportion of traffic fatalities and about one-half of all traffic injuries in the United States. Object detection data were collected in 2024 across three intersections in Colorado Springs, CO, USA, over the course of multiple days and various times to induce a heterogeneous mix of traffic conditions and behaviors. The purpose of the data collection exercises was to learn various attributes about infrastructure sensors and to build a repository of high-resolution, object-level data that can be used for research and development (e.g., to develop multisensor data fusion algorithms). The Infrastructure Perception and Control:Multi-Sensor Object tracking (IPC-MSOT) dataset was collected as part of the U.S. Department of Transportation's Strengthening Mobility and Revolutionizing Transportation (SMART) project, where the city of Colorado Springs, Colorado, and the National Renewable Energy Laboratory collaborated to collect object-level trajectory data from road users using multiple types of infrastructure sensors deployed at different intersections. This dataset allows for testing of late-stage sensor fusion algorithms and their ability to ingest multimodal sensor data, and it can be utilized by traffic engineers to design and evaluate trajectory-based signal control strategies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A priori estimate of the quality of a data compression system based on statistical characteristics of the sensors used

Knowledge of the composition and certain statistical characteristics of the output signals of the scientific instruments on board a space vehicle allows determination of possible signal processing algorithms in the system and to evaluate the prospects for utilization of data reduction. A method is presented to estimate the compression factor of an on-board data collection and processing system with known mean activities of the sensors used and unknown mutual correlation of their output signals.

Khodarev, Y. K.↗

Model Update of a Micro Air Vehicle (MAV) Flexible Wing Frame with Uncertainty Quantification

This paper describes a procedure to update parameters in the finite element model of a Micro Air Vehicle (MAV) to improve displacement predictions under aerodynamics loads. Because of fabrication, materials, and geometric uncertainties, a statistical approach combined with Multidisciplinary Design Optimization (MDO) is used to modify key model parameters. Static test data collected using photogrammetry are used to correlate with model predictions. Results show significant improvements in model predictions after parameters are updated; however, computed probabilities values indicate low confidence in updated values and/or model structure errors. Lessons learned in the areas of wing design, test procedures, modeling approaches with geometric nonlinearities, and uncertainties quantification are all documented.

Reaves, Mercedes C.↗

Rover Technology for Mars Surface Exploration

Provided is an overview of emerging technologies in miniaturized roving vehicles that enable new types of low-cost planetary missions, those which are aimed at detailed survey of extended surface areas, collection and analysis of interesting samples, and in-situ analysis of scientific data. New types of planetary surface data can be acquired at low-cost through the use of innovative technologies.

Mars Rover Surface Exploration Pathfinder↗

Evaluating Attenuation of Vibration Response using Particle Impact Damping for a Range of Equipment Assemblies

Particle dampers provide a mechanism for diverting energy away from resonant structural vibrations. This experimental study provides data from a series of acoustically excited tests to determine the effectiveness of these dampers for equipment mounted to a curved orthogrid panel for a launch vehicle application. Vibration attenuation trends are examined for variations in particle damper fill level, component mass, and excitation energy. A significant response reduction at the component level was achieved, suggesting that comparatively small, strategically placed, particle damper devices might be advantageously used in launch vehicle design. These test results were compared to baseline acoustic response tests without particle damping devices, over a range of isolation and damping parameters. Instrumentation consisting of accelerometers, microphones, and still photography data will be collected to correlate with the analytical results.

Knight, Brent↗

High Altitude Small Engine Test Techniques at the NASA Glenn Propulsion Systems Lab

A High Altitude Test was performed in the Propulsion Systems Lab (PSL) at the NASA Glenn Research Center using a Pratt and Whitney Canada PW545 jet engine. This engine was tested to develop a highaltitude database on small, high-bypass ratio, engine performance and operability. Industry is interested in the use of high-bypass engines for Uninhabited Aerial Vehicles (UAV's) to perform high altitude surveillance. The tests were a combined effort between Pratt & Whitney Canada (PWC) and NASA Glenn Research Center. A large portion of this test activity was to collect performance data with a highly instrumented low-pressure turbine. Low-pressure turbine aerodynamic performance at low Reynolds numbers was collected and compared to analytical models developed by NASA and PWC. This report describes the test techniques implemented to obtain high accuracy turbine performance data in an altitude test facility, including high accuracy airflow at high altitudes, very low mass flow, and low air temperatures. Major accomplishments from this test activity were to collect accurate and repeatable turbine performance data at high altitudes to within 1 percent. Data were collected at 19,800m, 16,750m, and 13,700m providing documentation of diminishing LPT performance with reductions in Reynolds number in an actual engine flight environment. The test provided a unique database for the development of engine analysis codes to be used for future LPT performance improvements.

Castner, Raymond↗

Greased Lightning (GL-10) Performance Flight Research: Flight Data Report

Modern aircraft design methods have produced acceptable designs for large conventional aircraft performance. With revolutionary electronic propulsion technologies fueled by the growth in the small UAS (Unmanned Aerial Systems) industry, these same prediction models are being applied to new smaller, and experimental design concepts requiring a VTOL (Vertical Take Off and Landing) capability for ODM (On Demand Mobility). A 50% sub-scale GL-10 flight model was built and tested to demonstrate the transition from hover to forward flight utilizing DEP (Distributed Electric Propulsion)[1][2]. In 2016 plans were put in place to conduct performance flight testing on the 50% sub-scale GL-10 flight model to support a NASA project called DELIVER (Design Environment for Novel Vertical Lift Vehicles). DELIVER was investigating the feasibility of including smaller and more experimental aircraft configurations into a NASA design tool called NDARC (NASA Design and Analysis of Rotorcraft)[3]. This report covers the performance flight data collected during flight testing of the GL-10 50% sub-scale flight model conducted at Beaver Dam Airpark, VA. Overall the flight test data provides great insight into how well our existing conceptual design tools predict the performance of small scale experimental DEP concepts. Low fidelity conceptual design tools estimated the (L/D)( sub max)of the GL-10 50% sub-scale flight model to be 16. Experimentally measured (L/D)( sub max) for the GL-10 50% scale flight model was 7.2. The aerodynamic performance predicted versus measured highlights the complexity of wing and nacelle interactions which is not currently accounted for in existing low fidelity tools.

McSwain, Robert G.↗

Development of Monte Carlo Capability for Orion Parachute Simulations

Parachute test programs employ Monte Carlo simulation techniques to plan testing and make critical decisions related to parachute loads, rate-of-descent, or other parameters. This paper describes the development and use of a MATLAB-based Monte Carlo tool for three parachute drop test simulations currently used by NASA. The Decelerator System Simulation (DSS) is a legacy 6 Degree-of-Freedom (DOF) simulation used to predict parachute loads and descent trajectories. The Decelerator System Simulation Application (DSSA) is a 6-DOF simulation that is well suited for modeling aircraft extraction and descent of pallet-like test vehicles. The Drop Test Vehicle Simulation (DTVSim) is a 2-DOF trajectory simulation that is convenient for quick turn-around analysis tasks. These three tools have significantly different software architectures and do not share common input files or output data structures. Separate Monte Carlo tools were initially developed for each simulation. A recently-developed simulation output structure enables the use of the more sophisticated DSSA Monte Carlo tool with any of the core-simulations. The task of configuring the inputs for the nominal simulation is left to the existing tools. Once the nominal simulation is configured, the Monte Carlo tool perturbs the input set according to dispersion rules created by the analyst. These rules define the statistical distribution and parameters to be applied to each simulation input. Individual dispersed parameters are combined to create a dispersed set of simulation inputs. The Monte Carlo tool repeatedly executes the core-simulation with the dispersed inputs and stores the results for analysis. The analyst may define conditions on one or more output parameters at which to collect data slices. The tool provides a versatile interface for reviewing output of large Monte Carlo data sets while preserving the capability for detailed examination of individual dispersed trajectories. The Monte Carlo tool described in this paper has proven useful in planning several Crew Exploration Vehicle parachute tests.

Moore, James W.↗

SULI Oral Presentation

Furthering our understanding of the prevalence and severity of issues that customers face when charging their electric vehicles (EVs) is crucial in order to improve the charging experience across the United States. This project utilizes web-scraping, machine leaning (ML), and natural language processing (NLP) techniques to analyze and categorize user-generated reviews. Selenium was used to build a data collection tool that can scrape vast amounts of user review data from the PlugShare website. Sentiment analysis was employed on this dataset in order to filter out negative reviews for further analysis. NLP techniques such as tokenization and word embedding were then used to convert user-written comments into a numerical format that a ML model can interpret. Multiple ML approaches are currently being explored in order to identify and categorize the charging issues being talked about in each review. Ultimately, the results from the ML model will be visualized and explained in a report on customer pain points to be delivered to the ChargeX Consortium, therefore revealing specific areas for improvement in the customer charging experience.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

SULI Oral Presentation

Furthering our understanding of the prevalence and severity of issues that customers face when charging their electric vehicles (EVs) is crucial in order to improve the charging experience across the United States. This project utilizes web-scraping, machine leaning (ML), and natural language processing (NLP) techniques to analyze and categorize user-generated reviews. Selenium was used to build a data collection tool that can scrape vast amounts of user review data from the PlugShare website. Sentiment analysis was employed on this dataset in order to filter out negative reviews for further analysis. NLP techniques such as tokenization and word embedding were then used to convert user-written comments into a numerical format that a ML model can interpret. Multiple ML approaches are currently being explored in order to identify and categorize the charging issues being talked about in each review. Ultimately, the results from the ML model will be visualized and explained in a report on customer pain points to be delivered to the ChargeX Consortium, therefore revealing specific areas for improvement in the customer charging experience.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Accelerating the Adoption of Energy Efficiency and Renewables in Warehouses and Distribution Centers

Commercial warehouses and storage facilities represent a large part of the commercial buildings in the United States, and their share increases every year. NREL is working with the U.S. Department of Energy to understand barriers, sector needs, and opportunities to enhance sustainability in the warehouse sector, driving ultra-high efficient, zero-energy design, while considering electrification in buildings and vehicles, grid-friendly operation, and decarbonization. After investigating literature about warehouse sustainability practices and high-performance warehouse case studies, several one-on-one interviews were carried out with warehouse managers and stakeholders. Data collected through literature and the interviews were captured to provide the current status of warehousing in the context of energy efficiency, renewables, carbon emissions, and overall sustainability. The results are intended to inform areas for new research and deployment activities to achieving zero energy and zero carbon goals.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗