Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “vehicle operating data”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

GIS Methodology for Planning Planetary-Rover Operations

A document describes a methodology for utilizing image data downlinked from cameras aboard a robotic ground vehicle (rover) on a remote planet for analyzing and planning operations of the vehicle and of any associated spacecraft. Traditionally, the cataloging and presentation of large numbers of downlinked planetary-exploration images have been done by use of two organizational methods: temporal organization and correlation between activity plans and images. In contrast, the present methodology involves spatial indexing of image data by use of the computational discipline of geographic information systems (GIS), which has been maturing in terrestrial applications for decades, but, until now, has not been widely used in support of exploration of remote planets. The use of GIS to catalog data products for analysis is intended to increase efficiency and effectiveness in planning rover operations, just as GIS has proven to be a source of powerful computational tools in such terrestrial endeavors as law enforcement, military strategic planning, surveying, political science, and epidemiology. The use of GIS also satisfies the need for a map-based user interface that is intuitive to rover-activity planners, many of whom are deeply familiar with maps and know how to use them effectively in field geology.

Powell, Mark↗
NASA NTRS1971

Mariner Mars 1971: Press kit

The news release describes the 1971 launches of Mariner 8 and 9 which were to be the first attempt by NASA to orbit another planet, Mars. Described are: (1) mission capsule; (2) planetary missions; (3) aiming zones; (4) the spacecraft; (5) scientific experiments to be performed; (6) Atlas Centaur launch vehicle; (7) launch operations; (8) tracking and data system and mission operations; and (9) Mariner Mars 71 team and subcontractors.

Mittauer, R. T.↗
NASA NTRS1992

Shuttle entry aerothermodynamic flight research - The Orbiter Experiments (OEX) Program

Results of the OEX program are summarized with emphasis on the information on entry aerothermodynamic phenomena derived from Space Shuttle operations. The discussion focuses on OEX experiment complement and operational history, freestream environment and vehicle attitude data, aerodynamic force and moment data, aerodynamic surface data, and vehicle configuration data. Attention is also given to orbiter aerodynamic performance, stability and control, high-altitude atmospheric density variability, direct simulation Monte Carlo validation, orbital drag variation, and computational fluid dynamic technique validation.

Throckmorton, David A.↗
NASA NTRS2010

Ares I-X: First Flight of a New Era

Since 2005, NASA s Constellation Program has been designing, building, and testing the next generation of launch and space vehicles to carry humans beyond low-Earth orbit (LEO). The Ares Projects at Marshall Space Flight Center (MSFC) are developing the Ares I crew launch vehicle and Ares V cargo launch vehicle. On October 28, 2009, the first development flight test of the Ares I crew launch vehicle, Ares I-X, lifted off from a launch pad at Kennedy Space Center (KSC) on successful suborbital flight. Basing exploration launch vehicle designs on Ares I-X information puts NASA one step closer to full-up "test as you fly," a best practice in vehicle design. Although the final Constellation Program architecture is under review, the Ares I-X data and experience in vehicle design and operations can be applied to any launch vehicle. This paper presents the mission background as well as results and lessons learned from the flight.

Davis, Stephen R.↗
NASA NTRS1989

Applications of graphics to support a testbed for autonomous space vehicle operations

Researchers describe their experience using graphics tools and utilities while building an application, AUTOPS, that uses a graphical Machintosh (TM)-like interface for the input and display of data, and animation graphics to enhance the presentation of results of autonomous space vehicle operations simulations. AUTOPS is a test bed for evaluating decisions for intelligent control systems for autonomous vehicles. Decisions made by an intelligent control system, e.g., a revised mission plan, might be displayed to the user in textual format or he can witness the effects of those decisions via out of window graphics animations. Although a textual description conveys essentials, a graphics animation conveys the replanning results in a more convincing way. Similarily, iconic and menu-driven screen interfaces provide the user with more meaningful options and displays. Presented here are experiences with the SunView and TAE Plus graphics tools used for interface design, and the Johnson Space Center Interactive Graphics Laboratory animation graphics tools used for generating out out of the window graphics.

Schmeckpeper, K. R.↗
NASA NTRS2016

Results of the NASA Kennedy Space Center 50-MHz Doppler Radar Wind Profiler Operational Acceptance Test

This paper presents results of the new Kennedy Space Center (KSC) 50-MHz Doppler Radar Wind Profiler (DRWP) Operational Acceptance Test (OAT). The goal of the OAT was to verify the data quality of the new DRWP against the performance of the previous DRWP in order to use wind data derived by the new DRWP for space launch vehicle operations support at the Eastern Range. The previous DRWP was used as a situational awareness asset for mission operations to identify rapid changes in the wind environment that weather balloons cannot depict. The Marshall Space Flight Center's Natural Environments Branch assessed data from the new DRWP collected during Jan-Feb 2015 against a specified set of test criteria. Data examination verified that the DRWP provides complete profiles every five minutes from 1.8-19.5 km in vertical increments of 150 m. Analysis of 49 concurrent DRWP and balloon profiles presented root mean square wind component differences around 2.0 m/s. Evaluation of the DRWP's coherence between five-minute wind pairs found the effective vertical resolution to be Nyquist-limited at 300 m for both wind components. In addition, the sensitivity to rejecting data that do not have adequate signal was quantified. This paper documents the data, quality control procedures, methodology, and results of each analysis.

Barbre', Robert E., Jr.↗
NASA NTRS1976

Titan/Centaur D-1TTC-5 Helios B flight data report

The fourth operational flight of the newest NASA unmanned launch vehicle is reported. The spacecraft was the Helios B, the second of two solar probes designed and built by the Federal Republic of Germany. The primary mission objective, to place the Helios spacecraft on a heliocentric orbit in the ecliptic plane with a perihelion distance of 0.29 AU, was successfully accomplished. After successful injection of the Helios spacecraft, a series of experiments were performed with the Centaur stage to demonstrate its operational capabilities. All objectives of the extended mission phase were successfully met. This report presents the analysis of the launch vehicle flight data for the primary mission phase of the TC-5 flight.

Adams, K. A.↗
NASA NTRS1977

JSC thunderstorm experiment results

To gain more insight into the various effects of lightning and thunderstorms on future shuttle vehicle launch and landing operations, an experiment was conducted to obtain data on the nature of electric fields in the vicinity of thunderstorms and particularly in the region of cumulonimbus cloud anvils during their various stages of build-up, maturity, and dissipation. These data supplement the airborne electric field data collected during the summer of 1975 in support of the Apollo Soyuz Test Project and the Viking launches. A Learjet aircraft was outfitted with four special electric field meters for collecting data. The onboard aircraft radar was also used to investigate cells embedded in large thunderstorm systems such as those found in frontal and squall line activities. Data were collected from 33 storm cells and used to establish a launch criteria to preclude triggering lightning during shuttle vehicle operations in close proximity to thunderstorms.

Source record↗
DOE OSTI2025

Improving commercial truck fleet composition in emission modeling using 2021 US VIUS data

Commercial trucks are essential elements of the nation's supply chain system. Meanwhile, intensive truck movements contribute significantly to system externalities, such as energy use and air pollution. However, collecting detailed fleet composition and distribution of operational patterns remains a barrier to accurately accounting for these impacts. The recently released 2021 US Vehicle Inventory and Use Survey (US VIUS) fills a critical gap in understanding commercial truck fleet distributions, their operations, and business constraints at the national scale. This study aims to understand the latest US commercial vehicle fleet composition and operational characteristics using 2021 US VIUS data and calibrate the fleet inputs in regulatory emission models to assess the potential emission implications of the VIUS-derived fleet composition. The emission rates for commercial trucks and default fleet composition are collected from the U.S. EPA's MOtor Vehicle Emission Simulator (MOVES4). The 2021 US VIUS data is applied to improve fleet characteristics such as the long-haul fraction and the vehicle mileage accumulation rate. The study also investigates potential emission reduction benefits under various forecasted fleet electrification scenarios. The energy consumption and critical air pollutant rates by vehicle types are compared between MOVES4 and US VIUS fleets for both current and future scenarios to provide insights into the latest U.S. commercial vehicle fleet characteristics and their implications on energy and emissions. This study helps policymakers and practitioners advance the commercial fleet generation for emission models. It also deepens the understanding of the emission reduction potential of the commercial fleet under various fleet projections.

2021 US VIUS↗
NASA NTRS1995

Defining Support Requirements During Conceptual Design of Reusable Launch Vehicles

Current methods for defining the operational support requirements of new systems are data intensive and require significant design information. Methods are being developed to aid in the analysis process of defining support requirements for new launch vehicles during their conceptual design phase that work with the level of information available during this phase. These methods will provide support assessments based on the vehicle design and the operating scenarios. The results can be used both to define expected support requirements for new launch vehicle designs and to help evaluate the benefits of using new technologies. This paper describes the models, their current status, and provides examples of their use.

Morris, W. D.↗
NASA NTRS1989

Application of statistical distribution theory to launch-on-time for space construction logistic support

The ability to launch-on-time and to send payloads into space has progressed dramatically since the days of the earliest missile and space programs. Causes for delay during launch, i.e., unplanned 'holds', are attributable to several sources: weather, range activities, vehicle conditions, human performance, etc. Recent developments in space program, particularly the need for highly reliable logistic support of space construction and the subsequent planned operation of space stations, large unmanned space structures, lunar and Mars bases, and the necessity of providing 'guaranteed' commercial launches have placed increased emphasis on understanding and mastering every aspect of launch vehicle operations. The Center of Space Construction has acquired historical launch vehicle data and is applying these data to the analysis of space launch vehicle logistic support of space construction. This analysis will include development of a better understanding of launch-on-time capability and simulation of required support systems for vehicle assembly and launch which are necessary to support national space program construction schedules. In this paper, the author presents actual launch data on unscheduled 'hold' distributions of various launch vehicles. The data have been supplied by industrial associate companies of the Center for Space Construction. The paper seeks to determine suitable probability models which describe these historical data and that can be used for several purposes such as: inputs to broader simulations of launch vehicle logistic space construction support processes and the determination of which launch operations sources cause the majority of the unscheduled 'holds', and hence to suggest changes which might improve launch-on-time. In particular, the paper investigates the ability of a compound distribution probability model to fit actual data, versus alternative models, and recommends the most productive avenues for future statistical work.

Morgenthaler, George W.↗
NASA NTRS2009

Modeling and Simulation of Variable Mass, Flexible Structures

The advent of the new Ares I launch vehicle has highlighted the need for advanced dynamic analysis tools for variable mass, flexible structures. This system is composed of interconnected flexible stages or components undergoing rapid mass depletion through the consumption of solid or liquid propellant. In addition to large rigid body configuration changes, the system simultaneously experiences elastic deformations. In most applications, the elastic deformations are compatible with linear strain-displacement relationships and are typically modeled using the assumed modes technique. The deformation of the system is approximated through the linear combination of the products of spatial shape functions and generalized time coordinates. Spatial shape functions are traditionally composed of normal mode shapes of the system or even constraint modes and static deformations derived from finite element models of the system. Equations of motion for systems undergoing coupled large rigid body motion and elastic deformation have previously been derived through a number of techniques [1]. However, in these derivations, the mode shapes or spatial shape functions of the system components were considered constant. But with the Ares I vehicle, the structural characteristics of the system are changing with the mass of the system. Previous approaches to solving this problem involve periodic updates to the spatial shape functions or interpolation between shape functions based on system mass or elapsed mission time. These solutions often introduce misleading or even unstable numerical transients into the system. Plus, interpolation on a shape function is not intuitive. This paper presents an approach in which the shape functions are held constant and operate on the changing mass and stiffness matrices of the vehicle components. Each vehicle stage or component finite element model is broken into dry structure and propellant models. A library of propellant models is used to describe the distribution of mass in the fuel tank or Solid Rocket Booster (SRB) case for various propellant levels. Based on the mass consumed by the liquid engine or SRB, the appropriate propellant model is coupled with the dry structure model for the stage. Then using vehicle configuration data, the integrated vehicle model is assembled and operated on by the constant system shape functions. The system mode shapes and frequencies can then be computed from the resulting generalized mass and stiffness matrices for that mass configuration. The rigid body mass properties of the vehicle are derived from the integrated vehicle model. The coupling terms between the vehicle rigid body motion and elastic deformation are also updated from the constant system shape functions and the integrated vehicle model. This approach was first used to analyze variable mass spinning beams and then prototyped into a generic dynamics simulation engine. The resulting code was tested against Crew Launch Vehicle (CLV-)class problems worked in the TREETOPS simulation package and by Wilson [2]. The Ares I System Integration Laboratory (SIL) is currently being developed at the Marshall Space Flight Center (MSFC) to test vehicle avionics hardware and software in a hardware-in-the-loop (HWIL) environment and certify that the integrated system is prepared for flight. The Ares I SIL utilizes the Ares Real-Time Environment for Modeling, Integration, and Simulation (ARTEMIS) tool to simulate the launch vehicle and stimulate avionics hardware. Due to the presence of vehicle control system filters and the thrust oscillation suppression system, which are tuned to the structural characteristics of the vehicle, ARTEMIS must incorporate accurate structural models of the Ares I launch vehicle. The ARTEMIS core dynamics simulation models the highly coupled nature of the vehicle flexible body dynamics, propellant slosh, and vehicle nozzle inertia effects combined with mass and flexible body properties that vary significant with time during the flight. All forces that act on the vehicle during flight must be simulated, including deflected engine thrust force, spatially distributed aerodynamic forces, gravity, and reaction control jet thrust forces. These forces are used to excite an integrated flexible vehicle, slosh, and nozzle dynamics model for the vehicle stack that simulates large rigid body translations and rotations along with small elastic deformations. Highly effective matrix math operations on a distributed, threaded high-performance simulation node allow ARTEMIS to retain up to 30 modes of flex for real-time simulation. Stage elements that separate from the stack during flight are propagated as independent rigid six degrees of freedom (6DOF) bodies. This paper will present the formulation of the resulting equations of motion, solutions to example problems, and describe the resulting dynamics simulation engine within ARTEMIS.

Tobbe, Patrick A.↗
DOE OSTI2026

Data-Driven Modeling and Correction of Vehicle Dynamics

We develop a data-driven framework for learning and correcting nonautonomous vehicle dynamics. Physics-based vehicle models are often simplified for tractability and therefore exhibit inherent model-form uncertainty, motivating the need for data-driven correction. Moreover, nonautonomous dynamics are governed by time-dependent control inputs, which pose challenges in learning predictive models directly from temporal snapshot data. To address these, we reformulate the vehicle dynamics via a local parameterization of the time-dependent inputs, yielding a modified system composed ofa sequence of local parametric dynamical systems. Here, we approximate these parametric systems using two complementary approaches. First, we employ the dimension reduction and interpolation in parameter space (DRIPS) methodology to construct efficient linear surrogate models, equipped with lifted observable spaces and manifold-based operator interpolation. This enables data-efficient learning of vehicle models whose dynamics admit accurate linear representations in the lifted spaces. Second, for more strongly nonlinear systems, we employ flow map learning (FML), a deep neural network (DNN) approach that approximates the parametric evolution map without requiring special treatment of nonlinearities. We further extend FML with a transfer-learning-based model correction procedure, enabling the correction of misspecified prior models using only a sparse set of high-fidelity or experimental measurements, without assuming a prescribed form for the correction term. Through a suite of numerical experiments on unicycle, simplified bicycle, and slip-based bicycle models, we demonstrate that DRIPS offers robust and highly data-efficient learning of nonautonomous vehicle dynamics, while FML provides expressive nonlinear modeling and effective correction of model-form errors under severe data scarcity.

data-driven modeling↗
NASA NTRS2013

Design Study of Propulsion and Drive Systems for the Large Civil TiltRotor (LCTR2) Rotorcraft

Boeing, Rolls Royce, and NASA have worked together to complete a parametric sizing study for NASA's Large Civil Tilt Rotor (LCTR2) concept 2nd iteration. Vehicle gross weight and fuel usage were evaluated as propulsion and drive system characteristics were varied to maximize the benefit of reduced rotor tip speed during cruise conditions. The study examined different combinations of engine and gearbox variability to achieve rotor cruise tip speed reductions down to 54% of the hover tip speed. Previous NASA studies identified that a 54% rotor speed reduction in cruise minimizes vehicle gross weight and fuel burn. The LCTR2 was the study baseline for initial sizing. This study included rotor tip speed ratios (cruise to hover) of 100%, 77% and 54% at different combinations of engine RPM and gearbox speed reductions, which were analyzed to achieve the lightest overall vehicle gross weight (GW) at the chosen rotor tip speed ratio. Different engine and gearbox technology levels are applied ranging from commercial off-the-shelf (COTS) engines and gearbox technology to entry-in-service (EIS) dates of 2025 and 2035 to assess the benefits of advanced technology on vehicle gross weight and fuel burn. Interim results were previously reported1. This technical paper extends that work and summarizes the final study results including additional engine and drive system study accomplishments. New vehicle sizing data is presented for engine performance at a single operating speed with a multispeed drive system. Modeling details for LCTR2 vehicle sizing and subject engine and drive sub-systems are presented as well. This study was conducted in support of NASA's Fundamental Aeronautics Program, Subsonic Rotary Wing Project.

Robuck, Mark↗
NASA NTRS2015

Assimilation of Wind Profiles from Multiple Doppler Radar Wind Profilers for Space Launch Vehicle Applications

Atmospheric wind data are required by space launch vehicles in order to assess flight vehicle loads and performance on day-of-launch. Space launch ranges at NASA's Kennedy Space Center co-located with the United States Air Force's (USAF) Eastern Range (ER) at Cape Canaveral Air Force Station and USAF's Western Range (WR) at Vandenberg Air Force Base have extensive networks of in-situ and remote sensing instrumentation to measure atmospheric winds. Each instrument's technique to measure winds has advantages and disadvantages in regards to use within vehicle trajectory analyses. Balloons measure wind at all altitudes necessary for vehicle assessments, but two primary disadvantages exist when applying balloon output. First, balloons require approximately one hour to reach required altitudes. Second, balloons are steered by atmospheric winds down range of the launch site that could significantly differ from those winds along the vehicle ascent trajectory. These issues are mitigated by use of vertically pointing Doppler Radar Wind Profilers (DRWPs). However, multiple DRWP instruments are required to provide wind data over altitude ranges necessary for vehicle trajectory assessments. The various DRWP systems have different operating configurations resulting in different temporal and spatial sampling intervals. Therefore, software was developed to combine data from both DRWP-generated profiles into a single profile for use in vehicle trajectory analyses. This paper will present details of the splicing software algorithms and will provide sample output.

Decker, Ryan K.↗
NASA NTRS2013

Discrete Data Qualification System and Method Comprising Noise Series Fault Detection

A Sensor Data Qualification (SDQ) function has been developed that allows the onboard flight computers on NASA s launch vehicles to determine the validity of sensor data to ensure that critical safety and operational decisions are not based on faulty sensor data. This SDQ function includes a novel noise series fault detection algorithm for qualification of the output data from LO2 and LH2 low-level liquid sensors. These sensors are positioned in a launch vehicle s propellant tanks in order to detect propellant depletion during a rocket engine s boost operating phase. This detection capability can prevent the catastrophic situation where the engine operates without propellant. The output from each LO2 and LH2 low-level liquid sensor is a discrete valued signal that is expected to be in either of two states, depending on whether the sensor is immersed (wet) or exposed (dry). Conventional methods for sensor data qualification, such as threshold limit checking, are not effective for this type of signal due to its discrete binary-state nature. To address this data qualification challenge, a noise computation and evaluation method, also known as a noise fault detector, was developed to detect unreasonable statistical characteristics in the discrete data stream. The method operates on a time series of discrete data observations over a moving window of data points and performs a continuous examination of the resulting observation stream to identify the presence of anomalous characteristics. If the method determines the existence of anomalous results, the data from the sensor is disqualified for use by other monitoring or control functions.

Fulton, Christopher↗
NASA NTRSDate not supplied

Immutable Secure Data Exchange and Storage for Urban Air Mobility Environments

The Urban Air Mobility (UAM) environment is derived from the Unmanned Traffic Management (UTM) concept of operations. Within the environment, UAM operators work independently to manage aerial vehicles in the urban environment. Providers of Services (PSU), UAM operators, and Supplemental Data Service Providers provide services to support flight operations within the UAM environment. The intent of this work is to leverage a permissioned blockchain approach, to, simulate secure data exchange and storage for UAM environments. Blockchain technologies can be used for identity management of vehicles, people, and systems.

Blockchain↗