Search NASA⌕ Search

SEARCH · Search NASA

Results for “engineering 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 1,765 records · Page 98
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Internship Abstract - Aerosciences and Flight Mechanics Intern

Mars is a hard place to land on, but my internship with NASA's Aerosciences & Flight Mechanics branch has shown me the ways in which men and women will one day land safely. I work on Mars Aerocapture, an aeroassist maneuver that reduces the fuel necessary to "capture" into Martian orbit before a descent. The spacecraft flies through the Martian atmosphere to lose energy through heating before it exits back into space, this time at a slower velocity and in orbit around Mars. Spacecraft will need to maneuver through the Martian atmosphere to accurately hit their orbit, and they will need to survive the generated heat. Engineering teams need simulation data to continue their designs, and the guidance algorithm that ensures a proper orbit insertion needs to be refined - two jobs that fell to me at the summer's start. Engineers within my branch have developed two concept aerocapture vehicles, and I run simulations on their behavior during the maneuver. I also test and refine the guidance algorithm. I spent the first few weeks familiarizing myself with the simulation software, troubleshooting various guidance bugs and writing code. Everything runs smoothly now, and I recently sent my first set of trajectory data to a Thermal Protection System group so they can incorporate it into their heat-bearing material designs. I hope to generate plenty of data in the next few weeks for various engineering groups before my internship ends mid-August. My major accomplishment so far is improving the guidance algorithm. It is a relatively new algorithm that promises higher accuracy and fuel efficiency, but it hasn't undergone extensive testing yet. I've had the opportunity to work with the principal developer - a professor at Iowa State University - to find and fix several issues. I was also assigned the task of expanding the branch's aerodynamic heating simulation software. I am excited to do this because engineers in the future will use my work to generate meaningful data and make design decisions. My internship has taught me to how to teach myself. There are no tutors, study sessions or professor office hours. When I am given an assignment I am expected to figure out how to accomplish it, and I have grown in my problem solving abilities. My summer experience has reinforced my drive to work at NASA, and I can definitely see myself working full time on the aerocapture project, or something similar.

Rangel, John↗
NASA NTRS2013

Combustion Stability of the Gas Generator Assembly from J-2X Engine E10001 and Powerpack Tests

Testing of a powerpack configuration (turbomachinery and gas generator assembly) and the first complete engine system of the liquid oxygen/liquid hydrogen propellant J-2X rocket engine have been completed at the NASA Stennis Space Center. The combustion stability characteristics of the gas generator assemblies on these two systems are of interest for reporting since considerable effort was expended to eliminate combustion instability during early development of the gas generator assembly with workhorse hardware. Comparing the final workhorse gas generator assembly development test data to the powerpack and engine system test data provides an opportunity to investigate how the nearly identical configurations of gas generator assemblies operate with two very different propellant supply systems one the autonomous pressure-fed test configuration on the workhorse development test stand, the other the pump-fed configurations on the powerpack and engine systems. The development of the gas generator assembly and the elimination of the combustion instability on the pressure-fed workhorse test stand have been reported extensively in the two previous Liquid Propulsion Subcommittee meetings 1-7. The powerpack and engine system testing have been conducted from mid-2011 through 2012. All tests of the powerpack and engine system gas generator systems to date have been stable. However, measureable dynamic behavior, similar to that observed on the pressure-fed test stand and reported in Ref. [6] and attributed to an injection-coupled response, has appeared in both powerpack and engine system tests. As discussed in Ref. [6], these injection-coupled responses are influenced by the interaction of the combustion chamber with a branch pipe in the hot gas duct that supplies gaseous helium to pre-spin the turbine during the start transient. This paper presents the powerpack and engine system gas generator test data, compares these data to the development test data, and provides additional combustion stability analyses of the configurations.

Hulka, J. R.↗
DOE OSTI2023

Utilizing data-based modeling with low life cycle GHG emissions algae biofuels for engine optimization

Aquatic microalgae are a highly promising feedstock for the production of biocrude and tailored biofuels, with distinct advantages over traditional terrestrial crops, such as reduced land use and avoidance of food production competition. However, unlocking their full potential requires the development of biofuels with low life cycle greenhouse emissions biofuels, such as algae biofuels, which can significantly reduce the environmental impact of the transportation systems without requiring a complete overhaul of existing engine technology. In this study, we employ cutting-edge data-based AI modeling techniques to optimize the performance of heavy-duty engines, with a focus on transitioning towards biofuels with low life cycle greenhouse emissions biofuels. Our methodology offers significant advantages over traditional sweep testing, enabling efficient and accurate optimization of engine performance with minimal time and resources consumption. Our findings demonstrate the potential of utilizing this approach, with up to 55% NOx emissions reductions and up to 2% reduction in fuel consumption compared to the baseline optimized point. Moving forward, we plan to utilize a 30% blend of algae biofuels with diesel fuel, with the ultimate goal of achieving up to 60% lifecycle GHG emissions. Lastly, we plan to compare the results with 100% renewable biodiesel to add an additional dimension of investigating the impact of fuel chemistry on engine optimization. Overall, this study underscores the vital importance of biofuels for reducing the carbon footprint of the transportation sector and supporting a sustainable future. By harnessing the power of data-based AI modeling with low life cycle greenhouse emissions biofuels, we can accelerate the adoption of more environmentally friendly transportation systems and reduce their impact on the planet. Our findings contribute to this transition and offer insights for developing efficient and effective strategies for addressing global climate change.

09 BIOMASS FUELS↗
NASA NTRS1972

Study of solid rocket motor for space, shuttle booster, volume 2, book 4 appendices B thru D

The mass properties and related data for the solid propellant rocket engine for use with the space shuttle are presented. Data for three solid propellant rocket engines are provided. The three designs considered are: (1) baseline parallel burn, (2) optional parallel burn, and (3) baseline series burn. Layouts of the respective designs to show design and dimensional data are included.

Source record↗
NASA NTRS1976

Modeling and analysis of the TF30-P-3 compressor system with inlet pressure distortion

Circumferential inlet distortion testing of a TF30-P-3 afterburning turbofan engine was conducted at NASA-Lewis Research Center. Pratt and Whitney Aircraft analyzed the data using its multiple segment parallel compressor model and classical compressor theory. Distortion attenuation analysis resulted in a detailed flow field calculation with good agreement between multiple segment model predictions and the test data. Sensitivity of the engine stall line to circumferential inlet distortion was calculated on the basis of parallel compressor theory to be more severe than indicated by the data. However, the calculated stall site location was in agreement with high response instrumentation measurements.

Mazzawy, R. S.↗
NASA NTRS1974

Real-time simulation of the TF30-P-3 turbofan engine using a hybrid computer

A real-time, hybrid-computer simulation of the TF30-P-3 turbofan engine was developed. The simulation was primarily analog in nature but used the digital portion of the hybrid computer to perform bivariate function generation associated with the performance of the engine's rotating components. FORTRAN listings and analog patching diagrams are provided. The hybrid simulation was controlled by a digital computer programmed to simulate the engine's standard hydromechanical control. Both steady-state and dynamic data obtained from the digitally controlled engine simulation are presented. Hybrid simulation data are compared with data obtained from a digital simulation provided by the engine manufacturer. The comparisons indicate that the real-time hybrid simulation adequately matches the baseline digital simulation.

Szuch, J. R.↗
NASA NTRS1981

Reporting Capabilities and Management of the DSN Energy Data Base

The DSN Energy Data Base is a collection of computer files developed and maintained by DSN Engineering. The energy consumption data must be updated monthly and summarized and displayed in printed output as desired. The methods used to handle the data and perform these tasks are described.

Hughes, R. D.↗
NASA NTRS2022

VIPRE: A Tool Aiding the Design for Entry Probe Missions

Exploring planetary atmospheres uncovers important information for how our solar system formed and evolved. While remote sensing is extensively used, some crucial observations require in-situ measurements by an atmospheric probe. Given their scientific importance, probe missions to Saturn, Uranus and Neptune are considered for the coming decades. In anticipation of future probe missions, the software tool VIPRE was developed as proof-of-concept to facilitate selection of probe entry locations. Currently, there is no analytical way to identify which interplanetary trajectory from thousands of feasible launch opportunities is optimal for a considered mission concept. The search and decision process for that solution is complex and relies on the intuition of mission designers, who focus on a subset of trajectories to make the trade space manageable. The idea of VIPRE is to (1) generate a multi-dimensional data cube showing relevant engineering and science parameters simultaneously for thousands of trajectories, and (2) visualize the data for all entry sites over the body's envelope. VIPRE lays the foundation to make the data available for browsing in a 3-D visualization to identify the best family of solutions for a given mission. The paper introduces the validated and verified core algorithms of VIPRE, published on GitHub. VIPRE serves as a basic framework to be used and extended for different purposes. The paper presents the motivation for the development and algorithms. It explains the computation and data visualization strategy, and gives a list of suggested functionalities to extend and further develop VIPRE to fully leverage its potential.

Ice Giants↗
DOE OSTI2026

Leveraging Inequality-Constrained Data for Enhanced Liquidus Temperature Prediction in Nuclear Waste Glass Melts

Inequality-constrained data are frequently discarded in engineering, leading to significant information loss in data-scarce domains like glass characterization in nuclear waste vitrification. This paper presents a nonparametric censored-data regression framework based on an l1-norm optimization criterion that leverages slack variables to integrate left-, right-, and interval-constrained observations into training without distributional assumptions. Validated on synthetic data and a Physics-Informed Neural Network (PINN) for predicting liquidus temperature (TL), the method improved R2 from 0.60 to 0.89 and reduced Mean Absolute Error (MAE) by 48% (51.46 to 26.89?rC) on deterministic values. The traditional models failed to satisfy any inequality constraints while the proposed l1-norm PINN satisfies 81.25% of the constraints. The proposed framework effectively extracts actionable information from previously unusable data to enhance predictive accuracy, reduce epistemic uncertainty, and ensure physical consistency in complex industrial applications.

Garcia-Morado, Erick↗
NASA NTRS1975

Longitudinal aerodynamic characteristics of a deflected-thrust propulsive-lift transport model

A wind-tunnel investigation was conducted to determine the effect of deflecting the engine exit of a four-engine double-slotted flap transport to provide STOL performance. Longitudinal aerodynamic data were obtained at various engine exit positions and deflections. The data were obtained at three flap deflections representing cruise, take-off, and landing conditions for a range of angles of attack and various thrust coefficients. Downwash angles at the location of the horizontal tail were measured. The data are presented without analysis or discussion. Photographs of the test configurations are shown.

Hoad, D. R.↗
NASA NTRS1988

Liquid rocket booster study. Volume 2, book 4, appendices 6-8: Reports of Rocketdyne, Pratt and Whitney, and TRW

For the pressure fed engines, detailed trade studies were conducted defining engine features such as thrust vector control methods, thrust chamber construction, etc. This was followed by engine design layouts and booster propulsion configuration layouts. For the pump fed engines parametric performance and weight data was generated for both O2/H2 and O2/RP-1 engines. Subsequent studies resulted in the selection of both LOX/RP-1 and O2/H2 propellants for the pump fed engines. More detailed analysis of the selected LOX/RP-1 and O2/H2 engines was conducted during the final phase of the study.

Source record↗
NASA NTRS2009

Data Mining at NASA: From Theory to Applications

This slide presentation demonstrates the data mining/machine learning capabilities of NASA Ames and Intelligent Data Understanding (IDU) group. This will encompass the work done recently in the group by various group members. The IDU group develops novel algorithms to detect, classify, and predict events in large data streams for scientific and engineering systems. This presentation for Knowledge Discovery and Data Mining 2009 is to demonstrate the data mining/machine learning capabilities of NASA Ames and IDU group. This will encompass the work done re cently in the group by various group members.

Srivastava, Ashok N.↗
NASA NTRS1975

Effect of afterburner lights and inlet unstarts on a mixed compression inlet turbofan engine operating at Mach 2.5

Data are presented to show the response of an uncontrolled inlet to afterburner lightoff disturbances when a mixed-compression inlet is coupled to a turbofan engine. The results show a significant upstream shock excursion when the afterburner lights which is a result of the direct communication between the afterburner region and the inlet by means of the fan duct and fan stages. In addition results of a waveform analysis on the inlet pressure response to the afterburner light is presented. Inlet unstarts and their effect on operation of the propulsion system is also discussed.

Baumbick, R. J.↗
NASA NTRS2019

Charactarization of Thermal Protection Systems

In 2012, NASA's mission of landing the Mars Science Laboratory (MSL) on Mars was successful. MSL was protected by an ablative heatshield of tiled low density material known as PICA (phenolic impregnated carbon ablator). The heatshield was instrumented with MEDLI (MSL Entry Descent Landing Instrument) a suite of sensors & thermocouples at discrete locations in order to monitor the in-depth ablator temperature response and surface pressure. MEDLI was designed and developed by NASA Langley, in partnership with NASA Ames Research Center for the purposes of probing Mars and evaluating the performance of the spacecraft upon entry into the Martian atmosphere. The flight data reduces the uncertainty in engineer models for predicting the response of a spacecraft towards the extreme heating environment of an entry into the Martian atmosphere. MEDLI2 is a part of the Mars 2020 mission and is the next-generation sensor suite for entry, descent, and landing. This data will again help engineers validate their flight models. Additionally, the atmospheric data, can help us understand atmospheric density and winds. This is a critical study for reducing risks to both robotic and future human missions to Mars. Engineered models for Mars 2020 are dependent upon parameters related to the materials response to heating and radiation. In this work, the thermal properties and other measurements of various ablative materials are analyzed to achieve greater utility of the 2012 MEDLI flight data and more accurately determine the parameters being used in Mars 2020. The purpose of this study was to measure specific heat, thermal conductivity, char yield, reflectance as a function of wavelength, and other thermal parameters and optical properties of various ablative materials. CO2(g) at extreme temperatures emits radiation impacting MEDLI2 flight predictions. Emissivity & absorptivity as a function of temperature were calculated from FTIR and UV-Vis data as a means of investigating whether these materials might absorb CO2 radiation upon entry into the Mars atmosphere.

HEEET↗
DOE OSTI2019

Towards a CAN IDS Based on a Neural Network Data Field Predictor

Modern vehicles contain a few controller area networks (CANs), which allow scores of on-board electronic control units (ECUs) to communicate messages critical to vehicle functions and driver safety. CAN provides a lightweight and reliable broadcast protocol but is bereft of security features. As evidenced by many recent research works, CAN exploits are possible both remotely and with direct access, fueling a growing CAN intrusion detection system (IDS) body of research. A challenge for pioneering vehicle-agnostic IDSs is that passenger vehicles' CAN message encodings are proprietary, defined and held secret by original equipment manufacturers (OEMs). Targeting detection of next-generation attacks, in which messages are sent from the expected ECU at the expected time but with malicious content, researchers are now seeking to leverage "CAN data models'', which predict future CAN messages and use prediction error to identify anomalous, hopefully malicious CAN messages. Yet, current works model CAN signals post-translation, i.e., after applying OEM-donated or reverse-engineered translations from raw data. We present initial IDS results testing deep neural networks used to predict CAN data at the bit level, targeting IDS capabilities that avoiding reverse engineering proprietary encodings. Our results suggest the method is promising for data with signals exhibiting dependence on previous or concurrent inputs.

Pawelec, Krzysztof↗
NASA NTRS2017

A Dynamic Model for the Evaluation of Aircraft Engine Icing Detection and Control-Based Mitigation Strategies

Aircraft flying in regions of high ice crystal concentrations are susceptible to the buildup of ice within the compression system of their gas turbine engines. This ice buildup can restrict engine airflow and cause an uncommanded loss of thrust, also known as engine rollback, which poses a potential safety hazard. The aviation community is conducting research to understand this phenomena, and to identify avoidance and mitigation strategies to address the concern. To support this research, a dynamic turbofan engine model has been created to enable the development and evaluation of engine icing detection and control-based mitigation strategies. This model captures the dynamic engine response due to high ice water ingestion and the buildup of ice blockage in the engines low pressure compressor. It includes a fuel control system allowing engine closed-loop control effects during engine icing events to be emulated. The model also includes bleed air valve and horsepower extraction actuators that, when modulated, change overall engine operating performance. This system-level model has been developed and compared against test data acquired from an aircraft turbofan engine undergoing engine icing studies in an altitude test facility and also against outputs from the manufacturers customer deck. This paper will describe the model and show results of its dynamic response under open-loop and closed-loop control operating scenarios in the presence of ice blockage buildup compared against engine test cell data. Planned follow-on use of the model for the development and evaluation of icing detection and control-based mitigation strategies will also be discussed. The intent is to combine the model and control mitigation logic with an engine icing risk calculation tool capable of predicting the risk of engine icing based on current operating conditions. Upon detection of an operating region of risk for engine icing events, the control mitigation logic will seek to change the engines operating point to a region of lower risk through the modulation of available control actuators while maintaining the desired engine thrust output. Follow-on work will assess the feasibility and effectiveness of such control-based mitigation strategies.

engine control↗