SEARCH · Engineering Papers

Results for “load 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.

SourceResearch connectionFrom yearThrough year

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

At least 469 records · Page 26

All sources NASA NTRS DOE OSTI

DOE OSTI2023

Creating an Advanced Sensor Network to calculate real-time, mass-weighted flue gas composition and air heater leakage of a coal-fired utility boiler under dynamic operating conditions

Utilization of renewable energy sources to minimize the environmental impact of energy production has changed the way utility boilers operate, requiring frequent load cycling between full load and partial loads as low as 30%. Dynamic operation of coal-fired utility boilers significantly reduces boiler efficiency when compared to steady state at full load. Data-driven plant optimization has shown success with coal-fired utility boilers under dynamic operating conditions. The purpose of this work was to create an Advanced Sensor Network (ASN) to provide more extensive real-time data to inform dynamic plant optimization of Net Unit Heat Rate (NUHR). The ASN consists of gas sampling grids in the convective pass of the boiler and downstream of the air heater. These sampling grids allow for quantification of spatial variation of flue gas within the boiler and calculation of mass-weighted composition of flue gas through the combination of composition, velocity, and temperature measurements. The comparison of O 2 between the inlet and outlet of the air heater is used to calculate air leakage in real time. Flue gas composition and air heater leakage are both important factors in boiler efficiency and NUHR. Further, the results of this work support the value of mass-weighted averages for determining flue gas composition accurately. The measurements from the ASN show increased composition stratification during dynamic operation, with an average standard deviation 38% higher than observed during steady-state operation. Air heater leakage was also observed to increase from 2.8% to 5.1% following a load change. Prior to the installation of the ASN, these data would not have been available for dynamic control. These real-time data will be leveraged to calculate and optimize for NUHR during dynamic operation in future work.

42 ENGINEERING↗

NASA NTRSDate not supplied

Applicability of Loads Estimation Techniques Using Sparse Acceleration Sensor Data to Spacecraft Structural Health Monitoring

The use of structural health monitoring systems on spacecraft structures can play a crucial role in ensuring the safety, reliability, and longevity of the structure by gathering and analyzing onboard sensor data. Of specific importance is monitoring for excessive loading at critical interfaces as any off-nominal structural excitations experienced by spacecraft structures can cause early unpredicted high structural life consumption or damage. The availability and cost of flight-certified sensors along with the size of spacecraft structures and allowable payload mass drives the need for a method to estimate loads using sparsely-located sensors. Numerous approaches such as physics-based, statistical learning, and physics-enhanced statistical learning algorithms have gained popularity among structural prognostics applications. However, developing noise-robust prediction models to assess loads and structural life predictions from a sparse multi-sensor data acquisition system can be a challenging task. This paper discusses the evaluation of physics-based versus machine-learning algorithms for predicting loads and structural life at mission critical locations on the spacecraft structure using a finite element loads analysis with the application of simulated noise and noise reduction techniques. To estimate the loads from accelerations, the physics-based algorithm leverages a loads transformation matrix from a Craig-Bampton reduced finite element model. A System Equivalent Reduction Expansion Process (SEREP) and a pseudo-inverse approach are considered to expand from the onboard sensor degrees of freedom to the Craig-Bampton model degrees of freedom. The machine learning algorithm provides a data driven solution/mapping of the sensor accelerations to the loads at the mission critical locations using a high dimensionality analysis. Although these strategies produce comparable loads prediction without noise, the limitations of these strategies with incorporating simulated noise and noise reduction techniques with low signal to noise ratio signals are evaluated. The study demonstrates the immense potential of statistical learning algorithms for sparse structural prognostic models and enhancing signal denoising techniques. These findings also highlight the need for noise-resilient prognostic models and low-noise data acquisition systems onboard spacecraft structures.

Spacecraft Structural Health Monitoring↗

NASA NTRS1977

Determination of stack plume properties from satellite imagery

LANDSAT imagery data were analyzed to determine the quantitative properties of a stack plume emitted from a moderate-sized pulp mill. Overlapping, consecutive-day MSS data provided plume/no plume radiances upwelling from the area of interest. These values from both the plume and its shadow were used to evaluate plume radius, height, particle concentration and scattering function, and total particle loading. Imagery data from a 10 by 10 km region in the vicinity of the mill were normalized to correct for minor atmospheric, solar and viewing angle changes for the two observation days, and cloud shadow data were used to evaluate sky radiance. The effects of the Sun angle, surface reflectance, SNR and spatial resolution are treated in the paper.

Staylor, W. F.↗

NASA NTRS1998

Wind-Tunnel Evaluation of the Effect of Blade Nonstructural Mass Distribution on Helicopter Fixed-System Loads

This report provides data obtained during a wind-tunnel test conducted to investigate parametrically the effect of blade nonstructural mass on helicopter fixed-system vibratory loads. The data were obtained with aeroelastically scaled model rotor blades that allowed for the addition of concentrated nonstructural masses at multiple locations along the blade radius. Testing was conducted for advance ratios ranging from 0.10 to 0.35 for 10 blade-mass configurations. Three thrust levels were obtained at representative full-scale shaft angles for each blade-mass configuration. This report provides the fixed-system forces and moments measured during testing. The comprehensive database obtained is well-suited for use in correlation and development of advanced rotorcraft analyses.

ARES-1(AEROELASTIC ROTOR EXPERIMENTAL SYSTEM 1)↗

DOE OSTI2025

Energy innovation in the US buildings sector: Setting the stage and mapping the future

Jared Langevin is a staff scientist at Lawrence Berkeley National Laboratory, where he leads modeling of US buildings sector innovation and its implications for energy demand, consumer costs, and the power grid. Eric Wilson is a senior research engineer in the Building Technologies and Sciences Center at the National Renewable Energy Laboratory (NREL). Much of his 15-year career at NREL has revolved around modeling and analysis of the US building stock. Jared and Eric co-led the development of a National Blueprint for buildings sector innovation while serving as advisors to the US Department of Energy’s Deputy Assistant Secretary for Buildings and Industry.

Langevin, Jared↗

NASA NTRS1991

Expert system development for probabilistic load simulation

A knowledge based system LDEXPT using the intelligent data base paradigm was developed for the Composite Load Spectra (CLS) project to simulate the probabilistic loads of a space propulsion system. The knowledge base approach provides a systematic framework of organizing the load information and facilitates the coupling of the numerical processing and symbolic (information) processing. It provides an incremental development environment for building generic probabilistic load models and book keeping the associated load information. A large volume of load data is stored in the data base and can be retrieved and updated by a built-in data base management system. The data base system standardizes the data storage and retrieval procedures. It helps maintain data integrity and avoid data redundancy. The intelligent data base paradigm provides ways to build expert system rules for shallow and deep reasoning and thus provides expert knowledge to help users to obtain the required probabilistic load spectra.

Ho, H.↗

NASA NTRS1980

Expanded study of feasibility of measuring in-flight 747/JT9D loads, performance, clearance, and thermal data

The JT9D jet engine exhibits a TSFC loss of about 1 percent in the initial 50 flight cycles of a new engine. These early losses are caused by seal-wear induced opening of running clearances in the engine gas path. The causes of this seal wear have been identified as flight induced loads which deflect the engine cases and rotors, causing the rotating blades to rub against the seal surfaces, producing permanent clearance changes. The real level of flight loads encountered during airplane acceptance testing and revenue service and the engine's response in the dynamic flight environment were investigated. The feasibility of direct measurement of these flight loads and their effects by concurrent measurement of 747/JT9D propulsion system aerodynamic and inertia loads and the critical engine clearance and performance changes during 747 flight and ground operations was evaluated. A number of technical options were examined in relation to the total estimated program cost to facilitate selection of the most cost effective option. It is concluded that a flight test program meeting the overall objective of determining the levels of aerodynamic and inertia load levels to which the engine is exposed during the initial flight acceptance test and normal flight maneuvers is feasible and desirable. A specific recommended flight test program, based on the evaluation of cost effectiveness, is defined.

Sallee, G. P.↗

DOE OSTI2024

Load summary table for all sites

Summary peak load for all analyzed sites as part of study. The results are presented in 5 year increments

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1993

An examination of the aerodynamic moment on rotor blade tips using flight test data and analysis

The analysis CAMRAD/JA is used to model two aircraft, a Puma with a swept-tip blade and a UH-60A Black Hawk. The accuracy of the analysis in predicting the torsion loads is assessed by comparing the predicted loads with measurements from flight tests. The influence of assumptions in the analytical model is examined by varying model parameters and comparing the predicted results to baseline values for the torsion loads. Flight test data from a research Puma are used to identify the source of torsion loads. These data indicate that the aerodynamic section moment in the region of the blade tip dominates torsion loading in high-speed flight. Both the aerodynamic section moment at the blade tip and the pitch-link loads are characterized by large positive (nose-up) moments in the first quadrant with rapid reversal of load so that the moment is negative in the second quadrant. Both the character and magnitude of this loading are missed by the CAMRAD/JA analysis.

Maier, Thomas H.↗

NASA NTRS2010

Enhanced Modeling of First-Order Plant Equations of Motion for Aeroelastic and Aeroservoelastic Applications

A methodology is described for generating first-order plant equations of motion for aeroelastic and aeroservoelastic applications. The description begins with the process of generating data files representing specialized mode-shapes, such as rigid-body and control surface modes, using both PATRAN and NASTRAN analysis. NASTRAN executes the 146 solution sequence using numerous Direct Matrix Abstraction Program (DMAP) calls to import the mode-shape files and to perform the aeroelastic response analysis. The aeroelastic response analysis calculates and extracts structural frequencies, generalized masses, frequency-dependent generalized aerodynamic force (GAF) coefficients, sensor deflections and load coefficients data as text-formatted data files. The data files are then re-sequenced and re-formatted using a custom written FORTRAN program. The text-formatted data files are stored and coefficients for s-plane equations are fitted to the frequency-dependent GAF coefficients using two Interactions of Structures, Aerodynamics and Controls (ISAC) programs. With tabular files from stored data created by ISAC, MATLAB generates the first-order aeroservoelastic plant equations of motion. These equations include control-surface actuator, turbulence, sensor and load modeling. Altitude varying root-locus plot and PSD plot results for a model of the F-18 aircraft are presented to demonstrate the capability.

Pototzky, Anthony S.↗

DOE OSTI2020

Real-World Distribution System Modeling Framework for Transmission-and-Distribution Cosimulation: Preprint

This paper presents a modeling methodology for realistic distribution system simulation and analysis. The methodology involves three major approaches: utility model conversion, feeder load modeling, and feeder model validation. The feeder models obtained from the utility are converted to the format that is more flexible for analysis and algorithm development. The load profiles down to each node are modeled in detail using advanced metering infrastructure data and supervisory control and data acquisition (SCADA) system measured load data. Then the distribution system models are validated by comparing the simulated feeder-head voltage results and SCADA measured voltage data. To better understand the bulk system operations and the interactions between transmission and distribution systems, the modeled realistic distribution systems are integrated into a transmission-and-distribution cosimulation framework to perform the system simulation from the bulk system down to each node in the distribution system.

load modeling↗

DOE OSTI2023

IDB Data Loader

The International Database of Reference Gamma-Ray Spectra of Various Nuclear Matter is designed to hold curated gamma spectral data and will be hosted by the International Atomic Energy Agency on its public facing web site. Currently, the database to be hosted is given to the International Atomic Energy Agency by Sandia. This document describes the application used by Sandia to load spectral data into a database.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

NASA NTRS1998

Wind-Tunnel Evaluation of the Effect of Blade Nonstructural Mass Distribution on Helicopter Fixed-System Loads

Wilbur, Matthew L.↗

NASA NTRS1972

Preliminary design of an auxiliary power unit for the space shuttle. Volume 5: Selected system cycle performance data

Detailed cycle steady-state performance data are presented for the final auxiliary power unit (APU) system configuration. The selection configuration is a hydrogen-oxygen APU incorporating a recuperator to utilize the exhaust energy and using the cycle hydrogen flow as a means of cooling the component heat loads. The data are given in the form of computer printouts and provide the following: (1) verification of the adequacy of the design to meet the problem statement for steady-state performance; (2) overall system performance data for the vehicle system analyst to determine propellant consumption and hydraulic fluid temperature as a function for varying mission profiles, propellant inlet conditions, etc.; and (3) detailed component performance and cycle state point data to show what is happening in the cycle as a function of the external forcing functions.

Hamilton, M. L.↗

NASA NTRS1990

Extraterrestrial halogen and sulfur contents of the stratosphere

Interplanetary dust represents a potential source of environmentally important chemical species in the earth's atmosphere. Previous studies have used computational models of atmospheric evolution of meteor debris to conclude that the steady-state stratospheric component of extraterrestrial matter is a small fraction of the total aerosol load. Observational data suggest such calculations may underestimate stratospheric residence times and, thus, concentrations. Two computational methods were employed here to obtain reasonable limits for the stratospheric contents of halogens and sulfur from extraterrestrial sources. The lower limit was based on the total stratospheric aerosol load and the relative influxes from interplanetary dust and tropospheric sources. The upper limit was obtained using a viscous settling method. These results suggest that the steady-state extraterrestrial influxes of halogens are minor compared to tropospheric sources but the sulfur input may be comparable to the present observed stratospheric content. Temporal enhancements in the meteoroid flux, such as passage through comet debris lanes or impact by large bodies, may produce significant chemical perturbations in the atmosphere.

Sutton, S. R.↗

DOE OSTI2024

Data-Efficient Dimensionality Reduction and Surrogate Modeling of High-Dimensional Stress Fields

Tensor datatypes representing field variables like stress, displacement, velocity, etc., have increasingly become a common occurrence in data-driven modeling and analysis of simulations. Numerous methods [such as convolutional neural networks (CNNs)] exist to address the meta-modeling of field data from simulations. As the complexity of the simulation increases, so does the cost of acquisition, leading to limited data scenarios. Modeling of tensor datatypes under limited data scenarios remains a hindrance for engineering applications. Here, in this article, we introduce a direct image-to-image modeling framework of convolutional autoencoders enhanced by information bottleneck loss function to tackle the tensor data types with limited data. The information bottleneck method penalizes the nuisance information in the latent space while maximizing relevant information making it robust for limited data scenarios. The entire neural network framework is further combined with robust hyperparameter optimization. We perform numerical studies to compare the predictive performance of the proposed method with a dimensionality reduction-based surrogate modeling framework on a representative linear elastic ellipsoidal void problem with uniaxial loading. The data structure focuses on the low-data regime (fewer than 100 data points) and includes the parameterized geometry of the ellipsoidal void as the input and the predicted stress field as the output. The results of the numerical studies show that the information bottleneck approach yields improved overall accuracy and more precise prediction of the extremes of the stress field. Additionally, an in-depth analysis is carried out to elucidate the information compression behavior of the proposed framework.

artificial intelligence↗

NASA NTRS1987

Spectral feature design for data compression in high dimensional multispectral data

Data transmission loads of high dimensional remote sensor systems can be greatly reduced by applying generalized Karhunen-Loeve transform as a feature design technique. Two spectral feature design approaches based upon the generalized K-L transform are developed to compress information effectively. Six sets of field data from Kansas and North Dakota on three different dates each are used to test the methods. Spatially, temporally and spatially/temporally combined data sets are formed in this paper to test the robustness property of the schemes. The probability of correct classification using Landsat MSS, Thematic Mapper bands and the proposed bands are found and compared. The comparison shows that the results are improved by the proposed methods, and they appear to be satisfactorily robust. The overall data compression ratio in this paper is about 100/16, i.e., about 6 to 1 with no loss in classification accuracy.

Chen, C.-C. Thomas↗

NASA NTRS1991

In-situ x-ray monitoring of damage accumulation in SiC/RBSN tensile specimens

The room-temperature tensile testing of silicon carbide fiber reinforced reaction-bonded silicon nitride (SiC/RBSN) composite specimens was monitored by using in-situ x ray film radiography. Radiographic evaluation before, during, and after loading provided data on the effect of preexisting volume flaws (high density impurities, and local density variations) on the fracture behavior of composites. Results from (0)1, (0)3, (0)5, and (0)8 composite specimens, showed that x ray film radiography can monitor damage accumulations during tensile loading. Matrix cracking, fiber-matrix debonding, and fiber pullout were imaged throughout the tensile loading history of the specimens. Further, in-situ film radiography was found to be a helpful and practical technique for estimating interfacial shear strength between the SiC fiber and the RBSN matrix by the matrix crack spacing method. It is concluded that pretest, in-situ, and post-test radiography can provide for a greater understanding of ceramic matrix composite mechanical behavior, a verification of related experimental procedures, and a validation and development of related analytical models.

Baaklini, George Y.↗