SEARCH · Engineering Papers

Results for “modeling and performance analysis”

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 1,153 records · Page 64

All sources NASA NTRS DOE OSTI

NASA NTRS2016

High Fidelity Surface Charging and Magnetic Noise Analysis of the Juno Magnetometer

During Earth flyby of NASA’s Juno spacecraft, unexpected noise was observed in magnetometer data. The noise is attributed to surface currents sourced from ionospheric plasma and directed through the magnetometer boom structure by a vxB electric field. Approximate hand calculations under-predicted the severity of the noise by an order of magnitude. In response, a high fidelity analysis was performed to assess confidence in our model and risk to magnetometer science at Jupiter. Combining NASCAP2k with commercial FEA software, and using detailed inputs from a variety of environment models and CAD tools, the observed effect at Earth was replicated with agreement to a factor of 2. Extending the model to the Jovian environment, we predict a signal-to-noise ratio that is more favourable than at Earth and acceptable to magnetometer science.

Chinn, James↗

NASA NTRSDate not supplied

S-Band Transponder Multi-Network Compatibility, Space Environment and Radiation Testing

This paper presents the development and testing of the Software Define Radio (SDR) transceiver to meet the emerging needs for SmallSat communication and navigation. Vulcan Wireless and NASA Goddard Space Flight Center (GSFC) collaborated in testing the Vulcan Wireless S-band SDR engineering model. Apart from testing, communication link analysis was performed for a Low Earth Orbit (LEO) 400 km scenario. The results of the compatibility, radiation, environmental testing, and link analysis are presented. Also, this paper reviews a set of SmallSat missions under development at NASA GSFC.

Software Define Radio, transceiver, S-band↗

NASA NTRS2024

Assessing the Number of Crew for Mars Against Trade Space Parameters

Missions to Mars will differ from all previous human spaceflight missions in that the onboard crew of astronauts will be required to operate in an Earth-independent manner given the long communication delays on Mars missions. Without a systematic, repeatable process to determine the number and composition of crew necessary to successfully accomplish these missions, NASA increases the risk in that crew sizes may be too small to meet primary mission objectives under nominal conditions and, more consequentially, the crewmembers may not have the expertise needed to successfully respond to unforeseen failures without the real-time expertise in the Mission Control Central (MCC) team on which NASA has come to rely. We present a framework for trade space analysis along with results from human-performance models developed in IMPRINT. We discuss the implications of model results on the trade space for number of crew for missions to Mars. This work was funded by the NASA Engineering and Safety Center (NESC) with support from NASA’s Human Research Program (HRP).

Donna Dempsey↗

DOE OSTI2020

Ultimate Bifacial Showdown: 75kW Field Results

This work presents one year results for a side-by-side comparison of 5 different bifacial technologies, deployed in a 75-kW single-axis tracked field at Golden, CO. Four PERC (multi and mono) and 1 Silicon Heterojunction manufacturers are represented. Reference strings of equivalent monofacial PV modules are also installed for a direct technology comparison and calculation of bifacial gain. Analysis indicates performance within expectation, with a cumulative model mean error within +/- 2% for both bifacial and monofacial models and cumulative bifacial energy gain between 6-9%. High accuracy string-level DC monitoring and module-level measurements are also presented, showing effects of snow and edge effects in the order of +/- 3% for non-uniform irradiance across the row. Data from a custom-module to measure shading loss from the torque-tube is installed, showing up to 6% irradiance non-uniformity for the month of January.

bifacial field validation↗

NASA NTRS1989

Analytical and finite element solutions of some problems using a viscoplastic model

The feasibility of using a viscoplastic model developed by Robinson to perform a nonlinear structural analysis was investigated. The paper presents analytical solutions for three classical problems: (1) a pressurized thick-walled cylinder, (2) a thin rotating disk, and (3) a pressurized thick-walled sphere. The analytical expressions derived for the stress and the strain rates for these components are general in nature as they consider both the mechanical and thermal loadings to be time-dependent. A computer program VISTAN (VIscoplastic STructural ANalyzer) was developed to obtain the stress and strain distributions. The finite element solutions for these problems are also presented. The numerical results pertaining to isothermal loading conditions are provided. The results obtained demonstrate the feasibility of using the viscoplastic model developed by Robinson to perform nonlinear structural analyses.

Arya, V. K.↗

NASA NTRS2006

Technology developments integrating a space network communications testbed

hybrid simulations↗

NASA NTRS2006

Technology Developments Integrating a Space Network Communications Testbed

As future manned and robotic space explorations missions involve more complex systems, it is essential to verify, validate, and optimize such systems through simulation and emulation in a low cost testbed environment. The goal of such a testbed is to perform detailed testing of advanced space and ground communications networks, technologies, and client applications that are essential for future space exploration missions. We describe the development of new technologies enhancing our Multi-mission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE) that enable its integration in a distributed space communications testbed. MACHETE combines orbital modeling, link analysis, and protocol and service modeling to quantify system performance based on comprehensive considerations of different aspects of space missions. It can simulate entire networks and can interface with external (testbed) systems. The key technology developments enabling the integration of MACHETE into a distributed testbed are the Monitor and Control module and the QualNet IP Network Emulator module. Specifically, the Monitor and Control module establishes a standard interface mechanism to centralize the management of each testbed component. The QualNet IP Network Emulator module allows externally generated network traffic to be passed through MACHETE to experience simulated network behaviors such as propagation delay, data loss, orbital effects and other communications characteristics, including entire network behaviors. We report a successful integration of MACHETE with a space communication testbed modeling a lunar exploration scenario. This document is the viewgraph slides of the presentation.

hybrid simulation↗

DOE OSTI2020

The Role of Subsurface Flow on Evapotranspiration: A Global Sensitivity Analysis

Abstract Water resources are impacted by water‐energy balance fluxes at the land surface, most notably evapotranspiration ( ET ), the largest component of surface energy balance. While integrated hydrologic models show promise in quantifying the nonlinear dynamics at this interface, the model results are plagued by parametric uncertainties. Given the high computational demand of running multiple parameter spaces of these models, little is known about how these uncertainties propagate into land surface processes. In this work, we perform a global sensitivity analysis by computing Sobol and AMAE indices using a surrogate model constructed with a polynomial chaos expansion to assess the impacts of the subsurface physical properties on ET . We do so by modeling a semisynthetic test case. Our results show that the effects of vertical hydraulic conductivity, porosity, and the water retention curve parameter Van Genuchten α mainly control ET . However, we note that while evaporation ( E ) shows behavior similar to the ET with high sensitivity to the parameters controlling the flow in the unsaturated zone, transpiration ( T ) is very sensitive to the saturated zone parameters and groundwater flow, especially during periods without rain. Our results also show that heterogeneities in land cover impact the flow in the saturated zone. Furthermore, our work demonstrates that reduced‐order models can be developed to make integrated models more accessible for rigorous sensitivity analyses and calibration purposes.

Maina, Fadji Zaouna↗

DOE OSTI2023

Data, scripts, and figures associated with a manuscript studying impact of climate and topography on post-fire vegetation recovery.

This data package is associated with the publication “Impact of Topography and Climate on Post-fire Vegetation Recovery Across Different Burn Severity and Land Cover Types through Machine Learning” submitted to Remote Sensing of Environment (Zahura et al. 2023). In this research, a machine learning algorithm, random forest (RF), was utilized to examine the impact of climate and topography on post-fire vegetation recovery. We used enhanced vegetation index (EVI) to examine varying burn severity and land cover types. The data package includes the input files for RF model training, outputs from model predictions and analysis, and python scripts to run the model, analyze the results to understand model performance and interpretability, and plot manuscript figures. This data package contains three folders (Data, Scripts, and Figures), a file-level metadata (FLMD) csv, and a data dictionary (dd) csv. Please see Postfire_recovery_flmd.csv for a list of all files contained in this data package and descriptions for each. The data dictionary (Postfire_recovery_dd.csv) describes the csv column headers. The “Data” folder provides all the inputs and outputs to train the RF model, evaluate performance, and interpret predictions. The “Scripts” folder contains python scripts and jupyter notebooks for model training and result analysis. The “Figures” folder includes the figures used in the manuscript in “.png” and “.jpg” format.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2000

An Overview of SAL

To become practical for assurance, automated formal methods must be made more scalable, automatic, and cost-effective. Such an increase in scope, scale, automation, and utility can be derived from an emphasis on a systematic separation of concerns during verification. SAL (Symbolic Analysis Laboratory) attempts to address these issues. It is a framework for combining different tools to calculate properties of concurrent systems. The heart of SAL is a language, developed in collaboration with Stanford, Berkeley, and Verimag for specifying concurrent systems in a compositional way. Our instantiation of the SAL framework augments PVS with tools for abstraction, invariant generation, program analysis (such as slicing), theorem proving, and model checking to separate concerns as well as calculate properties (i.e., perform, symbolic analysis) of concurrent systems. We. describe the motivation, the language, the tools, their integration in SAL/PAS, and some preliminary experience of their use.

Bensalem, Saddek↗

NASA NTRS2019

Assimilation of Aerosol Observations in the NASA GEOS Model

In the GEOS near real-time system, as well as in MERRA-2 which is the latest reanalysis produced at NASA's Global Modeling Assimilation Office (GMAO), the assimilation of aerosol observations is performed by means of a so-called analysis splitting method. The prognostic model is based on the GEOS model radiatively coupled to GOCART aerosol module and includes assimilation of bias-corrected Aerosol Optical Depth (AOD) at 550 nm from various space-based remote sensing platforms. In line with the transition of the GEOS meteorological data assimilation system to a hybrid Ensemble-Variational formulation, we are updating the aerosol component of our assimilation system to a variational ensemble type of scheme. In this talk we will examine the impact of replacing the current analysis splitting scheme with this new approach. Starting with the assimilation of satellite based single-channel retrievals; we will discuss the impact of this aerosol data assimilation technique on the 3D aerosol distributions by means of innovation statistics and verification against independent datasets such as the Aerosol Robotic Network (AERONET) and surface PM2.5. We will also present preliminary results related to the introduction of new aerosol data types in GEOS, including multi-spectral AOD retrievals.

AERONET↗

NASA NTRSDate not supplied

Electric Aircraft Propulsion Power System Impedance Modelling Methodology

This paper describes techniques to be used to model megawatt Electrified Aircraft Propulsion (MW EAP) components, specifically motor/generators and inverters, DC-DC converters, and long power leads; resulting in impedance-based models which require no information from the component manufacturers. A custom curve fitting method is described, and an example power supply model is fit using measured impedance data. A method called subscale measurement, employing measurement equipment which has much lower power capability than the MW EAP system under test, is described, simulated, and used to generate an impedance transfer function model of a load. Finally, stability analysis using a Nyquist based approach is performed on the combined supply and load system, using the generated models.

Megawatt electrified aircraft propulsion↗

DOE OSTI2026

DEMO-FTES: Development, Monitoring, and Control of Fracture Thermal Energy Storage in Crystalline Rock Formations (CRADA Final Report)

The DEMO-FTES project investigated the feasibility of Fracture Thermal Energy Storage (FTES) as a seasonal energy storage solution in crystalline rock formations. FTES leverages hydraulically induced fractures to exchange heat between circulating fluids and the surrounding rock mass, enabling long-term thermal energy retention due to the high specific heat and low thermal conductivity of rock. This approach has the potential to reduce heating and cooling energy demands and enhance building energy resilience. The project combined dimensional analysis, numerical modeling, laboratory experiments, and meso-scale field tests to evaluate FTES performance and advance its technology readiness level from 3 to 5. Scaling analysis identified key dimensionless parameters governing heat transfer and fluid flow, ensuring laboratory and field tests were representative of larger-scale systems. Numerical simulations using TOUGH and iTOUGH2 frameworks supported experiment design and interpretation, modeling fracture geometry, thermal-hydraulic behavior, and thermo-mechanical coupling. Laboratory tests at EPFL involved creating single and multiple fractures in 25 cm cubic samples of Gabbro and Granite under true triaxial stress.

25 ENERGY STORAGE↗

NASA NTRSDate not supplied

Modal Test and Model Correlation of NASA Plum Brook Station Mechanical Vibration Facility Head Expander –Lessons Learned from the Perspective of an Early-Career Engineer

In preparation for the Sierra Nevada Corporation’s (SNC) Dream Chaser spacecraft vibration test campaign at the Mechanical Vibration Facility (MVF) at NASA Plum Brook Station (PBS) in Sandusky, Ohio, a test-verified model of MVF is needed in order to be able to perform accurate pretest analysis used for determining response limits and abort levels. MVF was designed to vibration test MPCV Orion and was used to perform the system level vibration test of the European Service Module Structural Test Article (E-STA) in 2016. MVF is comprised of an 18 ft diameter annulus table that is driven with sixteen hydraulic vertical actuator assemblies and four hydraulic horizontal actuator assemblies, which allow it to perform single axis vibration testing in the vertical axis and in each of the two orthogonal horizontal axes without the need for reconfiguring the test article. A head expander for the MVF Table has been designed and built that fills in the center opening providing a continuous flat mounting surface with a maximum diameter of 16.25feet that expands the vibration testing capabilities of MVF. The MVF Table with this head expander will be used during the SNC Dream Chaser spacecraft vibration test campaign. Therefore, a critical element in a test-verified model of the MVF will be a test correlated finite element model (FEM) of the head expander. To obtain this, engineers from the Structural Dynamics Lab (SDL) at NASA Glenn Research Center (GRC) in Cleveland, Ohio performed a modal pretest analysis, conducted a modal test in July 2019, and most recently correlated the head expander finite element model to the modal test data up to 300 Hz. From the initial test preparations to the final delivery of a correlated finite element model, all efforts mentioned were led by the same early-career engineers at NASA GRC. From the viewpoint of an early-career engineer, lessons learned about modal pretest analysis, modal testing, and finite element model correlation of the MVF Table expander head will be presented and discussed. This will include the importance of understanding the limitations of using uncorrelated finite element models in the modal pretest analysis and planning, the importance of orthogonality metrics in judging adequacy and accuracy of test mode shapes, and the importance of having the FEM match the as built hardware in the model correlation effort.

Emma L Pierson↗

DOE OSTI2024

DeepPhenoMem V1.0: deep learning modelling of canopy greenness dynamics accounting for multi-variate meteorological memory effects on vegetation phenology

Abstract. Vegetation phenology plays a key role in controlling the seasonality of ecosystem processes that modulate carbon, water and energy fluxes between the biosphere and atmosphere. Accurate modelling of vegetation phenology in the interplay of Earth's surface and the atmosphere is thus crucial to understand how the coupled system will respond to and shape climatic changes. Phenology is controlled by meteorological conditions at different timescales: on the one hand, changes in key meteorological variables (temperature, water, radiation) can have immediate effects on the vegetation development; on the other hand, phenological changes can be driven by past environmental conditions, known as memory effects. However, the processes governing meteorological memory effects on phenology are not completely understood, resulting in their limited performance of vegetation phenology represented in land surface models. A deep learning model, specifically a long short-term memory network (LSTM), has the potential to capture and model the meteorological memory effects on vegetation phenology. Here, we apply the LSTM to model the vegetation phenology using meteorological drivers and high-temporal-resolution canopy greenness observations through digital repeat photography by the PhenoCam network. We compare a multiple linear regression model, a no-memory-effect LSTM model and a full-memory-effect LSTM model to predict the whole seasonal greenness trajectory and the corresponding phenological transition dates across 50 sites and 317 site years during 2009–2018, covering deciduous broadleaf forests, evergreen needleleaf forests and grasslands. Results show that the deep learning model outperforms the multiple linear regression model, and the full-memory-effect LSTM model performs better than the no-memory-effect model for all three plant function types (median R2 of 0.878, 0.957 and 0.955 for broadleaf forests, evergreen needleleaf forests and grasslands). We also find that the full-memory-effect LSTM model is capable of predicting the seasonal dynamic variations of canopy greenness and reproducing trends in shifting phenological transition dates. We also performed a sensitivity analysis of the full-memory-effect LSTM model to assess its plausibility, revealing its coherence with established knowledge of vegetation phenology sensitivity to meteorological conditions, particularly changes in temperature. Our study highlights that (1) multi-variate meteorological memory effects play a crucial role in vegetation phenology, and (2) deep learning opens up new avenues for improving the representation of vegetation phenological processes in land surface models via a hybrid modelling approach.

Geology↗

NASA NTRSDate not supplied

Characterizing Char Rate and Extent in Fiber-Reinforced Plastics Using X-ray Computed Tomography

Orbital debris is a growing problem for the space industry and the world in general, and an important component of the problem is what happens when that debris reenters the Earth’s atmosphere. With more spacecraft opting for fiber-reinforced polymer (FRP) components, we need to understand the thermal destruction process of these materials during an atmospheric reentry and how much of the material can survive to impact the ground. The NASA Orbital Debris Program Office (ODPO) has developed a new charring model for FRP components to be integrated into the latest version of the Object Reentry Survival Analysis Tool (ORSAT). To validate this new model, the ODPO performed several test series using the Inductively Coupled Plasma (ICP) Torch facility at UT Austin. To measure the extent of charred material at different conditions, some of the test samples were scanned using x-ray computed tomography (CT) by the Astromaterials Curation Lab at Johnson Space Center. 3D image analysis was then used to calculate the volume and density of the char in each test sample. This paper presents the image analysis methodology, an assessment of the accuracy of the data analysis, and a comparison with calculations using the ORSAT charring model.

Benton Greene↗

NASA NTRS2018

Active Turbine Tip Clearance Control Trade Space Analysis of an Advanced Geared Turbofan Engine

Tip clearance within the high pressure turbine of a gas turbine engine is a significant factor in engine performance and efficiency. In the pursuit of higher efficiency, aero-engine designs are migrating toward compact gas turbine (CGT) technology that seeks to increase the bypass ratio of the gas turbine engine without increasing the size of the fan, which is constrained by its underwing location. The reduced size of CGTs invoke concern over increased sensitivity of engine performance due to turbine tip clearance gap that makes an argument for advanced tip clearance mitigation and control techniques to be employed. This paper evaluates the tip clearance trade space for a conceptual geared turbofan engine with a CGT core. This is accomplished through a modeling and simulation approach that includes a sensitivity analysis of engine performance in response to high pressure turbine tip clearance as well as an evaluation of the sensitivity of tip clearance to various design parameters, including material properties and component cooling characteristics. Also included is a parametric study of actuators that provides preliminary requirements for implementation of active turbine tip clearance control actuation systems. The results produced from these studies are meant to be informative, with special emphasis on the demonstration of a systematic approach. The modeling approach appears to capture expected trends. The studies suggest that the tip clearance gap will have a greater impact on the new CGT engines and that a relatively slow, actively controlled actuation system may be sufficient as long as it has control authority to both open and close the tip clearance gap.

tip clearance control↗

NASA NTRS1989

Vibration analysis of rotor systems using reduced subsystem models

A general impedance method using reduced submodels has been developed for the linear dynamic analysis of rotor systems. Formulated in terms of either modal or physical coordinates of the subsystems, the method enables imbalance responses at specific locations of the rotor systems to be efficiently determined from a small number of 'master' degrees of freedom. To demonstrate the capability of this impedance approach, the Space Shuttle Main Engine high-pressure oxygen turbopump has been investigated to determine the bearing loads due to imbalance. Based on the same formulation, an eigenvalue analysis has been performed to study the system stability. A small 5-DOF model has been utilized to illustrate the application of the method to eigenvalue analysis. Because of its inherent characteristics of allowing formulation of reduced submodels, the impedance method can significantly increase the computational speed.

Fan, Uei-Jiun↗