Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “data fidelity”

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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Intersymbol Interference Investigations Using a 3D Time-Dependent Traveling Wave Tube Model

For the first time, a time-dependent, physics-based computational model has been used to provide a direct description of the effects of the traveling wave tube amplifier (TWTA) on modulated digital signals. The TWT model comprehensively takes into account the effects of frequency dependent AM/AM and AM/PM conversion; gain and phase ripple; drive-induced oscillations; harmonic generation; intermodulation products; and backward waves. Thus, signal integrity can be investigated in the presence of these sources of potential distortion as a function of the physical geometry and operating characteristics of the high power amplifier and the operational digital signal. This method promises superior predictive fidelity compared to methods using TWT models based on swept- amplitude and/or swept-frequency data. First, the TWT model using the three dimensional (3D) electromagnetic code MAFIA is presented. Then, this comprehensive model is used to investigate approximations made in conventional TWT black-box models used in communication system level simulations. To quantitatively demonstrate the effects these approximations have on digital signal performance predictions, including intersymbol interference (ISI), the MAFIA results are compared to the system level analysis tool, Signal Processing Workstation (SPW), using high order modulation schemes including 16 and 64-QAM.

Kory, Carol L.↗
NASA NTRS2007

Application of Risk within Net Present Value Calculations for Government Projects

In January 2004, President Bush announced a new vision for space exploration. This included retirement of the current Space Shuttle fleet by 2010 and the development of new set of launch vehicles. The President's vision did not include significant increases in the NASA budget, so these development programs need to be cost conscious. Current trade study procedures address factors such as performance, reliability, safety, manufacturing, maintainability, operations, and costs. It would be desirable, however, to have increased insight into the cost factors behind each of the proposed system architectures. This paper reports on a set of component trade studies completed on the upper stage engine for the new launch vehicles. Increased insight into architecture costs was developed by including a Net Present Value (NPV) method and applying a set of associated risks to the base parametric cost data. The use of the NPV method along with the risks was found to add fidelity to the trade study and provide additional information to support the selection of a more robust design architecture.

Grandl, Paul R.↗
NASA NTRS2011

Design, Optimization and Evaluation of Integrally Stiffened Al 7050 Panel with Curved Stiffeners

A curvilinear stiffened panel was designed, manufactured, and tested in the Combined Load Test Fixture at NASA Langley Research Center. The panel was optimized for minimum mass subjected to constraints on buckling load, yielding, and crippling or local stiffener failure using a new analysis tool named EBF3PanelOpt. The panel was designed for a combined compression-shear loading configuration that is a realistic load case for a typical aircraft wing panel. The panel was loaded beyond buckling and strains and out-of-plane displacements were measured. The experimental data were compared with the strains and out-of-plane deflections from a high fidelity nonlinear finite element analysis and linear elastic finite element analysis of the panel/test-fixture assembly. The numerical results indicated that the panel buckled at the linearly elastic buckling eigenvalue predicted for the panel/test-fixture assembly. The experimental strains prior to buckling compared well with both the linear and nonlinear finite element model.

Slemp, Wesley C. H.↗
NASA NTRS2015

CFD Modeling of the Multipurpose Hydrogen Test Bed (MHTB) Self-Pressurization and Spray Bar Mixing Experiments in Normal Gravity: Effect of Accommodation Coefficient on the Tank Pressure

In this paper, a computational model that describes pressure control phase of a typical MHTB experiment will be presented. The fidelity of the model will be assessed by comparing the models predictions with MHTB experimental data. In this paper CFD results for MHTB spray bar cooling case with 50 tank fill ratio will be presented and analyzed. Effect of accommodation coefficient for calculating droplet-ullage mass transfer will be evaluated.

cryogenic fluid storage↗
NASA NTRS2016

Non-Invasive Tension Measurement Devices for Parachute Cordage

The need for lightweight and non-intrusive tension measurements has arisen alongside the development of high-fidelity computer models of textile and fluid dynamics. In order to validate these computer models, data must be gathered in the operational environment without altering the design, construction, or performance of the test article. Current measurement device designs rely on severing a cord and breaking the load path to introduce a load cell. These load cells are very reliable, but introduce an area of high stiffness in the load path, directly affecting the structural response, adding excessive weight, and possibly altering the dynamics of the parachute during a test. To capture the required data for analysis validation without affecting the response of the system, non-invasive measurement devices have been developed and tested by NASA. These tension measurement devices offer minimal impact to the mass, form, fit, and function of the test article, while providing reliable, axial tension measurements for parachute cordage.

Litteken, Douglas A.↗
NASA NTRS2018

Space-to-Ground Interactions While Conducting Scientific Fieldwork Under Mars Mission Constraints

The Biologic Analog Science Associated with Lava Terrains (BASALT) project is a 4-year program dedicated to iteratively designing, implementing, and evaluating concepts of operations (ConOps) and supporting capabilities to enable and enhance scientific exploration for future human Mars missions. BASALT incorporates three field deployments during which real (non-simulated) biological and geochemical field science is conducted at two high-fidelity Mars analog locations under simulated Mars mission conditions, including communication de-lays and data transmission limitations. BASALT’s primary science objective is to investigate how the redox conditions of altered basaltic environments affect the development of microbial communities in these Mars-relevant settings. Field sites include the active East Rift Zone on the Big Island of Hawaii, reminiscent of early Mars when basaltic volcanism and interaction with water were widespread, and the dormant eastern Snake River Plain in Idaho, similar to present-day Mars where basaltic volcanism is rare and most evidence for volcano-driven hydrothermal activity is relict. BASALT’s primary science operations objective is to investigate exploration ConOps and capabilities that facilitate scientific return during human-robotic exploration under Mars mission constraints. Each field deployment consists of ten extravehicular activities (EVAs) on the volcanic flows in which two extravehicular and two intravehicular (IV) crew-members conduct the science while communicating across time delay and under bandwidth constraints with an Earth-based Mission Support Center (MSC) comprised of expert scientists and operators. Communication latencies of 5 and 15-minute one-way light time and low (0.512 Mb/s uplink, 1.54 Mb/s down-link) and high (5.0 Mb/s uplink, 10.0 Mb/s downlink) bandwidth conditions are being evaluated. EVA crewmembers communicate with the MSC via voice and text messaging and provide scientific instrument data, still imagery, video streams, and GPS tracking information. The MSC reviews this data across delay and provides recommendations for presampling and sampling tasks. The scientists used dynamic leaderboards (priority rank-ing lists), to track and rank candidate samples relative to one another and against the science objectives for the current EVA and the overall mission. Updates to the dynamic leaderboards are relayed regularly to the IV crewmembers to provide scientific feedback from Earth and to help minimize crew idle time (time spent waiting for Earth input during which no productive tasks are performed). EVA timelines are strategically designed to enable continuous (delayed) feedback from an Earth-based science team while simultaneously minimizing crew idle time. Such timelines are operationally advantageous, reducing transport costs by eliminating the need for crews to return to the same locations on multiple EVAs while still providing opportunities for recommendations from science experts on Earth, and scientifically advantageous by minimizing the potential for cross-contamination across sites. This paper will highlight the space-to-ground interaction results from the three BASALT field deployments, including planned versus actual EVA time-line data, ground assimilation times (the amount of time available to the MSC to provide input to the crew), and idle time. Furthermore, we describe how these results vary under the different communication latency and bandwidth conditions. Together, these data will provide a basis for guiding and prioritizing capability development for future human exploration missions.

Beaton, Kara H.↗
NASA NTRSDate not supplied

Analytical Modeling of Planetary Excavation for in Situ Resource Utilization

The space-faring capabilities of humans are dependent on the ability to interact with plan-etary surfaces safely and efficiently and utilize local re-sources. Since planetary regolith will be the primary feedstock for in situ resource utilization (ISRU) and infrastructure development activities [1,2], the site-specific geomechanical properties must be understood to optimize excavation operations [3]. Excavating planetary regolith is challenging due to its unique geomechanical properties, 1/6th G reduced gravity extreme conditions, and limited energy resources. Therefore, it is critical to develop technologies that reduce excavation force requirements and minimize tool path inefficiencies to save time and energy during planetary re-source acquisition and infrastructure development [3]. There have been several experimental investigations of methods to optimize planetary excavations [4,5], but none developed predictive capabilities. This abstract presents a simple analytical method that will be used to model laboratory and mission excavation data. Future work will build on the simple analytical method here to include high-fidelity numerical simulations of planetary excavation mechanics.

Regolith↗
NASA NTRSDate not supplied

Advancements to Wind Tunnel Testing at the Marshall Space Flight Center Aerodynamic Research Facility by the Utilization of Additively Manufactured Models

In recent years, the Aerodynamic Research Facility (ARF) at NASA’s Marshall Space Flight Center (MSFC) has heavily utilized additive manufacturing (AM) technology for the manufacturing of models for aerodynamic testing in the 14 x 14-inch Trisonic Wind Tunnel (TWT). This process change resulted in speed and cost improvements to the design and manufacture of model parts, which has provided the capability to perform parametric tests at a rapid pace with high fidelity models that are more finely detailed than previously tested. This paper outlines the model design and fabrication workflow of the ARF and the improvements made, focusing specifically on two vehicles tested. First, identical traditionally machined and AM models of a test missile configuration were tested to isolate effects of differences in manufacturing. Second, a high-fidelity model of NASA’s Space Launch System (SLS) was tested to investigate improvements in data quality possible by utilizing AM on small-scale wind tunnel tests. This paper also discusses detailed model inspections and data comparisons that were performed to prove the reliability of data across the TWT’s entire Mach range.

Ryan C Connelly↗
NASA NTRS2011

Surrogate Modeling of High-Fidelity Fracture Simulations for Real-Time Residual Strength Predictions

A surrogate model methodology is described for predicting, during flight, the residual strength of aircraft structures that sustain discrete-source damage. Starting with design of experiment, an artificial neural network is developed that takes as input discrete-source damage parameters and outputs a prediction of the structural residual strength. Target residual strength values used to train the artificial neural network are derived from 3D finite element-based fracture simulations. Two ductile fracture simulations are presented to show that crack growth and residual strength are determined more accurately in discrete-source damage cases by using an elastic-plastic fracture framework rather than a linear-elastic fracture mechanics-based method. Improving accuracy of the residual strength training data does, in turn, improve accuracy of the surrogate model. When combined, the surrogate model methodology and high fidelity fracture simulation framework provide useful tools for adaptive flight technology.

Spear, Ashley D.↗
DOE OSTI2022

ADROC: An Emulation Experimentation Platform for Advancing Resilience of Control Systems

Cyberattacks against industrial control systems have increased over the last decade, making it more critical than ever for system owners to have the tools necessary to understand the cyber resilience of their systems. However, existing tools are often qualitative, subject matter expertise-driven, or highly generic, making thorough, data-driven cyber resilience analysis challenging. The ADROC project proposed to develop a platform to enable efficient, repeatable, data-driven cyber resilience analysis for cyber-physical systems. The approach consists of two phases of modeling: computationally efficient math modeling and high-fidelity emulations. The first phase allows for scenarios of low concern to be quickly filtered out, conserving resources available for analysis. The second phase supports more detailed scenario analysis, which is more predictive of real-world systems. Data extracted from experiments is used to calculate cyber resilience metrics. ADROC then ranks scenarios based on these metrics, enabling prioritization of system resources to improve cyber resilience.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A Deep Learning Modeling Framework to Capture Mixing Patterns in Reactive-Transport Systems

Prediction and control of chemical mixing are vital for many scientific areas such as subsurface reactive transport, climate modeling, combustion, epidemiology, and pharmacology. Due to the complex nature of mixing in heterogeneous and anisotropic media, the mathematical models related to this phenomenon are not analytically tractable. Numerical simulations often provide a viable route to predict chemical mixing accurately. However, contemporary modeling approaches for mixing cannot utilize available spatial-temporal data to improve the accuracy of the future prediction and can be compute-intensive, especially when the spatial domain is large and for long-term temporal predictions. To address this knowledge gap, in this work we will present in this paper a deep learning (DL) modeling framework applied to predict the progress of chemical mixing under fast bimolecular reactions. This framework uses convolutional neural networks (CNN) for capturing spatial patterns and long short-term memory (LSTM) networks for forecasting temporal variations in mixing. By careful design of the framework—placement of non-negative constraint on the weights of the CNN and the selection of activation function, the framework ensures non-negativity of the chemical species at all spatial points and for all times. Our DL-based framework is fast, accurate, and requires minimal data for training. The time needed to obtain a forecast using the model is a fraction (≈ O(-6)) of the time needed to obtain the result using a high-fidelity simulation. To achieve an error of 10% (measured using the infinity norm) for capturing local-scale mixing features such as interfacial mixing, only 24% to 32% of the sequence data for model training is required. To achieve the same level of accuracy for capturing global-scale mixing features, the sequence data required for model training is 64% to 70% of the total spatial-temporal data. Hence, the proposed approach—a fast and accurate way to forecast long-time spatial-temporal mixing patterns in heterogeneous and anisotropic media—will be a valuable tool for modeling reactive-transport in a wide range of applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRSDate not supplied

Effect of Geometric Fidelity on the Aerodynamics of a Swept Wing with Scalloped Ice Accretion

The effect of geometric fidelity on the aerodynamics of a swept wing with a “scallop” ice shape was studied. Three geometric fidelity versions of the ice shape were studied. The High Fidelity ice shape maintained all of the highly 3D features of the scallop shape. The 3D Smooth ice shape was smoothly lofted over the High Fidelity shape in order to eliminate all of the locally 3D feature. The third ice shape was the 3D Smooth ice shape with roughness grit attached to the surface. The two 3D Smooth versions of the ice shape exhibited a flowfield characterized by a leading edge separation bubble that rolled into spanwise running vortex. The surface pressure data showed classic leading edge separation bubbles that are observed on 2D airfoils with leading edge horn ice shapes. The High Fidelity ice shape exhibited a flowfield characterized by streamwise vortices that formed downstream of the ice shape. The streamwise vortices observed downstream of the High Fidelity ice shape appeared to reduce the size of the separation suction peak observed downstream of the 3D Smooth ice shapes. This reduced the lift for the High Fidelity ice shape, when compared to the 3D Smooth ice shapes. However, these streamwise vortices may have allowed the flow to remain attached longer and slightly increased the stall angle of attack, even though the maximum lift was lower.

Aircraft icing↗
DOE OSTI2021

Money Matters: A Three-Step Process for Using Budget Data in Program Evaluation to Assess the Design and Management of a Novel Public Health Program

We applied a three-step process, abstracting and analyzing program budgets to examine how Colorectal Cancer Control Program (CRCCP) awardees are structuring their programs and to assess the fidelity of program design to the CRCCP public health model. We reviewed 23 state, one tribal organization, and six university awardee budgets. We assessed resource allocations, staffing structures, and contracted partners and their activities. Awardees allocated 83% of all funds to contracts and personnel. Program managers were the most budgeted personnel type across three measures: number of people, full-time equivalency, and personnel costs. Awardees not only contracted with health care systems and clinics (39% of all contracts) but also contracted other partner types. Contractors were mainly funded to implement evidence-based interventions (25%) and conduct evaluation (24%). Program design varied among awardees in the number of staff (0–22), number of full-time equivalencies (0–5.4), and the number of contracts (1–11) budgeted. State awardees budgeted more resources to contracts, compared with university awardees (57% vs. 31%), while universities budgeted more for total personnel costs (41% vs. 30%). We learned that awardees designed their programs with fidelity to the CRCCP model. Although implementation approaches varied, overall results suggest implementation requires a combination of internal capacities and contracted partners. Budgets provide opportunities to use already existing program data to evaluate program design, partnerships, and planned activities.

Uhd, Justin↗
DOE OSTI2024

Active learning of ternary alloy structures and energies

Abstract Machine learning models with uncertainty quantification have recently emerged as attractive tools to accelerate the navigation of catalyst design spaces in a data-efficient manner. Here, we combine active learning with a dropout graph convolutional network (dGCN) as a surrogate model to explore the complex materials space of high-entropy alloys (HEAs). We train the dGCN on the formation energies of disordered binary alloy structures in the Pd-Pt-Sn ternary alloy system and improve predictions on ternary structures by performing reduced optimization of the formation free energy, the target property that determines HEA stability, over ensembles of ternary structures constructed based on two coordinate systems: (a) a physics-informed ternary composition space, and (b) data-driven coordinates discovered by the Diffusion Maps manifold learning scheme. Both reduced optimization techniques improve predictions of the formation free energy in the ternary alloy space with a significantly reduced number of DFT calculations compared to a high-fidelity model. The physics-based scheme converges to the target property in a manner akin to a depth-first strategy, whereas the data-driven scheme appears more akin to a breadth-first approach. Both sampling schemes, coupled with our acquisition function, successfully exploit a database of DFT-calculated binary alloy structures and energies, augmented with a relatively small number of ternary alloy calculations, to identify stable ternary HEA compositions and structures. This generalized framework can be extended to incorporate more complex bulk and surface structural motifs, and the results demonstrate that significant dimensionality reduction is possible in thermodynamic sampling problems when suitable active learning schemes are employed.

Chemistry↗
DOE OSTI2024

Multi-range vehicle speed prediction using vehicle connectivity for enhanced energy efficiency of vehicles

An integrated speed prediction framework based on historical traffic data mining and real-time V2I communications for CAVs. The present framework provides multi-horizon speed predictions with different fidelity over short and long horizons. The present multi-horizon speed prediction is integrated with an economic model predictive control (MPC) strategy for the battery thermal management (BTM) of connected and automated electric vehicles (EVs) as a case study. The simulation results over real-world urban driving cycles confirm the enhanced prediction performance of the present data mining strategy over long prediction horizons. Despite the uncertainty in long-range CAV speed predictions, the vehicle level simulation results show that 14% and 19% energy savings can be accumulated sequentially through eco-driving and BTM optimization (eco-cooling), respectively, when compared with normal-driving and conventional BTM strategy.

Amini, Mohammad Reza↗
DOE OSTI2026

Seismic Elastic Double-Beam Characterization of Faults and Fractures for CO₂ Storage Site Selection

Site characterization for underground injection and storage of gigatonne-scale CO₂ requires reliable and cost-effective methods to detect and characterize faults and fractures and to assess their stress state and fault activation potential. This is critical, as wastewater injection and disposal have been shown to activate faults and induce earthquakes, and CO₂ leakage remains a key concern for long-term storage. In this project, we developed seismic methods to detect and characterize large-scale sedimentary and crystalline basement faults and associated small-scale fractures below conventional seismic imaging resolution using multicomponent (9C) surface seismic data. Machine learning was used to automatically interpret large-scale faults, providing key information for estimating the maximum magnitude of potential induced earthquakes. High-fidelity imaging was achieved by exploiting redundancy across multiple elastic wave modes, where independent images from different modes and frequencies cross-validate each other. We also used our nonlinear signal comparison (NLSC) method for ground roll removal, improving data quality in complex near-surface conditions. The methods were validated using field data acquired in central Montana. Results show that basement faults extend into the sedimentary section and that small-scale fractures are widespread above the basement. The inferred stress orientation is consistent with regional stress data, and the estimated maximum induced earthquake magnitude is small (Mw ~2.3). The developed workflow provides a practical approach for fault and fracture characterization and for assessing induced seismicity and leakage risk. It is directly applicable to CO₂ storage site selection and to other subsurface systems.

02 PETROLEUM↗