SEARCH · Engineering Papers

Results for “model types”

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 811 records · Page 45

All sources NASA NTRS DOE OSTI

NASA NTRSDate not supplied

Modeling Deformable Linear Objects for Autonomous Robotic Outfitting of Lunar Surface Systems

This paper presents structural models of deformable linear objects (DLOs). DLOs are a subclass of deformable objects that encompasses common outfitting elements such as cables and ropes. Models are validated through hardware experiments, and integration in a robotic autonomy architecture for space environments is discussed. A persistent human presence on the lunar surface is one of the next major milestones in space exploration. This requires the development of robust extraplanetary construction technologies including structures and materials modeling and robotic systems. Previous robotic construction technology development has primarily focused on structural assembly, with significantly less focus on robotically performed outfitting tasks to instantiate subsystems providing power, data, life support, etc. These tasks involve manipulation of highly flexible elements, which are difficult to model, such as cable harnesses, ropes, and hoses. Robotic manipulation of DLOs, especially cable harnesses, is an active area of research as cable harnesses are essential for providing power and data to space assets. DLO models that can be used for robot manipulator trajectory generation are necessary for autonomous operation of lunar infrastructure. There are many proposed methods for modeling DLOs, and they primarily fall into three types: 1) discrete model-based, 2) continuum model-based, and 3) Neural Network-based. These types each have pros and cons, and the tradeoff between model accuracy and computational speed informs which type should be used. An understanding of this trade-off is imperative for real-time control of autonomous systems. High computational requirements reduce the speed of the model, making real-time control difficult, while accuracy is critical to preventing collisions. Discrete models, such as a mass-spring multibody representation, require relatively few calculations, and accuracy is directly tied to the step size of the discretization. Continuum models, such as a B-spline representation or a Cosserat rod model (a mix of continuous and discrete), are more informed of the structural properties of the cable and are much more accurate than a rigid body mass-spring model, but at significant computational cost. A Neural Network approach can provide an online solution with very few computational steps, but properly generating training data can be difficult and validation for an in-space application is not trivial. This paper explores the trade-off between different modeling approaches and compares accuracy and computational speed/complexity of the three types mentioned above. Model accuracy is evaluated using a cable in a static configuration. True cable shape is obtained using a depth camera for RGB images and point-cloud segmentation. The purpose of this experiment is to evaluate the trade-offs of different approaches to the DLO modeling problem. Understanding the tradeoffs between different cable modeling techniques paves the way for developing robotic control and planning architectures necessary for real-time manipulation of DLOs for lunar infrastructure outfitting. Real-time control is required for robotic systems to be able to actively manipulate a cable in a harsh environment where model and sensor errors compound, and environmental conditions can cause significant disturbances. Cable routing must be performed in areas with high density of objects/obstacles: through truss structures, near solar panels or mirror arrays, next to bundles of electrical equipment. Understanding the best way to plan and manipulate a cable without disrupting the environment or damaging the cable is imperative to robotic outfitting operations on the lunar surface.

Amy M Quartaro↗

NASA NTRS1985

On stellar X-ray emission

Stellar X-ray astronomy represents an entirely new astronomical discipline which has emerged during the past five years. It lies at the crossroads of solar physics, stellar physics, and general astrophysics. The present review is concerned with the main physical problems which arise in connection with a study of the stellar X-ray data. A central issue is the extent to which the extrapolation from solar physics is justified and the definition (if possible) of the limits to such extrapolation. The observational properties of X-ray emission from stars are considered along with the solar analogy and the modeling of X-ray emission from late-type stars, the modeling of X-ray emission from early-type stars, the physics of stellar X-ray emission, stellar X-ray emission in the more general astrophysical context, and future prospects.

Rosner, R.↗

DOE OSTI2023

Model: Year-Long Reforecast, Extended Forecast, Coldstart type ICBC, Domain 01

The primary purpose of WFIP2 Model Development Team is to improve existing numerical weather prediction models in a manner that leads to improved wind forecasts in regions of complex terrain. Improvements in the models will come through better understanding of the physics associated with the wind flow in and around the wind plant across a range of temporal and spatial scales, which will be gained through WFIP2’s observational field study and analysis.

17 WIND ENERGY↗

DOE OSTI2023

Model: Year-Long Reforecast, Extended Forecast, Coldstart type ICBC, Domain 02

17 WIND ENERGY↗

NASA NTRS2016

Spatial and Temporal Uncertainty of Crop Yield Aggregations

The aggregation of simulated gridded crop yields to national or regional scale requires information on temporal and spatial patterns of crop-specific harvested areas. This analysis estimates the uncertainty of simulated gridded yield time series related to the aggregation with four different harvested area data sets. We compare aggregated yield time series from the Global Gridded Crop Model Inter-comparison project for four crop types from 14 models at global, national, and regional scale to determine aggregation-driven differences in mean yields and temporal patterns as measures of uncertainty. The quantity and spatial patterns of harvested areas differ for individual crops among the four datasets applied for the aggregation. Also simulated spatial yield patterns differ among the 14 models. These differences in harvested areas and simulated yield patterns lead to differences in aggregated productivity estimates, both in mean yield and in the temporal dynamics. Among the four investigated crops, wheat yield (17% relative difference) is most affected by the uncertainty introduced by the aggregation at the global scale. The correlation of temporal patterns of global aggregated yield time series can be as low as for soybean (r = 0.28).For the majority of countries, mean relative differences of nationally aggregated yields account for10% or less. The spatial and temporal difference can be substantial higher for individual countries. Of the top-10 crop producers, aggregated national multi-annual mean relative difference of yields can be up to 67% (maize, South Africa), 43% (wheat, Pakistan), 51% (rice, Japan), and 427% (soybean, Bolivia).Correlations of differently aggregated yield time series can be as low as r = 0.56 (maize, India), r = 0.05∗Corresponding (wheat, Russia), r = 0.13 (rice, Vietnam), and r = −0.01 (soybean, Uruguay). The aggregation to sub-national scale in comparison to country scale shows that spatial uncertainties can cancel out in countries with large harvested areas per crop type. We conclude that the aggregation uncertainty can be substantial for crop productivity and production estimations in the context of food security, impact assessment, and model evaluation exercises.

Aggregation uncertainty↗

NASA NTRS1979

Starspots as the cause of the intrinsic light variations in RS Canum Venaticorum type stars

A starspot model is proposed to interpret the light curves of three RS CVn type binary systems. Two of the systems are RS CVn and SZ Psc, which are detached, while the third system, RT Lac, is semidetached. Solar activity and the surface activity of the RS CVn type stars are compared. It is found that the spot model permits the detailed fitting of both the out-of-eclipse complications and the distorted shapes of the secondary eclipses in the light curves of these stars.

Eaton, J. A.↗

NASA NTRS1989

Effects of cumulus entrainment and multiple cloud types on a January global climate model simulation

An improved version of the GISS Model II cumulus parameterization designed for long-term climate integrations is used to study the effects of entrainment and multiple cloud types on the January climate simulation. Instead of prescribing convective mass as a fixed fraction of the cloud base grid-box mass, it is calculated based on the closure assumption that the cumulus convection restores the atmosphere to a neutral moist convective state at cloud base. This change alone significantly improves the distribution of precipitation, convective mass exchanges, and frequencies in the January climate. The vertical structure of the tropical atmosphere exhibits quasi-equilibrium behavior when this closure is used, even though there is no explicit constraint applied above cloud base.

Yao, Mao-Sung↗

DOE OSTI2022

Transport model comparison studies of intermediate-energy heavy-ion collisions

Transport models are the main method to obtain physics information on the nuclear equation of state and in-medium properties of particles from low to relativistic-energy heavy-ion collisions. The Transport Model Evaluation Project (TMEP) has been pursued to test the robustness of transport model predictions in reaching consistent conclusions from the same type of physical model. To this end, calculations under controlled conditions of physical input and set-up were performed with various participating codes. These included both calculations of nuclear matter in a box with periodic boundary conditions, which test separately selected ingredients of a transport code, and more realistic calculations of heavy-ion collisions. Over the years, six studies have been performed within this project. In this intermediate review, we summarize and discuss the present status of the project. We also provide condensed descriptions of the 26 participating codes, which contributed to some part of the project. These include the major codes in use today. After a compact description of the underlying transport approaches, we review the main results of the studies completed so far. They show, that in box calculations the differences between the codes can be well understood and a convergence of the results can be reached. These studies also highlight the systematic differences between the two families of transport codes, known under the names of Boltzmann–Uehling–Uhlenbeck (BUU) and Quantum Molecular Dynamics (QMD) type codes. However, when the codes were compared in full heavy-ion collisions using different physical models, as recently for pion production, they still yielded substantially different results. This calls for further comparisons of heavy-ion collisions with controlled models and of box comparisons of important ingredients, like momentum-dependent fields, which are currently underway. Furthermore, our evaluation studies often indicate improved strategies in performing transport simulations and thus can provide guidance to code developers. Results of transport simulations of heavy-ion collisions from a given code will have more significance if the code can be validated against benchmark calculations such as the ones summarized in this review.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1960

Transonic Aerodynamic Characteristics of a Model of a Proposed Six-Engine Hull-Type Seaplane Designed for Supersonic Flight

Force tests of a model of a proposed six-engine hull-type seaplane were performed in the Langley 8-foot transonic pressure tunnel. The results of these tests have indicated that the model had a subsonic zero-lift drag coefficient of 0.0240 with the highest zero-lift drag coefficient slightly greater than twice the subsonic drag level. Pitchup tendencies were noted for subsonic Mach numbers at relatively high lift coefficients. Wing leading-edge droop increased the maximum lift-drag ratio approximately 8 percent at a Mach number of 0.80 but this effect was negligible at a Mach number of 0.90 and above. The configuration exhibited stable lateral characteristics over the test Mach number range.

Wornom, Dewey E.↗

DOE OSTI2023

Context-aware learning of hierarchies of low-fidelity models for multi-fidelity uncertainty quantification

Multi-fidelity Monte Carlo methods leverage low-fidelity and surrogate models for variance reduction to make tractable uncertainty quantification even when numerically simulating the physical systems of interest with high-fidelity models is computationally expensive. This work proposes a context-aware multi-fidelity Monte Carlo method that optimally balances the costs of training low-fidelity models with the costs of Monte Carlo sampling. It generalizes the previously developed context-aware bi-fidelity Monte Carlo method to hierarchies of multiple models and to more general types of low-fidelity models. When training low-fidelity models, the proposed approach takes into account the context in which the learned low-fidelity models will be used, namely for variance reduction in Monte Carlo estimation, which allows it to find optimal trade-offs between training and sampling to minimize upper bounds of the mean-squared errors of the estimators for given computational budgets. This is in stark contrast to traditional surrogate modeling and model reduction techniques that construct low-fidelity models with the primary goal of approximating well the high-fidelity model outputs and typically ignore the context in which the learned models will be used in upstream tasks. Further, the proposed context-aware multi-fidelity Monte Carlo method applies to hierarchies of a wide range of types of low-fidelity models such as sparse-grid and deep-network models. Numerical experiments with the gyrokinetic simulation code Gene show speedups of up to two orders of magnitude compared to standard estimators when quantifying uncertainties in small-scale fluctuations in confined plasma in fusion reactors. This corresponds to a runtime reduction from 72 days to four hours on one node of the Lonestar6 supercomputer at the Texas Advanced Computing Center.

42 ENGINEERING↗

DOE OSTI2025

Fracton models from product codes

We explore a deep connection between fracton order and product codes. In particular, we propose and analyze conditions on classical seed codes which lead to fracton order in the resulting quantum product codes. Depending on the properties of the input codes, product codes can realize either Type-I or Type-II fracton models, in both nonlocal and local constructions. For the nonlocal case, we show that a recently proposed model of lineons on nonlocal graphs can be obtained as a hypergraph product code. Interestingly, constrained mobility in this model arises only from energy barriers associated with the graph. For the local case, we introduce a novel type of classical LDPC code defined on a planar aperiodic tiling. By considering the specific example of the pinwheel tiling, we demonstrate the systematic construction of local Type-I and Type-II fracton models as product codes. Our work establishes product codes as a natural setting for exploring fracton order.

Fractons↗

DOE OSTI2024

Availability of Critical Benchmark Experiments for the Pebble Tanker Transportation Model for Nuclear Criticality Safety Validation of TRISO Pebbles

This study addresses the need for comprehensive investigations into TRi-structural ISOtropic (TRISO) fuel pebble transportation validation. In this work, an exploratory model, the pebble tanker(PT), was developed with the aim of facilitating the validation of nuclear criticality safety calculations in the context of industrial-scale transportation of TRISO fuel. The PT model was designed to investigate the availability and applicability of critical benchmark experiments crucial for assessing the transportation of these pebbles. This work incorporated sensitivity/uncertainty (S/U) similarity studies to quantify the applicability of critical benchmark experiments and to address nuclear data uncertainties in the context of TRISO transportation. Two container models were investigated: one for the Hermes-type pebble and one for the Pebble Bed Modular Reactor (PBMR)–type pebble. The models were simplified, considering fuel, containment, and either water or air, to enable a focus on the underlying physics of applications involving TRISO fuel pebbles using the PT model. A crucial aspect under consideration was the capacity of the transport package to hold pebbles while ensuring subcriticality in the flooded state. An approach in the criticality validation process involves assessing the similarity between systems through an integral index parameter evaluation. This involves calculating a correlation coefficient (referred to as c k ) based on shared nuclear data–induced uncertainty between a benchmark experiment and the application of the PT model. To facilitate this analysis, the SCALE tools, particularly the CSAS6-Shift, TSUNAMI-3D-Shift, and TSUNAMI-IP sequences, were employed for comprehensive studies in neutronics and S/U analysis. Our findings showed that there are sufficient critical experimental benchmarks to perform this validation of the PT model in the most reactive state, i.e. when the tanker is flooded. This paper provides valuable insights into validating a transport package for Generation IV TRISO fuel pebbles.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

Pebble Tanker Model for Nuclear Criticality Safety Needs

This report documents a study performed to investigate the requirements for criticality safety benchmark experiments for high-assay, low-enriched uranium (HALEU) fuel in transportation applications. In this work, an exploratory application model, the “Pebble Tanker,” was developed to represent TRISO fuel in a transportation scenario for an analysis of the validation basis in industrial quantities. An aspect of the criticality validation process involves assessing the “similarity” between application and experimental benchmark systems through an integral index parameter evaluation. Here, this includes propagating nuclear data uncertainties and calculating a correlation coefficient (hereinafter referred to as “c k ”) to evaluate the similarity of benchmark experiments compared with the application Pebble Tanker model. Finding sufficient critical benchmark experiments allows for the evaluation of bias and bias uncertainty, thus determining the upper subcritical limit (USL) of the transportation package. A target k eff of ~0.94 was used in this work to establish appropriate modeling conditions, reflecting a reasonable estimate for a USL. Two container models were investigated: one with the Hermes-type pebble and one with the Pebble Bed Modular Reactor (PBMR)–type pebble. The models were simplified, considering only fuel, containment structure, and either water or air. This allows a focus on the underlying physics of applications involving TRISO fuel pebbles using the Pebble Tanker model. A crucial consideration is the transport package's ability to safely hold pebbles while flooded, maintaining subcritical conditions. Tools available in the SCALE 6.3.1 suite—the CSAS6-Shift, TSUNAMI-3D-Shift, and TSUNAMI-IP sequences—were employed for neutronics and sensitivity and uncertainty (S/U) analysis of the Pebble Tanker. Findings demonstrated sufficient available critical experiment benchmarks to perform a validation of the Pebble Tanker in the most reactive state, i.e., when the Tanker is flooded.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS1988

Estimating water flow through a hillslope using the massively parallel processor

A new two-dimensional model of water flow in a hillslope has been implemented on the Massively Parallel Processor at the Goddard Space Flight Center. Flow in the soil both in the saturated and unsaturated zones, evaporation and overland flow are all modelled, and the rainfall rates are allowed to vary spatially. Previous models of this type had always been very limited computationally. This model takes less than a minute to model all the components of the hillslope water flow for a day. The model can now be used in sensitivity studies to specify which measurements should be taken and how accurate they should be to describe such flows for environmental studies.

Devaney, Judy E.↗

NASA NTRS1990

Nonlinear damping model for flexible structures

The study of nonlinear damping problem of flexible structures is addressed. Both passive and active damping, both finite dimensional and infinite dimensional models are studied. In the first part, the spectral density and the correlation function of a single DOF nonlinear damping model is investigated. A formula for the spectral density is established with O(Gamma(sub 2)) accuracy based upon Fokker-Planck technique and perturbation. The spectral density depends upon certain first order statistics which could be obtained if the stationary density is known. A method is proposed to find the approximate stationary density explicitly. In the second part, the spectral density of a multi-DOF nonlinear damping model is investigated. In the third part, energy type nonlinear damping model in an infinite dimensional setting is studied.

Zang, Weijian↗

NASA NTRS1999

Tropical Convection and Climate Processes in a Cumulus Ensemble Model

Local convective-radiative equilibrium states of the tropical atmosphere are determined by the following external forcing: 1) Insolation, 2) Surface heat and moisture exchanges (primarily radiation and evaporation), 3) Heating and moistening induced by large-scale circulation. Understanding the equilibrium states of the tropical atmosphere in different external forcing conditions is of vital importance for studying cumulus parameterization, climate feedbacks, and climate changes. We extend our previous study using the Goddard Cumulus Ensemble (GCE) Model which resolves convective-radiative processes more explicitly than global climate models do. Several experiments are carried out under fixed insolation and sea surface temperature. The prescribed SST consists of a uniform warm pool (29C) surrounded by uniform cold SST (26C). The model produces "Walker"-type circulation with the ascending branch of the model atmosphere more humid than the descending part, but the vertically integrated temperature does not show a horizontal gradient. The results are compared with satellite measured moisture by SSM/I (Special Sensor Microwave/Imager) and temperature by MSU in the ascending and descending tropical atmosphere. The vertically integrated temperature and humidity in the two model regimes are comparable to the observed values in the tropics.

Sui, Chung-Hsiung↗

NASA NTRS2013

Modeling Errors in Daily Precipitation Measurements: Additive or Multiplicative?

The definition and quantification of uncertainty depend on the error model used. For uncertainties in precipitation measurements, two types of error models have been widely adopted: the additive error model and the multiplicative error model. This leads to incompatible specifications of uncertainties and impedes intercomparison and application.In this letter, we assess the suitability of both models for satellite-based daily precipitation measurements in an effort to clarify the uncertainty representation. Three criteria were employed to evaluate the applicability of either model: (1) better separation of the systematic and random errors; (2) applicability to the large range of variability in daily precipitation; and (3) better predictive skills. It is found that the multiplicative error model is a much better choice under all three criteria. It extracted the systematic errors more cleanly, was more consistent with the large variability of precipitation measurements, and produced superior predictions of the error characteristics. The additive error model had several weaknesses, such as non constant variance resulting from systematic errors leaking into random errors, and the lack of prediction capability. Therefore, the multiplicative error model is a better choice.

Modeling↗

NASA NTRS2017

Point-Mass Aircraft Trajectory Prediction Using a Hierarchical, Highly-Adaptable Software Design

A highly adaptable and extensible method for predicting four-dimensional trajectories of civil aircraft has been developed. This method, Behavior-Based Trajectory Prediction, is based on taxonomic concepts developed for the description and comparison of trajectory prediction software. A hierarchical approach to the "behavioral" layer of a point-mass model of aircraft flight, a clear separation between the "behavioral" and "mathematical" layers of the model, and an abstraction of the methods of integrating differential equations in the "mathematical" layer have been demonstrated to support aircraft models of different types (in particular, turbojet vs. turboprop aircraft) using performance models at different levels of detail and in different formats, and promise to be easily extensible to other aircraft types and sources of data. The resulting trajectories predict location, altitude, lateral and vertical speeds, and fuel consumption along the flight path of the subject aircraft accurately and quickly, accounting for local conditions of wind and outside air temperature. The Behavior-Based Trajectory Prediction concept was implemented in NASA's Traffic Aware Planner (TAP) flight-optimizing cockpit software application.

Karr, David A.↗