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Results for “Design and modelling”

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.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

Design model for the baffle aperture region of a hollow cathode thruster

A current balance on the main discharge chamber of an electron bombardment thruster is carried out. It is shown that the discharge current is the sum of the net cathode emission current, the beam current, and the ion current to cathode potential surfaces. Measurements of ion currents outside the virtual anode surface in a SERT II divergent magnetic field thruster show that relatively few ions cross this surface. This implies that ions are directed preferentially toward the anode and cathode pole pieces. A simple theoretical model useful as an aid in the design of the baffle aperture region of a hollow cathode equipped thruster is developed. The electron diffusion process through the aperture is modeled in accordance with the Bohm diffusion theory. The model is shown to yield consistent results for a given thruster geometry over substantial changes in operating conditions. The model's design usefulness is limited by a factor of two uncertainty observed over different thruster/cathode region geometries and by the accuracy to which the plasma parameters required as inputs to the model can be specified.

Brophy, J. R.↗
DOE OSTI2022

Component-wise reduced-order model design optimization such as for lattice design optimization

Systems and methods for optimizing a lattice structure design are disclosed herein. In some embodiments, a method for optimizing a lattice structure design can include (i) modeling the lattice structure with a component-wise reduced-order model (CWROM) and (ii) optimizing the CWROM based on a selected criterion using a topology optimization algorithm for lattice design. The selected criterion can include a boundary condition and a load applied to the lattice structure. By modeling the lattice structure as a CWROM, the optimization process can be very fast while still permitting the accurate computation of physical quantities of the lattice structure.

Choi, Youngsoo↗
NASA NTRS2011

Exploring the Model Design Space for Battery Health Management

Battery Health Management (BHM) is a core enabling technology for the success and widespread adoption of the emerging electric vehicles of today. Although battery chemistries have been studied in detail in literature, an accurate run-time battery life prediction algorithm has eluded us. Current reliability-based techniques are insufficient to manage the use of such batteries when they are an active power source with frequently varying loads in uncertain environments. The amount of usable charge of a battery for a given discharge profile is not only dependent on the starting state-of-charge (SOC), but also other factors like battery health and the discharge or load profile imposed. This paper presents a Particle Filter (PF) based BHM framework with plug-and-play modules for battery models and uncertainty management. The batteries are modeled at three different levels of granularity with associated uncertainty distributions, encoding the basic electrochemical processes of a Lithium-polymer battery. The effects of different choices in the model design space are explored in the context of prediction performance in an electric unmanned aerial vehicle (UAV) application with emulated flight profiles.

Saha, Bhaskar↗
DOE OSTI2025

Steam generator model design parameter sensitivity study for small modular reactor system

Here, this study focuses on design parameter sensitivity studies pertaining to several Once-Through Steam Generator (OTSG) model cases both with and without a riser using python and advanced risk assessment and optimization tool, i.e. Risk Analysis Virtual Environment (RAVEN) developed at Idaho National Laboratory (INL), to support a Small Modular Reactor (SMR) system. The presented Steam Generator (SG) python-based model is a mathematical representation of a steam-generating unit for a Pressurized Water Reactor (PWR)-type SMR system, including fluid flow and heat transfer equations, models, and correlations. Design studies involve changing the model’s input design parameters (e.g., temperature, pressure, mass flow rate) to observe the resulting effects on the output of the system, such as the Heat Transfer Coefficient (HTC), Reynolds number, Nusselt number, and heat transfer performance. Sensitivity studies analyze the degree to which system output and/or desired parameters (e.g., HTC or heat transfer performance) are sensitive to changes in the input parameters. By using RAVEN, detailed design parametric sensitivity studies. Six input parameters—namely, the pressure, temperature, and mass flow rate for the inlet of the primary-side (hot fluid) and secondary-side (cold fluid) of the SG—were randomly perturbed via RAVEN’s Monte Carlo Sampler module, using uniform distributions (i.e., ±1%, ±5% and ±10 % relative changes) for 600 samples. The analysis results give valuable insights into SG system performance, and provide justification for further research and development such as optimized sensor placement, design verification, validation, and optimization.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1993

Test model designs for advanced refractory ceramic materials

The next generation of space vehicles will be subjected to severe aerothermal loads and will require an improved thermal protection system (TPS) and other advanced vehicle components. In order to ensure the satisfactory performance system (TPS) and other advanced vehicle materials and components, testing is to be performed in environments similar to space flight. The design and fabrication of the test models should be fairly simple but still accomplish test objectives. In the Advanced Refractory Ceramic Materials test series, the models and model holders will need to withstand the required heat fluxes of 340 to 817 W/sq cm or surface temperatures in the range of 2700 K to 3000 K. The model holders should provide one dimensional (1-D) heat transfer to the samples and the appropriate flow field without compromising the primary test objectives. The optical properties such as the effective emissivity, catalytic efficiency coefficients, thermal properties, and mass loss measurements are also taken into consideration in the design process. Therefore, it is the intent of this paper to demonstrate the design schemes for different models and model holders that would accommodate these test requirements and ensure the safe operation in a typical arc jet facility.

Tran, Huy Kim↗
NASA NTRS1993

Space Station Freedom natural environment design models

The Space Station Freedom program has established a series of natural environment models and databases for utilization in design and operations planning activities. The suite of models and databases that have either been selected from among internationally recognized standards or developed specifically for spacecraft design applications are presented. The models have been integrated with an orbit propagator and employed to compute environmental conditions for planned operations altitudes of Space Station Freedom.

Suggs, Robert M.↗
NASA NTRS2005

Development of a New Approach to Instrument Model Design Used by Team X

The Jet Propulsion Laboratory's Advanced Design Team was formed in April 1995 to improve the quality and reduce the cost of JPL proposals and advanced mission studies. Currently a consolidation attempt is underway to develop a Model Library for use by JPL's Advanced Projects Design Team by collecting existing instrument models for inclusion in the library. This will allow users to readily find models of interest. In addition to this, there is also an attempt underway to develop a new approach to instrument model design used by the Advanced Design Team (Team X). This new approach consists of splitting up the different model parts such as orbital parameters, instrument parameters and instrument outputs into separate searchable parts. The user can then decide between design trades and use the different pieces to construct a model that will fit their needs. As well, this will lead to the opportunity for the large variety of usable instrument models.

Andrew, Shanna E.↗
DOE OSTI2024

Steam Generator Model Design Parameter Sensitivity Study Using Advanced Optimization Tools

This study focuses on design parameter sensitivity studies pertaining to a steam generator (SG) model, using both Python and machine-learning tools. The SG model is a mathematical representation (including fluid flow and heat transfer equations/models/correlations) of a steam-generating unit in a pressurized water reactor (PWR)-type small modular reactor (SMR) system. Design studies involve changing the model’s input design parameters (e.g., temperature, pressure, mass flow rate) to observe the resulting effects on the output of the system (e.g., heat transfer coefficient [HTC], Nusselt number, heat transfer performance). Sensitivity studies analyze the degree to which system output and/or desired parameters (e.g., HTC or heat transfer performance) are sensitive to changes in input parameters. By using machine-learning tools such as the Risk Analysis Virtual Environment (RAVEN) developed at Idaho National Laboratory (INL), detailed design parametric sensitivity studies and model optimization were performed. Six input parameters—namely, the pressure, temperature, and mass flow rate for the inlet of the primary-side (hot fluid) and secondary-side (cold fluid) of the SG—were randomly perturbed via RAVEN’s Monte Carlo Sampler module, using uniform distributions (±1% relative changes). The analysis results give valuable insights into SG system performance and optimization, and provide justification for researching optimized sensor placement to effectively monitor and obtain experimental data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Steam Generator Model Design Parameter Sensitivity Study Using Advanced Optimization Tools

This study focuses on design parameter sensitivity studies pertaining to a steam generator (SG) model, using both Python and machine-learning tools. The SG model is a mathematical representation (including fluid flow and heat transfer equations/models/correlations) of a steam-generating unit in a pressurized water reactor (PWR)-type small modular reactor (SMR) system. Design studies involve changing the model’s input design parameters (e.g., temperature, pressure, mass flow rate) to observe the resulting effects on the output of the system (e.g., heat transfer coefficient [HTC], Nusselt number, heat transfer performance). Sensitivity studies analyze the degree to which system output and/or desired parameters (e.g., HTC or heat transfer performance) are sensitive to changes in input parameters. By using machine-learning tools such as the Risk Analysis Virtual Environment (RAVEN) developed at Idaho National Laboratory (INL), detailed design parametric sensitivity studies and model optimization were performed. Six input parameters—namely, the pressure, temperature, and mass flow rate for the inlet of the primary-side (hot fluid) and secondary-side (cold fluid) of the SG—were randomly perturbed via RAVEN’s Monte Carlo Sampler module, using uniform distributions (±1% relative changes). The analysis results give valuable insights into SG system performance and optimization, and provide justification for researching optimized sensor placement to effectively monitor and obtain experimental data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2015

The PDS4 Information Model Design Principles - How Well Did They Work?

The Planetary Data System (PDS) recently released Version 1.5 of the PDS4 Information Model, the primary component of the PDS4 Information Architecture. The Information Model is now stable and is in use by three active missions and several missions in various phases of development. The Information Model drives the PDS4 Information System using a multi-level governance structure that provides for common, discipline, and mission level management of the system’s information standards. For the development of the PDS4 Information Model several design principles were adopted. This paper will describe each design principle and then explain how well they worked, problems encountered during development and their solutions, and how well the results meet the requirements of the multi-discipline planetary science community.

Martin, Michael↗
NASA NTRS1991

Inverse problems in the design, modeling and testing of engineering systems

Formulations, classification, areas of application, and approaches to solving different inverse problems are considered for the design of structures, modeling, and experimental data processing. Problems in the practical implementation of theoretical-experimental methods based on solving inverse problems are analyzed in order to identify mathematical models of physical processes, aid in input data preparation for design parameter optimization, help in design parameter optimization itself, and to model experiments, large-scale tests, and real tests of engineering systems.

Alifanov, Oleg M.↗
NASA NTRS1988

Cross-guide coupler modeling and design

Modeling of cross-guide couplers based on the theory of equivalent electric and magnetic dipoles of an aperture is described. Additional correction factors due to nonzero wall thickness and large aperture are also included in this analysis. Comparisons of the measured and calculated results are presented for cross-guide couplers with circular or cross-shaped coupling apertures. A cross-guide coupler was designed as a component of the C-band feed to support the Phobos mission.

Chen, J.↗
NASA NTRS2011

JPL Thermal Design Modeling Philosophy and NASA-STD-7009 Standard for Models and Simulations - A Case Study

The Standard JPL thermal engineering practice prescribes worst-case methodologies for design. In this process, environmental and key uncertain thermal parameters (e.g., thermal blanket performance, interface conductance, optical properties) are stacked in a worst case fashion to yield the most hot- or cold-biased temperature. Thus, these simulations would represent the upper and lower bounds. This, effectively, represents JPL thermal design margin philosophy. Uncertainty in the margins and the absolute temperatures is usually estimated by sensitivity analyses and/or by comparing the worst-case results with "expected" results. Applicability of the analytical model for specific design purposes along with any temperature requirement violations are documented in peer and project design review material. In 2008, NASA released NASA-STD-7009, Standard for Models and Simulations. The scope of this standard covers the development and maintenance of models, the operation of simulations, the analysis of the results, training, recommended practices, the assessment of the Modeling and Simulation (M&S) credibility, and the reporting of the M&S results. The Mars Exploration Rover (MER) project thermal control system M&S activity was chosen as a case study determining whether JPL practice is in line with the standard and to identify areas of non-compliance. This paper summarizes the results and makes recommendations regarding the application of this standard to JPL thermal M&S practices.

thermal blanket performance↗
NASA NTRS1984

Error detection process - Model, design, and its impact on computer performance

An analytical model is developed for computer error detection processes and applied to estimate their influence on system performance. Faults in the hardware, not in the design, are assumed to be the potential cause of transition to erroneous states during normal operations. The classification properties and associated recovery methods of error detection are discussed. The probability of obtaining an unreliable result is evaluated, along with the resulting computational loss. Error detection during design is considered and a feasible design space is outlined. Extension of the methods to account for the effects of extant multiple faults is indicated.

Shin, K. G.↗
DOE OSTI2025

DVMDOSTEM v0.8.3: a terrestrial ecosystem model designed to represent arctic, boreal and permafrost ecosystem dynamics

The impacts of climate change on natural ecosystems are the result of complex physical and ecological processes operating and interacting at a variety of spatio-temporal scales, that can be represented in process-based ecosystem models. DVMDOSTEM is an advanced process-based terrestrial ecosystem model (TEM) designed to study ecosystem responses to climate changes and disturbances. It has a particular focus on permafrost regions (i.e. regions characterized by soils that stay partially frozen all year round for at least two consecutive years), encompassing boreal, arctic, and alpine landscapes. The model couples two previous versions of the Terrestrial Ecosystem Model (TEM) (McGuire et al., 1992): DVMTEM that includes a dynamic vegetation module (DVM) (E. S. Euskirchen et al., 2009), and DOSTEM that includes a dynamic organic soil module (DOS) (H. Genet et al., 2013; Yi et al., 2010). DVMDOSTEM simulates processes at yearly and monthly scales, with some physical processes operating at an even finer temporal resolution. Its versatility allows for site-specific to regional simulations, making it valuable for predicting shifts in permafrost, vegetation, and carbon (C) and nitrogen (N) dynamics. While DVMDOSTEM has been described in the methods sections of many manuscripts, this paper is the first stand alone description of DVMDOSTEM, independent of a particular scientific investigation.

Carman, Tobey B. [Univ. of Alaska, Fairbanks, AK (↗
NASA NTRS1980

Exploratory studies of the cruise performance of upper surface blown configurations. Experimental program: Test facilities, model design instrumentation, and lowspeed, high-lift tests

The model hardware, test facilities and instrumentation utilized in an experimental study of upper surface blown configurations at cruise is described. The high speed (subsonic) experimental work, studying the aerodynamic effects of wing nacelle geometric variations, was conducted around semispan model configurations composed of diversified, interchangeable components. Power simulation was provided by high pressure air ducted through closed forebody nacelles. Nozzle geometry was varied across size, exit aspect ratio, exit position and boattail angle. Three dimensional force and two dimensional pressure measurements were obtained at cruise Mach numbers from 0.5 to 0.8 and at nozzle pressure ratios up to about 3.0. The experimental investigation was supported by an analytical synthesis of the system using a vortex lattice representation with first order power effects. Results are also presented from a compatibility study in which a short haul transport is designed on the basis of the aerodynamic findings in the experimental study as well as acoustical data obtained in a concurrent program. High lift test data are used to substantiate the projected performance of the selected transport design.

Braden, J. A.↗