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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 415 records · Page 23

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NASA NTRS2014

Bringing Back the Social Affordances of the Paper Memo to Aerospace Systems Engineering Work

Model-based systems engineering (MBSE) is a relatively new field that brings together the interdisciplinary study of technological components of a project (systems engineering) with a model-based ontology to express the hierarchical and behavioral relationships between the components (computational modeling). Despite the compelling promises of the benefits of MBSE, such as improved communication and productivity due to an underlying language and data model, we observed hesitation to its adoption at the NASA Jet Propulsion Laboratory. To investigate, we conducted a six-month ethnographic field investigation and needs validation with 19 systems engineers. This paper contributes our observations of a generational shift in one of JPL's core technologies. We report on a cultural misunderstanding between communities of practice that bolsters the existing technology drag. Given the high cost of failure, we springboard our observations into a design hypothesis - an intervention that blends the social affordances of the narrative-based work flow with the rich technological advantages of explicit data references and relationships of the model-based approach. We provide a design rationale, and the results of our evaluation.

design↗

DOE OSTI2023

Heat Exchanger Intensification Through Powder Processing and Enhanced Design (HIPPED)

High intensity, supercritical CO 2 heat exchangers capable of operating at temperatures between 800 and 1100 ˚C and pressures greater than 80 bar are considered a critical component for high efficiency power generation and a range of next-generation industrial processes. A novel heat exchanger concept was proposed in this project. The proposed concept involved a plate-type architecture with three-dimensional fins, called twisted s-shaped fins, that capitalize on additive manufacturing. Four manufacturing processes were studied to realize the complex envisioned design: press and sinter of metallic powders, directed energy deposition, laser powder bed fusion, and a novel powder bed process involving a photoreactive polymer called SEAM (scalable expeditious additive manufacturing), that later was developed at MSU. The team was able to manufacture subscale heat exchangers using laser powder bed fusion (LPBF) and SEAM. The team settled on using SEAM as a final manufacturing approach due to its very low cost. The SEAM-manufactured heat exchanger, however, when tested under pressure, exhibited leaks and the process still requires further development beyond the timeline of the project. To support the heat exchanger design and testing, the team developed a new high temperature flow loop allowing testing under high temperature and pressure. Computational modeling of the heat exchanger was also performed for the twisted s-shaped fins and the computations were validated with experimental data. The new twisted fins resulted in enhanced heat transfer and reduced pressure drop. To further minimize pressure drop in the plate heat exchanger, the team also developed a simplified model for flow maldistribution in the manifolds, providing a new tool for designers that eliminates the need for complex CFD calculations. A technoeconomic analysis was also developed to contrast SEAM with LPBF, this tool indicated that SEAM is several times less costly and offer significant promises as a rapid low cost additive manufacturing process for metallic systems.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2022

Characterization and Accelerated Life Testing of a New Solid Oxide Electrolysis Cell

The project aims to develop mechanistic degradation models that realistically predict long-term Solid Oxide Electrolysis Cell (SOEC) durability, using input data from accelerated electrochemical life testing combined with quantitative microstructural and microchemical evaluation. A promising SOEC type will be further developed. The understanding achieved by combining experimental results and theory will be used to guide improvements in long-term SOEC durability, and validate that this technology can reach DOE H 2 production cost and durability targets. Planned outcomes include: (1) new experimental accelerated testing data on SOEC degradation at the oxygen electrode, fuel electrode, and electrolyte; (2) predictive theory of degradation developed based on the accelerated test data; (3) new electrode materials and processing methods that minimize degradation rate; (4) determination of the impact of SOEC electrolyte thickness and electrode composition/microstructure on performance and degradation; (5) determination of the operating conditions where degradation is minimized; and (6) validation of degradation models for extrapolating accelerated test data to predict long-term durability.

08 HYDROGEN↗

DOE OSTI2020

A Review of Computational Models for the Flow of Milled Biomass Part I: Discrete-Particle Models

Biomass is a renewable and sustainable energy resource. Current design of biomass handling and feeding equipment leverage both experiments and numerical modeling. This paper reviews the state-of-the-art discrete element methods (DEM) for the flow of milled biomass (Part I), accompanied by a comprehensive review on continuum-based computational models (Part II). The present review on DEM is primarily focused on the features and suitability of various particle shape models for different types of milled biomass because particle shape is the predominant attribute controlling the flow behavior of complex-shaped granular material. The general strengths and weaknesses in the applicability of those models for the milled biomass modeling are summarized. In particular, comments are provided to balance the numerical model capabilities and the computational cost for the development of DEM models. To our best knowledge, this is the first-of-its-kind review on DEM specifically for biomass. Our study indicates that the current DEM models require further development, calibration, and validation based on a deep understanding of biomass particle contact mechanics and experimental data support before they can be reliably used for predictive simulations in handling and feeding systems.

42 ENGINEERING↗

DOE OSTI2023

A Novel Partitioned Approach for Reduced Order Model—Finite Element Model (ROM-FEM) and ROM-ROM Coupling

Partitioned methods allow one to build a simulation capability for coupled problems by reusing existing single-component codes. In so doing, partitioned methods can shorten code development and validation times for multiphysics and multiscale applications. In this work, we consider a scenario in which one or more of the “codes” being coupled are projection-based reduced order models (ROMs), introduced to lower the computational cost associated with a particular component. We simulate this scenario by considering a model interface problem that is discretized independently on two non-overlapping subdomains. Here we then formulate a partitioned scheme for this problem that allows the coupling between a ROM “code” for one of the subdomains with a finite element model (FEM) or ROM “code” for the other subdomain. The ROM “codes” are constructed by performing proper orthogonal decomposition (POD) on a snapshot ensemble to obtain a low-dimensional reduced order basis, followed by a Galerkin projection onto this basis. The ROM and/or FEM “codes” on each subdomain are then coupled using a Lagrange multiplier representing the interface flux. To partition the resulting monolithic problem, we first eliminate the flux through a dual Schur complement. Application of an explicit time integration scheme to the transformed monolithic problem decouples the subdomain equations, allowing their independent solution for the next time step. We show numerical results that demonstrate the proposed method’s efficacy in achieving both ROM-FEM and ROM-ROM coupling.

de Castro, Amy↗

DOE OSTI2020

Southeast Regional CO 2 Utilization and Storage Acceleration Partnership (SECARB-USA): Preliminary Regional Assessment of Potential Storage Complexes, Including Capacities and Costs, Based on Application of NRAP and SCO2T (Deliverable 3.3) Storage Complexes

The Recipient will assist with the field validation of one or more risk assessment toolsets through: 1) collaborative research; 2) sharing of relevant datasets, information, and technical insights from field efforts; and 3) other modeling and simulation toolsets as they are developed. Collaborative research could include, but is not limited to: 1) demonstrating use of field data for improved leakage pathway characterization, uncertainty reduction, and risk management and uncertainty workflows; 2) testing and validation of a specific National Risk Assessment Partnership (NRAP) tool using site specific data; and 3) improved modeling or reduced-order modeling of geophysical monitoring.

42 ENGINEERING↗

NASA NTRS1987

Structural tailoring of advanced turboprops

A computer program has been developed for the performance of numerical optimizations of highly swept propfan blades by minimizing an objective function that is defined either as direct operating cost or the aeroelastic difference between a blade and its scaled model. Three component analysis categories are employed: an optimization algorithm, approximate analysis procedures for objective function and constraint evaluation, and refined analysis procedures for optimum design validation. The analyses conducted by the program encompass aerodynamic efficiency evaluation, finite element stress and vibration analysis, acoustics, flutter, and forced response life prediction.

Brown, K. W.↗

NASA NTRS2006

Mission Scenario Development Workbench

The Mission Scenario Development Workbench (MSDW) is a multidisciplinary performance analysis software tool for planning and optimizing space missions. It provides a number of new capabilities that are particularly useful for planning the surface activities on other planets. MSDW enables rapid planning of a space mission and supports flight system and scientific-instrumentation trades. It also provides an estimate of the ability of flight, ground, and science systems to meet high-level mission goals and provides means of evaluating expected mission performance at an early stage of planning in the project life cycle. In MSDW, activity plans and equipment-list spreadsheets are integrated with validated parameterized simulation models of spacecraft systems. In contrast to traditional approaches involving worst-case estimates with large margins, the approach embodied in MSDW affords more flexibility and more credible results early in the lifecycle through the use of validated, variable- fidelity models of spacecraft systems. MSDW is expected to help maximize the scientific return on investment for space missions by understanding early the performance required to have a successful mission while reducing the risk of costly design changes made at late stages in the project life cycle.

Kordon, Mark↗

DOE OSTI2024

2022 Component Innovation Awardee: Pecos Wind Power

Distributed wind energy systems supply electricity for nearby homes and businesses, often in remote and rural regions. Systems capable of capturing energy in areas with low wind speeds make it possible to deploy these clean energy systems in many geographic locations. Pecos Wind Power's 85-kilowatt (kW) horizontal-axis PW85 wind turbine shows potential to reduce the levelized cost of energy by approximately 55% when compared to typical small wind systems while achieving utility-scale capacity factors of more than 40% in areas with lower wind speeds. To maximize cost competitiveness, the Pecos Wind Power turbine needs a blade optimized for low wind speeds. Through its 2022 Competitiveness Improvement Project (CIP) award, Pecos Wind Power and partner Wetzel Wind Energy Services will model, optimize, fabricate, and validate a 14.5-meter wind turbine blade made specifically for these applications. Three prior CIP awards supported Pecos Wind Power's initial development of the PW85 turbine.

CIP↗

DOE OSTI2026

Second-order wave excitation forces in WEC-Sim/MOST: Implementation, experimental validation, and code-to-code comparison

Accurate prediction of second-order hydrodynamic loads is essential for floating bodies, including floating offshore wind turbines, wave energy converters, and hybrid wind–wave platforms. These nonlinear effects, arising from both sum- and difference-frequency forcing, are critical for capturing key response characteristics but remain challenging to model efficiently. In this work, we extend the open-source Wave Energy Converter Simulator / MATLAB for Offshore Simulation Tool by implementing second-order wave excitation forces, supporting both the full Quadratic Transfer Function formulation and the Newman approximation. The full Quadratic Transfer Function method is used for all code-to-code comparisons and experimental validation, while the Newman approximation is provided as a computationally lighter alternative. To benchmark the new capability, we perform a code-to-code comparison with OpenFAST and OrcaFlex. We then validate the enhanced model using wave-tank measurements of a 1:96 scale DeepCwind semi-submersible, showing that second-order effects are required to reproduce platform motions. The implementation employs a computationally efficient pre-computation strategy for second-order wave excitation forces, reducing simulation cost while maintaining engineering accuracy. Overall, this work advances the tool as an open-source and versatile tool for modelling floating offshore renewable-energy systems requiring second-order hydrodynamic fidelity.

17 WIND ENERGY↗

DOE OSTI2025

Toward a sustainable circular economy of multilayer plastic films: Life cycle and techno-economic assessment with a focus on end-of-life treatment and multiple recovery cycles

This study presents a life cycle assessment (LCA) and techno-economic analysis (TEA) of end-of-life technologies for treating polyethylene–polyamide barrier film waste, focusing on quality degradation across recovery cycles. Novel treatment methods are experimentally validated, while others are drawn from literature and industry consultations. A displacement approach, assuming no quality loss, is first applied. Results show that solvent-based recycling via the solvent-targeted recovery and precipitation (STRAP) process outperforms alternatives across environmental indicators, reducing global warming potential (GWP) by 40% compared to landfilling. Incineration performs worst in most categories, particularly eutrophication (80% higher than landfilling), due to nitrogen emissions. Experimentally validated downcycling (pelletizing) proves more economically viable. The assumption of infinite recoverability is overly optimistic. To address this, we propose a mathematical framework accounting for a finite number of recovery cycles. This refined model shows reduced GWP and cost savings for solvent recovery, making its benefits less pronounced than initially estimated. Sensitivity and uncertainty analyses reveal strong dependence on recovered material quality and solvent recovery efficiency, underscoring the need for optimized process design. Finally, hotspot analysis identifies greenhouse gas emissions from the polyamide supply chain as the dominant GWP contributor. In conclusion, the results underscore potential trade-offs across pathways and show that solvent-based recovery’s sustainability depends heavily on process conditions.

36 MATERIALS SCIENCE↗

DOE OSTI2020

HPC4Mfg with Carbon Inc.

Continuous Liquid Interface Production (CLIP) is poised to bring additive manufacturing to multiple American manufacturing sectors owing to its unique combination of rapid print speeds and material options that resemble injection molding thermoplastics. In spite of these benefits, CLIP is still a maturing process. To improve our understanding and control of the process, this project developed a multi-physics computational model that encompasses the coupled chemical-physical processes of photopolymerization and fluid flow to predict part outcomes. A physically predictive model can enable rapid optimization of CLIP and reduce the current cycle time and waste associated with optimization by four-fold. Ultimately, this effort will help open the U.S. $400B plastic manufacturing industry to the key benefits of additive manufacturing, namely mass customization, unlimited design space, and a cost- and energy-effective path to mainstream manufacturing. In the course of the project we produced a model which coupled fluid-flow, species transport, and photochemistry to model the Carbon CLIP process. As the development proceeded, we validated the code against theory and experiments. The resulting code was transferred to Carbon, and we expect it to be a useful part of their modeling capability. Future work includes improvements to the fluid solver’s robustness and performance, along with the addition of additional physics models.

42 ENGINEERING↗

DOE OSTI2021

Development of a Multi-physics Model to Optimize Continuous Liquid Interface Production (CLIP) for Additive Manufacturing (Carbon3D HPC4Mfg Final Report)

36 MATERIALS SCIENCE↗

NASA NTRS1985

Fixed gain and adaptive techniques for rotorcraft vibration control

The results of an analysis effort performed to demonstrate the feasibility of employing approximate dynamical models and frequency shaped cost functional control law desgin techniques for helicopter vibration suppression are presented. Both fixed gain and adaptive control designs based on linear second order dynamical models were implemented in a detailed Rotor Systems Research Aircraft (RSRA) simulation to validate these active vibration suppression control laws. Approximate models of fuselage flexibility were included in the RSRA simulation in order to more accurately characterize the structural dynamics. The results for both the fixed gain and adaptive approaches are promising and provide a foundation for pursuing further validation in more extensive simulation studies and in wind tunnel and/or flight tests.

Roy, R. H.↗

NASA NTRS1992

Methodology for sensitivity analysis, approximate analysis, and design optimization in CFD for multidisciplinary applications

Fundamental equations of aerodynamic sensitivity analysis and approximate analysis for the two dimensional thin layer Navier-Stokes equations are reviewed, and special boundary condition considerations necessary to apply these equations to isolated lifting airfoils on 'C' and 'O' meshes are discussed in detail. An efficient strategy which is based on the finite element method and an elastic membrane representation of the computational domain is successfully tested, which circumvents the costly 'brute force' method of obtaining grid sensitivity derivatives, and is also useful in mesh regeneration. The issue of turbulence modeling is addressed in a preliminary study. Aerodynamic shape sensitivity derivatives are efficiently calculated, and their accuracy is validated on two viscous test problems, including: (1) internal flow through a double throat nozzle, and (2) external flow over a NACA 4-digit airfoil. An automated aerodynamic design optimization strategy is outlined which includes the use of a design optimization program, an aerodynamic flow analysis code, an aerodynamic sensitivity and approximate analysis code, and a mesh regeneration and grid sensitivity analysis code. Application of the optimization methodology to the two test problems in each case resulted in a new design having a significantly improved performance in the aerodynamic response of interest.

Taylor, Arthur C., III↗

NASA NTRS2003

Input-Output Modeling and Control of the Departure Process of Congested Airports

A simple queueing model of busy airport departure operations is proposed. This model is calibrated and validated using available runway configuration and traffic data. The model is then used to evaluate preliminary control schemes aimed at alleviating departure traffic congestion on the airport surface. The potential impact of these control strategies on direct operating costs, environmental costs and overall delay is quantified and discussed.

Pujet, Nicolas↗

NASA NTRS2014

Background Error Covariance Estimation Using Information from a Single Model Trajectory with Application to Ocean Data Assimilation

An attractive property of ensemble data assimilation methods is that they provide flow dependent background error covariance estimates which can be used to update fields of observed variables as well as fields of unobserved model variables. Two methods to estimate background error covariances are introduced which share the above property with ensemble data assimilation methods but do not involve the integration of multiple model trajectories. Instead, all the necessary covariance information is obtained from a single model integration. The Space Adaptive Forecast error Estimation (SAFE) algorithm estimates error covariances from the spatial distribution of model variables within a single state vector. The Flow Adaptive error Statistics from a Time series (FAST) method constructs an ensemble sampled from a moving window along a model trajectory.SAFE and FAST are applied to the assimilation of Argo temperature profiles into version 4.1 of the Modular Ocean Model (MOM4.1) coupled to the GEOS-5 atmospheric model and to the CICE sea ice model. The results are validated against unassimilated Argo salinity data. They show that SAFE and FAST are competitive with the ensemble optimal interpolation (EnOI) used by the Global Modeling and Assimilation Office (GMAO) to produce its ocean analysis. Because of their reduced cost, SAFE and FAST hold promise for high-resolution data assimilation applications.

Error Covariance↗

NASA NTRS2014

Background Error Covariance Estimation using Information from a Single Model Trajectory with Application to Ocean Data Assimilation into the GEOS-5 Coupled Model

An attractive property of ensemble data assimilation methods is that they provide flow dependent background error covariance estimates which can be used to update fields of observed variables as well as fields of unobserved model variables. Two methods to estimate background error covariances are introduced which share the above property with ensemble data assimilation methods but do not involve the integration of multiple model trajectories. Instead, all the necessary covariance information is obtained from a single model integration. The Space Adaptive Forecast error Estimation (SAFE) algorithm estimates error covariances from the spatial distribution of model variables within a single state vector. The Flow Adaptive error Statistics from a Time series (FAST) method constructs an ensemble sampled from a moving window along a model trajectory. SAFE and FAST are applied to the assimilation of Argo temperature profiles into version 4.1 of the Modular Ocean Model (MOM4.1) coupled to the GEOS-5 atmospheric model and to the CICE sea ice model. The results are validated against unassimilated Argo salinity data. They show that SAFE and FAST are competitive with the ensemble optimal interpolation (EnOI) used by the Global Modeling and Assimilation Office (GMAO) to produce its ocean analysis. Because of their reduced cost, SAFE and FAST hold promise for high-resolution data assimilation applications.

Data Assimilation↗