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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Development and Demonstration of a Prototype Molten Salt Sampling System

Molten salt reactors (MSRs) offer potential operability and safety advantages when compared to commercial light water reactors (LWRs). However, operating experience with MSRs is sparse in comparison to what exists for LWRs. Further, the chemical and isotopic composition of the fuel and/or coolant salt is dynamic and difficult to characterize continuously, posing potential safety, operability, and safeguards unknowns that need to be addressed. A molten salt sampling system (MSSS) is regarded as a necessary subsystem within first generation MSRs used to obtain samples of salt for chemical and isotopic analysis in support of the need to monitor and control salt composition during operation. The MSSS is being developed using the Safety-in-Design (SiD) methodology, which incorporates incremental integration of safety analysis into the design process. The MSSS conceptual design emerging from the application of the early stages of the SiD methodology consists of a sample collection system and its housing, a freeze port, and inert gas control and delivery systems. This article describes the prototypes developed to test the functions of these MSSS subsystems, presents the results of testing in both dry and molten salt environments (including reliability data collection performed in accordance with the principles of SiD and the development of a semiquantitative fault tree model), and summarizes the opportunities for future design and testing enhancements based on the results of prototype testing.

molten salt reactor↗
DOE OSTI2020

Non-Equilibrium Processes, Stability, Design and Control of Pulsed Plasmas for Materials Processing

The energy and angle of impact of ions, interspersed with fluxes of neutral radicals, on the surface of wafers during plasma materials processing are critical parameters for the fabrication of microelectronic devices, nanostructure materials and biocompatible materials. This sensitivity extends to nearly all applications of plasmas to materials processing and surface modification. Low temperature plasmas for plasma materials processing have traditionally used continuously excited plasmas. However, pulsed plasma processing is an enabling technology for achieving finer resolution of microelectronics fabrication and for producing unique surface properties in a wide range of applications. This research project is addressing fundamental plasma physics issues in materials processing – the control of pulsed plasmas and the means for optimizing plasma produced reactant fluxes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1993

Cost model relationships between textile manufacturing processes and design details for transport fuselage elements

Textile manufacturing processes offer potential cost and weight advantages over traditional composite materials and processes for transport fuselage elements. In the current study, design cost modeling relationships between textile processes and element design details were developed. Such relationships are expected to help future aircraft designers to make timely decisions on the effect of design details and overall configurations on textile fabrication costs. The fundamental advantage of a design cost model is to insure that the element design is cost effective for the intended process. Trade studies on the effects of processing parameters also help to optimize the manufacturing steps for a particular structural element. Two methods of analyzing design detail/process cost relationships developed for the design cost model were pursued in the current study. The first makes use of existing databases and alternative cost modeling methods (e.g. detailed estimating). The second compares design cost model predictions with data collected during the fabrication of seven foot circumferential frames for ATCAS crown test panels. The process used in this case involves 2D dry braiding and resin transfer molding of curved 'J' cross section frame members having design details characteristic of the baseline ATCAS crown design.

Metschan, Stephen L.↗
DOE OSTI2022

Two-stage membrane-based process utilizing highly CO 2 -selective membranes for cost and energy efficient carbon capture from coal flue gas: A process simulation study

Membrane technology for CO 2 capture has become an attractive strategy due to its cost and energy efficiency and low materials costs. In the past decade, membrane-based process designs for post-combustion power plant CO 2 capture have been developed, utilizing existing highly CO 2 -permeable membranes with relatively low CO 2 /N 2 selectivity (<50), and have obtained reasonably economic carbon capture. However, few membrane-based process designs were proposed for moderate to highly CO 2 -selective membranes (CO 2 /N 2 selectivity of 50–300, and >300, respectively), which have vastly emerged in recent years, such as various facilitated transport membranes (FTMs). Herein, we proposed a two-stage membrane-base process design targeting economic carbon capture from coal-fired flue gas. This process design features the utilization of highly CO 2 -selective membranes for one-stage CO 2 enrichment to 95% dry-base purity in the first stage and recycle of the remaining CO 2 by a highly CO 2 -permeable membrane in the second stage, in order to achieve economic CO 2 capture with 90% capture rate and >95% CO 2 product purity. Through an integration-iteration membrane model and the Aspen Plus process simulation, a sensitivity study of operating pressures (feed and permeate pressures) and membrane properties (CO 2 permeance and CO 2 /N 2 selectivity) was conducted. Critical CO 2 /N 2 selectivity of 300–400 was found for the highly CO 2 -selctive membranes to meet the demand for cost and energy efficient results. The lowest possible membrane area of 4.8 × 10 5 m 2 and fractional energy of 19.3% were obtained, which is comparable to or even more attractive than reported membrane-based process designs. Here, this work provides a new membrane process design option for highly CO 2 -selective membranes and gives insights on the influence of membrane performance and operation condition.

42 ENGINEERING↗
NASA NTRS1996

Aerodynamic Influence Coefficient Computations Using Euler/Navier-Stokes Equations on Parallel Computers

Modem design requirements for an aircraft push current technologies used in the design process to their limit or sometimes require more advanced technologies to meet the requirement. New design requirements always demand to improve the operational performance. Accurate prediction of aerodynamic coefficients is essential to improve the performance. For example, in the design of an advanced subsonic civil transport, since the fluid flow at transonic regime shows strong nonlinearities, high fidelity equations, such as the Euler or Navier-Stokes equations predict flow characteristics more accurately than the linear aerodynamics, which are widely used in the current design process However, high fidelity flow equations are computationally expensive and require an order of magnitude longer time to obtain aerodynamic coefficients required in the design. Parallel computing is one possibility to cut down the computational turn-around time in using high fidelity equations so that high fidelity equations would be incorporated into the design process. By doing so, high fidelity equations would be used in the routine design process. This work will demonstrate the feasibility of using high fidelity flow equations in a design process by computing aerodynamic influence coefficients of a wing-body-empennage configuration on a multiple-instruction, multiple-data parallel computer.

Byun, Chansup↗
NASA NTRS1994

Estimating Delays In ASIC's

Verification is important aspect of process of designing application-specific integrated circuit (ASIC). Design must not only be functionally accurate, but must also maintain correct timing. IFA, Intelligent Front Annotation program, assists in verifying timing of ASIC early in design process. This program speeds design-and-verification cycle by estimating delays before layouts completed. Written in C language.

Burke, Gary↗
DOE OSTI2023

How to Decarbonize Our Energy Systems: Process‐Informed Design of New Materials for Carbon Capture

Decarbonisation from a variety of industrial and power emission sectors highlights a marked need for capture technologies that can be optimized for different CO 2 sources and integrated into an equally diverse range of applications of captured CO 2 as a feedstock. Some capture technologies are already operated at an industrial scale but may not be optimal for all required applications. Advanced tailored sorbent-based technologies allow flexible operation and reduced costs as they offer higher capture capacities and significantly lower energy penalties than the state-of-the-art systems. To accelerate the discovery, development, and deployment of novel advanced materials, it is critically important that efforts between experimentalists, theoreticians, and process engineers are coordinated. The PrISMa project addresses this challenge by integrating materials design with process design and environmental considerations to allow for tailor-making carbon capture solutions optimally tuned for local sources and sinks. In this article, we highlight some of the recent results obtained with the PrISMa platform.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2002

System Level Uncertainty Assessment for Collaborative RLV Design

A collaborative design process utilizing Probabilistic Data Assessment (PDA) is showcased. Given the limitation of financial resources by both the government and industry, strategic decision makers need more than just traditional point designs, they need to be aware of the likelihood of these future designs to meet their objectives. This uncertainty, an ever-present character in the design process, can be embraced through a probabilistic design environment. A conceptual design process is presented that encapsulates the major engineering disciplines for a Third Generation Reusable Launch Vehicle (RLV). Toolsets consist of aerospace industry standard tools in disciplines such as trajectory, propulsion, mass properties, cost, operations, safety, and economics. Variations of the design process are presented that use different fidelities of tools. The disciplinary engineering models are used in a collaborative engineering framework utilizing Phoenix Integration's ModelCenter and AnalysisServer environment. These tools allow the designer to join disparate models and simulations together in a unified environment wherein each discipline can interact with any other discipline. The design process also uses probabilistic methods to generate the system level output metrics of interest for a RLV conceptual design. The specific system being examined is the Advanced Concept Rocket Engine 92 (ACRE-92) RLV. Previous experience and knowledge (in terms of input uncertainty distributions from experts and modeling and simulation codes) can be coupled with Monte Carlo processes to best predict the chances of program success.

Charania, A. C.↗
NASA NTRSDate not supplied

Synthetic Failure Mode Generation for Resilience Analysis and Failure Mechanism Discovery

Traditional risk-based design processes seek to mitigate operational hazards by manually identifying possible faults and corresponding mitigation strategies—a tedious process which critically relies on the designer’s limited knowledge. Resilience-based design, on the other hand, seeks to embody generic hazard-mitigating properties in the system to mitigate unknown hazards, often by modelling the system's response to potential hazardous events. This work adapts this approach to the traditional risk-based design process to synthetically generate hazardous modes, by representing them as a unique combination of internal component health-states which can then be injected and simulated in a model of the system failure dynamics. The design process may then reduce the risk of unknown internal hazards by iteratively mitigating the effects of these modes. The performance of this approach is evaluated in a model of an autonomous rover, where cluster analysis shows that elaborating the space of synthetic faults in the drive system using this approach uncovers a wider range of possible hazardous trajectories and failure consequences within each trajectory. However, this increase in hazard information comes at a high computational expense, highlighting the need for advanced, efficient methods to search and sample the hazard space.

Simulation↗
NASA NTRSDate not supplied

Synthetic Failure Mode Generation for Resilience Analysis and Failure Mechanism Discovery

Traditional risk-based design processes seek to mitigate operational hazards by manually identifying possible faults and corresponding mitigation strategies—a tedious process which critically relies on the designer’s limited knowledge. Resilience-based design, on the other hand, seeks to embody generic hazard-mitigating properties in the system to mitigate unknown hazards, often by modelling the system's response to potential hazardous events. This work adapts this approach to the traditional risk-based design process to synthetically generate hazardous modes, by representing them as a unique combination of internal component health-states which can then be injected and simulated in a model of the system failure dynamics. The design process may then reduce the risk of unknown internal hazards by iteratively mitigating the effects of these modes. The performance of this approach is evaluated in a model of an autonomous rover, where cluster analysis shows that elaborating the space of synthetic faults in the drive system using this approach uncovers a wider range of possible hazardous trajectories and failure consequences within each trajectory. However, this increase in hazard information comes at a high computational expense, highlighting the need for advanced, efficient methods to search and sample the hazard space.

Simulation↗
NASA NTRS2010

Control Design for a Generic Commercial Aircraft Engine

This paper describes the control algorithms and control design process for a generic commercial aircraft engine simulation of a 40,000 lb thrust class, two spool, high bypass ratio turbofan engine. The aircraft engine is a complex nonlinear system designed to operate over an extreme range of environmental conditions, at temperatures from approximately -60 to 120+ F, and at altitudes from below sea level to 40,000 ft, posing multiple control design constraints. The objective of this paper is to provide the reader an overview of the control design process, design considerations, and justifications as to why the particular architecture and limits have been chosen. The controller architecture contains a gain-scheduled Proportional Integral controller along with logic to protect the aircraft engine from exceeding any limits. Simulation results illustrate that the closed loop system meets the Federal Aviation Administration s thrust response requirements

Csank, Jeffrey↗
NASA NTRS1996

Cost Models for MMC Manufacturing Processes

The quality cost modeling (QCM) tool is intended to be a relatively simple-to-use device for obtaining a first-order assessment of the quality-cost relationship for a given process-material combination. The QCM curve is a plot of cost versus quality (an index indicating microstructural quality), which is unique for a given process-material combination. The QCM curve indicates the tradeoff between cost and performance, thus enabling one to evaluate affordability. Additionally, the effect of changes in process design, raw materials, and process conditions on the cost-quality relationship can be evaluated. Such results might indicate the most efficient means to obtain improved quality at reduced cost by process design refinements, the implementation of sensors and models for closed loop process control, or improvement in the properties of raw materials being fed into the process. QCM also allows alternative processes for producing the same or similar material to be compared in terms of their potential for producing competitively priced, high quality material. Aside from demonstrating the usefulness of the QCM concept, this is one of the main foci of the present research program, namely to compare processes for making continuous fiber reinforced, metal matrix composites (MMC's). Two processes, low pressure plasma spray deposition and tape casting are considered for QCM development. This document consists of a detailed look at the design of the QCM approach, followed by discussion of the application of QCM to each of the selected MMC manufacturing processes along with results, comparison of processes, and finally, a summary of findings and recommendations.

Elzey, Dana M.↗
DOE OSTI2024

Progressive Hedging Decomposition for Solutions of Large-Scale Process Family Design Problems

In previous work, we have introduced a mathematical model for solving a discretized version of the process family design problem. This involves two sets of decision variables. One set selects which unit module designs are included in the process platform out of a candidate set of options; the other set determines which of these unit module designs are assigned to each variant. In this work, we exploit a parallelized Progressive Hedging (PH) algorithm to solve even larger scale design problems. PH is a well-known algorithm traditionally used to solve stochastic programming problems. While our problem is not a two-stage stochastic programming problem, the structure is similar, and it can be directly mapped to the PH approach, which we employ here to solve this deterministic optimization problem. We decompose our problem by process variant. We treat the platform unit module design variables as first-stage and the assignment of unit module designs to variants as second-stage, solving the problem using mpi-sppy. We demonstrate this approach on case studies of CC, water desalination, and refrigeration.

Stinchfield, Georgia↗
DOE OSTI2024

Progressive Hedging Decomposition for Solutions of Large-Scale Process Family Design Problems

Rapid, wide-scale deployment of green process systems, such as carbon capture or water desalination systems, is essential for combatting climate change. Methods relying on traditional design or modularity fail to capture the benefits of both economies of numbers and economies of scale. We have proposed process family design, which designs a family of processes simultaneously exploiting opportunities for common elements. In previous work, we explored different optimization formulations to solve this problem. In this work, we develop a decomposition approach to tackle larger problems efficiently. We solve a water desalination case study, which is too large to solve within a reasonable timeframe with the discretization formulation. We exploit the block angular structure of the discretization problem to decompose and solve using Progressive Hedging (PH). We use the open-source Python package mpi-sppy to execute PH which allows us to leverage parallelization and a HPC cluster to further improve solution time.

Stinchfield, Georgia↗
NASA NTRS1984

Regression analysis as a design optimization tool

The optimization concepts are described in relation to an overall design process as opposed to a detailed, part-design process where the requirements are firmly stated, the optimization criteria are well established, and a design is known to be feasible. The overall design process starts with the stated requirements. Some of the design criteria are derived directly from the requirements, but others are affected by the design concept. It is these design criteria that define the performance index, or objective function, that is to be minimized within some constraints. In general, there will be multiple objectives, some mutually exclusive, with no clear statement of their relative importance. The optimization loop that is given adjusts the design variables and analyzes the resulting design, in an iterative fashion, until the objective function is minimized within the constraints. This provides a solution, but it is only the beginning. In effect, the problem definition evolves as information is derived from the results. It becomes a learning process as we determine what the physics of the system can deliver in relation to the desirable system characteristics. As with any learning process, an interactive capability is a real attriubute for investigating the many alternatives that will be suggested as learning progresses.

Perley, R.↗