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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Integrated aerodynamic-structural design of a forward-swept transport wing

The introduction of composite materials is having a profound effect on aircraft design. Since these materials permit the designer to tailor material properties to improve structural, aerodynamic and acoustic performance, they require an integrated multidisciplinary design process. Futhermore, because of the complexity of the design process, numerical optimization methods are required. The utilization of integrated multidisciplinary design procedures for improving aircraft design is not currently feasible because of software coordination problems and the enormous computational burden. Even with the expected rapid growth of supercomputers and parallel architectures, these tasks will not be practical without the development of efficient methods for cross-disciplinary sensitivities and efficient optimization procedures. The present research is part of an on-going effort which is focused on the processes of simultaneous aerodynamic and structural wing design as a prototype for design integration. A sequence of integrated wing design procedures has been developed in order to investigate various aspects of the design process.

Haftka, Raphael T.↗
NASA NTRS1993

Architectural design of the science complex at Elizabeth City State University

This paper gives an overall view of the architectural design process and elements in taking an idea from conception to execution. The project presented is an example for this process. Once the need for a new structure is established, an architect studies the requirements, opinions and limits in creating a structure that people will exist in, move through, and use. Elements in designing a building include factors such as volume and surface, light and form changes of scale and view, movement and stasis. Some of the other factors are functions and physical conditions of construction. Based on experience, intuition, and boundaries, an architect will utilize all elements in creating a new building. In general, the design process begins with studying the spatial needs which develop into an architectural program. A comprehensive and accurate architectural program is essential for having a successful building. The most attractive building which does not meet the functional needs of its users has failed at the primary reason for its existence. To have a good program an architect must have a full understanding of the daily functions that will take place in the building. The architectural program along with site characteristics are among a few of the important guidelines in studying the form, adjacencies, and circulation for the structure itself and also in relation to the adjacent structures. Conceptual studies are part of the schematic design, which is the first milestone in the design process. The other reference points are design development and construction documents. At each milestone, review and coordination with all the consultants is established, and the user is essential in refining the project. In design development phase, conceptual diagrams take shape, and architectural, structural, mechanical, and electrical systems are developed. The final phase construction documents convey all the information required to construct the building. The design process and elements described were applied in the following project.

Jahromi, Soheila↗
NASA NTRS1997

Multicriteria Gain Tuning for Rotorcraft Flight Controls (also entitled The Development of the Conduit Advanced Control System Design and Evaluation Interface with a Case Study Application Fly by Wire Helicopter Design)

Handling qualities analysis and control law design would seem to be naturally complimenting components of aircraft flight control system design, however these two closely coupled disciplines are often not well integrated in practice. Handling qualities engineers and control system engineers may work in separate groups within an aircraft company. Flight control system engineers and handling quality specialists may come from different backgrounds and schooling and are often not aware of the other group's research. Thus while the handling qualities specifications represent desired aircraft response characteristics, these are rarely incorporated directly in the control system design process. Instead modem control system design techniques are based on servo-loop robustness specifications, and simple representations of the desired control response. Comprehensive handling qualities analysis is often left until the end of the design cycle and performed as a check of the completed design for satisfactory performance. This can lead to costly redesign or less than satisfactory aircraft handling qualities when the flight testing phase is reached. The desire to integrate the fields of handling qualities and flight,control systems led to the development of the CONDUIT system. This tool facilitates control system designs that achieve desired handling quality requirements and servo-loop specifications in a single design process. With CONDUIT, the control system engineer is now able to directly design and control systems to meet the complete handling specifications. CONDUIT allows the designer to retain a preferred control law structure, but then tunes the system parameters to meet the handling quality requirements.

Biezad, Daniel↗
DOE OSTI2025

Mixed-Integer Linear Programming Formulation with Embedded Machine Learning Surrogates for the Design of Chemical Process Families

In previous work, we introduced process family design. The main idea is to design a platform of common elements, and, allowing us to capture additional cost savings, simultaneously design a family of processes, and reducing both engineering and deployment timelines. We formulate this as an optimization problem, specifically a nonlinear generalized disjunctive program (GDP). We have proposed two approaches for reformulating and solving this problem: one based on full-discretization of the design space and one that uses Machine Learning (ML) surrogates to replace the nonlinear process models. Using ML surrogates to predict required system costs and performance indicators allows us to reformulate the nonlinearities in the GDP generate an efficient MILP formulation. In this work, we apply the ML surrogate approach to two case studies. One case study involves designing a family of carbon capture systems to cover a set of different flue gas flow rates and inlet CO 2 concentrations, where we consider the absorber and stripper as common unit module types. The second case study focuses on a water-desalination process, where we design a family of these processes for a variety of salt concentrations and flow rates. In both of these case studies, we demonstrate a scalable optimization approach that enables the design of multiple processes simultaneously, reducing the time-to-market and overall costs by maximizing the cost savings due to both economies of scale and economies of numbers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRSDate not supplied

Design and Optimization of a 3-Stage Axial Supercritical CO2 Compressor

This paper presents the detailed design and optimization of a three-stage axial supercritical carbon dioxide (sCO2) compressor to support the advancement of sCO 2 power cycles, recognized for their efficiency and compactness in energy conversion. The three-stage design is a scaled model of the original nine-stage 100 MW design. The aerodynamic design and structural analysis were performed at the University of Cincinnati, and the results are presented. The first stage of the design has been meticulously manufactured and experimentally tested at University of Notre Dame Turbomachinery Laboratory. The design process starts with the preliminary design process, considering the required operating boundary conditions and geometrical constraints for full stage design. The design is then scaled down to 3-stage based on the power limitation. The definition for design parameters has been inspired from the EEE HPC design and tweaked to fit the sCO 2 operation. Axisymmetric analysis is performed next and the parametric geometry modeler -Tblade3 has been used to create 3D blade geometry from the results which can then be exported for the 3D CFD analysis and optimization. An efficiency of 89.85% is predicted for the final design at the design point.

Compressor↗
NASA NTRS2024

Automation of the ICME Workflow Incorporating Material Digital Twins at Different Length Scales Within a Robust Information Management System

Recent successes in Integrated Computational Materials Engineering (ICME) have demonstrated the potential in designing ‘fit-for-purpose’ materials for a given application in a cost and time efficient manner. However, the material design process must contain a level of judicious automation in the material decision process; that is implementing some optimization algorithms to truly enable the benefits of ICME, particularly when considering materials at multiple length and time scales. Furthermore, the ability to effectively store developed material models, experimental data used for validation, and link models at multiple length and time scales must be implemented to ensure traceability across the material design process, such that the data gathered can be leveraged towards efficient material design. To enable such an optimization scheme a robust framework must exist: (1) that can capture changes made at a given length scale, (2) automatically propagate changes upstream to the highest scale, and (3) evaluate the material’s performance at the structural level. In this work, a developed framework for tracking material changes, automatically running the necessary simulations to determine the properties at the next highest scale, and saving each iteration of the design process to maintain the application’s digital thread is presented for polymer matrix composites (PMCs). The Automated Information Management Across Organizations and Scales (AIMAOS) program offers users an interactive graphical user interface (GUI) for defining constituent materials, building lamina and laminates, and applying effective laminate properties to finite element and composite optimization third party software. At each length scale, the necessary input files are automatically written, and subsequent analysis tools are called to solve for effective properties at the next scale, which are then read by the AIMAOS tool and displayed to the user. As changes are made to the material at lower length scales, information is automatically propagated upstream to higher length scales, and changes made are automatically tracked and versioned to maintain traceability during the design process. The AIMAOS tools serves as the first step in enabling optimized design of composites from the nano to the macroscale for a given application.

Brandon L Hearley↗
NASA NTRS1988

Figures of merit for airfoil/aircraft design integration

Because the airfoil can so strongly impact other aspects of an aircraft configuration, it is important that the airfoil design process be integrated with that of the aircraft to achieve the best possible performance of a new flight vehicle. To aid in preliminary design efforts, several aerodynamic figures of merit are presented which facilitate the matching of the airfoil performance characteristics to those of the aircraft. These figures of merit are fairly general and can assist the airfoil design process for flight vehicles designed for maximum endurance, range, or ceiling. Although specifically applicable to vehicles for which the wing area is sized by some required minimum airspeed, the discussion is pertinent to all airfoil/aircraft matching situations and points the way for developing similar figures of merit to aid the airfoil/aircraft design process for any flight vehicle.

Maughmer, Mark D.↗
DOE OSTI2025

Transforming the Process Industries through Electrification: Challenges and Opportunities

For the more than 70 years, the process industries have provided essential fuels and materials for global growth. Increased manufacturing production comes with substantial environmental impact. Reducing environmental impact through process electrification, carbon capture, and other emerging technologies would require large changes throughout the process industries. We review opportunities and challenges related to electrification, focusing on technical, operational, and economic considerations. Here, we conclude that electrification could completely eliminate scope 1 CO 2 emissions, increase product quality, and reduce the equipment size and cost. On the other hand, it calls for a significant expansion of power generation capacity, as well as new paradigms for process design and operations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2015

Advancing the State-of-the-Practice for Liquid Rocket Engine Injector Design

Current shortcomings in both the overall injector design process and its underlying combustion stability assessment methodology are rooted in the use of empirically based or low fidelity representations of complex physical phenomena and geometry details that have first order effects on performance, thermal environments and combustion stability. The result is a design and analysis capability that is often inadequate to reliably arrive at a suitable injector design in an efficient manner. Specifically, combustion instability has been particularly difficult to predict and mitigate. Large hydrocarbon-fueled booster engines have been especially problematic in this regard. Where combustion instability has been a problem, costly and time-consuming redesign efforts have often been an unfortunate consequence. This paper presents an overview of a recently completed effort at NASA Marshall Space Flight Center to advance the state-of-the-practice for liquid rocket engine injector design. Multiple perturbations of a gas-centered swirl coaxial (GCSC) element that burned gaseous oxygen and RP-1 were designed, assessed for combustion stability, and tested. Three designs, one stable, one marginally unstable and one unstable, were used to demonstrate both an enhanced overall injector design process and an improved combustion stability assessment process. High-fidelity results from state-of-the-art computational fluid dynamics CFD simulations were used to substantially augment and improve the injector design methodology. The CFD results were used to inform and guide the overall injector design process. They were also used to upgrade selected empirical or low-dimensional quantities in the ROCket Combustor Interactive Design (ROCCID) stability assessment tool. Hot fire single element injector testing was used to verify both the overall injector designs and the stability assessments. Testing was conducted at the Air Force Research Laboratory and at Purdue University. Companion papers provide details of the overall injector design process, full- and sub-scale testing, ROCCID-based stability assessments and the CFD simulations.

Tucker, P. K.↗
NASA NTRS1993

A dataflow analysis tool for parallel processing of algorithms

A graph-theoretic design process and software tool is presented for selecting a multiprocessing scheduling solution for a class of computational problems. The problems of interest are those that can be described using a dataflow graph and are intended to be executed repetitively on a set of identical parallel processors. Typical applications include signal processing and control law problems. Graph analysis techniques are introduced and shown to effectively determine performance bounds, scheduling constraints, and resource requirements. The software tool is shown to facilitate the application of the design process to a given problem.

Jones, Robert L., III↗
DOE OSTI2024

Decomposition and Algorithmic Approaches for Solving Large-Scale Process Family Design Problems

Our most recent work expands the water desalination case study from 76 variants to 10,897 variants using the equation-oriented model built in Pyomo as part of the PARETO project. Using the discretization formulation presented in Stinchfield (2024a), rather than solving for all 10,897 variants simultaneously, we decompose the formulation into subproblems containing subsets of variants from the process family. We solve the overall problem with Progressive Hedging (PH) deployed in parallel on a distributed HPC cluster using the open-source Python package mpi-sppy (Knueven et al., 2023). This approach allowed us to solve this process family design problem to ~1.5% relative optimality gap in about 5 hours; in comparison, Gurobi reached ~50% relative optimality gap in about 6 hours (Stinchfield et al., 2024b). However, this approach still requires discretization of the common unit module design ranges; additionally, PH acts as a heuristic for MILP’s with gap-closing capabilities. Ideally, we would not have to use ML surrogates or discretization to solve this problem, instead solving the process family design problem with the equation-oriented model directly to achieve the most accurate results. However, recall that we did not consider solving the MINLP directly due to complexity and size. In this work, we aim to decompose and solve this large-scale MINLP using a Structured Nonlinear Global Optimization algorithm presented by Cao and Zavala (2019).

Stinchfield, Georgia↗
NASA NTRS1989

The role of optimization in the next generation of computer-based design tools

There is a close relationship between design optimization and the emerging new generation of computer-based tools for engineering design. With some notable exceptions, the development of these new tools has not taken full advantage of recent advances in numerical design optimization theory and practice. Recent work in the field of design process architecture has included an assessment of the impact of next-generation computer-based design tools on the design process. These results are summarized, and insights into the role of optimization in a design process based on these next-generation tools are presented. An example problem has been worked out to illustrate the application of this technique. The example problem - layout of an aircraft main landing gear - is one that is simple enough to be solved by many other techniques. Although the mathematical relationships describing the objective function and constraints for the landing gear layout problem can be written explicitly and are quite straightforward, an approximation technique has been used in the solution of this problem that can just as easily be applied to integrate supportability or producibility assessments using theory of measurement techniques into the design decision-making process.

Rogan, J. Edward↗
NASA NTRS1993

Interdisciplinary technology

The 'computational test-cell' will enable the incorporation of new methodologies, such as concurrent engineering and probabilistic methods, into the propulsion design process. This will provide the capability to conduct credible, interdisciplinary analyses of new propulsion concepts and designs. Probabilistic methods can be used as the basis for reliability-based design. Recently methods have been devised that provide the capability of simulating the performance of propulsion systems at several levels of resolution. These methods make it possible to quantify uncertainty and to establish confidence bounds for the calculated values. The introduction of reliability-based design methodology along with probabilistic analyses will provide a tool to reduce the design space for new systems and to reduce our dependence on hardware testing for proof-of-concept and system integration demonstrations. The resulting simulations will reduce the need for testing and identify potential operational problems early in the design process. This capability will make it possible to compute the expected performance, stability, reliability, and life of propulsion components, subsystems, and systems at design and off-design conditions, to bring life cycle cost trade-offs early into the design process and to determine optimum designs to satisfy specified mission requirements.

Nichols, Lester D.↗
DOE OSTI2022

Process-informed adsorbent design guidelines for direct air capture

Direct air capture using solid adsorbents is a proven technology critical to reducing our net greenhouse gas emissions to zero and beyond. Currently, academic research into the technology mainly focuses on the development of new adsorbents. However, there is a discord between the adsorbent design and process performance. Many materials scientists focus on maximising metrics such as the CO 2 capacity of their adsorbent. Here, we combine detailed process modelling, machine learning, and extensive global sensitivity analysis, which entails varying all of the model parameters together, on a direct air capture process to show that the dry CO 2 adsorption capacity does not influence process performance for an amine-functionalised adsorbent operating in a temperature vacuum swing adsorption (TVSA) process, while it is important in a steam-assisted TVSA (S-TVSA) process. In fact, adsorption kinetics, density, and thermal conductivity are all critical attributes to obtaining a low energy penalty and reduced costs. The analysis also highlights the importance of heat transfer, directing process engineers to (alternative) adsorber designs that maximise this. By an in-depth evaluation of how process performance indicators are affected by materials properties and process operating parameters, this work provides guidance to both material scientists and process engineers towards the design of a “unicorn adsorbent” and intensified DAC processes. This will improve the performance of solid adsorbent direct air capture and help drive down the costs of this vital technology to avert the worst impacts of climate change.

42 ENGINEERING↗
DOE OSTI2024

LENS: Learning Enabled Network Synthesis

RTRC and UMD have developed novel machine learning based methods under the ARPA-E DIFFERENTIATE program for rapid acceleration of hypothesis generation in complex architecture design spaces involving both discrete choices of component inclusion and interconnection and continuous parametric decisions. The project named Learning Enabled Network Synthesis (LENS) further demonstrated the developed methods on challenging electrical power converter design problems by identifying the most suitable circuit topologies and simultaneously selecting the most appropriate components to achieve optimized design of power converter with improved performances. We demonstrated that LENS could enable exploration of very large design space of circuit topologies and components by addressing the limitations of conventional design process in non-linear, high switching speed, multi-dimensional power converter design and optimization. The key innovation developed in LENS is the seamless integration of statistical learning and logical reasoning techniques and building on the individual strengths of these techniques for rapid hypothesis discovery. The main component of LENS comprises of: 1) Graph Reasoning Engine (GRE) to enforce composition rules that rapidly reject all discrete architectures that are composed incorrectly and generates an adaptive database of feasible designs which can be used by ML modules, 2) Graph Generative Learning module which is a deep neural network based generative model for graph architectures which can enable design space exploration beyond the dataset generated by the GRE, 3) Graph Reduced Order Model (ROM) for graph domains for accelerating computation of output metrics, and 4) Active learning and Rule Discovery module for sample efficient learning and extracting logical rules from the learned ML models which will be integrated in the GRE to enhance the filtering effectiveness. LENS approach can be applied to any design domains where designs can be represented as multi-attribute graphs. The LENS team integrated the various technical innovations listed above into an optimization pipeline and exercised the optimization pipeline on the converter design problem. The LENS project demonstrated that the developed AI/ML technologies can be used to generate novel converter circuits >45x faster than experts on chosen use-cases. This can enable faster design space exploration and identification of new designs which are not considered by experts due to the increasing design space complexity. This has significant potential impact on the public and energy needs of the country. It is currently estimated that 30% of all electrical powers generated passes through power converters. The future estimate is that 80% of all power generated would be passing through converters. LENS fills a critical gap in this space since by accelerating the design process the designers would be able to generate more efficient converters which can lead to significant energy savings for the country.

42 ENGINEERING↗
NASA NTRS1999

The Numerical Propulsion System Simulation: A Multidisciplinary Design System for Aerospace Vehicles

Advances in computational technology and in physics-based modeling are making large scale, detailed simulations of complex systems possible within the design environment. For example, the integration of computing, communications, and aerodynamics has reduced the time required to analyze ma or propulsion system components from days and weeks to minutes and hours. This breakthrough has enabled the detailed simulation of major propulsion system components to become a routine part of design process and to provide the designer with critical information about the components early in the design process. This paper describes the development of the Numerical Propulsion System Simulation (NPSS), a multidisciplinary system of analysis tools that is focussed on extending the simulation capability from components to the full system. This will provide the product developer with a "virtual wind tunnel" that will reduce the number of hardware builds and tests required during the development of advanced aerospace propulsion systems.

Lytle, John K.↗
NASA NTRS2014

Conceptual Design Optimization of an Augmented Stability Aircraft Incorporating Dynamic Response Performance Constraints

This research focused on incorporating stability and control into a multidisciplinary de- sign optimization on a Boeing 737-class advanced concept called the D8.2b. A new method of evaluating the aircraft handling performance using quantitative evaluation of the sys- tem to disturbances, including perturbations, continuous turbulence, and discrete gusts, is presented. A multidisciplinary design optimization was performed using the D8.2b transport air- craft concept. The con guration was optimized for minimum fuel burn using a design range of 3,000 nautical miles. Optimization cases were run using xed tail volume coecients, static trim constraints, and static trim and dynamic response constraints. A Cessna 182T model was used to test the various dynamic analysis components, ensuring the analysis was behaving as expected. Results of the optimizations show that including stability and con- trol in the design process drastically alters the optimal design, indicating that stability and control should be included in conceptual design to avoid system level penalties later in the design process.

Welstead, Jason↗