Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “process design”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Status of integrated multidisciplinary rotorcraft optimization research at the Langley Research Center

This paper describes a joint NASA/Army research activity at the Langley Research Center to develop optimization procedures aimed at improving the rotor blade design process by integrating appropriate disciplines and accounting for important interactions among the disciplines. The activity is being guided by a Steering Committee made up of key NASA and Army researchers and managers. The paper describes the optimization formulation in terms of the objective function, design variables, and constraints. The analysis aspects are discussed, and the interdisciplinary interactions are defined in terms of the information that must be transferred among disciplinary analyses as well as the trade-offs between disciplines in determining the details of the design. At this writing, some significant progress has been made. Results given in the paper represent accomplishments in rotor aerodynamic performance optimization for minimum horsepower, rotor dynamic optimization for vibration reduction, approximate analysis of frequencies and mode shapes, rotor structural optimization for minimum weight, and integrated aerodynamic load/dynamics optimization for minimum vibration and weight.

Mantay, Wayne R.↗
NASA NTRS1993

Design and test of a small two stage counter-rotating turbine for rocket engine application

The aerodynamic design and rig test evaluation of a small counter-rotating turbine system is described. The technology represented by this turbine is being developed for application in an advanced upper stage rocket engine turbopump. This engine will employ an oxygen/hydrogen expander cycle and achieve high performance through efficient combustion, high combustion pressure, and high area ratio exhaust nozzle expansion. Engine performance goals require that the turbopump drive turbines achieve high efficiency at low gas flow rates. The low flow rates result in very small airfoil diameter, height and chord. The high efficiency and small size requirements present a challenging turbine design problem. The unconventional approach employed to meet this challenge is described, along with the detailed design process and resulting airfoil configurations. The method and results of full scale aerodynamic performance evaluation testing of both one and two stage configurations, as well as operation without the secondary stage stator are presented. The overall results of this effort illustrate that advanced aerodynamic design tools and hardware fabrication techniques have provided improved capability to produce small high performance turbines for advanced rocket engines.

Huber, F. W.↗
NASA NTRS2006

Single- and Multiple-Objective Optimization with Differential Evolution and Neural Networks

Genetic and evolutionary algorithms have been applied to solve numerous problems in engineering design where they have been used primarily as optimization procedures. These methods have an advantage over conventional gradient-based search procedures became they are capable of finding global optima of multi-modal functions and searching design spaces with disjoint feasible regions. They are also robust in the presence of noisy data. Another desirable feature of these methods is that they can efficiently use distributed and parallel computing resources since multiple function evaluations (flow simulations in aerodynamics design) can be performed simultaneously and independently on ultiple processors. For these reasons genetic and evolutionary algorithms are being used more frequently in design optimization. Examples include airfoil and wing design and compressor and turbine airfoil design. They are also finding increasing use in multiple-objective and multidisciplinary optimization. This lecture will focus on an evolutionary method that is a relatively new member to the general class of evolutionary methods called differential evolution (DE). This method is easy to use and program and it requires relatively few user-specified constants. These constants are easily determined for a wide class of problems. Fine-tuning the constants will off course yield the solution to the optimization problem at hand more rapidly. DE can be efficiently implemented on parallel computers and can be used for continuous, discrete and mixed discrete/continuous optimization problems. It does not require the objective function to be continuous and is noise tolerant. DE and applications to single and multiple-objective optimization will be included in the presentation and lecture notes. A method for aerodynamic design optimization that is based on neural networks will also be included as a part of this lecture. The method offers advantages over traditional optimization methods. It is more flexible than other methods in dealing with design in the context of both steady and unsteady flows, partial and complete data sets, combined experimental and numerical data, inclusion of various constraints and rules of thumb, and other issues that characterize the aerodynamic design process. Neural networks provide a natural framework within which a succession of numerical solutions of increasing fidelity, incorporating more realistic flow physics, can be represented and utilized for optimization. Neural networks also offer an excellent framework for multiple-objective and multi-disciplinary design optimization. Simulation tools from various disciplines can be integrated within this framework and rapid trade-off studies involving one or many disciplines can be performed. The prospect of combining neural network based optimization methods and evolutionary algorithms to obtain a hybrid method with the best properties of both methods will be included in this presentation. Achieving solution diversity and accurate convergence to the exact Pareto front in multiple objective optimization usually requires a significant computational effort with evolutionary algorithms. In this lecture we will also explore the possibility of using neural networks to obtain estimates of the Pareto optimal front using non-dominated solutions generated by DE as training data. Neural network estimators have the potential advantage of reducing the number of function evaluations required to obtain solution accuracy and diversity, thus reducing cost to design.

Rai, Man Mohan↗
NASA NTRS2014

Application of the Tool for Turbine Engine Closed-loop Transient Analysis (TTECTrA) for Dynamic Systems Analysis

Systems analysis involves steady-state simulations of combined components to evaluate the steady-state performance, weight, and cost of a system; dynamic considerations are not included until later in the design process. The Dynamic Systems Analysis task, under NASAs Fixed Wing project, is developing the capability for assessing dynamic issues at earlier stages during systems analysis. To provide this capability the Tool for Turbine Engine Closed-loop Transient Analysis (TTECTrA) has been developed to design a single flight condition controller (defined as altitude and Mach number) and, ultimately, provide an estimate of the closed-loop performance of the engine model. This tool has been integrated with the Commercial Modular Aero-Propulsion System Simulation 40,000 (CMAPSS 40k) engine model to demonstrate the additional information TTECTrA makes available for dynamic systems analysis. This dynamic data can be used to evaluate the trade-off between performance and safety, which could not be done with steady-state systems analysis data. TTECTrA has been designed to integrate with any turbine engine model that is compatible with the MATLAB Simulink (The MathWorks, Inc.) environment.

control↗
NASA NTRS2014

Path Toward a Unifid Geometry for Radiation Transport

The Direct Accelerated Geometry for Radiation Analysis and Design (DAGRAD) element of the RadWorks Project under Advanced Exploration Systems (AES) within the Space Technology Mission Directorate (STMD) of NASA will enable new designs and concepts of operation for radiation risk assessment, mitigation and protection. This element is designed to produce a solution that will allow NASA to calculate the transport of space radiation through complex computer-aided design (CAD) models using the state-of-the-art analytic and Monte Carlo radiation transport codes. Due to the inherent hazard of astronaut and spacecraft exposure to ionizing radiation in low-Earth orbit (LEO) or in deep space, risk analyses must be performed for all crew vehicles and habitats. Incorporating these analyses into the design process can minimize the mass needed solely for radiation protection. Transport of the radiation fields as they pass through shielding and body materials can be simulated using Monte Carlo techniques or described by the Boltzmann equation, which is obtained by balancing changes in particle fluxes as they traverse a small volume of material with the gains and losses caused by atomic and nuclear collisions. Deterministic codes that solve the Boltzmann transport equation, such as HZETRN [high charge and energy transport code developed by NASA Langley Research Center (LaRC)], are generally computationally faster than Monte Carlo codes such as FLUKA, GEANT4, MCNP(X) or PHITS; however, they are currently limited to transport in one dimension, which poorly represents the secondary light ion and neutron radiation fields. NASA currently uses HZETRN space radiation transport software, both because it is computationally efficient and because proven methods have been developed for using this software to analyze complex geometries. Although Monte Carlo codes describe the relevant physics in a fully three-dimensional manner, their computational costs have thus far prevented their widespread use for analysis of complex CAD models, leading to the creation and maintenance of toolkit-specific simplistic geometry models. The work presented here builds on the Direct Accelerated Geometry Monte Carlo (DAGMC) toolkit developed for use with the Monte Carlo N-Particle (MCNP) transport code. The workflow for achieving radiation transport on CAD models using MCNP and FLUKA has been demonstrated and the results of analyses on realistic spacecraft/habitats will be presented. Future work is planned that will further automate this process and enable the use of multiple radiation transport codes on identical geometry models imported from CAD. This effort will enhance the modeling tools used by NASA to accurately evaluate the astronaut space radiation risk and accurately determine the protection provided by as-designed exploration mission vehicles and habitats

Lee, Kerry↗
NASA NTRS2014

Application of the Tool for Turbine Engine Closed-loop Transient Analysis (TTECTrA) for Dynamic Systems Analysis

Systems analysis involves steady-state simulations of combined components to evaluate the steady-state performance, weight, and cost of a system; dynamic considerations are not included until later in the design process. The Dynamic Systems Analysis task, under NASAs Fixed Wing project, is developing the capability for assessing dynamic issues at earlier stages during systems analysis. To provide this capability the Tool for Turbine Engine Closed-loop Transient Analysis (TTECTrA) has been developed to design a single flight condition controller (defined as altitude and Mach number) and, ultimately, provide an estimate of the closed-loop performance of the engine model. This tool has been integrated with the Commercial Modular Aero-Propulsion System Simulation 40,000(CMAPSS40k) engine model to demonstrate the additional information TTECTrA makes available for dynamic systems analysis. This dynamic data can be used to evaluate the trade-off between performance and safety, which could not be done with steady-state systems analysis data. TTECTrA has been designed to integrate with any turbine engine model that is compatible with the MATLABSimulink (The MathWorks, Inc.) environment.

systems analysis↗
NASA NTRSDate not supplied

Astrobee Free-Flyer Nozzle Mechanism

This paper describes the development and design of the Astrobee Free-Flyer propulsion nozzle assemblies. As will be illustrated in this paper, the Free-Flyer nozzles are thrust control devices used to propel the Astrobee Free-Flyer robot autonomously inside the International Space Station (ISS). The development process, design evolution, and prototyping methods, are described. Key design features are discussed in greater detail to highlight how a seemingly simple design can present surprisingly large challenges. Several lessons learned are given.

Earl Daley↗
DOE OSTI2022

Creation of Simulated Test Cases for the Oscillation Source Location Contest: Preprint

This paper describes in detail the design process and creation of 13 oscillatory test cases for the IEEE and NASPI co-hosted Oscillation Source Locating Contest conducted in 2021. The challenges behind the 13 cases are fully demystified. Based on the philosophy, implementation considerations and techniques used for the case design presented in this paper, interested readers can create additional interesting cases for testing the efficiency of their oscillation source location methods.

ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

AbBERT: Learning Antibody Humanness via Masked Language Modeling

Understanding the degree of humanness of antibody sequences is critical to the therapeutic antibody development process to reduce the risk of failure modes like immunogenicity or poor manufacturability. We introduce AbBERT, a transformer-based language model trained on up to 20 million unpaired heavy/light chain sequences from the Observed Antibody Space database. We first validate AbBERT using a novel “multi-mask” scoring procedure to demonstrate high accuracy in predicting complementary determining regions—including the challenging hypervariable H3 region. We then demonstrate several uses of AbBERT at various points along the antibody design process. AbBERT enhances in silico antibody optimization via deep reinforcement learning by utilizing its learned embeddings as additional observations during optimization. Within a larger computational antibody design platform, AbBERT has been successfully applied as an additional design objective, where it displays strong correlations with computational tools predicting antibody structural stability. Finally, mutant antibody sequences that have been scored as unfavorable by AbBERT have shown corresponding low yields when expressed in cells. These use cases demonstrate the power of language modeling within computational antibody design.

Bioinformatics↗
NASA NTRS1988

Reliability Model Generator for fault-tolerant systems

This paper discusses an analysis tool, the Reliability Model Generator, that reasons from structural and functional system design specifications to generate a reliability model for the system under investigation. The resultant model defines a system state space sufficient to characterize the effects of single and multiple component failures. This model may then be examined by the analyst or used as input to an existing reliability evaluation tool, the Semi-Markov Unreliability Range Evaluator (SURE), to compute numeric bounds for system reliability (i.e., safety, mission success, availability, etc.). In defining the input to the Reliability Model Generator, a separation of the component function from structural specification is proposed to allow easy modification for analysis of alternative architectures. A hierarchical system description paradigm promotes multiple abstractions, thereby enabling analysis at all phases of the design process. The work described in this paper has been supported under NASA contract NAS1-10899, Integrated Airframe/Propulsion Control System Architecture (IAPSA II). IAPSA II promotes a system engineering methodology and supporting analytical tools to evaluate flight control architecture configuration alternatives during early phases of the design cycle when the cost and schedule impact of design revisions is minimal. Emphasis is placed on traceability to ensure that the requirements drive the resulting design.

Catherine M McCann↗
NASA NTRS1992

Integrated multidisciplinary rotorcraft optimization research at the NASA Langley Research Center

NASA-Langley and U.S. Army researchers have developed optimization procedures for improving helicopter rotor blade design processes through more extensive integration of the requisite disciplines. These disciplines encompass rotor aerodynamics, rotor dynamics, rotor structures, airframe dynamics, and acoustics. In the first phase of this integrated optimization approach, acoustics and airframe aerodynamics are decoupled and accounted for as effective constraints on the design for the first three disciplines. In phase two, acoustics is integrated with the first three disciplines; in phase three, airframe dynamics are integrated with the other four disciplines. Representative results are presented from recent work on blade shear force reduction and aerodynamic/dynamic optimization.

Adelman, Howard M.↗
NASA NTRS2002

Design, Fabrication, and Testing of Composite Energy-Absorbing Keel Beams for General Aviation Type Aircraft

A lightweight energy-absorbing keel-beam concept was developed and retrofitted in a general aviation type aircraft to improve crashworthiness performance. The energy-absorbing beam consisted of a foam-filled cellular structure with glass fiber and hybrid glass/kevlar cell walls. Design, analysis, fabrication and testing of the keel beams prior to installation and subsequent full-scale crash testing of the aircraft are described. Factors such as material and fabrication constraints, damage tolerance, crush stress/strain response, seat-rail loading, and post crush integrity, which influenced the course of the design process are also presented. A theory similar to the one often used for ductile metal box structures was employed with appropriate modifications to estimate the sustained crush loads for the beams. This, analytical tool, coupled with dynamic finite element simulation using MSC.Dytran were the prime design and analysis tools. The validity of the theory as a reliable design tool was examined against test data from static crush tests of beam sections while the overall performance of the energy-absorbing subfloor was assessed through dynamic testing of 24 in long subfloor assemblies.

Kellas, Sotiris↗
NASA NTRS2012

Deployment Analysis of a Simple Tape-Spring Hinge Using Probabilistic Methods

Acceptance of new deployable structures architectures and concepts requires validated design methods to minimize the expense involved with technology validation flight testing. Deployable concepts for large lightweight spacecraft include booms, antennae, and masts. This paper explores the implementation of probabilistic methods in the design process for the deployment of a strain-energy mechanism, specifically a simple tape-spring hinge. Strain-energy mechanisms are attractive for deployment in very lightweight systems because they do not require the added mass and complexity associated with motors and controllers. However, designers are hesitant to include free deployment, strain-energy mechanisms because of the potential for uncontrolled behavior. In the example presented here, the tapespring cross-sectional dimensions have been varied and a target displacement during deployment has been selected as the design metric. Specifically, the tape-spring should reach the final position in the shortest time with the minimal amount of overshoot and oscillations. Surrogate models have been used to reduce computational expense. Parameter values to achieve the target response have been computed and used to demonstrate the approach. Based on these results, the application of probabilistic methods for design of a tape-spring hinge has shown promise as a means of designing strain-energy components for more complex space concepts.

Lyle, Karen H.↗
NASA NTRS2016

Trajectory Design to Mitigate Risk on the Transiting Exoplanet Survey Satellite (TESS) Mission

The Transiting Exoplanet Survey Satellite (TESS) will employ a highly eccentric Earth orbit, in 2:1 lunar resonance, reached with a lunar flyby preceded by 3.5 phasing loops. The TESS mission has limited propellant and several orbit constraints. Based on analysis and simulation, we have designed the phasing loops to reduce delta-V and to mitigate risk due to maneuver execution errors. We have automated the trajectory design process and use distributed processing to generate and to optimize nominal trajectories, check constraint satisfaction, and finally model the effects of maneuver errors to identify trajectories that best meet the mission requirements.

design↗
NASA NTRS2018

Influence of Core and Hexapod Geometry, and Local Reinforcement on the Performance of Ultra-Lightweight ULE Mirror

The Habitable Exoplanet Observatory (HabEx) mission has unique optical performance requirements which drive the mirror design process beyond the traditional criteria. While mass and stiffness are still important, the response to inertia loading (expressed in terms of Zernike coefficients) to omni-directional excitation dominates the effort. While a Zerodur mirror is the current baseline, as mass budgets change, a ULE design is being studied as a potential alternative. This trade study looked at over 264 design variations using the Arnold Mirror Modeler and ANSYS(c) to investigate the influence of various design elements, including: substrate thickness, core cell size, hexapod geometry and local reinforcement. Design 'goodness' was evaluated based on the mirror's inertial deformation response to omni-directional input. This response was calculated via RSSing Zernike polynomial responses to (XYZ) accelerations.

Space Telescope Technology↗
NASA NTRS2020

Mars Science Helicopter Conceptual Design

Robotic planetary aerial vehicles increase the range of terrain that can be examined, compared to traditional landers and rovers, and have more near-surface capability than orbiters. Aerial mobility is a promising possibility for planetary exploration as it reduces the challenges that difficult obstacles pose to ground vehicles. The first use of a rotorcraft for a planetary mission will be in 2021, when the Mars Helicopter technology demonstrator will be deployed from the Mars 2020 rover. The Jet Propulsion Laboratory and NASA Ames Research Center are exploring possibilities for a Mars Science Helicopter, a second-generation Mars rotorcraft with the capability of conducting science investigations independently of a lander or rover (although this type of vehicle could also be used assist rovers or landers in future missions). This report describes the conceptual design of Mars Science Helicopters. The design process began with coaxial-helicopter and hexacopter configurations, with a payload in the range of two to three kg and an overall vehicle mass of approximately twenty kg. Initial estimates of weight and performance were based on the capabilities of the Mars Helicopter. Rotorcraft designs for Mars are constrained by the dimensions of the aeroshell and lander for the trip to the planet, requiring attention to the aircraft packaging in order to maximize the rotor dimensions and hence overall performance potential. Aerodynamic performance optimization was conducted, particularly through airfoils designed specifically for the low Reynolds number and high Mach number inherent to operation on Mars. Rotor structural designs were developed that met blade frequency and weight targets, subject to material stress limits. The final designs show a substantial capability for science operations on Mars: a 31 kg hexacopter that fits within a 2.5 m diameter aeroshell could carry a 5 kg payload for 10 min of hover time or over a range of 5 km.

Wayne Johnson↗
DOE OSTI2024

A review on machine learning-guided design of energy materials

Abstract The development and design of energy materials are essential for improving the efficiency, sustainability, and durability of energy systems to address climate change issues. However, optimizing and developing energy materials can be challenging due to large and complex search spaces. With the advancements in computational power and algorithms over the past decade, machine learning (ML) techniques are being widely applied in various industrial and research areas for different purposes. The energy material community has increasingly leveraged ML to accelerate property predictions and design processes. This article aims to provide a comprehensive review of research in different energy material fields that employ ML techniques. It begins with foundational concepts and a broad overview of ML applications in energy material research, followed by examples of successful ML applications in energy material design. We also discuss the current challenges of ML in energy material design and our perspectives. Our viewpoint is that ML will be an integral component of energy materials research, but data scarcity, lack of tailored ML algorithms, and challenges in experimentally realizing ML-predicted candidates are major barriers that still need to be overcome.

36 MATERIALS SCIENCE↗
NASA NTRS1979

High-resolution optical telescope for ultraviolet /UV/ radiation field

Design techniques are discussed for all-reflecting optics from first-order system considerations and applications currently utilized in the field of astronomical optics. The solution of the Dall-Karkham design problem is described, showing the advantage of inexpensive construction as compared with higher order surfaces. The design process reported here is a F/5 collecting system which quickly mates directly with the spectrometer; it is capable of achieving desired high resolution and sensitivity requirements. The theoretical limit of aberration tolerances is achieved with less than 1/8 of a wavelength at final focus (OPD). The design of spectrometer for ultra-violet (UV) radiation and its mechanism is included in this study.

Karayan, W. W.↗