Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Design optimization”

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 1,675 records · Page 93
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Fine Optimization of TES Design for the X-IFU Instrument on ATHENA

The X-ray Integral Field Unit (X-IFU) instrument on the Advanced Telescope for High ENergy Astrophysics (ATHENA) is baselined to have 3168 transition-edge sensor (TES) microcalorimeter pixels. These pixels will be DC biased and readout using time division multiplexing. We recently reported a demonstration of the required pixel and readout performance in 252 pixels from a 1 kilo-pixel array (e.g. 2.16 eV resolution for 6.9 keV X-rays). Having achieved the required performance, the 50um square TES design in this demonstration array is considered the baseline pixel design for X-IFU. However, by making small adjustments to the TES design, we may be able to make small but consequential improvements to the instrument performance, while staying within the many constraints of the X-IFU requirements. In this presentation, we will show results from newly fabricated devices with subtle changes from the baseline TES design to further optimize the performance for X-IFU. We will discuss optimizing the TES sheet resistance, normal metal features, X-ray absorber attachment points, TES aspect ratio, and heat capacity. These minor design changes can have significant effects on thermo-electric time constants, thermal fluctuation noise, resistive transition shape and uniformity, and non-linearity of X-ray event pulses. In addition, full characterization of these new TES designs allows greater understanding of the relevant physics within the TES and gives routes for further optimization.

Nick Wakeham↗
NASA NTRS1990

An enhanced integrated aerodynamic load/dynamic optimization procedure for helicopter rotor blades

An enhanced integrated aerodynamic load/dynamic optimization procedure is developed to minimize vibratory root shears and moments. The optimization is formulated with 4/rev vertical and 3/rev inplane shears at the blade root as objective functions and constraints, and 4/rev lagging moment. Constraints are also imposed on blade natural frequencies, weight, autorotational inertia, centrifugal stress, and rotor thrust. The 'Global Criteria Approach' is used for formulating the multi-objective optimization. Design variables include spanwise distributions of bending stiffnesses, torsional stiffness, nonstructural mass, chord, radius of gyration, and blade taper ratio. The program CAMRAD is coupled with an optimizer, which consists of the program CONMIN and an approximate analysis, to obtain optimum designs. The optimization procedure is applied to an advanced rotor as a reference design. Optimum blade designs, obtained with and without a constraint on the rotor thrust, are presented and are compared to the reference blade. Substantial reductions are obtained in the vibratory root forces and moments. As a byproduct, improvements are also found in some performance parameters, such as total power required, which were not considered during optimization.

Chattopadhyay, Aditi↗
NASA NTRS1999

A Computational/Experimental Study of Two Optimized Supersonic Transport Designs and the Reference H Baseline

Two supersonic transport configurations designed by use of non-linear aerodynamic optimization methods are compared with a linearly designed baseline configuration. One optimized configuration, designated Ames 7-04, was designed at NASA Ames Research Center using an Euler flow solver, and the other, designated Boeing W27, was designed at Boeing using a full-potential method. The two optimized configurations and the baseline were tested in the NASA Langley Unitary Plan Supersonic Wind Tunnel to evaluate the non-linear design optimization methodologies. In addition, the experimental results are compared with computational predictions for each of the three configurations from the Enter flow solver, AIRPLANE. The computational and experimental results both indicate moderate to substantial performance gains for the optimized configurations over the baseline configuration. The computed performance changes with and without diverters and nacelles were in excellent agreement with experiment for all three models. Comparisons of the computational and experimental cruise drag increments for the optimized configurations relative to the baseline show excellent agreement for the model designed by the Euler method, but poorer comparisons were found for the configuration designed by the full-potential code.

Cliff, Susan E.↗
NASA NTRS1997

Multidisciplinary Optimization Methods for Preliminary Design

An overview of multidisciplinary optimization (MDO) methodology and two applications of this methodology to the preliminary design phase are presented. These applications are being undertaken to improve, develop, validate and demonstrate MDO methods. Each is presented to illustrate different aspects of this methodology. The first application is an MDO preliminary design problem for defining the geometry and structure of an aerospike nozzle of a linear aerospike rocket engine. The second application demonstrates the use of the Framework for Interdisciplinary Design Optimization (FIDO), which is a computational environment system, by solving a preliminary design problem for a High-Speed Civil Transport (HSCT). The two sample problems illustrate the advantages to performing preliminary design with an MDO process.

Korte, J. J.↗
DOE OSTI2016

Data-Driven Optimization for the Design and Control of Large-Scale Systems (LDRD Final Report)

Engineering decisions are often formulated as optimization problems such as the optimal design or control of physical systems. In these applications, the resulting optimization problems are constrained by large-scale simulations involving systems of partial differential equations (PDEs), ordinary differential equations (ODEs), and differential algebraic equations (DAEs). In addition, critical components of these systems are fraught with uncertainty, including unverifiable modeling assumptions, unknown boundary and initial conditions, and uncertain coefficients. Typically, these components are estimated using noisy and incomplete data from a variety of sources (e.g., physical experiments). The lack of knowledge of the true underlying probabilistic characterization of model inputs motivates the need for optimal solutions that are robust to this uncertainty. In this report, we introduce a framework for handling "distributional" uncertainties in the context of simulation-based optimization. This includes a novel measure discretization technique that will lead to an adaptive optimization algorithm tailored to exploit the structures inherent to simulation- based optimization.

42 ENGINEERING↗
NASA NTRSDate not supplied

Assessment of Off-Design Low-Boom Characteristics of a Low-Boom Supersonic Transport

Most conceptual design methods for low-boom supersonic aircraft are developed for achieving an undertrack low-boom goal at the start of cruise. Although attempts have been made to design a supersonic aircraft achieving a low-boom goal for multiple azimuthal angles at the start of cruise, one unanswered question in inverse design optimization is how to define an achievable low-boom goal for multiple azimuthal angles. This paper proposes a new analysis method to assess off-design low-boom characteristics of a low-boom supersonic transport designed for an undertrack low-boom goal at the start of cruise. This method opens a potentially feasible path for conceptual design of a supersonic aircraft that has desired low-boom characteristics over the primary boom carpet for the entire cruise segment.

Low-boom supersonic transport↗
DOE OSTI2022

Reducing the Overnight Capital Cost of Advanced Reactors Using Equipment-Level Seismic Protective Systems

Consideration of the effects of earthquake shaking on the design and construction of nuclear power plants adds substantially to the overnight capital cost, with anecdotal estimates as high as 35+%, attributed to additional construction materials, need for one-off and sub-optimal designs of equipment due to conflicting design choices, the high cost of seismic qualification of equipment, and regulatory review. Safety-critical equipment in large light water reactors is designed and qualified for seismic demands imposed by the supporting reactor building, optimal mechanical designs are not possible, and designs of a given piece of equipment may vary with height above grade. Similar negative impacts are expected for advanced reactors unless the seismic design paradigm is changed. The overarching goal of this transformational MEITNER project, which involved a multidisciplinary engineering team and designers of three fundamentally different advanced reactors, was to adapt proven seismic isolation and damping technologies to operationalize modular protective systems for safety-class equipment inside advanced reactor buildings. Such seismic protective systems would be tightly integrated into design development for reactor support systems and balance-of-plant construction. The adoption of the technology, which is widely used in non-nuclear sectors, would simplify plant design, enable the use of standardized equipment and buildings, optimized for operational performance, and reduce plant size and weight. The need for site-specific equipment would be eliminated, enabling identical equipment to be used across multiple plants sited across the US and economies of scale, and catalyzing new interest and investment. The equipment-based protective systems would allow siting of advanced reactors in regions of high seismic hazard.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Toward digital design at the exascale: An overview of project ICECap

High performance computing has entered the Exascale Age. Capable of performing over 1018 floating point operations per second, exascale computers, such as El Capitan, the National Nuclear Security Administration's first, have the potential to revolutionize the detailed in-depth study of highly complex science and engineering systems. However, in addition to these kind of whole machine “hero” simulations, exascale systems could also enable new paradigms in digital design by making petascale hero runs routine. Currently, untenable problems in complex system design, optimization, model exploration, and scientific discovery could all become possible. Motivated by the challenge of uncovering the next generation of robust high-yield inertial confinement fusion (ICF) designs, project ICECap (Inertial Confinement on El Capitan) attempts to integrate multiple advances in machine learning (ML), scientific workflows, high performance computing, GPU-acceleration, and numerical optimization to prototype such a future. Built on a general framework, ICECap is exploring how these technologies could broadly accelerate scientific discovery on El Capitan. In addition to our requirements, system-level design, and challenges, we describe some of the key technologies in ICECap, including ML replacements for multiphysics packages, tools for human-machine teaming, and algorithms for multifidelity design optimization under uncertainty. As a test of our prototype pre-El Capitan system, we advance the state-of-the art for ICF hohlraum design by demonstrating the optimization of a 17-parameter National Ignition Facility experiment and show that our ML-assisted workflow makes design choices that are consistent with physics intuition, but in an automated, efficient, and mathematically rigorous fashion.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Minimum feature size control in level set topology optimization via density fields

A level set topology optimization approach that uses an auxiliary density field to nucleate holes during the optimization process and achieves minimum feature size control in optimized designs is explored. The level set field determines the solid-void interface and the density field describes the distribution of a fictitious porous material using the solid isotropic material with penalization. These fields are governed by two sets of independent optimization variables which are initially coupled using a penalty for hole nucleation. The strength of the density field penalization and projection is gradually increased during the optimization process to promote a 0-1 density distribution. In addition, a second penalty regulates the evolution of the density field in the void phase. The treatment of the density field combined with the second penalty mitigate the appearance of small design features. The minimum feature size of optimized designs is controlled by the radius of the linear filter applied to the density optimization variables. The structural response is predicted by the extended finite element method, the sensitivities by the adjoint method, and the optimization variables are updated by a gradient-based optimization algorithm. Numerical examples investigate the robustness of this approach with respect to algorithmic parameters and mesh refinement. The results show the applicability of the combined density level set topology optimization approach for both optimal hole nucleation and for minimum feature size control in 2D and 3D. This comes, however, at the cost of a more complex problem formulation and additional computational cost due to an increased number of optimization variables.

42 ENGINEERING↗
DOE OSTI2022

Comparison of CCM- and CRM-Based Boost Parallel Active Power Decoupler for PV Microinverter

Single-phase inverter or rectifier systems often make use of an active power decoupler (APD) to balance the mismatch between constant dc power and fluctuating ac power. This article deals with the comparison of continuous conduction mode (CCM) and critical conduction mode (CRM) operation-based design of a parallel boost-type APD for photovoltaic microinverter applications. From a design perspective, multiobjective analysis of efficiency, volume, and cost is explored within a decision space including planar inductors, gallium nitride based devices, film capacitors, switching frequency, and modulation (CCM vs. CRM). The theoretical study analyzes all possible design configurations within CCM and CRM and identifies Pareto-optimal designs, from which the selected CRM design can achieve reduced system volume and lower cost with the use of smaller inductor core, while operating with similar California Energy Commission efficiency drop as the selected CCM design. From a control perspective, a pulsewidth modulation based control strategy is proposed to implement closed-loop CRM modulation that does not rely on zero-crossing detection. Furthermore, closed-loop systems are designed for the optimal CCM and CRM realizations, and the final system characteristics are compared. Experimental results, obtained using two separate 40-V, 400-W hardware prototypes for CCM and CRM, are presented to verify the analyses.

42 ENGINEERING↗
NASA NTRS2019

Materials and Processes for New Propulsion Systems with Reduced Environmental Impact

Aeronautics research at NASA Glenn Research Center includes development, characterization and modeling of high temperature, lightweight materials and fabrication processes for aircraft propulsion systems with increased efficiency and reduced emissions, fuel burn and noise. Current propulsion materials research includes Ceramic Matrix Composites and Environmental Barrier Coatings, Polymer Matrix Composites and Additive Manufacturing processes. This presentation will summarize recent progress and plans in these areas. Ceramic Matrix Composites for Turbine Components: As part of NASA's Aeronautics research, Glenn Research Center has developed Ceramic Matrix Composites for 2700 degrees Fahrenheit turbine engine applications in the next generation of ultra-efficient aircraft. In this presentation, the development of advanced fiber and matrix constituents that enabled this advancement will be reviewed, and characterization of the resulting improvements in mechanical properties and durability will be summarized. Progress toward the development and validation of models predicting the effects of the engine environment on durability of Ceramic Matrix Composites and Environmental Barrier Coatings will be summarized. Progress and plans for collaborative research with industry and other government agencies will be reviewed. Polymer Matrix Composites for Powertrain and Impact Protection: A lightweight, hybrid polymer matrix composite/steel gear concept for rotorcraft power transmission applications was evaluated at realistic speed, torque, and power conditions. Dynamic testing was performed at 5000 horsepower and 5400 revolutions per minute with no performance degradation. Test results demonstrated the potential of hybrid composite / metal gears to reduce gear weight by approximately 15 percent, enabling the implementation of multi-speed drive systems, which would otherwise have a weight penalty, for increased speed and efficiency. Results of post-test inspection and endurance tests will be presented. Separately, ballistic impact tests demonstrated improved damage tolerance in polymer matrix composites by incorporating lightweight, thermoplastic veil materials between selected composite plies during the composite fabrication process. Results of impact tests and post-test inspection will be presented. Additive Manufacturing for Electric Propulsion: Additive Manufacturing processes offer the potential to fabricate new, high power density electric motor designs with complex geometries, multi-material components and optimally designed components that would not be feasible with traditional manufacturing processes. High performance stator components using advanced 3-phase conductive coils were fabricated using direct printing with optimized silver pastes. Additional additive manufacturing methods are being used to fabricate rotors and motor housing components. Systems studies show that the higher performance and lower weight motors offer improved energy efficiency and reduced emissions. Improvements to motor performance resulting from optimized materials and component designs will be presented.

Additive Manufacturing↗
DOE OSTI2022

Design of a Multi-Monochromatic X-ray Imager (MMI) for Kr K-shell line emission

We report the Multi-Monochromatic X-ray Imager (MMI) is a time-gated spectrometer used in implosion experiments at the OMEGA laser facility. From the data, electron temperature and density spatial distributions can be obtained at different implosion times. Previous MMI designs used Ar K-shell emission (3–6 keV) as a spectroscopic tracer and provided a spectral resolution of around 20 eV. However, Ar K-shell line emission becomes less useful at electron temperatures above 2 keV due to over-ionization. Kr K-shell (12–16 keV) has been shown to be an attractive alternative to diagnose hot implosion cores in recent publications. The purpose of this paper is to show a new point design that allows the MMI to detect this higher photon energy range with suitable spectral resolution. The algorithm used to find the optimal design couples a ray-tracing code and an exhaustive parameter space search. This algorithm may be useful as a tool to find optimal MMI designs for other purposes, i.e., other spectral regions for other spectroscopic tracers. So, the main change between the two designs is the replacement of the multi-layer mirror with a flat Bragg Ge (220) crystal. The final Kr K-shell MMI design has a photon energy range from 12 to 16.1 keV.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

MISPR : an open-source package for high-throughput multiscale molecular simulations

Computational tools provide a unique opportunity to study and design optimal materials by enhancing our ability to comprehend the connections between their atomistic structure and functional properties. However, designing materials with tailored functionalities is complicated due to the necessity to integrate various computational-chemistry software (not necessarily compatible with one another), the heterogeneous nature of the generated data, and the need to explore vast chemical and parameter spaces. The latter is especially important to avoid bias in scattered data points-based models and derive statistical trends only accessible by systematic datasets. Here, we introduce a robust high-throughput multi-scale computational infrastructure coined MISPR (Materials Informatics for Structure–Property Relationships) that seamlessly integrates classical molecular dynamics (MD) simulations with density functional theory (DFT). By enabling high-performance data analytics and coupling between different methods and scales, MISPR addresses critical challenges arising from the needs of automated workflow management and data provenance recording. The major features of MISPR include automated DFT and MD simulations, error handling, derivation of molecular and ensemble properties, and creation of output databases that organize results from individual calculations to enable reproducibility and transparency. In this work, we describe fully automated DFT workflows implemented in MISPR to compute various properties such as nuclear magnetic resonance chemical shift, binding energy, bond dissociation energy, and redox potential with support for multiple methods such as electron transfer and proton-coupled electron transfer reactions. The infrastructure also enables the characterization of large-scale ensemble properties by providing MD workflows that calculate a wide range of structural and dynamical properties in liquid solutions. MISPR employs the methodologies of materials informatics to facilitate understanding and prediction of phenomenological structure–property relationships, which are crucial to designing novel optimal materials for numerous scientific applications and engineering technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Machine Learning Software for Cylindrical Battery Design and Performance Prediction

A software that delivers optimal design parameters and performance predictions for cylindrical cells, which can range in size from micro batteries to EV batteries, is developed. The Cylindrical battery design V1.0 is comprised of three types of cylindrical batteries, Micro battery (Primary), Micro battery (Secondary) and 18650/21700/xxxxx cylindrical battery. The software was developed in MATLAB. The software has the capability to output the cell design with the capacity ranges from several mAh to several million Ah. The software utilizes machine learning and includes a graphical user interface to enable rapid prototyping to accelerate energy storage research, development, and manufacturing.

25 ENERGY STORAGE↗