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At least 1,621 records · Page 90

Structural optimization of rotor blades with straight and swept tips subject to aeroelastic constraints

The main conclusions obtained in the present study are summarized. Their application to the structural optimization of a helicopter blade should be limited by the assumptions used in obtaining the numerical results presented here. The optimum design procedure described here is very efficient, and can produce improved designs with a very limited number of precise analyses. The method of constructing the approximate problem is such that previously conducted aeroelastic analyses can be reused in a new optimization problem. For example, if an optimization study is preceded by a parametric study in which the effect of various combinations of blade design parameters is examined, all the aeroelastic analyses performed for the parametric study can be reutilized in the optimization study. This is not possible when the approximate problem is built from Taylor series expansions. The results of the optimization are quite sensitive to the aeroelastic stability margins required of the blade. In the optimization of case 2, changing the aeroelastic stability constraints from simply requiring that the blade be stable in hover, to requiring that the stability margins be maintained during the course of the optimization, reduced the gains in n/rev vibration levels by more than 50 percent. The introduction of tip sweep can reduce the n/rev vertical hub shears beyond the level that can be obtained by just modifying the mass and stiffness distributions of the blade.

Friedmann, Peretz P.↗

Computation Of Flutter In Turbomachinery

"Direct" solution procedure supplants conventional eigenmode analysis. Iterative computational procedure yields critical mach number for onset of flutter and flutter angular frequency, of propfan, turbine with unshrouded blades, or other turbomachinery. Procedure applied to aeroelastic analysis of propfan, in which finite-element model of propfan structure combined with model of unsteady aerodynamics based on three-dimensional subsonic-lifting-surface theory. Particularly suitable for optimization in design because as optimal design evolves, flutter solution expected to change incrementally, so previous solution provides good estimates for start of current solution.

Murthy, Durbha V.↗

Microsandwich cellular solids

This article introduces a new concept of microsandwiching in which the cell wall itself is a sandwich structure and is substantially stiffer. Some experimental results are presented to show the efficacy of this approach. A method for optimizing the design of honeycomb microsandwich is also briefly outlined.

Balakrishna Bhat, T.↗

Thermal/structural Tailoring of Engine Blades (T/STAEBL) User's Manual

The Thermal/Structural Tailoring of Engine Blades (T/STAEBL) system is a family of computer programs executed by a control program. The T/STAEBL system performs design optimizations of cooled, hollow turbine blades and vanes. This manual contains an overview of the system, fundamentals of the data block structure, and detailed descriptions of the inputs required by the optimizer. Additionally, the thermal analysis input requirements are described as well as the inputs required to perform a finite element blade vibrations analysis.

Brown, K. W.↗

Near minimum-time maneuvers of the advanced space structures technology research experiment (ASTREX) test article: Theory and experiments

The Phillips Laboratory at the Edwards Air Force Base has developed the Advanced Space Structures Technology Research Experiment (ASTREX) facility to serve as a testbed for demonstrating the applicability of proven theories to the challenges of spacecraft maneuvers and structural control. This report describes the work performed on the ASTREX test article by Texas A&M University under contract NAS119373 as a part of the Control-Structure Interaction (CSI) Guest Investigator Program. The focus of this work is on maneuvering the ASTREX test article with compressed air thrusters that can be throttled, while attenuating structural excitation. The theoretical foundation for designing the near minimum-time thrust commands is based on the generation of smooth, parameterized optimal open-loop control profiles, and the determination of control laws for final position regulation and tracking using Lyapunov stability theory. Details of the theory, mathematical modeling, model updating, and compensation for the presence of 'real world' effects are described and the experimental results are presented. The results show an excellent match between theory and experiments.

Vadali, Srinivas R.↗

Risks and reliability of manufacturing processes as related to composite materials for spacecraft structures

Fabricating primary aircraft and spacecraft structures using advanced composite materials entail both benefits and risks. The benefits come from much improved strength-to-weight ratios and stiffness-to-weight ratios, potential for less part count, ability to tailor properties, chemical and solvent resistance, and superior thermal properties. On the other hand, the risks involved include high material costs, lack of processing experience, expensive labor, poor reproducibility, high toxicity for some composites, and a variety of space induced risks. The purpose of this project is to generate a manufacturing database for a selected number of materials with potential for space applications, and to rely on this database to develop quantitative approaches to screen candidate materials and processes for space applications on the basis of their manufacturing risks including costs. So far, the following materials have been included in the database: epoxies, polycyanates, bismalemides, PMR-15, polyphenylene sulfides, polyetherimides, polyetheretherketone, and aluminum lithium. The first four materials are thermoset composites; the next three are thermoplastic composites, and the last one is is a metal. The emphasis of this database is on factors affecting manufacturing such as cost of raw material, handling aspects which include working life and shelf life of resins, process temperature, chemical/solvent resistance, moisture resistance, damage tolerance, toxicity, outgassing, thermal cycling, and void content, nature or type of process, associate tooling, and in-process quality assurance. Based on industry experience and published literature, a relative ranking was established for each of the factors affecting manufacturing as listed above. Potential applications of this database include the determination of a delta cost factor for specific structures with a given process plan and a general methodology to screen materials and processes for incorporation into the current conceptual design optimization of future spacecrafts as being coordinated by the Vehicle Analysis Branch where this research is being conducted.

Bao, Han P.↗

Wing Weight Optimization Under Aeroelastic Loads Subject to Stress Constraints

A minimum weight optimization of the wing under aeroelastic loads subject to stress constraints is carried out. The loads for the optimization are based on aeroelastic trim. The design variables are the thickness of the wing skins and planform variables. The composite plate structural model incorporates first-order shear deformation theory, the wing deflections are expressed using Chebyshev polynomials and a Rayleigh-Ritz procedure is adopted for the structural formulation. The aerodynamic pressures provided by the aerodynamic code at a discrete number of grid points is represented as a bilinear distribution on the composite plate code to solve for the deflections and stresses in the wing. The lifting-surface aerodynamic code FAST is presently being used to generate the pressure distribution over the wing. The envisioned ENSAERO/Plate is an aeroelastic analysis code which combines ENSAERO version 3.0 (for analysis of wing-body configurations) with the composite plate code.

Kapania, Rakesh K.↗

Efficient Evaluation and Optimization of Structural Reliability

Use of approximations for calculating the structural failure probability under uncertainties is a necessary aspect. But efficient use of suitable approximations at different stages of reliability prediction and design makes this valuable tool practical for many large scale structures. This research addresses the modern approximation concepts and their utility in structural reliability estimation. Emphasis is placed on building higher order approximations using intervening variables to closely represent the nonlinear limit state functions. Several test problems with highly nonlinear performance functions are used to demonstrate the accuracy of the proposed method. Many of the structural problems are modeled and simulated using the finite element methods (FEM) for obtaining a detailed structural response. FEM is a computationally intensive numerical procedure with a large number of degrees of freedom. With an increase in the complexity of the structural model and the multidisciplinary nature of analyses, the number of limit states and their computation increases very significantly. The requirement of frequent repetitive analysis of the structure hinders the utility of any tool and discourages that approach from being used. One particular tool which faces this difficulty is the computation of the structural reliability under parametric uncertainties.

Grandhi, Ramana V.↗

Establishing and Maintaining the Digital Thread of Additively Manufactured Materials and Applications

Additive Manufacturing (AM) and Integrated Computational Materials Engineering (ICME) are complementary enabling technologies for design and manufacturing of “fit-for-purpose” materials. Both technologies will impact rapid material design, reduction in cost- and time-to-market for new applications, and discovery and implementation of new materials. An ICME approach to design, however, requires experimentally validated material models at multiple length and time scales, an integrated framework that can connect analysis tools with one another to ensure the digital thread of an application is maintained, and the manufacturing (e.g., AM) capability to leverage processing-structure-property-performance (PSPP) relationships to achieve spatially varying material properties where desired. AM enables the implementation of the design of an optimized, spatially varying microstructure through careful selection of the processing parameters used during an additively manufactured build. In order to establish these PSPP relations, a large amount of data is necessary, and that data must be properly captured, analyzed and maintained in an information management system that can establish the required traceability between various aspects of the design process to ensure an application’s digital thread is maintained (from design to end of life). Such an information management system must be able to capture feedstock material pedigree, resulting microstructure from various build parameters, subsequent mechanical properties derived from testing, developed material models, and enable spatial variations in material assignment in an engineering application. Furthermore, the information management system should be easily integrated with traditionally engineered materials in a single, centralized platform to enable an ICME optimization tool to explore both types of manufacturing processes. At NASA GRC, a robust, 21st century materials information management system has been previously developed with a focus towards enabling ICME. In this work, GRC’s ICME schema is extended to accommodate additively manufactured materials, enabling storage of both traditionally and additively manufactured materials in the same construct. The methodology for properly capturing additively manufactured materials across the entire material lifecycle is presented, following the previously established database best practices, as a potential framework for establishing PSPP relationships for additively manufactured materials and applying them to engineering applications.

Data management↗

Machine Learning for Advanced Building Construction: Preprint

High-efficiency retrofits can play a key role in reducing carbon emissions associated with buildings if processes can be scaled-up to reduce cost, time, and disruption. Here we demonstrate an artificial intelligence/computer vision (AI/CV)- enabled framework for converting exterior build scans and dimensional data directly into manufacturing and installation specifications for overclad panels. In our workflow point clouds associated with LiDAR-scanned buildings are segmented into a facade feature space, vectorized features are extracted using an iterative random-sampling consensus algorithm, and from this representation an optimal panel design plan satisfying manufacturing constraints is generated. This system and the corresponding construction process is demonstrated on a test facade structure constructed at the National Renewable Energy Laboratory (NREL). We also include a brief summary of a techno-economic study designed to estimate the potential energy and cost impact of this new system.

building retrofits↗

Machine Learning for Advanced Building Construction

High-efficiency retrofits can play a key role in reducing carbon emissions associated with buildings if processes can be scaled-up to reduce cost, time, and disruption. Here we demonstrate an artificial intelligence/computer vision (AI/CV)-enabled framework for converting exterior build scans and dimensional data directly into manufacturing and installation specifications for overclad panels. In our workflow point clouds associated with LiDAR-scanned buildings are segmented into a facade feature space, vectorized features are extracted using an iterative random-sampling consensus algorithm, and from this representation an optimal panel design plan satisfying manufacturing constraints is generated. This system and the corresponding construction process is demonstrated on a test facade structure constructed at the National Renewable Energy Laboratory (NREL). We also include a brief summary of a techno-economic study designed to estimate the potential energy and cost impact of this new system.

build scans↗

Digital robust active control law synthesis for large order flexible structure using parameter optimization

A generic procedure for the parameter optimization of a digital control law for a large-order flexible flight vehicle or large space structure modeled as a sampled data system is presented. A linear quadratic Guassian type cost function was minimized, while satisfying a set of constraints on the steady-state rms values of selected design responses, using a constrained optimization technique to meet multiple design requirements. Analytical expressions for the gradients of the cost function and the design constraints on mean square responses with respect to the control law design variables are presented.

Mukhopadhyay, V.↗

Active Learning Guided Computational Discovery of Plant-Based Redoxmers for Organic Nonaqueous Redox Flow Batteries

Organic nonaqueous redox flow batteries (ONRFBs) are promising energy storage devices due to their scalability and reliance on sourceable materials. However, finding suitable redox-active organic molecules (redoxmers) for these batteries remains a challenge. Using plant-based compounds as precursors for these redoxmers can decrease their costs and environmental toxicity. In this computational study, flavonoid molecules have been examined as potential redoxmers for ONRFBs. Flavone and isoflavone derivatives were selected as catholyte (positive charge carrier) and anolyte (negative charge carrier) molecules, respectively. To drive their redox potentials to the opposite extremes, in silico derivatization was performed using a novel algorithm to generate a library of > 40000 candidate molecules that penalizes overly complex structures. A multiobjective Bayesian optimization based active learning algorithm was then used to identify best redoxmer candidates in these search spaces. Furthermore, our study provides methodologies for molecular design and optimization of natural scaffolds and highlights the need of incorporating expert chemistry awareness of the natural products and the basic rules of synthetic chemistry in machine learning.

25 ENERGY STORAGE↗

Acoustic design considerations: Review of rotor acoustic sources

It is not sufficient to optimize a rotor design in terms of a single noise level calculated for a single flight condition and a single measurement location. The various noise sources, their frequency content, amplitude, and directivity as a function of operating condition must be considered. A summary of the frequency ranges, directivity patterns and the most important operational and design parameters for major rotor noise sources is presented. It is difficult to generalize design requirements for rotor noise because the acoustic output varies so widely depending on the noise source, flight condition, measurement location, and frequency range. However, assuming the rotor must lift a fixed nominal payload and operate over a wide range of flight conditions, three general design guidelines can be stated: (1) minimize tip Mach number; (2) minimize blade thickness in the tip region; and (3) minimize gradients in the spanwise lift distribution in the tip region. Constraints on blade thickness, maximum values for hover tip Mach number, advancing tip Mach number and spanwise lift coefficient gradient will be specified during the aerodynamic, dynamic and structural optimization process. The rotor noise sources to be considered include the low frequency loading and thickness noise, and the higher frequency noise due to blade-vortex interactions (BVI). The analyses to be employed will include the comprehensive rotor analysis and design program CAMRAD and the rotor noise prediction program WOPWOP.

Martin, Ruth M.↗

Optimal sensor placement for reconstructing wind pressure field around buildings using compressed sensing

Deciding how to optimally deploy sensors in a large, complex, and spatially extended structure is critical to ensure that the surface pressure field is accurately captured for subsequent analysis and design. In some cases, reconstruction of missing data is required in downstream tasks such as the development of digital twins. Here, this paper presents a data-driven sparse sensor selection algorithm, aiming to provide the most information contents for reconstructing aerodynamic characteristics of wind pressures over tall building structures parsimoniously. The algorithm first fits a set of basis functions to the training data, then applies a computationally efficient QR algorithm that ranks existing pressure sensors in order of importance based on the state reconstruction to this tailored basis. The findings of this study show that the proposed algorithm successfully re- constructs the aerodynamic characteristics of tall buildings from sparse measurement locations, generating stable and optimal solutions across a range of conditions. As a result, this study serves as a promising first step toward leveraging the success of data-driven and machine learning algorithms to supplement traditional genetic algorithms currently used in wind engineering.

42 ENGINEERING↗

Optimization of neutron chopper and optics for CENTAUR, the SANS/WANS diffractometer at the spallation neutron source second target station

Herein this report presents the physics design and optimization of the neutron chopper and optics systems for the CENTAUR instrument, a multifunctional small-angle and wide-angle neutron scattering diffractometer for the Spallation Neutron Source Second Target Station. This instrument will offer a wide range of capabilities, including small-angle neutron scattering with wide Q coverage (e.g., 0.001–20 Å –1 ), providing a tool to investigate structures from atomic to mesoscopic scales simultaneously. To efficiently transport desired neutrons from the compact high-brightness cold source, several innovative designs are utilized: a time-zero chopper with a straight guide system for short-wavelength neutrons, octagonal guides for higher flux, and a correlation chopper to reduce inelastic scattering. The optimization process considers factors such as useable time-integrated flux, instrument resolution, brilliance transfer, divergence, and acceptance diagram uniformity. The overall design prioritizes flexibility to accommodate diverse user requirements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

More Than 30 000-fold Field Enhancement of Terahertz Nanoresonators Enabled by Rapid Inverse Design

The rapid development of 6G communications using terahertz (THz) electromagnetic waves has created a demand for highly sensitive THz nanoresonators capable of detecting these waves. Among the potential candidates, THz nanogap loop arrays show promising characteristics but require significant computational resources for accurate simulation. This requirement arises because their unit cells are 10 times smaller than millimeter wavelengths, with nanogap regions that are 1 000 000 times smaller. To address this challenge, we propose a rapid inverse design method using physics-informed machine learning, employing double deep Q-learning with an analytical model of the THz nanogap loop array. In ~39 h on a middle-level personal computer, our approach identifies the optimal structure through 200 000 iterations, achieving an experimental electric field enhancement of 32 000 at 0.2 THz, 300% stronger than prior results. In conclusion, our analytical model-based approach significantly reduces the amount of computational resources required, offering a practical alternative to numerical simulation-based inverse design for THz nanodevices.

21 terahertz time-domain spectroscopy↗

Structure and epitope of a neutralizing monoclonal antibody that targets the stem helix of β coronaviruses

Monoclonal antibodies that retain neutralizing activity against multiple coronavirus (CoV) lineages and variants of concern (VoC) must be developed to protect against future pandemics. These broadly neutralizing MAbs (BNMAbs) may be used as therapeutics and/or to assist in the rational design of vaccines that induce BNMAbs. 1249A8 is a BNMAb that targets the stem helix (SH) region of CoV spike (S) protein and neutralizes Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) original strain, delta, and omicron VoC, Severe Acute Respiratory Syndrome CoV (SARS-CoV), and Middle East Respiratory Syndrome CoV (MERS-CoV). To understand its mechanism of action, the crystal structure of 1249A8 bound to a MERS-CoV SH peptide was determined at 2.1 Å resolution. BNMAb 1249A8 mimics the SARS-CoV-2 S loop residues 743–749, which interacts with the N-terminal end of the SH helix in the S post-fusion conformation. The conformation of 1249A8-bound SH is distinct from the SH conformation observed in the post-fusion SARS-CoV-2 S structure, suggesting 1249A8 disrupts the secondary structure and refolding events required for CoV post-fusion S to initiate membrane fusion and ultimately infection. This study provides novel insights into the neutralization mechanisms of SH-targeting CoV BNMAbs that may inform vaccine development and the design of optimal BNMAb therapeutics.

60 APPLIED LIFE SCIENCES↗