Results for “modal model” — Page 74

NASA NTRS2007

Quiet Spike Build-Up Ground Vibration Testing Approach

NASA's Dryden Flight Research Center uses a modified F-15B (836) aircraft as a testbed for a variety of flight research:experiments mounted underneath the aircraft fuselage. The F-15B was selected to fly Gulfstream Aerospace Corporation's (GAC)QuietSpike(TM)(QS) project; however, this experiment is very unique and unlike any of the previous testbed experiments flown on the F-15B. It involves the addition of a relatively long quiet spike boom attached to the radar bulkhead of the aircraft. This QS experiment is a stepping stone to airframe structural morphing technologies designed to mitigate sonic born strength of business jets over land. The QS boom is a concept in Which an aircraft's front-end would be extended prior to supersonic acceleration. This morphing would effectively lengthen the aircraft, reducing peak sonic boom amplitude, but is also expected to partition the otherwise strong bow shock into a series of reduced-strength, non-coalescing shocklets. Prior to flying the Quietspike(TM) experiment on the F-15B aircraft several ground vibration tests (GVT) were required in order to understand the QS modal characteristics and coupling effects with the F-15B. However, due to the project's late hardware delivery of the QS and the intense schedule, a "traditional" GVT of the mated F-1513 Quietspike(tm) ready-for-flight configuration would not have left sufficient time available for the finite element model update and flutter analyses before flight testing. Therefore, a "nontraditional" ground vibration testing approach was taken. The objective of the QuietSpike (TM) build-up ground testing approach was to ultimately obtain confidence in the F-15B Quietspike(TM) finite element model (FEM) to be used for the flutter analysis. In order to obtain the F15B QS FEM with reliable foundation stiffness between the QS and the F-15B radar bulkhead as well as QS modal characteristics, several different GVT configurations were performed. EAch of the four GVT's performed had a specific objective. The overall intent was to provide adequate data which would replicate a "traditional" F-15B QS GVT with actual ready-for-flight hardware. NASA Dryden was tasked with the conduct of the 1st, 2nd and 4th GVT and the 3rd GVT was GAC's responsibility. In order for this build-up GVT approach to be feasible, it was absolutely critical that each GVT configuration matched as closely as possible the connection interface configuration between the and aircraft bulkhead.

Spivey, Natalie D.↗

NASA NTRS2001

Dynamic Analysis of a Building Under Rocket Engine Plume Acoustic Load

Studies have been performed to develop finite-element modeling and simulation techniques to predict the dynamic structural response of Building 4010 to the acoustic load from the plume of high-thrust rocket motors. The building is the Test Control Center and general office space for the E-complex at Stennis Space Center. It is a large single span; light-structured building located approximately 1,000 feet from the E-1 test stand. A three-dimensional shell/beam combined model of the building was built using Pro/Engineer platform and imported into Pro/Mechanica for analysis. An Equivalent Shell technique was developed to simplify the highly complex building structure so that the calculation is more efficient and accurate. A deterministic approach was used for the dynamic analysis. A pre-stressed modal analysis was performed to simulate the weight stiffening of the structure, through which about 200 modes ranging from 0 to 35 Hz were identified. In an initial dynamic frequency analysis, the maximum response over the model was found. Then the complete 3-D distributions of the displacement, as well as the stresses, were calculated through a final frequency analysis. The results were compared to a strain gage and accelerometer recordings from rocket engine tests and showed reasonable agreement.

Qian, Z.↗

DOE OSTI2022

Dynamics retrieval from stochastically weighted incomplete data by low-pass spectral analysis

Time-resolved serial femtosecond crystallography (TR-SFX) provides access to protein dynamics on sub-picosecond timescales, and with atomic resolution. Due to the nature of the experiment, these datasets are often highly incomplete and the measured diffracted intensities are affected by partiality. To tackle these issues, one established procedure is that of splitting the data into time bins, and averaging the multiple measurements of equivalent reflections within each bin. This binning and averaging often involve a loss of information. Here, we propose an alternative approach, which we call low-pass spectral analysis (LPSA). In this method, the data are projected onto the subspace defined by a set of trigonometric functions, with frequencies up to a certain cutoff. This approach attenuates undesirable high-frequency features and facilitates retrieving the underlying dynamics. A time-lagged embedding step can be included prior to subspace projection to improve the stability of the results with respect to the parameters involved. Subsequent modal decomposition allows to produce a low-rank description of the system's evolution. Using a synthetic time-evolving model with incomplete and partial observations, we analyze the LPSA results in terms of quality of the retrieved signal, as a function of the parameters involved. We compare the performance of LPSA to that of a range of other sophisticated data analysis techniques. We show that LPSA allows to achieve excellent dynamics reconstruction at modest computational cost. Finally, we demonstrate the superiority of dynamics retrieval by LPSA compared to time binning and merging, which is, to date, the most commonly used method to extract dynamical information from TR-SFX data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Development of Multimodal Few-Shot Analytics for Electron Micrographs

Recent advances in materials data analytics have provided new avenues for determining process-structure-property (PSP) linkages in a variety of materials. Machine learning techniques including few-shot learning have increased the efficiency of classifying microscopy images for the purposes of material characterization. Attempts at creating a multimodal approach can provide further improvements to current models and help extract more salient features from data. In this vein, raw spectrum data was taken to provide an additional modality to our current pyCHIP classifier. Modifications in segmentation also show potential in improving the accuracy of the pyCHIP classifier. Classifier output was analyzed using network graphs and unsupervised clustering algorithms such as spectral clustering to detect better segmentation methods than the current “chipping” approach. We suggest that the chip selection process can be automated in the future using a combination of these techniques to enable high-throughput analyses.

36 MATERIALS SCIENCE↗

NASA NTRS1972

Dynamic analysis for shuttle design verification

Two approaches that are used for determining the modes and frequencies of space shuttle structures are discussed. The first method, direct numerical analysis, involves finite element mathematical modeling of the space shuttle structure in order to use computer programs for dynamic structural analysis. The second method utilizes modal-coupling techniques of experimental verification made by vibrating only spacecraft components and by deducing modes and frequencies of the complete vehicle from results obtained in the component tests.

Fralich, R. W.↗

NASA NTRS1985

Dynamic Identification for Control of Large Space Structures

This is a compilation of reports by the one author on one subject. It consists of the following five journal articles: (1) A Parametric Study of the Ibrahim Time Domain Modal Identification Algorithm; (2) Large Modal Survey Testing Using the Ibrahim Time Domain Identification Technique; (3) Computation of Normal Modes from Identified Complex Modes; (4) Dynamic Modeling of Structural from Measured Complex Modes; and (5) Time Domain Quasi-Linear Identification of Nonlinear Dynamic Systems.

Ibrahim, S. R.↗

NASA NTRS1990

Multi-disciplinary optimization of aeroservoelastic systems

Efficient analytical and computational tools for simultaneous optimal design of the structural and control components of aeroservoelastic systems are presented. The optimization objective is to achieve aircraft performance requirements and sufficient flutter and control stability margins with a minimal weight penalty and without violating the design constraints. Analytical sensitivity derivatives facilitate an efficient optimization process which allows a relatively large number of design variables. Standard finite element and unsteady aerodynamic routines are used to construct a modal data base. Minimum State aerodynamic approximations and dynamic residualization methods are used to construct a high accuracy, low order aeroservoelastic model. Sensitivity derivatives of flutter dynamic pressure, control stability margins and control effectiveness with respect to structural and control design variables are presented. The performance requirements are utilized by equality constraints which affect the sensitivity derivatives. A gradient-based optimization algorithm is used to minimize an overall cost function. A realistic numerical example of a composite wing with four controls is used to demonstrate the modeling technique, the optimization process, and their accuracy and efficiency.

Karpel, Mordechay↗

NASA NTRS1992

Research Studies on Advanced Optical Module/Head Designs for Optical Data Storage

Preprints are presented from the recent 1992 Optical Data Storage meeting in San Jose. The papers are divided into the following topical areas: Magneto-optical media (Modeling/design and fabrication/characterization/testing); Optical heads (holographic optical elements); and Optical heads (integrated optics). Some representative titles are as follow: Diffraction analysis and evaluation of several focus and track error detection schemes for magneto-optical disk systems; Proposal for massively parallel data storage system; Transfer function characteristics of super resolving systems; Modeling and measurement of a micro-optic beam deflector; Oxidation processes in magneto-optic and related materials; and A modal analysis of lamellar diffraction gratings in conical mountings.

Source record↗

NASA NTRS1988

Eigenvalue/Eigenvector derivatives for SAVI Gimbalflex nonlinear transient response analysis

An eigenvector expansion method is utilized to predict eigenvalue and eigenvector derivatives due to geometric reconfiguration of a Gimbalflex fine-pointing/vibration isolation system called SAVI (Space Active Vibration Isolation). The eigenvector expansion method used is a modification of the classical method and allows for rigid body roots. Using the resulting modal derivatives, free-free nonlinear equations of motion are developed with Lagrange's Method. These equations represent a nonlinear plant model to be used in conjunction with a control system transient response simulation.

Orr, M. F., Jr.↗

NASA NTRS1994

Ground vibration test of the XV-15 Tiltrotor Research Aircraft and pretest predictions

The first comprehensive ground vibration survey was performed on the XV-15 Tiltrotor Research Aircraft to measure the vibration modes of the airframe and to provide data critical for determining whirl flutter stability margins. The aircraft was suspended by the wings with bungee cords and cables. A NASTRAN finite element model was used in the design of the suspension system to minimize its interference with the wing modes. The primary objective of the test was to measure the dynamic characteristics of the wings and pylons for aeroelastic stability analysis. In addition, over 130 accelerometers were placed on the airframe to characterize the fuselage, wing, and tail vibration. Pretest predictions were made with the NASTRAN model as well as correlations with the test data. The results showed that the suspension system provided the isolation necessary for modal measurements.

Studebaker, Karen↗

NASA NTRS1997

TBIEM3D: A Computer Program for Predicting Ducted Fan Engine Noise

This document describes the usage of the ducted fan noise prediction program TBIEM3D (Thin duct - Boundary Integral Equation Method - 3 Dimensional). A scattering approach is adopted in which the acoustic pressure field is split into known incident and unknown scattered parts. The scattering of fan-generated noise by a finite length circular cylinder in a uniform flow field is considered. The fan noise is modeled by a collection of spinning point thrust dipoles. The program, based on a Boundary Integral Equation Method (BIEM), calculates circumferential modal coefficients of the acoustic pressure at user-specified field locations. The duct interior can be of the hard wall type or lined. The duct liner is axisymmetric, locally reactive, and can be uniform or axially segmented. TBIEM3D is written in the FORTRAN programming language. Input to TBIEM3D is minimal and consists of geometric and kinematic parameters. Discretization and numerical parameters are determined automatically by the code. Several examples are presented to demonstrate TBIEM3D capabilities.

Dunn, M. H.↗

NASA NTRS2001

Cross-Correlation Analysis of UV Profile Variations and Nonradial Pulsations in Be Stars

This study is an investigation of the role of photospheric nonradial pulsations in the mass loss processes of Be stars. Some 18 Be stars were the focus of intensive, multi-wavelength campaigns between 1985 and 1996 with the NASA/ESA International Ultraviolet Explorer Satellite (IUE) . The campaigns were designed to monitor variations in the UV flux and stellar wind lines with near simultaneous, high signal-to-noise, optical spectroscopy of photospheric lines. The high quality, ground-based spectra were required to record the subtle, blue-to-red moving bump patterns in spectral line profiles that result from nonradial pulsations. We found that the same fine variations in the UV photospheric lines can be extracted from noisy IUE spectra by cross-correlating each target spectrum with a narrow-lined standard spectrum. Time series analyses of the cross-correlation functions then reveal the periodic signals, amplitudes, phases, and modal identifications of the pulsations. Our goals are to compare such results from UV and optical time series in order to model the stellar photospheric temperature and velocity fluctuations, and to search for correlated UV wind line variations to determine whether there is a connection between pulsation and mass loss.

Gies, Douglas R.↗

NASA NTRS2004

Parametric Studies of Square Solar Sails Using Finite Element Analysis

Parametric studies are performed on two generic square solar sail designs to identify parameters of interest. The studies are performed on systems-level models of full-scale solar sails, and include geometric nonlinearity and inertia relief, and use a Newton-Raphson scheme to apply sail pre-tensioning and solar pressure. Computational strategies and difficulties encountered during the analyses are also addressed. The purpose of this paper is not to compare the benefits of one sail design over the other. Instead, the results of the parametric studies may be used to identify general response trends, and areas of potential nonlinear structural interactions for future studies. The effects of sail size, sail membrane pre-stress, sail membrane thickness, and boom stiffness on the sail membrane and boom deformations, boom loads, and vibration frequencies are studied. Over the range of parameters studied, the maximum sail deflection and boom deformations are a nonlinear function of the sail properties. In general, the vibration frequencies and modes are closely spaced. For some vibration mode shapes, local deformation patterns that dominate the response are identified. These localized patterns are attributed to the presence of negative stresses in the sail membrane that are artifacts of the assumption of ignoring the effects of wrinkling in the modeling process, and are not believed to be physically meaningful. Over the range of parameters studied, several regions of potential nonlinear modal interaction are identified.

Sleight, David W.↗

NASA NTRS2017

Advanced Characterisation of Aerosol Size Properties from Measurements of Spectral Optical Depth Using the GRASP Algorithm

This study evaluates the potential of using aerosol optical depth (τ (sub a)) measurements to characterise the microphysical and optical properties of atmospheric aerosols. With this aim, we used the recently developed GRASP (Generalized Retrieval of Aerosol and Surface Properties) code for numerical testing of six different aerosol models with different aerosol loads. The direct numerical simulations (self-consistency tests) indicate that the GRASP-AOD retrieval provides modal aerosol optical depths (fine and coarse) to within 0.01 of the input values. The retrieval of the fine-mode radius, width and volume concentration are stable and precise if the real part of the refractive index is known. The coarse-mode properties are less accurate, but they are significantly improved when additional a priori information is available. The tests with random simulated errors show that the uncertainty in the bimodal log-normal size distribution parameters increases as the aerosol load decreases. Similarly, the reduction in the spectral range diminishes the stability of the retrieved parameters. In addition to these numerical studies, we used optical depth observations at eight AERONET locations to validate our results with the standard AERONET inversion products. We found that bimodal log-normal size distributions serve as useful input assumptions, especially when the measurements have inadequate spectral coverage and/or limited accuracy, such as moon photometry. Comparisons of the mode median radii between GRASP-AOD and AERONET indicate average differences of 0.013µm for the fine mode and typical values of 0.2–0.3µm for the coarse mode. The dominant mode (i.e. fine or coarse) indicates a 10 % difference in mode radii between the GRASP-AOD and AERONET inversions, and the average of the difference in volume concentration is around 17 % for both modes. The retrieved values of the fine-mode τ(sub a)(500) using GRASP-AOD are generally between those values obtained by the standard AERONET inversion and the values obtained by the AERONET spectral deconvolution algorithm (SDA), with differences typically lower than 0.02 between GRASP-AOD and both algorithms. Finally, we present some examples of application of GRASP-AOD inversion using moon photometry and the airborne PLASMA sun photometer during the ChArMEx summer 2013 campaign in the western Mediterranean.

Torres, Benjamin↗

NASA NTRSDate not supplied

Earth Independent Medical Operations (EIMO) Datascope: Challenges and Potential Solutions

Data flows and storage/retrieval capacity are severely constrained during missions in space and challenges will become even greater during exploration class missions. There is a need for an artificial intelligence (AI)-based clinical decision support system (CDSS) to monitor and analyze data to provide real-time consultative support for crew medical officer (CMO) decision-making. EIMO is defined as the gradual transition of medical care and decision making from terrestrial to space-based assets, enabling support of astronaut health and performance and reducing overall mission risk. While a hallmark of this paradigm shift from low-earth orbit is that on-board care will increasingly become the responsibility of the astronauts for primary management and decision making, terrestrial assets will continue to be paramount in pre-mission screening and planning, as well as prevention, health maintenance and long-term care contingencies. New capabilities and systems that enable progressively more robust and resilient systems and crews will be necessary to reduce risk and increase probability of deep space exploration mission success. An aspiration for EIMO is to develop AI-enhanced solutions for analysis of crew health & performance data and to facilitate clinical decision support for autonomous medical operations. A “system of systems” approach is envisioned whereby EIMO will deploy AI-supported natural language processing and machine learning (ML) techniques to utilize embedded reference databases and real-time data streams [input vectors] from multiple data sources. Constituent input vectors may include environmental controls, countermeasures data, behavioral data, physiologic wearables, point-of-care laboratory tests, personalized medical records, inventory trade space risk assessments, COTS medical databases, and ground support inputs. An ideal AI capability would possess trained fusion algorithms to cross reference input vectors with medical ‘knowledge’ [cultivated database] to stratify relevant data streams for predictive and actionable capabilities. In addition, EIMO will feature mobility, in that it can be accessed and can push/pull data within and between multiple vehicles/habitats. Large amounts and variable sources of data can be leveraged to diagnose, inform treatment strategies, and potentially predict medical events and performance decrements. Inclusion of advanced training tools using extended reality will enable increasingly autonomous medical care to aid a CMO when ground support is unavailable or time-delayed beyond required action window, e.g., emergent medical situations. EIMO CDSS would require very large datasets to train pre-flight and significant amounts of data are needed to support ML via in-flight CDSS operations. An additional challenge will be to find sufficient data to train a model relevant to astronaut demographics. The rapid, accelerating evolution of this field creates a propitious solution space to leverage multi-modal AI through public-private partnership(s). The status of multi-modal AI systems today would preclude their use for long duration missions as they remain unreliable and are subject to “digital hallucinations” and other errors that could pose operational risk. A federated labs structure is being considered to test and optimize data flow from the multiple input vectors leading to field testing in suitable ground/flight analogs. Critical to the success of an EIMO CDSS will be integration and interoperability and success will be defined by a system that can serve as an in-flight medical consult for the CMO providing critical support during medical contingencies. Benefits to terrestrial medicine may be significant as an outflow of the EIMO medical system, particularly for remote areas and communities lacking significant infrastructure, personnel and resources.

J Lemery↗

NASA NTRS2024

Earth Independent Medical Operations (EIMO) Datascope: Challenges and Potential Solutions

Data flows and storage/retrieval capacity are severely constrained during missions in space and challenges will become even greater during exploration class missions. There is a need for an artificial intelligence (AI)-based clinical decision support system (CDSS) to monitor and analyze data to provide real-time consultative support for crew medical officer (CMO) decision-making. EIMO is defined as the gradual transition of medical care and decision making from terrestrial to space-based assets, enabling support of astronaut health and performance and reducing overall mission risk. While a hallmark of this paradigm shift from low-earth orbit is that on-board care will increasingly become the responsibility of the astronauts for primary management and decision making, terrestrial assets will continue to be paramount in pre-mission screening and planning, as well as prevention, health maintenance and long-term care contingencies. New capabilities and systems that enable progressively more robust and resilient systems and crews will be necessary to reduce risk and increase probability of deep space exploration mission success. An aspiration for EIMO is to develop AI-enhanced solutions for analysis of crew health & performance data and to facilitate clinical decision support for autonomous medical operations. A “system of systems” approach is envisioned whereby EIMO will deploy AI-supported natural language processing and machine learning (ML) techniques to utilize embedded reference databases and real-time data streams [input vectors] from multiple data sources. Constituent input vectors may include environmental controls, countermeasures data, behavioral data, physiologic wearables, point-of-care laboratory tests, personalized medical records, inventory trade space risk assessments, COTS medical databases, and ground support inputs. An ideal AI capability would possess trained fusion algorithms to cross reference input vectors with medical ‘knowledge’ [cultivated database] to stratify relevant data streams for predictive and actionable capabilities. In addition, EIMO will feature mobility, in that it can be accessed and can push/pull data within and between multiple vehicles/habitats. Large amounts and variable sources of data can be leveraged to diagnose, inform treatment strategies, and potentially predict medical events and performance decrements. Inclusion of advanced training tools using extended reality will enable increasingly autonomous medical care to aid a CMO when ground support is unavailable or time-delayed beyond required action window, e.g., emergent medical situations. EIMO CDSS would require very large datasets to train pre-flight and significant amounts of data are needed to support ML via in-flight CDSS operations. An additional challenge will be to find sufficient data to train a model relevant to astronaut demographics. The rapid, accelerating evolution of this field creates a propitious solution space to leverage multi-modal AI through public-private partnership(s). The status of multi-modal AI systems today would preclude their use for long duration missions as they remain unreliable and are subject to “digital hallucinations” and other errors that could pose operational risk. A federated labs structure is being considered to test and optimize data flow from the multiple input vectors leading to field testing in suitable ground/flight analogs. Critical to the success of an EIMO CDSS will be integration and interoperability and success will be defined by a system that can serve as an in-flight medical consult for the CMO providing critical support during medical contingencies. Benefits to terrestrial medicine may be significant as an outflow of the EIMO medical system, particularly for remote areas and communities lacking significant infrastructure, personnel and resources.

Medical Operations↗

DOE OSTI2014

Dynamic behaviour of thin composite plates for different boundary conditions

In the context of composite materials technology, which is increasingly present in industry, this article covers a topic of great interest and theoretical and practical importance. Given the complex design of fiber-reinforced materials and their heterogeneous nature, mathematical modeling of the mechanical response under different external stresses is very difficult to address in the absence of simplifying assumptions. In most structural applications, composite structures can be idealized as beams, plates, or shells. The analysis is reduced from a three-dimensional elasticity problem to a oneor two-dimensional problem, based on certain simplifying assumptions that can be made because the structure is thin. This paper aims to validate a mathematical model illustrating how thin rectangular orthotropic plates respond to the actual load. Thus, from the theory of thin plates, new analytical solutions are proposed corresponding to orthotropic rectangular plates having different boundary conditions. The proposed analytical solutions are considered both for solving equation orthotropic rectangular plates and for modal analysis.

36 MATERIALS SCIENCE↗

DOE OSTI2014

WE-A-12A-01: Medical Physics 1.0 to 2.0, Session 2: Radiography, Mammography and Fluoroscopy

Medical Physics 2.0 is a bold vision for an existential transition of clinical imaging physics in face of the new realities of value-based and evidencebased medicine, comparative effectiveness, and meaningful use. It speaks to how clinical imaging physics can expand beyond traditional insular models of inspection and acceptance testing, oriented toward compliance, towards team-based models of operational engagement, prospective definition and assurance of effective use, and retrospective evaluation of clinical performance. Organized into four sessions of the AAPM, this particular session focuses on three specific modalities as outlined below. Radiography 2.0: The development of electronic capture in recent years has changed the landscape and spurred reinvestment by healthcare providers. The radiography presentation will explore how the diagnostic medical physicist must adapt to these changes to support radiographic imaging, and how she/he can add value in radiography practice over the next 5-10 years. Topics of discussion include new metrology of evaluation, new models of clinical engagement, and effective integration of new technologies. Mammography 2.0: Mammography has been an interesting testing ground on the effectiveness of close involvement of medical physicists with equipment in the past twenty years. The outcomes have clearly shown major improvements in image quality and significant reduction in the average glandular dose. However, the medical physicist's role in mammography has been largely focused to annual surveys and with limited input on operational issues with image artifacts, optimal mammographic acquisition mode and problems with image quality. This mammography presentation will address why and how medical physicists must be prepared to address the new models of practice that include new metrics of performance and the integration of new technologies (DBT, syncretized mammograms, contrast mammography, breast CT) into clinical practice. Fluoroscopy 2.0: Physics support of fluoroscopy should be operationally as opposed to compliance focused. Testing protocols must address new hardware, acquisition methods, and image processing. Future available tools are discussed. Proper configuration of acquisition parameters (focal spot size, voltage and added filter, tube current, pulse width, pulse rate, scatter removal) as a function of patient size from the neonate to bariatric patient is key to providing diagnostic image quality at properly managed radiation doses. Learning Objectives: Appreciate the limitations of the currently available tools and techniques in clinical medical physics in radiography, mammography, and fluoroscopy, and ways to improve upon current deficiencies. Appreciate the changing environment of imaging practice and the need for the medical physicist to be an expert consultant and educator in a capacity that extends beyond the annual survey of equipment. Understand the status of the rapidly changing environment in breast imaging from planar imaging to tomosynthesis and possibly to breast CT. Identify appropriate configuration of acquisition parameters as a function of patient size to manage radiation dose and ensure diagnostic image quality.

60 APPLIED LIFE SCIENCES↗