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At least 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Universality for quintessence

Several recent works suggested the possibility of describing inflation by means of a renormalization group equation. In this paper we discuss the application of these methods to models of quintessence. In this framework a period of exponential expansion corresponds to the slow evolution of the scalar field in the neighborhood of a fixed point. A minimal set of universality classes for models of quintessence is defined and the transition from a matter dominated to quintessence dominated universe is studied. Models in which quintessence is non-minimally coupled with gravity are also discussed. We show that the formalism proves to be extremely convenient to describe quintessence and moreover we find that in most of the models discussed in this work quintessence naturally takes over ordinary matter.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2013

Reduced discretization error in HZETRN

The deterministic particle transport code HZETRN is an efficient analysis tool for studying the effects of space radiation on humans, electronics, and shielding materials. In a previous work, numerical methods in the code were reviewed, and new methods were developed that further improved efficiency and reduced overall discretization error. It was also shown that the remaining discretization error could be attributed to low energy light ions (A < 4) with residual ranges smaller than the physical step-size taken by the code. Accurately resolving the spectrum of low energy light particles is important in assessing risk associated with astronaut radiation exposure. In this work, modifications to the light particle transport formalism are presented that accurately resolve the spectrum of low energy light ion target fragments. The modified formalism is shown to significantly reduce overall discretization error and allows a physical approximation to be removed. For typical step-sizes and energy grids used in HZETRN, discretization errors for the revised light particle transport algorithms are shown to be less than 4% for aluminum and water shielding thicknesses as large as 100 g/cm{sup 2} exposed to both solar particle event and galactic cosmic ray environments.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2025

Accelerated data-driven materials science with the Materials Project

The Materials Project was launched formally in 2011 to drive materials discovery forwards through high-throughput computation and open data. More than a decade later, the Materials Project has become an indispensable tool used by more than 600,000 materials researchers around the world. This Perspective describes how the Materials Project, as a data platform and a software ecosystem, has helped to shape research in data-driven materials science. We cover how sustainable software and computational methods have accelerated materials design while becoming more open source and collaborative in nature. Next, we present cases where the Materials Project was used to understand and discover functional materials. We then describe our efforts to meet the needs of an expanding user base, through technical infrastructure updates ranging from data architecture and cloud resources to interactive web applications. Finally, we discuss opportunities to better aid the research community, with the vision that more accessible and easy-to-understand materials data will result in democratized materials knowledge and an increasingly collaborative community.

Horton, Matthew K↗
DOE OSTI2012

Electric Dipole Transitions Within The Ab initio No-Core Shell Model With Continuum

The no-core shell model with continuum (NCSMC) offers a unified approach to nuclear bound and continuum states based on the coupling of the no-core shell model (NCSM), a bound-state tech nique, with the no-core shell model/resonating group method (NCSM/RGM), a nuclear scattering technique. This new ab initio method leads to convergence properties superior to either NCSM or NCSM/RGM while providing a balanced approach to different classes of states. The NCSMC many nucleon wave function contains: i) a pre-diagonalized A-nucleon NCSM component expanded in the harmonic oscillator basis; ii) a binary-cluster NCSM/RGM component with asymptotic boundary conditions that properly describe weakly bound states, resonances and scattering. Here, we review the main aspects of the NCSM formalism, and provide algebraic expression for the reduced matrix elements of the electric dipole operator, needed to calculate E1 transition probabilities, radiative captures and photodisintegration cross sections.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2014

Amorphous In–Ga–Zn–O thin-film transistor active pixel sensor x-ray imager for digital breast tomosynthesis

Purpose: The breast cancer detection rate for digital breast tomosynthesis (DBT) is limited by the x-ray image quality. The limiting Nyquist frequency for current DBT systems is around 5 lp/mm, while the fine image details contained in the high spatial frequency region (>5 lp/mm) are lost. Also today the tomosynthesis patient dose is high (0.67–3.52 mGy). To address current issues, in this paper, for the first time, a high-resolution low-dose organic photodetector/amorphous In–Ga–Zn–O thin-film transistor (a-IGZO TFT) active pixel sensor (APS) x-ray imager is proposed for next generation DBT systems. Methods: The indirect x-ray detector is based on a combination of a novel low-cost organic photodiode (OPD) and a cesium iodide-based (CsI:Tl) scintillator. The proposed APS x-ray imager overcomes the difficulty of weak signal detection, when small pixel size and low exposure conditions are used, by an on-pixel signal amplification with a significant charge gain. The electrical performance of a-IGZO TFT APS pixel circuit is investigated by SPICE simulation using modified Rensselaer Polytechnic Institute amorphous silicon (a-Si:H) TFT model. Finally, the noise, detective quantum efficiency (DQE), and resolvability of the complete system are modeled using the cascaded system formalism. Results: The result demonstrates that a large charge gain of 31–122 is achieved for the proposed high-mobility (5–20 cm{sup 2}/V s) amorphous metal-oxide TFT APS. The charge gain is sufficient to eliminate the TFT thermal noise, flicker noise as well as the external readout circuit noise. Moreover, the low TFT (<10{sup −13} A) and OPD (<10{sup −8} A/cm{sup 2}) leakage currents can further reduce the APS noise. Cascaded system analysis shows that the proposed APS imager with a 75 μm pixel pitch can effectively resolve the Nyquist frequency of 6.67 lp/mm, which can be further improved to ∼10 lp/mm if the pixel pitch is reduced to 50 μm. Moreover, the detector entrance exposure per projection can be reduced from 1 to 0.3 mR without a significant reduction of DQE. The signal-to-noise ratio of the a-IGZO APS imager under 0.3 mR x-ray exposure is comparable to that of a-Si:H passive pixel sensor imager under 1 mR, indicating good image quality under low dose. A threefold reduction of current tomosynthesis dose is expected if proposed technology is combined with an advanced DBT image reconstruction method. Conclusions: The proposed a-IGZO APS x-ray imager with a pixel pitch <75 μm is capable to achieve a high spatial frequency (>6.67 lp/mm) and a low dose (<0.4 mGy) in next generation DBT systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Magnetic Bloch theorem and reentrant flat bands in twisted bilayer graphene at 2 π flux

Bloch's theorem is the centerpiece of topological band theory, which itself has defined an era of quantum materials research. However, Bloch's theorem is broken by a perpendicular magnetic field, making it difficult to study topological systems in strong flux. For the first time, moiré materials have made this problem experimentally relevant, and its solution is the focus of this paper. We construct gauge-invariant irreps of the magnetic translation group at 2π flux on infinite boundary conditions, allowing us to give analytical expressions in terms of the Siegel theta function for the magnetic Bloch Hamiltonian, non-Abelian Wilson loop, and many-body form factors. We illustrate our formalism using a simple square lattice model and the Bistritzer-MacDonald Hamiltonian of twisted bilayer graphene, obtaining reentrant ground states at 2π flux under the Coulomb interaction.

2-dimensional systems↗
DOE OSTI2013

The topology and size of the universe from CMB temperature and polarization data

We analyze seven year and nine year WMAP temperature maps for signatures of three finite flat topologies M{sub 0} = T{sup 3}, M{sub 1} = T{sup 2} × R{sup 1}, and M{sub 2} = S{sup 1} × R{sup 2}. We use Monte-Carlo simulations with the Feldman-Cousins method to obtain confidence intervals for the size of the topologies considered. We analyze the V, W, and Q frequency bands along with the ILC map and find no significant difference in the results. The 95.5% confidence level lower bound on the size of the topology is 1.5L{sub 0} for M{sub 0}, 1.4L{sub 0} for M{sub 1}, and 1.1L{sub 0} for M{sub 2}, where L{sub 0} is the radius of the last scattering surface. Our results agree very well with the recently released results from the Planck temperature data. We show that the likelihood function is not Gaussian in the size, and therefore simulations are important for obtaining accurate bounds on the size. We then introduce the formalism for including polarization data in the analysis. The improvement that we find from WMAP polarization maps is small because of the high level of instrumental noise, but our forecast for Planck maps shows a much better improvement on the lower bound for L. For the M{sub 0} topology we expect an improvement on the lower bound of L from 1.7L{sub 0} to 1.9L{sub 0} at 95.5% confidence level. Using both polarization and temperature data is important because it tests the hypothesis that deviations in the TT spectrum at small l originate in the primordial perturbation spectrum.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

A Bayesian Approach for Quantifying Data Scarcity when Modeling Human Behavior via Inverse Reinforcement Learning

Computational models that formalize complex human behaviors enable study and understanding of such behaviors. However, collecting behavior data required to estimate the parameters of such models is often tedious and resource intensive. Thus, estimating dataset size as part of data collection planning (also known as Sample Size Determination) is important to reduce the time and effort of behavior data collection while maintaining an accurate estimate of model parameters. In this paper, we present a sample size determination method based on Uncertainty Quantification (UQ) for a specific Inverse Reinforcement Learning (IRL) model of human behavior, in two cases: 1) pre-hoc experiment design—conducted in the planning stage before any data is collected, to guide the estimation of how many samples to collect; and 2) post-hoc dataset analysis—performed after data is collected, to decide if the existing dataset has sufficient samples and whether more data is needed. Here, we validate our approach in experiments with a realistic model of behaviors of people with Multiple Sclerosis (MS) and illustrate how to pick a reasonable sample size target. Our work enables model designers to perform a deeper, principled investigation of effects of dataset size on IRL.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Persistent Homology Metrics Reveal Quantum Fluctuations and Reactive Atoms in Path Integral Dynamics

Nuclear quantum effects (NQEs) are known to impact a number of features associated with chemical reactivity and physicochemical properties, particularly for light atoms and at low temperatures. In the imaginary time path integral formalism, each atom is mapped onto a “ring polymer” whose spread is related to the quantum mechanical uncertainty in the particle’s position, i.e., its thermal wavelength. A number of metrics have previously been used to investigate and characterize this spread and explain effects arising from quantum delocalization, zero-point energy, and tunneling. Many of these shape metrics consider just the instantaneous structure of the ring polymers. However, given the significant interest in methods such as centroid molecular dynamics and ring polymer molecular dynamics that link the molecular dynamics of these ring polymers to real time properties, there exists significant opportunity to exploit metrics that also allow for the study of the fluctuations of the atom delocalization in time. Here we consider the ring polymer delocalization from the perspective of computational topology, specifically persistent homology, which describes the 3-dimensional arrangement of point cloud data, (i.e. atomic positions). We employ the Betti sequence probability distribution to define the ensemble of shapes adopted by the ring polymer. The Wasserstein distances of Betti sequences adjacent in time are used to characterize fluctuations in shape, where the Fourier transform and associated principal components provides added information differentiating atoms with different NQEs based on their dynamic properties. We demonstrate this methodology on two representative systems, a glassy system consisting of two atom types with dramatically different de Broglie thermal wavelengths, and ab initio molecular dynamics simulation of an aqueous 4 M HCl solution where the H-atoms are differentiated based on their participation in proton transfer reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

Derivation of new 3D discrete ordinate equations

The Sn equations have been the workhorse of deterministic radiation transport calculations for many years. Here we derive two new angular discretizations of the 3D transport equation. The first set of equations, derived using Lagrange interpolation and collocation, retains the classical Sn structure, with the main difference being how the scattering source is calculated. Because of the formal similarity with the classical S n equations, it should be possible to modify existing computer codes to take advantage of the new formulation. In addition, the new S n-like equations correctly capture delta function scattering. The second set of equations, derived using a Galerkin technique, does not retain the classical Sn structure because the streaming term is not diagonal. However, these equations can be cast into a form similar to existing methods developed to reduce ray effects. Numerical investigation of both sets of equations is under way. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Transition to metallization in warm dense helium-hydrogen mixtures using stochastic density functional theory within the Kubo-Greenwood formalism

The Kubo-Greenwood (KG) formula is often used in conjunction with Kohn-Sham (KS) density functional theory (DFT) to compute the optical conductivity, particularly for warm dense matter. For applying the KG formula, all KS eigenstates and eigenvalues up to an energy cutoff are required and thus the approach becomes expensive, especially for high temperatures and large systems, scaling cubically with both system size and temperature. Here, we develop an approach to calculate the KS conductivity within the stochastic DFT framework, which requires knowledge only of the KS Hamiltonian but not its eigenstates and values. We show that the computational effort associated with the method scales linearly with system size and reduces in proportion to the temperature, unlike the cubic increase with traditional deterministic approaches. In addition, we find that the method allows an accurate description of the entire spectrum, including the high-frequency range, unlike the deterministic method which is compelled to introduce a high-frequency cutoff due to memory and computational time constraints. Finally, we apply the method to helium-hydrogen mixtures in the warm dense matter regime at temperatures of ~60 kK and find that the system displays two conductivity phases, where a transition from nonmetal to metal occurs when hydrogen atoms constitute ~0.3 of the total atoms in the system.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

NUMERICAL CONVERGENCE IN SMOOTHED PARTICLE HYDRODYNAMICS

We study the convergence properties of smoothed particle hydrodynamics (SPH) using numerical tests and simple analytic considerations. Our analysis shows that formal numerical convergence is possible in SPH only in the joint limit N → ∞, h → 0, and N{sub nb} → ∞, where N is the total number of particles, h is the smoothing length, and N{sub nb} is the number of neighbor particles within the smoothing volume used to compute smoothed estimates. Previous work has generally assumed that the conditions N → ∞ and h → 0 are sufficient to achieve convergence, while holding N{sub nb} fixed. We demonstrate that if N{sub nb} is held fixed as the resolution is increased, there will be a residual source of error that does not vanish as N → ∞ and h → 0. Formal numerical convergence in SPH is possible only if N{sub nb} is increased systematically as the resolution is improved. Using analytic arguments, we derive an optimal compromise scaling for N{sub nb} by requiring that this source of error balance that present in the smoothing procedure. For typical choices of the smoothing kernel, we find N{sub nb} ∝N {sup 0.5}. This means that if SPH is to be used as a numerically convergent method, the required computational cost does not scale with particle number as O(N), but rather as O(N {sup 1} {sup +} {sup δ}), where δ ≈ 0.5, with a weak dependence on the form of the smoothing kernel.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Quasielastic electromagnetic scattering cross sections and world data comparisons in the GENIE Monte Carlo event generator

The usage of Monte Carlo neutrino event generators (MC$\textit{ν}$EGs) is a norm within the high-energy $\textit{ν}$ scattering community. The relevance of quasielastic (QE) energy regimes to $\textit{ν}$ oscillation experiments implies that accurate calculations of $\textit{ν}$A cross sections in this regime will be a key contributor to reducing the systematic uncertainties affecting the extraction of oscillation parameters. In spite of this, many MC$\textit{ν}$EGs utilize highly phenomenological, parametrized models of QE scattering cross sections. Moreover, a culture of validation of MC$\textit{ν}$EGs against prolific electron ($\textit{e}$) scattering data has been historically lacking. In this work, we implement new eA cross sections obtained from nuclear ab initio approaches in GENIE, the primary MC$\textit{ν}$EG utilized by the FNAL community. In particular, we utilize results from quantum MC methods which solve the many-body nuclear problem in the short-time approximation (STA), allowing consistent retention of two-nucleon dynamics which are crucial to explain available nuclear electromagnetic (electroweak) data over a wide range of energy and momentum transfers. This new implementation in GENIE is fully tested against the world QE electromagnetic data, finding agreement with available data below ~2 GeV of beam energy with the aid of a scaling function formalism. The STA is currently limited to study $\textit{A}$ ≤ 12 nuclei, however, its semi-inclusive multibody identity components are exportable to other many-body computational techniques such as auxiliary field diffusion MC which can reach $\textit{A}$ ≤ 40 systems while continuing to realize the factorization contained within the STA’s multinucleon dynamics. Together, these developments promise to make future experiments such as DUNE more accurate in their assessment of MC$\textit{ν}$EG systematics, $\textit{ν}$ properties, and potentially empower the discovery of physics beyond the Standard Model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

MO-D-213-06: Quantitative Image Quality Metrics Are for Physicists, Not Radiologists: How to Communicate to Your Radiologists Using Their Language

Purpose: A framework for explaining differences in image quality to non-technical audiences in medial imaging is needed. Currently, this task is something that is learned “on the job.” The lack of a formal methodology for communicating optimal acquisition parameters into the clinic effectively mitigates many technological advances. As a community, medical physicists need to be held responsible for not only advancing image science, but also for ensuring its proper use in the clinic. This work outlines a framework that bridges the gap between the results from quantitative image quality metrics like detectability, MTF, and NPS and their effect on specific anatomical structures present in diagnostic imaging tasks. Methods: Specific structures of clinical importance were identified for a body, an extremity, a chest, and a temporal bone protocol. Using these structures, quantitative metrics were used to identify the parameter space that should yield optimal image quality constrained within the confines of clinical logistics and dose considerations. The reading room workflow for presenting the proposed changes for imaging each of these structures is presented. The workflow consists of displaying images for physician review consisting of different combinations of acquisition parameters guided by quantitative metrics. Examples of using detectability index, MTF, NPS, noise and noise non-uniformity are provided. During review, the physician was forced to judge the image quality solely on those features they need for diagnosis, not on the overall “look” of the image. Results: We found that in many cases, use of this framework settled mis-agreements between physicians. Once forced to judge images on the ability to detect specific structures inter reader agreement was obtained. Conclusion: This framework will provide consulting, research/industrial, or in-house physicists with clinically relevant imaging tasks to guide reading room image review. This framework avoids use of the overall “look” or “feel” to dictate acquisition parameter selection. Equipment grants GE Healthcare.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-R-22: Malignancy Classification for Small Pulmonary Nodules with Radiomics and Logistic Regression

Purpose: We conducted a retrospective study of Radiomics research for classifying malignancy of small pulmonary nodules. A machine learning algorithm of logistic regression and open research platform of Radiomics, IBEX (Imaging Biomarker Explorer), were used to evaluate the classification accuracy. Methods: The training set included 100 CT image series from cancer patients with small pulmonary nodules where the average diameter is 1.10 cm. These patients registered at Chang Gung Memorial Hospital and received a CT-guided operation of lung cancer lobectomy. The specimens were classified by experienced pathologists with a B (benign) or M (malignant). CT images with slice thickness of 0.625 mm were acquired from a GE BrightSpeed 16 scanner. The study was formally approved by our institutional internal review board. Nodules were delineated and 374 feature parameters were extracted from IBEX. We first used the t-test and p-value criteria to study which feature can differentiate between group B and M. Then we implemented a logistic regression algorithm to perform nodule malignancy classification. 10-fold cross-validation and the receiver operating characteristic curve (ROC) were used to evaluate the classification accuracy. Finally hierarchical clustering analysis, Spearman rank correlation coefficient, and clustering heat map were used to further study correlation characteristics among different features. Results: 238 features were found differentiable between group B and M based on whether their statistical p-values were less than 0.05. A forward search algorithm was used to select an optimal combination of features for the best classification and 9 features were identified. Our study found the best accuracy of classifying malignancy was 0.79±0.01 with the 10-fold cross-validation. The area under the ROC curve was 0.81±0.02. Conclusion: Benign nodules may be treated as a malignant tumor in low-dose CT and patients may undergo unnecessary surgeries or treatments. Our study may help radiologists to differentiate nodule malignancy for low-dose CT.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Willingness to Receive mHealth Services Among Patients with Diabetes on Chronic Follow-up in Public Hospitals in Eastern Ethiopia: Multicenter Mixed-Method Study

Background: Management of diabetes requires a long-term care strategy, including support for adherence to a healthy lifestyle and treatment. Exploring the willingness of patients with diabetes to receive mHealth services is essential for designing efficient and effective services. This study aimedto determine willingness to receive mHealth services and associated factors, as well as explore the barriers to receive mHealth services among patients with diabetes. Methods: A multicenter mixed-method study was employed from September 1 to November 30, 2022. For the quantitative part, a total of 365 patients with diabetes receiving chronic follow-up at three public hospitals were enrolled. Data were gathered using structured questionnaires administered by interviewers, entered into Epi-data version 4.6, and analyzed using Stata version 17. A binary and multivariable logistic regression model was computed to identify the associated factors. For qualitative, eight key informants and seven in-depth interviews were conducted. After verbatim transcription and translation, the data were thematically analyzed using ATLAS.ti V. 7.5. Results: Overall, 77.3% had access to a mobile phone, and 74.5% of them were willing to receive mHealth services. Higher odds of willingness to receive mHealth services were reported among patients with an age below 35 years [AOR = 4.11 (1.15– 14.71)], attended formal education [AOR = 2.63 (1.19– 5.77)], without comorbidity [AOR = 3.6 (1.54– 8.41)], < 1-hour travel to reach a health facility [AOR = 3.57 (1.03– 12.36)], answered unknown calls [AOR = 2.3 (1.04– 5.13)], and were satisfied with health-care provider service [AOR = 2.44 (1.04– 5.72)]. In the qualitative part, infrastructure, health facilities, socioeconomic factors, and patients’ behavioral factors were major identified barriers to receiving mHealth services. Conclusion: In this study, the willingness to receive mHealth services for those who have access to mobile phones increased. Additionally, the study highlighted common barriers to receiving mHealth services.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Methods for Specifying Scientific Data Standards and Modeling Relationships with Applications to Neuroscience [Plus Supplementary Data]

Neuroscience continues to experience a tremendous growth in data; in terms of the volume and variety of data, the velocity at which data is acquired, and in turn the veracity of data. These challenges are a serious impediment to sharing of data, analyses, and tools within and across labs. Here, we introduce BRAINformat, a novel data standardization framework for the design and management of scientific data formats. The BRAINformat library defines application-independent design concepts and modules that together create a general framework for standardization of scientific data. We describe the formal specification of scientific data standards, which facilitates sharing and verification of data and formats. We introduce the concept of Managed Objects, enabling semantic components of data formats to be specified as self-contained units, supporting modular and reusable design of data format components and file storage. We also introduce the novel concept of Relationship Attributes for modeling and use of semantic relationships between data objects. Based on these concepts we demonstrate the application of our framework to design and implement a standard format for electrophysiology data and show how data standardization and relationship-modeling facilitate data analysis and sharing. The format uses HDF5, enabling portable, scalable, and self-describing data storage and integration with modern high-performance computing for data-driven discovery. The BRAINformat library is open source, easy-to-use, and provides detailed user and developer documentation and is freely available at: https://bitbucket.org/oruebel/brainformat.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Application and Certification of Comparative Vacuum Monitoring Sensors for Structural Health Monitoring of 737 Wing Box Fittings

Multi-site fatigue damage, hidden cracks in hard-to-reach locations, disbonded joints, erosion, impact, and corrosion are among the major flaws encountered in today's extensive fleet of aging aircraft and space vehicles. The use of in-situ sensors for real-time health monitoring of aircraft structures are a viable option to overcome inspection impediments stemming from accessibility limitations, complex geometries, and the location and depth of hidden damage. Reliable, structural health monitoring systems can automatically process data, assess structural condition, and signal the need for human intervention. Prevention of unexpected flaw growth and structural failure can be improved if on-board health monitoring systems are used to continuously assess structural integrity. Such systems are able to detect incipient damage before catastrophic failures occurs. Condition-based maintenance practices could be substituted for the current time-based maintenance approach. Other advantages of on-board distributed sensor systems are that they can eliminate costly, and potentially damaging, disassembly, improve sensitivity by producing optimum placement of sensors and decrease maintenance costs by eliminating more time- consuming manual inspections. This report presents a Sandia Labs-aviation industry effort to move SHM into routine use for aircraft maintenance. This program addressed formal SHM technology validation and certification issues so that the full spectrum of concerns, including design, deployment, performance and certification were appropriately considered. The Airworthiness Assurance NDI Validation Center (AANC) at Sandia Labs, in conjunction with Boeing, Delta Air Lines, Structural Monitoring Systems Ltd., Anodyne Electronics Manufacturing Corp. and the Federal Aviation Administration (FAA) carried out a certification program to formally introduce Comparative Vacuum Monitoring (CVM) as a structural health monitoring solution to a specific aircraft wing box application. Validation tasks were designed to address the SHM equipment, the health monitoring task, the resolution required, the sensor interrogation procedures, the conditions under which the monitoring will occur, the potential inspector population, adoption of CVM into an airline maintenance program and the document revisions necessary to allow for routine use of CVM as an alternate means of performing periodic structural inspects. To carry out the validation process, knowledge of aircraft maintenance practices was coupled with an unbiased, independent evaluation. Sandia Labs designed, implemented, and analyzed the results from a focused and statistically-relevant experimental effort to quantify the reliability of the CVM system applied to the Boeing 737 Wing Box fitting application. All factors that affect SHM sensitivity were included in this program: flaw size, shape, orientation and location relative to the sensors, as well as operational and environmental variables. Statistical methods were applied to performance data to derive Probability of Detection (POD) values for CVM sensors in a manner that agrees with current nondestructive inspection (NDI) validation requirements and also is acceptable to both the aviation industry and regulatory bodies. This report presents the use of several different statistical methods, some of them adapted from NDI performance assessments and some proposed to address the unique nature of damage detection via SHM systems, and discusses how they can converge to produce a confident quantification of SHM performance An important element in developing SHM validation processes is a clear understanding of the regulatory measures needed to adopt SHM solutions along with the knowledge of the structural and maintenance characteristics that may impact the operational performance of an SHM system. This report describes the major elements of an SHM validation approach and differentiates the SHM elements from those found in NDI validation. The activities conducted in this program demonstrated the feasibility of routine SHM usage in general and CVM in particular for the application selected. They also helped establish an optimum OEM-airline-regulator process and determined how to safely adopt SHM solutions. This formal SHM validation will allow aircraft manufacturers and airlines to confidently make informed decisions about the proper utilization of CVM technology. It will also streamline the regulatory actions and formal certification measures needed to assure the safe application of SHM solutions.

42 ENGINEERING↗