Damage Detection Based on Electromechanical Impedance Principle and Principal Components

This paper presents a novel time domain approach for Structural Health Monitoring (SHM) systems based on Electromechanical Impedance (EMI) principle and Principal Component Coefficients (PCC), also known as loadings. Differently of typical applications of EMI applied to SHM, which are based on computing the Frequency Response Function (FRF), in this work the procedure is based on the EMI principle but all analysis is conducted directly in time-domain. For this, the PCC are computed from the time response of PZT (Lead Zirconate Titanate) transducers bonded to the monitored structure, which act as actuator and sensor at the same time. The procedure is carried out exciting the PZT transducers using a wide band chirp signal and getting their time responses. The PCC are obtained in both healthy and damaged conditions and used to compute statistics indexes. Tests were carried out on an aircraft aluminum plate and the results have demonstrated the effectiveness of the proposed method making it an excellent approach for SHM applications. Finally, the results using EMI signals in both frequency and time responses are obtained and compared. © The Society for Experimental Mechanics 2014.

Identificação de parâmetros modais utilizando apenas as respostas da estrutura: identificação estocástica de subespaço e decomposição no domínio da frequência

Pós-graduação em Engenharia Mecânica - FEIS

Estudo de técnicas de análise modal operacional em sistemas sujeitos a excitações aleatórias com a presença de componente harmônico

A metodologia tradicional de identificação de parâmetros na análise modal de estruturas é realizada a partir de sinais medidos de força de entrada e de movimento de resposta da estrutura em condições laboratoriais controladas. Entretanto, quando é necessária a obtenção dos parâmetros modais de estruturas de máquinas em operação, as condições para controlar e medir a excitação nestas situações impossibilita a realização da análise modal tradicional. Neste caso, o teste modal é realizado utilizando somente dados de resposta do sistema. A Análise Modal Operacional (AMO) é um método de extração modal em que nenhuma excitação artificial necessita ser aplicada ao sistema, utilizando-se a própria excitação operacional como entrada para medição da resposta do sistema. A técnica clássica de Análise Modal Operacional NExT considera, para isso, que a excitação operacional do sistema seja um ruído branco. Esta técnica faz a consideração de que as funções de correlação obtidas de estruturas podem ser consideradas como funções de resposta ao impulso e então métodos tradicionais de identificação modal no domínio do tempo podem ser empregados. Entretanto, caso a excitação operacional contenha componentes harmônicos que se sobressaiam, estes podem ser confundidos como modos naturais do sistema. Neste trabalho é demonstrada que através da função densidade de probabilidade da banda estreita contendo o pico de um modo, é possível identifica-lo como natural ou operacional (proveniente da excitação operacional da estrutura). É apresentada também uma modificação no método de identificação modal Exponencial Complexa Mínimos Quadrados (LSCE), passando a considerar sinais harmônicos de freqüências conhecidas presentes na excitação operacional, em um ensaio utilizando a técnica NExT. Para validação desses métodos, utiliza-se um modelo teórico de parâmetros modais conhecidos analiticamente e como estudo de caso experimental, um sistema formado por uma viga bi-apoiada suportando um motor elétrico com desbalanceamento de massa.

Plant identification based on leaf midrib cross-section images using fractal descriptors

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Application of Volterra series in nonlinear mechanical system identification and in structural health monitoring problems

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

EVIDENCE-BASED PRACTICES PUBLISHED IN BRAZIL: IDENTIFICATION AND ANALYSIS STUDIES ABOUT HUMAN HEALTH PREVENTION

Integrative review of Brazilian studies about evidence-based practices (EBP) about prevention in human health, published in Web of Science/JCR journals, between October 2010 and April 2011. The aim was to identify the specialties that most accomplished these studies, their foci and methodological approaches. Based on inclusion criteria, 84 studies were selected, mainly published in public health journals, focusing on primary care and also addressing clinical issues and different specialties. Prevention foci and methodological approaches also varied, with a predominance of systematic reviews without meta-analysis. The results indicate that there is no single way to conceptualize and practice EBP in the field of prevention, and that its application may not only serve to obtain indisputable evidence to equip intervention actions. This endless knowledge area is under construction, with a view to the analysis and further understanding of health phenomena.

Reliable identification of mycobacterial species by PCR-restriction enzyme analysis (PRA)-hsp65 in a reference laboratory and elaboration of a sequence-based extended algorithm of PRA-hsp65 patterns

Abstract Background Identification of nontuberculous mycobacteria (NTM) based on phenotypic tests is time-consuming, labor-intensive, expensive and often provides erroneous or inconclusive results. In the molecular method referred to as PRA-hsp65, a fragment of the hsp65 gene is amplified by PCR and then analyzed by restriction digest; this rapid approach offers the promise of accurate, cost-effective species identification. The aim of this study was to determine whether species identification of NTM using PRA-hsp65 is sufficiently reliable to serve as the routine methodology in a reference laboratory. Results A total of 434 NTM isolates were obtained from 5019 cultures submitted to the Institute Adolpho Lutz, Sao Paulo Brazil, between January 2000 and January 2001. Species identification was performed for all isolates using conventional phenotypic methods and PRA-hsp65. For isolates for which these methods gave discordant results, definitive species identification was obtained by sequencing a 441 bp fragment of hsp65. Phenotypic evaluation and PRA-hsp65 were concordant for 321 (74%) isolates. These assignments were presumed to be correct. For the remaining 113 discordant isolates, definitive identification was based on sequencing a 441 bp fragment of hsp65. PRA-hsp65 identified 30 isolates with hsp65 alleles representing 13 previously unreported PRA-hsp65 patterns. Overall, species identification by PRA-hsp65 was significantly more accurate than by phenotype methods (392 (90.3%) vs. 338 (77.9%), respectively; p < .0001, Fisher's test). Among the 333 isolates representing the most common pathogenic species, PRA-hsp65 provided an incorrect result for only 1.2%. Conclusion PRA-hsp65 is a rapid and highly reliable method and deserves consideration by any clinical microbiology laboratory charged with performing species identification of NTM.

Substructuring approache in state space models for dynamic system parameters identification

In the recent decade, the request for structural health monitoring expertise increased exponentially in the United States. The aging issues that most of the transportation structures are experiencing can put in serious jeopardy the economic system of a region as well as of a country. At the same time, the monitoring of structures is a central topic of discussion in Europe, where the preservation of historical buildings has been addressed over the last four centuries. More recently, various concerns arose about security performance of civil structures after tragic events such the 9/11 or the 2011 Japan earthquake: engineers looks for a design able to resist exceptional loadings due to earthquakes, hurricanes and terrorist attacks. After events of such a kind, the assessment of the remaining life of the structure is at least as important as the initial performance design. Consequently, it appears very clear that the introduction of reliable and accessible damage assessment techniques is crucial for the localization of issues and for a correct and immediate rehabilitation. The System Identification is a branch of the more general Control Theory. In Civil Engineering, this field addresses the techniques needed to find mechanical characteristics as the stiffness or the mass starting from the signals captured by sensors. The objective of the Dynamic Structural Identification (DSI) is to define, starting from experimental measurements, the modal fundamental parameters of a generic structure in order to characterize, via a mathematical model, the dynamic behavior. The knowledge of these parameters is helpful in the Model Updating procedure, that permits to define corrected theoretical models through experimental validation. The main aim of this technique is to minimize the differences between the theoretical model results and in situ measurements of dynamic data. Therefore, the new model becomes a very effective control practice when it comes to rehabilitation of structures or damage assessment. The instrumentation of a whole structure is an unfeasible procedure sometimes because of the high cost involved or, sometimes, because it’s not possible to physically reach each point of the structure. Therefore, numerous scholars have been trying to address this problem. In general two are the main involved methods. Since the limited number of sensors, in a first case, it’s possible to gather time histories only for some locations, then to move the instruments to another location and replay the procedure. Otherwise, if the number of sensors is enough and the structure does not present a complicate geometry, it’s usually sufficient to detect only the principal first modes. This two problems are well presented in the works of Balsamo [1] for the application to a simple system and Jun [2] for the analysis of system with a limited number of sensors. Once the system identification has been carried, it is possible to access the actual system characteristics. A frequent practice is to create an updated FEM model and assess whether the structure fulfills or not the requested functions. Once again the objective of this work is to present a general methodology to analyze big structure using a limited number of instrumentation and at the same time, obtaining the most information about an identified structure without recalling methodologies of difficult interpretation. A general framework of the state space identification procedure via OKID/ERA algorithm is developed and implemented in Matlab. Then, some simple examples are proposed to highlight the principal characteristics and advantage of this methodology. A new algebraic manipulation for a prolific use of substructuring results is developed and implemented.

Performance evaluation of low environmental impact asphalt concretes using the mechanistic empirical design method based on laboratory fatigue and permanent deformation models

The "sustainability" concept relates to the prolonging of human economic systems with as little detrimental impact on ecological systems as possible. Construction that exhibits good environmental stewardship and practices that conserve resources in a manner that allow growth and development to be sustained for the long-term without degrading the environment are indispensable in a developed society. Past, current and future advancements in asphalt as an environmentally sustainable paving material are especially important because the quantities of asphalt used annually in Europe as well as in the U.S. are large. The asphalt industry is still developing technological improvements that will reduce the environmental impact without affecting the final mechanical performance. Warm mix asphalt (WMA) is a type of asphalt mix requiring lower production temperatures compared to hot mix asphalt (HMA), while aiming to maintain the desired post construction properties of traditional HMA. Lowering the production temperature reduce the fuel usage and the production of emissions therefore and that improve conditions for workers and supports the sustainable development. Even the crumb-rubber modifier (CRM), with shredded automobile tires and used in the United States since the mid 1980s, has proven to be an environmentally friendly alternative to conventional asphalt pavement. Furthermore, the use of waste tires is not only relevant in an environmental aspect but also for the engineering properties of asphalt [Pennisi E., 1992]. This research project is aimed to demonstrate the dual value of these Asphalt Mixes in regards to the environmental and mechanical performance and to suggest a low environmental impact design procedure. In fact, the use of eco-friendly materials is the first phase towards an eco-compatible design but it cannot be the only step. The eco-compatible approach should be extended also to the design method and material characterization because only with these phases is it possible to exploit the maximum potential properties of the used materials. Appropriate asphalt concrete characterization is essential and vital for realistic performance prediction of asphalt concrete pavements. Volumetric (Mix design) and mechanical (Permanent deformation and Fatigue performance) properties are important factors to consider. Moreover, an advanced and efficient design method is necessary in order to correctly use the material. A design method such as a Mechanistic-Empirical approach, consisting of a structural model capable of predicting the state of stresses and strains within the pavement structure under the different traffic and environmental conditions, was the application of choice. In particular this study focus on the CalME and its Incremental-Recursive (I-R) procedure, based on damage models for fatigue and permanent shear strain related to the surface cracking and to the rutting respectively. It works in increments of time and, using the output from one increment, recursively, as input to the next increment, predicts the pavement conditions in terms of layer moduli, fatigue cracking, rutting and roughness. This software procedure was adopted in order to verify the mechanical properties of the study mixes and the reciprocal relationship between surface layer and pavement structure in terms of fatigue and permanent deformation with defined traffic and environmental conditions. The asphalt mixes studied were used in a pavement structure as surface layer of 60 mm thickness. The performance of the pavement was compared to the performance of the same pavement structure where different kinds of asphalt concrete were used as surface layer. In comparison to a conventional asphalt concrete, three eco-friendly materials, two warm mix asphalt and a rubberized asphalt concrete, were analyzed. The First Two Chapters summarize the necessary steps aimed to satisfy the sustainable pavement design procedure. In Chapter I the problem of asphalt pavement eco-compatible design was introduced. The low environmental impact materials such as the Warm Mix Asphalt and the Rubberized Asphalt Concrete were described in detail. In addition the value of a rational asphalt pavement design method was discussed. Chapter II underlines the importance of a deep laboratory characterization based on appropriate materials selection and performance evaluation. In Chapter III, CalME is introduced trough a specific explanation of the different equipped design approaches and specifically explaining the I-R procedure. In Chapter IV, the experimental program is presented with a explanation of test laboratory devices adopted. The Fatigue and Rutting performances of the study mixes are shown respectively in Chapter V and VI. Through these laboratory test data the CalME I-R models parameters for Master Curve, fatigue damage and permanent shear strain were evaluated. Lastly, in Chapter VII, the results of the asphalt pavement structures simulations with different surface layers were reported. For each pavement structure, the total surface cracking, the total rutting, the fatigue damage and the rutting depth in each bound layer were analyzed.

Aircraft-based in-situ aerosol mass spectrometry: Chemical characterization and source identification of submicron particulate matter in the free and upper troposphere and lower stratosphere

The composition of the atmosphere is frequently perturbed by the emission of gaseous and particulate matter from natural as well as anthropogenic sources. While the impact of trace gases on the radiative forcing of the climate is relatively well understood the role of aerosol is far more uncertain. Therefore, the study of the vertical distribution of particulate matter in the atmosphere and its chemical composition contribute valuable information to bridge this gap of knowledge. The chemical composition of aerosol reveals information on properties such as radiative behavior and hygroscopicity and therefore cloud condensation or ice nucleus potential. rnThis thesis focuses on aerosol pollution plumes observed in 2008 during the POLARCAT (Polar Study using Aircraft, Remote Sensing, Surface Measurements and Models, of Climate, Chemistry, Aerosols, and Transport) campaign over Greenland in June/July and CONCERT (Contrail and Cirrus Experiment) campaign over Central and Western Europe in October/November. Measurements were performed with an Aerodyne compact time-of-flight aerosol mass spectrometer (AMS) capable of online size-resolved chemical characterization of non-refractory submicron particles. In addition, the origins of pollution plumes were determined by means of modeling tools. The characterized pollution episodes originated from a large variety of sources and were encountered at distinct altitudes. They included pure natural emissions from two volcanic eruptions in 2008. By the time of detection over Western Europe between 10 and 12 km altitude the plume was about 3 months old and composed to 71 % of particulate sulfate and 21 % of carbonaceous compounds. Also, biomass burning (BB) plumes were observed over Greenland between 4 and 7 km altitude (free troposphere) originating from Canada and East Siberia. The long-range transport took roughly one and two weeks, respectively. The aerosol was composed of 78 % organic matter and 22 % particulate sulfate. Some Canadian and all Siberian BB plumes were mixed with anthropogenic emissions from fossil fuel combustion (FF) in North America and East Asia. It was found that the contribution of particulate sulfate increased with growing influences from anthropogenic activity and Asia reaching up to 37 % after more than two weeks of transport time. The most exclusively anthropogenic emission source probed in the upper troposphere was engine exhaust from commercial aircraft liners over Germany. However, in-situ characterization of this aerosol type during aircraft chasing was not possible. All long-range transport aerosol was found to have an O:C ratio close to or greater than 1 implying that low-volatility oxygenated organic aerosol was present in each case despite the variety of origins and the large range in age from 3 to 100 days. This leads to the conclusion that organic particulate matter reaches a final and uniform state of oxygenation after at least 3 days in the free troposphere. rnExcept for aircraft exhaust all emission sources mentioned above are surface-bound and thus rely on different types of vertical transport mechanisms, such as direct high altitude injection in the case of a volcanic eruption, or severe BB, or uplift by convection, to reach higher altitudes where particles can travel long distances before removal mainly caused by cloud scavenging. A lifetime for North American mixed BB and FF aerosol of 7 to 11 days was derived. This in consequence means that emission from surface point sources, e.g. volcanoes, or regions, e.g. East Asia, do not only have a relevant impact on the immediate surroundings but rather on a hemispheric scale including such climate sensitive zones as the tropopause or the Arctic.

Robust Nonlinear Output Regulation by Identification Tools

The present thesis focuses on the problem of robust output regulation for minimum phase nonlinear systems by means of identification techniques. Given a controlled plant and an exosystem (an autonomous system that generates eventual references or disturbances), the control goal is to design a proper regulator able to process the only measure available, i.e the error/output variable, in order to make it asymptotically vanishing. In this context, such a regulator can be designed following the well known “internal model principle” that states how it is possible to achieve the regulation objective by embedding a replica of the exosystem model in the controller structure. The main problem shows up when the exosystem model is affected by parametric or structural uncertainties, in this case, it is not possible to reproduce the exact behavior of the exogenous system in the regulator and then, it is not possible to achieve the control goal. In this work, the idea is to find a solution to the problem trying to develop a general framework in which coexist both a standard regulator and an estimator able to guarantee (when possible) the best estimate of all uncertainties present in the exosystem in order to give “robustness” to the overall control loop.

Multi-antenna non-line-of-sight identification techniques for target localization in mobile ad-hoc networks

Target localization has a wide range of military and civilian applications in wireless mobile networks. Examples include battle-field surveillance, emergency 911 (E911), traffc alert, habitat monitoring, resource allocation, routing, and disaster mitigation. Basic localization techniques include time-of-arrival (TOA), direction-of-arrival (DOA) and received-signal strength (RSS) estimation. Techniques that are proposed based on TOA and DOA are very sensitive to the availability of Line-of-sight (LOS) which is the direct path between the transmitter and the receiver. If LOS is not available, TOA and DOA estimation errors create a large localization error. In order to reduce NLOS localization error, NLOS identifcation, mitigation, and localization techniques have been proposed. This research investigates NLOS identifcation for multiple antennas radio systems. The techniques proposed in the literature mainly use one antenna element to enable NLOS identifcation. When a single antenna is utilized, limited features of the wireless channel can be exploited to identify NLOS situations. However, in DOA-based wireless localization systems, multiple antenna elements are available. In addition, multiple antenna technology has been adopted in many widely used wireless systems such as wireless LAN 802.11n and WiMAX 802.16e which are good candidates for localization based services. In this work, the potential of spatial channel information for high performance NLOS identifcation is investigated. Considering narrowband multiple antenna wireless systems, two xvNLOS identifcation techniques are proposed. Here, the implementation of spatial correlation of channel coeffcients across antenna elements as a metric for NLOS identifcation is proposed. In order to obtain the spatial correlation, a new multi-input multi-output (MIMO) channel model based on rough surface theory is proposed. This model can be used to compute the spatial correlation between the antenna pair separated by any distance. In addition, a new NLOS identifcation technique that exploits the statistics of phase difference across two antenna elements is proposed. This technique assumes the phases received across two antenna elements are uncorrelated. This assumption is validated based on the well-known circular and elliptic scattering models. Next, it is proved that the channel Rician K-factor is a function of the phase difference variance. Exploiting Rician K-factor, techniques to identify NLOS scenarios are proposed. Considering wideband multiple antenna wireless systems which use MIMO-orthogonal frequency division multiplexing (OFDM) signaling, space-time-frequency channel correlation is exploited to attain NLOS identifcation in time-varying, frequency-selective and spaceselective radio channels. Novel NLOS identi?cation measures based on space, time and frequency channel correlation are proposed and their performances are evaluated. These measures represent a better NLOS identifcation performance compared to those that only use space, time or frequency.

MODEL UPDATING AND STRUCTURAL HEALTH MONITORING OF HORIZONTAL AXIS WIND TURBINES VIA ADVANCED SPINNING FINITE ELEMENTS AND STOCHASTIC SUBSPACE IDENTIFICATION METHODS

Wind energy has been one of the most growing sectors of the nation’s renewable energy portfolio for the past decade, and the same tendency is being projected for the upcoming years given the aggressive governmental policies for the reduction of fossil fuel dependency. Great technological expectation and outstanding commercial penetration has shown the so called Horizontal Axis Wind Turbines (HAWT) technologies. Given its great acceptance, size evolution of wind turbines over time has increased exponentially. However, safety and economical concerns have emerged as a result of the newly design tendencies for massive scale wind turbine structures presenting high slenderness ratios and complex shapes, typically located in remote areas (e.g. offshore wind farms). In this regard, safety operation requires not only having first-hand information regarding actual structural dynamic conditions under aerodynamic action, but also a deep understanding of the environmental factors in which these multibody rotating structures operate. Given the cyclo-stochastic patterns of the wind loading exerting pressure on a HAWT, a probabilistic framework is appropriate to characterize the risk of failure in terms of resistance and serviceability conditions, at any given time. Furthermore, sources of uncertainty such as material imperfections, buffeting and flutter, aeroelastic damping, gyroscopic effects, turbulence, among others, have pleaded for the use of a more sophisticated mathematical framework that could properly handle all these sources of indetermination. The attainable modeling complexity that arises as a result of these characterizations demands a data-driven experimental validation methodology to calibrate and corroborate the model. For this aim, System Identification (SI) techniques offer a spectrum of well-established numerical methods appropriated for stationary, deterministic, and data-driven numerical schemes, capable of predicting actual dynamic states (eigenrealizations) of traditional time-invariant dynamic systems. As a consequence, it is proposed a modified data-driven SI metric based on the so called Subspace Realization Theory, now adapted for stochastic non-stationary and timevarying systems, as is the case of HAWT’s complex aerodynamics. Simultaneously, this investigation explores the characterization of the turbine loading and response envelopes for critical failure modes of the structural components the wind turbine is made of. In the long run, both aerodynamic framework (theoretical model) and system identification (experimental model) will be merged in a numerical engine formulated as a search algorithm for model updating, also known as Adaptive Simulated Annealing (ASA) process. This iterative engine is based on a set of function minimizations computed by a metric called Modal Assurance Criterion (MAC). In summary, the Thesis is composed of four major parts: (1) development of an analytical aerodynamic framework that predicts interacted wind-structure stochastic loads on wind turbine components; (2) development of a novel tapered-swept-corved Spinning Finite Element (SFE) that includes dampedgyroscopic effects and axial-flexural-torsional coupling; (3) a novel data-driven structural health monitoring (SHM) algorithm via stochastic subspace identification methods; and (4) a numerical search (optimization) engine based on ASA and MAC capable of updating the SFE aerodynamic model.

DNA-based identification of novel bovine casein gene variants

In cattle, at least 39 variants of the 4 casein proteins (α(S1)-, β-, α(S2)- and κ-casein) have been described to date. Many of these variants are known to affect milk-production traits, cheese-processing properties, and the nutritive value of milk. They also provide valuable information for phylogenetic studies. So far, the majority of studies exploring the genetic variability of bovine caseins considered European taurine cattle breeds and were carried out at the protein level by electrophoretic techniques. This only allows the identification of variants that, due to amino acid exchanges, differ in their electric charge, molecular weight, or isoelectric point. In this study, the open reading frames of the casein genes CSN1S1, CSN2, CSN1S2, and CSN3 of 356 animals belonging to 14 taurine and 3 indicine cattle breeds were sequenced. With this approach, we identified 23 alleles, including 5 new DNA sequence variants, with a predicted effect on the protein sequence. The new variants were only found in indicine breeds and in one local Iranian breed, which has been phenotypically classified as a taurine breed. A multidimensional scaling approach based on available SNP chip data, however, revealed an admixture of taurine and indicine populations in this breed as well as in the local Iranian breed Golpayegani. Specific indicine casein alleles were also identified in a few European taurine breeds, indicating the introgression of indicine breeds into these populations. This study shows the existence of substantial undiscovered genetic variability of bovine casein loci, especially in indicine cattle breeds. The identification of new variants is a valuable tool for phylogenetic studies and investigations into the evolution of the milk protein genes.

Air Force web-based preventive health assessement alcohol screening effectiveness using the Alcohol Use Disorders Identification Tool (AUDIT)

Alcohol consumption has a long-standing tradition in the United States Air Force (USAF). From squadron bars to officers and enlisted clubs, alcohol has been used in social settings to increase morale and also as a way to help decrease the stress of military operations. Surveys have demonstrated that the USAF has more than double the percentage of heavy drinkers than the US population. More than one-third of the Air Force reports binge drinking in the last month while only six percent of the nation reports the same consumption pattern.^ However, alcohol has a significant harmful health effect if consumed in excess. As part of an overall prevention and treatment program aimed at curbing the harmful effects of alcohol consumption, the USAF uses the Alcohol Use Disorder Identification Test (AUDIT) to screen for high-risk alcohol consumption patterns before alcohol disorder and disability occur. All Air Force active-duty members are required to complete a yearly Preventive Health Assessment questionnaire. Various health topics are included in this questionnaire including nutrition, exercise, tobacco use, family history, mental health and alcohol use. While this questionnaire has been available in a web-based format for several years, mandatory use was not implemented until 2009.^ Although the AUDIT was selected due to its effectiveness in assessing high-risk alcohol consumption in other populations, its effectiveness in the Air Force population had not been studied previously. In order to assess the sensitivity, specificity, and positive predictive value of this screening tool, the Air Force Web-based Preventive Health Assessment alcohol screening results were compared to whether any alcohol-related diagnosis was made from January 1, 2009 to March 31, 2010.^ While the AUDIT has previously been shown to have a high sensitivity and specificity, the Air Force screening values were 27.9% and 93.0% respectively. Positive predictive value was only 4.9%. With the screening statistics found, less than one-third of those having an alcohol disorder will be found with this screening tool and only 1 out of 20 Airmen who require further evaluation actually have an alcohol-related diagnosis.^