995 resultados para Argonne National Laboratory.


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This paper illustrates the damage identification and condition assessment of a three story bookshelf structure using a new frequency response functions (FRFs) based damage index and Artificial Neural Networks (ANNs). A major obstacle of using measured frequency response function data is a large size input variables to ANNs. This problem is overcome by applying a data reduction technique called principal component analysis (PCA). In the proposed procedure, ANNs with their powerful pattern recognition and classification ability were used to extract damage information such as damage locations and severities from measured FRFs. Therefore, simple neural network models are developed, trained by Back Propagation (BP), to associate the FRFs with the damage or undamaged locations and severity of the damage of the structure. Finally, the effectiveness of the proposed method is illustrated and validated by using the real data provided by the Los Alamos National Laboratory, USA. The illustrated results show that the PCA based artificial Neural Network method is suitable and effective for damage identification and condition assessment of building structures. In addition, it is clearly demonstrated that the accuracy of proposed damage detection method can also be improved by increasing number of baseline datasets and number of principal components of the baseline dataset.

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Structural damage detection using measured dynamic data for pattern recognition is a promising approach. These pattern recognition techniques utilize artificial neural networks and genetic algorithm to match pattern features. In this study, an artificial neural network–based damage detection method using frequency response functions is presented, which can effectively detect nonlinear damages for a given level of excitation. The main objective of this article is to present a feasible method for structural vibration–based health monitoring, which reduces the dimension of the initial frequency response function data and transforms it into new damage indices and employs artificial neural network method for detecting different levels of nonlinearity using recognized damage patterns from the proposed algorithm. Experimental data of the three-story bookshelf structure at Los Alamos National Laboratory are used to validate the proposed method. Results showed that the levels of nonlinear damages can be identified precisely by the developed artificial neural networks. Moreover, it is identified that artificial neural networks trained with summation frequency response functions give higher precise damage detection results compared to the accuracy of artificial neural networks trained with individual frequency response functions. The proposed method is therefore a promising tool for structural assessment in a real structure because it shows reliable results with experimental data for nonlinear damage detection which renders the frequency response function–based method convenient for structural health monitoring.

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Standards have been placed to regulate the microbial and preservative contents to assure that foods are safe to the consumer. In a case of a food-related disease outbreak, it is crucial to be able to detect and identify quickly and accurately the cause of the disease. In addition, for every day control of food microbial and preservative contents, the detection methods must be easily performed for numerous food samples. In this present study, quicker alternative methods were studied for identification of bacteria by DNA fingerprinting. A flow cytometry method was developed as an alternative to pulsed-field gel electrophoresis, the golden method . DNA fragment sizing by an ultrasensitive flow cytometer was able to discriminate species and strains in a reproducible and comparable manner to pulsed-field gel electrophoresis. This new method was hundreds times faster and 200,000 times more sensitive. Additionally, another DNA fingerprinting identification method was developed based on single-enzyme amplified fragment length polymorphism (SE-AFLP). This method allowed the differentiation of genera, species, and strains of pathogenic bacteria of Bacilli, Staphylococci, Yersinia, and Escherichia coli. These fingerprinting patterns obtained by SE-AFLP were simpler and easier to analyze than those by the traditional amplified fragment length polymorphism by double enzyme digestion. Nisin (E234) is added as a preservative to different types of foods, especially dairy products, around the world. Various detection methods exist for nisin, but they lack in sensitivity, speed or specificity. In this present study, a sensitive nisin-induced green fluorescent protein (GFPuv) bioassay was developed using the Lactococcus lactis two-component signal system NisRK and the nisin-inducible nisA promoter. The bioassay was extremely sensitive with detection limit of 10 pg/ml in culture supernatant. In addition, it was compatible for quantification from various food matrices, such as milk, salad dressings, processed cheese, liquid eggs, and canned tomatoes. Wine has good antimicrobial properties due to its alcohol concentration, low pH, and organic content and therefore often assumed to be microbially safe to consume. Another aim of this thesis was to study the microbiota of wines returned by customers complaining of food-poisoning symptoms. By partial 16S rRNA gene sequence analysis, ribotyping, and boar spermatozoa motility assay, it was identified that one of the wines contained a Bacillus simplex BAC91, which produced a heat-stable substance toxic to the mitochondria of sperm cells. The antibacterial activity of wine was tested on the vegetative cells and spores of B. simplex BAC91, B. cereus type strain ATCC 14579 and cereulide-producing B. cereus F4810/72. Although the vegetative cells and spores of B. simplex BAC91 were sensitive to the antimicrobial effects of wine, the spores of B. cereus strains ATCC 14579 and F4810/72 stayed viable for at least 4 months. According to these results, Bacillus spp., more specifically spores, can be a possible risk to the wine consumer.

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The purpose of this dissertation was to study the applicability of minced autologous fascia graft for injection laryngoplasty of unilateral vocal fold paralysis (UVFP). Permanence of augmentation and host versus graft tissue reactions were of special interest. The topic deals with phonosurgery, which is a subdivision of the Ear, Nose and Throat-speciality of medicine. UVFP results from an injury to the recurrent or the vagal nerve. The main symptom is a hoarse and weak voice. Surgery is warranted for patients in whom spontaneous reinnervation and a course of voice therapy fails to improve the voice. Injection laryngoplasty is a widespread surgical technique which aims to restore glottic closure by augmenting the atrophied vocal muscle, and also by turning the paralyzed vocal fold towards midline. Currently, there exists a great diversity of synthetic, xenologous, homologous, and autologous substances available for injection. An autologous graft is perfect in terms of biocompatibility. Free fascia grafts have been successfully used in the head and neck surgery for decades, but fascia had not been previously applied into the vocal fold. The fascia is harvested from the lateral thigh under local anesthesia and minced into paste by scissors. Injection of the vocal fold is performed in laryngomicroscopy under general anesthesia. Three series of clinical trials of injection laryngoplasty with autologous fascia (ILAF) for patients with UVFP were conducted at the Department of Otorhinolaryngology of the Helsinki University Central Hospital. The follow-up ranged from a few months to ten years. The aim was to document the vocal results and possible morbidity related to graft harvesting and vocal fold injection. To address the tissue reactions and the degree of reabsoprtion of the graft, an animal study with a follow-up ranging from 3 days to 12 months was performed at the National Laboratory Animal Center, University of Kuopio. Harvesting of the graft and injection was met with minor morbidity. Histological analysis of the vocal fold tissue showed that fascia was well tolerated. Although some resorption or compaction of the graft during the first months is evident, graft volume is maintained well. When injected deep and laterally into the vocalis muscle, the fascia graft allows normal vibration of the vocal fold mucosa to occur during phonation. Improvement of voice quality was seen in all series by multiple objective parameters of voice evaluation. However, the vocal results were poor in cases where the nerve trauma was severe, such as UVFP after chest surgery. ILAF is most suitable for correction of mild to moderate glottic gaps related to less severe nerve damage. Our results indicate that autologous fascia is a feasible and safe new injection material with good and stable vocal results. It offers a practical solution for surgeons who treat this complex issue.

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The dynamic properties of a structure are a function of its physical properties, and changes in the physical properties of the structure, including the introduction of structural damage, can cause changes in its dynamic behavior. Structural health monitoring (SHM) and damage detection methods provide a means to assess the structural integrity and safety of a civil structure using measurements of its dynamic properties. In particular, these techniques enable a quick damage assessment following a seismic event. In this thesis, the application of high-frequency seismograms to damage detection in civil structures is investigated.

Two novel methods for SHM are developed and validated using small-scale experimental testing, existing structures in situ, and numerical testing. The first method is developed for pre-Northridge steel-moment-resisting frame buildings that are susceptible to weld fracture at beam-column connections. The method is based on using the response of a structure to a nondestructive force (i.e., a hammer blow) to approximate the response of the structure to a damage event (i.e., weld fracture). The method is applied to a small-scale experimental frame, where the impulse response functions of the frame are generated during an impact hammer test. The method is also applied to a numerical model of a steel frame, in which weld fracture is modeled as the tensile opening of a Mode I crack. Impulse response functions are experimentally obtained for a steel moment-resisting frame building in situ. Results indicate that while acceleration and velocity records generated by a damage event are best approximated by the acceleration and velocity records generated by a colocated hammer blow, the method may not be robust to noise. The method seems to be better suited for damage localization, where information such as arrival times and peak accelerations can also provide indication of the damage location. This is of significance for sparsely-instrumented civil structures.

The second SHM method is designed to extract features from high-frequency acceleration records that may indicate the presence of damage. As short-duration high-frequency signals (i.e., pulses) can be indicative of damage, this method relies on the identification and classification of pulses in the acceleration records. It is recommended that, in practice, the method be combined with a vibration-based method that can be used to estimate the loss of stiffness. Briefly, pulses observed in the acceleration time series when the structure is known to be in an undamaged state are compared with pulses observed when the structure is in a potentially damaged state. By comparing the pulse signatures from these two situations, changes in the high-frequency dynamic behavior of the structure can be identified, and damage signals can be extracted and subjected to further analysis. The method is successfully applied to a small-scale experimental shear beam that is dynamically excited at its base using a shake table and damaged by loosening a screw to create a moving part. Although the damage is aperiodic and nonlinear in nature, the damage signals are accurately identified, and the location of damage is determined using the amplitudes and arrival times of the damage signal. The method is also successfully applied to detect the occurrence of damage in a test bed data set provided by the Los Alamos National Laboratory, in which nonlinear damage is introduced into a small-scale steel frame by installing a bumper mechanism that inhibits the amount of motion between two floors. The method is successfully applied and is robust despite a low sampling rate, though false negatives (undetected damage signals) begin to occur at high levels of damage when the frequency of damage events increases. The method is also applied to acceleration data recorded on a damaged cable-stayed bridge in China, provided by the Center of Structural Monitoring and Control at the Harbin Institute of Technology. Acceleration records recorded after the date of damage show a clear increase in high-frequency short-duration pulses compared to those previously recorded. One undamage pulse and two damage pulses are identified from the data. The occurrence of the detected damage pulses is consistent with a progression of damage and matches the known chronology of damage.

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̄pp backward elastic scattering has been measured for the cos θcm region between – 1.00 and – 0.88 and for the incident ̄p laboratory momentum region between 0.70 and 2.37 GeV/c. These measurements, done in intervals of approximately 0.1 GeV/c, have been performed at the Alternating Gradient Synchrotron at Brookhaven National Laboratory during the winter of 1968. The measured differential cross sections, binned in cos θcm intervals of 0.02, have statistical errors of about 10%. Backward dipping exists below 0.95 GeV/c and backward peaking above 0.95 GeV/c. The 180˚ differential cross section extrapolated from our data shows a sharp dip centered at 0.95 GeV/c and a broad hump centered near 1.4 GeV/c. Our data have been interpreted in terms of resonance effects and in terms of diffraction dominance effects.

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The lowest T = 2 states have been identified and studied in the nuclei 12C, 12B, 20F and and 28Al. The first two of these were produced in the reactions 14C(p,t)12C and 14C (p,3He)12B, at 50.5 and 63.4 MeV incident proton energy respectively, at the Oak Ridge National Laboratory. The T = 2 states in 20F and 28Al were observed in (3He,p) reactions at 12-MeV incident energy, with the Caltech Tandem accelerator.

The results for the four nuclei studied are summarized below:

(1) 12C: the lowest T = 2 state was located at an excitation energy of 27595 ± 20 keV, and has a width less than 35 keV.

(2) 12B: the lowest T = 2 state was found at an excitation energy of 12710 ± 20 keV. The width was determined to be less than 54 keV and the spin and parity were confirmed to be 0+. A second 12B state (or doublet) was observed at an excitation energy of 14860 ± 30 keV with a width (if the group corresponds to a single state) of 226 ± 30 keV.

(3) 20F: the lowest T = 2 state was observed at an excitation of 6513 ± 5 keV; the spin and parity were confirmed to be 0+. A second state, tentatively identified as T = 2 from the level spacing, was located at 8210 ± 6 keV.

(4) 28Al: the lowest T = 2 state was identified at an excitation of 5997 ± 6 keV; the spin and parity were confirmed to be 0+. A second state at an excitation energy of 7491 ± 11 keV is tentatively identified as T = 2, with a corresponding (tentative) spin and parity assignment Jπ = 2+.

The results of the present work and the other known masses of T = 2 states and nuclei for 8 ≤ A ≤ 28 are summarized, and massequation coefficients have been extracted for these multiplets. These coefficients were compared with those from T = 1 multiplets, and then used to predict the mass and stability of each of the unobserved members of the T = 2 multiplets.

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