Characterizing the Impacts of the Invasive Hemlock Woolly Adelgid on the Forest Structure of New England

Climate change is raising winter temperatures in the Northeastern United States, both expanding the range of an invasive pest, the hemlock woolly adelgid (HWA; Adelges tsugae), and threatening the survival of its host species, eastern hemlock (Tsuga canadensis). As a foundation species, hemlock trees underlie a distinct network of ecological, biogeochemical, and structural systems that will likely disappear as the HWA infestation spreads northward. Remote sensing can offer new perspectives on this regional transition, recording the progressive loss of an ecological foundation species and the transition of evergreen hemlock forest to mixed deciduous forest over the course of the infestation. Lidar remote sensing, unlike other remote sensing tools, has the potential to penetrate dense hemlock canopies and record HWA’s distinct impacts on lower canopy structure. Working with a series of lidar data from the Harvard Forest experimental site, these studies identify the unique signals of HWA impacts on vertical canopy structure and use them to predict forest condition. Methods for detecting the initial impacts of HWA are explored and a workflow for monitoring changes in forest structure at the regional scale is outlined. Finally, by applying terrestrial, airborne, and spaceborne lidar data to characterize the structural variation and dynamics of a disturbed forest ecosystem, this research illustrates the potential of lidar as a tool for forest management and ecological research

A multiscale strategy for fouling prediction and mitigation in gas turbines

Gas turbines are one of the primary sources of power for both aerospace and land-based applications. Precisely for this reason, they are often forced to operate in harsh environmental conditions, which involve the occurrence of particle ingestion by the engine. The main implications of this problem are often underestimated. The particulate in the airflow ingested by the machine can deposit or erode its internal surfaces, and lead to the variation of their aerodynamic geometry, entailing performance degradation and, possibly, a reduction in engine life. This issue affects the compressor and the turbine section and can occur for either land-based or aeronautical turbines. For the former, the problem can be mitigated (but not eliminated) by installing filtration systems. For what concern the aerospace field, filtration systems cannot be used. Volcanic eruptions and sand dust storms can send particulate to aircraft cruising altitudes. Also, aircraft operating in remote locations or low altitudes can be subjected to particle ingestion, especially in desert environments. The aim of this work is to propose different methodologies capable to mitigate the effects of fouling or predicting the performance degradation that it generates. For this purpose, both hot and cold engine sections are considered. Concerning the turbine section, new design guidelines are presented. This is because, for this specific component, the time scales of failure events due to hot deposition can be of the order of minutes, which makes any predictive model inapplicable. In this respect, design optimization techniques were applied to find the best HPT vane geometry that is less sensitive to the fouling phenomena. After that, machine learning methods were adopted to obtain a design map that can be useful in the first steps of the design phase. Moreover, after a numerical uncertainty quantification analysis, it was demonstrated that a deterministic optimization is not sufficient to face highly aleatory phenomena such as fouling. This suggests the use of robust or aggressive design techniques to front this issue. On the other hand, with respect to the compressor section, the research was mainly focused on the building of a predictive maintenance tool. This is because the time scales of failure events due to cold deposition are longer than the ones for the hot section, hence the main challenge for this component is the optimization of the washing schedule. As reported in the previous sections, there are several studies in the literature focused on this issue, but almost all of them are data-based instead of physics-based. The innovative strategy proposed here is a mixture between physics-based and data-based methodologies. In particular, a reduced-order model has been developed to predict the behaviour of the whole engine as the degradation proceeds. For this purpose, a gas path code that uses the components’ characteristic maps has been created to simulate the gas turbine. A map variation technique has been used to take into account the fouling effects on each engine component. Particularly, fouling coefficients as a function of the engine architecture, its operating conditions, and the contaminant characteristics have been created. For this purpose, both experimental and computational results have been used. Specifically for the latter, efforts have been done to develop a new numerical deposition/detachment model.Le turbine a gas sono una delle pricipali fonti di energia, sia per applicazioni aeronautiche che terrestri. Proprio per questa ragione, esse sono spesso costrette ad operare in ambienti non propriamente puliti, il che comporta l’ingestione di contaminanti solidi da parte del motore. Le principali implicazioni di questo problema sono spesso sottovalutate. Le particelle solide presenti nel flusso d’aria che il motore ingerisce durante il suo funzionamento possono depositarsi o erodere le superfici interne della macchina, e portare a variazioni alla sua aerodinamica, quindi a degrado di performance e, molto probabilmente, alla diminuzione della sua vita utile. Questo problema aflligge sia la parte del compressore che la parte della turbina, e si manifesta sia in applicazioni terrestri che aeronautiche. Per quanto riguarda la prima, la questione può essere mitigata (ma non eliminata) dall’installazione di sistemi di filtraggio all’ingresso della macchina. Per le applicazioni aeronautiche invece, i sistemi di filtraggio non possono essere utilizzati. Questo implica che il particolato presente ad alte quote, magari grazie ad eventi catastrofici quali eruzioni vulcaniche, o a basse quote, quindi ambienti deseritic, entra liberamente nella turbina a gas. Lo scopo principale di questo lavoro di tesi, è quello di proporre differenti metodologieallo scopo di mitigare gli effetti dello sporcamento o predirre il degrado che esso comporta nelle turbine a gas. Per questo scopo, sia la parte del compressore che quella della turbina sono state prese in considerazione. Per quanto riguarda la parte turbina, saranno presentate nuove guide progettuali volte al trovare la geometria che sia meno sensibile possibile al problema dello sporcamento. Dopo di ciò, i risultati ottenuti verranno trattati tramite tecniche di machine learning, ottenendo una mappa di progetto che potrà essere utile nelle prime fasi della progettazione di questi componenti. Inoltre, essendo l’analisi fin qui condotta di tipo deterministico, un’analisi delle principali fonti di incertezza verrà eseguita con l’utilizzo di tecniche derivanti dall’uncertainty quantification. Questo dimostrerà che l’analisi deterministica è troppo semplificativa, e che sarebbe opportuno spingersi verso una progettazione robusta per affrontare questa tipologia di problemi. D’altro canto, per quanto concerne la parte compressore, la ricerca è stata incentrata principalmente sulla costruzione di uno strumento predittivo, questo perchè la scala temporale del degrado dovuto alla deposizione a "freddo" è molto più dilatata rispetto a quella della sezione "calda". La trategia proposta in questo lavoro di tesi è un’insieme di modelli fisici e data-driven. In particolare, si è sviluppato un modello ad ordine ridotto per la previsione del comportamento del motore soggetto a degrado dovuto all’ingestione di particolato, durante un’intera missione aerea. Per farlo, si è generato un codice cosiddetto gas-path, che modella i singoli componenti della macchina attraverso le loro mappe caratteristiche. Quest’ultime vengono modificate, a seguito della deposizione, attraverso opportuni coefficienti di degrado. Tali coefficienti devono essere adeguatamente stimati per avere una corretta previsione degli eventi, e per fare ciò verrà proposta una strategia che comporta l’utilizzo sia di metodi sperimentali che computazionali, per la generazione di un algoritmo che avrà lo scopo di fornire come output questi coefficienti

Development of Spect and Ct Tomographic Image Reconstruction

The purpose of this study was to contribute to the advancement of statistically-based iterative reconstruction algorithms and protocols for both SPECT and micro CT data. Major contributions of this work to SPECT reconstruction include formulation and implementation of fully three-dimensional voxel-based system matrix in parallel-beam, fan-beam, and cone-beam collimator geometries while modeling the process of attenuation, system resolution and sensitivity. This is achieved by casting rays through a volume of voxels and using ray-voxel intersection lengths to determine approximate volume contributions. Qualitative and quantitative analysis of reconstructed Monte Carlo data sets show that this is a very effective and efficient method. Using this method, three SPECT studies were conducted. First, the reconstruction performance was studied for a triple-head cone-beam SPECT system using a helical orbit acquisition. We looked at various subset groupings for the ordered-subsets expectation maximization (OSEM) algorithm. We also examined how rotational and translational sampling affects reconstructed image quality when constrained by total injected dose and scan time. We conclude the following: When reconstructing noiseless datasets, varying the rotational sampling from 90 views to 360 views over 360 degrees does not affect the reconstructed activity regardless of the object size in terms of both convergence and accuracy. When using ordered subsets, the subset group arrangement is important in terms of both image quality and accuracy. The smaller the object is that is being reconstructed, the rate of convergence decreases, the spatial resolution decreases, and accuracy decreases. Second, we examined a system composed of three, possibly different, converging collimators using a circular orbit. We conclude the following: When reconstructing noiseless datasets, using a triple-cone beam system resulted in distortion artifacts along the axial direction and diminished resolution along the transaxial direction. Using a triple-fan beam system resulted in the best reconstructed image quality in terms of bias, noise, and contrast. When noisy datasets were reconstructed, a cone-cone-fan beam system resulted in best reconstructed image quality in terms of mean-to-actual ratio for small lesions and a triple-fan beam system for large lesions. Finally, a two-dimensional mesh-based system matrix for parallel-beam collimation with attenuation and resolution modeling was designed, implemented, and studied. We conclude that no more than two divisions per detector bin width are needed for satisfactory reconstruction. Also, using more than two divisions per detector bin does not significantly improve reconstructed images. A chapter on iterative micro-CT reconstruction is also included. Our contribution to micro-CT reconstruction is the formulation and implementation of a cone-beam system matrix that reduces ring artifacts associated with sampling of the reconstruction space. This new approach reduces the common 3 D ray-tracing technique into 2-D, making it very efficient. The images obtained using our approach are compared to images reconstructed by means of analytical techniques. We observe significant improvement in image quality for the images reconstructed using our iterative method

High-Resolution Quantitative Cone-Beam Computed Tomography: Systems, Modeling, and Analysis for Improved Musculoskeletal Imaging

This dissertation applies accurate models of imaging physics, new high-resolution imaging hardware, and novel image analysis techniques to benefit quantitative applications of x-ray CT in in vivo assessment of bone health. We pursue three Aims: 1. Characterization of macroscopic joint space morphology, 2. Estimation of bone mineral density (BMD), and 3. Visualization of bone microstructure. This work contributes to the development of extremity cone-beam CT (CBCT), a compact system for musculoskeletal (MSK) imaging. Joint space morphology is characterized by a model which draws an analogy between the bones of a joint and the plates of a capacitor. Virtual electric field lines connecting the two surfaces of the joint are computed as a surrogate measure of joint space width, creating a rich, non-degenerate, adaptive map of the joint space. We showed that by using such maps, a classifier can outperform radiologist measurements at identifying osteoarthritic patients in a set of CBCT scans. Quantitative BMD accuracy is achieved by combining a polyenergetic model-based iterative reconstruction (MBIR) method with fast Monte Carlo (MC) scatter estimation. On a benchtop system emulating extremity CBCT, we validated BMD accuracy and reproducibility via a series of phantom studies involving inserts of known mineral concentrations and a cadaver specimen. High-resolution imaging is achieved using a complementary metal-oxide semiconductor (CMOS)-based x-ray detector featuring small pixel size and low readout noise. A cascaded systems model was used to performed task-based optimization to determine optimal detector scintillator thickness in nominal extremity CBCT imaging conditions. We validated the performance of a prototype scanner incorporating our optimization result. Strong correlation was found between bone microstructure metrics obtained from the prototype scanner and µCT gold standard for trabecular bone samples from a cadaver ulna. Additionally, we devised a multiresolution reconstruction scheme allowing fast MBIR to be applied to large, high-resolution projection data. To model the full scanned volume in the reconstruction forward model, regions outside a finely sampled region-of-interest (ROI) are downsampled, reducing runtime and cutting memory requirements while maintaining image quality in the ROI

PREDICTION AND CONTROL OF IMAGE PROPERTIES IN ADVANCED COMPUTED TOMOGRAPHY

Computed Tomography (CT) is an important technique that is in widespread use for disease diagnosis, monitoring, and interventional procedures. There are many varieties of CT including cone-beam CT (CBCT) that has exceptional high spatial resolution and spectral CT that incorporates energy-dependent measurements for advanced material discrimination. The goal of this research is to quantify image properties using a prospective prediction framework for advanced reconstruction in CBCT and spectral CT systems. These predictors analyze the dependencies of image properties on system configuration, acquisition strategy, and reconstruction regularization design. The prospective estimation of image properties facilitates novel system and acquisition design, adaptive and task-driven imaging, and tuning of regularization for robust and reliable performance. The proposed research quantifies the image properties of model-based iterative reconstruction (MBIR) in CBCT and model-based material decomposition (MBMD) in spectral CT, including spatial resolution, the generalized response to local perturbations, and noise correlation. Predictions are derived with a realistic system model including physical blur, noise correlation, and a poly-energetic model that applies to a variety of spectral CT protocols. Reconstruction methods combining data statistical fidelity and various advanced regularization designs are explored. Prediction accuracy is validated with measured image properties in both simulation and physical experiments. The theoretical understanding is applied to applications with prospective reconstruction regularization design

A New Compactification for Celestial Mechanics

This is an exposition of a new compactification of Euclidean space enabling the study of trajectories at and approaching spatial infinity, as well as results obtained for polynomial differential systems and Celestial Mechanics. The Lorenz system has an attractor for all real values of its parameters, and almost all of the complete quadratic systems share an interesting feature with the Lorenz system.;Informed by these results, the main theorem is established via a contraction mapping arising from an integral equation derived from the Celestial Mechanics equations of motion. We establish the existence of an open set of initial conditions through which pass solutions without singularities, to Newton\u27s gravitational equations in Euclidean space on a semi-infinite interval in forward time, for which every pair of particles separates like a multiple of time, as time tends to infinity. The solutions are constructible as series with rapid uniform convergence and their asymptotic behavior to any order is prescribed. We show that this family of solutions depends on 6N parameters subject to certain constraints. This confirms the logical converse of Chazy\u27s 100-year old result assuming solutions exist for all time, they take the form given by Bohlin: solutions of Bohlin\u27s form do exist for all time. An easy consequence not found elsewhere is that the asymptotic directions of many configurations exiting the universe depend solely on the initial velocities and not on their initial positions.;The N-body problem is fundamental to astrodynamics, since it is an idealization to point masses of the general problem of the motion of gravitating bodies, such as spacecraft motion within the Solar System. These new trajectories model paths of real particles escaping to infinity. A particle escaping its primary on a hyperbolic trajectory in the Kepler problem is the simplest example. This work may have relevance to new interplanetary trajectories or insight into known trajectories for potential space missions

Nitroxide Radicals for Low Frequency Electron Paramagnetic Resonance Imaging (EPRI)

Optimization of nitroxides as probes for EPR imaging requires detailed understanding of spectral properties such as spin lattice relaxation times, spin packet linewidths, and nuclear hyperfine splitting. Initial measurements of relaxation times for six low molecular weight nitroxides at X-band stimulated further measurement at frequencies between 250 MHz and 34 GHz. The impact of tumbling was studied with perdeuterated 2,2,6,6-tetramethyl-4-piperidinyl-1-oxyl (PDT) in five solvents with viscosities resulting in tumbling correlation times, τR, between 4 and 50 ps. A set of three 14N/15N pairs of nitroxides in water was selected such that τR varied between 9 and 19 ps. To test the impact of structure on relaxation, three additional nitroxides with τR between 10 and 26 ps were studied. In the fast tumbling regime 1/T2 ~ 1/T1 and relaxation is dominated by spin rotation, modulation of A-anisotropy and a thermally activated process. The contribution to 1/T1 from spin rotation is independent of frequency and decreases as τR increases. The modulation of nitrogen hyperfine anisotropy increases as frequency decreases and as τR increases, dominating at low frequencies for τR~ 15 ps. The modulation of g anisotropy is significant only at 34 GHz. Inclusion of a thermally activated process was required to account for the observation that for most of the radicals, 1/T1 was smaller at 250 MHz than at 1-2 GHz. The thermally activated process likely arises from intramolecular motions of the nitroxide ring that modulate the isotropic A values. A phantom of three 4 mm tubes containing different 15N,2H-substituted nitroxides was constructed for use at 250 MHz. Projections for 2D spectral-spatial images were obtained by continuous wave (CW) and rapid scan (RS) EPR using a bimodal cross-loop resonator. Relative to CW projections obtained for the same data acquisition time (5 min), RS projections had significantly improved image quality. All experiments were facilitated by advancements in resonator design and testing, which are also described

COMBAT SYSTEMS Volume 1. Sensor Elements Part I. Sensor Functional Characteristics

This document includes: CHAPTER 1. SIGNATURES, OBSERVABLES, & PROPAGATORS. CHAPTER 2. PROPAGATION OF ELECTROMAGNETIC RADIATION. I. – FUNDAMENTAL EFFECTS. CHAPTER 3. PROPAGATION OF ELECTROMAGNETIC RADIATION. II. – WEATHER EFFECTS. CHAPTER 4. PROPAGATION OF ELECTROMAGNETIC RADIATION. III. – REFRACTIVE EFFECTS. CHAPTER 5. PROPAGATION OF ELECTROMAGNETIC RADIATION IV. – OTHER ATMOSPHERIC AND UNDERWATER EFFECTS. CHAPTER 6. PROPAGATION OF ACOUSTIC RADIATION. CHAPTER 7. NUCLEAR RADIATION: ITS ORIGIN AND PROPAGATION. CHAPTER 8. RADIOMETRY, PHOTOMETRY, & RADIOMETRIC ANALYSIS. CHAPTER 9. SENSOR FUNCTIONS. CHAPTER 10. SEARCH. CHAPTER 11. DETECTION. CHAPTER 12. ESTIMATION. CHAPTER 13. MODULATION AND DEMODULATION. CHAPTER 14. IMAGING AND IMAGE-BASED PERCEPTION. CHAPTER 15. TRACKING. APPENDIX A. UNITS, PHYSICAL CONSTANTS, AND USEFUL CONVERSION FACTORS. APPENDIX B. FINITE DIFFERENCE AND FINITE ELEMENT TECHNIQUES. APPENDIX C. PROBABILITY AND STATISTICS. INDEX TO VOLUME 1. Note by author: Note: Boldface entries in the table of contents are not yet completed

Research reports: 1985 NASA/ASEE Summer Faculty Fellowship Program

A compilation of 40 technical reports on research conducted by participants in the 1985 NASA/ASEE Summer Faculty Fellowship Program at Marshall Space Flight Center (MSFC) is given. Weibull density functions, reliability analysis, directional solidification, space stations, jet stream, fracture mechanics, composite materials, orbital maneuvering vehicles, stellar winds and gamma ray bursts are among the topics discussed