Thesis. 1977. Ph.D.--Massachusetts Institute of Technology. Dept. of Civil Engineering. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING. / Bibliography: leaves 207-211. / by Hugo Scaletti Farina. / Ph.D.

Thesis. 1976. M.S.--Massachusetts Institute of Technology. Dept. of Civil Engineering. / Microfiche copy available in Archives and Engineering. / Includes bibliographical references. / M.S.

Measurement is the foundation of epidemiologic thought and practice. The appropriate measurement of exposures and outcomes of interest is the underlying assumption to all causal investigations. Poor quality measurement, be it through inappropriate data collection methods or changing diagnostic criteria, which can result in erroneous estimates, has a deleterious impact on scientists, policy makers, and the public. Mental health disorders particularly suffer from a lack of diagnostic clarity as diagnosis is often based on self-report of overlapping symptoms with no clear measureable biomarkers. The release of the Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-5) in May of 2013 is the most recent attempt to codify existing diagnostic criteria for psychiatric disorders. Posttraumatic stress disorder (PTSD) diagnostic criteria shifted from a three-cluster approach of avoidance, hyper-arousal, and re- experiencing to a four-cluster approach of avoidance, arousal, negative cognitions and mood, and re- experiencing. The very existence of multiple diagnostic frameworks for the same psychiatric disorder is proof that accurate diagnosis is a complex and unresolved issue that warrants investigation. This complexity in posttraumatic stress disorder (PTSD) symptom presentation, limits our ability to develop appropriate responses. In this dissertation I conducted four independent but related studies to explore the construct validity of PTSD. In Chapter 1 I systematically reviewed the extant empiric literature from PubMed and PsychINFO on PTSD symptom structure to identify a universal PTSD factor structure. I found 40 (3%) of 1,302 citations published between 1980-2014 provided empiric PTSD factor structure estimates forming the basis of my review. While consensus exists with respect to the general multifactorial make-up of PTSD, a universal understanding of the specific operationalization of this structure, supported by the empiric literature, is absent. In Chapter 2, I used population-based, cross-sectional data from adult survivors of the 2010 earthquake in Haiti, to assesses model fit of six theoretical factor structures of PTSD: one-factor Diagnostic and Statistical Manual of Mental Disorders (DSM)-IV; three-factor DSM-IV-TR (arousal, avoidance, and intrusion); three-main factor (arousal, avoidance, and intrusion) and one-hierarchical factor DSM-IV-TR; four-factor King 1998 (avoidance, hypervigilance, emotional numbing, re-experiencing); four-factor Simms 2002 (avoidance, dysphoria, hyperarousal, intrusion); and four-factor DSM-5 (arousal, avoidance, intrusion, negative mood and cognition) models through confirmatory factor analyses (CFA). While all models adequately fit the data, the three-factor DSM-IV-TR (arousal, avoidance, and intrusion) model best fit the sample (χ2=593.257, 116 degrees of freedom; RMSEA=0.056; CFI=0.927; TLI=0.915, WRMR=1.769; AIC=24,760.459; and BIC=24,952.178). Again drawing on the cross-sectional, population data from Haitian earthquake survivors, in Chapter 3 I used multiple linear regressions to model pre-, peri-, and post-earthquake factor associations with mean PTSD symptom cluster (arousal, intrusion, and avoidance, validated in Chapter 2) endorsement. I found that mean PTSD symptom factor endorsement is heterogeneously associated with pre-, peri-, and post- earthquake factors, consistent with dimensional theoretical foundations: arousal endorsement more likely to be associated with pre-earthquake factors, intrusion endorsement more likely to be associated with factors across the temporal field, and avoidance endorsement more likely to be associated with post- earthquake factors. In Chapter 4, I used exploratory factor analysis (EFA) to assess the factor stability of the DSM-IV-TR (arousal, intrusion, avoidance) defined PTSD structure when major depressive disorder (MDD) items are introduced, in the same Haitian post-earthquake population-based study. A six-factor, 25-item model was estimated and fit the data (χ2=253.427, 165 degrees of freedom, p<0.001; RMSEA=0.021, 90% CI:0.016, 0.026; CFI=0.987; TLI=0.976) better than the PTSD-only model specified in Chapter 2. PTSD-specific items did not load on the original PTSD factors or with the original factor items (new factors included items from 0-3 different original PTSD factors), in the presence of MDD items. PTSD dimensionality was not stable in the presence of MDD items, thus challenging the discriminant validity of PTSD. This exploration into PTSD construct validity found that while consensus exists with respect to the general multifactorial make-up of PTSD, a universal understanding of the specific operationalization of this structure, supported by the empiric literature, is absent. The tight range in model fit statistics documented in the CFA provides additional evidence of this, suggesting that empirical-based model selection is insufficient to universally characterize PTSD. Given the overall consensus of general factors, the significant and heterogeneous pre-, peri-, and post-earthquake factor associations with the unique PTSD symptom clusters provides additional evidence of the multidimensional theoretical mechanisms behind PTSD psychopathology. PTSD model stability, an indication of discriminant validity, failed to hold when challenged by MDD items, further challenging PTSD construct validity. There are several important implications of this work. First, based on the systematic review and CFA findings, adjudication of PTSD model selection based on empiric findings is insufficient and should be theoretically driven. Future investigations should always include the most commonly supported models as they develop and refine additional models, thus enabling rigorous cross-context, cross-potentially traumatic event, and cross-study comparisons that are currently not possible. Second, the multidimensional modeling of PTSD factors provided valuable insight into the psychopathology of PTSD without additional data collection burden and should be widely adopted. Researchers should look to model PTSD both as a dichotomous variable and on a continuous scale, both as a complete construct and by each dimensional component. Third, while the exploration into discriminant validity builds on another study that found PTSD factor structure unstable in the presence of MDD item challenges, more research is needed here to understand the theoretic and empiric utility of the specified six-factor model across settings and diagnostic criteria. Fourth, while endeavoring to explore construct validity, exploratory qualitative methods with populations beyond the highly studied U.S. military populations are needed to propose additional items that could, provide valuable missing empiric evidence for PTSD factor dimensionality.

Thesis. 1975. M.S.--Massachusetts Institute of Technology. Dept. of Civil Engineering. / Bibliography: leaf 106. / by Joseph Parker Morray, Jr. / M.S.

The insurance industry relies on both commercial and in-house software packages to quantify financial risk to natural hazards. For earthquakes, the initial loss estimates from the industry’s catastrophe risk (CAT) models are based on the probabilistic damage a building would sustain due to a catalog of simulated earthquake events. Based on the occurrence rates of the simulated earthquake events, an exceedance probability (EP) curve is calculated, which provides the probability of exceeding a specific loss threshold. Initially these loss exceedence probabilities help a company decide what insurance policies are most cost efficient. In addition they can also provide insights into loss predictions in the event that an actual natural disaster takes place, thus the insurance company is prepared to pay out their insured parties the necessary amount. However, there is always an associated uncertainty with the loss calculations produced by these models. The goal of this research is to reduce this uncertainty by using Bayesian inference with real time earthquake data to calculate an updated loss. Bayes theory is an iterative process that modifies the loss distribution with every piece of incoming information. The posterior updates are calculated by multiplying a baseline prior distribution with a likelihood function and normalization factor. The first prior is the initial loss distribution from the simulated events database before any information about a real earthquake is available. The crucial step in the update procedure is defining a likelihood function that establishes a relative weight for each simulated earthquake, relating how alike or dislike the attributes of a simulated earthquake are to those of a real earthquake event. To define this likelihood function, the general proposed approach is to quantify real time earthquake attributes such as magnitude, location, building tagging and damage, and compare them to an equivalent value for each simulated earthquake from the CAT model database. In order to obtain the simulated model parameters, the catastrophe risk model is analyzed for different building construction types, such as steel and reinforced concrete. For every model case, the loss, peak ground acceleration per building and simulated event magnitude and locations are recorded. Next, in order to calculate the real earthquake attributes, data was collected for three case studies, the 7.1 magnitude 1997 Punitaqui, the 8.8 magnitude 2010 Chile earthquake and the 6.7 magnitude 1994 Northridge earthquake. For each of these real earthquake events, the magnitude, location, peak ground acceleration at every available accelerometer location, building tagging and qualitative damage descriptions were recorded. Once the data was collected for both the real and simulated events, they were quantified so they could be compared on equal scales. Using the quantified parameter values, a likelihood function was defined for each update step. In general, as the number of updates increased, the loss estimates tended to converge to a steady value for both the medium and large event. In addition, the loss for the 6.7 and 7.1 event converged to a smaller value than that of the 8.8 event. The proposed methodology was only applied to earthquakes, but is broad enough to be applied to any type of peril.

No Chile, país de terremotos, a surpresa foi total quando multitudinários saques a estabelecimentos comerciais começaram logo depois do megassismo que atingiu, na madrugada de sábado 27 de fevereiro de 2010, Concepción, a terceira maior área metropolitana do país. Organizaram-se nos bairros estratégias de autodefesa por temor aos rumores sobre a chegada de saqueadores. Para se restabelecer a ordem social, foi decretado Estado de Exceção. Este estudo exploratório e qualitativo busca enxergar a relação entre terremoto, violência coletiva e insegurança urbana com base nos depoimentos de homens e mulheres que entrevistamos em Concepción dois anos depois do cataclismo. Inspirados no debate teórico sobre a memória coletiva, analisaremos os silêncios e olvidos que fazem parte dos testemunhos; assim, iremos interrogar o caráter inédito que os entrevistados, mas também acadêmicos e autoridades, outorgaram aos saques pós-terremoto, que, como iremos ver, foram interpretados como sintoma do deterioramento moral da sociedade chilena sob o regime neoliberal. Por intermédio de diferentes registros do passado, buscaremos rastros sobre conflitos sociais e políticos em outros momentos da história telúrica nacional. Sobre os episódios de 2010 em específico, e seguindo os trabalhos de Charles Tilly e Javier Auyero, apresentamos numa escala microespacial alvos, dinâmicas e repertórios dos saques conforme as rememorações dos consultados, entre eles, donos de lojas vitimizados pela multidão. Por fim, para indagar o deslocamento do medo do terremoto ao medo dos outros, chamaremos a atenção sobre os modos pelos quais são representados diferentes bairros da cidade e o papel dos rumores. / Chileans, a population used to earthquakes, woke up with surprise in the morning of February 27th, 2010 since right after the earthquake that hit Concepción, the third largest metropolitan area in the country, massive looting to stores came about. Fed by rumors about roving mobs, Concepcion residents formed their own neighborhood defense squads to guard their homes, whereas the Chilean government declared State of Exception to restore the social order. Drawing on testimonies of men and women I interviewed in Concepción two years after the disaster, this exploratory and qualitative research examines the relationship between earthquake, collective violence, and urban insecurity. Following a theoretical discussion about collective memories, I explore how silence and forgetting are active elements in the process of collective remembering. In addition, this project analyzes the sense of exceptionality that my interviewees, other scholars, and state authorities have assigned to looting in the aftermath of the earthquake; events that, as I shall demonstrate, were interpreted as a symptom of moral decadence of Chilean society under the neoliberal regime. By scrutinizing historical data about past earthquakes, I look at traces of social and political conflicts associated with the occurrence of natural disaster like the one I describe here. Concerning the 2010 facts, I make use of the framework offered by Charles Tilly and Javier Auyero to present, at a micro-scale level, looting targets, dynamics and repertoires based on narratives collected empirically (among them, testimonies of storeowners who were victimized by the crowd). Finally, to explore the displacement of fearin particular, from the fear to earthquake to the fear of the othersI point out the need to pay attention to the ways in which different neighborhoods are conceived of as well as the role of rumors.

My work focused on the development of improved methodologies for the evaluation of seismic hazard and its related uncertainties, based on the study of active faults systems and dynamic modelling of the seismic cycle. I worked in particular on the probabilistic estimate of a fault's maximum magnitude earthquake and of its return period. Those parameters are indeed crucial to estimate seismic hazard. Seismicity can be viewed as a stochastic process which is constrained by the principle of moment conservation: seismic ruptures must in principle rupture fault portions which had accumulated a deficit of slip, in view of their long term slip rate, during the interseismic period. In Chapter 1, I explain how we implemented those constraints in the evaluation of the probability distribution describing the magnitude and return period of the largest earthquake, propagating the geodetic uncertainties up to the hazard calculation. We applied this methodology to the Parkfield Segment of the San Andreas Fault, where the seismic cycle is particularly well documented. Our study implies potential maximum magnitude between 6.5 and 7.5, with a return period of 140 to 300 years. In Chapter 2, we applied the same methodology to the Cascadia subduction zone, known to have produced a M~9 earthquake in 1700 but where the seismic hazard remains poorly constrained. As part of this study we determined a model of interseismic coupling and of fault slip due to Slow Slip Events using an Independent Component Analysis-based inversion method. Finally, in Chapter 3, I use dynamic modelling to tackle the problem of partial ruptures. Large earthquakes tend to be confined to fault areas locked in the interseismic period but they often rupture them only partially. For example, during the 2015 M7.8 Gorkha earthquake, Nepal, a slip pulse propagating along-strike unzipped the bottom edge of the locked portion of the Main Himalayan Thrust. The lower edge of the rupture produced dominant high-frequency (>1 Hz) radiation of seismic waves. We showed that similar partial ruptures occur spontaneously in a simple dynamic model of earthquake sequences on a planar fault without mechanical, frictional and geometrical heterogeneities.

Liquefaction-induced settlements can cause a large economic toll on a region, from severe infrastructural damage, after an earthquake occurs. The ability to predict, and design for, these settlements is crucial to prevent extensive damage. However, the inherent uncertainty involved in predicting seismic events and hazards makes calculating accurate settlement estimations difficult. Currently there are several seismic hazard analysis methods, however, the performance-based earthquake engineering (PBEE) method is becoming the most promising. The PBEE framework was presented by the Pacific Earthquake Engineering Research (PEER) Center. The PEER PBEE framework is a more comprehensive seismic analysis than any past seismic hazard analysis methods because it thoroughly incorporates probability theory into all aspects of post-liquefaction settlement estimation. One settlement estimation method, used with two liquefaction triggering methods, is incorporated into the PEER framework to create a new PBEE (i.e., fully-probabilistic) post-liquefaction estimation procedure for the cone penetration test (CPT). A seismic hazard analysis tool, called CPTLiquefY, was created for this study to perform the probabilistic calculations mentioned above. Liquefaction-induced settlement predictions are computed for current design methods and the created fully-probabilistic procedure for 20 CPT files at 10 cities of varying levels of seismicity. A comparison of these results indicate that conventional design methods are adequate for areas of low seismicity and low seismic events, but may significantly under-predict seismic hazard for areas and earthquake events of mid to high seismicity.

Liquefaction-induced settlement can cause significant damage to structures and infrastructure in the wake of a seismic event. Predicting settlement is an essential component of a comprehensive seismic design. The inherent uncertainty associated with seismic events makes the accurate prediction of settlement difficult. While several methods of assessing seismic hazards exist, perhaps the most promising is performance-based earthquake engineering, a framework presented by the Pacific Earthquake Engineering Research (PEER) Center. The PEER framework incorporates probability theory to generate a comprehensive seismic hazard analysis. Two settlement estimation methods are incorporated into the PEER framework to create a fully probabilistic settlement estimation procedure. A seismic hazard analysis tool known as PBLiquefY was updated to include the fully probabilistic method described above. The goal of the additions to PBLiquefY is to facilitate the development of a simplified performance-based procedure for the prediction of liquefaction-induced free-field settlements. Settlement estimations are computed using conventional deterministic methods and the fully probabilistic procedure for five theoretical soil profiles in 10 cities of varying seismicity levels. A comparison of these results suggests that deterministic methods are adequate when considering events of low seismicity but may result in a considerable under-estimation of seismic hazard when considering events of mid to high seismicity.

Underground structures perform an important role in transportation systems in many seismically active regions around the world, but empirical data regarding the seismic behavior of these structures is limited. This research works towards filling that empirical gap through the use of scale model shake table testing. Underground seismic soil-structure interaction (USSSI) effects were investigated for a stiff rectangular tunnel cross-section embedded within soft clay. San Francisco Young Bay Mud was used as a prototype soil for developing a scale model soil mixture consisting of kaolinite, bentonite, class C fly ash, and water. A single cell Bay Area Rapid Transit (BART) cut-and-cover subway tunnel was used as the prototype for the 10th scale model subway cross-section. A flexible walled test container originally developed for a pile study at UC Berkeley was modified for use at Cal Poly, San Luis Obispo. The flexible container allows for close approximation of one-dimensional (1D) free-field site response by significantly limiting the rigidity of the boundary conditions and allowing the soil to deform under simple shear. The study was conducted over two shake table testing phases: Phase I consisted of shaking a model soil column to evaluate the ability of the test container to produce adequate 1D free-field site response, and Phase II tests explored the horizontal racking distortion of a shallow rectangular tunnel cross-section subjected to strong transverse ground shaking. Phase I test results and comparison with SHAKE models indicate that the test container can sufficiently mimic 1D free-field conditions, specifically for the primary shear deformation mode. Similarly, the equivalent linear soil-structure interaction code FLUSH was found to adequately model site response for the Phase II soil-structure system. Comparison of recorded horizontal racking distortions of the model structure with those from numerical modeling suggest that current simplified design methods may overestimate distortions to some degree for cases similar to those examined in this research. Overall, the flexible wall testing container shows promise as a viable means for gaining further insight into USSSI topics, as well as various other geotechnical and soil-structure interaction problems.