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ARCHITECTURAL DESIGN, BIM, AND ARTIFICIAL INTELLIGENCE: A REVIEW OF RULE-BASED AND MACHINE LEARNING APPLICATIONS
Get PDFArchitectural design projects can reach high complexity, long lists of requirements and intricate architectural programs, require effective ways to assess and predict building performance. Building Information Modeling (BIM) has proven to be a valuable tool in improving the design process by offering a range of resources for managing geometric data and building performance. However, BIM's current limitations, particularly in terms of geometry and function representation and its ability to predict performance, hinder its full potential. In this context, Artificial Intelligence (AI) is presented as an opportunity to enhance BIM workflows. AI's capabilities in prediction, automation, and analysis have the potential to improve design processes, offering more accurate simulations and predictions. This research explores how AI can be integrated into BIM-supported architectural design by conducting a case study using early-stage design AI tools, specifically Autodesk Forma. The study examines how AI-powered design tools can assist in the creation of building designs that meet specific performance criteria, such as energy efficiency, sustainability, and compliance with local regulations. Through this case study, the research aims to provide insights into how AI is helping to refine the BIM design process and to uncover the potential of AI in overcoming BIM's limitations. Ultimately, the findings will highlight the growing role of AI in architecture and offer perspectives on its future integration into design workflows
Bayesian Posterior Exploration and Predictive Analysis of Finite-Fault Earthquake Models
Get PDFAlthough earthquake rupture process is inherently complex, recent inversion techniques enable data-constrained physical models that image the spatiotemporal evolution of fault slip. Among these methods, Bayesian inversion framework yields an ensemble of plausible models to reproduce data, in contrast with conventional methods that produce a single best-fit solution. These posterior model ensembles are valuable for exploring relationships among physical parameters, generating downstream physical observables, and quantifying interlinked uncertainty structures. However, large ensembles (from thousands to millions) of high-dimensional models pose computational challenges. Here, we analyze inferred rupture properties and predictive observables of five Bayesian kinematic finite-fault models for large megathrust earthquakes in Japan, Chile, Ecuador and Nepal: 2011 Mw9.0 Tohoku, 2014 Mw8.1 Iquique, 2015 Mw8.3 Illapel, 2016 Mw7.8 Pedernales, and 2015 Mw7.8 Gorkha. We compare joint probability distributions of kinematic rupture parameters, including slip, rupture speed, rise time, and average slip rate, and assess relationships locally and fault-wise across events. We use posterior model ensembles to compute static surface deformation and on-fault stress changes, dynamic ground motion, and their spatiotemporal covariances. We find patch-level correlations are robust between some parameters given expected tradeoffs, but intra-event correlations between most parameters are variable across events. This result conflicts with predicted relations, e.g., between peak slip rate and rupture speed, established by dynamic rupture simulations, suggesting limitations in adopted physics and/or inversion approaches for heterogeneous rupture scenarios. Our static forward simulations reveal characteristic patterns in the predicted deformation and stress changes across the explored megathrust settings. The predicted surface deformation exhibits spatial variations in amplitude and direction largely inherited from source properties, whereas on-fault static stress is more heterogeneous in space. The variability in uncertainty is influenced by station coverage, source characteristics, and the data-model error structure. Despite source heterogeneity, the event-average static elastic strain drop is tightly constrained within ~100–300 microstrain, while static stress drop spans ~5–25 MPa. In the dynamic simulations, displacement waveforms stabilize earlier and faster in smaller earthquakes. Predicted peak ground displacements (PGD) exhibit near-field discrepancies with empirical scaling laws due to finite-source and directivity effects. Our findings can inform physics-based earthquake modeling and improve quantification of rupture complexity and hazard impacts
AN ANALYSIS OF RED SLIPPED CERAMICS FROM CLEMENT (34MC8): A MULTI-MOUND CENTER IN SOUTHEASTERN OKLAHOMA
No full textClement (34MC8) is a multi-mound ancestral Caddo center located in McCurtain County, Oklahoma. The site is comprised of at least two mounds, multiple structures, and midden areas. The site was first excavated by the WPA in 1941 and subsequently by the OU field school during the summer of 2008. The Clement site has an abundance of ceramics including extremely well-crafted red slipped ceramics which comprise about 30% of the total ceramic assemblage. The focus of this thesis is these red slipped ceramics. I analyzed 2,164 sherds for this study. Only diagnostic, rim or decorated, red slipped ceramics were included in this analysis. Physical attributes such as thickness, weight, decoration type, motifs, slip thickness, and slip color were recorded. LA-ICP-MS analysis was completed at the University of Missouri Nuclear Research Reactor (MURR) on thirty red slipped sherds and four possible pigment sources to understand the chemical composition and materials used in red slip. These attributes were recorded to better understand possible communities of practice among potters at Clement. The results of my analysis are used to understand slip groups based on composition, different usage of the site throughout time, purpose of red slipped ceramics at Clement, and production of red slipped ceramics. Through my analysis I aim to specifically answer the following questions: (1) What contexts are red slipped ceramics in at Clement? (2) How are red-slipped ceramics at Clement being made? (3) what does compositional analysis of red-slipped ceramics explain about communities of practice among potters at or around Clement
EFFICIENCY VERSUS EFFECTIVENESS: WHY DO NUCLEAR WEAPON PROGRAMS COST MORE AND TAKE LONGER THAN THEY DID DURING THE COLD WAR ERA?
No full textUnited States nuclear weapons are high reliability engineered systems managed by high reliability organizations that make up what is collectively referred to as the Nuclear Security Enterprise. In the Post-Cold War era, there was a monumental shift in nuclear weapons policy from increasing effectiveness of underground system testing, new design, and innovation to sustainment and enhancing fiscal efficiency through management controls. However, absent from high reliability systems and organizations literature are studies of effectiveness versus efficiency and the balance of management controls. Instead, the high reliability systems and organization literature describes intense concentrations in areas such as safety, security, reliability, error reporting, high functioning public-private partnerships, continuous organizational self-evaluation, mission-driven cultures, and specialized expertise as theoretical features leading to effective outcomes. Thus, this dissertation integrates a management controls reforms-as-routines framework into a Black Box Model of Implementation on a high reliability organization responsible for nuclear weapons to generate and explore an observational measure of labor resources spanning a 21 fiscal year timeframe. The output is utilized to explore the primary empirical research question: Over time, how have changes in reforms for management controls in the Post-Cold War Era impacted the distribution of resources across the Nuclear Security Enterprise? The empirical results illustrate a larger increase in the labor resources implementing management controls reforms than the technical resources responsible for the United States Nuclear Deterrence Mission. The results are useful to high reliability system and organization theorists as an empirical case study regarding the implications of shifting the balance between policy priorities of cost, schedule, and performance in a resource constrained environment. Furthermore, these results should inform policymakers and other high reliability organizations responsible for high reliability engineered systems in the United States that increasing management controls may not be the preferred mechanism to improving effectiveness of mission outcomes
A NEEDS ANALYSIS STUDY OF NON-STANDARD CERTIFIED OKLAHOMA CAREER TECHNOLOGY CENTER TEACHERS’ IMPRESSIONS OF SELF-EFFICACY IN CLASSROOM MANAGEMENT
No full textThis needs analysis, cross-sectional, observational study examined the relationship between Oklahoma Career Technology Center instructors’ certification type, standard vs. non-standard, and self-efficacy in classroom management. Thirty CTE teachers in nine of the twenty-nine Oklahoma Career Tech districts were surveyed using an adapted form of the Teachers’ Sense of Efficacy Scale (Tschannen-Moran & Hoy, 2001). Results indicate non-significant but conforming results for the classroom management portion of the TSES, Teachers’ Sense of Efficacy Scale among standard and non-standard Oklahoma Career Tech instructors. Though significance was not established, trends in these results align with broader findings in the field associated with K-12 teachers, and support implementation of programs to retain these second-career and/or non-standard certification teachers (SC/NCTs)
FAMILY AND INTERGENERATIONAL MOBILITY
No full textThis dissertation consists of three chapters focused on family and intergenerational mobility. Chapter 1 examines an under-explored determinant of intergenerational mobility: racial assortative mating. Our unique identification strategy leverages two historical events - changes in the marriageable Black population during the Second Great Migration and the landmark 1967 Supreme Court ruling in Loving v. Virginia. The interplay of these events presents exogenous shocks to marriage market conditions that are conducive to interracial marriages, thereby reducing racial assortative mating. We find a pronounced, negative relationship between racial assortative mating and mobility. We further show that the negative mobility impacts associated with assortative mating might be channeled through factors such as social network formations, neighborhood characteristics, and family structure. Finally, we also uncover a significant heterogeneity in the effects across the income distribution. The negative effects are more markedly pronounced for children from low-income families than for children from more affluent families. Such a pattern is consistent with the differential influence of alternative mechanisms across the income distribution. Chapter 2 explores the important role of environmental factors, specifically sunlight exposure, in shaping intergenerational educational mobility. Our findings reveal a significant and positive relationship between sunlight exposure and educational mobility, but this effect is predominantly driven by its influence on the educational mobility of sons. In contrast, sunlight exposure appears to have a negligible or even negative effect on daughters’ educational mobility. We suggest that these heterogeneous effects may be mediated by factors such as fertility rates, lifetime maternal mortality risk, mental health, and time preference. Specifically, individuals in regions with more sufficient sunlight exposure tend to experience higher fertility rates, a lower risk of maternal mortality, better mental health, and lower levels of patience. These factors may, in turn, influence parental investment in their children’s education, contributing to the observed gender-based heterogeneity in the impact of sunlight exposure on educational mobility. Child gender could affect not only intergenerational mobility but also family stability. In Chapter 3, we explore the heterogeneous effects of having a firstborn daughter on the likelihood of divorce using the causal forest method. Our causal forest model reveals substantial heterogeneity in the effect of daughters on divorce, with the mother’s age at first marriage being the most important factor driving this heterogeneity. The daughter effect varies significantly both across different maternal characteristics and over time. For mothers who were older than 30 at their first marriage, having a firstborn daughter significantly increased divorce risk, but this effect has diminished. Conversely, mothers who married at 25 or younger are increasingly likely to divorce after having a firstborn daughter. As for middle-married mothers, child gender has no significant impact on their likelihood of divorce. These patterns demonstrate the interplay of son preference and income constraints in shaping the daughter-divorce relationship. Compared to early-married mothers, late-married mothers are more susceptible to social pressure for sons but less impacted by child-rearing costs. Over time, as son preference has declined and the cost of raising daughters has increased, the positive daughter effect on divorce has shifted from being primarily driven by late-married mothers in the 1960-1969 childbirth cohorts to early-married mothers in the post-1980 childbirth cohorts
Hot Topics in Earth Science: Development and Evaluation of a Climate Change-Centered Professional Development Program for Secondary Science Teachers
No full textThere is a limited window to address global climate change (GCC) if we want to avoid the most severe impacts (Millar et al., 2017). This time window has almost closed, with little actual progress made toward significant changes in policy or consumption patterns. Simultaneously, misinformation and disinformation campaigns still influence the general understanding of GCC. The Next Generation Science Standards (NGSS) include the integration of climate change education into elementary and secondary science as a critical component (NGSS Lead States, 2013) but some states—such as Oklahoma—fail to meet the science standards set by NGSS (e.g. Colston & Ivey, 2015). Teachers might avoid these topics owing to several (perceived) barriers (Ennes et al., 2021; Li et al., 2021): 1. Time constraints 2. Lack of support (institutional, curricular, societal) 3. Complexity of the science In order to improve the teaching of climate change science, any professional development (PD) program that addresses climate change at the forefront of its topics should also seek to address these barriers by providing implementable resources and strategies. Hot Topics in Earth Science (HTES) was a PD developed for in-service secondary science teachers (Grades 6-12) in central Oklahoma. It had a dual focus on pedagogical and curricular approaches to teaching climate change science at the secondary level and the associated content. Techniques were discussed explicitly by facilitators and modeled by subject matter experts through content designed to challenge and broaden teachers’ conceptual understandings related to climate change science. Teachers were encouraged, with the support of science education personnel, to develop high-context lesson sequences to facilitate with their students throughout the academic year. Here we present a summary of our approach to the PD, samples of teacher products and responses over the course of the PD, and a reflection on successes and areas of improvement for similar PDs in the future
Investigating the Effects of Small Peptides on Amyloid Aggregation
No full textAmyloids, a class of protein aggregates, are highly stable elongated fibril structures. They areassociated with numerous diseases, such as Alzheimer’s, Parkinson’s, and type II diabetes. Following the COVID-19 pandemic, there have been numerous cases of individuals suffering with Long-COVID, whose symptoms overlap with common neurodegenerative and amyloid associated diseases. To explore the potential interactions between SARS-CoV-2 and amyloid proteins, two amyloidogenic protein fragments from SARS-CoV-2 were investigated with amylin, the amyloid protein associated with type II diabetes, and a-synuclein, associated with Parkinson’s. These investigations were performed utilizing all-atomistic molecular dynamics simulations in explicit solvent. Additionally, presented in this dissertation is research performed to identify and evaluate the effect of novel D-retro-inverso (DRI) peptides on mouse serum amyloid A3 (SAA3) fibril stability via virtual screening and molecular dynamics simulations
Enhancing Lost Circulation Control: Synergistic Effects of Cedar Fiber, Nutshell, and Sweeps on Filtration of Water-based Drilling Fluids
No full textThe effective management of lost circulation remains a critical challenge in drilling operations, necessitating the development of advanced strategies to minimize fluid loss and enhance wellbore stability. This study investigates the synergistic effects of various Lost Circulation Materials (LCMs) on fluid loss control and sealing efficiency.The study further demonstrates the efficacy of specific LCM combinations, such as cedar fiber, nutshell, and sweeps, in reducing filtration volume over time. The baseline for the experiments was drilling mud containing water, bentonite, nutshell, sweeps, and cedar fiber. Experiments were conducted by varying the concentrations of one of LCM components while maintaining the concentration of the other LCMs to assess the individual impact on filtration rates. The filtration tests were conducted using a permeability plugger tester (PPT). When the concentrations of each LCM have been increased the filtration volume significantly dropped down. Comparatively when cedar fiber concentration increased maximum (50%) reduction in filtration was obtained while the minimum (30%) filtration reduction was observed with sweeps addition. The smaller cedar particles were more effective in plugging the disk slot compared to nutshell and sweeps particles. Additionally, the results showed that cedar fiber reduced the filtration volume more efficiently than the other LCMs at all tested concentration