The conventional signalized diamond interchange provides numerous essential freeway-to-arterial connections. However, it tends to become operationally inefficient when high traffic demands exist on the arterial or off-ramps. To address this problem, diverging diamond interchanges (DDIs) have been implemented at many sites to replace conventional diamond interchanges (CDIs). While DDIs have been shown to outperform CDIs under high left-turn demands, their operational performance diminishes when through demands on the arterial become heavy. In this work, I proposed a new service interchange design named the “one-sided diverging diamond interchange” (one-sided DDI) as a replacement for congested CDIs and DDIs. Through a comprehensive series of microscopic simulation tests with the software PTV Vissim, I analyzed and compared the operational attributes of the one-sided DDI to those of the CDI and DDI over a range of traffic demands. Overall, the results from the simulation tests indicate that the one-sided DDI significantly outperforms both the CDI and DDI in vehicle travel time and throughput when through demands on the arterial are dominant. On the other hand, the one-sided DDI tends to modestly outperform the traditional DDI in travel time when handling moderate to high proportions of left-turning traffic.

Following a seismic event, the serviceability of buildings, bridges and other infrastructure is critical. However, determining the safety of these structures post-disaster is challenging and time consuming. Most damage assessment is done through visual inspection, which can miss structural damage that is hidden from view, behind architectural elements or in hard to access areas. To improve the efficiency of post-earthquake damage assessment, low-cost sensors that could monitor structures and send alerts of significant damage would be invaluable. One specific example of critical damage would be that of steel fracture, which significantly impacts the safety of steel and reinforced concrete structures. Fractures are highly energetic, creating a distinctive gunshot-like sound. Microphones are already used to detect gun fire, and a similar methodology could be employed to detect and locate fractures in buildings. This project explored this possibility. A database of fracture sounds from experimental tests of structural components was built from a variety of sources, including an online research repository maintained by the National Hazards Engineering Research Infrastructure (NSF-NHERI). Specific features of the audio signals, for example Mel-frequency and linear predictive coefficients, were used to train machine learning algorithms  to classify these sounds and detect fractures. Physical experiments were also conducted to record rebar fractures using an array of low-cost microphones. The placement of the microphones and the difference in arrival times were used to estimate the location of the fractures, which were compared to the true location. This research constitutes the first step in the development of a robust acoustical monitoring strategy to aid in efficiently making decisions to restrict service to compromised structures following an earthquake. This concept is becoming increasingly viable as the availability of inexpensive instruments increases. As sensors improve, this approach could become the prevailing method for post-event assessment.

Wildfire smoke contains fine, inhalable particles called PM2.5, as well as dangerous levels of heavy metals and other toxins. Wildfire smoke can increase emergency room visits for asthma and upper respiratory infections in kids, reduce immune function, lead to cardiovascular and lung diseases later in life, and create long-term cancer risks. When schools close from wildfire smoke, learning loss and lost school days can affect children’s health and wellbeing throughout the rest of their lives. Low-income kids could be left without access to learning resources, meals, or school support services. Installing, improving, and maintaining HVAC (Heating, Ventilation, and Air Conditioning) systems is critical for mitigating exposure to smoke, as well as other emerging challenges. The state does not keep records of the ventilation systems in California’s 10,000 public schools or which schools might need additional support in funding their HVAC. I calculated the cost estimate of installing, maintaining, and upgrading HVAC systems to all K-12 schools in California. Methods I conducted include gathering data from the county Superintendent of education, emailing school admins listed on the California Department of State database, calling over 700 school districts for data collection, and consulting with HVAC contractors and other partners. The estimate for installation, maintenance, and upgrading cost is approximately $4.0 billion. The estimate will be used to advocate for further funding for wildfire preparedness for schools. Results will be used in the policy roadmap for implementing the Green New Deal for Public Schools in California and policy brief.

This research project will focus on the measurement of the influence of the fibers on the strength of fiber-reinforced concrete (FRC), examining both the experimental method used and the theoretical background needed to extract the salient material properties. Here, the primary interest is in the tension strength. The stress-strain relationship of most engineering materials is determined with direct compression and tension tests. However, this method proves to be unsuitable for testing the tension strength of FRC due to various factors. In this research project, we will determine the stress-strain relationship of FRC using a flexural beam test. The beam test is considered more reliable because the load can be controlled better than in the direct tension test, and stress concentrations and eccentricities can more easily be avoided. However, the experimental results must be combined with theory to extract relevant information. In structural analysis and design, it is common practice to begin with a known stress-strain relationship and the dimensions of a beam section and integrate to determine curvature for a sequence of moments. Our approach is the reverse of this process. Using a system of differential equations relating strains, moments, and axial stresses, and with strain measurements from the top and bottom midspans of the beam, we intend to inversely develop the stress-strain relationship of FRC in compression and tension through differentiation of a polynomial regression. We expect results to indicate that fiber-reinforced concrete has a higher residual strength than what is currently accepted and that our testing procedure will yield more accurate and valuable results than traditional tests. These findings could change the way cementitious materials are tested and improve efficiency in the built environment thereby decreasing carbon emissions. This presentation will highlight the steps, challenges, results, and implications of our project.

The Strand Lab Formaldehyde Team studied the use of genetically engineered houseplants to reduce indoor air pollution. Our goal was to make these houseplants accessible to the public, provide environmentally friendly décor, while also making homes safer. Formaldehyde is a ubiquitous carcinogenic chemical found in homes across the world. The houseplants are genetically engineered to express the enzyme formaldehyde dehydrogenase (FALDH) cloned from bacterium Brevibacillus brevis. FALDH oxidizes formaldehyde to harmless formate. Our houseplant, Epipremnum aureum, commonly known as pothos ivy, was chosen for its ease of growth, for its susceptibility to genetic manipulation, and for its inability to flower, which prevents the uncontrolled spread of genetically engineered plants. We tested the abilities of these houseplants to remove formaldehyde from the air. With the use of a flow through bioreactor and high pressure liquid chromatography (HPLC) we determined that formaldehyde was removed more rapidly by genetically engineered pothos ivy compared to the wild-type. By using the bioreactor with a permeation chamber to dose the inflowing air with trace amounts of formaldehyde we exposed the plants to concentrations of formaldehyde typical of those found in homes. We also used 2,4-dinitrophenylhydrazine (DNPH) traps to concentrate the formaldehyde in the effluent of the bioreactor for injection onto the HPLC. Thus, we were able to determine whether and with what rates the genetically engineered plants removed and degraded formaldehyde.