The drying of limestone is usually done industrially in a rotary drum dryer. The purpose of this project is to generate a model that will predict limestone particle motion as it passes through the dryer.  By creating an accurate model of the particle movement during the drying cycle, the operator will be able increase the dryer’s efficiency.  Using basic physics and through experimental testing, our team was able to produce a model that will provide detail of particle motion inside the dryer.

The Mississippi River Delta is the 7th largest river delta on Earth that consists of the Mississippi River and the Gulf of Mexico. Additionally, it contains 40% of the wetlands in the contiguous United States and over two million hectares (4,942,108 acres), an area equivalent to the size of two football fields, of agricultural lands. Due to fertilizer runoff from agricultural lands, the river delta has been experienced excess levels of nitrogen and phosphorus. The excess levels of these nutrients have contributed to water pollution in the delta and the hypoxia zone in the Gulf of Mexico. This research will focus on mapping the levels of nitrogen and phosphorous across the river delta to determine where the highest levels are

To understand wildlife ecology, one common strategy is a technique known as telemetry. This technique involves attaching radio-transmitters to animals. For volant species, such as bats, transmitters are attached to their backs with an adhesive. However, one issue is that it is easy for the bats to remove the transmitter. The loss of transmitters early in surveys is not only costly, but limits the amount of data that can be collected. Thus, there is a real need to extend the length of time a transmitter remains on a bat. To address this, we conducted a two-part behavioral observation study in the bat flight facility at TCU. In part 1 from April to September 2019, we tested 1) two currently available transmitter brands and 2) three different prototype designs to determine if the overall shape and size of the transmitter impacted the length of time they remained attached. We found that regardless of transmitter brand or design, the antennas incurred a significant amount of damage, suggesting the bats used the antennas to grab and pull them off. Thus, for part 2 from August to September 2020, we conducted a series of trials to establish the effectiveness of three coatings at preventing bats from damaging the antennas. We found that transmitters did not remain attached significantly longer with cayenne pepper, nail-biting deterrent, or Tabasco sauce on the antenna, suggesting that either 1) bats were not deterred by the three coatings we selected, or 2) bats may not be chewing the antennas or putting them in their mouths to provide leverage to remove them. Overall, our study revealed that bats can and will remove transmitters by grooming them off using the antennas and recommend that future research focuses on integrating the antenna into the body of the transmitter as a preventative measure.

Agricultural soils require the presence of three basic plant nutrients: Nitrogen, phosphorus, and Potassium (NPK). Each nutrient has its role in plant growth and their deficiencies have adverse effects. Therefore, detailed analysis was required to analyze whether soils from a lake were sufficient in terms of these nutrients and could be suggested for use as an agricultural soil amendment on a particular plot of land. Experimental study by way of specific chemical analysis methods (LOI, spectroscopy, etc.) looked at water content, pH, EC, SOC (Soil Organic Carbon), phosphorus and nitrogen content in the lake sediments; these values were used to determine what contents/nutrients in the lake sediments would need to be optimized for crops of interest. Results from the concluding experimental procedures would allow the property owner to effectively make use of their resources.

The Atlantic Forest, which extends over 17 Brazilian States, is one of the richest biomes in the world. Historically it has been a hot spot for biodiversity including endangered and endemic species. Despite this, only 15% of the forest’s original range remains. This loss is disproportionally distributed as 4 of the 17 states accounts for 90% of the loss. The source of this deforestation can be attributed primarily to logging developments and eucalyptus plantations. Through using public geodatabases, satellite imagery, and ArcGIS Pro we will show this forest loss and fragmentation in a visually accessible way.

Anxiety related to academics, especially with regards to testing, is a rapidly growing mental health issue impacting all undergraduates at TCU. High levels of test anxiety have been shown to inhibit memory recall, reduce exam scores, and promote poor study habits. Expressive writing is a form of test anxiety intervention consisting of a type of free response developed to allow students to release their minds of anxious thoughts and emotions related to exams. Expressive writing has been shown to reduce test anxiety and improve exam performance. However, the effectiveness of expressive writing may be mitigated by a students’ level of emotional intelligence. Emotional intelligence is defined as the capacity to be aware of, control, and express one’s emotions. In order to better understand the connection between emotional intelligence and expressive writing, I conducted an exploratory mixed-methods study using quantitative survey data to inform our selection of interview participants and the initial development of my interview protocol. Initially, to gain insight into students’ responses to the expressive writing prompt, I collected and coded expressive writing samples from GEOL 10113 students during the Fall of 2020. Prior to the beginning of the semester, I asked the students to complete a Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF) to assign a numerical value to their approximate emotional intelligence levels. Next, I stratified students by quartiles into high (Q3), medium (Q2), and low (Q1) emotionally intelligent groups. Then, GEOL 10113 students were asked to participate in focus group interviews, and volunteers were subsequently grouped by their TEIQue-SF score into three focus groups relating to the high, medium, and low emotional intelligence bins. Finally, using the focus group interview data and the selected student’s responses from the initial expressive writing exercise, I found that all of the student responses showed consistent differences between the three focus groups. Highly emotionally intelligent students had more positive experiences with the expressive writing exercise while lower emotionally intelligent students tended to have neutral or negative experiences with the activity. Overall, these data suggest that the level of emotional intelligence relates to how willing students were to convey their thoughts and emotions during the activity, which helped the higher emotionally intelligent students to have positive experiences with the writing exercise. The implications of my study are that while the efficacy of the expressive writing exercise is assumed, emotional intelligence is a confounding variable. Students must engage with it in some sort of authentic manner if they are to benefit from the exercise.

Solar energy is a significant contributor to the renewable energy mix. Many urban developments are making investments to install solar systems across feasible areas. The allocation of solar systems relies on the land’s geography and the amount of solar radiation received. The purpose of this study is to apply to determine the best sites for solar installations in urban areas. Using the TCU area of Fort Worth, Texas as a case study, this study will use ESRI’s ArcMap and ArcGIS Pro to estimate the solar power potential of different residential rooftops. The results will be useful in showing what households are most suitable for solar installation based on their expected energy yield.

Rapid industrialization and global population growth have increased the number of people living in urban areas worldwide. Developing countries, have seen tremendous increases in their industries over the past decades, which generated both positives and negative effects on their people, environment, and economy. One of the negative impacts of industrialization is industrial pollution and the increase in the number of pollutants released into the environment_ in this case, heavy metals. Heavy metal contamination is an alarming problem that many Developing countries are becoming aware of and trying to address. Heavy metal direct or indirect consumption may result in several health effects in the body, including damage and alteration of normal functioning of organs such as the brain, kidney, lungs, liver, and blood, which later result into acute or chronic diseases. This case study will look at heavy metal contamination cases in Rwanda in different drinking water sources. The focus of this case study will be on some common heavy metals released from industrial waste: Lead, Manganese, Iron, Cadmium, Zinc, and Chromium.

Teachers have experimented with the idea of virtual learning and its’ effects on student achievement. Due to the coronavirus pandemic, many schools and universities transitioned from traditional classroom-focused learning to asynchronous online learning. Asynchronous online learning is a type of instruction where online learning is not happening at the same time or place. Consequently, TCU made the abrupt transition in the Spring of 2021 to fully online asynchronous courses. To understand the magnitude of how remote learning can effect students’ academic success, my research project looks at what factors, including remote learning, can predict final grade utilizing GEOL 10113 student performance data and survey data from the spring semester of 2020 surveys. To investigate the impact of online learning, I tested several linear models to determine what confounders have a significant role in predicting students’ success in online and in remote learning. These models investigated which factors, ranging from demographic information to GPA, are significant predictors of both final grade and remote grade. I started the linear model selection process by testing a complex linear model, which had all the possible factors including interactions that can impact final grade or remote grade from the surveys. Once I knew which factors were significant from the complex model, I eliminated non-significant variables and created new models, comparing each model by their AIC values until I found the best-fit linear model for final grade and remote grade. AIC is a measurement of how well a linear model fits and the lower the AIC value the better fit the linear model has. After testing each linear model: GPA, students’ lecture section, remote grade, and exam average were significant to final grade. These models suggest that while remote grade is a significant predictor of final grade, no variable measured in this study is significant enough to impact remote grade. Differing from previous research, my results showed that there were no gaps in achievement amongst gender and underrepresented minority students. Although statistically no variable significantly impacted remote grade, there are trends amongst demographic variables and remote grade, suggesting some potential relationships that could be explored in future studies.

The reusing, recycling, and reduction of waste streams is seen as a viable sustainability strategy. One major waste stream is coffee grounds with about 11.5 million kilograms being generated per day in America of which 90% is landfilled. This waste stream can be repurposed into usable carbon-based materials to address issues of climate, pollution, or engineering applications. For my research, I am converting spent (used) coffee grounds into biochars, a type of carbon-based material, with different charring (burning) temperature to measure the removal of lead (Pb2+) from contaminated water. The charring temperature was changed in order to determine the optimal charring temperature for water treatment. This presentation will go into the maximum amount of lead the biochars can remove, how fast the biochars can remove the lead and the properties of biochars that allow for such removal. Further results, methodology, and modeling applications will be discussed in the presentation.