One of the most important data elements recorded in the National Automotive Sampling System / Crashworthiness Data System (NASS/CDS) is the vehicle change in velocity, or ?V. ?V is the vector change in velocity experienced by a vehicle during a collision, and is widely used as a measure of collision severity in crash safety research. The ?V information in NASS/CDS is used by the U.S. National Highway Traffic Safety Administration (NHTSA) to determine research needs, regulatory priorities, design crash test procedures (e.g., test speed), and to determine countermeasure effectiveness. The WinSMASH crash reconstruction code is used to compute the ?V estimates in the NASS/CDS. However, the reconstruction accuracy of the current WinSMASH version has not previously been examined for side impacts. Given the importance of side impact crash modes and the widespread use of NASS/CDS data, an assessment of the program's reconstruction accuracy is warranted. The goal of this thesis is to quantify the accuracy of WinSMASH ?V estimations for side impact crashes, and to suggest possible means of improving side impact reconstruction accuracy. Crash tests provide a wealth of controlled crash response data against which to evaluate WinSMASH. Knowing the accuracy of WinSMASH in reconstructing crash tests, we can infer WinSMASH accuracy in reconstructing real-world side crashes. In this study, WinSMASH was compared to 70 NHTSA Moving Deformable Barrier (MDB) - to - vehicle side crash tests. Tested vehicles were primarily cars (as opposed to Light Trucks and Vans, or LTVs) from model years 1997 - 2001. For each test, the actual ?V was determined from test instrumentation and this ?V was compared to the WinSMASH-reconstructed ?V of the same test. WinSMASH was found to systemically over-predict struck vehicle resultant ?V by 12% at time of vehicle separation, and by 22% at time of maximum crush. A similar pattern was observed for the MDB ?V; WinSMASH over-predicted resultant MDB ?V by 6.6% at separation, and by 23% at maximum crush. Error in user-estimated reconstruction parameters, namely Principal Direction Of Force (PDOF) error and damage offset, was controlled for in this analysis. Analysis of the results indicates that this over-prediction of ?V is caused by over-estimation of the energy absorbed by struck vehicle damage. In turn, this ultimately stems from the vehicle stiffness parameters used by WinSMASH for this purpose. When WinSMASH was forced to use the correct amount of absorbed energy to reconstruct the crash tests, systemic over-prediction of ?V disappeared. WinSMASH accuracy when reconstructing side crash tests may be improved in two ways. First, providing WinSMASH with side stiffness parameters that are correlated to the correct amount of absorbed energy will correct the systemic over-prediction of absorbed energy when reconstructing NHTSA side crash tests. Second, providing some treatment of restitution in the reconstruction process will correct the under-prediction of ?V due to WinSMASH's assumption of zero restitution. At present, this under-prediction partially masks the over-prediction of ?V caused by over-prediction of absorbed energy. If the over-prediction of absorbed energy is corrected, proper treatment of restitution will correct much of the remaining error observed in WinSMASH reconstructions of NHTSA side crash tests. / Master of Science

When a gas turbine operates in a particle laden environment, such as a desert, small solid particles are ingested into the engine. The ingested sand particles can cause damage to engine components and reduce the service life of the engine. Particle ingestion causes the erosion of metal blades and vanes, and, if the firing temperature is hot enough, deposition of molten particles in the hot sections of the engine. Both deposition and erosion phenomena can severely reduce overall engine performance. The Coefficient of Restitution (COR) is a measure of the particle-wall interaction, and has been widely used to quantify particle rebound characteristics in past particle impact studies. This work investigates the effects of temperature on sand particle impact characteristics by measuring the COR and other deposition related impact parameters. The first study presented as part of the dissertation contains a description of a novel method used to measure COR using a Particle Tracking Velocimetry (PTV) method. This is combined with Computational Fluid Dynamics (CFD) flow field to allow for an accurate determination of the particle impact velocity. The methodology described in this paper allows for measurement of the COR in a wide range of test conditions in a relatively simple manner. The COR data for two different sizes of Arizona Road Dust (ARD) and one size of glass beads are presented in this paper. Target material was stainless steel 304 and the impact angle was varied from 25 to 85 degrees. The second study details the first quantification of the COR of san particles at elevated temperatures. Temperatures used in this study were 533 K, 866 K, and 1073 K. In this study the mass flow rate through the experimental setup was fixed. This meant that velocity and temperature were coupled. Target material for this study was stainless steel 304 and the impact angle was varied from 30° to 80°. The COR was found to decrease substantially at the temperatures and velocity increased. It was determined that the decrease in COR was almost certainly caused by the increase in velocity, and not the decrease in temperature. The third study contains COR results at elevated temperatures. Significant improvements from the method used to calculate COR in the first paper are described. The particle used for these tests was an ARD sand of 20-40 μm size. Target materials used were stainless steel 304 and Hastelloy X. The particles impinged on the target coupon at a velocity of 28m/s. Tests were performed at three different temperatures, 300 K (ambient), 873 K, and 1073 K to simulate temperatures seen in gas turbine cooling flows. The angle of impingement of the bulk flow sand on the coupon was varied between 30° and 80°. A substantial decrease in COR was discovered at the elevated temperatures of this experiment. Hastelloy X exhibited a much larger decrease in COR than does stainless steel 304. The results were compared to previously published literature. The final study also used the ARD size of 20-40 μm. The target material was a nickel alloy Hastelloy X. Experiments for this study were performed at a constant velocity of 70m/s. Various temperatures ranging from 1073 K up to and including 1323 K were studied. Particle angle of impact was varied between 30° and 80°. Significant deposition was observed and quantified at the highest two temperatures. The COR of the ARD sand at the highest temperatures was found not to change despite the occurrence of deposition. At elevated temperatures, many of the particles are not molten due to sand's non-homogenous and crystalline nature. These particles rebound from the target with little if any change in COR. / Ph. D.

In this thesis, the complete design, fabrication, and calibration of an instrumented drop weight impact tester is described. Included in this description are all the sketches and drawings that are needed to duplicate this project, if so desired. This impact tester was built for around $23,000 less than it would have cost to buy and modify a commercial tester for the intended research application. This tester, as designed, was intended to be used in the field of impact location detection using artificial neural networks. Even though this impact tester was built for a specific research application, the design concepts that are presented can easily be adapted to a variety of testing needs. This impact tester was built using an non-working milling machine for a base. This provides a rigid, stable base along with a moveable X-Y table. The tester itself has the capability for drop weights ranging from 3.518 Ib up to 15.408 lb, and impact energy levels ranging from 0.6 ft-lb up to 45.6 ft-lb. Also, it is capable of impacting multiple locations of large plates with variable boundary condition sizes up to 12" x 24". Furthermore, it uses a computer program written using a data acquisition software package to provide output plots for the impact event, including the force and energy applied to the specimen versus time and the force versus displacement. Finally, initial experimental results obtained from this tester agree very well with those obtained from a commercially available tester, allowing it to be used in future tests involving intelligent material systems. / Master of Science

This thesis examines the economic impact of two alternative canning plant sizes in Scott County, Virginia. The impacts of a community cannery as well as a commercial cannery are analyzed with respect to changes in output, employment, and income. Several uses for the commercial cannery are considered, such as specialization in different product categories. In both cases, an input-output model is used to evaluate the effects of the operation of the cannery in the county. The results indicate that the impact of the commercial cannery is significantly larger than the community cannery. Specialization of the commercial cannery in the Canned Specialties sector has the largest impact with respect to industry output and labor income while specialization in the Sausages and Other Prepared Meats sector has the largest impact with respect to employment. / Master of Science

Detailed information about negative effects of fine sediments on early life stages of brook trout (Salvelinus fontinalis) in southern Appalachian streams is lacking. Information on survival to different stages of egg and alevin development could indicate critical timing of sediment impacts. This study was designed to determine the effects of fine sediments (0.43-0.85 rom in diameter) on survival of brook trout eggs through early development stages under controlled laboratory and field conditions. Recently fertilized eggs were loaded into Whitlock-Vibert (W-V) boxes lined with 0.4 rom Nitex netting that contained mixtures of gravel and fine sediments. Survival to eyed, hatched, and emerged stages of development was determined for six amounts of fine sediment (0-25% by weight) in the laboratory study and for three amounts of fine sediment (0-20% by weight) in the field study. Survival in laboratory systems to each stage of development was inversely related to the percentage of fine sediment; even at low levels of fine sediment survival was reduced. In the field study, fine sediment may have played a role in the survival success of developing embryos, but determining a definitive relationship was confounded by effects of scouring flows and fungal infestations. The fungus Saprolegnia spp., may have increased the mortality rate of viable eggs and facilitated the disintegration of nonviable embryos, especially in the field study. Brook trout are sensitive to increasing levels of fine sediment through early development. However under field conditions such an effect may be difficult detect. / Master of Science

Mild traumatic brain injury in snowsports is a prevalent concern. With as many as 130,000 hospitalized injuries in the U.S. associated with snowsports in 2017, head injury constitutes about 28% and is the main cause of fatality. Studies have found that a combination of rotational and linear velocities is the most mechanistic way to model brain injury, but despite decades of research, the biomechanical mechanisms remain largely unknown. However, evidence suggests a difference in concussion tolerance may exist between athlete populations. To improve the ability to predict and therefore reduce concussions, we need to understand the impact conditions associated with head impacts across various sports. There is limited research on the conditions associated with head impacts in snowsports. These head impacts often occur on an angled slope, creating a normal and tangential linear velocity component. Additionally, the impact surface friction in a snowsport environment is highly variable, but could greatly influence the rotational kinematics of head impact. Currently helmet testing standards don't consider these rotational kinematics, or varying friction conditions that potentially occur in real-world scenarios. The purpose of this study is to investigate the head impact conditions in a snowsport environment to inform laboratory testing and evaluate snow helmet design. We determined head impact conditions through video analysis to determine the impact locations, mechanism of fall, and the kinematics pre-impact. We used these data to develop a test protocol that evaluates snowsport helmets in a realistic manner. Ultimately, the results from this research will provide snowsport participants unbiased impact data to make informed helmet purchases, while concurrently providing a realistic test protocol that allows for design interventions to reduce the risk of injury. / Master of Science / Mild traumatic brain injury in snowsports is a prevalent concern. With as many as 130,000 hospitalized injuries in the U.S. associated with snowsports in 2017, head injury constitutes about 28% and is the main cause of fatality. Studies have found that a combination of rotational and linear velocities is the most mechanistic way to model brain injury, but despite decades of research, the biomechanical mechanisms remain largely unknown. However, evidence suggests a difference in concussion tolerance may exist between athlete populations. To improve the ability to predict and therefore reduce concussions, we need to understand the impact conditions associated with head impacts across various sports. There is limited research on the conditions associated with head impacts in snowsports. These head impacts often occur on an angled slope, creating a normal and tangential linear velocity component. Additionally, the impact surface friction in a snowsport environment is highly variable, but could greatly influence the rotational kinematics of head impact. Currently helmet testing standards don't consider these rotational kinematics, or varying friction conditions that potentially occur in real-world scenarios. The purpose of this study is to investigate the head impact conditions in a snowsport environment to inform laboratory testing and evaluate snow helmet design. We determined head impact conditions through video analysis to determine the impact locations, mechanism of fall, and the kinematics pre-impact. We used these data to develop a test protocol that evaluates snowsport helmets in a realistic manner. Ultimately, the results from this research will provide snowsport participants unbiased impact data to make informed helmet purchases, while concurrently providing a realistic test protocol that allows for design interventions to reduce the risk of injury.

One of the most painful events in life that an adolescent can face is the loss of someone with whom they had a strong emotional attachment (Harvey, 2002). This loss could be a friend, relative, parent, or any person that was strongly attached to the adolescent. In today's literature, there is a lack of attention given to adolescents, college students in particular who experience loss. This retrospective study consisted of 224 university students who had lost someone during adolescence or preadolescence. I examined if the impact of the stress accompanied by the loss and the coping strategies used to deal with loss differed by gender and the time in which students experienced their loss. Results from this study indicate that gender plays a significant role in both coping behaviors and the impact of the loss on the individual. In particular, females were found have more coping behaviors and felt a higher degree of impact of the loss than males. Another variable that played a significant factor in this study was the time of loss, early or later in life. Those students who experienced their loss later in life (between 13-19) were impacted more than those who experienced their loss early in life (between 5-12). However, time of loss did not play a role in the individual coping behaviors exhibited. / Master of Science

Public agricultural research has been conducted in Africa for decades and has generated numerous crop technologies, while little is understood on how agricultural research affects the poor and vulnerable groups such as children, and how farmers' perceptions affect their adoption decisions. This dissertation helps fill this gap with three essays on adoption and impacts of improved maize varieties in rural Ethiopia. The first essay estimates poverty impacts. Field-level treatment effects on yield and cost changes with adoption are estimated using instrumental variable techniques, with treatment effect heterogeneity fully accounted for in marginal treatment effect estimation. A backward derivation procedure is then developed within an economic surplus framework to identify the counterfactual income distribution without improved maize varieties. Poverty impacts are estimated by exploiting the differences between the observed and counterfactual income distributions. Improved maize varieties have led to 0.8-1.3 percentage drop in poverty headcount ratio and relative reductions in poverty depth and severity. However, poor producers benefit the least from adoption due to their small land holdings. The second paper assesses the impacts on child nutrition outcomes. The conceptual linkage between maize adoption and child nutrition is first established using an agricultural household model. Instrumental variable (IV) estimation suggests the overall impacts to be positive and significant. Quantile IV regressions further reveal that such impacts are largest among the most severely malnourished. By combining a decomposition procedure with estimates from a system of equations, it is found that the increase in own-produced maize consumption is the major channel such impacts occur. The third paper explores how farmers' perceptions of crop traits affects their willingness to adopt improved maize varieties. Under a random utility framework, a mixed logit procedure is implemented to model farmer's adoption intention, where perceptions of key varietal traits are first identified, and then instrumented using a control function approach to account for potential endogeneity. Perceived yield is found to be the most important trait affecting farmers' adoption intention. Further, yield perceptions among previous adopters appear to be affected by within-village peer effects rather than the real crop performance. / Ph. D.

New agricultural technologies can improve productivity to meet the increased demand for food that places pressure on agricultural production systems in developing countries. Because technological innovation is one of major factors shaping agriculture in both developing and developed countries, it is important to identify factors that help or that hinder the adoption process. Adoption analysis can assist policy makers in making informed decisions about dissemination of technologies that are under consideration. It is also important to estimate the impact of a technology. This dissertation contains three essays that estimate factors affecting integrated pest management (IPM) adoption and the impact of IPM on sweet gourd farming in Bangladesh. The first essay estimates factors that affect the timing of IPM adoption in Bangladesh. It employs duration models, fully parametric and semiparametric, and (i) compares results from different estimation methods to provide the best model for the data, and (ii) identifies factors that affect the length of time before Bangladeshi farmers adopt an agricultural technology. The paper provides two conclusions: 1) even though the non-parametric estimate of the hazard function indicated a non-monotone model such as log-normal or log-logistic, no differences are found in the sign and significance of the estimated coefficients between the non-monotone and monotone models. 2) economic factors do not directly influence the adoption decision but rather factors related to information diffusion and farmer's non-economic characteristics such as age and education. Particularly, farmer's age and education, membership in an association, training, distance of the farmer's house from local and town markets, and farmer's perception about the use of IPM affect the length of time to adoption. Farm size is the only variable closely related to economic factors that is found to be significant and it decreases the length of time to adoption. The second paper measures Bangladeshi farmers' attitudes toward risk and ambiguity using experimental data. In different sessions, the experiment allows farmers to make decisions alone and communicate with peers in groups of 3 and 6 to see how social exchanges among peers affect attitudes toward uncertainty. Combining the measured attributes to household survey data, the paper investigates the factors affecting those attributes as well as the role of risk aversion and ambiguity aversion in technology choice by farmers who: face uncertainty alone, in a group of 3, or in a group of 6. It finds that Bangladeshi farmers in the sample are mostly risk and ambiguity averse. Their risk and ambiguity aversion, moreover, differ when they face the uncertain prospects alone from when they can communicate with other peer farmers before making decisions. In addition, farmer's demographic characteristics affect both risk and ambiguity aversion. Finally, findings suggest that the roles of risk and ambiguity aversion in technology adoption depend on which measure of uncertainty behavior is incorporated in the adoption model. While risk aversion increases the likelihood of technology adoption when farmers face uncertainty alone, only ambiguity aversion matters and it reduces the likelihood of technology adoption when farmers face uncertainty in groups of three. Neither risk aversion nor ambiguity aversion matter when farmers face uncertainty in groups of six. The third paper presents an impact assessment of integrated pest management on sweet gourd in Bangladesh. It employs an instrumental variable and marginal treatment effects approach to estimate the impact of IPM on yield and cost of sweet gourd in Bangladesh. The estimation methods consider both homogeneous and heterogeneous treatment effects. The paper finds that IPM adoption has a 7% - 34% yield advantage over traditional pest management practices. Results regarding the effect of IPM adoption on cost are mixed. IPM adoption alters production costs from -1.2% cost to +42%, depending on the estimation method employed. However, most of the cost changes are not statistically significant. Therefore, while we confidently argue that the IPM adoption provides a yield advantage over non-adoption, we do not find a robust effect regarding a cost advantage of adoption. / Ph. D.

Pre-disaster damage predictions and post-disaster damage assessments are challenging because they result from complicated interactions between multiple drivers, including exposure to various hazards as well as differing levels of community resiliency. Certain societal characteristics, in particular, can greatly magnify the impact of a natural hazard, however they are frequently ignored in disaster management because they are difficult to incorporate into quantitative analyses. In order to more accurately identify areas of greatest need in the wake of a disaster, both the hazards and the vulnerabilities need to be carefully assessed since they have been shown to be positively correlated with damage patterns. This study evaluated the contribution of eight drivers of structural damage from Hurricane Mar'ia in Puerto Rico, leveraging machine learning algorithms to determine the role that societal factors played. Random Forest and Stochastic Gradient Boosting Trees algorithms analyzed a diverse set of data including wind, flooding, landslide, and vulnerability measures. These data trained models to predict the structural damage caused by Hurricane Mar'ia in Puerto Rico and the importance of each predictive feature was calculated. Results indicate that vulnerability measures are the leading predictors of damage in this case study, followed by wind, flood, and landslide measures. Each predictive variable exhibits unique, often nonlinear, relationships with damage. These results demonstrate that societal-driven vulnerabilities play critical roles in damage pattern analysis and that targeted, pre-disaster mitigation efforts should be enacted to reinforce household resiliency in socioeconomically vulnerable areas. Recovery programs may need to be reworked to focus on the highly impacted vulnerable populations to avoid the persistence, or potential enhancement, of preexisting social inequalities in the wake of a disaster. / Master of Science / Disasters are not entirely natural phenomena. Rather, they occur when natural hazards interact with the man-made environment and negatively impact society. Most risk and impact assessment studies focus on natural hazards (processes beyond human control) and do not incorporate the role of societal circumstances (within human agency). However, it has been shown that certain socioeconomic, demographic, and structural characteristics increase the severity of disaster impacts. These characteristics define the the susceptibility of a community to negative disaster impacts, known as vulnerability. This study quantifies the role of vulnerability via a case study of Hurricane Mar'ia. A variety of statistical modeling, known as machine learning, analyzed flood, wind, and landslide hazards along with the aforementioned vulnerabilities. These variables were correlated with a damage assessment database and the model calculated the strength of each variable's relationship with damage. Results indicate that vulnerability measures exhibit the strongest predictive correlations with the damage caused by Hurricane Mar'ia, followed by wind, flood, and landslide measures, respectively, suggesting that efforts to improve societal equality and improvements to infrastructure in vulnerable areas can mitigate the impacts of future hazardous events. In addition, societal information is critical to include in future risk and impact assessment efforts in order to prioritize areas of greatest need and allocate resources to those who would benefit from them most.