Ultraprecise Single Point Inverted Cutting of Right Triangular Prismatic Retroreflectors: Process Enhancements and Cutting Mechanics

Automotive lighting industry relies on retroreflective components to increase driver awareness in low-light conditions since their primary functionality is to return incident light back to the source and/or observer with minimal scatter. Presently, industry makes use of conventional pin-bundling techniques for the fabrication of the retroreflective components. This method is time consuming, labour intensive, and restrictive with respect to the design process. For these reasons, the ultraprecise single point inverted cutting (USPIC) technology was developed as an efficient alternative for manufacturing novel right triangular prismatic (RTP) retroreflective structures. This thesis outlines a number of enhancements that improve both the quality and productivity of the USPIC technology. Furthermore, in-depth analyses of the USPIC cutting mechanics uncovered both certain process characteristics as well as possible future investigational avenues. Cumulatively, these contributions define USPIC as a viable, efficient and versatile process to be further exploited in the fabrication of dissimilar retroreflective structures

Interdependence Between Tool Misalignment and Cutting Forces in Ultraprecise Single Point Inverted Cutting

Abstract Ultraprecise single point inverted cutting (USPIC) is a microfabrication technique that has been recently developed for the generation of micro-optical microstructures with sharp concave geometries. Among the multiple challenges encountered during the micromachining process, tool alignment represents one of the critical factors affecting the overall accuracy of the microstructure that in turn affects its optical functionality. Since none of the presently available tool alignment techniques was found to perform well in the particular context of the diamond insert used in USPIC, an in-depth analysis of its mechanics was used in this study to provide insight on the interdependence between cutting tool misalignment and cutting forces. For this purpose, an experimental setup was devised to record the 3D cutting forces generated during the fabrication of two representative concave geometries delimited by planar facets. The first test geometry represents an instance of an isolated right triangular prism (RTP) whose quality and optical functionality will be significantly affected by diamond insert misalignment, particularly due to the undesirable contact to occur between the secondary/lateral cutting edges of the tool and the optically nonfunctional RTP facets. By contrast, the second test geometry had both lateral facets removed, such that the cutting conditions obtained in this case could be regarded as similar with that of the classical orthogonal cutting setup. Direct comparisons of the cutting force profiles obtained for the two cutting scenarios enable unequivocal identifications of tool misalignment direction and magnitude, such that targeted corrective actions could be performed to address the issue

Axial strategy for ultraprecise single point cutting of V-grooves Case 1: constant chip thickness

47th SME North American Manufacturing Research Conference, NAMRC 47, June 10-14, 2019, Pennsylvania, US

Reduction of cutting forces by elliptical vibration in multi-pass ultraprecise single point axial cutting of V-grooves

48th SME North American Manufacturing Research Conference, NAMRC 48 (Cancelled due to COVID-19

Centimeter to decimeter hollow concretions and voids in Gale Crater sediments, Mars

Voids and hollow spheroids between ∼1 and 23 cm in diameter occur at several locations along the traverse of the Curiosity rover in Gale crater, Mars. These hollow spherical features are significantly different from anything observed in previous landed missions. The voids appear in dark-toned, rough-textured outcrops, most notably at Point Lake (sols 302-305) and Twin Cairns Island (sol 343). Point Lake displays both voids and cemented spheroids in close proximity; other locations show one or the other form. The spheroids have 1-4 mm thick walls and appear relatively dark-toned in all cases, some with a reddish hue. Only one hollow spheroid (Winnipesaukee, sol 653) was analyzed for composition, appearing mafic (Fe-rich), in contrast to the relatively felsic host rock. The interior surface of the spheroid appears to have a similar composition to the exterior with the possible exceptions of being more hydrated and slightly depleted in Fe and K. Origins of the spheroids as Martian tektites or volcanic bombs appear unlikely due to their hollow and relatively fragile nature and the absence of in-place clearly igneous rocks. A more likely explanation to both the voids and the hollow spheroids is reaction of reduced iron with oxidizing groundwater followed by some re-precipitation as cemented rind concretions at a chemical reaction front. Although some terrestrial concretion analogs are produced from a precursor siderite or pyrite, diagenetic minerals could also be direct precipitates for other terrestrial concretions. The Gale sediments differ from terrestrial sandstones in their high initial iron content, perhaps facilitating a higher occurrence of such diagenetic reactions

Long-term thermal sensitivity of Earth’s tropical forests

The sensitivity of tropical forest carbon to climate is a key uncertainty in predicting global climate change. Although short-term drying and warming are known to affect forests, it is unknown if such effects translate into long-term responses. Here, we analyze 590 permanent plots measured across the tropics to derive the equilibrium climate controls on forest carbon. Maximum temperature is the most important predictor of aboveground biomass (−9.1 megagrams of carbon per hectare per degree Celsius), primarily by reducing woody productivity, and has a greater impact per °C in the hottest forests (>32.2°C). Our results nevertheless reveal greater thermal resilience than observations of short-term variation imply. To realize the long-term climate adaptation potential of tropical forests requires both protecting them and stabilizing Earth’s climate

Consistent patterns of common species across tropical tree communities

Trees structure the Earth’s most biodiverse ecosystem, tropical forests. The vast number of tree species presents a formidable challenge to understanding these forests, including their response to environmental change, as very little is known about most tropical tree species. A focus on the common species may circumvent this challenge. Here we investigate abundance patterns of common tree species using inventory data on 1,003,805 trees with trunk diameters of at least 10 cm across 1,568 locations1,2,3,4,5,6 in closed-canopy, structurally intact old-growth tropical forests in Africa, Amazonia and Southeast Asia. We estimate that 2.2%, 2.2% and 2.3% of species comprise 50% of the tropical trees in these regions, respectively. Extrapolating across all closed-canopy tropical forests, we estimate that just 1,053 species comprise half of Earth’s 800 billion tropical trees with trunk diameters of at least 10 cm. Despite differing biogeographic, climatic and anthropogenic histories7, we find notably consistent patterns of common species and species abundance distributions across the continents. This suggests that fundamental mechanisms of tree community assembly may apply to all tropical forests. Resampling analyses show that the most common species are likely to belong to a manageable list of known species, enabling targeted efforts to understand their ecology. Although they do not detract from the importance of rare species, our results open new opportunities to understand the world’s most diverse forests, including modelling their response to environmental change, by focusing on the common species that constitute the majority of their trees.Publisher PDFPeer reviewe

The global abundance of tree palms

Aim Palms are an iconic, diverse and often abundant component of tropical ecosystems that provide many ecosystem services. Being monocots, tree palms are evolutionarily, morphologically and physiologically distinct from other trees, and these differences have important consequences for ecosystem services (e.g., carbon sequestration and storage) and in terms of responses to climate change. We quantified global patterns of tree palm relative abundance to help improve understanding of tropical forests and reduce uncertainty about these ecosystems under climate change. Location Tropical and subtropical moist forests. Time period Current. Major taxa studied Palms (Arecaceae). Methods We assembled a pantropical dataset of 2,548 forest plots (covering 1,191 ha) and quantified tree palm (i.e., ≥10 cm diameter at breast height) abundance relative to co‐occurring non‐palm trees. We compared the relative abundance of tree palms across biogeographical realms and tested for associations with palaeoclimate stability, current climate, edaphic conditions and metrics of forest structure. Results On average, the relative abundance of tree palms was more than five times larger between Neotropical locations and other biogeographical realms. Tree palms were absent in most locations outside the Neotropics but present in >80% of Neotropical locations. The relative abundance of tree palms was more strongly associated with local conditions (e.g., higher mean annual precipitation, lower soil fertility, shallower water table and lower plot mean wood density) than metrics of long‐term climate stability. Life‐form diversity also influenced the patterns; palm assemblages outside the Neotropics comprise many non‐tree (e.g., climbing) palms. Finally, we show that tree palms can influence estimates of above‐ground biomass, but the magnitude and direction of the effect require additional work. Conclusions Tree palms are not only quintessentially tropical, but they are also overwhelmingly Neotropical. Future work to understand the contributions of tree palms to biomass estimates and carbon cycling will be particularly crucial in Neotropical forests

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages