Rendering Light and Shadows for Transparent Objects

This masters thesis presents a new approach to enable complex illuminationand shadowing for transparent objects such as glass or smoke. This is achievedby combining two algorithms which are intended to run in a real-time environment commonly found in modern computer games. The first algorithm is called "Light Linked List", it solves the problem of illuminating transparent objects and was recently presented at the SIGGRAPH2014 conference. The second algorithm is used for shadow calculations and is a new take on the "Deep Shadow Maps" technique. Both algorithms use linked lists to a high degree. The lists are constructed on the GPU by taking advantage of recent hardware improvements and updates to the OpenGL API. By using these two algorithms together, we enable illumination and shadow casting of transparent object with a performance that allows for real-time frame rates.A big challenge in computer graphics is calculating light and shadows. Common methods today do not produce these correctly for transparent objects. The objective of this master thesis is to solve that

Analysis and Valorization of Bark from Silver Birch, Scots Pine, and Norway Spruce : Compositional analysis of bark from common Swedish trees in forestry, to optimize sustainability procedures and monetary value of bark residue

Silver birch, Scots pine, and Norway spruce are the three most common types of trees in Sweden and make up to 90% of standing volume in Swedish forests (Skogsstyrelsen 2015, 3). With millions of cubic meters of wood being cut down annually, bark and other residues that cannot be used for sawn timber is left over and burnt for energy. Since bark makes up ~10-15% of harvested volume, it is a prime target for valorization and could be incorporated into preexisting procedures or used as feedstock for new processes. Bark samples obtained from the above-mentioned tree species were characterized by analyzing the chemical composition and the susceptibility to hydrothermal pretreatment and enzymatic saccharification. The study helps to understand and compare the fundamental properties of the three bark materials and determine the potential for utilization in a biorefinery context. Chemical compositional analysis of the three bark types were performed. All bark types were high in ethanol extractives (mass fraction 23.6-27.4%, dry weight). Pine and spruce bark showed similarities in chemical composition with respect to arabinan (3.5-5.2%), galactan (2.0%), glucan (18.9%), mannan (1.9%), xylan (1.8%), total lignin (33.9%) and total ash (2.7-3.7%). However, the bark of birch varied mainly in the composition of lignin and carbohydrate content, i.e., arabinan (2.5%), galactan (1.2%), glucan (8.1%), mannan (0.8%), xylan (3.3%), total lignin (50.2%) and total ash (2.0%). Hydrothermal pretreatment at a lower combined severity (CS 2.5) seems to be more efficient for birch bark than at CS 3.3. However, the bark material of the softwood species seemed to be more susceptible to enzymatic saccharification than the hardwood species. There was a clear differentiation in the chemical composition of the hardwood and softwood bark material. Birch bark was rich in ethanol extractives, total lignin or lignin-like substances, and hemicelluloses (especially xylan). Whereas pine and spruce bark has higher fractions of ash and glucan. Comparison of the effect of enzymatic hydrolysis between samples showed clear increases in glucose concentration over time for pine and spruce. However, values for birch were much lower as it was more recalcitran

Analysis and Valorization of Bark from Silver Birch, Scots Pine, and Norway Spruce : Compositional analysis of bark from common Swedish trees in forestry, to optimize sustainability procedures and monetary value of bark residue

Silver birch, Scots pine, and Norway spruce are the three most common types of trees in Sweden and make up to 90% of standing volume in Swedish forests (Skogsstyrelsen 2015, 3). With millions of cubic meters of wood being cut down annually, bark and other residues that cannot be used for sawn timber is left over and burnt for energy. Since bark makes up ~10-15% of harvested volume, it is a prime target for valorization and could be incorporated into preexisting procedures or used as feedstock for new processes. Bark samples obtained from the above-mentioned tree species were characterized by analyzing the chemical composition and the susceptibility to hydrothermal pretreatment and enzymatic saccharification. The study helps to understand and compare the fundamental properties of the three bark materials and determine the potential for utilization in a biorefinery context. Chemical compositional analysis of the three bark types were performed. All bark types were high in ethanol extractives (mass fraction 23.6-27.4%, dry weight). Pine and spruce bark showed similarities in chemical composition with respect to arabinan (3.5-5.2%), galactan (2.0%), glucan (18.9%), mannan (1.9%), xylan (1.8%), total lignin (33.9%) and total ash (2.7-3.7%). However, the bark of birch varied mainly in the composition of lignin and carbohydrate content, i.e., arabinan (2.5%), galactan (1.2%), glucan (8.1%), mannan (0.8%), xylan (3.3%), total lignin (50.2%) and total ash (2.0%). Hydrothermal pretreatment at a lower combined severity (CS 2.5) seems to be more efficient for birch bark than at CS 3.3. However, the bark material of the softwood species seemed to be more susceptible to enzymatic saccharification than the hardwood species. There was a clear differentiation in the chemical composition of the hardwood and softwood bark material. Birch bark was rich in ethanol extractives, total lignin or lignin-like substances, and hemicelluloses (especially xylan). Whereas pine and spruce bark has higher fractions of ash and glucan. Comparison of the effect of enzymatic hydrolysis between samples showed clear increases in glucose concentration over time for pine and spruce. However, values for birch were much lower as it was more recalcitran