Sustainable Patterson

The Patterson School Foundation is a nonprofit organization located in Happy Valley, North Carolina. Originally, the Patterson School Foundation operated as a teaching school and farm However, they were forced to discontinue their educational mission in 2009 due to economic difficulties. The Patterson School has partnered with the Nicholas School of the Environment to gain insight regarding development opportunities for their property. Specifically, the Patterson School Foundation has requested an analysis of their property that would investigate the land’s potential for economic and sustainable development. Potential projects must be economical in order to avoid selling parts of their property as debt service. The request for sustainability stems from the Patterson School’s commitment to environmental stewardship. Our team sought to find recommendations that would utilize the preexisting resources at the Patterson School. The foundation has large amounts of land available for development and multiple existing buildings that are currently underutilized. Solutions that could more effectively utilize these resources include renewable energy development and transformation of the school into a sustainability destination. Due to the large amount of land resources available, our team was immediately attracted to renewable energies as a development strategy. However, our research uncovered many possible complications for these projects. First, large-scale solar is not an ideal project for the Patterson School. Large-scale solar energy development would require a large section of land to be dedicated to renewable energy development for multiple decades. The Patterson School is currently not comfortable setting aside large tracts of land for such a long period of time. Similarly, large-scale wind is also not feasible for the Patterson School. The North Carolina Mountain Ridge Protection Act prevents the development of wind turbines larger than 100 feet in height from being developed on mountain ridges. This greatly limits wind power development on mountain ridges, where wind speeds are highest. However, to keep with the sustainability requirement of our task we decided to further investigate small-scale wind and solar development at the Patterson School. We created wind and solar models to provide insight for their decision-making process. Data for the wind model was gathered from the Hickory Regional Airport, which served as a proxy location for the Patterson School. Three years of wind data was analyzed and the observed distribution was used to construct a wind power model. The solar analysis was conducted primarily by using PVWatts, a tool created by the National Renewable Energy Laboratory. The analyses of small-scale wind and solar were revealed to be uneconomic options in isolation. Both the wind turbine and solar arrays had a negative net present value. However, we recommend that the Patterson School Foundation construct a small 1 kilowatt wind turbine and a small 15 kilowatt solar array on their property. These renewable energy plays will be used to increase the overall sustainability of the Patterson School. Additionally, they can be leveraged to bring in revenue streams through the introduction of sustainability classes. Since the sustainable energy projects have negative net present values, other revenue streams needed to be pursued. We examined the possibility of introducing small-scale educational classes at the Patterson School. We chose to examine small-scale educational courses for two reasons. First, the Patterson School has the strong educational background to facilitate this type of project. Additionally, our research suggests that there is a strong demand for small scale courses focusing on sustainability. Our team chose to investigate the logistics of offering classes on permaculture and renewable energy. Permaculture was chosen because the Patterson School has expressed interest in this topic, and because their abundant land resources are ideal for demonstration purposes. Renewable energy was chosen as a course topic because we see a strong demand for these types of courses, and because it can leverage the recommended renewable energy installations. To determine the overall economic benefit of the recommended projects a financial model was created. This model considered all expected costs and revenue streams incurred by the renewable energy projects and small-scale educational classes. The model assumes the fixed costs of the projects would be incurred at year zero. Classes are assumed to begin with an enrollment of 10 students per class and grow at a rate of 20 percent each year, until a predetermined class capacity is reached. The variable cost of the course is calculated to grow alongside the class as capacity increases. Under these assumptions the simple payback period of the portfolio was found to be three years when no discount rate was applied. When discounted at a rate of six percent the simple payback period increased to three and half years. After this point in time revenues will grow until the eighth year. After the eighth year, the revenue stream is expected to be steady and generate 52,038 dollars each year. Due to the strong economic performance of the portfolio we recommend that the Patterson School install small-scale renewable energy systems on their property. Additionally, we recommend that the Patterson School introduce small-scale educational courses, starting with classes on permaculture and renewable energy. Our analysis suggests that if the Patterson School Foundation follows these recommendations they will see an increase in the overall sustainability of their organization. Additionally, the portfolio of projects will pay for itself in under four years. This report will examine each project in detail. The proposed plan for the Patterson School takes into consideration the strengths, weaknesses, opportunities, and risks associated with each recommendation

Analysis of Influencing Factors of Green Building Energy Consumption Based on Genetic Algorithm

With the advancement of modernization, high energy consumption buildings can no longer meet the needs of social development. Under the background of low carbon and energy saving, the development of green buildings has become the only way, but its energy-saving design effect needs to be further studied. Aiming at lighting and energy consumption, this study carried out multi-factor optimization analysis based on genetic algorithm on factors such as windowing ratio, wall heat transfer coefficient, window heat transfer coefficient, window transmittance and roof insulation coefficient. Firstly, the theory and technical scheme of applying data mining technology to solve the energy-saving design problems of different buildings are proposed and implemented, including the design of new and existing buildings, as well as the determination of decisive parameters and non-decisive parameters. Secondly, computer simulation and theoretical analysis are used to optimize the analysis of the building scheme, so as to find the optimal design range of each influencing factor and the optimal design method of green low-energy building. Multi-factor optimization theory and genetic algorithm principle are summarized, and the heat transfer coefficient of external wall and window of the building is selected as the optimization variable, so as to achieve low energy consumption and enclosure cost of the building. Aiming at better thermal comfort, an optimization model was established. Finally, through empirical research, an energysaving plan was designed, and genetic algorithm was used to obtain the optimal solution for maximizing the incremental benefits obtained by unit input incremental cost. The results indicate that the ideal incremental benefits come from a reasonable and effective combination of technologies, mainly from air conditioning systems and lighting systems; the setting of the benchmark return rate will directly affect the optimization effect of energy-saving plans, providing decision-makers with the optimal combination of energy-saving technologies

Unprecedented Centimeter-Long Carbon Nitride Needles: Synthesis, Characterization and Applications

This is the peer reviewed version of the following article: Barrio, J., Lin, L., Amo‐Ochoa, P., Tzadikov, J., Peng, G., Sun, J., ... & Shalom, M. (2018). Unprecedented Centimeter‐Long Carbon Nitride Needles: Synthesis, Characterization and Applications. Small, 14(21), 1800633, which has been published in final form at https://doi.org/10.1002/smll.201800633. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived VersionsFree standing centimeter-long 1D nanostructures are highly attractive for electronic and optoelectronic devices due to their unique photophysical and electrical properties. Here a simple, large-scale synthesis of centimeter-long 1D carbon nitride (CN) needles with tunable photophysical, electric, and catalytic properties is reported. Successful growth of ultralong needles is acquired by the utilization of 1D organic crystal precursors comprised of CN monomers as reactants. Upon calcination at high temperatures, the shape of the starting crystal is fully preserved while the CN composition and porosity, and optical and electrical properties can be easily tuned by tailoring the starting elements ratio and final calcination temperature. The facile manipulation and visualization of the CN needles endow their direct electrical measurements by placing them between two conductive probes. Moreover, the CN needles exhibit good photocatalytic activity for hydrogen production owing to their improved light harvesting properties, high surface area, and advantageous energy bands position. The new growth strategy developed here may open opportunities for a rational design of CN and other metal-free materials with controllable directionality and tunable photophysical and electronic properties, toward their utilization in (photo)electronic devices.The authors thank Dr. Alex Upcher and Dr. Einat Nativ-Roth for their assistance with electronic microscopy analysis. The authors thank also the financial support from the Spanish Ministerio de Economía y Competitividad (MAT2016-77608-C3-1-P). The authors thank Dr. Hod for fruitful discussio

First Place Solution to the CVPR'2023 AQTC Challenge: A Function-Interaction Centric Approach with Spatiotemporal Visual-Language Alignment

Affordance-Centric Question-driven Task Completion (AQTC) has been proposed to acquire knowledge from videos to furnish users with comprehensive and systematic instructions. However, existing methods have hitherto neglected the necessity of aligning spatiotemporal visual and linguistic signals, as well as the crucial interactional information between humans and objects. To tackle these limitations, we propose to combine large-scale pre-trained vision-language and video-language models, which serve to contribute stable and reliable multimodal data and facilitate effective spatiotemporal visual-textual alignment. Additionally, a novel hand-object-interaction (HOI) aggregation module is proposed which aids in capturing human-object interaction information, thereby further augmenting the capacity to understand the presented scenario. Our method achieved first place in the CVPR'2023 AQTC Challenge, with a Recall@1 score of 78.7\%. The code is available at https://github.com/tomchen-ctj/CVPR23-LOVEU-AQTC.Comment: Winner of CVPR2023 Long-form Video Understanding and Generation Challenge (Track 3