Sunset Park, Brooklyn: Reclaiming an Urban Industrial Area and Creating Community

Like many metropolises around the world, urban renewal in New York dominates the process of urban development due to the scarcity of urban land resources and the ever-expanding population of New York. In the history of New York’s urban expansion, with the continuous expansion of the city’s outer edge and industrial relocation, industrial land originally on the edge of the city is gradually surrounded by residential areas. The large area of vacant land and building also limits the further development of the region. How to reuse the existing infrastructure and brownfield with the highly degraded environment is particularly important for urban regeneration. The physical development of Sunset Park, which began over 100 years ago, was based on a different platform for manufacturing and distributing goods, one which was well-suited to the infrastructure and building types developed at the time. Today, the main challenge is to figure out ways to adapt and reuse this antiquated industrial infrastructure and develop Sunset Park into a 21st century model for diverse, dense and environmentally sustainable industry. Through the transformation of two different types of brownfields at the Sunset Park waterfront area, this design proposal will promote the process of urban restoration and promote the sustainable development of existing brownfield

Novel adaptive stability enhancement strategy for power systems based on deep reinforcement learning

As the access rate of wind energy in a power system has significantly increased, stabilizing the power system has become challenging. Among these challenges, low-frequency oscillation is one of the most harmful problems, effectively resolved by adding a damping controller according to the relevant properties of the low-frequency oscillation. However, the controller often fails to adapt to the constantly changing wind energy system owing to the lack of a targeted dynamic change strategy. Thus, to address this issue, an adaptive stabilization strategy that uses a static var compensator with an additional damping controller structure is proposed. Specifically, the entire power system is equivalently represented as a generalized regression neural network, with a deep reinforcement learning algorithm called soft actor-critic introduced to train the agent based on the generalized regression neural network model. After the training process, the agent can provide additional efficient static var compensator damping controller parameters under different operating conditions, vastly improving the system stability. Simulation results verify the improved performance using the proposed strategy compared to other optimization methods, regardless of whether the low-frequency oscillations were suppressed in the time or frequency domains

Placemaking in Metro East Springfield - Creating a Landscape Framework

PLACEMAKING IN METRO EAST SPRINGFIELD - Creating a Landscape Framework Placemaking in Metro East Springfield – Creating a Landscape Framework provides strategies to use the landscape as a framework for rebuilding community in a downtown urban area that has “good bones” but has been neglected and overlooked for decades. A catalyst for the development of project area is the recent acquisition of the historical 1916 Willys Overland building through a developer. The Graduate Urban Design Studio 2018 developed five proposals for urban revitalization in the area that are centered on the landscape. The programming of the proposals was developed in collaboration with neighborhood representatives and stakeholders of the area. The public response was very positive and the project got recognized in the local press and media. The Landscape Framework is interwoven with cultural activities such as public art and education, new opportunities for small neighborhood commerce, future employment and possibilities for new housing. The Landscape Framework will bring expand urban greening and will reduce heat island effects to reduce the impact of climate change. The presented Landscape Framework will guide the future of the area as overlapping and simultaneous measures. They encompass: Tangible tactile interventions on streets, facades and underutilized lots that change the perception of the landscape at low cost but are highly effective. New parks that create areas for recreation and contemplation. Greenway promenades connect to shorten long blocks and create a network to the neighboring residential areas. Establishment of urban agriculture activities to build community, provide food security and education. Collaboration with existing organizations in Springfield that are actively involved with urban agriculture: Gardening the Community (GTC) Springfield, Wellspring Harvest first commercial hydroponic greenhouse, UMass Extension and UMass Permaculture, Springfield Technical Community College (STCC). Walkable streets through extensive street tree plantings, widening of sidewalks, adding bicycle lanes and introducing shared multi-functional streets for community events. Stormwater Management through bioswales along streets, green roofs, larger infiltration areas in new parks and porous pavement. Promotion of alternative stormwater management through education and artistic interventions. People want to connect culturally and socially. Creating a sense of place, common ownership, and connectivity are a vital part of a sustainable community. This includes: Complimentary cultural, art, craft and education at new Maker-Spaces. Daycare Center and other childcare services. Outdoor pop-up business opportunities for food vendors such as food carts and trucks. Indoor pop-up business opportunities in abandoned or underutilized buildings. Adaptive reuse of existing architecture and infill. Diversification of housing market with inclusion of market-rate housing to create a more balanced economy. Legal framework through zoning changes and permitting that supports small businesses, reduces bureaucratic burdens and secures public open green space

Design of wide range DC input power module used in coal mine

In view of problems that power supply voltage level and power type between mine-used sensors and DC power supply system is inconsistent, a design scheme of new type of wide range DC input and intrinsic safety type power module was put forward. The power module is based on Buck and isolated flyback topology, front-end uses the Buck circuit to avoid risk caused by direct use of the flyback topology which may bring high pressure to switch tube, and the back-end uses isolated flyback topology to meet isolation requirements of electrical equipment with non-intrinsic safety and intrinsic safety. The power module has advantages of anti reverse input, DC9-350 V input, intrinsic safety power output and easy integration

Insulator Detection Method in Inspection Image Based on Improved Faster R-CNN

The detection of insulators in power transmission and transformation inspection images is the basis for insulator state detection and fault diagnosis in thereafter. Aiming at the detection of insulators with different aspect ratios and scales and ones with mutual occlusion, a method of insulator inspection image based on the improved faster region-convolutional neural network (R-CNN) is put forward in this paper. By constructing a power transmission and transformation insulation equipment detection dataset and fine-tuning the faster R-CNN model, the anchor generation method and non-maximum suppression (NMS) in the region proposal network (RPN) of the faster R-CNN model were improved, thus realizing a better detection of insulators. The experimental results show that the average precision (AP) value of the faster R-CNN model was increased to 0.818 with the improved anchor generation method under the VGG-16 Net. In addition, the detection effect of different aspect ratios and different scales of insulators in the inspection images was improved significantly, and the occlusion of insulators could be effectively distinguished and detected using the improved NMS

A Method for Autonomous Navigation and Positioning of UAV Based on Electric Field Array Detection

At present, the method of using unmanned aerial vehicles (UAVs) with traditional navigation equipment for inspection of overhead transmission lines has the limitations of expensive sensors, difficult data processing, and vulnerable to weather and environmental factors, which cannot ensure the safety of UAV and power systems. Therefore, this paper establishes a mathematical model of spatial distribution of transmission lines to study the field strength distribution information around transmission lines. Based on this, research the navigation and positioning algorithm. The data collected by the positioning system are input into the mathematical model to complete the identification, positioning, and safety distance diagnosis of the field source. The detected data and processing results can provide reference for UAV obstacle avoidance navigation and safety warning. The experimental results show that the positioning effect of the positioning navigation algorithm is obvious, and the positioning error is within the range of use error and has good usability and application value

A Method for Autonomous Navigation and Positioning of UAV Based on Electric Field Array Detection

At present, the method of using unmanned aerial vehicles (UAVs) with traditional navigation equipment for inspection of overhead transmission lines has the limitations of expensive sensors, difficult data processing, and vulnerable to weather and environmental factors, which cannot ensure the safety of UAV and power systems. Therefore, this paper establishes a mathematical model of spatial distribution of transmission lines to study the field strength distribution information around transmission lines. Based on this, research the navigation and positioning algorithm. The data collected by the positioning system are input into the mathematical model to complete the identification, positioning, and safety distance diagnosis of the field source. The detected data and processing results can provide reference for UAV obstacle avoidance navigation and safety warning. The experimental results show that the positioning effect of the positioning navigation algorithm is obvious, and the positioning error is within the range of use error and has good usability and application value

Low-Photon Counts Coherent Modulation Imaging via Generalized Alternating Projection Algorithm

Phase contrast imaging is advantageous for mitigating radiation damage to samples, such as biological specimens. For imaging at nanometer or atomic resolution, the required flux on samples increases dramatically and can easily exceed the sample damage threshold. Coherent modulation imaging (CMI) can provide quantitative absorption and phase images of samples at diffraction-limited resolution with fast convergence. When used for radiation-sensitive samples, CMI experiments need to be conducted under low illumination flux for high resolution. Here, an algorithmic framework is proposed for CMI involving generalized alternating projection and total variation constraint. A five-to-ten-fold lower photon requirement can be achieved for near-field or far-field experiment dataset. The work would make CMI more applicable to the dynamics study of radiation-sensitive samples