Dual-wavelength Interdigital Capacitive Sensor for Dielectric Material Detection

Interdigital capacitive sensors are widely used for non-destructive measurement of dielectric material properties in industry, with the advantages of one-sided inspection, adjustable signal strength and tomography capability. The dual-wavelength interdigital capacitive sensor has dual penetration depth, can be used for inspection material properties at different depths from the surface (Figure 1). In order to improve the imaging quality of capacitive sensor systems and enhance the inspection accuracy, the structure parameters optimization of the sensor and the edge-detection algorithm is studied. An analysis of how the sensor unit parameters affect the performances, such as the sensitive field distribution, sensitivity, and signal strength is presented. The interpolation algorithm and Canny Operator edge-detection is also studied. For example with the two-layer damaged dielectric material, the area is 240 × 240 mm2, the thickness of the first and the second layer are 0.35 mm, 0.3mm respectively. The relative permittivity of the first and the second layer are 3 and 6.The dual-wavelength sensor (Figure 2) is designed for the damage detection and the simulation is conducted. The results show that the damages in different layer can be detected effectively

Physics Informed Reinforcement Learning for Power Grid Control using Augmented Random Search

Wide adoption of deep reinforcement learning in energy system domain needs to overcome several challenges , including scalability, learning from limited samples, and high-dimensional continuous state and action spaces. In this paper, we integrated physics-based information from the generator operation state formula, also known as Swing Equation, into the reinforcement learning agent's neural network loss function, and applied an augmented random search agent to optimize the generator control under dynamic contingency. Simulation results demonstrated the reliability performance improvements in training speed, reward convergence, and future potentials in its transferability and scalability

Unsupervised Cross-Modality Domain Adaptation for Vestibular Schwannoma Segmentation and Koos Grade Prediction based on Semi-Supervised Contrastive Learning

Domain adaptation has been widely adopted to transfer styles across multi-vendors and multi-centers, as well as to complement the missing modalities. In this challenge, we proposed an unsupervised domain adaptation framework for cross-modality vestibular schwannoma (VS) and cochlea segmentation and Koos grade prediction. We learn the shared representation from both ceT1 and hrT2 images and recover another modality from the latent representation, and we also utilize proxy tasks of VS segmentation and brain parcellation to restrict the consistency of image structures in domain adaptation. After generating missing modalities, the nnU-Net model is utilized for VS and cochlea segmentation, while a semi-supervised contrastive learning pre-train approach is employed to improve the model performance for Koos grade prediction. On CrossMoDA validation phase Leaderboard, our method received rank 4 in task1 with a mean Dice score of 0.8394 and rank 2 in task2 with Macro-Average Mean Square Error of 0.3941. Our code is available at https://github.com/fiy2W/cmda2022.superpolymerization

Comparison of 2006 IECC and 2009 IECC Commercial Energy Code Requirements for Kansas City, MO

This report summarizes code requirements and energy savings of commercial buildings in climate zone 4 built to the 2009 IECC when compared to the 2006 IECC. In general, the 2009 IECC has higher insulation requirements for exterior walls, roof, and windows and have higher efficiency requirements for HVAC equipment (HVAC equipment efficiency requirements are governed by National Appliance Conversion Act of 1987 (NAECA), and are applicable irrespective of the IECC version adopted). The energy analysis results show that residential and nonresidential commercial buildings meeting the 2009 IECC requirements save between 6.1% and 9.0% site energy, and between 6.4% and 7.7% energy cost when compared to 2006 IECC. Analysis also shows that semiheated buildings have energy and cost savings of 3.9% and 5.6%

Energy Savings and Economics of Advanced Control Strategies for Packaged Heat Pumps

Pacific Northwest National Laboratory (PNNL), with funding from the U.S. Department of Energy’s (DOE’s) Building Technologies Program (BTP), evaluated a number of control strategies for packaged cooling equipment that can be implemented in an advanced controller, which can be retrofit into existing packaged heat pump units to improve their operational efficiency. This report documents the results of that analysis

Energy Savings and Economics of Advanced Control Strategies for Packaged Air-Conditioning Units with Gas Heat

Pacific Northwest National Laboratory (PNNL) with funding from the U.S. Department of Energy's Building Technologies Program (BTP) evaluated a number of control strategies that can be implemented in a controller, to improve the operational efficiency of the packaged air conditioning units. The two primary objectives of this research project are: (1) determine the magnitude of energy savings achievable by retrofitting existing packaged air conditioning units with advanced control strategies not ordinarily used for packaged units and (2) estimating what the installed cost of a replacement control with the desired features should be in various regions of the U.S. This document reports results of the study