Fault Detection and Diagnosis for Residential HVAC Systems using Transient Cloud-based Thermostat Data

Fault detection and diagnosis (FDD) using aggregated smart thermostat data is a relatively new research field, but one with immediate practical application to residential indoor climate control. This paper analyzes a cloud-based dataset which contains thermostat history records of nearly 370,000 distinct residential HVAC systems in the U.S. The large, diverse, and growing dataset enables novel methods for detecting and diagnosing faults on systems with limited sensor data. This paper proposes a statistics-based FDD method for non-variable speed heat pump and air conditioning units, and demonstrates the effectiveness with several case studies. The proposed method identifies systems within a similar climate region, and then segments and classifies the time series data based on operational mode and behavior. Various data features are then extracted from the time series segments to identify systems that exhibit poor transient behavior. Additional features are used to refine and classify the problem severity. Statistical methods are then used to compare system performance to the entire population and identify outlier behavior due to operational faults that affect system efficiency and occupancy comfort. The resulting algorithm demonstrates the potential of big data fault detection for air conditioning systems using limited cloud-based sensor information

NOMA-enhanced computation over multi-access channels

Massive numbers of nodes will be connected in future wireless networks. This brings great difficulty to collect a large amount of data. Instead of collecting the data individually, computation over multi-access channels (CoMAC) provides an intelligent solution by computing a desired function over the air based on the signal-superposition property of wireless channels. To improve the spectrum efficiency in conventional CoMAC, we propose the use of non-orthogonal multiple access (NOMA) for functions in CoMAC. The desired functions are decomposed into several sub-functions, and multiple sub-functions are selected to be superposed over each resource block (RB). The corresponding achievable rate is derived based on sub-function superposition, which prevents a vanishing computation rate for large numbers of nodes. We further study the limiting case when the number of nodes goes to infinity. An exact expression of the rate is derived that provides a lower bound on the computation rate. Compared with existing CoMAC, the NOMA-based CoMAC not only achieves a higher computation rate but also provides an improved non-vanishing rate. Furthermore, the diversity order of the computation rate is derived, which shows that the system performance is dominated by the node with the worst channel gain among these sub-functions in each RB

A Method of Mapping Heat Exchanger as Simple Polynomials

Conducting economic comparison studies of vapor-compression systems early in the product development process allows the designer to balance competing objectives of raw material costs, life-cycle cost, and system performance. However, detailed performance simulation models typically require iterative solutions at both the component and system levels. These nested iterative models make economic comparison studies computationally prohibitive. To address the challenge of nested iterations, non-iterative polynomial representations of components can be implemented. In this paper, a method to represent the heat exchangers’ effectiveness, pressure loss, refrigerant charge, and mass with non-iterative models is presented. A method of mapping the heat exchanger using Monte Carlo sampling over its operational and design space is given. The method is then applied to map the heat exchanger effectiveness, refrigerant charge level, pressure drop, and mass of a flooded type shell and tube heat exchanger. Heat exchangers are represented as a function of inlet conditions and heat exchanger geometries. This proposed method of representing heat exchanger as a polynomial map relieves the computationally heavy nature of finite control volume modeling of heat exchangers with non-iterative empirical maps. Such a method of mapping heat exchangers enables rapid iterations of the system model, thus enabling effective economic trade-off studies of vapor-compression systems

Flavonoids from Lycium barbarum leaves attenuate obesity through modulating glycolipid levels, oxidative stress, and gut bacterial composition in high-fat diet-fed mice

Traditional herbal therapy made from Lycium barbarum leaves has been said to be effective in treating metabolic diseases, while its exact processes are yet unknown. Natural flavonoids are considered as a secure and reliable method for treating obesity. We thus made an effort to investigate the processes by which flavonoids from L. barbarum leaves (LBLF) reduce obesity. To assess the effectiveness of the intervention following intragastric injection of various dosages of LBLF (50, 100, and 200 mg/kg⋅bw), obese model mice developed via a high-fat diet were utilized. Treatment for LBLF may decrease body weight gain, Lee’s index, serum lipids levels, oxidative stress levels, and hepatic lipids levels. It may also enhance fecal lipids excretion and improve glucose tolerance. Additionally, LBLF therapy significantly restored gut dysfunction brought on by a high-fat diet by boosting gut bacterial diversities and altering the composition of the gut bacterial community by elevating probiotics and reducing harmful bacteria

Town Of Duxbury, Massachusetts Annual Town Report For The Period Covering July 1, 2015 Through June 30, 2016 

Future networks are expected to connect an enormous number of nodes wirelessly using wide-band transmission. This brings great challenges. To avoid collecting a large amount of data from the massive number of nodes, computation over multi-access channel (CoMAC) is proposed to compute a desired function over the air utilizing the signal-superposition property of wireless channel. Due to frequency-selective fading, wideband CoMAC is more challenging and has never been studied before. In this work, we propose the use of orthogonal frequency division multiplexing (OFDM) in wide-band CoMAC to transmit functions in a similar way to bit sequences through division, allocation, and reconstruction of functions. An achievable rate without any adaptive resource allocation is derived. To prevent a vanishing computation rate from the increase in the number of nodes, a novel sub-function allocation of sub-carriers is derived. Furthermore, we formulate an optimization problem considering power allocation. A sponge-squeezing algorithm adapted from the classical water-filling algorithm is proposed to solve the optimal power allocation problem. The improved computation rate of the proposed framework and the corresponding allocation has been verified through both theoretical analysis and simulation