A data analytics-based energy information system (EIS) tool to perform meter-level anomaly detection and diagnosis in buildings

Recently, the spread of smart metering infrastructures has enabled the easier collection of building-related data. It has been proven that a proper analysis of such data can bring significant benefits for the characterization of building performance and spotting valuable saving opportunities. More and more researchers worldwide are focused on the development of more robust frameworks of analysis capable of extracting from meter-level data useful information to enhance the process of energy management in buildings, for instance, by detecting inefficiencies or anomalous energy behavior during operation. This paper proposes an innovative anomaly detection and diagnosis (ADD) methodology to automatically detect at whole-building meter level anomalous energy consumption and then perform a diagnosis on the sub-loads responsible for anomalous patterns. The process consists of multiple steps combining data analytics techniques. A set of evolutionary classification trees is developed to discover frequent and infrequent aggregated energy patterns, properly transformed through an adaptive symbolic aggregate approximation (aSAX) process. Then a post-mining analysis based on association rule mining (ARM) is performed to discover the main sub-loads which mostly affect the anomaly detected at the whole-building level. The methodology is developed and tested on monitored data of a medium voltage/low voltage (MV/LV) transformation cabin of a university campus

Online implementation of a soft actor-critic agent to enhance indoor temperature control and energy efficiency in buildings

Recently, a growing interest has been observed in HVAC control systems based on Artificial Intelligence, to improve comfort conditions while avoiding unnecessary energy consumption. In this work, a model-free algorithm belonging to the Deep Reinforcement Learning (DRL) class, Soft Actor-Critic, was implemented to control the supply water temperature to radiant terminal units of a heating system serving an office building. The controller was trained online, and a preliminary sensitivity analysis on hyperparameters was performed to assess their influence on the agent performance. The DRL agent with the best performance was compared to a rule-based controller assumed as a baseline during a three-month heating season. The DRL controller outperformed the baseline after two weeks of deployment, with an overall performance improvement related to control of indoor temperature conditions. Moreover, the adaptability of the DRL agent was tested for various control scenarios, simulating changes of external weather conditions, indoor temperature setpoint, building envelope features and occupancy patterns. The agent dynamically deployed, despite a slight increase in energy consumption, led to an improvement of indoor temperature control, reducing the cumulative sum of temperature violations on average for all scenarios by 75% and 48% compared to the baseline and statically deployed agent respectively

Enhancing operational performance of AHUs through an advanced fault detection and diagnosis process based on temporal association and decision rules

The pervasive monitoring of HVAC systems through Building Energy Management Systems (BEMSs) is enabling the full exploitation of data-driven based methodologies for performing advanced energy management strategies. In this context, the implementation of Automated Fault Detection and Diagnosis (AFDD) based on collected operational data of Air Handling Units (AHUs) proved to be particularly effective to prevent anomalous running modes which can lead to significant energy waste over time and discomfort conditions in the built environment. The present work proposes a novel methodology for performing AFDD, based on both unsupervised and supervised data-driven methods tailored according to the operation of an AHU during transient and non-transient periods. The whole process is developed and tested on a sample of real data gathered from monitoring campaigns on two identical AHUs in the framework of the Research Project ASHRAE RP-1312. During the start-up period of operation, the methodology exploits Temporal Association Rules Mining (TARM) algorithm for an early detection of faults, while during non-transient period a number of classification models are developed for the identification of the deviation from the normal operation. The proposed methodology, conceived for quasi real-time implementation, proved to be capable of robustly and promptly identifying the presence of typical faults in AHUs

Phase separation of binary fluids with dynamic temperature

Phase separation of binary fluids quenched by contact with cold external walls is considered. Navier-Stokes, convection-diffusion, and energy equations are solved by lattice Boltzmann method coupled with finite-difference schemes. At high viscosity, different morphologies are observed by varying the thermal diffusivity. In the range of thermal diffusivities with domains growing parallel to the walls, temperature and phase separation fronts propagate towards the inner of the system with power-law behavior. At low viscosity hydrodynamics favors rounded shapes, and complex patterns with different lengthscales appear. Off-symmetrical systems behave similarly but with more ordered configurations.Comment: Accepted for publication in Phys. Rev. E, 11 figures, best quality figures available on reques

Late Quaternary activity along the Scorciabuoi Fault (Southern Italy) as inferred from electrical resistivity tomographies

The Scorciabuoi Fault is one of the major tectonic structures affecting the Southern Apennines, Italy. Across its central sector, we performed several electrical resistivity tomographies with different electrode spacing (5 and 10 m) and using a multielectrode system with 32 electrodes. All tomographies were acquired with two different arrays, the dipole-dipole and the Wenner-Schlumberger. We also tested the different sensitivity of the two arrays with respect to the specific geological conditions and research goals. Detailed geological mapping and two boreholes were used to calibrate the electrical stratigraphy. In all but one tomography (purposely performed off the fault trace), we could recognise an abrupt subvertical lateral variation of the main sedimentary bodies showing the displacement and sharp thickening of the two youngest alluvial bodies in the hanging-wall block. These features are interpreted as evidence of synsedimentary activity of the Scorciabuoi Fault during Late Pleistocene and possibly as recently as Holocene and allow accurate location of the fault trace within the Sauro alluvial plain

Electrical resistivity tomography for studying liquefaction induced by the May 2012 Emilia-Romagna earthquake (Mw = 6.1, northern Italy)

Abstract. This work shows the result of an electrical resistivity tomography (ERT) survey carried out for imaging and characterizing the shallow subsurface affected by the coseismic effects of the Mw = 6.1 Emilia-Romagna (northern Italy) earthquake that occurred on 20 May 2012. The most characteristic coseismic effects were ground failure, lateral spreading and liquefaction that occurred extensively along the paleo-Reno River in the urban areas of San Carlo and Mirabello (southwestern portion of Ferrara Province). In total, six electrical resistivity tomographies were performed and calibrated with surface geological surveys, exploratory boreholes and aerial photo interpretations. This was one of first applications of the electrical resistivity tomography method in investigating coseismic liquefaction

Study of a high spatial resolution 10B-based thermal neutron detector for application in neutron reflectometry: the Multi-Blade prototype

Although for large area detectors it is crucial to find an alternative to detect thermal neutrons because of the 3He shortage, this is not the case for small area detectors. Neutron scattering science is still growing its instruments' power and the neutron flux a detector must tolerate is increasing. For small area detectors the main effort is to expand the detectors' performances. At Institut Laue-Langevin (ILL) we developed the Multi-Blade detector which wants to increase the spatial resolution of 3He-based detectors for high flux applications. We developed a high spatial resolution prototype suitable for neutron reflectometry instruments. It exploits solid 10B-films employed in a proportional gas chamber. Two prototypes have been constructed at ILL and the results obtained on our monochromatic test beam line are presented here

Hepatocellular Carcinoma Metastasis to the Orbit in a Coinfected HIV+ HBV+ Patient Previously Treated with Orthotopic Liver Transplantation: A Case Report

Hepatocellular carcinoma rarely metastasizes to the orbit. We report a 45-year-old male, HBV+, HIV+, with a past history of a liver transplant for ELSD (end-stage liver disease) with hepatocellular carcinoma and recurrent HCC, who presented with proptosis and diplopia of the left eye. CT scans of the head revealed a large, irregular mass in the left orbit causing superior and lateral destruction of the orbital bone. Biopsy specimens of the orbital tumor showed features of metastatic foci of hepatocellular carcinoma. Only 16 other cases of HCC metastasis to the orbit have been described in literature, and this is the first case in a previously transplanted HIV+, HBV+ patient

Abdominal nodal localization of Castleman's disease: report of a case.

Abstract Introduction Castleman's disease (CD) is a rare benign disorder that may grow in any area where lymphoid tissue is normally present but the most frequent site is mediastinum (67%); the abdomen is rarely affected by this pathology. In the pathogenesis of CD an important role could be played by HHV-8. Diagnosis is difficult and the diagnostic certainty is obtained only by histological examination. For this disease there is no gold-standard treatment. Case report We report the case of a woman of 33 years of age affected by a rare form of abdominal nodal localization of Castleman's Disease for which the patient underwent surgery. Conclusion CD must be included in the differential diagnosis of retroperitoneal tumors even though the definitive diagnosis can only be achieved by histological and immunohistochemical examination. In the case of single location, the treatment of choice is surgical removal