Handling Unit Research Articles

Humidity Detection Based on Chitosan/PEO Film Sensor

PEO (Polyethylene Oxide) addition in chitosan has been successfully fabricated as a humidity sensor. In this study, 3% w/v chitosan solution was added by 0.1, 0.2, 0.3, 0.4 and 0.5 (%w/v) of PEO respectively. The sensing properties of chitosan and chitosan/PEO films as humidity sensors have been characterized using Air Handling Unit Trainer, model KT-2000AHU to determine response, repeatability, and recovery toward relative humidity (20-90% RH). The results show that the chitosan/PEO films have a good response when exposed to 90 %RH at room temperature. Those are 288,09 mV obtained by pure chitosan film; 338.97, 384.44, 406.81, 359.69, and 345.84 mV for 0.1, 0.2, 0.3, 0.4, and 0.5% of PEO films respectively that show higher electrical response. The smooth and porous film morphology and chemical interaction between chitosan and PEO through hydrogen bond obtained by SEM and FTIR could be responsible for the higher electrical response. Furthermore, humidity sensing material based on chitosan/PEO films shows good recovery and repeatability.

An Extension of HVAC-AHU System Using PROMETHEE Method

An HVAC system is an indoor climate control system that combines heating and cooling equipment of various types. The Air Handling Unit (AHU) is the central component of a central air conditioning system. HVAC systems are used to provide comfort to the inhabitants of a building or to protect goods or objects placed in a space, and include mechanical, electrical, and I&C components. They remove dust and other particles from both outdoor and room air, and adjust temperature and humidity to provide chilled air through pipes to individual rooms. PROMETHEE is a ranking system used for assessing and enriching priority, and its interactive help provides descriptive complementary geometric analysis known as PROMETHEE methods. The PROMETHEE method determines the best solution from the analysis by calculating the distance between solutions and the negative-ideal solution. In this analysis, the shorter the distance and the longer the negative-ideal solution, the better the ranking. However, the comparison of these distances was not considered significant. The results show that the Heating and Cooling Split Systems received the first rank, while the Packaged Heating and Air Conditioning System received the lowest rank. Specifically, the Heating and Cooling Split Systems ranked first, the Duct-Free (Mini-Split) ranked second, the Hybrid Split System ranked third, and the Packaged Heating and Air Conditioning System ranked fourth

A comparative life cycle assessment (LCA) analysis of innovative methods employing cutting-edge technology to improve sludge reduction directly in wastewater handling units

Sludge reduction technologies can be used as an alternative plan to dispose of excess sludge in wastewater treatment plants, but the sustainability of these strategies is a challenging task. In this study, the potential environmental implications of innovative technologies based on lab-scale results published in the literature were assessed from the life cycle assessment (LCA) view point. Accordingly, three different scenarios using various sludge reduction mechanisms were selected and analyzed. The scenarios include (1) an integrated oxic-setting-anaerobic and ultrasound process; (2) a sequencing batch reactor (SBR) with an anaerobic side-stream reactor to its return activated sludge line; and (3) the anaerobic-anoxic-oxic system in conjunction with an ozone reactor. LCA was conducted through the CML-IA (baseline 2000) method. A sensitivity analysis was also done in order to determine how changes in the inputs are affecting the overall sustainability of the system. The environmental impact evaluation of three scenarios indicated that the integrated SBR with an anaerobic side-stream reactor was the most efficient and sustainable alternative in environmental terms. Although the upgraded SBR system was not the best alternative in terms of sludge reduction (65 % versus 78 % for Scenario 1 and 70 % for Scenario 3), it showed the highest overall performance and also demonstrated the lowest environmental impact compared to other scenarios. Because the scenarios studied were cutting-edge and provided novel sludge reduction strategies based on lab-scale results published in the literature, a comprehensive economic analysis and scale-up considerations are recommended to effectively assist decision-makers in guiding the development of emerging technologies.

Development of an Airflow Monitoring System for Air Handling Unit using IoT

This paper presents the development of an airflow monitoring system for air handling units using NodeMCU ESP32. The main purpose of this project is to improvise the use of microcontroller with on-par performance for industrial applications. This proposed system consists of two sensors that measure airflow from the air handling unit. The first sensor is an airflow speed, which measures the airflow speed from the air handling unit. The second sensor detects and indicates the temperature and humidity of the airflow. The testing parameters show very good correlations among variables, indicating the efficiency of the system to monitor the airflow. Keywords: Airflow, IoT, Temperature, Humidity, Air Handling Unit eISSN: 2398-4287 © 2022. The Authors. Published for AMER ABRA cE-Bs by E-International Publishing House, Ltd., UK. This is an open-access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under the responsibility of AMER (Association of Malaysian Environment-Behavior Researchers), ABRA (Association of Behavioral Researchers on Asians), and cE-Bs (Centre for Environment-Behavior Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia.

Cascaded Control for Building HVAC Systems in Practice

Actuator hunting is a widespread and often neglected problem in the HVAC field. Hunting is typically characterized by sustained or intermittent oscillations, and can result in decreased efficiency, increased actuator wear, and poor setpoint tracking. Cascaded control loops have been shown to effectively linearize system dynamics and reduce the prevalence of hunting. This paper details the implementation of cascaded control architectures for Air Handling Unit chilled water valves at three university campus buildings. A framework for implementation the control in existing Building Automation software is developed that requires only a single line of additional code. Results gathered for more than a year show that cascaded control not only eliminates hunting in control loops with documented hunting issues, but provides better tracking and more consistent performance during all seasons. A discussion of efficiency losses due to hunting behavior is presented and illustrated with comparative data. Furthermore, an analysis of cost savings from implementing cascaded chilled water valve control is presented. Field tests show 2.2–4.4% energy savings, with additional potential savings from reduced operational costs (i.e., maintenance and controller retuning).

Cross Domain Data Generation for Smart Building Fault Detection and Diagnosis

Benefiting extensively from the Internet of Things (IoT) and sensor network technologies, the modern smart building achieves thermal comfort. It prevents energy wastage by performing automatic Fault Detection and Diagnosis (FDD) to maintain the good condition of its air-conditioning systems. Often, real-time multi-sensor measurements are collected, and supervised learning algorithms are adopted to exploit the data for an effective FDD. A key issue with the supervised methods is their dependence on well-labeled fault data, which is difficult to obtain in many real-world scenarios despite the abundance of unlabelled sensor data. Intuitively, the problem can be greatly alleviated if some well-labeled fault data collected under a particular setting can be re-used and transferred to other cases where labeled fault data is challenging or costly. Bearing this idea, we proposed a novel Adversarial Cross domain Data Generation (ACDG) framework to impute missing fault data for building fault detection and diagnosis where labeled data is costly. Unlike traditional Transfer Learning (TL)-related applications that adapt models or features learned in the source domain to the target domain, ACDG essentially “generates” the unknown sensor data for the target setting (target domain). This is accomplished by capturing the data patterns and common knowledge from known counterparts in the other setting (source domain), the inter-domain knowledge, and the intra-domain relations. The proposed ACDG framework is tested with the real-world Air Handling Unit (AHU) fault dataset of the ASHRAE Research Project 1312. Extensive experimental results on the cross-domain AHU fault data showed the effectiveness of ACDG in supplementing the data for a missing fault category by exploiting the underlying commonalities between different domain settings.

P154 Fungal spore count in a tertiary care hospital in Mumbai, India

Poster session 2, September 22, 2022, 12:30 PM - 1:30 PM ObjectivesFungal spores are ubiquitously present in the environment. Appropriate temperature and humidity can lead to fungal growth. It is of concern in a hospital environment. Diabetic and immunosuppressed persons are more vulnerable to such infections. The fairly humid and slightly warm climate of Mumbai is ideal for fungal growth. According to an article released in March 2021, the total fungal count in Mumbai was 16.2 CFUs. Here is a brief gist of how fungal spores were controlled within a tertiary hospital in Mumbai, India which is located near sea by simple but effective methods.MethodsAir sampling of the Operation Theatre (OT), Central Sterile Supply Department (CSSD), Bone marrow transplant (BMT) areas is done on weekly basis in the hospital and for areas such as ICU (Intensive Care Unit), Oncology (ONCO) Ward, Cardiac Catheterization (Cath) lab and Digital subtraction angiography (DSA) lab monthly air sampling is done to check for bacterial and fungal load. Two types of air samplers are used: Heico air sampler from HiMedia and Dyanamicro air sampler. OT, BMT, CSSD have HEPA (high efficiency particulate air) filters installed for filtration of air. The other areas like ICU, ONCO ward, Cath lab, and DSA lab do not have HEPA filters.ResultsIn the last 4 years there were two instances where fungal growth was observed once in BMT and once in ICU. In ICU Aspergillus niger growth was observed and in BMT there was a growth of multiple Aspergillus spp. It took nearly 3-4 months for the eradication of the fungus in BMT and 2 months to clear the fungus from ICU. Due to strict engineering control, we were able to restrict the spread within hospital.In BMT unit the growth was observed during rainy season when because of heavy rain there was seepage in one wall of the unit and also there was a leakage of sink in the ante-room area. When these repairs were done the fungal growth was not observed afterward.In ICU thorough cleaning of the Air Handling Unit (AHU) filter leads to resolution of the issue.Both these episodes were uneventful as no patient had any infection due to these.Factors that helped in controlling the fungal spores spread are:Controlled temperatureHumidityAC duct cleaningRegular AHU filter cleaningDifferent sizes of filters used for filtration of circulating air in hospitalNumber of air changesUse of antifungal paints in the hospitalRegular checks in hospital for any leakage or seepage issues.Monitoring of constructional activities in the hospital with appropriate measures to control fungal spore disseminationConclusionEven though the hospital is situated near sea and the outside air has high humidity and high microbial load, effective engineering measures and close monitoring of the areas can help in controlling the spread of fungus within the hospital. Routine periodic checks of the air for fungal spores can also help prevent nosocomial infections.

Analysis of Particulate and Microbiological Filtration Performance of Air Handling Unit Filters in a Low-Energy Office Building over 12 Months

Indoor air quality is an important consideration for the health and well-being of building occupants, and the SARS CoV-2 pandemic highlighted the importance of maintaining proper ventilation in buildings. Air handling units (AHUs) are used to provide fresh air and maintain occupant comfort. The objective of this work was to study the evolution of filtration efficiency in an AHU fitted with bag filters, installed to treat office air in a low-energy building, over a 12-month period. The particulate filtration efficiency (PFE) and the microbial filtration efficiency (MFE) were quantified by measuring particle size distribution and bacterial and fungal concentration in the air circulating in the AHU. The resulting microbial concentration measurements in the fresh air (between 10²–103 CFU/m3 for fungi and around 103 CFU/m3 for bacteria) were higher than those in the extracted air from the offices (between 101 and 102 CFU/m3 for fungi and around 102 CFU/m3 for bacteria). The PFE and MFE measured were almost constant throughout the 12 months, with an increase of the filter pressure drop from 70 to 90 Pa. The PFE and MFE were quite comparable for a particle diameter. Therefore, the measurement of PFE is a reliable indicator of the MFE.

Examination of Energy Efficiency of Air Handling Unit with Integrated Air to Air Heat Exchanger in Cooling Mode

Object of the present study is an experimental determination of parameters, showing efficiency of air handling unit with integrated air to air heat exchanger in cooling mode: effectiveness of supply side of air to air heat exchanger, coefficient of performance and specific fan power of air handling unit. A daily performance of air handling unit in cooling mode is conducted. Effectiveness of supply side of air to air heat exchanger in range of 50.5 % to 74.3 % is received. Coefficient of performance in range of 0.88 to 2.99 and specific fan power of air handling unit in range of 1.77 kW/(m3/s) to 3.06 kW/(m3/s) are received. A relation between effectiveness of supply side of air to air heat exchanger and ratio of heat capacity rates of supply and exhaust air is received. Effectiveness of supply side of air to air heat exchanger depends on values of mass flow of supply and the exhaust air. High values of mass flow of exhaust air responds to high effectiveness of supply side of air to air heat exchanger.

Roles of Dispute Handling Unit in Resolving Labour Disagreements in the Hotel Sector of North Region of Unguja, Tanzania

The study focused on the roles of Dispute Handling Unit in resolving labour disagreements in the hotel sector of Zanzibar . The specific objectives were : To examine the harmonious labour relationship that is created by Dispute Handling Unit in resolving labour disputes in the hotel sector of Zanzibar, to examine the training on labour laws for employers and employees by Dispute Handling Unit in resolving labour disputes, and To examine the influence of timely dispute resolution by Dispute Handling Unit on resolving disputes in the hotel sector of Zanzibar The descriptive research design was adopted. A sample of 152 respondents participated in the study, and data were collected using a questionnaire. The findings found a significant positive relationship among harmonious labour relationship, training of labour laws, timely dispute resolution, and dispute resolving in Zanzibar. However, the study concluded that DHU's creation of a harmonious labour relationship in the hotel sector did not lead to resolving disputes in the Zanzibar hotel sector because the low effort was made by the DHU in harmonious labour relationship in the hotel sector in Zanzibar. Also, it was found that training by DHU on labour laws helped resolve disputes in the hotel sector in Zanzibar because they were not frequently organised, and timely dispute resolution influenced dispute resolution in the hotel sector in Zanzibar. Lastly, the study concluded that there were significant positive relationships among creating a harmonious labour relationship, timely dispute resolution, DHU training, and resolving disputes in the Zanzibar hotel sector.

Air Handling Unit Shutdowns During Scheduled Unoccupied Hours: US Commercial Building Stock Prevalence and Energy Impact

Abstract Commercial buildings account for 18% of U.S. energy consumption, with 44% used for heating, ventilation, and air conditioning (HVAC). American Society of Heating, Refrigerating and Air Conditioning Engineers (ASHRAE) 90.1 requires HVAC systems to shutdown fans and outdoor air ventilation during unoccupied times, only allowing fans to cycle on, without outdoor air, to maintain thermostat setpoints. However, it is minimally understood how often existing building operations align with energy code requirements and the energy implications of not doing so. This study used building automation system data from 843 buildings containing 5706 air handling units (AHUs) to determine three unoccupied AHU shutdown control schemes ranging in efficiency and then estimated their prevalence in the U.S. commercial building stock, segmented by building type. ComStock was then used to analyze the energy savings potential of implementing the most energy efficient unoccupied shutdown control scheme in non-participating buildings across the U.S commercial building stock. Results show that only 23% of AHUs align completely with the ASHRAE 90.1 requirement. ComStock modeling results show 4% annual stock energy savings by switching all non-participating buildings to the most efficient scheme, with 19% annual energy savings demonstrated for the median building switching from the least efficient scheme to the most efficient. Findings also show 114.5 TBtu electricity and 75.8 TBtu natural gas fuel savings when converting to the most efficient scheme. These findings help stakeholders understand the high prevalence of buildings not aligning with the ASHRAE-90.1 requirements for unoccupied AHU shutdowns and the energy savings potential of utilizing the most efficient unoccupied AHU shutdown scheme.

Multiscale Shear Properties and Flow Performance of Milled Woody Biomass

One dominant challenge facing the development of biorefineries is achieving consistent system throughput with highly variant biomass feedstock quality and handling performance. Current handling unit operations are adapted from other sectors (primarily agriculture), where some simplifying assumptions about granular mechanics and flow performance do not translate well to a highly compressible and anisotropic material with nonlinear time- and stress-dependent properties. This work explores the shear and frictional properties of loblolly pine at multiple experimental test apparatus and particle scales to elucidate a property window that defines the shear behavior over a range of material attributes (particle size, size distribution, moisture content, etc.). In general, it was observed that the bulk internal friction and apparent cohesion depend strongly on both the stress state of the sample in granular shear testers and the overall particle size and distribution span. For equipment designed to characterize the quasi-static shear stress failure of bulk materials ranging from 50 to 1,000 ml in test volume, similar test results were observed for finely milled particles (50% passing size of 1.4 mm) with a narrow size distribution (span between 10 and 90% passing size of 0.9 mm), while stress chaining and over-torque issues persisted for the bench-scale test apparatus for larger particle sizes or widely dispersed sample sizes. Measurement of the anisotropic particle–particle friction ranged from coefficients of approximately 0.20 to 0.45 and resulted in significantly higher and more variable friction measurements for larger particle sizes and in perpendicular alignment orientations. To supplement these laboratory-scale properties, this work explores the flow of loblolly pine and Douglas fir through a pilot-scale wedge-shaped hopper and a screw feeder. For the gravity-driven hopper flow, the critical arching distance and mass discharge rate ranged from approximately 10 to 30 mm and 2 to 16 tons/hour, respectively, for both materials, where the arching distance depends strongly on the overall particle size and depends less on the hopper inclination angle. Comparatively, the auger feeder was found to be much more impacted by the size of the particles, where smaller particles had a more consistent and stable flow while consuming less power.

A high-fidelity building performance simulation test bed for the development and evaluation of advanced controls

We present an open-source building performance simulation test bed, the Advanced Controls Test Bed (ACTB), that interfaces high-fidelity Spawn of EnergyPlus building models, with advanced controllers implemented in Python. The ACTB leverages the Building Optimization Testing and Alfalfa platforms for managing simulations, providing an external clock, a representational state transfer (REST) application programming interface (API), and key performance indicators for evaluating the effectiveness of control strategies. The REST API allows the development of external controllers programmed in languages such as Python, which provides flexibility and a rich choice of scientific libraries for designing control sequences. We present three test cases based on the U.S. Department of Energy's Reference Small Office Building to demonstrate the ACTB's capabilities: (a) rule-based controls compliant with ASHRAE Guideline 36 control sequences; (b) an economic model predictive control implemented using do-mpc; and (c) a deep Q-network reinforcement learning agent implemented using OpenAI Gym. Abbreviations: ACTB: Advanced Controller Test Bed; AHU: Air Handling Unit; AI:Artificial Intelligence; API: Application Programming Interface; BEM: Building EnergyModeling; BSS: Best Subset Selection; DOE: Department of Energy; DQN: Deep-QNetwork; EKF: Extended Kalman Filter; FMI: Functional Mock-up Interface; FMU:Functional Mock-up Unit; FSS: Forward Stepwise Selection; HVAC: Heating; Ventilationand Air Conditioning; KPI: Key Performance Indicator; LTI: Linear Time-Invariant; MBL: Modelica Buildings Library; MHE: Moving Horizon Estimator; MPC: ModelPredictive Control; N4SID: Numerical Subspace State-Space System Identification; REST: Representational State Transfer; RL: Reinforcement Learning; ROM: Reducedorder model

ANALISIS OPERASI POMPA CHILLER MENGGUNAKAN FIXED SPEED DRIVE DAN VARIABLE SPEED DRIVE (STUDI KASUS : FOUR SEASON HOTEL JIMBARAN)

Four Season Jimbaran Hotel is one of the hotels in Bali using a cooling system which isusually called the water chiller. The electrical energy consumption in Four Season Hotel is oneof the factors that increase the use of electrical energy in which the star delta system is stillused to switch on the pump. Along with the electricity rate which keeps increasing every year,the electrical energy consumption in Four Season Hotel can increase the operational cost. It isconcluded that one of the largest electrical energy consumptions is water chiller pump. Chillerpump is a pump used for pushing water flow towards chiller condenser and Air Handling Unit(AHU) when the water chiller system is still active. Starters of the chiller pump used in FourSeason Jimbaran Hotel are inverter and star delta. The method used in conducting research was calculation of the electrical energy requirement and cost in two pumps set by star delta atan initial frequency of 50Hz in water chiller pump 160 TR, compared with inverter system withthe decrease of frequency by 5Hz (45Hz) in water chiller pump 230 TR. Monitoring wasperformed by analyzing the consumption of electrical energy (kWh), temperature (°C), andhumidity (%) in every pump set by every system. In these two pumps, energy consumption(kWh) and cost were compared in daily, weekly, and monthly needs. From the result ofresearch, in inverter system, the frequency reduction by 5Hz in water chiller pump 230 TR cansave electrical energy of 117,120 kWh and the cost of IDR 130,471,680 in the next five years.The comparison analysis of operation of the chiller pump supplied with star delta (fixed speeddrive) with an inverter (variable speed drive) has a difference energy consumption of 117,120kWh in both systems and the difference cost is Rp. 130,471,680.00 in next 5 years.

Air Handling Unit Monitoring and Control System Based on Internet of Things

The Internet of Things (IoT) contributed to developing new concepts of monitoring and control systems for Air Handling Units (AHU). This paper proposes a modification of the traditional temperature monitoring and controlling system in AHU to a system based on the principles of the IoT. This is to take advantage of the features and characteristics of the Internet of things in accessing the system, following it up, and modifying it, Also evaluate the extent of reliance on software instead of hardware if the physical controller is replaced with a cloud controller in terms of data transfer rate and security of communication between the controller and field devices. The proposed system is applied to a real AHU. In the proposed system, the existing traditional temperature sensor and actuator are modified to be connected to the internet. With this modification, data can be received and sent with the IoT platform. So, the physical controller is replaced by a cloud controller on the IoT platform to receive the sensor readings and send the control signals to the actuator. Moreover, it configures a temperature alarm mails system to be sent to the authorized people in case of the temperature value is out of limits. The proposed system gives remote access to display the temperature readings and the controller’s output. Thus, the performance of the system can be monitored with the ability to modify the controller to suit the system’s needs.

Thermal, physical, and engineering properties of Okra (Abelmoschus esculentus L. (Moench) grown in Nigeria

As a result of lack of information about the thermal, physical and engineering properties of okra gown in Nigeria some of these properties were studied in order to contribute to the database for properties related to grading, handling, packaging, transportation, cleaning, processing, storage and other futuristic processing units. The study showed that the thermal conductivity, specific heat capacity, latent heat and thermal diffusivity were 0.26 Wm-1K-1, 1.77 KJKg-1K-1, 16.75 KJKg-1 and 0.06×10-7m2s-1 respectively. The mean values of length, width, thickness, arithmetic mean diameter, geometric mean diameter, equivalent diameter, surface area, volume, sphericity and coefficient of contact surface of okra seeds were 6.58 mm, 4.75 mm, 2.37 mm, 4.56 mm, 4.20 mm, 4.33 mm, 55.44 mm2, 38.80 mm3, 63.83% and 63.97% respectively. While the aspect ratio, flakiness, 1000 seed mass, bulk density, true density and porosity were 72.19%, 49.89%, 47.43g, 0.61, 0.62, and 27.00% respectively. The study also revealed that the angle of ripose and coefficient of static friction for stainless steel, glass, formica and plywood were 24.51o, 0.30, 0.34, 0.37 and 0.40 respectively. Stainless steel had the lowest coefficient of static friction and so will be most suitable among the materials tested for the production of okra seeds processing machines.

A Digital Twin predictive maintenance framework of air handling units based on automatic fault detection and diagnostics

The building industry consumes the most energy globally, making it a priority in energy efficiency initiatives. Heating, ventilation, and air conditioning (HVAC) systems create the heart of buildings. Stable air handling unit (AHU) functioning is vital to ensuring high efficiency and extending the life of HVAC systems. This research proposes a Digital Twin predictive maintenance framework of AHU to overcome the limitations of facility maintenance management (FMM) systems now in use in buildings. Digital Twin technology, which is still at an initial stage in the facility management industry, use Building Information Modeling (BIM), Internet of things (IoT) and semantic technologies to create a better maintenance strategy for building facilities. Three modules are implemented to perform a predictive maintenance framework: operating fault detection in AHU based on the APAR (Air Handling Unit Performance Assessment Rules) method, condition prediction using machine learning techniques, and maintenance planning. Furthermore, the proposed framework was tested in a real-world case study with data between August 2019 and October 2021 for an educational building in Norway to validate that the method was feasible. Inspection information and previous maintenance records are also obtained through the FM system. The results demonstrate that the continually updated data combined with APAR and machine learning algorithms can detect faults and predict the future state of Air Handling Unit (AHU) components, which may assist in maintenance scheduling. Removing the detected operating faults resulted in annual energy savings of several thousand dollars due to eliminating the identified operating faults.

A Decentralized Boltzmann-machine-based fault diagnosis method for sensors of Air Handling Units in HVACs

As a key module in a Heating, Ventilation, and Air Conditioning (HVAC) system, an Air Handling Unit (AHU) is controlled based on information collected by sensors to satisfy human thermal comfort and air quality requirements. Fault diagnosis is critical since it allows maintenance crews to know which faults have occurred to improve system availability. However, fault diagnosis in AHUs is challenging because of the following reasons. First, widely used fault indicators are correlated with changing environments, e.g., weather dynamics or occupants, thus may not be enough to distinguish faults. Second, existing decentralized fault diagnosis methods developed for sensors require solving many optimization problems, leading to high computational requirements. To overcome these challenges, this paper develops a decentralized Boltzmann-machine-based method. To address the first issue, residuals between actual values of several sensor readings and their estimates are considered as fault indicators since they are not related to changing environments. To address the second issue, a novel decentralized voting mechanism is developed based on the convergence characteristic of the Boltzmann machine to locate sensor faults while avoiding solving many optimization problems. However, the established Boltzmann machine usually has an asymmetric weight matrix, and thus it does not converge to the state estimates of sensors. To guarantee convergence, a new symmetrization method is developed to symmetrize the Boltzmann machine by adding an extra unit into the Boltzmann machine to reset the weight matrix while retaining the original voting. Experimental results demonstrate that our method can effectively diagnose sensor faults with high diagnostic accuracy.

Transforming a Historic Public Office Building in the Centre of Rome into nZEB: Limits and Potentials

According to the last census of 2019, about two million Italian buildings are more than 100 years old. Building energy retrofitting involves a diverse mix of influencing factors, depending on history, intended use, and construction techniques. This paper aims to assess the energy needs of a historic building by evaluating the variability of climatic conditions and internal loads, as well as the thermal capacity of the building envelope. The energy analysis was conducted using dynamic simulation systems (TRNSYS). The purpose of the study is to provide an analysis of the current energy conditions of the building to identify the main critical issues and suggest the most suitable interventions to be implemented. All the transformations were conducted to meet the nZEB requirements and evaluate technical and economic feasibility, compatibility with architectural and landscape constraints, and large-scale replicability. Specifically, to reach the proposed targets, a 36 kWp PV system was implemented for an area of 210 m2, in addition to the Air Handling Unit (AHU) already present. The profit index is above the unit, and it yields a time range between three and four years. Therefore, fully respecting the energy performance parameters required by the Italian legislation, the study demonstrated the unattainability of the nZEB class for a listed building.

Benefits of a hygienic, efficient and smart solution for ventilation systems in the era of the “New Normal”

Ventilation with external air is one of the most effective strategies to eliminate pathogens from indoor environments. The Air Handling Unit (AHU) is the heart of the ventilation system in commercial buildings and it is designed to achieve this goal. The guidelines for the reduction of the risk of spreading the Sars-CoV2-19 virus have introduced new operating criteria for ventilation systems, which counterbalance a better healthiness of the air in rooms with a higher energy consumption. Unfortunately, there is no standardized and shared approach to date for the designer to use as a starting point to balance these two different needs. Therefore, engineers should be aware of and pay a greater attention to the identification of practical and effective design solutions. This document proposes a technological solution for AHUs based on three key principles: Hygiene, Energy Saving and Digitization. We propose a complete and integrated architecture for the recovery of energy, humidification, system control and continuous monitoring of operating conditions, capable of ensuring health and safety, on the one hand, in compliance with the main guidelines, such as VDI 6022, and of increasing the overall efficiency of the equipment, on the other hand. The analysis compares this innovative solution with several conventional functional schemes or with systems otherwise linked to the new requirements emerged with the pandemic, and shows the resulting economic benefits, even for different climate conditions. The result shows how the selection of integrated systems for the control of ventilation, energy recovery and humidification is a winning solution that ensures healthy environments, while simultaneously reducing operating costs