Hasil untuk "Heating and ventilation. Air conditioning"

Austin J. Lin, Jacques A. de Chalendar, Johanna L. Mathieu

Commercial building Heating, Ventilation, and Air Conditioning (HVAC) systems can provide flexibility to the electricity grid. Some researchers have found it convenient to model HVAC systems as virtual batteries. These models also better align with models used by grid planners and operators. However, experiments have shown that HVAC load shifting can be inefficient, and virtual battery models do not capture this inefficiency well. While the models typically use the average room temperature as the system's ``state of charge," they do not capture other factors that affect HVAC power/energy such as airflow and mixing. Here, we develop a new analytical building model to explore how incomplete mixing of supply air into a conditioned space leads to inefficiency in a virtual battery capturing the dynamics of HVAC fan power load shifting. The model qualitatively matches experimental results better than previous models, and shows that, as mixing becomes worse, the virtual battery becomes less efficient. Unfortunately, air mixing is unmeasured/unmeasurable. However, we show that, by closing the loop around measurements of fan power, we can improve the virtual battery's performance without the need for air mixing measurements. For example, in one case, we show a roundtrip efficiency improvement from 0.75 to 0.99.

Shri H. Viswanathan, Ankit Joshi, Isabella DeClair et al.

Overheating poses significant threats to human health and productivity. In hot conditions, the human body primarily cools through sweat evaporation; however, we show that understanding of physical phenomena controlling the evaporation rate is surprisingly incomplete. This rate is equal to the product of the skin to air water vapor concentration difference and the flow dependent mass transfer coefficient, which, according to the Lewis heat and mass transfer analogy, is proportional to the convective heat transfer coefficient. In low wind, free convection conditions, current models for the human heat transfer coefficients consider only temperature driven air buoyancy. Here, we show that in arid heat, humidity from sweat exerts a comparable but opposing buoyant effect. Using sweating thermal manikin experiments and digital twin multiphysics simulations, we demonstrate that the dueling thermal and humidity induced buoyancy can severely suppress sweat evaporation (e.g., by over half in conditions that occur in Arizona for one-third of the year). Neglecting humidity-induced buoyancy leads to substantial errors in thermoregulation model predictions; within 2 hour exposure to typical arid heat conditions, core temperature increases by 1C more than predicted by legacy calculations. We provide compact, physics informed models for free convective heat transfer coefficients for wide temperature and humidity ranges, enabling improved thermoregulation modeling and thermal audits for more accurate heat stress assessment and optimization of extreme heat mitigation strategies.

Henry C. Burridge, Sen Liu, Sara Mohamed et al.

The quality of the classroom environment, including ventilation, air quality and thermal conditions, has an important impact on children's health and academic achievements. The use of portable HEPA filter air cleaners is widely suggested as a strategy to mitigate exposure to particulate matter and airborne viruses. However, there is a need to quantify the relative benefits of such devices including the impacts on energy use. We present a simple coupled dynamic thermal and air quality model and apply it to naturally ventilated classrooms, representative of modern and Victorian era construction. We consider the addition of HEPA filters with, and without, reduced opening of windows, and explore concentrations of carbon dioxide (\co), \PM, airborne viral RNA, classroom temperature and energy use. Results indicate the addition of HEPA filters was predicted to reduce \PM~ by 40--60\% and viral RNA by 30--50\% depending on the classroom design and window opening behaviour. The energy cost of running HEPA filters is likely to be only 1\%--2\% of the classroom heating costs. In scenarios when HEPA filters were on and window opening was reduced (to account for the additional clean air delivery rate of the filters), the heating cost was predicted to be reduced by as much as -13\%, and these maximum reductions grew to -46\% in wintertime simulations. In these scenarios the HEPA filters result in a notable reduction in \PM~and viral RNA, but the \co\ concentration is significantly higher. The model provides a mechanism for exploring the relative impact of ventilation and air cleaning strategies on both exposures and energy costs, enabling an understanding of where trade-offs lie.

Qian Yang, Jin Xu, Wenrui Liu et al.

Recently, instruction-following audio-language models have received broad attention for human-audio interaction. However, the absence of benchmarks capable of evaluating audio-centric interaction capabilities has impeded advancements in this field. Previous models primarily focus on assessing different fundamental tasks, such as Automatic Speech Recognition (ASR), and lack an assessment of the open-ended generative capabilities centered around audio. Thus, it is challenging to track the progression in the Large Audio-Language Models (LALMs) domain and to provide guidance for future improvement. In this paper, we introduce AIR-Bench (\textbf{A}udio \textbf{I}nst\textbf{R}uction \textbf{Bench}mark), the first benchmark designed to evaluate the ability of LALMs to understand various types of audio signals (including human speech, natural sounds, and music), and furthermore, to interact with humans in the textual format. AIR-Bench encompasses two dimensions: \textit{foundation} and \textit{chat} benchmarks. The former consists of 19 tasks with approximately 19k single-choice questions, intending to inspect the basic single-task ability of LALMs. The latter one contains 2k instances of open-ended question-and-answer data, directly assessing the comprehension of the model on complex audio and its capacity to follow instructions. Both benchmarks require the model to generate hypotheses directly. We design a unified framework that leverages advanced language models, such as GPT-4, to evaluate the scores of generated hypotheses given the meta-information of the audio. Experimental results demonstrate a high level of consistency between GPT-4-based evaluation and human evaluation. By revealing the limitations of existing LALMs through evaluation results, AIR-Bench can provide insights into the direction of future research.

Emanuele Spinosa, Silvano Grizzi, Alessandro Iafrati

The water entry at high horizontal speed of double-curvature specimens, reproducing the rear part of the fuselage that first gets in contact with the water during aircraft ditching, is investigated experimentally. Three shapes are analysed, representing different aircraft types. Pressure and load measurements are taken, supported by underwater high-speed visualization. The effects of different horizontal speeds, pitch angles, and curvatures are analysed, while keeping a constant vertical-to-horizontal velocity ratio. It is observed that the longitudinal curvature plays a significant role in the hydrodynamics, potentially leading to cavitation and ventilation in the rear part of the specimen at high speeds. The transverse curvature affects the pressures and loads both at the front and at the rear, since a lower transverse curvature increases the possibility of the fluid to escape from the sides. An increase in pitch angle results in an increased loading, in terms of both amplitude and distribution. Finally, an increased horizontal speed leads to higher loads at the front but also affects the cavitation and ventilation modalities at the rear. The load scaling for flat plates also applies to these specimens at the front, but the occurrence of cavitation and ventilation invalidates it at the rear. The time evolution of the cavitation region and of the wetted area are examined through advanced image processing techniques and pressure data analysis. The comparison with the geometric intersection area of the specimen with the still water surface provides further insight into the hydrodynamic phenomena during the water entry.

Anwesh Mohanty, Supreeth P. Shashikumar, Jonathan Y. Lam et al.

In the intensive care unit, the capability to predict the need for mechanical ventilation (MV) facilitates more timely interventions to improve patient outcomes. Recent works have demonstrated good performance in this task utilizing machine learning models. This paper explores the novel application of a deep learning model with multi-head attention (FFNN-MHA) to make more accurate MV predictions and reduce false positives by learning personalized contextual information of individual patients. Utilizing the publicly available MIMIC-IV dataset, FFNN-MHA demonstrates an improvement of 0.0379 in AUC and a 17.8\% decrease in false positives compared to baseline models such as feed-forward neural networks. Our results highlight the potential of the FFNN-MHA model as an effective tool for accurate prediction of the need for mechanical ventilation in critical care settings.

Min Young Hwang, Burcu Akinci, Mario Bergés

Current fault diagnosis (FD) methods for heating, ventilation, and air conditioning (HVAC) systems do not accommodate for system reconfigurations throughout the systems’ lifetime. However, system reconfiguration can change the causal relationship between faults and symptoms, which leads to a drop in FD accuracy. In this paper, we present Fault-Symptom Brick (FSBrick), an extension to the Brick metadata schema intended to represent information necessary to propagate system configuration changes onto FD algorithms, and ultimately revise FSRs. We motivate the need to represent FSRs by illustrating their changes when the system reconfigures. Then, we survey FD methods’ representation needs and compare them against existing information modeling efforts within and outside of the HVAC sector. We introduce the FSBrick architecture and discuss which extensions are added to represent FSRs. To evaluate the coverage of FSBrick, we implement FSBrick on (i) the motivational case study scenario, (ii) Building Automation Systems’ representation of FSRs from 3 HVACs, and (iii) FSRs from 12 FD method papers, and find that FSBrick can represent 88.2% of fault behaviors, 92.8% of fault severities, 67.9% of symptoms, and 100% of grouped symptoms, FSRs, and probabilities associated with FSRs. The analyses show that both Brick and FSBrick should be expanded further to cover HVAC component information and mathematical and logical statements to formulate FSRs in real life. As there is currently no generic and extensible information model to represent FSRs in commercial buildings, FSBrick paves the way to future extensions that would aid the automated revision of FSRs upon system reconfiguration.

Nikhil Pachauri, Chang Wook Ahn

Shuzhe Chen, Li Li, Zhichao Lin et al.

The Pulmonary Function Test (PFT) is an widely utilized and rigorous classification test for lung function evaluation, serving as a comprehensive tool for lung diagnosis. Meanwhile, Electrical Impedance Tomography (EIT) is a rapidly advancing clinical technique that visualizes conductivity distribution induced by ventilation. EIT provides additional spatial and temporal information on lung ventilation beyond traditional PFT. However, relying solely on conventional isolated interpretations of PFT results and EIT images overlooks the continuous dynamic aspects of lung ventilation. This study aims to classify lung ventilation patterns by extracting spatial and temporal features from the 3D EIT image series. The study uses a Variational Autoencoder network with a MultiRes block to compress the spatial distribution in a 3D image into a one-dimensional vector. These vectors are then concatenated to create a feature map for the exhibition of temporal features. A simple convolutional neural network is used for classification. Data collected from 137 subjects were finally used for training. The model is validated by ten-fold and leave-one-out cross-validation first. The accuracy and sensitivity of normal ventilation mode are 0.95 and 1.00, and the f1-score is 0.94. Furthermore, we check the reliability and feasibility of the proposed pipeline by testing it on newly recruited nine subjects. Our results show that the pipeline correctly predicts the ventilation mode of 8 out of 9 subjects. The study demonstrates the potential of using image series for lung ventilation mode classification, providing a feasible method for patient prescreening and presenting an alternative form of PFT.

Justin Tahmassebpur, Patrick H. Diamond

We show that enhanced turbulent mixing can be used to mitigate airborne COVID-19 transmission by dispersing virus-laden clouds in enclosed, poorly ventilated spaces. A simple system of fan-driven turbulent jets is designed so as to minimize peak concentrations of passive contaminants on time scales short compared to the room ventilation time. Standard Reynolds-average and similarity methods are used, and combinations of circular and radial wall jets are considered. The turbulent diffusivity and contaminant mixing time are calculated. Results indicate that this approach can significantly reduce peak virus cloud concentrations, especially in small spaces with low occupancy, such as restrooms. Turbulent mixing is, of course, ineffective in the absence of ventilation.

Anish Pal, Riddhideep Biswas, Sourav Sarkar et al.

The risks of disease transmission due to these droplets are significantly high in confined public spaces like elevators. A numerical analysis using OpenFOAM has been performed in this work to investigate the droplet dispersion routes in an enclosed environment resembling an elevator. The effect of two scenarios on droplet dispersal, namely the quiescent and the fan-driven ventilation, both subjected to various climatic conditions (of temperature and humidity) ranging from cold humid (15 degree C, 70 percent relative humidity) to hot dry (30 degree C, 30 percent relative humidity and 30 degree C, 50 percent relative humidity) and hot humid (30 degree C, 70 percent relative humidity) have been studied. A risk factor derived from a dose response model based on the time averaged pathogen quantity present around the passengers mouth is used to quantify the risk of infection through airborne mode. It is found that the hot, dry quiescent scenario poses the greatest threat of infection (spatio averaged risk factor 42 percent), whereas the cold humid condition poses the least risk of infection (spatio averaged risk factor 30 percent. The implementation of Fan ventilation at low RPM increases the risk as compared to a quiescent scenario, however with the increase in speed the risk decreases significantly. The Fan ventilation scenario with 1100 RPM (having a spatio averaged risk factor of 10 percent) decreases the risk of infection by 67 percent in a hot, dry climatic condition as compared to a quiescent scenario. However, there is no significant reduction in risk beyond a certain Fan speed, 1100 RPM. The deposition potential of aerosolized droplets in various parts of the respiratory tract namely the Extrathoracic and the Alveolar and Bronchial regions has been analyzed thoroughly because of the concomitant repercussions of infection in various depths of the respiratory region.

Liu Lu, Liu Yantao, Zhan Feilong et al.

Air conditioning systems commonly adopt multipath heat exchangers, which require distributors to guide the two-phase refrigerant to each flow path of heat exchangers uniformly. The gas-liquid two phase refrigerant may separate when it flows through the connecting tubes of distributors with bends, resulting in the deterioration of distribution uniformity. In this study, an optimization method was proposed for changing the traditional single-bending of tubes to the multi-bending of tubes to reduce the degree of separation of the gas-liquid two phase refrigerant. First, the influence of the bending structure factors of the connecting tubes on the distribution uniformity was investigated, including the bending angle, bending radius, and tube diameter. Second, the optimized structural parameters of the bending angle, bending radius, and tube diameter were combined to design an optimized connecting tube for the distributor. Finally, the distribution unevenness was compared between the optimized and original connecting tubes of the distributor. The results from the case studies in this study show that the bending angle is the main influencing factor, and the proposed optimization connecting tube of the distributor with three bends can reduce the distribution unevenness by 64.4% compared with the original one with a single bend.

S. Algarni, C. Saleel, M. A. Mujeebu

Leyan Pan, Cichong Liu, Zhang Ziqi et al.

Abstract The stock of electric vehicle is booming recently. However, the range of the electric vehicle is still a main barrier in its adoption. Air conditioning system is the second largest energy consumption device on vehicle, which will cause significant range reduction during operation. In this paper, the energy-saving effect of utilizing the recirculated air in air conditioning system is evaluated. The outside air ventilation rate based on CO2 limits and windshield anti-fog requirements are calculated, and the energy-saving effect of this strategy in 30 cities across China is evaluated using an annual energy consumption model. It is found that utilizing the recirculated air can save 14–46% heating energy when using PTC heater, and 33–57% heating energy in heat pump AC system. Throughout a year, utilizing the recirculated air can extend the driving range by 11–30%.

Pengmin Hua, Tianyi Zhao, Wuhe Dai et al.

Xu Feng, Zhenying Zhang, Jianjun Yang et al.

Shanshan Cai, Xu Luo, Xing Zhou et al.

Yaxiu Gu, Yang Zou, Song Pan et al.

Yasser Khan, Hossain Mohammad Fahad, Sifat Muin et al.

Coronavirus disease 2019 (COVID-19) has created an unprecedented need for breathing assistance devices. Since the demand for commercial, full-featured ventilators is far higher than the supply capacity, many rapid-response ventilators are being developed for invasive mechanical ventilation of patients. Most of these emergency ventilators utilize mechanical squeezing of bag-valve-masks or Ambu-bags. These "bag squeezer" designs are bulky and heavy, depends on many moving parts, and difficulty to assemble and use. Also, invasive ventilation requires intensive care unit support, which may be unavailable to a vast majority of patients, especially in developing countries. In this work, we present a low-cost ($<$\$200), portable (fits in an 8"x8"x4" box), non-invasive ventilator (NIV), designed to provide relief to early-stage COVID-19 patients in low-resource settings. We used a high-pressure blower fan for providing noninvasive positive-pressure ventilation. Our design supports continuous positive airway pressure (CPAP) and bilevel positive airway pressure (BiPAP) modes. A common concern of using CPAP or BiPAP for treating COVID-19 patients is the aerosolization of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We used a helmet-based solution that contains the spread of the virus. Our end-to-end solution is compact, low-cost ($<$\$400 including the helmet, viral filters, and a valve), and easy-to-use. Our NIV provides 0-20 cmH$_{2}$O pressure with flow rates of 60-180 Lmin$^{-1}$. We hope that our report will encourage implementations and further studies on helmet-based NIV for treating COVID-19 patients in low-resource settings.

C. Galbiati, A. Abba, P. Agnes et al.

Presented here is the design of the Mechanical Ventilator Milano (MVM), a novel mechanical ventilator designed for rapid mass production in response to the COVID-19 pandemic to address the urgent shortage of intensive therapy ventilators in many countries, and the growing difficulty in procuring these devices through normal supply chains across borders. This ventilator is an electro-mechanical equivalent of the old and reliable Manley Ventilator, and is able to operate in both pressure-controlled and pressure-supported ventilation modes. MVM is optimized for the COVID-19 emergency, thanks to the collaboration with medical doctors in the front line. MVM is designed for large-scale production in a short amount of time and at a limited cost, as it relays on off-the-shelf components, readily available worldwide. Operation of the MVM requires only a source of compressed oxygen (or compressed medical air) and electrical power. Initial tests of a prototype device with a breathing simulator are also presented. Further tests and developments are underway. At this stage the MVM is not yet a certified medical device but certification is in progress.