Hasil untuk "Heating and ventilation. Air conditioning"

Saman Taheri, A. Razban

Zhen-ying Zhang, Jiayu Wang, Xu Feng et al.

Abstract The air conditioning (AC) system provides cool, heating and ventilation in the cabin of the electric vehicles (EVs). It is necessary to control the interior thermal environments of the vehicle and ensure safety in visibility. Because AC systems are electrically powered, vehicle range is reduced drastically when the AC system is operating. EVs present a particular challenge to the development of more efficient AC systems for automotive applications. In this paper, the state of the art for various AC system solutions to EVs was critically reviewed. The investigations of alternative solutions are continuing along many parallel routes, e.g. vapor compression refrigeration-dedicated heater AC systems, reversible vapor compression heat pump AC systems, non-vapor compression AC systems and integrated thermal management system combined AC and battery pack. The characteristics and particular applications of each solution have been extensively discussed. Finally, a comparison listing the various pros and cons of the different available solutions was presented.

Yue Bao, Wang Longyan, Cao Haomin et al.

To simulate and optimize an enhanced vapor-injection system, it is necessary to develop a vapor-injection scroll compressor model with fast calculation speed, high accuracy, good extrapolation accuracy, and few parameters for computation. However, existing models cannot meet these demands simultaneously. In this study, a physics-based explicit form semi-empirical model of a scroll compressor with vapor injection was developed to predict its mass flow rate, input power, and discharge temperature. In this model, the suction mass flow rate was derived by correcting the pressure ratio using the specific heat ratio and multiplying it by the quadratic function of frequency. The injection mass flow rate was based on the assumption of an isochoric mixing process and obtained by expanding the coefficients. The discharge flow rate was the sum of the suction and injection mass flow rates. The input power was based on the assumption of isentropic compression and corrected by pressure, and the discharge temperature model was based on the heat leakage factor. The model was validated based on experimental data, and the results showed that the model had a calculation speed of milliseconds, and was able to accurately predict the performance of the compressor, with the average deviations of the suction mass flow rate and discharge mass flow rate both within 2%, and the average deviations of the injection mass flow rate, input power, and discharge temperature within 5%, 3%, and 3 ℃, respectively. The model can provide reasonable results outside the range of fitted conditions, and the amount of data required for model fitting has been reduced by more than 50% compared to that of existing models.

Carla Rodrigues, Fausto Freire

For product systems that heavily rely on user profiles, such as buildings, vehicles, HVAC (heating, ventilation, and air conditioning) systems, or toilet systems, estimating environmental impacts during the use phase can be challenging, which can be a major contributor to life cycle impacts. User-behavior uncertainty has not been sufficiently addressed in life cycle assessment studies. The goal of this article is twofold: i) to propose a probabilistic life cycle approach that combines user-behavior scenario analysis, pairwise comparative analysis, and global sensitivity analysis, and ii) to apply this approach to a novel toilet system (WashOne) for comparison with a conventional system (toilet and bidet). A combination of deterministic usage patterns and stochastic scenarios (as a result of combining uncertain parameters) was employed. A pairwise comparison indicator presents uncertain results, indicating that the WashOne has significantly lower environmental impacts than the conventional system in all categories. Results from the global sensitivity analysis (using Spearman Rank Correlation Coefficient) show that toilet paper (in the conventional system) and washlet use (in the novel system) have the most significant effect on the impacts. This article concludes that (i) novel systems that greatly depend on user preferences can reduce impacts compared to conventional systems, and (ii) it highlights that user behavior becomes less influential as product systems are designed to be more efficient.

Muhammad Usman, Muhammad Usman, Owais Ahmad et al.

The building sector accounts for nearly 40% of global primary energy consumption, with heating, ventilation, and air conditioning (HVAC) systems contributing significantly to energy use and greenhouse gas emissions. Conventional HVAC systems face challenges in addressing humidity control and efficiency, particularly in cold and dry climates. This research demonstrates the development and transient simulation of a novel solar-assisted desiccant wheel-based system for heating and humidification (SDHH) in Taxila, Pakistan. The proposed system includes a desiccant wheel, heat wheel, water-to-air heat exchanger, and a direct evaporative cooler. An array of flat plate collectors supply hot water to the heat exchanger. TRNSYS simulations investigated the performance of SDHH by evaluating heating capacity, humidification, and indoor temperature and humidity values in winter. Results show that the SDHH system maintained the required temperature in the zone and improved the zone humidity level. The desiccant wheel increased the absolute humidity of product air by 0.003 kg/kg. The average indoor temperature was 21 °C, and the average absolute humidity was around 0.008 kg/kg. These results justify using the proposed system in dry and cold climate conditions.

Sina Saffaran, Tng Chang Kwok, Don Sharkey et al.

Background: Mechanical ventilation is life-saving for preterm infants with respiratory distress syndrome but can also contribute to lung injury and long-term morbidity. Protective ventilation strategies are recommended, yet implementation in neonatal intensive care units remains inconsistent, and infants continue to be exposed to injurious ventilator settings. Objective: To develop and validate a cohort of neonatal digital twins, based on mechanistic models of cardiopulmonary physiology calibrated to individual patient data, as a tool for simulating and optimising protective ventilation strategies. Methods: A high-fidelity computational simulator of human cardiopulmonary physiology was adapted to neonatal-specific parameters, including lung compliance, dead space, pulmonary vascular resistance, oxygen consumption, and fetal haemoglobin oxygen affinity. Digital twins were generated using data at 65 time points from 11 preterm neonates receiving volume-controlled ventilation. Model parameters were calibrated to minimise the error between simulated and observed PaO2, PaCO2, and peak inspiratory pressure (PIP). Results: Digital twins reproduced measured data with mean absolute percentage errors of 3.9% (PaO2), 3.0% (PaCO2), and 5.8% (PIP) across the cohort. Predictions for uncalibrated variables (pHa, SaO2, mean and minimum airway pressure) also showed high accuracy, with errors <5%. Strong correlations and narrow limits of agreement were observed across all patients and time points. Conclusions: This study demonstrates, for the first time, the feasibility of creating fully mechanistic digital twins of mechanically ventilated neonates with RDS. The twins accurately captured patient-specific gas exchange and respiratory mechanics, supporting their potential as a platform for conducting virtual clinical trials and for the design of individualized, lung-protective ventilation strategies.

Ziren Jiang, Philip S. Crooke, John J. Marini et al.

Mechanical ventilation is critical for managing respiratory failure, but inappropriate ventilator settings can lead to ventilator-induced lung injury (VILI), increasing patient morbidity and mortality. Evaluating the causal impact of ventilator settings is challenging due to the complex interplay of multiple treatment variables and strong confounding due to ventilator guidelines. In this paper, we propose a modified vector-valued treatment policy (MVTP) framework coupled with energy balancing weights to estimate causal effects involving multiple continuous ventilator parameters simultaneously in addition to sensitivity analysis to unmeasured confounding. Our approach mitigates common challenges in causal inference for vector-valued treatments, such as infeasible treatment combinations, stringent positivity assumptions, and interpretability concerns. Using the MIMIC-III database, our analyses suggest that equal reductions in the total power of ventilation (i.e., the mechanical power) through different ventilator parameters result in different expected patient outcomes. Specifically, lowering airway pressures may yield greater reductions in patient mortality compared to proportional adjustments of tidal volume alone. Moreover, controlling for respiratory-system compliance and minute ventilation, we found a significant benefit of reducing driving pressure in patients with acute respiratory distress syndrome (ARDS). Our analyses help shed light on the contributors to VILI.

Davide Modesti, Sergio Pirozzoli

We establish a theoretical framework for predicting friction and heat transfer coefficients in variable-properties forced air convection. Drawing from concepts in high-speed wall turbulence, which also involves significant temperature, viscosity, and density variations, we utilize the mean momentum balance and mean thermal balance equations to develop integral transformations that account for the impact of variable fluid properties. These transformations are then applied inversely to predict the friction and heat transfer coefficients, leveraging the universality of passive scalars transport theory. Our proposed approach is validated using a comprehensive dataset from direct numerical simulations, covering both heating and cooling conditions up to a friction Reynolds number of approximately $\Rey_τ\approx 3200$. The predicted friction and heat transfer coefficients closely match DNS data with an accuracy margin of 1-2\%, representing a significant improvement over the current state of the art.

Bryce Cyr, Sandeep Kumar Acharya, Jens Chluba

The presence of an abundant population of low frequency photons at high redshifts (such as a radio background) can source leading order effects on the evolution of the matter and spin temperatures through rapid free-free absorptions. This effect, known as soft photon heating, can have a dramatic impact on the differential brightness temperature, $ΔT_{\rm b}$, a central observable in $21$cm cosmology. Here, we introduce a semi-analytic framework to describe the dynamics of soft photon heating, providing a simplified set of evolution equations and a useful numerical scheme which can be used to study this generic effect. We also perform quasi-instantaneous and continuous soft photon injections to elucidate the different regimes in which soft photon heating is expected to impart a significant contribution to the global $21$cm signal and its fluctuations. We find that soft photon backgrounds produced after recombination with spectral index $γ> 3.0$ undergo significant free-free absorption, and therefore this heating effect cannot be neglected. The effect becomes stronger with steeper spectral index, and in some cases the injection of a synchrotron-like spectrum ($γ= 3.6$) can suppress the amplitude of $ΔT_{\rm b}$ relative to the standard model prediction, making the global $21$cm signal even more difficult to detect in these scenarios.

Timo Häckel, Luca von Roenn, Nemo Juchmann et al.

The trend for Urban Air Mobility (UAM) is growing with prospective air taxis, parcel deliverers, and medical and industrial services. Safe and efficient UAM operation relies on timely communication and reliable data exchange. In this paper, we explore Cooperative Perception (CP) for Unmanned Aircraft Systems (UAS), considering the unique communication needs involving high dynamics and a large number of UAS. We propose a hybrid approach combining local broadcast with a central CP service, inspired by centrally managed U-space and broadcast mechanisms from automotive and aviation domains. In a simulation study, we show that our approach significantly enhances the environmental awareness for UAS compared to fully distributed approaches, with an increased communication channel load, which we also evaluate. These findings prompt a discussion on communication strategies for CP in UAM and the potential of a centralized CP service in future research.

Farid Bikmukhametov, Lana Glazko, Yaroslav Muravev et al.

Acoustic black holes represent a special class of metastructures allowing efficient absorption based on the slow sound principle. The decrease of the wave speed is associated with the spatial variation of acoustic impedance, while the absorption properties are linked to thermoviscous losses induced by the local resonances of the structure. While most of the developments in the field of sonic black holes are dedicated to one-dimensional structures, the current study is concerned with their two-dimensional counterparts. It is shown that the change of the dimensionality results in the change of noise insulation mechanism, which relies on the opening of band-gaps rather then thermoviscous losses. The formation of band-gaps is associated with the strong coupling between the resonators constituting the considered structures. Numerically and experimentally it is shown than the structure is characterized by broad stop-bands in transmission spectra, while the air flow propagation is still allowed. In particular, a realistic application scenario is considered, in which the acoustic noise and the air flow are generated by a fan embedded into a ventilation duct. The obtained results pave the way towards the development of next-level ventilated metamaterials for efficient noise control.

Florian Jäger, Oliver Bertram, Sascha M. Lübbe et al.

The work presented herein has been conducted within the DLR internal research project HorizonUAM, which encompasses research within numerous areas related to urban air mobility. One of the project goals was to develop a safe and certifiable onboard system concept. This paper aims to present the conceptual propulsion system architecture design for an all-electric battery-powered multirotor electric Vertical Takeoff and Landing (eVTOL) vehicle. Therefore, a conceptual design method was developed that provides a structured approach for designing the safe multirotor propulsion architecture. Based on the concept of operation the powertrain system was initially predefined, iteratively refined based on the safety assessment and validated through component sizing and simulations. The analysis was conducted within three system groups that were developed in parallel: the drivetrain, the energy supply and the thermal management system. The design process indicated that a pure quadcopter propulsion system can merely be designed reasonably for meeting the European Union Aviation Safety Agency (EASA) reliability specifications. By adding two push propellers and implementing numerous safety as well as passivation measures the reliability specifications defined by EASA could finally be fulfilled. The subsequent system simulations also verified that the system architecture is capable of meeting the requirements of the vehicle concept of operations. However, further work is required to extend the safety analysis to additional system components as the thermal management system or the battery management system and to reduce propulsion system weight.

Andreas Strand, Patrick Gorton, Martin Asprusten et al.

A substantial part of fighter pilot training is simulation-based and involves computer-generated forces controlled by predefined behavior models. The behavior models are typically manually created by eliciting knowledge from experienced pilots, which is a time-consuming process. Despite the work put in, the behavior models are often unsatisfactory due to their predictable nature and lack of adaptivity, forcing instructors to spend time manually monitoring and controlling them. Reinforcement and imitation learning pose as alternatives to handcrafted models. This paper presents the Learning Environment for the Air Domain (LEAD), a system for creating and integrating intelligent air combat behavior in military simulations. By incorporating the popular programming library and interface Gymnasium, LEAD allows users to apply readily available machine learning algorithms. Additionally, LEAD can communicate with third-party simulation software through distributed simulation protocols, which allows behavior models to be learned and employed using simulation systems of different fidelities.

Aaron D. Ludlow, S. Michael Fall, Matthew J. Wilkinson et al.

We use two cosmological simulations to study the impact of spurious heating of stellar motions within simulated galaxies by dark matter (DM) particles. The simulations share the same numerical and subgrid parameters, but one used a factor of 7 more DM particles. Many galaxy properties are unaffected by spurious heating, including their masses, star formation histories, and the spatial distribution of their gaseous baryons. The distribution and kinematics of stellar and DM particles, however, are affected. Below a resolution-dependent virial mass, $M_{200}^{\rm spur}$, galaxies have higher characteristic velocities, larger sizes, and more angular momentum in the simulation with lower DM mass resolution; haloes have higher central densities and lower velocity dispersions. Above $M_{200}^{\rm spur}$, galaxies and haloes have similar properties in both runs. The differences arise due to spurious heating, which transfers energy from DM to stellar particles, causing galaxies to heat up and haloes to cool down. The value of $M_{200}^{\rm spur}$ can be derived from an empirical disc heating model, and coincides with the mass below which the predicted {\em spurious} velocity dispersion exceeds the {\em measured} velocity dispersion of simulated galaxies. We predict that galaxies in the $100^3\, {\rm Mpc}^3$ \eagle\, run and IllustrisTNG-100 are robust to spurious collisional effects at their half-mass radii provided $M_{200}^{\rm spur}\approx 10^{11.7}{\rm M_\odot}$; for the $25^3\, {\rm Mpc}^3$ \eagle\, run and IllustrisTNG-50, we predict $M_{200}^{\rm spur}\approx 10^{11}{\rm M_\odot}$. Suppressing spurious heating at smaller/larger radii, or for older/younger stellar populations, requires haloes to be resolved with more/fewer DM particles.

Jihoon Chung, Nastaran Shahmansouri, Rhys Goldstein et al.

This paper explores the benefits of incorporating natural ventilation (NV) simulation into a generative process of designing residential buildings to improve energy efficiency and indoor thermal comfort. Our proposed workflow uses the Wave Function Collapse algorithm to generate a diverse set of plausible floor plans. It also includes post-COVID occupant presence models while incorporating adaptive comfort models. We conduct four sets of experiments using the workflow, and the simulated results suggest that multi-mode cooling strategies combining conventional air conditioning with NV can often significantly reduce energy use while introducing only slight reductions in thermal comfort.

P. Tien, S. Wei, Tianshu Liu et al.

Francesco Chirico, A. Sacco, Nicola Luigi Bragazzi et al.

The airborne transmission of SARS-CoV-2 is still debated. The aim of this rapid review is to evaluate the COVID-19 risk associated with the presence of air-conditioning systems. Original studies (both observational and experimental researches) written in English and with no limit on time, on the airborne transmission of SARS-CoV, MERS-CoV, and SARS-CoV-2 coronaviruses that were associated with outbreaks, were included. Searches were made on PubMed/MEDLINE, PubMed Central (PMC), Google Scholar databases, and medRxiv. A snowball strategy was adopted to extend the search. Fourteen studies reporting outbreaks of coronavirus infection associated with the air-conditioning systems were included. All studies were carried out in the Far East. In six out the seven studies on SARS, the role of Heating, Ventilation, and Air Conditioning (HVAC) in the outbreak was indirectly proven by the spatial and temporal pattern of cases, or by airflow-dynamics models. In one report on MERS, the contamination of HVAC by viral particles was demonstrated. In four out of the six studies on SARS-CoV-2, the diffusion of viral particles through HVAC was suspected or supported by computer simulation. In conclusion, there is sufficient evidence of the airborne transmission of coronaviruses in previous Asian outbreaks, and this has been taken into account in the guidelines released by organizations and international agencies for controlling the spread of SARS-CoV-2 in indoor environments. However, the technological differences in HVAC systems prevent the generalization of the results on a worldwide basis. The few COVID-19 investigations available do not provide sufficient evidence that the SARS-CoV-2 virus can be transmitted by HVAC systems.

R. Homod, Amjad Almusaed, Asaad Almssad et al.

Abstract Recently, a numerous number of houses has been built using AAC materials, which consume the most amount of energy in the building sector by Heating, ventilation, and air -conditioning (HVAC) systems. Thus, the most significant factor affecting the energy consumed by HVAC systems is the materials used in the building. Building models are important tools in determining the energy efficiency of buildings. Numerous strategies have been established to construct building models, such as the weight, gray, and black boxes, as well as hybrid models. Hybrid models have not been researched extensively, although they provide a reasonable representation of actual indoor conditions. Therefore, this study employs a hybrid calculation model for the analysis of physical and empirical correlations to evaluate thermal comfort in buildings, which reflects their energy consumption. The residential load factor (RLF) technique is adopted owing to its systematic organization and ease of use, which is achieved by dividing the model into submodels. The model is verified and validated by drawing a comparison with field measurements and the output obtained from ANSYS software. The actual field measurements and ANSYS outputs match the outputs of the proposed model; the results show small residual errors, indicating a well-defined model structure. The cost and energy savings of vernacular buildings and autoclaved aerated concrete (AAC) (or low-cost) buildings have been highly debated in Basra city. Models of these two different building materials are simulated within the MATLAB/Simulink environment. Their results indicate that the vernacular building has the highest energy saving potential up to 47.83% over 24 h a day. These results provide an excellent argument to realize the benefits of vernacular buildings by reducing the dependency on powered cooling.

Austin P. Rogers, Fang-Cheng Guo, Bryan P. Rasmussen

Abstract The fault detection and diagnosis (FDD) for air conditioning systems has been an active area of research for over two decades. However, the majority of methods have been developed for commercial buildings. While much of this work applies to the residential market, this market has unique challenges and opportunities that should be considered separate from the commercial heating, ventilation, and air conditioning (HVAC) and industrial refrigeration systems. This paper reviews and evaluates state-of-the-art methods for performing FDD for air conditioning systems. In the field of applying these methods to the residential market, the opportunities for development include: (a) Considering the level of fault diagnosis that is most cost-effective in the residential market. (b) Simplifying the set of required sensors for FDD. This paper also reviews the emerging field of fault detection of residential air conditioning systems by using cloud-based thermostat data. Publishers have only recently started releasing large-scale analyses of thermostat data, but experts predict considerable growth in this field.

Brandi Jess, James Brusey, Matteo Maria Rostagno et al.

Car-cabin thermal systems, including heated seats, air-conditioning, and radiant panels, use a large proportion of the energy budget of electric vehicles and thus reduce their effective range. Optimising these systems and their controllers might be possible with computationally efficient simulation. Unfortunately, state-of-the-art simulators are either too slow or provide little resolution of the cabin’s thermal environment. In this work, we propose a novel approach to developing a fast simulation by machine learning (ML) from measurements within the car cabin over a number of trials within a climatic wind tunnel. A range of ML approaches are tried and compared. The best-performing ML approach is compared to more traditional 1D simulation in terms of accuracy and speed. The resulting simulation, based on Multivariate Linear Regression, is fast (5 microseconds per simulation second), and yields good accuracy (NRMSE 1.8%), which exceeds the performance of the traditional 1D simulator. Furthermore, the simulation is able to differentially simulate the thermal environment of the footwell versus the head and the driver position versus the front passenger seat, but unlike a traditional 1D model cannot support changes to the physical structure. This fast method for obtaining computationally efficient simulators of car cabins will accelerate adoption of techniques such as Deep Reinforcement Learning for climate control.