Recent high-energy lithium-ion batteries contain highly densified electrodes, but they are expected to endure fast charging without safety compromises or accelerated aging. To investigate fast ...charging strategies, we use a multi-dimensional model consisting of several newman-type electrochemical models (p2D) coupled to an electrical-thermal cell domain model. Open-circuit potential, infrared thermography and calorimetry experiments of a high-energy 18650 NMC-811/SiC lithium-ion cell are used for model parameterization and validation. First, a single p2D model is used to compare the charging rate capabilities of NMC-811/SiC and NMC-111/graphite cells. We assess the modeling error of the single p2D model relative to the multi-dimensional model as a function of tab design. The multi-dimensional model is then used to study different tab and electrode designs regarding their susceptibility to lithium plating, which is evaluated based on local anode overpotential and local temperature. High-rate charging current profiles that minimize the risk of lithium plating are derived by implementing an anode potential threshold. We show that a state of charge beyond 60% can be reached in less than 18 min.
•Combined calorimetry, thermography and OCP measurements for model parameterization.•Charge-rate capability of NMC-111/graphite vs. NMC-811/SiC at varying porosities.•Tab design correlated to Li-plating at high-rate constant-current charging.•Accuracy of single p2D vs. multi-dimensional model as a function of tab design.•Optimum charging current profile as a function of tab and electrode design.
•Characteristics of the non-intrusive thermal comfort detection are defined.•A camera network is introduced to assess thermal comfort in multi-occupancy spaces.•Thermal and RGB-D cameras are fused to ...measure facial skin temperature.•Subjects can have flexible postures and movements during the data collection.•Facial mean skin temperature can serve as an indicator of one’s thermal comfort.
About 40% of the energy produced globally is consumed within buildings, primarily for providing occupants with comfortable work and living spaces. However, despite the significant impacts of such energy consumption on the environment, the lack of thermal comfort among occupants is a common problem that can lead to health complications and reduced productivity. To address this problem, it is particularly important to understand occupants’ thermal comfort in real-time to dynamically control the environment. This study investigates an infrared thermal camera network to extract skin temperature features and predict occupants’ thermal preferences at flexible distances and angles. This study distinguishes from existing methods in two ways: (1) the proposed method is a non-intrusive data collection approach which does not require human participation or personal devices; (2) it uses low-cost thermal cameras and RGB-D sensors which can be rapidly reconfigured to adapt to various settings and has little or no hardware infrastructure dependency. The proposed camera network is verified using the facial skin temperature collected from 16 subjects in a multi-occupancy experiment. The results show that all 16 subjects observed a statistically higher skin temperature as the room temperature increases. The variations in skin temperature also correspond to the distinct comfort states reported by the subjects. The post-experiment evaluation suggests that the networked thermal cameras have a minimal interruption of building occupants. The proposed approach demonstrates the potential to transition the human physiological data collection from an intrusive and wearable device-based approach to a truly non-intrusive and scalable approach.
This work placed an emphasis that constructing segregated boron nitride (BN)/carbon nanotube (CNT) hybrid network brought an immense benefit to enhance the thermal conductivity (TC) of ...poly(vinylidene fluoride) (PVDF) composites. The segregated composites ((CNT + BN)@PVDF) showed a high TC of 1.8 W/mK at the total filler fraction of 25 vol %, outperforming PVDF composites with random structure (CNT/BN/PVDF) and segregated BN structure (BN@PVDF) by 169% and 50%, respectively. Infrared thermal images further demonstrated that (CNT + BN)@PVDF exhibited superior capability to dissipate heat compared to BN/PVDF. The segregated architecture increased the effective utilization of fillers and interfacial thermal resistance between neighboring BN platelets was reduced by the bridging effect of CNTs. Molding pressure and temperature governed the integration of segregated networks and thus the enhancement efficiency of TC. The design of hybrid segregated structure holds promise in a broad range of the preparation of thermal management materials.
Effectively thermal conduction pathways are essential for the thermal conductivity of polymer-based composites. In this contribution, we proposed a facile and feasible strategy to improve the thermal ...conductivity of polymer composites through constructing a segregated structure and hybrid conductive network. Boron nitride (BN) and aluminium nitride (AlN) were mechanically wrapped upon ultrahigh-molecular-weight polyethylene (UHMWPE) granules and then high-pressure consolidated. Morphology observation revealed that in the typical segregated pathways, polyhedral AlNs were in tandem with adjacent BN plates. A significantly synergistic enhancement in the thermal conductivity was achieved by the hybrid conductive network. At the total filler content of 50 wt%, the BN/AlN/UHMWPE composite with a filler ratio of 6:1 showed the thermal conductivity of 7.1 Wm-1 K−1, outperforming BN/UHMWPE and AlN/UHMWPE composites by 35.1% and 613%, respectively. Infrared thermal images further demonstrated that the composites with hybrid segregated structure had strongest capability to dissipate the heat against the counterparts with single segregated structure. Based on the percolation effect with an effective medium approach, the theoretical calculation suggested that AlN played a bridge role to interconnect the BN platelets in the segregated conductive pathways, leading to the formation of the more effective thermally conductive pathways. The obtained results offer valuable fundamentals to design and fabricate the highly thermal-conductive polymer composites as advanced thermal management materials.
From a wide range of bibliography (148 publications composed by books, guidelines, scientific papers, and other documents), the study presents a critical review of the use of the infrared ...thermography (IRT) survey in the building energy audit. After explaining its historical growth, the applicability of passive and active approaches has been described, considering well-established and emerging techniques, general procedures, types of IR-camera used, technical issues, and limitations. The passive approach is the most common to detect thermally significant defects. Thus, a specific procedure for the energy audit has been reported, matching different standards, guidelines, and professional advice. Similarly, recurring energy related problems are toughly presented (i.e. thermal characterization of buildings; thermal bridging, insulation level, air leakage and moisture detection; indoor temperature and U-value measurements; human comfort assessment). Finally, advantages and potential sources of errors as well as future trends in the use of IRT for the energy audit have been described. The research aims to serve as a reference for energy auditors and thermographers, to decide upon the best procedure for detecting specific energy defects.
Effects of substrate temperature, substrate wettability, and particle concentration are experimentally investigated for evaporation of a sessile water droplet containing colloidal particles. ...Time-varying droplet shapes and temperature of the liquid–gas interface are measured using high-speed visualization and infrared thermography, respectively. The motion of the particles inside the evaporating droplet is qualitatively visualized by an optical microscope and the profile of the final particle deposit is measured by an optical profilometer. On a nonheated hydrophilic substrate, a ring-like deposit forms after the evaporation, as reported extensively in the literature, while on a heated hydrophilic substrate, a thinner ring with an inner deposit is reported in the present work. The latter is attributed to Marangoni convection, and recorded motion of the particles as well as measured temperature gradient across the liquid–gas interface confirms this hypothesis. The thinning of the ring scales with the substrate temperature and is reasoned to stronger Marangoni convection at larger substrate temperature. In the case of a nonheated hydrophobic substrate, an inner deposit forms due to very early depinning of the contact line. On the other hand, in the case of a heated hydrophobic substrate, the substrate heating as well as larger particle concentration helps in the pinning of the contact line, which results in a thin ring with an inner deposit. We propose a regime map for predicting three types of depositsnamely, ring, thin ring with inner deposit, and inner depositfor varying substrate temperature, substrate wettability, and particle concentration. A first-order model corroborates the liquid–gas interface temperature measurements and variation in the measured ring profile with the substrate temperature.
•A non-contact and non-invasive data acquisition method via infrared thermography was utilized.•A hidden Markov model learning approach is introduced to capture dynamic thermal comfort.•Comfort is ...achieved via preventing existence of uncomfortable conditions as a logical inference.•82.8% of prediction accuracy for detection uncomfortable conditions was obtained.•Generalizing hyper-parameters of the model enables unsupervised learning of thermal comfort.
Maintaining thermal comfort in built environments is important for occupant health, well-being, and productivity, and also for efficient HVAC system operations. Most of the existing personal thermal comfort learning methods require occupants to provide feedback via a survey to label the monitored environmental or physiological conditions in order to train the prediction models. Accuracy of these models usually drops after the training process as personal thermal comfort is dynamic and changes over time due to climatic variations and/or acclimation. In this paper, we present a hidden Markov model (HMM) based learning method to capture personal thermal comfort using infrared thermography of the human face. We chose human face since its blood vessels has a higher density and it is not covered while performing regular activities in built environments. The learning algorithm has 3 hidden states (i.e., uncomfortably warm, comfortable, uncomfortably cool) and uses discretization for forming the observed states from the continuous infrared measurements. The approach can potentially be used for continuous monitoring of thermal comfort to capture the variations over time. We tested and validated the method in a four-day long experiment with 10 subjects and demonstrated an accuracy of 82.8% for predicting uncomfortable conditions.
Understanding occupants’ thermal sensation and comfort is essential to defining the operational settings for Heating, Ventilation and Air Conditioning (HVAC) systems in buildings. Due to the ...continuous impact of human and environmental factors, occupants’ thermal sensation and comfort level can change over time. Thus, to dynamically control the environment, thermal comfort should be monitored in real time. This paper presents a novel non-intrusive infrared thermography framework to estimate an occupant's thermal comfort level by measuring skin temperature collected from different facial regions using low-cost thermal cameras. Unlike existing methods that rely on placing sensors directly on humans for skin temperature measurement, the proposed framework is able to detect the presence of occupants, extract facial regions, measure skin temperature features, and interpret thermal comfort conditions with minimal interruption of the building occupants. The method is validated by collecting thermal comfort data from a total of twelve subjects under cooling, heating and steady-state experiments. The results demonstrate that ears, nose and cheeks are most indicative of thermal comfort and the proposed framework can be used to assess occupants’ thermal comfort with an average accuracy of 85%.
Reducing the energy requirements of buildings is essential in order to address anthropogenic global warming. Among the various factors affecting the energy requirements of buildings, the thermal ...transmittance of the walls is critical in understanding heat loss. It is therefore necessary to assess the thermal transmittances carefully in order to develop effective means of energy conservation. Although various theoretical methods and methods using in situ measurements are available for this purpose, the correct use of such methods depends on many factors. In a detailed review of more than 150 publications (scientific papers, congress reports, books, and other documents), the best-developed methods in use by researchers and professionals are analysed. These methods are as follows: the theoretical method, the heat flow meter method, the simple hot box-heat flow meter method, the thermometric method, and the quantitative infrared thermography method. This review is intended to be a useful resource for researchers and professionals in that it covers the fundamental theoretical background, the equipment and material required for in situ measurements, the criteria for installing the equipment, the errors caused by metrological and environmental aspects, data acquisition, data processing, and data analysis.
•Theoretical fundamentals of assessment methods of thermal transmittance.•Analysis of the benefits and limitations of the different assessment methods.•Acquisition, post-processing and data analysis for the different methods.
Building Information Modeling (BIM), as a rising technology in the Architecture, Engineering and Construction (AEC) industry, has been applied to various research topics from project planning, ...structural design, facility management, among others. Furthermore, with the increasing demand for energy efficiency, the AEC industry requires an expeditious energy retrofit of the existing building stock to successfully achieve the 2020 Energy Strategy targets.
As such, this article seeks to survey the recent developments in the energy efficiency of buildings, combining energy retrofitting and the technological capabilities of BIM, providing a critical exposition in both engineering and energy domains. The result is a thorough review of the work done by other authors in relevant fields, comprising the entire spectrum from on-site data acquisition, through the generation of Building Energy Models (BEM), data transfer to energy analysis software and, finally, the identification of major issues throughout this process. Additionally, a BIM-based methodology centered on the acquired knowledge is presented.
Solutions for as-built data acquisition such as laser scanning and infrared thermography, and on-site energy tests that benefit the acquisition of energy-related data are explored. The most predominant BIM software regarding not only energy analysis but also model development is examined. In addition, interoperability restrictions between BIM and energy analysis software are addressed using the Industry Foundation Classes (IFC) and Green Building Extensible Markup Language (gbXML) schemes.
Lastly, the article argues the future innovations in this subject, predicting future trends and challenges for the industry.
•A BIM-based methodology for building energy-retrofit is presented.•Multiple methods for geometric and energy-related data acquisition are examined.•Evaluation of the usage of BIM authoring and energy-analysis tools in scientific research.•Analysis of the interoperability between energy and authoring tools.
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