Real-world Conditions Research Articles

Local Evaluation of Large-scale Remote Sensing Machine Learning-generated Building and Road Dataset: The Case of Rwanda

AbstractAccurate and up-to-date building and road data are crucial for informed spatial planning. In developing regions in particular, major challenges arise due to the limited availability of these data, primarily as a result of the inherent inefficiency of traditional field-based surveys and manual data generation methods. Importantly, this limitation has prompted the exploration of alternative solutions, including the use of remote sensing machine learning-generated (RSML) datasets. Within the field of RSML datasets, a plethora of models have been proposed. However, these methods, evaluated in a research setting, may not translate perfectly to massive real-world applications, attributable to potential inaccuracies in unknown geographic spaces. The scepticism surrounding the usefulness of datasets generated by global models, owing to unguaranteed local accuracy, appears to be particularly concerning. As a consequence, rigorous evaluations of these datasets in local scenarios are essential for gaining insights into their usability. To address this concern, this study investigates the local accuracy of large RSML datasets. For this evaluation, we employed a dataset generated using models pre-trained on a variety of samples drawn from across the world and accessible from public repositories of open benchmark datasets. Subsequently, these models were fine-tuned with a limited set of local samples specific to Rwanda. In addition, the evaluation included Microsoft’s and Google’s global datasets. Using ResNet and Mask R‑CNN, we explored the performance variations of different building detection approaches: bottom-up, end-to-end, and their combination. For road extraction, we explored the approach of training multiple models on subsets representing different road types. Our testing dataset was carefully designed to be diverse, incorporating both easy and challenging scenes. It includes areas purposefully chosen for their high level of clutter, making it difficult to detect structures like buildings. This inclusion of complex scenarios alongside simpler ones allows us to thoroughly assess the robustness of DL-based detection models for handling diverse real-world conditions. In addition, buildings were evaluated using a polygon-wise comparison, while roads were assessed using network length-derived metrics.Our results showed a precision (P) of around 75% and a recall (R) of around 60% for the locally fine-tuned building model. This performance was achieved in three out of six testing sites and is considered the lowest limit needed for practical utility of RSML datasets, according to the literature. In contrast, comparable results were obtained in only one out of six sites for the Google and Microsoft datasets. Our locally fine-tuned road model achieved moderate success, meeting the minimum usability threshold in four out of six sites. In contrast, the Microsoft dataset performed well on all sites. In summary, our findings suggest improved performance in road extraction, relative to building extraction tasks. Moreover, we observed that a pipeline relying on a combination of bottom-up and top-down segmentation, while leveraging open global benchmark annotation dataset as well as a small number of samples for fine-tuning, can offer more accurate RSML datasets compared to an open global dataset. Our findings suggest that relying solely on aggregated accuracy metrics can be misleading. According to our evaluation, even city-level derived measures may not capture significant variations in performance within a city, such as lower accuracy in specific neighbourhoods. Overcoming the challenges of complex areas might benefit from exploring alternative approaches, including the integration of LiDAR data, UAV images, aerial images or using other network architectures.

Investigation of emission characteristics of a marine cargo ship in real-world conditions

Pollution caused by ship emissions will considerably impact coastal areas. A test system that matched the actual conditions of a ship was designed based on a portable emission measurement system (PEMS), and the emission characteristic of gaseous and particle emissions and the particle size distribution of the ship's main engine were investigated under real-world operating conditions. The results showed that the emission concentrations of the main pollutants fluctuated greatly under the departure, anchoring, and docking conditions, and the peaks of CO, CO2, and NOx emissions appeared under these transient conditions. The emission concentrations of CO2, hydrocarbons, particle number (PN), and particulate mass increased with the increase in speed. The PN-based particle size distribution of the engine presented a unimodal distribution under daily operating conditions. The maximum emission factor of NOx based on the engine power was 29.53 g/kWh at the engine speed of 66 r/min. The results of the study may contribute to supplementing the emission factors of this type of ship, and provide data support for monitoring and assessment of the marine environment.

Experimental performance evaluation of air-based photovoltaic–thermal collector with rectangular turbulators and longitudinal fins

An air-based photovoltaic–thermal collector (PVTC) simultaneously generates electricity and heats air using energy from incident solar radiation. Its simple design ensures low initial costs and easier maintenance. However, its thermal efficiency is limited by the low heat conductivity of air. To address this shortcoming, considerable research has focused on enhancing either the heat transfer area or the heat transfer coefficient. However, only one of these two methods has typically been utilized, and information regarding PVTCs that incorporate both technologies is lacking. Thus, a novel air-based PVTC featuring longitudinal fins and rectangular turbulators is proposed herein. In this PVTC, the fins enlarge the heat transfer area, while the turbulators improve the heat transfer coefficient by creating turbulence near the fin surface. The proposed PTVC (PTVC-LFRT) was experimentally evaluated under real-world weather conditions and also compared with two other PVTC configurations: one with a smooth air channel (PTVC-SMAC) and one with only fins (PTVC-LF) to reveal the potential thermal and electrical gains achievable with the proposed design. As a result, PVTC-LFRT achieved an electrical efficiency of 17.06 %, whereas PVTC-SMAC and PTVC-LF recorded corresponding values of 16.55 % and 16.8 %, respectively. Moreover, PVTC-LFRT exhibited a thermal efficiency of 38.93 %, while PVTC-SMAC and PVTC-LF achieved thermal efficiencies of 22.68 % and 33.56 %, respectively. Finally, the total daily energy output of PVTC-LFRT from incident solar radiation was 42.73 % and 11.2 % higher than those of PVTC-SMAC and PVTC-LF, respectively. These findings verify that incorporating fins with turbulators into a PVTC effectively enhances its electrical and thermal efficiency. Consequently, the feasibility of the proposed system could be confirmed, and its promotion is considered worthwhile.

Performance of cementitious systems containing calcined clay in a chloride-rich environment: a review by TC-282 CCL

In this review by TC- 282 CCL, a comprehensive examination of various facets of chloride ingress in calcined clay-based concrete in aggressive chloride-rich environments is presented due to its significance in making reinforced concrete structures susceptible to chloride-induced corrosion damages. The review presents a summary of available literature focusing on materials characteristics influencing the chloride resistance of calcined clay-based concrete, such as different clay purity, kaolinite content and other clay minerals, underscoring the significance of pore refinement, pore solution composition, and chloride binding mechanisms. Further, the studies dealing with the performance at the concrete scale, with a particular emphasis on transport properties, curing methods, and mix design, are highlighted. Benchmarking calcined clay mixes with fly ash or slag-based concrete mixes that are widely used in aggressive chloride conditions instead of OPC is recommended. Such comparison could extend the usage of calcined clay as a performance-enhancing mineral admixture in the form of calcined clay or LC2 (limestone-calcined clay). The chloride diffusion coefficient in calcined clay concrete is reported to be significantly lower (about 5–10 times in most literature available so far) compared to OPC, and even lower compared to fly ash and slag-based concrete at early curing ages reported across recent literature made with different types of cements and concrete mixes. Limited studies dealing with reinforcement corrosion point out that calcined clay delays corrosion initiation and reduces corrosion rates despite the reduction in critical chloride threshold. Most of these results on corrosion performance are mainly from laboratory studies and warrant field evaluation in future. Finally, two case studies demonstrating the application of calcined clay-based concrete in real-world marine exposure conditions are discussed to showcase the promising potential of employing low-purity calcined clay-based concrete for reducing carbon footprint and improving durability performance in chloride exposure.

Real-time testing of AI enabled automatic emergency braking system for ADAS vehicle using 3D point cloud and precise depth information

At the forefront of automobile safety technology, Automatic Emergency Braking (AEB) represents a major advancement in collision avoidance systems. The cutting-edge technology provides an additional layer of security at pivotal times, making it a vital part of the changing landscape of vehicle safety. This research introduces an effective system for automatic emergency braking in ADAS-equipped or Autonomous vehicles using a combination of 3d lidar and stereo vision camera for a swift and robust system in the vehicle that is faster than human drivers in cases of unexpected emergencies. Utilizing the power of clustering algorithms on 3d point clouds and state-of-the-art computer vision algorithms on an RGB image mapped to a depth frame from the stereo vision camera, the system as a whole provides a comprehensive system adding to the safety of the vehicle and the passengers. Further, the efficiency of the system is studied based on various parameters. The data from an external inertial measurement unit is also utilized to derive results that support the claims of the study. The system has been developed and implemented on a passenger car that has been modified into an electric vehicle and further tested in real-world traffic conditions in autonomous driving mode. The findings of the study were having exceptionally good precision in split-second decision-making in emergency maneuvers.

Co-Ability and embodied data: blurring the lines between human and nonhuman entities in an interconnected world

This article explores the dynamic interplay between human and non-human entities, focusing on how embodied data representation is distributed. It examines how predictive coding, which utilizes preconceived knowledge, interacts with tangible experiences to shape our understanding of the world. Emphasizing this, I propose the concept of co-Ability as a deep underlying explanatory framework for understanding adaptive behaviors within a networked world. A non-verbal dialog between humans and a data-saturated environment is analyzed through an action-oriented perspective and the predictive coding framework in cognition, utilizing digital craft and rapid prototyping. This transformative approach augments human interaction with digital landscapes through tangible prototypes, bridging physical experience with abstract information, and identifying potential ways to conceptualize data materially. The article discusses the various aspects of connectivity among network agents and the evolving nature of these connections as they adapt to real-world conditions and dynamic shifts in data, highlighting that information exchange in an interconnected network is more than bilateral; it generates ripple effects that extend beyond immediate connections. These reciprocal exchanges simultaneously alter both the digital and analog domains, with data constantly bifurcating into multiple pathways and outcomes. A significant challenge addressed in this article is the question of how to frame information materially, inviting further exploration.

The Ecology of Human Sleep (EcoSleep) Cohort Study: Protocol for a longitudinal repeated measurement burst design study to assess the relationship between sleep determinants and outcomes under real-world conditions across time of year.

The interplay of daily life factors, including mood, physical activity, or light exposure, influences sleep architecture and quality. Laboratory-based studies often isolate these determinants to establish causality, thereby sacrificing ecological validity. Furthermore, little is known about time-of-year changes in sleep and circadian-related variables at high resolution, including the magnitude of individual change across time of year under real-world conditions. The Ecology of Human Sleep (EcoSleep) cohort study will investigate the combined impact of sleep determinants on individuals' daily sleep episodes to elucidate which waking events modify sleep patterns. A second goal is to describe high-resolution individual sleep and circadian-related changes across the year to understand intra- and inter-individual variability. This study is a prospective cohort study with a measurement-burst design. Healthy adults aged 18-35 years (N = 12) will be enrolled for 12 months. Participants will continuously wear actimeters and pendant-attached light loggers. A subgroup will also measure interstitial fluid glucose levels (six paticipants). Every 4 weeks, all participants will undergo three consecutive measurement days of four ecological momentary assessments each day ('bursts') to sample sleep determinants during wake. Participants will also continuously wear temperature loggers (iButtons) during the bursts. Body weight will be captured before and after the bursts in the laboratory. The bursts will be separated by two at-home electroencephalogram recordings each night. Circadian phase and amplitude will be estimated during the bursts from hair follicles, and habitual melatonin onset will be derived through saliva sampling. Environmental parameters (bedroom temperature, humidity, and air pressure) will be recorded continuously.

Ab initio study of surfaces of lead and tin based metal halide perovskite structures

Abstract Hybrid perovskite materials, known for their potential in cost-effective optoelectronic applications, face a knowledge gap in crucial areas, particularly the atomic-level properties of the surface. This study addresses this challenge by refining ab initio methods for characterizing surface structures of cubic methylammonium lead bromide and methylammonium tin bromide (MAMeBr3 with Me = Sn, Pb), avoiding superficial restrictions in atomic movement during geometry optimization. The resulting structures confirmed nearly random MA+ molecule alignment, comparable to real-world experimental conditions. Calculating surface energies for these structures with crystal orientations {100} and {110}, each with different terminations, provides valuable insights into structural properties. Using a carefully chosen thermodynamic reference state, mimicking experimental conditions enables a thermodynamic discussion and facilitates the modulation of the MeBr2 component’s chemical potential. This modulation, in turn, allows for the prediction of crystal morphologies, as illustrated by Wulff’s construction. This approach establishes a crucial link between theoretical predictions and experimental conditions, shedding light on the complexities of hybrid perovskite materials.

Biological and Procedural Predictors of Outcome in the Stroke Preclinical Assessment Network (SPAN) Trial.

The SPAN trial (Stroke Preclinical Assessment Network) is the largest preclinical study testing acute stroke interventions in experimental focal cerebral ischemia using endovascular filament middle cerebral artery occlusion (MCAo). Besides testing interventions against controls, the prospective design captured numerous biological and procedural variables, highlighting the enormous heterogeneity introduced by the multicenter structure that might influence stroke outcomes. Here, we leveraged the unprecedented sample size achieved by the SPAN trial and the prospective design to identify the biological and procedural variables that affect experimental stroke outcomes in transient endovascular filament MCAo. The study cohort included all mice enrolled and randomized in the SPAN trial (N=1789). Mice were subjected to 60-minute MCAo and followed for a month. Thirteen biological and procedural independent variables and 4 functional (weight loss and 4-point neuroscore on days 1 and 2, corner test on days 7 and 28, and mortality) and 3 tissue (day 2, magnetic resonance imaging infarct volumes and swelling; day 30, magnetic resonance imaging tissue loss) outcome variables were prospectively captured. Multivariable regression with stepwise elimination was used to identify the predictors and their effect sizes. Older age, active circadian stage at MCAo, and thinner and longer filament silicone tips predicted higher mortality. Older age, larger body weight, longer anesthesia duration, and longer filament tips predicted worse neuroscores, while high-fat diet and blood flow monitoring predicted milder neuroscores. Older age and a high-fat diet predicted worse corner test performance. While shorter filament tips predicted more ipsiversive turning, longer filament tips appeared to predict contraversive turning. Age, sex, and weight interacted when predicting the infarct volume. Older age was associated with smaller infarcts on day 2 magnetic resonance imaging, especially in animals with larger body weights; this association was most conspicuous in females. High-fat diet also predicted smaller infarcts. In contrast, the use of cerebral blood flow monitoring and more severe cerebral blood flow drop during MCAo, longer anesthesia, and longer filament tips all predicted larger infarcts. Bivariate analyses among the dependent variables highlighted a disconnect between tissue and functional outcomes. Our analyses identified variables affecting endovascular filament MCAo outcome, an experimental stroke model used worldwide. Multiple regression refuted some commonly reported predictors and revealed previously unrecognized associations. Given the multicenter prospective design that represents a sampling of real-world conditions, the degree of heterogeneity mimicking clinical trials, the large number of predictors adjusted for in the multivariable model, and the large sample size, we think this is the most definitive analysis of the predictors of preclinical stroke outcome to date. Future multicenter experimental stroke trials should standardize or at least ensure a balanced representation of the biological and procedural variables identified herein as potential confounders.

Arctic accessibility: recent trend in observed ship tracks and validation of arctic transport accessibility model

ABSTRACT The Arctic region is undergoing significant changes in maritime accessibility. This study investigates observed ship trajectories from 2013 to 2020 to demonstrate the recent trends of Arctic traffic. A notable surge in maritime activities has been observed, particularly during summer months, driven by economic interests and the increasing popularity of existing routes. Unique patterns in the northern Barents Sea have been observed where ships favour different routes based on seasonal ice conditions. Another contribution from this work is the validation of the Arctic Traffic Accessibility Model (ATAM) using the observed ship traffic data. Results show that the ATAM model underestimates the accessibility and vessel travel speed. This is largely due to outdated model parameters. The predefined ice multipliers and calculation of ice numerals used in the ATAM may not accurately reflect real-world conditions.

Laboratory Study on Wave Attenuation by Elastic Mangrove Model with Canopy

This study evaluates the effectiveness of artificial Kandelia obovata forests in wave attenuation through physical model experiments conducted in a wave flume. The experiments meticulously replicated real-world hydrodynamic conditions and mangrove movement responses using the principles of gravitational and motion similarity, with a scaled 1:10 model of Kandelia obovata. Our approach included comparative experiments against a 1:100 gradient concrete slope to isolate the effects of seabed friction and flume wall reflections. The wave height was measured using strategically placed wave gauges. The findings indicated that the artificial Kandelia obovata forests significantly attenuated waves, with a decrease in the total attenuation capacity as the water depth increased from 2.75 m to 3.28 m under both regular and irregular waves. The elastic mangrove model with a canopy effect led to a 15% increase in wave attenuation over cylindrical models. Predictive models using multivariate nonlinear regression and back propagation neural networks showed that the latter provided a superior accuracy in estimating wave transmission coefficients

Leveraging SUMO for Real-World Traffic Optimization: A Comprehensive Approach

This paper illuminates the utilization of SUMO as a powerful tool for addressing real-world traffic management issues. There is a gap in testing and validating solutions to in-field conditions due to the high cost and complexity of urban and suburban road networks. The validation step is often skipped, which can lead to a higher risk in implementing sophisticated solutions that exist in our multimodal transportation environment. This challenge is addressed by introducing simulations as a crucial preliminary step before real-world application. Accurate simulations require detailed data on intersection geometries, vehicle distribution, and driver behavior to accurately mirror real-world conditions. To meet these criteria, detailed sensor data on trajectories, types of road users, and their locations are extensively employed. This data forms the foundation for calibrated traffic simulations by NoTraffic™ . In conclusion, an in-depth demonstration of the method used to address a real-world traffic problem with SUMO is provided, emphasizing SUMO’s effectiveness in building confidence for deploying solutions in the field.

3D electromagnetic assessment of bended CORC® cables

Conductor on round core (CORC®) cables have emerged as a leading contender in high-temperature superconducting (HTS) cable designs, offering exceptional performance with current densities surpassing 300 A/mm2 and the ability to withstand high axial tensile and compressive strain. Despite their remarkable properties, optimizing CORC® cables remains a challenge, particularly in accurately estimating their AC losses under real-world conditions, which necessitates advanced numerical modeling techniques. Building upon recent advancements in simulating straight CORC® cables, where Bean’s-like current profiles were observed across the actual thickness of wound superconducting tapes, we introduce a tailored computational approach to enhance the processing speed of three-dimensional (3D) finite element models of wound HTS tapes. This tailored approach is specifically designed to address the complexities of bent CORC® cables, which exhibit helicoidal winding and are subjected to varying mechanical strain. We focus on analyzing their electromagnetic performance by transitioning from idealized straight-former designs to more realistic scenarios where cable-formers are bent to accommodate flexible cable routing or coil configurations. Our simulations consider a typical cable design comprising three 4 mm-wide SuperPower tapes (SCS4050) with a twist pitch of 40 mm. We demonstrate the capability to accurately model the full electromagnetic behavior of bent CORC® cables without the reduction of degrees of freedom, providing valuable insights into their performance under bending conditions. Our findings contribute to the ongoing optimization of CORC® cable designs for a wide range of practical applications in high-current and high-magnetic field environments.

A Simulation Approach for Analysis of the Regenerative Potential of High-Speed Train Suspensions

This study primarily investigates the adaptability and performance of hydraulic–electric regenerative dampers for high-speed trains by substituting conventional primary dampers with hydraulic–electric regenerative dampers. The primary objectives are to develop a detailed model of primary suspension regenerative damper (PSRD) energy conversion that incorporates factors such as oil pressure loss, motor efficiency, and overall system efficiency, and to perform a comprehensive comparative analysis of vibration responses, wheel wear, comfort indices, and power generation using an integrated MATLAB and SIMPACK co-simulation platform. The results reveal that at an operational speed of 350 km/h, the dynamic responses of the carbody, bogie, wheelset, and dampers equipped with the proposed PSRD systems closely align with those of conventional primary vertical damper systems. The detailed PSRDs’ hydraulic–mechanical–electrical model effectively captures the subtleties of oil pressure fluctuations and their impacts. The wear distribution and magnitude across the vehicle remain consistent during acceleration, constant, and deceleration speeds, ensuring uniform wear characteristics. Under real-world railway operational conditions, the ride comfort metrics of vehicles fitted with regenerative dampers are comparable to those with conventional primary vertical dampers. Furthermore, each regenerative damper can generate up to 21.72 W of electrical power, achieving a generation efficiency of 45.28%. Finally, a test rig was designed and fabricated to validate the primary suspension regenerative damper (PSRD) model, showing good agreement between predicted and actual damping force and power regeneration, with results indicating a peak damping force of 12.5 kN and approximately 230 W of regenerated power. This research provides a theoretical foundation and experimental validation for implementing power regeneration mechanisms in railway transportation, demonstrating that the hydraulic–mechanical–electrical PSRD model can fulfil the performance criteria of conventional dampers while offering substantial energy harvesting capabilities. This advancement not only enhances energy efficiency but also contributes to the sustainable development of high-speed rail systems.

Continuous glucose monitoring devices in people over 65 years: literature review

The use of continuous glucose monitoring (CGM) in elderly patients with diabetes is not well documented. The present study search to know the current status of use of CGM devices in patients with diabetes over 65 years of age. A systematic literature search was performed in PubMed and Scopus databases in November 2023. The following descriptors were used, linked using the Boolean operators AND and OR: Diabetes, Continuous glucose monitoring, Flash glucose monitoring, Glycemia, Glycemic control, Controlled diabetes, Diabetes care, Metrics, Older and Elder. The CASPe critical reading system and the PRISMA methodology were applied to document the review. Fourteen selected studies published between 2019 and 2023 were reviewed. Publications from European countries used small sample sizes and were intervention studies. The duration of the interventions was generally short: 7 were ≤14 days in duration and only 3 were 6-12 months in duration. Overall, the selected articles found that CGM improved glycemic outcomes due to a decrease in glycosylated hemoglobin value and an improvement in CGM metrics, and diabetes-associated complications in elderly patients with diabetes. CGM seems to be a useful and effective tool to improving glycemic outcomes of people with diabetes over age 65. Further studies under real-world conditions and of longer duration are needed to expand and improve the evidence.

MODERN CHALLENGES TO THE MANAGEMENT OF INNOVATION AND COMPETITIVENESS OF ORGANIZATIONS IN THE FIELD OF MEDICAL SERVICES

The latest realities of development of the medical services sector have highlighted the effectiveness of innovation management as an important factor in the competitiveness of a medical organization. The authors hypothesized that at this stage certain challenges have emerged that have identified a number of problems for managing innovation in the field of medical services. So, they create threats to the competitiveness of organizations that cannot find reliable approaches to managing innovation in real-world conditions. A study of the flow of innovations in the medical field in recent years has confirmed this situation. Тhe main challenges and problems of innovation management at the present stage were formulated at the work and were put forward proposals for their possible solutions.

Investigation Lubricity Performance of Lubricating Oil Used in Marine Diesel Engine—Fuel Injection Pump

Diesel engines commonly suffer from oil contamination by fuel and other chemicals during operation and maintenance. This contamination alters the oil’s lubricating properties, leading to increased wear, corrosion, and other potential problems. Therefore, it is crucial to understand how oil degrades and becomes contaminated due to different replacement strategies is crucial for both engine operators and manufacturers. This study focuses on the impact of fuel dilution on specific properties of engine oil under real-world operating conditions in a marine diesel engine. Oil samples were collected regularly from the crankcase of the engine fuel injection pump and tribological tests were performed. These tests aimed to assess how marine gas oil affects the oil lubricity performance and how it maintains its useful life. The results confirm that diesel dilution primarily affects the oil lubricating abilities as well as overall performance.

Virtual Plug-In Hybrid Concept Development and Optimization under Real-World Boundary Conditions

The automotive industry faces development challenges due to emerging technologies, regulatory demands, societal trends, and evolving customer mobility needs. These factors contribute to a wide range of vehicle variants and increasingly complex powertrains. The layout of a vehicle is usually based on standardized driving cycles such as WLTC, gradeability, acceleration test cases, and many more. In real-world driving cycles, however, this can lead to limitations under certain boundary conditions. To ensure that all customer requirements are met, vehicle testing is conducted under extreme environmental conditions, e.g., in Sweden or Spain. One way to reduce the development time while ensuring high product quality and cost-effectiveness is to use model-based methods for the comprehensive design of powertrains. This study presents a layout methodology using a top-down approach. Initially, powertrain-relevant requirements for an exemplary target customer are translated into a specification sheet with specific test cases. An overall vehicle model with detailed thermal sub-models is developed to evaluate the different requirements. A baseline design for a C-segment plug-in hybrid vehicle was developed as part of the FVV research project HyFlex-ICE using standardized test cases, highlighting the influence of customer profiles on the design outcome through varying weighting factors. The target customer’s design is analyzed in four real driving scenarios, considering variations in parameters such as the ambient temperature, traffic, driver type, trailer pulling, and battery state-of-charge, to assess their influence on the target variables. In the next step, the potential of hardware technologies and predictive driving functions is examined in selected driving scenarios based on the identified constraints of the baseline design. As a result, four application-specific technology packages (Cost neutral, Cold country, Hot country, and Premium) for different customer requirements and sales markets are defined, which, finally, demonstrates the applicability of the holistic methodology.

Thermal performance assessment of exterior building walls under intermittent air-conditioning operation in China's hot summer and cold winter zone

Optimizing the design and accurately assessing the performance of building envelopes are critical for substantially reducing energy use in the building sector. Existing studies on methods for evaluating the thermal performance of building envelopes have primarily focused on periodic unsteady conditions (often associated with continuous air-conditioning operation). This study aims to investigate the initial transient thermal performance of exterior building envelopes. Specifically, we examined varying insulation distributions considering the hot summer and cold winter zone of China as an example. To simulate real-world conditions, we developed a dynamic hot box facility that mimics both outdoor and indoor environments, enabling the measurement of key parameters of the dynamic thermal process of the wall. We evaluated the thermal response, energy performance, and heat storage metrics of the wall to understand the impact of the insulation distribution and air-conditioning operation modes on the thermal performance of opaque building walls. This assessment covered six intermittent operation stages—four construction structures and two types of building usage—for both summer and winter conditions. The proposed methodology provides a quantitative approach for assessing the dynamic thermal processes of the wall, with the results indicating that the heat transmission of walls during intermittent operation exhibited initial transient characteristics. As a result, thermal performance indices suitable for periodic unsteady conditions could not be directly applied to initial transient conditions. To address this issue, the metrics of daily mean dynamic thermal transmittance and daily mean dynamic thermal resistance were proposed and validated. These metrics accurately reflected the actual fluctuations in total transmission loads, thus providing an accurate rapid index-oriented method for assessing the energy-saving performance of walls. Overall, this study lays the groundwork for evaluating dynamic thermal behaviour of building envelopes.

Highly transparent, self-cleaning, and UV-shielding composite coating: When eco-friendly waterborne omniphobic surface cooperates with quantum dots

Solar energy is an inexhaustible carbon-free source, and solar cells are invaluable enablers for achieving carbon neutrality; however, the surface contamination on the glass of solar cells poses a formidable obstacle to maintaining a high power conversion efficiency. Existing self-cleaning coatings for combating surface contamination generally lack the highly comprehensive properties required for applications in real-world conditions. Herein, eco-friendly, highly transparent, waterborne omniphobic Si2.5WPA/AmZnO@SiO2 coatings were developed by the ingenious design of polydimethylsiloxane-grafted waterborne polyacrylate (SixWPA) and (3-aminopropyl)triethoxysilane-modified-SiO2 encapsulated ZnO quantum dots (AmZnO@SiO2). The enriched PDMS flexible chains on the coating surface overcame the energy barriers for moving liquids, and the AmZnO@SiO2 inside absorbed and scattered UV rays, which synergistically endowed the coating with self-cleaning and UV-shielding properties. Importantly, after the self-cleaning procedure, the light transmission of dust-contaminated glass and short-circuit current density of corresponding solar cells could be restored to 99.78 % and 97.77 % of initial metrics, respectively. Furthermore, the commonly ignored self-cleaning mechanism was investigated and proposed: the coating weakened the adhesion of dust particles and utilized the drag force generated during liquid slip to achieve self-cleaning. The coating also showed good UV/humidity/thermal stability and mechanical strength, providing a design blueprint for outdoor optical device protection.