Uncertainty and sensitivity analyses of operational errors in air handling units and unexpected user behavior for energy efficiency and thermal comfort

Resource scarcity and anthropogenic climate change require the reduction of performance gaps in existing buildings. In addition to unexpected user behavior, performance gaps are primarily caused by the technical gap due to operational errors in building technology. The main objective of this paper is to quantify model input uncertainty incorporating uncertain boundary conditions in terms of operational errors using thermo-dynamic building performance simulations and to identify the most relevant input parameters for the performance gaps in air conditioning systems by means of sensitivity analyses. Model input uncertainty is stochastically determined using Monte-Carlo Simulations to calculate the target values “primary energy demand” as well as “over- and under-temperature degree hours” for an office building. Selected parameters are simulated in a specific uncertainty and sensitivity analyses using the Sobol’ and Jansen estimators, which distinguish between a direct influence on the target variables and interactions between the parameters. The methodology requires a selection process, which is carried out as part of relative uncertainty and relative sensitivity analyses. Furthermore, the operational errors are compared with construction factors as well as building physics inputs and design parameters for building technology systems to show their reciprocal effects as part of a comprehensive investigation. The main findings of this paper are that operational errors in air conditioning systems play an essential role in decreasing energy efficiency and thermal comfort, but do not warrant the significance of certain construction factors as well as setpoints in building technology. Moreover, the impact of operational errors on thermal overheating of the building investigated is minor compared to other targets that cause greater model input uncertainty.

Development and Application of Virtual Simulation Teaching Platform for the Transcritical CO2 Two-Stage Compression Refrigeration System Based on LabVIEW

Based on the principle of transcritical CO2 two-stage compression refrigeration system, a virtual simulation teaching platform was developed. Two operation modes can be selected which are practice mode and test mode. According to questions and tips about experiments, students can do simulation experiments by open required valves, running the refrigeration system, adjusting pressure control valves and so on. When these operations are completed, students can save the file of the simulation experiment and exit the system. Then, test marks of students can be exported to Excel for teachers to view. In addition, some risks of operational errors can also be avoided, such as equipment damage. Moreover, if there is a computer, the simulation experiments can be done by this virtual simulation teaching platform, which is very convenient. The virtual simulation teaching platform is innovative and practical. The application of this virtual simulation teaching platform can improve the quality of the traditional teaching in the refrigeration field.

A Novel Training and Collaboration Integrated Framework for Human–Agent Teleoperation

Human operators have the trend of increasing physical and mental workloads when performing teleoperation tasks in uncertain and dynamic environments. In addition, their performances are influenced by subjective factors, potentially leading to operational errors or task failure. Although agent-based methods offer a promising solution to the above problems, the human experience and intelligence are necessary for teleoperation scenarios. In this paper, a truncated quantile critics reinforcement learning-based integrated framework is proposed for human–agent teleoperation that encompasses training, assessment and agent-based arbitration. The proposed framework allows for an expert training agent, a bilateral training and cooperation process to realize the co-optimization of agent and human. It can provide efficient and quantifiable training feedback. Experiments have been conducted to train subjects with the developed algorithm. The performances of human–human and human–agent cooperation modes are also compared. The results have shown that subjects can complete the tasks of reaching and picking and placing with the assistance of an agent in a shorter operational time, with a higher success rate and less workload than human–human cooperation.

Condition Assessment of Solar Modules by Flash Test and Electroluminescence Test

The Hungarian society and the Hungarian state are constantly increasing their solar capacity. More and more solar power plants are being put into operation. The largest of these has a 100 MW peak capacity. Such power plants do not require constant maintenance. However, in the case of low productivity, a conditional assessment is required. The reason for production loss can also be manufacturing, installation, and operational errors. A flying drone was used for finding failures by thermographic scouting. Furthermore, electroluminescent (EL) and flash tests give a comprehensive view of the real state of the modules in a mobile laboratory. We had the opportunity to summarize these test results of more than a thousand modules operating in a solar power plant. The report on the power plant shows that a significant part of the modules became unusable in a short time. After four years, 10% of the 260 Wp modules suffered a performance reduction of more than 10%.

The Working Conditions and Optimisation of a Large Rainwater Harvesting and Treatment System in an Area at a Risk of Erosion

Rainwater harvesting and treatment systems (RHTS) are used in many places around the world as a part of sustainable water management. They decrease the risk of overloading the sewage network and environmental pollution. The efficiency and reasonableness of using such solutions in specific erosive conditions are not sufficiently understood. The aim of the study was to evaluate the operation of RHTS, receiving effluents from the wholesale market and fuel station (twenty years of observations). The studied system is located in an area endangered by water erosion. In the study period, due to the accumulation of erosive phenomena, it was necessary to optimise the system (including the installation of new devices and increasing the capacity of reservoirs). The analyses referred to the stability and work safety of the most important equipment and water treatment efficiency. The quality of water in the reservoirs was measured before and after the modernisation of the system. Selected physical, oxygen, biogenic and salinity indicators were determined in the water. During the study, RHTS had a positive effect on the quality of rainwater runoff – the values of many contaminants were reduced (RHTS 1: suspended solids, nitrogen, iron, potassium; RHTS 2: conductivity, suspended solids, nitrogen). Design and operational errors were noticed that in the long run may contribute to deteriorating the operational efficiency and even lead to a building collapse (intense erosive phenomena). This study clearly demonstrates that building a rainwater management system is a highly site-specific issue.

An End-to-End Bidirectional Authentication System for Pallet Pooling Management Through Blockchain Internet of Things (BIoT)

Pallet pooling is regarded as a sustainable and cost-effective measure for the industry, but challenging to advocate due to weak data and pallet authentication.In order to establish trust between end-users and pallet pooling services, we propose an end-to-end, bidirectional authentication system for transmitted data and pallets based on blockchain and Internet-of-things (IoT) technologies. In addition, secure data authentication fosters the pallet authenticity in the whole supply chain network, which is achieved by considering the tag, location, and object-specific features. To evaluate the object-specific features, the scale invariant feature transform (SIFT) approach is adopted to match key-points and descriptors between two pallet images. According to the case study, it is found that the proposed system provides a low bandwidth blocking rate and a high probability of restoring complete data payloads. Consequently, positive influences on end-user satisfaction, quality of service, operational errors, and pallet traceability are achieved through the deployment of the proposed system.

LC-MS-Based Urine Metabolomics for the Identification of Biomarkers Related to The Occurrence and Severity of Flight Fatigue

Background: Aircrew fatigue is a major contributor of operational errors in civil and military aviation, which translates a comprehensive performance associated with both neuromuscular and cognitive states. Here we have used untargeted and non-invasive urinary metabolomics to explore flight fatigue-related aberrations. In this sense, we aimed to identify biomarkers that could better monitor pilot fatigue and also assess its severity to prevent ‘nonfunctional over-reached’ state, thus promoting flight safety. Methods: In this study, 22 active-duty male pilots, who conducted different flight hour duties, were recruited to mimic different levels of fatigue. For this, respective urine samples were collected, before and after flight, and analyzed by liquid chromatography/mass spectrometry (LC/MS). Results: Except for the fatty acids and some amino acids, significant changes on metabolite levels were observed during the progression of flight fatigue. Most of these metabolites corresponded to acyl carnitines, carbohydrates, purines and indoles. The majority of amino acids were downregulated after the flight mission. A total of 61 metabolites were found to be significantly changed along with the extent of flight fatigue. To efficiently discriminate the occurrence of flight fatigue, three candidate biomarkers (beta-guanidinopropionic acid, 3-dehydro-L-gulonate and 2-propylpent-3-enoic acid) were further characterized. Lastly, Bayes discriminant function models were established to stratify pilots with severity of fatigue and, therefore, to aid in flight risk management.Conclusion: To our knowledge, this study inaugurally provides a metabolic profiling in response to flight fatigue, thus offering a novel and effective way to monitor and manage this physiological condition.

Impact of shift work on excessive daytime sleepiness among healthcare professionals and its association with medical incidents: A review

Sleep disorders, especially excessive daytime sleepiness (EDS), is a common complaint among medical professionals such as physicians and nurses. EDS is associated with decreased level of alertness in everyday life and thus leads to road accidents, workspace errors, and lack of concentration in people. We reviewed the literature to know the influence of shift work in the development of EDS and to scrutinize the relation between EDS and medical incidents. In association with EDS, shift work is defined as major risk factors. As health-care professionals are regularly involved in shift work to complete the 24 h services, they were more prone to experience EDS and may cause occupational incidents. Even though it is apparent that working in long shifts leads to sleep disorders, as the body clock is unbalanced, ample or apt research is required to collect reliable evidence. Various studies have reported occupational errors among nurses on comparatively longer work hours like drug administration errors, needlestick injuries, and operational errors in the past 12 months. In conclusion, these variables, that is, shift work, EDS, and occupational errors are directly related to each other. Further studies are required to explore the scenario between these factors.

Establishment of open-source semi-automated behavioral analysis system and quantification of the difference of sexual motivation between laboratory and wild strains

Behavioral analysis plays an important role in wide variety of biological studies, but behavioral recordings often tend to be laborious and are associated with inevitable human-errors. It also takes much time to perform manual behavioral analyses while replaying the videos. On the other hand, presently available automated recording/analysis systems are often specialized for certain types of behavior of specific animals. Here, we established an open-source behavioral recording system using Raspberry Pi, which automatically performs video-recording and systematic file-sorting, and the behavioral recording can be performed more efficiently, without unintentional human operational errors. We also developed an Excel macro that enables us to easily perform behavioral annotation with simple manipulation. Thus, we succeeded in developing an analysis suite that mitigates human tasks and thus reduces human errors. By using this suite, we analyzed the sexual behavior of a laboratory and a wild medaka strain and found a difference in sexual motivation presumably resulting from domestication.