Predictive modelling of heating and cooling degree hour indexes for residential buildings based on outdoor air temperature variability.

Heating and cooling degree hours (HDH and CDH) are weather-based technical indexes designed to describe the need for energy requirements of buildings. Their calculation is the simplest method to estimate energy demand, providing the pattern of internal temperature variations in a building in response to weather conditions. The aim of the study is HDH and CDH prediction for Wroclaw, Poland, based on outdoor air temperature using machine learning methods: artificial neural networks and support vector regression (ANN and SVR). The key issues raise in the study are: a detailed analysis of the most significant temperature lags (from 1 to 24 past hours) serving as predictors for modelling and an assessment of the impact of the database clustering on its accuracy. The best results are obtained with the clustering approach. The best predictor is the outdoor temperature observed 1 and 24 h before forecast demand (R2 = 0.981 and 0.904 for heating degree and cooling degree hours indices, respectively). Models with the highest quality are created using ANN, and the lowest with SVR. Prediction of heating/cooling degree hour indices provides building demand in advance, does not require knowledge about its characteristics, and expresses the possible impact of regional climate modifications.

3D Hand Scanning Methodology for Determining Protective Glove Dimensional Allowances.

There are two types of dimensional allowance (inner and external) related to two distinct areas of occupational health and safety: those being a measure of fit of personal protective equipment (PPE) and those determining the safe and comfortable human interaction with tools and machines, e.g., the latter ones result from wearing PPE increasing the dimensions of the human body and generating limitations in the work environment. In this paper, they are taken to mean the difference between the dimensions of a bare and gloved hand (including glove construction and materials). Dimensional allowances are important in designing the work environment, e.g., machine control panels and tools. The absolute and relative maximum values of dimensional allowances determined in this study for a hand in a firefighter's protective glove for the main anthropometric data are: 16.90 mm (5.90%) for length, 12.00 mm (13.77%) for width, and 15.70 mm (7.96%) for circumference. The obtained results are useful for designers, and especially for designing keys on control panels and LCD touch displays and monitors integrated with machines.

Study of The Impact of Users' Features on Dimensional Allowances Resulting from the Use of Personal Protective Equipment.

Up-to-date anthropometric data on the human population are needed for designing safe and ergonomically efficient workplaces. An important determinant of safety and ergonomic comfort at work is knowledge of the value of dimensional allowances (DAs) when using personal protective equipment (PPE) as the dimensions and space occupied by workers increase. This is particularly important in environments characterized by spatial constraints. However, it is not well known to what extent the aforementioned DAs are affected by the users' features. The anthropometric dimensions of 200 people (151 males and 49 females) were obtained from 3D scans, and these became the basis for calculating DAs when using PPE kits normally worn by rescue and technical workers. DAs were determined for the entire body shape of a person wearing three types of PPE kits designed for firefighters, mine rescuers, and welders. In the study, maximum and mean values of height, width, and circumference DAs were obtained. In addition, percentage dimensional increments (DIs) were calculated. A three-dimensional analysis of the human body with and without PPE, involving a 3D scanning methodology, was applied to address the research question. Test results clearly indicate that the values of DAs do not depend on the anthropometric features of users, such as sex, age, and body height percentile-they remain constant for a given type of PPE. The presented data are useful for designing PPE products as well as work tools and infrastructure, including machinery, devices, workstations, means of transport, interiors, and building equipment. The results of the presented study indicate that dimensional allowances play a significant role in interactions between persons wearing PPE and their work environments. The obtained results (DAs and percentage DIs) are included in a new anthropometric atlas of human measures developed by the CIOP-PIB in 2023.

The importance of data splitting in combined NOx concentration modelling.

The polluted air breathed every day by those living in large conurbations poses a significant risk to their health. Through effective modelling (prediction) of concentrations of pollutants and identification of the factors influencing them, it should be possible to obtain advance information on dangers and to plan and implement measures to reduce them. This work describes two different modelling approaches: based on the NOx concentration of the previous hour (C&RT models); and based on meteorological factors, traffic flow, and past (up to two previous hours) NOx and NO2 concentrations (CA models). For each approach, three alternative machine learning methods were applied: artificial neutral network (ANN), random forest (RF), and support vector regression (SVR). The best fits were obtained for the models using ANN and RF (MAPE values in the range 18.3-18.5 %). Poorer fits were found for the SVR models (MAPE equal to 23.4 % for the C&RT approach and 29.3 % for CA). No significant preferences were identified between the C&RT and CA approaches (based on various goodness-of-fit measures). The choice should be determined by the purposes for which the forecast is to be used.

Improving short-term water demand forecasting using evolutionary algorithms.

Modern solutions in water distribution systems are based on monitoring the quality and quantity of drinking water. Identifying the volume of water consumption is the main element of the tools embedded in water demand forecasting (WDF) systems. The crucial element in forecasting is the influence of random factors on the identification of water consumption, which includes, among others, weather conditions and anthropogenic aspects. The paper proposes an approach to forecasting water demand based on a linear regression model combined with evolutionary strategies to extract weekly seasonality and presents its results. A comparison is made between the author's model and solutions such as Support Vector Regression (SVR), Multilayer Perceptron (MLP), and Random Forest (RF). The implemented daily forecasting procedure allowed to minimize the MAPE error to even less than 2% for water consumption at the water supply zone level, that is the District Metered Area (DMA). The conducted research may be implemented as a component of WDF systems in water companies, especially at the stage of data preprocessing with the main goal of improving short-term water demand forecasting.

Procedure for Determining Dimensional Allowances for PPE Using 3D Scanning Methods.

The article describes the importance of dimensional allowances, which are a consequence of the use of personal protective equipment (PPE) for work safety. The method of 3D scanning was proposed for determining the dimensional allowances which has been preliminary validated. Two geometric solids (a cylinder and a cuboid) were used to approximate the minimum space around the person using PPE. The solids are a simplified representation of the silhouette of a human subject performing activities in a confined work environment. They also correspond to the typical shapes of access openings and confined spaces, reflecting the real working conditions of welders, firefighters, mine rescuers, and other rescue teams. A detailed analysis of dimensional allowances for a full welding PPE set is provided. Based on the adopted parameters: the dimensions of the body, the base area and the volume, the differences in the dimensions of the body of a person dressed in underwear and in PPE were compared. The results of the presented studies indicate a significant role of dimensional allowances in interactions between persons wearing PPE and the work environment. The results are planned to be implemented in a new anthropometric atlas of human's measures used for ergonomic design.

The Influence of Intraocular Lenses (IOLs) on the Properties of Filters Protecting Human Eyes against Optical Radiation in the Work Environment.

Under the specific illumination conditions of many workplaces, e.g., in the metallurgical industry, decreased lighting may impair workers' vision and, as a result, their productivity. Spectrophotometric tests of two types of protective optical filters (welding filters and infrared protection filters), two types of intraocular lenses (IOLs with and without yellow chromophore), and filter-IOL systems were carried out. In spectrophotometric studies, the spectral characteristics of transmission and the coefficients for the assessment of light transmission were determined. This study explores the relationship between the eye protection levels offered by filters and the use of intraocular lenses (IOLs), and especially those containing a yellow chromophore which may lower the luminous transmittance of protective filters. In our previous works, we studied a large number of optical protective filters and many factors influencing their performance. A review of the literature has shown the absence of prior research on the subject. For this purpose, transmittance reduction factors were defined for the evaluation of the filter-IOL system. The spectral characteristics of luminous transmittance for the tested IOLs indicate a significant decrease of transmittance for those with yellow chromophore within the range up to approx. 475 nm, as compared to IOLs without chromophore. The main objective of this study was to determine whether people with IOLs need different protective filters against harmful optical radiation as well as whether IOLs may change the required category of protective filters. The key finding is that while the use of IOLs in conjunction with protective filters does change the light transmission coefficient, it does not affect the filter protection levels. The transmittance reduction factors were similar (0.95 to 0.99 relative units) for all filter-IOL systems irrespective of the presence or absence of yellow chromophore. It must be said clearly that, in reference to the requirements specified in the standards, IOLs did not affect the filter protection levels. This means that the quality of vision did not change significantly when using the analyzed filters and IOLs.

Influence of Insolation on the Efficiency of NO3 Removal from Wastewater Treated in the Hydroponic System.

The use of plants and natural processes for wastewater treatment is an issue that arouses interest among technologists and scientists around the world. The aim of the article was to analyze the influence of the air temperature and insolation on the removal of nitrate nitrogen from the wastewater treated in the hydroponic system, under greenhouse conditions. Samples of sewage for its quality tests were taken from a wastewater treatment plant (WWTP) located in the southwestern part of Poland. Data regarding daily sunshine duration and average daily air temperature values in selected periods of 2013-2016 come from a meteorological station located 30 km from WWTP. The conducted research and analyses of the results clearly indicate that under moderate climate conditions, the amount of solar radiation reaching the Earth's surface is insufficient to ensure the year-round, effective wastewater treatment process in the hydroponic system. In the case of air temperature, no correlation was found between the tested parameters, which indicates the lack of temperature influence on the efficiency of NO3 removal from the wastewater by macrophytes growing in the lagoon.