Investigating the environmental impact of reinforced-concrete and structural-steel frames on sustainability criteria in green buildings

Reducing the detrimental impact of human activities on our environment is an essential need. Buildings have a significant role in accomplishing this need, which necessitates the conduction of comprehensive research that adequately identifies the underlying factors and then seeks sustainable solutions. Green buildings have been one of the critical initiatives to lessen the negative impact of human endeavors on the environment. The structural frame is one of the most critical elements of buildings, especially owing to their impact on the environment. This study investigates how structural building frames perform according to sustainability criteria. A questionnaire was used to identify the relevant sustainability criteria, and a hybrid Delphi-SWARA model was used to determine the relative importance of eight comprehensive prioritized criteria. A building was simulated with DesignBuilder software to quantify the environmental impact of two main types of structural frames, reinforced concrete (RC) and structural steel (SS) frames, on sustainability criteria. Results illustrated that RC-framed buildings have a less detrimental impact on the environment due to less energy consumption and carbon emissions. The energy consumption in RC-framed buildings was 2.3% less in electricity consumption and 2.7 less in natural gas consumption. In addition, 88 tonnes of CO2 emission can be reduced with this type of frame in a 50-year lifecycle which is more than 5% of the total CO2 production of the building. The methodological approach used in this research introduces a novel way for decision-makers to consider the sustainability criteria in the design stage

Drone-Assisted Confined Space Inspection and Stockpile Volume Estimation

From MDPI via Jisc Publications RouterHistory: accepted 2021-08-18, pub-electronic 2021-08-24Publication status: PublishedThe accuracy of stockpile estimations is of immense criticality to process optimisation and overall financial decision making within manufacturing operations. Despite well-established correlations between inventory management and profitability, safe deployment of stockpile measurement and inspection activities remain challenging and labour-intensive. This is perhaps owing to a combination of size, shape irregularity as well as the health hazards of cement manufacturing raw materials and products. Through a combination of simulations and real-life assessment within a fully integrated cement plant, this study explores the potential of drones to safely enhance the accuracy of stockpile volume estimations. Different types of LiDAR sensors in combination with different flight trajectory options were fully assessed through simulation whilst mapping representative stockpiles placed in both open and fully confined areas. During the real-life assessment, a drone was equipped with GPS for localisation, in addition to a 1D LiDAR and a barometer for stockpile height estimation. The usefulness of the proposed approach was established based on mapping of a pile with unknown volume in an open area, as well as a pile with known volume within a semi-confined area. Visual inspection of the generated stockpile surface showed strong correlations with the actual pile within the open area, and the volume of the pile in the semi-confined area was accurately measured. Finally, a comparative analysis of cost and complexity of the proposed solution to several existing initiatives revealed its proficiency as a low-cost robotic system within confined spaces whereby visibility, air quality, humidity, and high temperature are unfavourable

PROTECT - A COVID-19 National Core Study: Keeping the UK building safely 2

TransmissionThere is evidence of a broad range of COVID-19 transmission mitigation measures in action; these were generally well received by participants, who reported high levels of compliance.There is evidence of competing requirements of COVID-19 specific and established construction health and safety regulations. For example, and as may be expected, social distancing proved problematic in situations where proximity working is required. Creative measures were used to mitigate risk where social distancingwasn’t feasible for example adapting tools and processes or using teams who cohabited. Whilst participants reported reductions in serious safety incidents on sites, the prevalence of minor incidents increased. For example, face coverings were cited as an inhibitor of effective communication between workers. The availability of remote working arrangements to some construction workers led tosome participants reporting the presence of an ‘us-them’ culture

Sensitivity analysis of higher order coherent spectra in machine faults diagnosis

In an earlier study, the poly-coherent composite higher order spectra (i.e. poly-coherent composite bispectrum and trispectrum) frequency domain data fusion technique was proposed to detect different rotor-related faults. All earlier vibration-based faults detection involving the application of poly-coherent composite bispectrum and trispectrum have been solely based on the notion that the measured vibration data from all measurement locations on a rotating machine are always available and intact. In reality, industrial scenarios sometimes deviate from this notion, due to faults and/or damages associated with vibration sensors or their accessories (e.g. connecting cables). Sensitivity analysis of the method to various scenarios of measured vibration data availability (i.e. complete data from all measurement locations and missing/erroneous data from certain measurement locations) is also examined through experimental and industrial cases, so as to bring out the robustness of the method

Combined bispectrum and trispectrum for faults diagnosis in rotating machines

Over the years, condition monitoring of rotating machines has been extensively applied for enhancing equipment reliability and maintenance cost-effectiveness, through the early detection and reliable diagnosis of incipient machine faults. Earlier studies suggest that bispectrum analysis is a good tool for detecting and distinguishing rotor-related faults in rotating machines, with a significantly reduced number of vibration sensors. Now, the trispectrum analysis is also applied to the measured vibration data, so as to explore the usefulness of this analysis in the diagnosis. It is observed that the trispectrum further improves the reliability of rotating machines’ faults diagnosis. This article presents the results and observations related to the bispectrum and trispectrum analyses for fault(s) diagnosis, through an experimental rig with different faults simulation. </jats:p