Using an accurate energy model, this paper simulated existing commercial buildings to compare PMV-based comfort control with conventional thermostatic control and conduct a sensitivity analysis using the Design of Experiments method with monitored energy consumption data. This analysis was applied considering the impact of building envelope characteristics including thermal insulation level of exterior walls and air leakage rate on the ability of both control options to maintain indoor thermal comfort while minimizing cooling energy consumption. The analysis findings indicated that PMV-based comfort control is viable for striking a middle ground between thermal comfort and heating energy consumption with a PPD level at 8% for any combination of walls' R-value and air infiltration rate while temperature-based controls result in an unacceptable indoor thermal comfort performance especially for low R-values regardless of the air infiltration rate with PPD level reaching over 76%. Also, the results show that in a comfort-controlled space, the average radioactive temperature and occupant-related features like metabolic rate and clothing level have a far bigger effect on energy use than other parameters like relative humidity.
The aim of this study was to improve the efficiency of external corrosion inspection of pipes in chemical plants. Currently, the preferred method involves manual examination of images of corroded pipes; however, this places significant workload on human experts owing to the very high number of such images. To address this issue, we developed an artificial intelligence (AI)-based corrosion diagnosis system and implemented it in a factory. Initially, interviews were conducted to understand the decision-making processes of human experts. Subsequently, we converted their tacit knowledge into explicit knowledge, which was used to define the training data for the machine learning (ML) model. The predictions of the ML model were compared with the manually obtained results, exhibiting an accuracy of 70 %. The proposed architecture was based on human-in-the-loop ML. It included a process to retrain the ML model using manual results gathered during operation. It was operated using a collaborative approach, in which human experts supported the ML model under development. The proposed model enhanced the efficiency of the inspection process successfully.
In this experimental work, an optically accessible rapid compression machine is used to study the ignition and combustion process under engine relevant operation conditions for five different air-natural gas equivalence ratios (λ) ignited with either 12.2 mg or 6.7 mg of pilot diesel injected at 1,600 bar.Initial temperature of the ambient mixture, walls and injector was 333 K. Additionally, for the short (6.7 mg) diesel injection, the variation in the ID (ignition delay) for two higher ambient temperatures (343 K and 353 K) was measured.Pressure and piston displacement are recorded while two high-speed cameras simultaneously capture signals in the visible range spectrum and at 305 nm wavelength for OH* chemiluminescence respectively.ID is measured both from OH* and pressure rise.From the recorded data, the heat release ratio is estimated and compared with the visual signals.This gives an insight of the temporal and spatial evolution of the flame, as well as a qualitative perception of the transition from spray ignition into a premixed flame in the ambient fuel-air mixture.It was found that increasing the methane concertation delays the ignition, reduces the natural flame luminosity and enhances the OH* chemiluminescence signal.
The present paper describes an investigation conducted on metal detection with a scanning probe. The authors applied a rotating magnetic field probe to metal detection. The rotating magnetic field probe was composed of two vertically placed rectangular exciting coils and a circular detecting coil. The experimental results confirmed that the probe could detect metal objects and provide more information about their shape, direction, and electromagnetic characteristics than conventional metal detector probes. A two‐dimensional signal display shows a blurred image of the metal object and the signal phase indicates the object's direction and electromagnetic characteristics. The experimental results showed that excellent restoration of the surface shapes of metal objects can be obtained for both magnetic and nonmagnetic metals under present conditions. There is also a possibility that the rough shape of a metal object can be estimated from the restored image. © 2011 Wiley Periodicals, Inc. Electr Eng Jpn, 177(4): 1–11, 2011; Published online in Wiley Online Library ( wileyonlinelibrary.com ). DOI 10.1002/eej.21178
In this article, the classic algorithms "Needleman-Wunsh" and "Smith-Waterman" are reviewed with which the alignment of genomic sequences is generated. The Smith-Waterman is improved with the aim of optimizing said process in order to provide optimal results through the implementation of Artificial Bee Colony. The experiments that are carried out show alternative alignments that the classical methods do notfind easiest, however they can be found in the analyzed data.
