The Effect of Changing Stirrup Spacing and Hook Angle on RC Cantilever Beams with Industrial Iron Chips Waste

In this study, the usability of industrial iron chips waste was investigated in order to provide recycling in the production of reinforced concrete cantilever beams with different stirrup spacing and hook angle. In the concrete produced for cantilever beams, aggregates not larger than 4 mm in diameter were reduced by 20% and replaced with iron chips waste. Cantilever beams are manufactured with stirrup spaces of 50, 100 and 150 mm. The hook angles of the stirrups are differentiated to be 90 and 135 degrees. The experimental setup was prepared in such a way that one side of the samples was fixed, and the other side was free. The loading process was done from the end point of the released side. Load-Displacement curves of cantilever beams were obtained. In the research, it was observed that although 20% iron chips added cantilever beams experienced a decrease in their strength compared to the reference beams, they increased their ductility values at all three different stirrup spaces. As the stirrup spacing widened, the ductility values decreased. However, the effect of iron chips additive on ductility has increased. Samples with stirrup hook angle of 135 degrees increased both strength and ductility values compared to samples with 90 degrees.

Client side and Server Side Load Balancing

In the microservice architecture it is vital to distribute loads across replicated instances of microservices. Load distribution such that no single instance is overloaded is called as load balancing. Often the instances of microservices are replicated across different racks, different data centers or even different geographies. Modern cloud based platforms offer deployment of microservices across different server instances which are geographically disperse. Having a system that will balance the load across service instances becomes a key success criteria for accurate functioning of distributed software architecture Keywords: Load Balancing, Microservices, Distributed software system

Development of site-specific non-intrusive load monitoring for maximum demand control

Demand-side load management (DSM) requires greater role-play by end-users. To lower the investment for this load management concept, non-intrusive load management (NILM) was introduced as the solution. However, most of the mathematical techniques used in NILM are complex. This may hinder users from actively take part in the energy management effort. This paper explores the possibilities of applying change point detection techniques with help of differentiation and application of filters. These filters were selected strictly based on site-specific conditions. As part of the NILM implementation, a new and practical technique was developed for this paper. It was found that the developed technique, despite its simplicity it can identify the electrical equipment which added the significant load demand. The performance of the technique was found to be satisfactory as compared to results reported by other researchers.

BIOMECHANICAL ASSESSMENT OFTHESTRESS-STRAIN STATUS OFSPLINTING STRUCTURES AND TEETH PERIODONTIUM IN CASE OF CHRONIC P

The authors have proposed an all-cast pin splint, whose technological feature is the ceramic lining of the over-the-bar part, which acts as a covering aesthetic structure, provides better distribution of the functional load and binds firmly mobile teeth affected by chronic moderate localized periodontitis. The paper offers a view at the outcomes of a comparative analysis of the stress-strain state of periodontal tissues, teeth, and cortical bone in chronic moderate localized periodontitis at the anterior group of teeth in the lower jaw, when they are splinted with a specially designed splint and a conventional metal-ceramic monolithic splint by finite element modeling. The developed 3D mathematical model included, as the initial data, the features of the periodontium, of dental tissue and of cortical bone. There was an examination carried out focusing on the distribution of stresses, which occur when using the designed splint under the impact of multidirectional loads of 130 N, acting strictly down relative to the tooth longitudinal axis (vertically), and a load at an angle of 45°. The proposed method of splinting reduces the maximum stress in the periodontium at a vertical load by 26.9%, while at a side load of 45° it reduced the stress by 34.7%, if compared to a traditional monolithic metal-ceramic splint.

Reactive Power Control Strategy of Demand Side Back-to-Back Converter Based on VSM

Background: The Demand Side Management (DSM) technology is playing an increasingly important role in the power system, in order to promote the real-time supply and demand balance of the power grid and improve the economy and safety of the power grid. Objective: To realize the flexible and continuous reactive power control of demand side load, a reactive power control strategy for the demand side back-to-back converter (DS-B2BC) is proposed. Methods: First, DS-B2BC is proposed. Then, the reactive power control model of DS-B2BC and its control loop are designed, and the reactive power control model, based on the Virtual Synchronous Motor (VSM), is established. Results: The simulation results verify that the reactive power control strategy proposed in this paper is effective, which can control the demand side load reactive power flexibly and continuously. Conclusion: Moreover, the strategy can counteract the disturbance from the power grid simultaneously.

Load Position and Weight Classification during Carrying Gait Using Wearable Inertial and Electromyographic Sensors

Lifting and carrying heavy objects is a major aspect of physically intensive jobs. Wearable sensors have previously been used to classify different ways of picking up an object, but have seen only limited use for automatic classification of load position and weight while a person is walking and carrying an object. In this proof-of-concept study, we thus used wearable inertial and electromyographic sensors for offline classification of different load positions (frontal vs. unilateral vs. bilateral side loads) and weights during gait. Ten participants performed 19 different carrying trials each while wearing the sensors, and data from these trials were used to train and evaluate classification algorithms based on supervised machine learning. The algorithms differentiated between frontal and other loads (side/none) with an accuracy of 100%, between frontal vs. unilateral side load vs. bilateral side load with an accuracy of 96.1%, and between different load asymmetry levels with accuracies of 75–79%. While the study is limited by a lack of electromyographic sensors on the arms and a limited number of load positions/weights, it shows that wearable sensors can differentiate between different load positions and weights during gait with high accuracy. In the future, such approaches could be used to control assistive devices or for long-term worker monitoring in physically demanding occupations.