Reinforced concrete Structures are subjected to temperature changes daily and seasonal this is besides the live and dead loads applied to the building the changes in the temperature consequently produce temperature loads due to their interaction with the surrounding environment as well as the solar radiation exposure of the building. Such temperature loadings consequently lead to thermal stresses in most structural elements. These thermal loads will produce thermal stresses that can be considered comparable to or sometimes exceed the stresses of the dead and live loading due to insufficient thermal insulation which may lead to severe structural elements damage if it is not considered in the design phase. This paper presents a study of the effect of thermal loads on multi-story RC. buildings in Saudi Arabia with fixed and hinged support constraints with and without bracing system under seismic loads on sloped terrain. RC. buildings have a high vulnerability when designed on sloped terrains due to the mass and vertical irregularity that will increase the values of shear forces and torsional moments on the building. This work attempts to study the building's behavior on sloped terrain under the effect of thermal loads using ETABS V18.1. Etabs Models were analyzed to present the effect of thermal loads concentrating on the displacement, drift, deformations, and base shear.

Digital technologies (DTs) have been recognized and adopted for safety training in construction to enhance the safety performance of organizations. This study aimed to understand the state-of-art review of the DTs adopted for safety training and their application areas in construction since 2000. Fifty-nine articles were found after conducting a systematic literature review (SLR) using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) review method. The research trend was identified and described using bibliometric analysis in terms of the number of publications per year, sources of documents, influential authors and regions, highly cited articles, and research areas. The findings indicated that immersive virtual reality (VR) technology was used widely to train and educate individuals in construction research. In terms of research areas, most of the DTs were focused on enhancing individuals’ hazard recognition (HR) skills. The findings summarized the mainstream research areas, discussed existing research gaps, and suggested future directions in DTs application for safety training in construction. The recommended future directions could improve safety training performance in the construction industry.

Underestimating the impact of complexity is an important reason for the poor performance of large-scale construction project management. The purpose of this paper is to improve the understanding of the perceived complexity of contractors, identify the complexity factors of construction projects in China, and provide basic research results for the treatment of complexity. From the perspective of contractors in the construction implementation stage, the literature on construction projects complexity is sorted out, and 17 initial indicators of influencing factors are determined through document analysis and expert interviews. Taking 130 questionnaires as samples, 17 influencing factors passed reliability and validity tests. Through exploratory factor analysis (EFA), a four-dimensional framework for influencing factors of perceived complexity of construction project contractors is proposed, including Social Complexity, Environment Complexity, Technical Complexity and Stakeholder Complexity. Among those factors, the project funding, geological conditions, survey and design quality, stakeholder relationships are the key factors affecting the perceived complexity of construction project contractors in China. The research results are mainly applied in the field of construction project complexity management, which can provide basis and reference for the complexity management of railway, highway, subway and other large engineering construction projects.

Due to the apparent demands and constraints faced by energy systems operating in the market world, the Prosumer Energy trade strategy was selected as a potential opportunity for research and industries. Energy trading has expanded due to the availability of dispersed energy sources and power users who produce more electricity than they would otherwise and can profitably export their excess fuel. The energy trading system blends energy from various sources and effectively coordinates it to ensure stable and optimal usage of available resources and better facilities for energy users. Peer-to-peer (P2P) energy trading is a joint research topic that involves various managerial and technical challenges. This paper provides an overview of peer-to-peer energy exchange and how blockchain can be used to increase transparency and overall performance, including the degree of decentralization, scalability, and device reliability. A thorough examination of the Prosumer Smart Grid environment is explored and clarified. The energy sharing mechanism among consumers comprises two major components: information/digital technology and optimization techniques. Three blockchain-based energy sharing models have been proposed to overcome technical and market barriers to adopt this revolutionary technology. The paper further discusses open topics and possible future paths for peer-to-peer blockchain-based energy sharing.

In a conventional furniture design process, the designer develops a number of design alternatives by drawing two dimensional sketches and 3d CAD models to start ideation and exploration. These ways of exploration and conceptualization are sometimes tiring, time taking and complex. Therefore, the designer is able to produce less output with limited results. However, with recent advancements in design simulation, visualization and modelling capabilities, the ways of design exploration and conceptualization have changed. Technological transformations have changed the entire product design and development process in the past years. Today, parametric modeling techniques are changing the role of CAD tools in the furniture design field. In comparison to the conventional CAD tools (direct drafting and modeling techniques) parametric and generative design techniques allow the designer to rapidly and easily generate iterations, providing a flexible way to explore and conceptualize innovative solutions based on specific parameters. Considering the growing transformations this research aims to explore the new language of design - generative design. The study focuses on to integrate generative design and parametric modeling techniques with conventional design process to develop a digital design and development methodology for furniture products.

This paper investigates the consensus problem of an array of large mobile sensor networks. A new framework for the dynamic of mobile sensors as a continuum which described by parabolic system with boundary disturbance is proposed. The communication topology of agents is a chain graph and fixed. Leader feedback laws which is designed in a manner to the boundary control of large mobile sensor networks allow the mobile sensors achieve the formation steadily. By referring to Lyapunov functional method and employing boundary control approach, a new protocol is established to deal with formation problem for the large mobile sensor networks. Finally, numerical examples are given to illustrate the usefulness of the results.

With an expanding number of institutions participating in the global education market, verifying the legitimacy of academic achievements such as CVs and certificates has grown more difficult. Blockchain is an enabling technology that has the potential to help solve this issue. This research presents a blockchain-based achievement record system that generates a verified record of accomplishments. Using the unique characteristics afforded by Blockchain technology (public Ethereum Blockchain) and smart contracts, the proposed solution intends to make the process of certificate authentication and validation more reliable, easy, and fast. The system’s design and structure, as well as its components and tools, are described. The system is then evaluated through a series of experiments to determine its usability, effectiveness, performance, and cost. A score of 77.1 was obtained on the System Usability Scale (SUS) test. In addition, an examination of End-User Computing Satisfaction (EUCS) revealed that participants deemed the system to be extremely useful and user-friendly. We show that this method is a major advance over older systems, being both more user-friendly and efficient, through a literature review. We also provide a thorough cost study and outline the benefits and drawbacks of various blockchain systems.

Allium sativum extract is one of the medicinal and aromatic products used in pharmaceutical and food industries. The scientific literature bibliography regarding process scale-up simulation and techno-economics of phenolic extract from Allium sativum microwave-assisted extraction is seldom reported. This study presented optimization and techno-economic evaluation of phenolics recovery from allium sativum microwave-assisted extraction. Box-benken design extraction experiment was conducted at irradiation power (520 – 1040 W), extraction time (2- 10 minutes) and solid-liquid ratio (0.4 – 1 g/100 ml). The extraction conditions that optimized experimental extractible yield and Total Phenolic Content (TPC) were evaluated in Box-benken desirability of Response Surface Methodology. Bioactive finger printing of the extract was analyzed using HPLC. Aspen Batch Process Developer was used for the process techno-economic analysis. Profitability uncertainty was analyzed using Monte-Carlo Simulation (MCS). Optimal extractible yield (28.62 %) and TPC (76.8 mgGAE/g dry extract) were obtained at irradiation time 7.62 mins, microwave power 826.67 Watt with solid-liquid ratio 0.55g/100ml. The HPLC fingerprint revealed Bentulinic acid, galic acid, chlorogenic acid, ellagic acid and ferulic acid. Cost of Manufacturing (COM) for 5L, 50L and 500L extractors gave US$ 1480, US$ 220 and US$ 56 respectively. Techno-economic results of 500L extraction capacity with 900 kg/year design gave batch size (0.25 kg), production rate (2 kg/mins), cycle time (125 mins), discounted NPV (38133 US$), ROI (34%), IRR (37%) and PBT (2.94yrs). MCS results show 85.58 % and 83.53certainties of achieving base case ROI PBT. Therefore, the study shows that MAE of garlic powder is economically feasible.

The design of structures for a long time use represents a big challenge in the rock mechanics and tunneling works. The water supply of the Pirtaghi Dam reservoir-pumping power plant in Iran is provided by the twin tunnels. Since the Pirtaghi dam site is located in an earthquake-prone area, it will probably experience earthquakes in its lifetime. So, in this project, the steady-state of the support system of the twin tunnels of the water supply of the Pirtaghi power plant under likely earthquake and static loading is evaluated by a 3D numerical modeling. The results show that the system is capable to guarantee stability against seismic loads.

Cd1-xZnxS thin films were deposited by chemical bath deposition (CBD) on glass substrate to study the influence of cadmium sulfate concentration on the structural characteristics of the thin film. The SEM results show that the thin film surfaces under the cadmium sulfate concentration of 0.005 M exhibit better compactness and uniformity. Due to the less Cd2+ involved in the reaction and little precipitation in the solution. The distribution diagrams of thin film elements illustrate that the film growth rate changes on the increase, decrease, and increase with the increase of cadmium sulfate concentration. XRD studies exhibit the crystal structure of the film is hexagonal phase, and there are obvious diffraction peaks and better crystallinity when the concentration is 0.005 M. Spectrophotometer test results demonstrate that the relationship between zinc content x and optical band gap value Eg can be expressed by the equation Eg(x)=0.59x2+0.69x+2.43. Increasing the zinc content can increase the optical band gap, the absorbance of the thin film can be improved by decreasing the cadmium sulfate concentration, however, all of them have good transmittance. At a concentration of 0.005 M, the thin film has good absorbance in the 300 - 800 nm range, 80% transmittance, and band gap value of 3.24 eV, which is suitable for use as a buffer layer for solar cells.

In this paper, with the purpose of improving the mechanical behavior of DeepCwind semi-submersible floating offshore wind turbine (FOWT) platform mooring lines, nonlinear catenary cables of platform are divided into multi-segments and intermediate buoy. The mathematical formulations of the dynamic equation acted on the cable with buoys are described. Present study is employed to the OC4-DeepCwind semi-submersible FOWT platform. It is designed for 200-meter water depth with mooring lines consist of three catenary steel chain cables that have an angle of 120 degrees to each other. The dynamic response of multi-segment catenary mooring line with different buoys radiuses and different positions along the cables were investigated. The full-scale platform was modeled in ANSYS-AQWA software and the simulations are performed in harsh offshore. The tension, strain, anchor uplift, cable uplift for different buoy radiuses and its position along cable are presented and discussed. Moreover, platform motions at three directions (surge, heave and pitch) are also analyzed. It is concluded that by correct selection of the buoy volume and position along cable, the tension of the cable may be reduced up to 45%. By incorrect selection of the buoy, the results will cause adverse effects.

To accurately analyze and evaluate the comparison and selection of multi-index and multi-route highway route schemes and address the disadvantages of traditional scheme evaluations, we focus on the economic costs of construction and improve on previous qualitative and quantitative analysis. A comprehensive weight and intelligent selection algorithm are introduced into the optimization of highway route schemes. This paper presents an evaluation index system for highway route schemes based on the full life cycle and considering technology, the ecological environment, the social environment and the economy. We propose an evaluation system for highway route schemes based on a comprehensive weight. Additionally, an optimization method for highway route schemes based on the TOPSIS model is studied. Finally, the optimal highway route scheme is obtained by calculation. According to the results of the research, the construction of evaluation indexes directly influences the results of the scheme evaluation. When established operations, management and maintenance indexes are based on the full life cycle, the evaluation results are more accurate. In addition to avoiding the defects of a single weighting method, the comprehensive weight vector uses subjective data as well as expert opinion. In addition, the comprehensive weight vector introduces a preference coefficient so that analysers can determine a scheme based on the accuracy of subjective and objective information and requirements. This method uses a large number of evaluation populations to evaluate schemes, and the result is more objective.

Under a microgrid based (bottom-up) restoration strategy, considering a disaster related outage, the local generation is required to energize and supply the unaffected part of the network. Considering 100% renewable generation, only hydro based generation systems, if well equipped, can be able to blackstart and re-energize the network. Wind Energy Conversion Systems (WECSs) have been restricted to the latter stages of restoration due to their source intermittency and non-dispatchability and in order for them to participate in the initial restoration stages, voltage and frequency support auxiliary devices are required. This paper investigates the capability of a hybrid windfarm to participate in the initial stages of restoration similar to a conventional blackstart unit: Re-energization of the various network components and pick up of load. The auxiliary equipment in this case is a dump load to absorb excess power produced by the windfarm and a synchronous condenser to provide a stable voltage reference required for normal operation of the WECS. Firstly, the nominal range of operation is determined with an additional pitch control mode linking the dump load power to individual WECSs introduced for frequency control. Flicker and harmonics are investigated in determination of the hosting capacity. Studies are undertaken to investigate energization of transformers, underground cables, overhead lines and other non-blackstart units (including other WECSs). Consideration is given to Type 1 and Type 3 WECSs to investigate the capability of a non-inverter and inverter based WECS. MATLAB/Simulink has been used as the simulation platform due to its modelling flexibility.

Deep reinforcement learning (DRL) algorithms are rapidly making inroads into fluid mechanics, following the remarkable achievements of these techniques in a wide range of science and engineering applications. In this paper, a deep reinforcement learning (DRL) agent has been employed to train an artificial neural network (ANN) using computational fluid dynamics (CFD) data to perform active flow control (AFC) around a 2-D circular cylinder. Flow control strategies are investigated at a diameter-based Reynolds number Re_D = 100 using advantage actor-critic (A2C) algorithm by means of two symmetric plasma actuators located on the surface of the cylinder near the separation point. The DRL agent interacts with the computational fluid dynamics (CFD) environment through manipulating the non-dimensional burst frequency (f+) of the two plasma actuators, and the time-averaged surface pressure is used as a feedback observation to the deep neural networks (DNNs). The results show that a regular actuation using a constant non-dimensional burst frequency gives a maximum drag reduction of 21.8 %, while the DRL agent is able to learn a control strategy that achieves a drag reduction of 22.6%. By analyzing the flow-field, it is shown that the drag reduction is accompanied with a strong flow reattachment and a significant reduction in the mean velocity magnitude and velocity fluctuations at the wake region. These outcomes prove the great capabilities of the deep reinforcement learning (DRL) paradigm in performing active flow control (AFC), and pave the way toward developing robust flow control strategies for real-life applications.