In-place analysis for offshore platforms is essentially required to ensure the structural integrity of platform components under extreme environmental conditions. The pile soil interaction is of great concern in structural behaviour of jacket-type fixed offshore platforms. Numerical modelling of a case-study platform with soil-pile-jacket-structure interaction is developed, the pile response demands in terms of lateral displacement and maximum bending moment and shear force, as well as soil reaction are investigated. The topsoil layers have important effects on the responses of the platform and supporting piles. A decrease in the upper soil layers’ resistance leads to higher lateral displacement responses at platform base and a decrease in the shear force and bending moment along the pile shaft. The response results of the soil-structure interaction model of the jacket foundation, confirm that the flexible foundation model simulation is necessary to estimate the loads and response demands of the offshore platform well.

Offshore platforms in seismically active areas must be designed to survive in the face of intense earthquakes without a global structural collapse. This paper scrutinizes the seismic performance of a newly designed and established jacket type offshore platform situated in the entrance of the Gulf of Suez region based on the API-RP2A normalized response spectra during seismic events. A nonlinear finite element model of a typical jacket type offshore platform is constructed taking into consideration the effect of structure-soil-interaction. Soil properties at the site were manipulated to generate the pile lateral soil properties in the form of load deflection curves, based on API-RP2A recommendations. Dynamic characteristics of the offshore platform, the response function, output power spectral density and transfer functions for different elements of the platform are discussed. The joints deflection and acceleration responses demands are presented. It is generally concluded that consideration of the interaction between structure, piles and soil leads to higher deflections and less stresses in platform elements due to soil elasticity, nonlinearity, and damping and leads to a more realistic platform design. The earthquake-based analysis for offshore platform structure is essential for the safe design and operation of offshore platforms.

To mitigate the trade-off between gain and bandwidth of CMOS multistage amplifiers, a receiver front-end (FE) that employs a high-gain narrowband transimpedance amplifier (TIA) followed by an equalizing main amplifier (EMA) is proposed. The EMA provides a high-frequency peaking to extend the FE’s bandwidth from 25% to 60% of the targeted data rate (fbit). The peaking is realized by adding a pole in the feedback paths of an active feedback-based wideband amplifier. By embedding the peaking in the main amplifier (MA), the front-end meets the sensitivity and gain of conventional equalizer-based receivers with better energy efficiency by eliminating the equalizer stages. Simulated in TSMC 65 nm CMOS technology, the proposed front-end achieves 7.4 dB and 6 dB higher gain at 10 Gb/s and 20 Gb/s, respectively, compared to a conventional front-end that is designed for equal bandwidth and dissipates the same power. The higher gain demonstrates the capability of the proposed technique in breaking the gain-bandwidth trade-off. The higher gain also reduces the power penalty incurred by the decision circuit and improves the sensitivity by 1.5 dB and 2.24 dB at 10 Gb/s and 20 Gb/s, respectively. Simulations also confirm that the proposed FE exhibits a robust performance against process and temperature variations and can support large input currents

The integration of optical receivers in nanoscale CMOS technologies is challenging due to less intrinsic gain and more noise compared to SiGe BiCMOS technologies. Recent research revealed that low-noise, high-gain, and low-power CMOS optical receivers can be designed by limiting the bandwidth of the front-end followed by equalization techniques that benefit from good switching characteristics offered by CMOS technologies. In this tutorial brief, the operation of decision-feedback equalization, feed-forward equalization, and continuous-time linear equalization is reviewed in the context of high baud-rate 2-PAM and 4-PAM modulation. Recent advances and techniques in 4-PAM optical receivers are reviewed and compared in terms of speed, sensitivity, bandwidth, and efficiency.

It is frequently essential to add rejuvenators to recycled mixtures comprising reclaimed asphalt pavement (RAP) to increase their performance. In this research, CR was desulfurized using WEO to produce a compound rejuvenator. The asphalt mixes containing 100% RAP binder were modified and rejuvenated with 0%, 3%, 6%, 9%, and 12% WEO-CR. The performance of the HMA samples were assessed using the Marshall stability-flow test, indirect tensile strength (ITS) test, and wheel-tracking device. The results showed that using a 9% WEO-CR rejuvenator restores the physical properties of the aged binder. In addition, the findings revealed that adding 100% RAP binder to the asphalt mixtures increased the tested properties of HMA samples; however, for the long-term performance of HMA, the aged binder may adversely affect the performance of the HMA mixture. Therefore, the addition of the WEO-CR rejuvenator was found to improve the overall performance of the mixture which improved the physical and chemical properties of the asphalt binder and enhanced the mechanical performance of HMA compared to the control mixture.

Temperature control is a critical factor in PCR for efficient DNA amplification. The main aim is to achieve tight control and high rate of heating and cooling for a portable, cost-effective PCR device. This speed depends on reduction of the thermal mass of the PCR heating part. The common methods used to decrease the device's thermal mass or heating/cooling time are to improve desirable device structural design and to choose a better heating and cooling mechanism with robust controller. Increasing the thermal mass provides a good temperature distribution on the heater surface, but it delays the heat transfer. Therefore, removing thermal mass makes the controller struggle to provide a high temperature uniformity distribution on Peltier surface. In this paper, we provide a cost-effective PCR heating/cooling system using Peltier element. This system is controlled using adaptive FLC with bang-bang as a hybrid 

Particle Swarm (PSO) and Bacterial Foraging (BF) Optimizers are two widely used optimization
techniques. A proper combination of these two algorithms would improve their search
capability while minimizing their shortcomings, such as parameter dependency and premature convergence.
This paper presents a hybrid optimization algorithm that combines PSO and BF
(HPSBF) to ensure security and the system’s stability following faults and disturbances. The formulated
objective function is claimed to be innovative and straightforward.
The set objectives are to minimize the dropped load by shedding relays while maximizing the lowermost
swing frequency. The optimal operation of Under-Frequency Load-Shedding (UFLS)
Relays is driven by the HPSBF technique as a bounded optimization with bounds representing
the limits of the system’s state variables. The viability of the HPSBF is verified against
conventional-, PSO-, and BF-UFLS approaches. The standard IEEE 9-bus and IEEE 39-bus systems
are exploited to examine the response of the developed UFLS techniques. The tested systems
are exposed to various operational scenarios such as loss of power plants and a considerable abrupt
load increase. The DigSilent power factor software is used to simulate the IEEE 9- and 39-bus systems,
while MATLAB code was implemented to obtain optimal operational points for the implemented
algorithms. The HPSBF accomplished the uppermost swing frequency and the
lowermost quantity of the disconnected load. Furthermore, the computational times of HPSBF
are equivalent to those of the PSO.

This paper presents a design of voltage controller for  standalone self-excited induction generator (SEIG) driven by a variable speed wind turbine. Particle swarm optimization (PSO) algorithm has been applied to predict the value of capacitance necessary to maintain the generator terminal voltage at a preset value under specific load and speed conditions. The proposed model completely avoids the tedious and erroneous manual work of segregating the real and imaginary components of the complex impedance of the machine for deriving the specific model for each operating modes. The use of FACTS device called static synchronous compensator (STATCOM) to control the reactive power and keep the output voltage of standalone SEIG at rated value under normal and abnormal conditions such as, de-excitation due to over-loading under balanced and unbalanced load conditions, symmetrical fault, and variation of wind turbine speed is presented. The dynamic model of the system is developed and a methodology to decide  the  ratings  of STATCOM  components  such  as  the  DC  bus  capacitor,  AC  side  filter  and insulated gate  bipolar transistors  (IGBT)  is introduced. The proposed system is modeled and simulated using Matlab/Simulink software program to examine the dynamic characteristics of the system with proposed control strategy. Dynamic simulation results demonstrate the effectiveness of the proposed STATCOM voltage controller.

The Micro energy grids (MEGs) are expected to play a vital role in designing smart grids because it reduces energy expense and gas emissions by utilizing renewable and non-renewable distributed energy resources. However, currently, problems exist concerning the design and utilization of MEGs. In our previous work , we assume that the distributed generators put the priority on electricity production and the surplus/deficient electricity can be sold to/bought from the utility grid. The surplus/deficient heat can be stored/or supplied by thermal storage tank, boiler and/or electrical heater. In this study the distributed generators put the priority on heat production and the deficient heat can be supplied by the boiler and/or electrical heater. Multi-objective particle swarm optimization (MOPSO) algorithm is used to specify the optimal combination of components and optimal sizing of all MEG components for minimization of the total system cost and total carbon dioxide emissions simultaneously.