Affect System Performance Research Articles

Scalable Load Balancing in the Presence of Heterogeneous Servers

In large-scale computer systems, deciding how to dispatch arriving jobs to servers is a primary factor affecting system performance. Consequently, there is a wealth of literature on designing, analyzing, and evaluating the performance of load balancing policies. For analytical tractability, most existing work on dispatching in large-scale systems makes a key assumption: that the servers are homogeneous, meaning that they all have the same speeds, capabilities, and available resources. But this assumption is not accurate in practice. Modern computer systems are instead heterogeneous: server farms may consist of multiple generations of hardware, servers with varied resources, or even virtual machines running in a cloud environment. Given the ubiquity of heterogeneity in today's systems, it is critically important to develop load balancing policies that perform well in heterogeneous environments. In this paper, we focus on systems in which server speeds are heterogeneous.

Intelligent Secure Networking in In-band Full-duplex Dynamic Access Networks: Spectrum Management and Routing Protocol

Recent developments in self-interference cancellation (SIC) techniques have made in-band full-duplex (IBFD) transmission systems possible. IBFD technology can enhance, or theoretically speaking double, spectrum utilization by allowing simultaneous transmission and reception using the same radio-frequency channel. Integrating the IBFD technology in cognitive radio (CR) systems can further enhance spectrum utilization and provide huge spectrum opportunities for efficient deployment of next-generation multi-hop wireless systems. Routing protocols for typical CR networks (CRNs) assume that CR users are equipped with half-duplex receivers. Limited number of protocols have been designed for FD-based CRNs. However, these protocols do not account for security threats in wireless environment, which could significantly affect system performance. In this paper, we develop a security-aware intelligent routing scheme that aims at mitigating the effects of jamming attacks on IBFD CRNs. This scheme considers the unique characteristics of the CRN environment while being IBFD-aware. Specifically, it considers the primary user’s channel-availability time, channel quality and jamming strategy. For a source-destination pair, our protocol collects a set of loop-free paths. Then, it attempts to assign channels for the hops along each path with the goal of achieving the highest Probability of Success (PoS) of each path. The per-hop channel selection for each path is derived as an optimization problem, for which sub-optimal solutions are found using a polynomial-time approximate method. Based on the computed channel assignment and PoS over each path, the path with the highest PoS between the source and destination is selected. Simulation results show that our secure-aware IBFD-based routing can significantly mitigate the jamming effects on CRN performance by improving the packet-delivery ratio, and consequently network throughput compared with existing FD-based routing protocols.

Effects of photovoltaic/thermal (PV/T) control strategies on the performance of liquid-based PV/T assisted heat pump for space heating

Hybrid solar PV/T system control strategy plays an important role not only in PV/T system energy gain but also in the energy consumption of PV/T assisted heat pump systems. However, no research has been carried out regarding the effect of PV/T control strategy on the performance of PV/T assisted heat pump systems. It remains unknown how the key parameters of the PV/T system control strategies affect system performance, and it has not yet been established which PV/T system control strategy is better. To study the effects of the commonly used PV/T system control strategies on the performance of liquid-based PV/T assisted heat pumps, models of liquid-based PV/T assisted heat pumps with three different PV/T system control strategies were developed using combined platforms of EES and TRNSYS. Based on the models, the effects of the key parameters for each of these PV/T system control strategies on the PV/T system energy gain, overall energy consumption, average heat pump coefficient of performance (COP), and the overall system performance were presented, and the comparison of the three PV/T control strategies was performed. The results showed that a much larger PV/T pump size was needed for the outlet temperature control strategy to achieve a roughly equivalent performance to the other two control strategies.

Activated sludge diffusion for efficient simultaneous treatment of municipal wastewater and odor in a membrane bioreactor

Although activated sludge (AS) diffusion is promising for odor control, disagreement still exists on its treatment efficiency of varying odorants, and its microbiological mechanisms remain largely unknown. Herein, we investigated the deodorization efficiency, wastewater treatment performance, and microbiological and ecological effects of AS diffusion in two in situ membrane bioreactors (MBRs). AS diffusion removed ≥ 94.7% of H2S and 100% of NH3, while other odorants were released at low concentrations. The odor-diffused system also achieved appreciable wastewater treatment performance (effluent phosphate at 0.13 ± 0.12 mg/L, COD at 12.1 ± 1.8 mg/L, and total nitrogen at 5.9 ± 1.8 mg-N/L), while membrane fouling was mitigated. Notably, influent wastewater substrates and nutrients, other than MBR system settings, significantly affected system performance, main functional taxa and bacterial community dynamics. Ecological null model and network analysis revealed that odor diffusion strengthened the niche-based deterministic processes (i.e., environmental selection) and caused more negative and intense microbial interactions. Organics competition was enhanced, and some hydrolytic bacteria correspondingly became keystone taxa in the odor-diffused system. The findings provide valuable guidance in establishing efficient AS systems for integrated wastewater and odor treatment.

Design and off-design performance comparison of supercritical carbon dioxide Brayton cycles for particle-based high temperature concentrating solar power plants

Concentrated solar power (CSP) plants using dense particle suspension as heat transfer fluid and particles as the storage medium are considered as a promising solution to provide the high temperature required for the supercritical carbon dioxide (S-CO2) Brayton cycle. During plant operation, variations in the heat transfer fluid temperature and ambient temperature would significantly affect system performance. Determining the suitable S-CO2 Brayton cycle configuration for this particle-based CSP plant requires accurate prediction and comprehensive comparison on the system performance both at design and off-design conditions. This study presents a common methodology to homogeneously assess the plant performance for six 10 MW S-CO2 Brayton cycles (i.e. simple regeneration, recompression, precompression, intercooling, partial cooling and split expansion) integrated with a hot particles thermal energy storage and a dry cooling system. This methodology includes both design and off-design detailed models based on the characteristic curves of all components. The optimal design for each thermodynamic cycle has been determined under the same boundary design constrains by a genetic algorithm. Then, their off-design performances have been quantitatively compared under varying particle inlet temperature and ambient temperature, in terms of cycle efficiency, net power output and specific work. Results show that the variation in ambient temperature contributes to a greater influence on the cycle off-design performance than typical variations of the heat transfer fluid temperature. Cycles with higher complexity have larger performance deterioration when the ambient temperature increases, though they could present higher peak efficiency and specific work at design-point. In particular, the cycle with maximum efficiency or specific work presents significant changes in different ranges of ambient temperature. This means that for the selection of the best configuration, the typical off-design operation conditions should be considered as well. For integrating with high-temperature CSP plants and dry cooling systems, the simple regeneration and the recompression cycles are the most suitable S-CO2 Brayton cycle configurations due to their fewer performance degradations at ambient temperatures above 30 °C, which is a frequent environmental condition in sunny areas of the world.

Experimental Study of A LiCl-H2O Bubble Pump Solar Absorption Cooling System

An experimental test rig is constructed and designed according to the results obtained from a thermodynamics model solves by EES software assuming a constant generator, condenser, absorber, and evaporator temperatures to study a bubble pump’s performance solar absorption cooling system. The whole system consists of a parabolic trough solar collector, a generator, a condenser, an absorber, an evaporator, and a cooling water system. The used PTC area is designed according to the quantity of thermal energy required to operate the bubble pump cooling system and the minimum solar radiation incident at Kufa city (Najaf/Iraq), which lies on (32°N and 44°E). A modification is added to the collector receiver to ensure water exposure to solar energy for a longer time. The weather features that affected system performance like the solar radiation incident and the ambient temperature are measured for each test. The maximum recorded receiver temperature is 122 °C without water flow, and it is reached to 90.5°C as a maximum in case of water flow through the receiver. The water in the storage tank is reached to 89 C as a maximum. The collector thermal efficiency reaches its maximum value of 69.2 % for a water flow rate of 0.3315 kg/s, while the maximum efficiency at 0.189 kg/s is 68.3%. The maximum recorded generator temperature is 87°C, and at the same test, a minimum evaporator temperature of 17°C is obtained at an ambient temperature of 46.8 °C.

Research and design of tripod-shaped UWB antenna for GPR

In recent years, GPR (Ground Penetrating Radar) has developed rapidly and has played an important role in many fields. As a key part of GPR, the antenna directly affects system performance. A suitable antenna can greatly improve the detection results. To this end, this paper introduces the design of GPR tripod-shaped ultra-wideband antenna based on bow tie antenna. The working bandwidth of the antenna is widened by means of structural loading with truncation as the main part and circular slot at the end of the antenna. Antenna optimization and simulation were performed using ANSYS HFSS (High Frequency Structure Simulator), and the effects of antenna arm truncation length on antenna performance were discussed. Simulation results show that the designed antenna has an operation bandwidth of 700MHz ~ 2GHz and good directionality. It is a miniaturized ultra-wideband antenna suitable for shallow underground pipeline detection.

Comprehensive analysis of distributed energy resource penetration and placement using probabilistic framework

Integration of distributed energy resources (DERs) affect system performance in multitude of ways such as reliability, losses and voltage profile. Thus, increasing distributed energy resource penetration necessitates impact assessment particularly when DERs comprise of stochastic RES based distributed generators (DGs) and storage system. This paper presents a formulation for the analysis of DER penetration and placement on system losses and voltage profile in probabilistic framework. Penetration level has been defined, giving due consideration to stochastic behaviour of RES based distributed generators. The work presented incorporates analysis and consideration of two important factors in placement problem, that is, intermittent nature of RES based distributed generators and dual nature of storage units. In order to account for uncertainties inherently present in RES, probabilistic load flow has been used in this work. Placement problem is solved for three different penetration levels, that is, 20%, 40% and 60% using utterfly particle swarm optimisation. The impact of seasonal effect on system losses and voltage profile in correlation with penetration levels has also been investigated. Results provide useful insights for identification of optimum penetration level.

Resilience of food, energy, and water systems to a sudden labor shortage.

Past research studies have acknowledged the role of resilience in policies and decisions to address disruptive events and proposed frameworks to measure it. The scope and diversity of these unwanted events highlight the need to evaluate the resilience of a system to a specific disruptive circumstance. The broad scope and generic form of the previous studies limit their usefulness as a practical tool for analyzing the factors affecting system performance. To overcome this problem, we are only focusing on the behavior of systems that produce, distribute, and deliver food, energy, and water (FEW) during and after the occurrence of a sudden shortage of labor. Resilience metrics are first developed to measure the resilience of the FEW systems. Next, the performance levels of the FEW systems are clearly defined based on the FEW demands that are not served. Third, the labor intensity of FEW productions is calculated to assess the impact of a sudden labor shortage. This study recognizes the complex interdependencies among the FEW systems and, thus, aims to examine their resilience as a single system. Last, the labor shortage in the USA caused by the COVID-19 pandemic is chosen as a use case to measure the system performance and role of adjustments on the FEW systems. The results show that a labor shortage can significantly impact the FEW system performance, possibly due to the high energy dependency of food and water systems and the high cost of storing energy. Also, the current food system has shown more resilience to a sudden labor shortage compared to the energy and water systems because of the availability of various food alternatives to meet the demand for each food category.

Analysis of Human Factors in Ship-to-ship Collision Accident: A Semi-quantitative Approach Based on Network Theory

As long as human beings operate the ship, human factors always have a substantial contribution to ship operation success and failure. Thereby, a study related to human factors, especially about the officer on board, is essential to create better maritime transportation. This research proposed the semi-quantitative analysis to determine how human factors are involved in a ship-to-ship collision using a network theory perspective. The study was conducted by describing the dependency amongst human activities (officer onboard) during ship-ship encounters. The ship-to-ship encounters model has been done in an undirected graph consisting of nodes and arcs. Through the vertex performance rate, system performance could be evaluated. Hence this research aimed to define the weight evolution when the unintended action emerges in a node and distributes its weight to its couplings. In conclusion, the network model for ship-to-ship collision accidents can describe the weight spreading process among functions and how it affects system performance then causes an accident.

전기자동차 모터 유냉식 방열성능 향상을 위한 열전달 해석 및 최적화

This paper presents the heat transfer analysis of the electric vehicle motor and optimization of an operating parameter for improving the performance of the motor with an oil cooling system. The homogeneous multi-phase flow model in commercial software, ANSYS CFX, is applied to solve the flow of mixture, including oil and air. We mainly focus on the influence of operating (oil level) and driving conditions (roll and pitch angles) on the cooling system. Several CFD simulations are performed with various input parameters (oil level, roll, and pitch angles) generated from the Latin Hypercube Sampling method. Based on the CFD results, we built a Polynomial Chaos Expansions based surrogate model to predict the temperature distribution, maximum temperature, and torque loss, which respond to the input parameters. Sensitivity analysis indicates that the oil level significantly affects system performance (maximum temperature and torque loss). Finally, the optimal range of oil level is estimated, considering the maximum allowable temperature of the motor.

Effective modeling of high-energy laboratory-based x-ray phase contrast imaging utilizing absorption masks or gratings

Model refinements for the edge illumination x-ray phase contrast imaging method have been developed to improve simulation accuracy for high energy, polychromatic beams. High-energy x rays are desirable in imaging due to their penetrative power and, for biological samples, their lower dose deposition rate. Accurate models of such scenarios are required for designing appropriate imaging systems and to predict signal strength in complex settings such as clinical imaging or industrial quality assurance. When using optical components appropriate for high-energy x rays in a non-synchrotron setting, system performance was observed to deviate from that predicted by existing models. In this work, experimental data utilizing increasing thicknesses of a known filter material are used to illustrate the limitations of existing models and as validation for the new modeling features. Angular filtration of the cone beam was observed to be the most significant effect; however, specific features of the source and detector are also shown to affect system performance. We conclude by showing that a significantly improved agreement between experimental and simulated data is obtained with the refined model compared to previously existing ones.

Impulse Noise Suppression based Iterative Hybrid Nonlinear in Power Line Communication

In power line orthogonal frequency division multiplexing (OFDM) communication systems, the presence of impulse noise can seriously affect system performance. One of the conventional solutions is to perform a mixed nonlinear processing on the time domain signal at the receiving end before performing subsequent OFDM demodulation. Therefore, this thesis studies an improved method based on iterative elimination of nonlinear distortion. Firstly, the received OFDM signal is subjected to hybrid nonlinear processing in the time domain. Secondly, the nonlinear distortion introduced by the time domain nonlinear processing is reconstructed by the symbols initially detected in the frequency domain, and the reconstruction accuracy is improved by iteration. Finally, the reconstructed nonlinear distortion is subtracted from the output of the hybrid nonlinear processing unit. The simulation results show that compared with the traditional hybrid nonlinear method, the performance of the proposed algorithm is much better than that of the traditional algorithm.

Exploring the Impact of COVID-19 Lock-down on Public Spaces through a Systems Modelling Approach

This paper offers a Human Factors and Ergonomic & Sociotechnical Systems (HFE & STS) methodology to assist in the exploration and description of COVID-19 lockdown impacts on public spaces in Queensland, Australia. The approach utilises an existing - before COVID - systems model of an archetype public space to identify activities that were restricted in public space, and how such restrictions affect system performance. First an overview of the HFE & STS system modelling approach, Cognitive Work Analysis, is provided and we present the systems model of an archetype public space. Next, the range of lockdown restrictions on public space activity are identified in the model and the system's implications on community and individual wellbeing are explored. In conclusion, the necessity for new activities and functions of public space, post COVID-19, are reflected upon and considered from a systems standpoint.

Lane Departure Warning Estimation Using Yaw Acceleration

Abstract Lane departure collisions have contributed to the traffic accidents that cause millions of injuries and tens of thousands of casualties per year worldwide. Due to vision-based lane departure warning limitation from environmental conditions that affecting system performance, a model-based vehicle dynamics framework is proposed for estimating the lane departure event by using vehicle dynamics responses. The model-based vehicle dynamics framework mainly consists of a mathematical representation of 9-degree of freedom system, which permitted to pitch, roll, and yaw as well as to move in lateral and longitudinal directions with each tire allowed to rotate on its axle axis. The proposed model-based vehicle dynamics framework is created with a ride model, Calspan tire model, handling model, slip angle, and longitudinal slip subsystems. The vehicle speed and steering wheel angle datasets are used as the input in vehicle dynamics simulation for predicting lane departure event. Among the simulated vehicle dynamic responses, the yaw acceleration response is observed to provide earlier insight in predicting the future lane departure event compared to other vehicle dynamics responses. The proposed model-based vehicle dynamics framework had shown the effectiveness in estimating lane departure using steering wheel angle and vehicle speed inputs.

A novel design method of organic Rankine cycle system harvesting waste heat of heavy‐duty trucks based on off‐design performance

AbstractThe organic Rankine cycle (ORC) system can effectively recover waste heat from engines of heavy‐duty trucks, and is a promising method to improve the efficiency of on‐board engines. However, engine operating conditions fluctuate greatly while driving, the waste heat recovery system must often work under off‐design conditions, which significantly affects system performance. Further, different component structures can also affect the off‐design performance of the system. Thus, a novel design method of preheating organic Rankine cycle (P‐ORC) system harvesting waste heat of heavy‐duty trucks based on off‐design performance is proposed in this study. The design method includes selection of the optimal types of components and design point to optimize the comprehensive performance of the waste heat recovery system in all road conditions. In this study, different heat exchanger combinations are applied to the P‐ORC system to obtain six different design systems. According to the principle of uniform coverage, the scatter diagram of exhaust temperature and mass flow rate of the engine under real road conditions are discretized into 19 alternative design points. Each system is designed with 19 discretized design points, and a total of 114 design systems are obtained. The optimal heat exchanger combination and design point are selected based on the off‐design performance. It is concluded that a P‐ORC system using a combination of plate preheater, finned tube air cooler, and shell‐tube evaporator is the optimal system. The optimal design point number is 10, and the corresponding engine speed atis 1471 rpm, the engine torque is 474 Nm, the occurrence probability is 14.48%, the exhaust temperature is 350°C, the exhaust mass flow rate is 0.11 kg/s, and the maximum combined net power output is 4.26 kW. The results reveal that the optimal design point of the system can be selected at the design point with medium engine load and high occurrence probability. It guides the system design toward a more practical direction, so as to obtain an optimal system that could operate efficiently and recover more waste heat under the full working conditions of the engines. This novel design method can be extended for other cycle configurations.

Robust artificial noise-aided beamforming for a secure MISO-NOMA visible light communication system

Visible light communication (VLC) and non-orthogonal multiple access (NOMA) have been deemed two promising techniques in the next wireless communication networks. In this paper, secure communications in the presence of potential eavesdropper are investigated for a multiple-input single-output VLC system with NOMA. The artificial noise jamming and beamforming technologies are applied to improve secure performance. A robust resource allocation scheme is proposed to minimize the total transmit power taking into account the constraints on the quality of service requirement of the desired users and the maximum tolerable data rate of the eavesdropper, and the practical imperfect channel state information of both the desired users and the eavesdropper. The formulated non-convex optimization problem is tackled based on S-Procedure and semi-definite programming relaxation. Simulation results illustrate that our proposed resource allocation scheme can effectively guarantee communication security and achieve transmit power saving. Moreover, the height and number of LED can significantly affect system performance and the optimum LED height can be obtained for different LED numbers.

Start-up of anammox systems with different feeding patterns: System performance, microbial community and potential microbial interactions

Successful start-up of the anaerobic ammonium oxidization (anammox) system is the main challenge for its application. Two anammox biofilm systems with pulse feeding pattern (AN-P) and constant feeding pattern (AN-C) were operated, and the performance of nitrogen removal and microbial interactions among anammox bacteria, heterotrophs, and other microorganisms were investigated. The total nitrogen removal percentage reached 82% (AN-P) and 82.4% (AN-C) in 13 days and 32 days, respectively. AN-P could start up and reach steady state quicker than AN-C. Candidatus Kuenenia was the dominant functional microorganism in both reactors. Heterotrophs (Pseudomonas and Hyphomicrobium) might play important roles in nitrogen and carbon metabolisms. N-decanoyl-DL-homoserine lactone and N-dodecanoyl-DL-homoserine lactone were detected, and acyl homoserine lactone-based quorum sensing system existed in the anammox system. Complex microbial interactions, including competition, cooperation and cross-feeding co-existed in the anammox system and affected system performance.

Competing Failure Modeling for Performance Analysis of Automated Manufacturing Systems With Serial Structures and Imperfect Quality Inspection

Fierce global competition drives automated manufacturing systems (AMSs) to be increasingly complex, which poses significant challenges on performance analysis and production control. The multistage production via serial stations will lead to the propagation of failures in AMSs, which will affect system performance by triggering complex competitions among multiple failure modes. Although machine performance and product quality have been considered, very little has been done to investigate the effect of imperfect quality inspection on competing failures. Focusing on a time balance serial AMS, this article presents a new competing failure model to investigate the complex interactions among machine failures, product quality, and inspection process, which enables the characterizations of time-delayed propagation of failure, accumulation of degradation, and dynamics of states in serial AMSs. In order to further analyze the impact of competing behaviors on system performance, we have also developed decision diagram models and algorithms, which are evaluated and validated on serial AMSs with imperfect inspection, revealing the characteristic of multistate interactions. Experimental results show that the proposed methods have strong potentials for performance modeling and analysis of serial AMSs and also demonstrate general applicability for manufacturing decision making.

A Signaling Figure of Merit (s-FoM) for Advanced Packaging

In this letter, we propose a novel signaling figure of merit (s-FoM) for comparison of signaling schemes across different packaging technologies. It considers all the essential metrics that affect system performance and efficiency and combines them in a simple, easily quantifiable manner. These include energy per bit, data-bandwidth per unit shoreline, latency, length of the link, and real-estate overhead. This tool captures all the performance trade-offs and enables a fair comparison across different packaging platforms and integration schemes.