Power Consumption Variation Research Articles

Experimental and optimization research of the rack thermal environment based on the dynamic server power

Dynamic fluctuations in server power consumption significantly impact the thermal environment within the rack and the efficiency of computer room air conditioners (CRACs), necessitating thorough analysis it for safe and effective thermal management. Drawing on field experiment, this study presents an overview of the range and characteristics of variations in rack power consumption within a data center, revealing that 74.3 % of racks display periodic changes in power consumption. The change cycle has a diurnal pattern, and the dynamic changes in rack power consumption depend on the number of servers, the amount of task processing, and the nature of the customers. Subsequently, we designed the rack thermal environment experimental platform to analyze the response characteristics of the rack thermal environment to server power consumption changes and the variation rules of the thermal environment with various server layouts. The results show that a shift in server power severely affects the rack outlet temperature and is accompanied by a specific delay phenomenon. The near heat source effect, thermal buoyancy, and top heat accumulation primarily affect and form the rack thermal environment. It is recommended to place the server in the middle of the rack and with a 1U or 2U gap or uniform arrangement to create a better thermal environment. Finally, we propose three methods for optimizing the rack's thermal environment. Compared to the use of blind plates, the installation of air inlet deflectors, rear baffles, and top outlets can collectively reduce the hot spot temperature by up to 1.3 °C, 2.1 °C, and 0.4 °C, with the supply heat index (SHI) optimized at 0.184, 0.142, and 0.13. The return temperature index (RTI) was optimized at 88.99 %, 88.76 %, and 92.5 %, respectively.

A comprehensive study on the aerodynamic influence of stationary and moving obstacles on an isolated phantom DJI 3 UAV propeller

AbstractUnmanned aerial vehicle (UAV) technology is experiencing strong growth in many fields such as military and civil. When operating around obstacles and in the proximity of walls or moving objects, the UAV is constrained to thrust and power consumption variation induced by several aerodynamic effects that can lead to severe flight instability. In this paper, a methodology based on multiple reference frames (MRF) is developed and applied to computational fluid dynamics (CFD) simulations on a Phantom DJI 3 propeller to reproduce the effect of fixed and moving wall proximity on the propeller aerodynamic performances. When hovering (3000 rpm) at 0.2 m above a moving obstacle (15 m/s), the results have shown a huge decrease in the thrust by 11.3% when compared to fixed obstacle thrust. This effect, however, is reduced when the propeller is hovering at 5000 rpm and neglected at 9550 rpm. Finally, the moving obstacle had a significant impact on the propeller's aerodynamic performance, resulting in a decrease in thrust force and power consumption at low hovering rotational velocities. Especially, when the obstacle is moving at a fast speed, the UAV could properly use high rotational velocity to maintain high power loading and ensure hovering stability.

A 1.58 nJ/conversion temperature-to-digital converter with low power variations

A 1.58 nJ/conversion temperature-to-digital converter at the supply voltage of 0.7 V was designed and fabricated on the die area of 0.147 mm2 using the 90 nm CMOS technology. The sub-nA constant reference current (I ref) and the sub-nA complementary-to-absolute temperature (CTAT) current (I CTAT) are generated by employing the gate leakage currents of PMOSFETs. The current-to-frequency oscillators using those currents followed by the frequency-to-digital converter are used to produce the digital codes inversely proportional to temperatures. With this approach, the power consumption at high temperatures can be alleviated significantly. Thus, the variation of power consumption is only 70% from −10 °C to 90 °C. The conversion time is 107 ms at the RT and the noise non-limited resolution is 0.052 °C.

Low power CMOS Gm-C based low pass filter for front end neural signal processing

The sub 100 µV voltage levels and sub 100 Hz frequency range makes the processing of most popular signal electroencephalograph (EEG) for brain functionality analysis, a complex task. The low frequency content of EEG (useful signals below 70 Hz) is commonly used for diagnosis of various brain related disorders making low-pass filter (LPF) a key block in front-end processing as noise reduction and resolution enhancement is crucial for precise recovery of these information. This paper is aimed to design reduced transconductance (Gm) based low power and small area CMOS LPF with cutoff frequency (fc) around 70 Hz. The proposed design is simulated using Cadence virtuoso tool and gives cut-off frequency of 72.958 Hz with low output noise of 3.0609 µV/√Hz and power consumption of 264.060 nW at operating voltage of 0.4 V. The simulation results show linearity of performance over -40 to 100 °C. Layout of circuit takes up area of 86.74×81.21 µm and post layout simulation shows 5% variation in power consumption as compared to pre layout simulations.

Microheater Topology for Advanced Gas Sensor Applications with Carbyne-Enriched Nanomaterials

The response characteristics of carbyne-enriched surface-acoustic-wave (SAW)-based gas sensors utilizing meander and rectangular microheater topologies were investigated to assess their desorption and recovery properties. Comparative analysis of contact resistance and interface capacitance before and after heating revealed minimal deviation in contact resistance, signifying strong thermal stability in the carbyne-enriched layer. However, the interface capacitance varied with the microheater size. Our analysis reveals that a small meander microheater configuration (line width: 300 µm) facilitates efficient sensor recovery at ethanol concentration measurements in the range of 180–680 ppm, maintaining a low deviation in time delay across different concentrations (~2.3%), resulting in a narrow hysteresis and linear sensor response. Conversely, the large meander microheater (line width: 450 µm) and rectangular dense microheater induce irreversible changes in the sensing structure, leading to a widened hysteresis at higher concentrations and increased power consumption. Recovery patterns display substantial deviations from initial values at different concentration levels. Higher concentrations exhibit broader hysteresis, while lower concentrations show narrower hysteresis loops, compared to the small meander microheater. The study offers insights into desorption rates, power consumption variations, and recovery behaviors related to different microheater configurations. It demonstrates the importance of microheater topology selection in tailoring recovery properties and response characteristics, contributing to the advancement of carbyne-based sensor technology.

Modified Decoupled Sense Amplifier with Improved Sensing Speed for Low-Voltage Differential SRAM

A modified decoupled sense amplifier (MDSA) and modified decoupled sense amplifier with NMOS foot-switch is proposed for improved sensing in differential SRAM for low-voltage operation at the 22-nm technology node. The MDSA and MDSANF both offer notable improvements to read delay over conventional voltage and current sense amplifiers. At an operating voltage of 0.8 V, the MDSA exhibited a reduced delay of 28.6%, 41.79%, 37.74%, and 30.94% compared to modified clamped sense amplifier (MCSA), double tail sense amplifier (DTSA), modified hybrid sense amplifier (MHSA), and conventional latch-type sense amplifier (LSA), respectively. Similarly, the MDSANF demonstrated a delay reduction of 26.13%, 39.78%, 35.58%, and 28.55% over MCSA, DTSA, MHSA, and LSA, respectively. To validate the performance, the MDSA and MDSANF are evaluated using the variation in delay and power consumption across various supply voltages, process corners, input differential bit line voltage (ΔV BL ), bit line capacitance (C BL ), and the sizing of decoupling transistors. Monte Carlo simulations were conducted to analyse the impact of voltage threshold variations on transistor mismatch which leads to an increased occurrence of read failures and a decline in SRAM yield. The performance analysis of various voltage and current sense amplifiers is presented along with MDSA and MDSANF. Area consideration for selection of sensing scheme is important and as such layout of MDSA and MDSANF was performed conforming to the design rules and estimated area for MDSA is 0.297 μm 2 whereas MDSANF occupies 0.5192 μm 2 .

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The power consumption of pumps in a hydrothermal heat pump system is important from environmental and economic points of view. In this study, an office building and a hydrothermal heat pump system were modeled by the TRNSYS 18 program, and building load and energy consumption were simulated. The variation in pump power consumption was analyzed according to changes in the design parameters for heat source-side piping in the heat pump system. The system consisted of a heat pump, pumps, heat exchangers, and a fan coil unit. The flow rate and power consumption of the pumps and the fan were calculated by the system operating time to satisfy the building load. A simulation was performed by changing the horizontal distance to the hydrothermal source from 200 m to 1000m, vertical height differences from 2 m to 10 m, and pipe diameters from 0.1 m to 0.3 m. The intake pump (Pump A) power consumption ratio to total power consumption increased from 6.5% to 11.7% with increases in the distance to the hydrothermal source. The simulation results showed that the pipe diameter had a great influence on the power consumption of the pump.

4E Transient Analysis of a Solar-Hybrid Gas-Turbine Cycle Equipped with Heliostat and MED

The current study investigates a cogeneration cycle of power and freshwater integrated with a solar system. The solar system is of the heliostat type, which is considered to preheat the inlet air in the combustion chamber of a 25-MW gas turbine. The waste heat of the turbine output stream is used to produce freshwater. Parameters such as the ambient temperature and solar irradiance significantly affect the system’s performance; hence, all analyses, including those pertaining to energy, exergy, economics, and environment, were conducted transiently, with a one-hour time step throughout the year so that the impacts of these effective parameters could be examined. Besides the analysis assuming a constant mass flow rate for the air entering the compressor, the calculations were repeated with the assumption of a constant volumetric flow rate to evaluate the cycle in the same conditions as those of natural gas power plants. Given the constant volumetric flow rate, for every 10-degree increase in temperature, the compressor power consumption decreased by approximately 2%. Moreover, a sensitivity analysis of the cycle performance in terms of ambient temperature was performed, and the corresponding results are presented. Finally, some correlations are presented to estimate variations in compressor power consumption and net turbine power due to temperature variations. The results demonstrate that in Bushehr, Iran, every one-degree increase in ambient temperature leads to an approximately 0.67 percentage decrease in net-generated power. In the end, the performance of the cycle was investigated under climatic conditions and solar irradiation intensities in several cities in Iran and some cities in different countries in which heliostat power plants have already been established. The results obtained in these cities were compared; it was concluded that the lowest annual cost of electricity generation is related to Isfahan in Iran, which reduces the cost of electricity generation by more than 20% (2.32 Cents/kWh) compared to the base cycle.

Optimization of the electricity consumption behaviors of users under uncertain electricity prices and consumption patterns

Real-time electricity prices and customer demands are inextricably linked in the smart grid environment. For the purpose of reducing grid load peaks, enhancing grid security, and optimizing customers’ electricity bills, it is critical to model dynamic real-time electricity prices and flexible customer requests, along with providing an optimized plan to guide users’ decisions regarding the use of household appliances and quantify their needs. The solution to this problem, however, is not straightforward due to the following factors. Firstly, the real-time electricity price is constantly changing, so it must be estimated from grid data associated with it. Furthermore, there are often some variations in the actual power consumption of appliances due to the uncertainty of human behavior, the characteristics of appliances, and the influence of the environment. In addition, when optimizing, serious problems such as tripping and circuit overload must be taken into account. Therefore, considering random electricity prices and random electricity consumption, in the paper, we present the models to simulate real-time changes in electricity prices and energy consumption behaviors, as well as a method to help users optimize their use of household appliances and quantify their requirements with lower electricity cost. By analyzing the experimental results, we demonstrate that our work can be used to provide a scheduling scheme for appliances that minimizes electricity costs and reduces grid pressure.

Efficient transient thermal analysis of chiplet heterogeneous integration

Thermal issue has significant effect on the reliability and performance of integrated circuits with the increase of integrated density, especially for 2.5-D and 3-D heterogeneous integration packaging systems. In this paper, a new highly efficient 3-D transient thermal distribution model has been constructed to capture the heat conduction behavior of multiple heat sources for chiplet heterogeneous integration (CHI) by improving the alternating direction implicit finite difference method (ADI-FDM). Firstly, a new floating optimization algorithm (FOA) of coefficient matrix assignment of heat conduction equation and a new boundary treatment utilizing virtual points are proposed to modify the ADI-FDM and improve the model efficiency of thermal analysis. Furthermore, a universal equivalent thermal conductivity model is also built up to describe the design features of through silicon via (TSV), bump and redistribution layer structures, which can enhance the flexibility of FDM-based thermal simulator. Compared with previous finite element analysis results, the present FOA-accelerated thermal model can not only obtain an accurate simulation result of temperature profile, but also give a simulation efficiency of 3.74 times faster than Douglas-Gunn approach for the coefficient matrix assignment. Finally, the effect of power consumption variation and the floorplaning effects of chiplets, TSVs and bumps on the temperature distribution are investigated in detail by utilizing the present FOA-based thermal solver. The simulated results of the present work demonstrate the viability and computational efficiency for temperature field optimization and indicate that the new proposed simulator is helpful in thermal analysis of packaging structures and can be adopted to assist in physical design optimization of 2.5-D CHI or 3-D heterogeneous stacked chips.

Programmable Electronic Load Prototype for the Power Quality Analysis of an Experimental Microgrid

Microgrids have been widely adopted in many countries because they provide more reliable electricity service to those users connected to the power grid. These systems comprise various power sources, energy storage devices, and loads. However, detailed studies require considering linear and nonlinear loads, which are now used in this type of network. In addition, experimental tests require devices that emulate loads, represent different topologies, and construct assemblies for better identification, validation, and theoretical approximations of the power grid. Therefore, this paper presents a programmable electronic load to emulate linear and nonlinear loads of a microgrid, based on the control of a single-phase voltage source converter that considers rectification and power dissipation stages. Furthermore, a control stage allows power consumption variations, controlling the current demanded by the load, according to the reference current waveform programmed through a user interface. A synchronous reference frame phase-locked loop is implemented on a microcontroller. Thus, the programmable electronic load enables studying power quality in microgrids. Finally, the operation of the programmable electronic load is validated through experimental and simulation tests, considering different case studies.

Simulación de un sistema de comunicaciones utilizando la tecnología BN-IoT (Narrow Band–Internet of Things)

Narrow Band Internet of Things (NB-IoT) was implemented by 3GPP in Release 13,14 y 15, as an IoT (Internet of Things) connectivity solution. Because, in addition to offering coverage improvements, NB-IoT has shown to be compatible across mobile or non-mobile virtual network carriers, locations, and providers. Additionally, it provides end-to-end Quality of Service (QoS) assurances and uses licensed spectrum to improve reliability and performance. This article proposes a study of NB-IoT technology, fundamental aspects of NB-IoT, its architecture, frequency bands, access protocols, physical layers, and quality of service metrics. Also, presents simulations of the energy consumption of NB-IoT devices during data transmission in three scenarios using MATLAB, as well as the parameters required for these simulations. Finally, the results obtained are presented based on path losses, battery lifetime versus physical channels, coverage classes, data rate on links (uplink and downlink), and packets sent per day, these show a variation in power consumption and battery lifetime performance in the devices.

An Efficient Secure Cryptography Scheme for New ML-based RPL Routing Protocol in Mobile IoT Environment

Internet of Things (IoT) offers reliable and seamless communication for the heterogeneous dynamic lowpower and lossy network (LLNs). To perform effective routing in IoT communication, LLN Routing Protocol (RPL) is developed for the tiny nodes to establish connection by using deflaut objective functions: OF0, MRHOF, for which resources are constraints like battery power, computation capacity, memory communication link impacts on varying traffic scenarios in terms of QoS metrics like packet delivery ratio, delay, secure communication channel. At present, conventional Internet of Things (IoT) are having secure communication channels issue for transmission of data between nodes. To withstand those issues, it is necessary to balance resource constraints of nodes in the network. In this paper, we developed a security algorithm for IoT networks with RPL routing. Initially, the constructed network in corporates optimizationbased deep learning (reinforcement learning) for route establishment in IoT. Upon the establishment of the route, the ClonQlearn based security algorithm is implemented for improving security which is based onaECC scheme for encryption and decryption of data. The proposed security technique incorporates reinforcement learning-based ClonQlearnintegrated with ECC (ClonQlearn+ECC) for random key generation. The proposed ClonQlearn+ECCexhibits secure data transmission with improved network performance when compared with the earlier works in simulation. The performance of network expressed that the proposed ClonQlearn+ECC increased the PDR of approximately 8% - 10%, throughput of 7% - 13%, end-to-end delay of 5% - 10% and power consumption variation of 3% - 7%.

APE: Metrics for understanding application performance efficiency under power caps

As supercomputers continue to grow in size and power consumption, the ability to understand application run time performance and energy/power usage is of growing importance. In the future it may be necessary for systems to operate under power caps imposed by facilities due to external influences such as renewable power generation (e.g. solar) impacting energy availability at an affordable cost during certain times of day and more frequent natural disasters due to climate change causing power transmission disruptions. However, current energy consumption and power characterization metrics like energy-delay products do not express all of the characteristics of an application that are relevant to understanding the impact of power capping on performance.In this study, we (1) characterize the useful features of a metric that effectively captures time-to-solution and power performance dynamics; and (2) design and evaluate a novel set of application power efficiency (APE) metrics that accounts for time-to-completion, power utilization and power variability. Power utilization quantifies a system’s trapped capacity (unused power budget) and power variability quantifies an application’s variation of power consumption over time. We demonstrate how APE can be used to quantify application characteristics which, in turn, enables reasoning about the impacts of power capping on an application.

A New Realization of Electronically Tunable Multiple-Input Single-Voltage Output Second-Order LP/BP Filter Using VCII

In this paper, a new realization of electronically tunable voltage output second-order low-pass (LP) and band-pass (BP) filter is presented. The circuit has a multiple-input single-output structure, and LP and BP outputs are provided using the same structure. One electronically variable second-generation voltage conveyor (VCII), whose impedance at the Y port can be electronically varied using a control current (Icon), two capacitors, and one resistor are used. By changing the value of Icon, the impedance value at the Y port can be electronically varied; therefore, the value of ω0 can be tuned. This feature helps to reduce the number of passive components used. Interestingly, the LP and BP outputs are provided at the low-impedance Z port of the VCII, and there is no need for an extra voltage buffer for practical use. The circuit enjoys a simple realization consisting of only 24 MOS transistors. Simulation results using PSpice and 0.18 μm CMOS parameters are provided. The value of ω0 can be varied from 1.2 MHz to 1.7 MHz, while Icon varies from 0 to 50 µA, with a power consumption variation from 244 µW to 515 µW.

Energy consumption modelling in milling of variable curved geometry

The accurate estimation of energy consumption is beneficial to manufacturing enterprises economically as well as to overcome global energy crisis. The present work concentrates on developing an energy consumption model in milling of variable curved geometries where magnitudes and directions of workpiece curvature vary along tool contact path of a component. The current work deals with estimation and analysis of energy consumption in peripheral milling of variable curved surfaces where cutting forces differ along tool contact path in the presence of workpiece curvature. The proposed hybrid model developed in MATLAB involves process mechanics, cutting forces and energy consumption and has modules for idle, auxiliary and cutting power. The proposed model is validated by the experimental work. The model is generic and versatile in nature and is useful for milling of straight, circular and curved surfaces. In addition to it, the influence of workpiece curvature on power consumption has been investigated to realize the variation of power consumption along the tool contact path. The developed model offers a basic platform to understand and characterize the energy consumption for general peripheral milling considering workpiece geometry. The comparison of predicted and measured results indicates that the model is capable to estimate the power consumption accurately. The proposed model will be used by the practitioners to find the optimum cutting conditions to reduce power consumption during the machining of curved geometries – a pragmatic condition but not much researched condition in machining.

Realization of an Electronically Tunable Resistor-Less Floating Inductance Simulator Using VCII

In this paper, a new implementation of an electronically tunable resistor-less floating inductance simulator using a second-generation voltage conveyor (VCII) is presented. The proposed circuit is resistor-free (benefiting from the intrinsic resistors at the Y terminals of the employed VCIIs) and composed of three VCIIs and a single grounded capacitor. Using a control current (Icon), the value of impedance at the Y terminal of the VCII is varied, whereby the value of the simulated inductance is tuned. The proposed circuit is designed at a transistor level using 0.18 µm TSMC CMOS parameters and ±0.9 V supply voltage. PSpice simulations are carried out to confirm the effectiveness of the proposed circuit. For a range of Icon from 0 µA to 50 µA, the value of the simulated L can be varied from −576 µH to −324 µH and from +316 µH to +576 µH for negative and positive simulators, respectively, in the frequency range of 100 kHz–3 MHz. Favorably, the value of the series resistance remains below 76 Ω. Simulation results show an error value below 4.8% and power consumption variation is from 1.64 mW to 1.92 mW. Moreover, application of the proposed circuit as a standard band-pass RLC filter is also included.

Energy and exergy analysis of a novel solar-air composite source multi-functional heat pump

As multi-functional heat pump with higher equipment utilization rate will face more complicated operation condition, the integration with composite heat source will be good solution to improve the operational stability and output performance. In this paper, a novel solar-air composite source multi-functional heat pump (SA-CMHP) has been proposed. Different from conventional single-source heat pump, the proposed system has two evaporators operating in parallel in space heating mode. As the distribution of refrigerant at evaporation side is associated with the output performance of SA-CMHP, the space heating performance under different refrigerant distribution ratio (γ) has been studied based on energy and exergy methods. Besides, economic performance of SA-CMHP for space heating has been analyzed and compared with single-source heat pump. The results indicate that with the increase of γ, the variation of evaporation capacity, power consumption, heating capacity, COP and exergy efficiency tends to increase at first and then decrease. When solar irradiation is 200W/m2, 300W/m2 and 400W/m2, COP and exergy efficiency reach the highest value at γ of 0.6, 0.7 and 0.8. When ambient temperature is 4 °C, 7 °C and 10 °C, COP and exergy efficiency reach the peak values at γ of 0.6.

VITI: A Tiny Self-Calibrating Sensor for Power-Variation Measurement in FPGAs

On-chip sensors, built using reconfigurable logic resources in field programmable gate arrays (FPGAs), have been shown to sense variations in signalpropagation delay, supply voltage and power consumption. These sensors have been successfully used to deploy security attacks called Remote Power Analysis (RPA) Attacks on FPGAs. The sensors proposed thus far consume significant logic resources and some of them could be used to deploy power viruses. In this paper, a sensor (named VITI) occupying a far smaller footprint than existing sensors is presented. VITI is a self-calibrating on-chip sensor design, constructed using adjustable delay elements, flip-flops and LUT elements instead of combinational loops, bulky carry chains or latches. Self-calibration enables VITI the autonomous adaptation to differing situations (such as increased power consumption, temperature changes or placement of the sensor in faraway locations from the circuit under attack). The efficacy of VITI for power consumption measurement was evaluated using Remote Power Analysis (RPA) attacks and results demonstrate recovery of a full 128-bit Advanced Encryption Standard (AES) key with only 20,000 power traces. Experiments demonstrate that VITI consumes 1/4th and 1/16th of the area compared to state-of-the-art sensors such as time to digital converters and ring oscillators for similar effectiveness.

On acoustic emission analysis in circular saw cutting beech wood with respect to power consumption and surface roughness

A sound or a noise that accompanies wood machining processes is introduced by the tool rotation itself, by the friction of moving machine parts, or by wood-tool interaction. The sounds generated during machining with a circular saw could be analysed in order to monitor and possibly control the cutting process. Applying altered cutting parameters while cutting beech wood (Fagus sylvatica L.), which is the most common wood species in the Republic of Serbia, caused acoustic emissions that could be analysed throughout corresponding spectra. As shown in previous studies, altering the cutting parameters, e.g., the feed speed and tool override, resulted in variations in power consumption, surface roughness, and acoustic emission (or acoustic pressure). The aim of this paper was to provide a possible correlation between the applied cutting parameters and the acoustic emission spectra with respect to consumed power and the state of the machined surface. Along with acoustic emissions, the power consumption and surface roughness data were also acquired in order to make a possible relationship. By associating the idle circular saw acoustic spectra with background noise and comparing them with those obtained during machining, it was possible to indicate spectrum areas of particular interest for further analysis.