Power Consumption Of Equipment Research Articles

Molecular Detection of Respiratory Tract Viruses in Chickens at the Point of Need by Loop-Mediated Isothermal Amplification (LAMP)

Accurate and timely molecular diagnosis of respiratory diseases in chickens is essential for implementing effective control measures, preventing the spread of diseases within poultry flocks, minimizing economic loss, and guarding food security. Traditional molecular diagnostic methods like polymerase chain reaction (PCR) require expensive equipment and trained personnel, limiting their use to centralized labs with a significant delay between sample collection and results. Loop-mediated isothermal amplification (LAMP) of nucleic acids offers an attractive alternative for detecting respiratory viruses in broiler chickens with sensitivity comparable to that of PCR. LAMP’s main advantages over PCR are its constant incubation temperature (∼65 °C), high amplification efficiency, and contaminant tolerance, which reduce equipment complexity, cost, and power consumption and enable instrument-free tests. This review highlights effective LAMP methods and variants that have been developed for detecting respiratory viruses in chickens at the point of need.

Prediction-Based Power Consumption Monitoring of Industrial Equipment Using Interpretable Data-Driven Models

Efficient energy optimization and scheduling in industrial factories depend on accurate, reasonable, and real-time monitoring of equipment power consumption. However, the power prediction of industrial equipment requires a large number of process data, which could be inevitably contaminated by some imperfect data, due to the harsh environments. Monitoring or predicting equipment power consumption is usually not feasible using data-driven black-box models with imperfect data. This paper proposes a prediction-based approach for power consumption monitoring using an interpretable data-driven model. First, a data preprocessing method is used to remove outliers and fill in missing values. Then, a Volterra polynomial basis function (VPBF) model is built to predict equipment power consumption. This model decomposes power values into a series of basis functions consisting of input parameters. Moreover, to compensate for data dropouts during the power consumption monitoring process, a networked predictive monitoring system is also proposed. Finally, this paper presents two case studies based on actual production equipment in an industrial manufacturing factory. The results demonstrate that the proposed approach can achieve satisfactory monitoring accuracy and adaptation ability. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This paper is motivated by the problem of power consumption monitoring of industrial equipment in harsh production environments. A conventional solution is to predict the power consumption using data-driven black-box models, with limited feasibility and interpretability. This paper proposes a new power consumption monitoring approach, utilizing an interpretable data-driven model and a networked predictive method. This approach accurately reveals the transparent relationships between the output and input parameters. The power prediction result is consequently interpretable and more reasonable. Meanwhile, this approach actively compensates for data dropouts in the network, which can help operators real-time grasp the power consumption of equipment. Furthermore, this approach can be integrated into energy optimization systems as a basis of optimization and decision-making. Practical applications in an aluminum manufacturing company located in Guangdong Province demonstrate that this approach is feasible and applicable. Future research is to expand this approach further for energy optimization and scheduling.

Power-aware high-capacity elastic optical networks

The power consumption of telecommunication equipment has been identified as a relevant contributor to global energy consumption. In fact, new-generation optical transponders employ power-intensive electronic application-specific integrated circuits (ASICs) for digital signal processing (DSP). DSP design has traditionally prioritized meeting transmission requirements over power consumption optimization. In general, the evolutions of transmission techniques and network design have always been mainly driven by traffic increase; in this context, in order to operate network resources more efficiently, margin reduction has been investigated in the past few years. Indeed, traditionally, high physical layer margins are used to ensure reliability over an extended period, resulting in overprovisioning the optical connections for both physical layer conditions and capacity. On the other hand, super-channels have emerged as a suitable solution for accommodating the continuous traffic growth. However, power consumption has not been deeply considered in the optimization of super-channel transmission. This paper first investigates the power efficiency of super-channels operated with designed and reduced margins. Low-margin operation is enabled by adapting sub-carrier spacing and filter bandwidth. Power-aware super-channel optimization is then experimentally demonstrated leveraging a 600 Gbit/s transponder in the SDN-controlled elastic optical network (EON). The results have identified a trade-off between power consumption and spectrum efficiency. Furthermore, the ongoing bandwidth demand has motivated the investigation of multi-band (MB) transmission for scaling the capacity of the existing infrastructures. However, novel networking devices (e.g., optical amplifiers operating beyond the C- and L-bands) will affect the overall power consumption. In this context, experimental power analysis of a thulium doped fiber amplifier (TDFA) is performed based on the traffic load and corresponding configuration. The results show that TDFA power consumption varies with configuration and increases with output power.

ANALISIS SISTEM KELISTRIKAN PADA LABORATORIUM CENTRAL SERVICE KUALA NAMU

Kuala Namu Central Service Laboratory is a laboratory that provides service-based services for electrical and electronic equipment specifically at kuala namu airport equipment. This laboratory uses a lot of laboratory equipment that uses electrical energy. The purpose of this study is to analyse the electrical system on electrical power consumption in the Kuala Namu Central Service Laboratory as well as conduct an analysis between the electrical system of the Kuala Namu Central Service Laboratory with the General Requirements for Electrical Installation and SPLN. Based on the calculation results in the discussion results obtained total power consumption of equipment around 86,637.30 W, from the measurement of operating power of 82,606.66 W. While according to the simulation results using DIg SILENT Power Factory 15.1 .7, the power is 82,604.95 W. The percentage of transformer loading is obtained at 44.08%, this already includes loading according to SPLN standards, while the percentage of generator loading is 89.496% which is declared overloaded. In the simulation results the transformer is 44.08% and the generator is 89.5%. The type of conductor and safety installed as well as the grounding resistance in the building has met the PUIL (General Requirements for Electrical Installation) standard. The grounding resistance of the CPS laboratory building is 2.6 Ω (5 Ω).

CO[formula omitted] dissociation using a lab-scale microwave plasma torch: An experimental study in view of industrial application

Under laboratory conditions, microwave plasma torches are known to be an energetically very efficient CO2 conversion technology, for pressures ranging from 100mbar up to atmospheric pressure. However, issues relevant for industrial application such as the total energy efficiency, including the power consumption of peripheral equipment, the performance for impure CO2 streams (such as directly from carbon capture facilities) and the stability at long-term operation are usually not addressed. To fill that gap, a lab-scale plasma torch and the corresponding vacuum pump are connected to an energy meter system. Measured wall-plug energy efficiencies yielded values up to 17.9%, corresponding to an electrical power consumption of 19.6kWh per produced Nm3 of carbon monoxide. Experiments with controlled amounts of impurities (Ar, N2, O2, real air and synthetic air) in the feed gas stream are performed. It is shown that small amounts of nitrogen can even increase energy efficiency whereas humidity in the CO2 stream might have an extremely detrimental effect on CO2 decomposition. Finally, a durability test over 29h was performed, demonstrating that microwave plasma torch operation is very reproducible and stable in all figures of merit with short ramp-up times, making it a promising technology for intermittent operation on industrial scale.

Study on the Change of Power Consumption Structure in Xumai Township, Nimu County, Lhasa, Xizang

The research on the evolution of rural power consumption structure in Xizang reflects the information on rural power development in Xizang, and the information on rural power development shows the people's living standards and demand trends. In order to understand the depth of changes in the power consumption structure of farmers and herdsmen households, the project team conducted a field survey of the changes in power supply sources, power consumption structure, power consumption equipment, and operation and management status of Sumai Township, a typical village in Nimu County, Lhasa City, Xizang over the years, and explored the history and trend of power development in remote villages in Xizang. Field research has found that before 2014, the township mainly relied on small-scale independent solar photovoltaic power supply, which was almost used for lighting; Since the implementation of the State Grid in 2014, electricity consumption has shifted from low voltage to wide voltage. In the past three years, the annual electricity consumption growth rate in Xumai Township has exceeded 6%, and the power supply stability has reached 90%. At the same time, the township utilizes solar photovoltaic street lights. The electrical appliances used have developed from a single lamp to power appliances such as household appliances, agricultural electric vehicles, tsamba machines and oil presses. The distribution line of the township is gradually being replaced with medium and low voltage, and is equipped with a 35kV Xumai substation. The 10kV medium and low voltage distribution network project of the rural power grid is gradually being put into operation and put into practice. However, research has found that villagers hope to use more clean energy such as solar energy for power supply and heating, in order to reduce the cost of electricity and gas bills.

Type series of resonant vibration equipment for concrete mixtures compaction and its main parameters calculation method

Introduction. Increasing the energy efficiency of vibration technology poses a number of challenges for its developers. A promising direction for reducing energy costs for driving vibration machines is the use of the resonance phenomenon. Due to the dynamic properties of the oscillatory system, it is possible to significantly reduce the power consumption of resonant vibration equipment, and in some cases, improve the quality of the products. The purpose of this article is to develop a standard range of resonant vibration equipment for compacting concrete mixtures and a methodology for calculating its main parameters.The object of research is the oscillatory system of a vibrating machine, consisting of two masses connected by the elastic and dissipative elements. In addition, the first mass is connected to a fixed base through elastic and dissipative elements.Materials and methods. The basic principles of theoretical mechanics, mathematical modelling and statistical processing of results were used in the research.Results. According to the research results, it was established that with an increase in the mass ratio of the oscillatory system, the dynamic coefficient decreases, and the width of the resonant zone increases. The regression equations are given. It has been established that with increasing rigidity of the working body, the dynamic coefficient decreases, and the horizontal section on the frequency response, the width of which does not change significantly, shifts to the region of higher frequencies. With an increase in the damping coefficient, the dynamic coefficient decreases, and the width of the resonant zone and the frequency range practically do not change. A wide range of nomenclature and masses of precast reinforced concrete justifies the development of a standard-size range of resonant vibration equipment. A standard range of light (up to 2 tons), medium (2-6 tons) and heavy (6-10 tons) types has been developed. Based on the analysis and generalization of research results, a method for calculating resonant vibration equipment for compacting concrete mixtures has been developed, which makes possible to increase its energy efficiency.

Evaluation of critical factors for the successful implementation of the Internet of Things based on PFN-Best Worst Method

Internet of Things (IoT) technology now has a new purpose and relevance as a result of the digitalization wave. In this setting, businesses start to plan how they will use IoT technology. But some critical factors can prevent the successful deployment of IoT, and businesses must get beyond these critical factors if they want to do so. The literature review, system literature review, and Delphi technique are used to identify 15 critical factors. These critical factors are then divided into four categories: organization, technology, process, and environment. The PFN-weighted power harmonic operator is proposed with the aim of more effectively obtaining assessment data from experts and lessening the inaccuracy of outcomes caused by information loss. The best and worst method (BWM) is used to determine the ideal weight of critical factors. Results indicate that the primary critical factors to the effective adoption of the Internet of Things are talent, resource limitations, integration complexity, technical operations, equipment power consumption, technical dependability, and data governance. This research will benefit corporate managers in recognizing the significance of the effective deployment of the Internet of Things, identifying major critical factors to this achievement, and making decisions to remove these factors. Thus, an organization may support the effective adoption of the animal Internet of Things.

Research on the Interface of Sustainable Plant Factory Based on Digital Twin

A digital twin (DT) system is a virtual system that can provide a comprehensive description of a real physical system. The DT system continuously receives data from physical sensors and user input information and provides information feedback to the physical system. It is an emerging technology that utilizes an advanced Internet of Things (IoT) to connect different objects, which is in high demand in various industries and its research literature is growing exponentially. Traditional physical systems provide data support for the monitoring of physical objects such as buildings through digital modeling techniques, data acquisition tools, human computer interfaces, and building information models (BIM). However, DT can offer much more than data presentation. DT uses the received data to perform operations such as analysis, prediction, and simulation, and finally transmits the analysis results to the physical system as feedback. Compared with other physical systems, DT has the characteristics of bidirectional data exchange and real-time autonomous management. The plant factory control system based on digital twin technology continuously measures the power consumption of electrical equipment through the sensors of the physical system and makes the corresponding virtual color-coded gradient map based on the obtained data. The darker the virtual device is, the more power it currently requires, and just based on the shade of color gives the user a very intuitive idea of the current power usage of the electronic device. There has been extensive research on digital twin technology, but there are few studies on implementing plant factories based on digital twin technology. This paper proposes the idea of combining digital twin technology with plant factories to provide research directions for future smart agriculture. It proves that smart agricultural production with sustainability can also benefit from this idea.

Feasibility study of using cogeneration plants at Kuzbass coal mines

The paper considers the problem of reducing greenhouse gas emissions in the process of coal mining during the coal mine methane utilization in power supply systems. An algorithm to form recommendations for the implementation of CMM generation is presented. A simulation model for one of the Kuzbass coal mines was developed in the PowerFactory software application. The simulation model considers the uneven nature of the power consumption of mining equipment. As a result of modeling, daily power consumption profiles and voltage levels in the coal mine power supply system were determined before and after the implementation of the proposed measures. Based on the results, the technical and economic effects was estimated, which consisted in reducing the direct and indirect carbon footprint, electricity and capacity fees. It has been established that the cost of carbon dioxide emission quotas significantly affects the investment attractiveness of cogeneration projects. Based on the results, recommendations are given to stimulate the development of small generation in coal mines.

Real-Time Fault Identification System for a Retrofitted Ultra-Precision CNC Machine from Equipment's Power Consumption Data: A Case Study of an Implementation

Real-Time Fault Identification System for a Retrofitted Ultra-Precision CNC Machine from Equipment's Power Consumption Data: A Case Study of an Implementation

Spatiochromatic and temporal natural image statistics modelling: Applications from display analysis to neural networks

Natural image statistics are well known to have a spatial frequency power spectra that has a 1/f^a behavior, with a typically stated as between 2 and 4. This indicates an invariance to scale. Further work has theorized how the visual system is tuned for such statistics in visual cortex (V1) [1]. Color image statistics also show an invariance to scale [2]. The luminance histogram is typically understood to be log normal with respect to luminance, although for HDR images, a subcomponent with skew toward much higher luminances is observed. Color statistics were initially described at the simplest level via the gray world hypothesis [3], but more details are now available, even at the hyperspectral [4]. The a power function for HDR was found to increase from the lower values of 2 to more typical values of 4 and 5 [5]. For temporal statistics, the data tends to be measured primarily for media, with a 1/f^a for scene cut statistics [6], and temporal frequency and temporal frequency for media with a focus on the motion statistics via optical flow [7]. Statistics for purely natural as well as human made environments (e.g., buildings and the resulting perspective geometry) have been studied, each having different orientation statistics [8]. The use of image statistics for standardized assessment of television power consumption was used to replace test targets, which were often detected and used to lower TV power consumption in well known cheating schemes. To prevent this, a short test video that had luminance statistics matching 48 hours of broadcast content was generated and used for TV power testing [9]. The highly adaptative nature of current TVs (power limiting, dual modulation, dynamic response) has motivated researchers to incorporate complex noise fields following natural image statistics into measurement targets [10,11]. One particular natural image statistic-based still image test target (dead leaves) is widely used in camera optics and sensor development. Algorithm development and testing for image and video processing has almost always been ad hoc, with a mixture of geometric test targets and hand selected test images, sometimes aiming to be corner cases, sometimes not. More recently, large data sets of images have been used to train various neural network models for tasks such as super resolution, bit rate compression, and dynamic range mapping. However, images are not ergodic, and possibly not even wide-sense stationary. We propose the use of imagery based on noise following the natural image statistics for spatio-chromatic (and temporal) to compactly probe the wide variety of image possibilities for algorithmic development, in addition to the existing uses for image capture and display analysis. While we don&#x2019;t suggest replacing actual practical imagery, we believe such noise fields can augment image algorithm analysis. To address the problem of non-ergodicity, we allow the basic power term a in the natural image statistic model to vary over a large range in a video, such that it includes the extremes of white noise and low frequency gradients. We use color image statistic models that include decorrelated colors to generate the RGB video. We will present results for traditional adaptive data compression (with chromatic subsampling), as well as a more contemporary neural network approach (Neural Fields [12]) as applied to upscaling and denoising. We analyze the results both visually and through several recent color image quality models. Field DJ. Relations between the statistics of natural images and the response properties of cortical cells. J. Opt. Soc. Am. A, 1987; 4:2379-2394 C. Parraga, T. Troscianko, and D.J. Tolhurst (2002) spatiochromatic properties of natural images and human vision. Current Biology V 12 R. M. Evans, Method for correcting photographic color prints, US Patent 2,571,697 (1951) A. Chakrabarti and T. Zickler (2011) Statistics of real-world hyperspectral images CVPR R. Dror, A. Willsky, and E. Adelson (2004) statistical characterization of real-world illumination. JOV V4 J. Cutting (2019) Sequences in popular cinema generate inconsistent event segmentation. Attn. Percept. And Psycho. V 81. D. Lee, H. Ko, J. Kim, and A. Bovik (2021) On the space-time statistics of motion pictures. JOSA A V 38 #7 A. Torralba and A. Oliva (2003) Statistics of natural image categories, Network: Computational Neural Systems 14 391-412 International Electrotechnical Commission, IEC 62087:2008(E), &#x201C;Methods of measurement for the power consumption of audio, video, and related Equipment. Kunkel T, Daly S. 57-1: Spatiotemporal Noise Targets Inspired by Natural Imagery Statistics. SID Symposium Digest of Technical Papers, 2020, 51:842-845. Kunkel, T, Friedrich, F. Utilizing advanced spatio-temporal backgrounds with dynamic test signals for high dynamic range display metrology. J Soc Inf Display. 2022; 30( 5): 423&#x2013; 432. https://doi.org/10.1002/jsid.1125 Yiheng Xie1, Towaki Takikawa, Shunsuke Saito, Or Litany, Shiqin Yan, Numair Khan, Federico Tombari, James Tompkin, Vincent Sitzmann, Srinath Sridhar1, "Neural Fields in Visual Computing and Beyond", Eurographics / CGF State-of-the-Art Report, 2022.

Investigation of the effect of algorithms of positioning robots on their power and energy consumption

The paper is devoted to the study of motion algorithms that determine the power and energy consumption of process equipment and positioning robots, which are important factors affecting the environment and environmental safety of the technosphere. Based on the study of mathematical models of the degrees of mobility of the gantry robot drives, it is found that under the traditional laws of motion, a fairly significant peak in power consumption occurs at the end of acceleration. The paper shows that by separating in time the moments of the end of acceleration of different drives, it is possible to significantly reduce the maximum power of the robot. A comprehensive approach to the choice of an algorithm and laws of motion that provide an acceptable combination of energy consumption and maximum power consumption has been developed. The authors have shown that there are such laws of motion that ensure the constancy of power for the duration of the acceleration stage and its minimization. The relationship between the minimum instantaneous power and power consumption for such robots has been established. The results obtained can be used to optimize the operation algorithms of both of existing and newly +-robots.

An external-compression air separation unit with energy storage and its thermodynamic and economic analysis

Long-term supply demand balance in a power grid may be maintained by electric energy storage. Liquid air energy storage (LAES) can effectively store off-peak electric energy, and it is extremely helpful for electric decarburisation; however, it also has problems of high cost, long investment payback period and low efficiency because of its very low liquefaction temperature. Air liquefaction is the basic process of air separation, and the total electricity consumption of air separation units in China accounts for about 5.24 % of its national electricity consumption. Moreover, there remains a surplus of production capacity in air separation. This paper proposes an external-compression air separation process, with liquid air energy storage function. It can effectively reduce the power consumption cost of air separation unit while realizing peak load shifting. The system consists of three subsystems, namely, air separation; air liquefaction and storage; and power generation and air recovery. Research on equipment power consumption, economic benefits, and power grid peak shaving effect, indicates that the round-trip efficiency is 54.52 %, the electricity cost saving rate is 5.13 % based on Shanghai's peak-valley industrial electricity price, and the minimum dynamic payback period is 5.5 years. The large-scale application of this process can reduce the average peak-to-valley difference rate in China by 4.95 %. The transfer of peak regulating load to the base load of the power grid can save 5.2 × 106 toe, which will result in a 2.1 × 107 ton reduction in carbon dioxide emissions annually.

Optimization of the Operation of Groundwater Intakes Using Two-Column Wells

The average number of wells at a typical water intake is 30–40; while the power of the submersible pump is usually 32–40 kW; which means that only at one well water intake the power consumption of electric pumping equipment during the hours of greatest water consumption can reach 900–1600 kW. In the structure of operating costs of well water intakes; the share of electricity costs reaches 85 %. Taking into account the requirements for reducing costs and water tariffs of housing and communal services enterprises as well as of water utilities; energy saving is an urgent task. The article considers the optimization of the operation of groundwater intakes with uneven water supply due to the use of two-column water intake wells instead of typical single-column ones. It is shown that the use of powerful pumps in single-column wells of such water intakes causes a sharp decrease in the dynamic water level in the borehole. On the one hand; this provokes the formation of colmating deposits in the filters due to their aeration; reduces the specific flow rate of the well and shortens the intervals between regenerations. On the other hand; this increases the geometric pressure of submersible pumps and energy consumption for lifting water. The theoretical foundations of determining the supply of pumps installed in single- and two-column water intake wells supplying water to the pressure filter of the water treatment plant are considered. An example of a comparative analysis of the operation of one working well with one powerful pump as part of a water intake of two single-column wells (working and reserve) to cover the entire water supply schedule and two two-column working wells containing one less powerful pump in each column is given. The energy efficiency of these pumping systems is investigated. As a result of calculations; it was found that when combining the operation of pumps of two-column wells during periods of peak; main and partial loads; the annual energy savings will amount to 33 %.

Visualizing electrical energy consumption with virtual augmented technology and the internet of things

Power consumption was considered one of the major expenses in households and small offices in the COVID pandemic situation. The proposed method employs virtual augmented technology and the Internet of Things (IoT) to provide a visual solution for monitoring the power consumption of electrical equipment. The IoT sensors are linked via mobile phones or portable communication devices. For the proposed work, the energy sensor devices are installed on the 4 single-phase electrical devices in the office room equipment. That equipment’s electrical consumption was saved, processed through the ESP8266 board, and then transmitted through WiFi to collect data on the cloud server. The saved electrical energy data in the dashboard can be displayed as a visual comparison with AR technology by using the mobile phone camera to scan the marker of each electrical device. The experimental results show that the value of electrical energy is accurate, and the data values can be used to manage the power consumption of electrical equipment.

PECULIARITIES OF DETERMINATION OF RECONSTRUCTION POTENTIAL OF ENERGY SOURCE IN THE CONDITIONS OF AVIATION ENTERPRISES

In the context of the world economy, air transport today, among other characteristics, is characterized by high technological complexity of vehicles, increasing the safety of air transport, strengthening measures to protect aviation from acts of unlawful interference and development of modern multimodal transport technologies and infrastructure for various modes of transport. Due to the global trend, unmanned aerial vehicles have become widespread in various areas and sectors of the world economy. Meanwhile, the issue of energy security as a component of aviation security at airfields and specialized enterprises in their operation, storage and maintenance remains unresolved. The problem of this work is the synthesis of the method of determining the potential of dispersed energy sources in aviation enterprises. Combining the parallel operation of dispersed generation and network will give a synergistic effect - the emergence of new properties that were not in the components, which is manifested, in particular, in increasing factors influencing energy performance, irregularity of the total load schedule of integrated systems, reducing its unevenness in daily, weekly and seasonal sections, reducing the dependence of the frequency of electric current on power balance fluctuations. In previous studies, the authors justify the positive effect of the introduction of sources of dispersed generation in industrial enterprises, namely modularity, reliability, local governance, reducing the negative impact on the environment and short start-up period. Given the complexity of the technological process and the specifics of the operation of electrical equipment of aviation enterprises, an urgent scientific and practical task is to develop a method for determining the potential of dispersed energy sources in these enterprises. To determine the potential of sources of dispersed generation in aviation enterprises, it is necessary to have as complete and clear data on electricity supply and power consumption of electrical equipment of these enterprises during the day, as well as data on electricity consumption in the power grid, operation and load consumption. At aviation enterprises, the introduction of dispersed generation based on renewable energy sources into the general structure of power supply systems is relevant and possible. The proposed method of determining the potential of dispersed energy sources in the conditions of aviation enterprises will allow to effectively implement dispersed generation in the power supply structure of aviation enterprises.

A measurement-based power consumption model of a server by considering inlet air temperature

The server power is critical not only for IT equipment power consumption, but also for non-IT power consumption in order to provide a suitable environment for IT equipment. The server power model is essential for thermal environment and energy efficiency. Due to the complication of the effects on power consumption of servers and few power models considering the inlet air temperature, this study firstly built an experimental setup to effectively facilitate the factor analysis. It then evaluated the effects of inlet air temperature and CPU utilization on server power consumption. During the experiment, the inlet air temperature was adjusted between 20 °C and 35 °C in 5 °C increments. Simultaneously, the SPECpower_ssj2008 was used to change the workload operations per second from 100% to idle, with a 10% interval. These measurements were also used in the server's various CPU power managements. When the inlet air temperature increases from 20 °C to 35 °C, the highest power increase was 17.60 W for Performance operating mode. Furthermore, in the DAPC and OS operating modes, the server power consumption has a piecewise linear relationship with its CPU temperature, and the function fits well when the CPU temperature is lower than 80 °C. For Performance and Workstation operating modes, the server power consumption is proportional to the temperature difference. The measurement-based correlation method employed by this paper can be used to investigate the power consumption model of other type or configured servers. If so, the adaptability of the model can be improved.

Integrated assessment of mine water pollution influence on water removal efficiency in Udachny Mine

Efficiency of water removal in underground mineral mining is mainly connected with operating cost&nbsp;of electrically driven pumps of water-drainage installations. In this regard, the comprehensive study&nbsp;of a water removal system structure shows that, alongside with electrically driven pumps, watercatchment roadways, pipeline system and mine water reinjection system (if any), it is expedient to add the water drainage system with load&ndash;haul&ndash;dumpers and hoists for haulage and lifting of thickened silt-and-slime slurry to ground surface. In this case, reduction in concentration of solid particles in mine water and effective dewatering of silt-and-slime slurry may result in higher technical and economic effect in terms of mineral mining cost than is anticipated. This article presents the studies in the field of integrated assessment of impact exerted by solid particles in mine water on water removal performance in Udachny Mine. The efficiency criteria are proposed for the system of water removal from the underground kimberlite mine. It is found that the cost of kimberlite ore mining in Udachny mine is mostly affected by mine water contamination in terms of expenses connected with power consumption and repair of pumping equipment of the main water-drainage installation, as well as due to a profit gap in kimberlite production. The developed mathematical model allows assessment of influence exerted by solid phase in mine water on the efficiency of water removal from Udachny Mine.

English

Guaranteeing security without compromising the exhibition and adaptability of a gadget is basically an exceptionally difficult endeavor for Researchers and Practitioners Approximate circuits (AxCs) tradeoff computational exactness against upgrades in equipment place, put off, or power consumption.