Identification of heat exchangers according to the criterion of energy efficiency

The article presents the results of the analysis of the characteristics of heat exchangers methods for determining their mathematical models. The necessity of the availability of the mathematical model during the synthesis of automatic control systems with desired properties. The method of identification of the thermal control object by the testing control action is proposed. Since technological control objects always be an energy of interaction the energy efficiency criterion applied for automatic formation of the control action. Also the analytical self-adjusting system with a reference model in the form of an integrating link was applied. From the analytical researches it follows that the movement of the system along the optimal trajectory occurs at a constant speed and does not depend on the properties of the control object, and the optimal control depends on the properties of the control object, time, and technological requirements. It is shown that mathematical models of heat exchangers of the first and second orders are determined quite simply. The accuracy of the mathematical model parameters is limited only by the accuracy of the experimental data. The quality of control systems with desired properties, synthesized by experimental, and accurate models are virtually indistinguishable

Universal computer vision system for monitoring the main parameters of wind turbines

The article presents universal autonomous system of computer vision to monitor the operation of wind turbines. The proposed system allows to estimate the rotational speed and the relative position deviation of the wind turbine. We present a universal method for determining the rotation of wind turbines of various shapes and structures. All obtained data are saved in the database. The presented method was tested at the Territory of Non-traditional Renewable Energy Sources of Ural Federal University Experimental wind turbines is produced by “Scientific and Production Association of automatics named after academician N.A. Semikhatov”. Results show the efficiency of the proposed system and the ability to determine main parameters such as the rotational speed, accuracy and quickness of orientation. The proposed solution is to assume that, in most cases a rotating and central parts of the wind turbine can be allocated different color. The color change of wind blade should not affect the system performance

A Model of Fuel and Energy Sector Contribution to Economic Growth

The study examined the impact of foreign direct investment (FDI) in the fuel and energy sector and related industries on economic growth in response to the debates on FDI's impact on economic growth being positive (government officials and policymakers) or negative (the World Bank, some researchers). The hypothesis that a significant relationship is present between the Russian Federation GDP and gross FDI in Fuel and Energy Sector (fuels and non-fuels fossils mining, coke and petrochemicals production, rubber and plastic production, and energy supply) is introduced and validated by using a regression model. The derived model tests changes of regression results patterns of the Russian GDP against FDI in energy-related industries in different periods 1998-2004 and 2010-2017. GDP is assessed in five different measures: current US dollars, international US dollars (purchasing power parity), growth rates of the former and the latter, and physical growth index. It was concluded that, to a greater extent, economic growth is influenced by foreign investment in energy supply and petrochemical production in the both periods. Increased investment in power generation also contributes to economic growth, while other constituents of the sector, including mining, have a statistically insignificant or even retarding effect on economic growth, thus evidencing in favor of the World Bank's criticism towards FDI. Policy implications of the findings prove the necessity to introduce structural changes intended to redirect capital flows from oil and gas to prevent from economic growth deterioration in the long-term perspective. Keywords: Economic growth; Foreign Direct Investment; Fuel and energy sector JEL Classifications: C3, O4, Q43 DOI: https://doi.org/10.32479/ijeep.784

Noise Performance of the CrIS Instrument

The Cross-track Infrared Sounder (CrIS) is a spaceborne Fourier transform spectrometer (FTS) that was launched into orbit on 28 October 2011 onboard the Suomi National Polar-orbiting Partnership satellite. CrIS is a sophisticated sounding sensor that accurately measures upwelling infrared radiance at high spectral resolution. Data obtained from this sensor are used for atmospheric profiles retrieval and assimilation by numerical weather prediction models. Optimum vertical sounding resolution is achieved with high spectral resolution and multiple spectral channels; however, this can lead to increased noise. The CrIS instrument is designed to overcome this problem. Noise Equivalent Differential Radiance (NEdN) is one of the key parameters of the Sensor Data Record product. The CrIS on-orbit NEdN surpassesmission requirements with margin and has comparable or better performance when compared to heritage hyperspectral sensors currently on orbit. This paper describes CrIS noise performance through the characterization of the sensor’s NEdN and compares it to calibration data obtained during ground test. In addition, since FTS sensors can be affected by vibration that leads to spectrally correlated noise on top of the random noise inherent to infrared detectors, this paper also characterizes the CrIS NEdN with respect to the correlated noise contribution to the total NEdN. Lastly, the noise estimated from the imaginary part of the complex FTS spectra is extremely useful to assess andmonitor in-flight FTS sensor health. Preliminary results on the imaginary spectra noise analysis are also presented

Retrieval of Physical Properties of Particulate Emission from Animal Feeding Operations Using Three-Wavelength Elastic Lidar Measurements

Agricultural operations produce a variety of particulates and gases that influence ambient air quality. Lidar (LIght Detection And Ranging) technology provides a means to derive quantitative information of particulate spatial distribution and optical/physical properties over remote distances. A three-wavelength scanning lidar system built at the Space Dynamic Laboratory (SDL) is used to extract optical parameters of particulate matter and to convert these optical properties to physical parameters of particles. This particulate emission includes background aerosols, emissions from the agricultural feeding operations, and fugitive dust from the road. Aerosol optical parameters are retrieved using the widely accepted solution proposed by Klett. The inversion algorithm takes advantage of measurements taken simultaneously at three lidar wavelengths (355, 532, and 1064 nm) and allows us to estimate the particle size distribution. A bimodal lognormal particle size distribution is assumed and mode radius, width of the distribution, and total number density are estimated, minimizing the difference between calculated and measured extinction coefficients at the three lidar wavelengths. The results of these retrievals are then compared with simultaneous point measurements at the feeding operation site, taken with standard equipment including optical particle counters, portable PM10 and PM2.5 ambient air samplers, multistage impactors, and an aerosol mass spectrometer

Lidar Based Emissions Measurement at the Whole Facility Scale: Method and Error Analysis

Particulate emissions from agricultural sources vary from dust created by operations and animal movement to the fine secondary particulates generated from ammonia and other emitted gases. The development of reliable facility emission data using point sampling methods designed to characterize regional, well-mixed aerosols are challenged by changing wind directions, disrupted flow fields caused by structures, varied surface temperatures, and the episodic nature of the sources found at these facilities. We describe a three-wavelength lidar-based method, which, when added to a standard point sampler array, provides unambiguous measurement and characterization of the particulate emissions from agricultural production operations in near real time. Point-sampled data are used to provide the aerosol characterization needed for the particle concentration and size fraction calibration, while the lidar provides 3D mapping of particulate concentrations entering, around, and leaving the facility. Differences between downwind and upwind measurements provide an integrated aerosol concentration profile, which, when multiplied by the wind speed profile, produces the facility source flux. This approach assumes only conservation of mass, eliminating reliance on boundary layer theory. We describe the method, examine measurement error, and demonstrate the approach using data collected over a range of agricultural operations, including a swine grow-finish operation, an almond harvest, and a cotton gin emission study

Integrating Lidar and Atmospheric Boundary Layer Measurements to Determine Fluxes and Dynamics of Particulate Emissions from an Agriculture Facility

Lidar technology offers the ability to quantify concentrations of small particulates in the atmosphere in certain ranges of time and space. While this is a valuable tool to visualize the behavior of plumes emitted from the surface, the actual flux of particles cannot be estimated from such data alone. To determine the mass flux of particles, the concentrations must be properly integrated with wind and turbulence properties. The goal of this study is to utilize a model that uses wind and particle density information to calculate the flux of particles from an animal facility near Ames, Iowa. The model is a simplified conservation equation for particle density in the atmosphere. This approach essentially quantifies fluxes in and out of a box centered over the facility and estimates the surface source by assuming conservation of mass. In addition, we hypothesize that distinct turbulence structures will sometimes interact with the intermittency of the surface emission from the buildings, resulting in episodic changes in emission fluxes from the site. A second objective involves documenting how intermittent the emission plumes are and how they are connected to periodic large scale turbulence events. Lidar data of particle size and density in the vicinity of the site were collected during an intensive field campaign lasting nearly 2 weeks. In addition to the lidar data, turbulence data were measured at several levels on each of three towers, located upwind, inside and downwind of the source area. The model requires measurements of the vertical profiles of both concentrations of particulates and the mean horizontal wind. The concentrations were measured using the lidar, while winds were measured using a combination of cup anemometers and sonic anemometers. This allows the emission fluxes to be calculated during 15 to 30 minute periods when winds are consistent. Flux calculations await the final calibration of the lidar returns using measured particle densities. Flux estimates will be made when distinct plumes are observed under steady-state wind conditions. Current results are presented showing evidence of episodic plumes of CO2 in response to intermittent vertical motions of turbulences

Aglite Lidar: A Portable Elastic Lidar System for Investivating Aerosol and Wind Motions at or Around Agricultural Production Facilities

The Aglite Lidar is a portable scanning lidar that can be quickly deployed at agricultural and other air quality study sites. The purpose of Aglite is to map the concentration of PM10 and PM2.5 in aerosol plumes from agricultural and other sources. Aglite uses a high-repetition rate low-pulse energy 3-wavelength YAG laser with photon-counting detection together with a steerable pointing mirror to measure aerosol concentration with high spatial and temporal resolution. Aglite has been used in field campaigns in Iowa, Utah and California. The instrument is described, and performance and lidar sensitivity data are presented. The value of the lidar in aerosol plume mapping is demonstrated, as is the ability to extract wind-speed information from the lidar dat

Production of He-4 and (4) in Pb-Pb collisions at root(NN)-N-S=2.76 TeV at the LHC

Results on the production of He-4 and (4) nuclei in Pb-Pb collisions at root(NN)-N-S = 2.76 TeV in the rapidity range vertical bar y vertical bar <1, using the ALICE detector, are presented in this paper. The rapidity densities corresponding to 0-10% central events are found to be dN/dy4(He) = (0.8 +/- 0.4 (stat) +/- 0.3 (syst)) x 10(-6) and dN/dy4 = (1.1 +/- 0.4 (stat) +/- 0.2 (syst)) x 10(-6), respectively. This is in agreement with the statistical thermal model expectation assuming the same chemical freeze-out temperature (T-chem = 156 MeV) as for light hadrons. The measured ratio of (4)/He-4 is 1.4 +/- 0.8 (stat) +/- 0.5 (syst). (C) 2018 Published by Elsevier B.V.Peer reviewe

Azimuthal anisotropy of charged jet production in root s(NN)=2.76 TeV Pb-Pb collisions

We present measurements of the azimuthal dependence of charged jet production in central and semi-central root s(NN) = 2.76 TeV Pb-Pb collisions with respect to the second harmonic event plane, quantified as nu(ch)(2) (jet). Jet finding is performed employing the anti-k(T) algorithm with a resolution parameter R = 0.2 using charged tracks from the ALICE tracking system. The contribution of the azimuthal anisotropy of the underlying event is taken into account event-by-event. The remaining (statistical) region-to-region fluctuations are removed on an ensemble basis by unfolding the jet spectra for different event plane orientations independently. Significant non-zero nu(ch)(2) (jet) is observed in semi-central collisions (30-50% centrality) for 20 <p(T)(ch) (jet) <90 GeV/c. The azimuthal dependence of the charged jet production is similar to the dependence observed for jets comprising both charged and neutral fragments, and compatible with measurements of the nu(2) of single charged particles at high p(T). Good agreement between the data and predictions from JEWEL, an event generator simulating parton shower evolution in the presence of a dense QCD medium, is found in semi-central collisions. (C) 2015 CERN for the benefit of the ALICE Collaboration. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).Peer reviewe